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Date of publication xxxx 00, 0000, date of current version xxxx 00, 0000.
Digital Object Identifier 10.1109/ACCESS. 2017.Doi Number
A Review of BLDC Motor: State of Art,
Advanced Control Techniques, and
Applications
DEEPAK MOHANRAJ1, RANJEEV ARULDAVID1, RAJESH VERMA2, K. SATHYASEKAR3,
ABDULWASA BAKR BARNAWI2, BHARATIRAJA CHOKKALINGAM1, (Senior Member,
IEEE), LUCIAN MIHET-POPA4, (Senior Member, IEEE)
1Department of Electrical and Electronics Engineering, SRM Institute of Science and Technology, Chennai, 603203, India.
2 Department of Electrical Engineering at the King Khalid University, Abha, KSA.
3Department of Electronics and Communication Engineering, Prathyusha Engineering College, Chennai, 602025 India.
4Faculty of Engineering, Østfold University College, 1757 Halden, Norway.
Corresponding authors: Bharatiraja Chokkalingam (e-mail: bharatiraja@gmail.com), Lucian Mihet-Popa (e-mail: lucian.mihet@hiof.no)
This work was supported in part by the Government of India, DST SERB Core Research Grant, File no.: CRG/2019/005483
ABSTRACT Brushless direct current (BLDC) motors are mostly preferred for dynamic applications such
as automotive industries, pumping industries, and rolling industries. It is predicted that by 2030, BLDC
motors will become mainstream of power transmission in industries replacing traditional induction motors.
Though the BLDC motors are gaining interest in industrial and commercial applications, the future of
BLDC motors faces indispensable concerns and open research challenges. Considering the case of
reliability and durability, the BLDC motor fails to yield improved fault tolerance capability, reduced
electromagnetic interference, reduced acoustic noise, reduced flux ripple, and reduced torque ripple. To
address these issues, closed-loop vector control is a promising methodology for BLDC motors. In the
literature survey of the past five years, limited surveys were conducted on BLDC motor controllers and
designing. Moreover, vital problems such as comparison between existing vector control schemes, fault
tolerance control improvement, reduction in electromagnetic interference in BLDC motor controller, and
other issues are not addressed. This encourages the author in conducting this survey of addressing the
critical challenges of BLDC motors. Furthermore, comprehensive study on various advanced controls of
BLDC motors such as fault tolerance control, Electromagnetic interference reduction, field orientation
control (FOC), direct torque control (DTC), current shaping, input voltage control, intelligent control,
drive-inverter topology, and its principle of operation in reducing torque ripples are discussed in detail. This
paper also discusses BLDC motor history, types of BLDC motor, BLDC motor structure, Mathematical
modeling of BLDC and BLDC motor standards for various applications.
INDEX TERMS BLDC motor, torque ripple, current shaping techniques, controlling input voltage, direct
torque control, drive-inverter topology, field orientation control, motor design, fault tolerance control and
electromagnetic interference reduction.
ABBREVIATION
ANN Artificial Neural Network IEC International Electrotechnical Commission
ASD Adjustable Speed Drives LISN Line Impedance Stabilization Network
BEMF Back Electro-Motive Force NVH Noise, Vibration, and Harshness
BLDC Brushless DC Motor NdFeB Neodymium Iron Boron
DTC Direct Torque Control PID Proportional Integral Derivative
EMF Electro Magnetic Field PWM Pulse Width Modulation
EMI Electromagnetic Interference SVPWM Space Vector PWM
EVs Electric Vehicles VSI Voltage Source Inverter
FEA Finite Element Analysis UAV Unmanned Aerial Vehicle
FOC Field Oriented Control ZCP Zero Crossing Point
FTC Fault-Tolerant Control
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VOLUME XX, 2017 37
I. INTRODUCTION
A. Background
Before 50 years, T. G Wilson and P.H. Trickey conducted
several experiments to run Direct Current (DC) motors with
solid-state commutation which paved the ideology of
developing BLDC motor [1] which is based on Lorentz‘s
force law. In recent decades, BLDC motors have been an
area of intensive research to facilitate the penetration of
electric vehicles in the automotive industry. Owing to
maneuverability, compact design and lightweight BLDC
motors are found to be used in several industries such as
automotive industries, pumping industries, and rolling
industries [2]. Since there will be an increase in demand for
electric vehicles in the upcoming 10 years, BLDC motors
are expected to play a vital role. The BLDC motors global
market is expected to reach a size of 15.2 billion USD by
2025, from an estimated 9.6 billion USD by 2020 as
illustrated in Fig.1. The enormous growth of this machine
has lured several applications [3]. Depending on the
purpose of applications such as static or dynamic, BLDC
motors provide a good response. They need to be designed
appropriately to have good magnetic linkage to be used for
various applications such as lifting, cutting, and bracing [4].
Compared to the other motors, BLDC motors are expected
to have higher efficiency, higher torque to weight ratio, and
lower operating noise [5]. These machines have stationary
flux in between the rotor and stator which primes the motor
to run with a unity power factor. BLDC motors are driven
using electronically commutated motor drives. Each phase
of the motor is driven via a closed-loop controller. The
main usage of a closed-loop controller is to provide a
current pulse to the motor windings to have control over the
speed and torque as both are complementary phenomena in
a motor [6]. BLDC motor is driven with high accuracy that
it produces high wear and tear in load conditions.
Few circuits use Hall Effect sensors to directly measure
the rotor's position, whereas few others measure the back
electromotive force within the non-driven coils to gather
the position of the rotor, which are known as sensorless
controls. A general hall sensor fixed BLDC motor contains
three dual-directional outputs which are controlled by a
circuit based on digital logic [7].
Billion dollars
2000 2005 2010 2020 2025
25
20
15
10
5
0
BLDC Motor Market analysis
Years
Figure 1. BLDC motor market analysis by market reports
Other sensor-less controllers are made for measuring the
winding current flow caused by the direction of the magnets
to get the position of the rotor and estimating parameters
such as back electromotive force (EMF) and flux [8]. Even
though indirect control (sensor-less) provides less response
compared to direct (with sensor) control and the structural
complexity increases, indirect controls are preferred in
many high-power automotive applications such as electric
trains, airplanes, etc., Sensor-less control is achieved in
three principles namely (i) EMF method with zero-crossing,
(ii) observer-based EMF method, and (iii) magnetic
anisotropy method [14]. Mostly EMF method with the zero-
crossing principle is preferred [9]. While the other two
principles are tedious to control and are not preferred for
low-speed operations.
For an efficient control, the speed of the motor and the
commutation logics are being controlled in the drive-by
collecting the inputs from both the drive and the motors
such as the position of the rotor or rotor angle, stator
currents, hysteresis band current, etc., Proper control of
switching of various switches in motor drives confirms the
correct rotation of the motor [10]. Even though there are
various methods for controlling the harmonic content in the
supply in drives, we prefer it to control through the Pulse
Width Modulation (PWM) technique [11]. Among the
PWM techniques, specifically, everyone prefers to use
space vector PWM (SVPWM) control. Current control
strategies with PWM and hysteresis controllers play a vital
role in improving the performance of the motor drives.
Current control strategies with unipolar PWM can be
classified as follows: (i) H-PWM-L-ON, (ii) H-ON-L-
PWM, ON-PWM, (iii) PWM-ON, (iv) PWM-ON-PWM,
(v) H-PWM-L-PWM modes [16].
B. Literature survey and background
Even though BLDC motors are found to have high
efficiency, the durability of the machine is less compared to
induction motors [12]. To improve the durability of BLDC
motors, the main challenges such as fault tolerance,
Electromagnetic interference, acoustic noise, torque ripple,
and flux ripple should be controlled. Thus, the controlling
techniques are discussed in this paper.
Since BLDC motors are used in dynamic applications,
Reliability control techniques of motor drives are
indispensable. Reliability control techniques such as fault-
tolerant control (FTC), electromagnetic interference control
(EMI), and acoustic noise control improve the feasibility of
the motor drive systems in dynamic applications. The
generation of EMI and acoustic noises lead to motor
failures. Hence, it‘s essential to control the faults in prior.
The various control used to mitigate EMI and acoustic
noise generation are discussed. If EMI and acoustic noise
lead to the development of fault. The fault-tolerant
approach used to work as a backup to continue the
operation. The main use of such a technique is to maintain
continuity in operations.
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VOLUME XX, 2017 37
TABLE I Comprehensive and concise literature survey
Topology
Adopted techniques
Motor type
Applications
Reliability
Torque ripple
mitigation
Ref
Fault-tolerant control
(FTC)
Survey fault tolerance is
improved by detecting the
fault tolerance by discrete
Fourier transform.
10 poles
3 phase BLDC
Industrial
and
commercial
applications.
--
[15]
Electromagnetic
interference (EMI)
A LISN network is used in
such a way that it reduces
load parasitic elements.
4 poles
3 phase BLDC
commercial
applications.
--
[16]
Torque ripple reduction
using scalar control
Torque ripples are reduced
by synthesizing the current
wave of power supply.
4 poles
3 phase BLDC
Industry
applications.
--
[17]
Torque ripple reduction
using vector control
Torque ripples are reduced
by using MPC Scheme.
8 poles
3 phase BLDC
Industry
applications.
--
[18]
Torque ripple reduction
using design topology
Torque ripples are reduced
by optimizing the stator and
rotor structure.
4 poles
3 phase BLDC
Industry
applications.
[19]
In [13] fast fault diagnosis is performed with help of a rapid
counter. Whenever the threshold value increases, the fault
is detected. The technique is not reliable for high
acceleration applications. In [14] EMI of the machine is
reduced by analyzing the dc bus voltage at the frequency
domain. On analysis, it found that motor structure can
improve or decrease the EMI generated. Table. I represent
the comprehensive and concise literature survey done in
this paper.
Torque ripples in motors are also mitigated properly by
designing the structural symmetry and aligning stator poles
in an optimized manner. This results in the reduction of the
cogging torque which is one of the main reasons for ripple
generation which affects high acoustic noise and EMI
interference in the machine itself [20]. The main reason
behind the cogging torque generation is the communication
between the permanent magnet and stator silicon core [21-
22]. Moreover, concerning the design aspects, the cogging
torque ripples are reduced by modifying the magnetic
circuit of the machines using various methods such as
feedback linearization algorithms, using T-shaped
bifurcations teeth in stator slots, closing the slots using a
sliding separator, using notches in the rotor of low power
motors, concentrating coil winding in the same phase
group, reducing claw pole size, magnet step skewing
method and U-shaped magnetic poles. These ideologies
were performed conventionally to control the torque ripple
of the BLDC motor through designing [23-24]. Every
ideology discussed has its disadvantages such as (i) Using
modified magnetic circuit reduces torque ripple but results
in the increase of additional harmonics, (ii) using T shaped
bifurcation teeth in stator slot reduces the mechanical
strength of BLDC machines, (iii) introducing notches in the
rotor is too difficult, (iv) sliding separators can‘t be used in
low power machines, (v) concentrating coil winding of the
same phase is too difficult, (vi) using magnetic step
skewing methodology increases structural complexity of
the BLDC machine [25].
Furthermore, vector control techniques such as field
orientation control (FOC), direct torque control (DTC), and
Model predictive control (MPC) schemes functioned drives
are preferred a lot to obtain less torque ripple and good
dynamic response over various vigorous conditions. FOC
functioned drives were found in the year 1972 and DTC
functioned drives were found in the year 1986. During the
invention of these techniques, the development of
embedded controllers was less [26]. However, the
improvement in the development of the embedded
controller resulted in the improvement of the steady-state
and dynamic response characteristics of the motor
controller. The development of various novel computational
techniques such as finite control set MPC, intelligent
control algorithm, particle swarm optimization, extended
Kalman filter algorithm and fuzzy logic estimation
functioned drives to improve dynamic response [27].
Therefore, this review article undertakes a comprehensive
study on the current research on brushless direct current
motor and summarizes the up-to-date technological
advancement in BLDC motor drive controls. Furthermore,
in this paper the mathematical modeling of motor and
motor drives. Reliability control techniques such as EMI
filter using LISN techniques, fault-tolerant control using
cost observer techniques, and acoustic noise control using
FPGA controller are discussed in this paper. The various
ideology of FTC is compared. EMI control techniques are
compared with suppression levels.
The significant contribution in this paper is as follows:
A brief history of BLDC motor and their categories are
discussed in detail with diagrams.
A comprehensive review of advanced control
techniques such as FTC, EMI control, acoustic noise
control, and torque ripple mitigation are discussed.
The fundamental theory behind BLDC motor designing
and its types are illustrated with real-time cases.
The simulation and designing of advanced motor
controls are discussed in detail.
The open challenges and future research opportunities
are discussed.
Fig.2. represents the flow and survey organization of the
presented paper. In the next section, the various types of
BLDC motors and state of art are discussed.
.
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VOLUME XX, 2017 37
Survey Organization
Chapt er I: Introduction
Chapter II: Types of BLDC motor
1. Inner surface rotor
2. Outer surface rotor
3. Different rotor structure
4. Art of BLDC Motor
Chapter III: Standards and applications
A. Standards
B. BLDC Hub motor
C. Water Pumping
D. Drone
E. Industry
F. House applications
Chapter V: To rque ripple mitigation
A. Source of Torque Ripple
B. Field Oriented control
C. Direct torque control
D. Current shaping techniques
E. Controlling input voltage
F. Intelligent control
G. Drive inverter topology
Chapter VI: Control techniques
equations and co mparison
A. Comparison of control techniques
B. Mathematical equations
Chapter VII: D esign platform for BLDC
A. Methodology
B. Inner rotor
C. Outer rotor
This section discuss on different types of flux
rotation and house mounting.
The mathematical model of designing and
construction for BLDC motor.
Discuss the motor challenges and developments.
Discuss the motor standards of efficiency by
governing bodies.
BLDC motor u sing different applications based on
their performance such as hub motor light vehicle,
water pumping, drone, industry and house
applications.
Mainly discussed limitation in motor to mitigate
torque ripple using different control tech niques.
A briefly analyses the torque ripple generation and
control techniques.
The most suitable control techniques are discussed
individually with block diag ram explanation.
The comparison of different con trol techniques with
respect to advantages and disadvantages are listed.
Each control techniques mathematical equations are
derived and listed.
Discuss the BLDC motor Multiphysics simulation
for high performance applications.
The mathematical equations of each control
technique are derived and listed.
The electromagnetic design procedure is discussed
step by step.
FEA analysis for inner and outer rotor simulation.
The simulation results of various control algorithm
such as FOC, DTC, and intelligent control using
MATLAB software.
Discussed BLDC mo tor market analysis of the past,
present, and future.
Detailed literature on BLDC motor with other
motors.
Discussed Conventional BLDC motor control
techniques.
Organization flow chart.
Future opportunities and challenges in BLDC motor
current control techniques and design aspects.
Chapter XI: Conclusion
A short summar y of the article is presented with
conclusion remarks.
Chapter X: Future challenges and opportunities
Chapter VIII: Control Tech niques Simulation
results.
The overall hardware setup with motor and
simulation results of control tech niques.
Chapter IX: HUB Motor hardware results
The comparison of differ ent control techniques for
fault-tolerant strategies in the conventional control.
Control techniques of bldc m otor dr ives to overcome
EMI and acoustic noises.
Chapter IV: R eliability control
techniques
A. Fault-tolerant control
B. Electromagnetic interference control
C. Acoustic noise control
Figure 2. Organization flow chart
II. TYPES OF BLDC MOTOR
BLDC motor physical design is divided into two parts
stator and rotor. The classification of BLDC motor types is
shown in Fig.4. The motor is constructed with various
configurations such as inner rotor and outer rotor. In [28]
the outer rotor-designed BLDC motor is discussed. The
rotor permanent magnet is embedded at the outer surface
and stator windings are kept stationary inside. The outer
rotor BLDC increases the output torque and power density
of the motor.
Interior PM
Rotor
Stator
Slot
Shaft
Air gap
Figure 3. Inner rotor
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VOLUME XX, 2017 37
BLDC Motor types
Rotor
Stator
Control algorithm
Inner rotor
Outer rotor
Slotted
Slot less
Radial flux
Axial flux Surface magnet
Inserted magnet
Buried magnet
Flux linkage
Design
Back EMF
Phases
Laminated
Iron core
Poles
Sensors
Control
Techniques
Sinusoidal
Trapezoidal
Single
Multi
Sensored
Sensor less
Scalar
Vector
Field oriented control
Direct torque control
Intelligent control
Figure 4. Types of BLDC Motor
TABLE II Comparison of the inner and outer rotor features
The outer rotor BLDC motor is mainly used in electric
vehicles, drones, variable drive industries, water pumping,
and home electronics. In [29] outer rotor BLDC motor is
designed, the airgap radius between stator and rotor is
minimized. Thus, increasing the torque capability per unit
length and current. In [30] structural elements are added to
increase the stability of the rotor. These improve motor
characteristics in dynamic conditions. Fig.5 depicts the
outer rotor-type BLDC motor. In [31] inner rotor BLDC
motor designing is discussed. Using finite element analysis,
the ferrite bonded magnet used BLDC motor is analyzed.
Surface PM
Outer rotor
Stator
Shaft
Slot
Figure 5. Outer rotor (Hub motor)
On experimentation, it found that the inner rotor motor
also provides good power characteristics over dynamic
conditions. In [32] preliminary algorithm of high-speed
ferrite-based BLDC motor is discussed. Magnetic flux
components are improvised by adjusting the mechanical
constraints. Fig.3 represents the inner rotor BLDC motor
structures. The comparison of the inner rotor and outer
rotor BLDC is discussed in Table. II.
Depending on the construction of the PM rotor, rotors in
BLDC motor usually consist of permanent magnets and a
shaft. The cross-section of permanent magnets in motors
can be classified into various types such as (i) surface
mounted magnet [33], (ii) inserted magnet [34], and (iii)
buried or embedded type rotor magnets [35-36]. In this, the
buried or embedded type has more efficiency compared to
other types. Table. III compares the various permanent
magnet rotor structures of the BLDC motor.
Depending on the expectation of the customers, these
BLDC motor drives are integrated in different ways such as
magnetic field path radial and axial flux. Axial flux motors
are more powerful than radial flux motors. In [37] the
characteristics of axial flux type BLDC motor are analyzed
using flux linkage methodology. The mechanical stability
of the BLDC motor is improved by the dual rotor
technique.
BLDC
motor
physical
design
Inner Rotor
Outer rotor
Stator
Iron less core stator
winding outside.
Iron cored stator
winding inside.
Speed
High-speed motors are
available.
Low and medium
speed motor available.
Inertia
Low inertia
High inertia
Noise
Quickly changing
direction makes noisy.
Noise less.
Maintenance
Less maintenance.
High maintenance.
Efficiency
High efficiency.
Less efficiency
compares to the inner
rotor.
Torque
Minimum torque.
Produce more torque.
Power to
weight ratio
Compare to outer run
less.
High.
Gear box
Gear box required.
No gear box required.
Advantage
Rotating shaft moment
of inertia is small.
Heat dissipation
efficiency high.
Reduce the downsize
unit.
Compact size.
High output power.
Increasing the torque
capability and current.
Reducing heat
dissipation.
Low cogging force.
Large airgap.
Increase torque.
Disadvantage
Requires high magnetic
flux density.
Need high-performance
magnet.
High cogging force.
Complex to design
rotor embedded with
magnets.
Mechanical stability.
Cooling stator
winding.
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VOLUME XX, 2017 37
TABLE III Comparison of the various permanent magnet rotor structure
Radial flux
Flux is produced
radially along the
sideways of the rotor
Axial flux
Flux is produced
axially along the axis
of the rotor
Figure 6. Outer rotor
In [38] three different types of radial flux motors are
compared and analyzed. On analysis, it‘s found that dual
rotor type produces good dynamic characteristics. The axial
flux and radial flux features are compared in Table. IV. Fig.
6 represents the axial and radial flux motor flux linkages
flow.
TABLE IV Electromagnetic axial and radial flux path difference
Further, BLDC motor classification based on stator
components is discussed. The stator in BLDC can be
classified based on the number of phases, laminated core
types, and back EMF. The stator in BLDC can be classified
based on the number of phases of operation. In static
applications, mostly single-phase and three-phase motors
are used. Three-phase, five-phase, and seven-phase motors
are preferred for dynamic applications such as electric
vehicles. In [39] multiphase BLDC motor is designed with
the help overlapping winding strategy. Using an
overlapping strategy provides better flux linkage between
the coils. Multiphase motor topologies provide good torque
characteristics and improved fault tolerance capability. The
stator coil winding is star or delta connected. These
winding models are preferred depending upon the
application. Star connection is preferred for high torque
low-speed applications and delta connection is preferred for
low torque low-speed applications. Depending on the
speed, the number of poles in the rotor is increased.
The laminated iron cores are classified as slotted and
slotless cores. In [40] due to the reaction of the PM flux
with the stator's varying permeance, the slotted stator often
generates high-order spatial harmonics. This causes a small
vibrating torque on the shaft, which is referred to as
cogging torque. As a result, it reduces operational noise
preferred for slotless machines. Furthermore, slot-less
machines have lower rotational eddy loss, allowing the
motor to run at faster speeds. Features of slotted and
slotless are compared in Table. V.
TABLE V BLDC stator slotted and slotless structure features
Stator structure
Slotted
Slotless
Advantages
Uneven magnetic
pull.
High power density.
Higher order spatial
harmonics.
Easier to protect.
High power density.
Low cogging torque
Better overload
capacity.
Limit the
operational noise.
Increase operating
frequency.
Disadvantages
Volume of the
machine size is big.
Poor overloading.
High cogging
torque.
Enables to operate
at high speed.
Less efficiency.
Increasing noise and
vibration.
Low inductance to
control motor is
challenging.
Not suitable for
harsh environmental
conditions.
The stators are also further classified based on their back
emf waveforms which are sinusoidal waveform and
trapezoidal waveform. The back emf shape depends on the
interconnection between the stator windings and the air gap
Content
Surface magnet
Inserted magnet
Buried magnet
PM rotor structure
Torque/weight ratio
Very good.
Very good.
Very good.
High-speed running capability
Less preferred for high-speed
operation.
Compared to surface
mounted it has a good affinity
towards high-speed operations.
It shows the best
performance at high speed.
Power factor
Power factor obtained is less.
Power factor obtained is less.
Power factor obtained is
good.
Efficiency
Less compared to buried.
Less compared to buried type.
Very high compared
to the other types.
Magnetic flux
direction
Axial flux
Radial flux
Flux direction
strength
Flux-path is shorter.
Flux-path is longer.
Magnetic field
Strong
weak
Efficiency
High
Compare to axial
low.
Power density
High
Minimum.
Direction
Flux unidirectional
path.
2D dimensional
path.
Iron loss
Decreasing iron loss.
Iron loss maximum.
winding
Minimum heat
conductivity.
Low thermal
conductivity.
diameter
High
Medium
Active length
Minimum
High
Mass
Low
High
Output voltage
High
Low.
Outer rotor
High torque.
Less torque.
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VOLUME XX, 2017 37
distance. BLDC motor is more efficient for sinusoidal back
emf compared to trapezoidal back emf. These motors are a
little bit costlier due to the use of more copper windings
compared to trapezoidal back EMF BLDC motors [39-41].
Mathematical modeling of BLDC motors is needed for
designing and constructing BLDC motors. The
mathematical modeling of BLDC motors is discussed in
detail. The position of the BLDC motor can be estimated by
designing the model of a conventional DC motor which can
be represented by winding resistance, the inductance of the
winding coils, and the back electromotive force [41].
A three-phase BLDC motor has three individual phase
windings and a permanent magnet rotor. Modeling rotor-
induced currents are neglected due to the high resistivity of
magnets and silicon core [42].
The three-phase voltage equations for windings are
modeled as follows,
00
0 0 (1)
00
x a aa ab ac a a
y b ba bb bc b b
z c ca cb cc c c
v R i L L L i e
d
v R i L L L i e
dt
v R i L L L i e
Where vx, vy, and vz are phase voltages of the BLDC motor,
R is the stator resistance of the BLDC motor, ia, ib and ic are
the stator currents of the BLDC motor, Laa, Lbb and Lcc
represent the stator inductance of the BLDC motor, ea, eb,
and ec represent the back EMF of the BLDC motor. The
resistance of the machine is assumed to be equal. The
reluctance between the stator and rotor are assumed to be
null (i.e., there is no change in the stator and rotor
reluctance angle.) then,
(2)
aa bb cc
L L L L
(3)
ab ac ba ca cb bc
L L L L L L M
Substituting the above equations in equation (1),
00
0 0 (4)
00
x a a a
y b b b
z c c c
V R i L M M i e
d
V R i M L M i e
dt
V R i M M L i e
Since the motor is star connected. The stator currents are
considered to be balanced.
0 (5)
abc
i i i
This is used to simplify the inductance matrix as,
(6)
b c a
Mi Mi Mi
Therefore, the main equation becomes,
0 0 0 0
0 0 0 0 (7)
0 0 0 0
x a a a
y b b b
z c c c
V R i L M i e
d
V R i L M i e
dt
V R i L M i e
Since the back EMF of BLDC motor is trapezoidal. The
back EMF equations are given as,
()
( ) (8)
()
a as r
b m m bs r
c cs r
ef
ef
ef
Where
m
is the rotating speed of the motor,
m
is the
flux linkage of the motor
()
as r
f
,
()
bs r
f
and
()
cs r
f
represents the functions of back EMF for various
magnitude instants. The flux linkages between the stator
and rotor are made smooth.
Hence the electromagnetic torque developed by the
BLDC motor is given by the following expression:
1*( ) (9)
e a a b b c c
m
T e i e i e i
The obtained phase voltage equation looks similar to the
armature voltage equation of the direct current machine.
The equation of motion of motor drive,
( ) (10)
em
d
T T J F t
dt
Where J is the combined inertia, F is the mechanical
friction co-efficient. Mechanical speed of the motor is
related by,
(11)
r
m
d
Pdt
Where P is the number of poles of the motor.
Combining all the relevant equations, the system in state-
space equation becomes,
(12)x Ax Bu Ce
Were,
(13)
a b c m r
x i i i
0 0 ( ) 0
0 0 ( ) 0
(14)
0 0 ( ) 0
( ) ( ) ( ) 0
0 0 0 0
2
m as r
m bs r
m cs r
m as r m bs r m cs r
Rf
LM
Rf
LM
R
Af
LM
B
f f f J
P
1000
1
0 0 0 (15)
1
0 0 0
1
000
LM
LM
B
LM
LM
100
1
0 0 (16)
1
00
LM
CLM
LM
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TABLE VI Switching operation for scalar control of BLDC motor.
The BLDC motor operates with Quasi-sinusoidal phase
current and trapezoidal back EMF provided by the rotor
switching table from Table. VI.
Fig. 7 depicts the power circuit for the scalar control of
the BLDC motor [43]. The power switches (T1 to T6) are
IGBT devices and are controlled by PWM signals (Sa, Sb,
Sc).
T1
T4
T3T5
T6T2
BLDC
Vdc +
-
SaSbSc
POSITION CONTROLLER
BLDC
Figure 7. The power circuit of scalar control of BLDC motor
With the above setup, the BLDC motor can also be clubbed
together in the future. Hence the motor transmission losses
are reduced [44-45]. The motor drive systems are classified
as (i) Radially housing mounted, (ii) Radially stator iron
mounted, (iii) Axially housing mounted, (iv) Axially stator
iron mounted. The integrated motor drive figure is depicted
in Fig. 8
Stator
Stator slot winding
Permanent magnet
Inner rotor
Outer surface
mounted
Shaft
Input
switches
Motor case
Housing
Sensors
Figure 8. BLDC Axial flux integrated inverter mounted
While reviewing the types and structure of BLDC motors,
various technical challenges that need to be considered
while designing and constructing BLDC motors are
discussed.
1. Reduced mass: The designed motor should have less
weight. The designed motor may be used for various
applications such as traction, pumping, household, etc.
Depending on the purpose, the designed motor weight may
vary but a motor with less weight can be used for various
applications. Reduced mass is much related to reducing
volume. For applications such as hand tools, the motor used
requires high power and reduced volume. Hence, the
designed motor should be of small size [46].
2. High efficiency: The main purpose of migrating from a
conventional motor system (i.e., induction motor) to a
BLDC motor is for improving the competence of the
system. This is achieved by designing a motor with less
torque ripple, improved flux linkage, and thermal stability
of the system [64].
3. Low cost: Usually BLDC motors run with motor drives.
These drives may be integrated or kept separately. Motors
and motor drives are usually very high in cost. Keeping a
drive separately may increase the installation cost using
wiring cables, individual wiring, etc., Cost reduction in
motor design is done using various component materials
while manufacturing [47].
4. Improved fault tolerance: While designing a BLDC
motor, it is very much necessary to detect the rotor position
for providing the commutation in power switches. These
rotor position detectors are hall sensors, speed sensors,
stator flux coils, etc. In heavy applications such as electrical
vehicle tractions, it is very difficult to continue the
operation if there is any fault in the rotor position sensors.
Hence, it is very necessary to improve the fault tolerance of
the motor [48].
5. Improved thermal stability: Technologies must be
developed which is very useful in improving the thermal
stability of the system. Thermal stability can be improved
by using winding materials with less resistance, stator core
with high flux linkage, and interior permanent magnet with
high flux linkage. In certain cases, the thermal stability can
also be improved by improving the cooling system. In some
static scenarios, motor drive systems are integrated with
motors which may lead the motor to operate in high
temperatures. Hence, proper cooling must be provided to
the system [49].
6. Less noise: The acoustic noise generation in BLDC
motor is due to the electromagnetic forces, structural
design, and odd harmonics development in the motor
Step
Rotor Position
Signal
Reference Currents
Hall Sensor output
Switch ON
position
Switch
OFF position
Controlled
Switch
θr
ia*
ib*
ic*
Ha
Hb
Hc
1
0°-60°
1
0
-1
1
0
0
T1
T3, T4, T5, T6
T2
2
60°-120°
0
1
-1
1
1
0
T2
T1, T4, T5, T6
T3
3
120°-180°
-1
1
0
0
1
0
T3
T1, T2, T5, T6
T4
4
180°-240°
-1
0
1
0
1
1
T4
T1, T2, T3, T6
T5
5
240°-300°
0
-1
1
0
0
1
T5
T1, T2, T3, T4
T6
6
300°-360°
1
1
0
1
0
1
T6
T2, T3, T4, T5
T1
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VOLUME XX, 2017 37
windings. A good BLDC machine has fewer acoustic noises
developed. This can be reduced by skewing rotor and stator
slots incorrect angles, and commutating power switch at the
correct instant [50].
7. High vibration: In the general case, whenever a motor is
operated by drives there will be the generation of common-
mode voltages in the cable which connects drive and motor
and bearing currents in the yoke of the motor. This leads to
frosting, spark tracks on the bearing. Hence, the motor also
experiences more vibration. This can be reduced by the
proper grounding of devices using dv/dt filters, and
electromagnetic interference (EMI) filters [50].
8. Reduction in power electronics cost: Usage of power
electronics drives in industry or household purposes may
lead to an increase in the overall expense of the system.
These motor drives may be integrated with motors or kept
separated. The cost reduction depends on major factors
such as materials, manufacturing process, standardization,
and modularization [51]. Owing to the various challenges
and state of art of BLDC motors, the various applications
and global standards of BLDC motors are reviewed in the
next section.
III. STANDARDS AND APPLICATIONS
A. Standards
The efficiency of the system is one of the key factors to
improve the feasibility of a product.
Standards of efficiency for motors are set and given by
governing bodies of that particular region such as the
International Electro-technical Commission (IEC) in
Europe and the National Electrical Manufacturers
Association (NEMA) in the United States of America.
Present IEC motor standards have four levels [50].
These IEC 60034-30-1 efficiency classes are categorized
into four are the following
1. IE1 (standard efficiency)
2. IE2 (high efficiency)
3. IE3 (premium efficiency)
4. IE4 (super premium efficiency)
The Standard given to the motor defines the efficiency of
either a 50 Hz or a 60 Hz motor drive with a single-phase
winding or three-phase windings built with the BLDC
motor drive with an output power higher than 120W [52].
National Electrical Manufacturers Association
(NEMA) of the United States of America has provided the
guidelines for motor efficiency standards. the standards are
classified as,
1. Old Standard Efficiency Motor
2. Prior NEMA EE
3. NEMA Energy
4. NEMA Premium
Like the International Electro-technical Commission
standards, the NEMA requirements for efficiency also
increase with higher output power. For most of the
standards, the assumptions are made in such a way that
each motor drive is manufactured and optimized for a
specific application with different sectors as shown in
Fig.9. In this section, we are reviewing the various
standards of BLDC motors in various applications [53].
Both inner and outer rotor-based BLDC motors are used
in diverse applications due to their advantages of high
torque-weight ratio, compact size, etc. However, depending
upon the required speed of less than 500rpm, 501 to 2000
rpm, 2001 to 10000rpm, and above 1000rpm, the BLDC
motor types are selected for specific applications.
BLDC motor Applications for different fields
Electric
vehicles Industry Water
pumping Drone Home
appliances
Figure 9. Applications of BLDC motors in diverse sector
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VOLUME XX, 2017 37
TABLE VII BLDC motor specifications for EVs in different ranges from India, China, UK, USA
EV Model
Country
Operating Voltage
(Volt)
Battery
type
Power
(kW)
Motor
Drive
Year
22 Motors, NDS Eco Motors
India
72
Li-ion
2.1,1.5
BLDC
Hub motor
2015
Ather 340
India
48
Li-ion
3.3
BLDC
Hub motor
2018
Ather 450
India
48
Li-ion
5.4
BLDC
Hub motor
2018
Bajaj chetak
India
48
Li ion
4
BLDC
Hub motor
2020
Hero electric A2B
India
36
Li-ion
0.5
BLDC
Hub motor
2021
Revolt RV400
India
72
Li-ion
4
BLDC
Mid-drive
2019
TVS I qube
India
48
Li-ion
4.4
BLDC
Hub motor
2020
Hero Electric flash
India
48
Li-ion
0.25
BLDC
Hub motor
2021
Detel EV Easy plus
India
48
Li-ion
0.25
BLDC
Hub motor
2021
Pure EV Pluto
India
48
Li-ion
2.2
BLDC
Hub motor
2020
Aima E Light Scooter
China
48
Lead-acid
0.5
BLDC
Hub motor
2020
Artisan es-1 pro
United
Kingdom
72
Li-ion
11
Advanced
PM
Mid-drive
2020
Artisan ev0
United
Kingdom
72
Li-ion
3
Advanced
PM
Mid-drive
2019
Harley Davidson Livewire
USA
12
Li-ion
78
Advanced
PM
Mid-drive
2019
B. Electric vehicle
By exploring several countries and their development in
electric vehicle transformation, during the first half of the
decade, electric vehicle sales were soaring. By now more
than 10 million electric vehicles are on the road. In this
47% of the vehicles are only from China. Similarly in
several countries, more than 1% of its market share is
contributed towards electric vehicles. BLDC motors are
preferred for lightweight electric vehicles. Especially
BLDC hub motors are used in electric scooters due to the
advantage of retrofitting. BLDC hub motors are driven
using both sensor and sensor-less motor controllers. In [54]
using hub motors in lightweight electric vehicles improves
the Back EMF by 3%. The main disadvantage of using hub
motors is (i) increases the weight at the power-driven side
which decreases the vehicle stability, (ii) Delivering
uniform torque is too difficult and (iii) Mechanical stress
experienced by hub motors is more compared to normal
BLDC motor. IE-2, IE-3, or IE-4 efficiency standards-
based BLDC motors are used in EVs. Fig.10 shows the
BLDC hub motor structure and its subparts. The motor
controller specifications are not standardized till now,
several manufacturers produce two-wheeler electric
vehicles of their customized standards such as operating
voltage 24 V and 48 V battery power from 40Ah-100Ah,
motor power till 6 kW. BLDC motors are not only preferred
for power transmission in electric vehicles. We can use
BLDC motors for applications such as turbochargers,
blowers, seat comforting systems, etc., [55]. Table. VII
shows a comparison of several electric vehicles and their
power rating and power train drive type, operating voltage,
power, and battery used across the world.
Increased fault tolerance capability, reduced EMI and
reduced torque and flux ripples increase the reliability of
the BLDC motor in the EV application. In electric vehicles,
the conducted emission sources are characterized in a
particular frequency which leads to distortion of the system.
In [56] the EMI sources which are spread through cables,
and their mitigation method are discussed. Power cables
generate more EMI due to conductive sources and
mismatching frequencies. These EMI are mitigated by
predicting distributed element parameters at the resonant
frequency of the system. This improves the reliability of
BLDC motor systems. Similarly, improving fault tolerance
capability also increases the reliability of the system. In
[57] a time-efficient fault detection algorithm for BLDC,
motors in electric vehicles applications are discussed. When
BLDC motors are subjected to fault conditions, the speed of
the machine fluctuates instead of being constant, the back
EMF of the machine also varies, and change in phase
sequence leads to stator faults. Thus, the fault conditions
are detected. The efficient FTC is performed by model-
based techniques which are discussed in detail in a further
section. Torque ripples in BLDC motors in EV applications
effects shaft failures, increased vibrations, and acoustic
noises. In [58] torque ripples and flux ripples are reduced
by using the DTC algorithm which reduces stator iron
losses using compensation and improves torque per ampere
of the machine.
In the future, multi-motor concepts are given special
importance in electric vehicle applications. Hence, the
BLDC motor-driven electric vehicles with four motors at
each wheel are discussed in this paper. The advantages and
disadvantages of multi-motor concepts are also discussed.
In [59] electric cars are driven using four hub wheel motors
is discussed. Driving hub motor at low speed increases the
acoustic noises. Hence, EVs of multi motoring concept
drive with huge noise. Acoustic noises are reduced by using
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a vector control algorithm which benefits in the reduction of torque ripple and acoustic noises.
Hub motor tire
Rim with magnets
Stator winding
Stator winding
Stator slot
Shaft
Rim
Magnets
Front cover
(a) (b) (c)
Without stator
winding
Stator slot
Without stator
winding
Rear cover
(d) (e)
Figure 10. (a) Hub motor structure (b) Stator winding connection (c) Tire rim (d) Without stator winding (e) Motor rear cover
Hence, EVs of multi motoring concept drive with huge
noise. Acoustic noises are reduced by using a vector control
algorithm. In multi motor-driven EVs, Regenerative
braking affects more energy storage compared to single
motor-driven EVs. In [60] the e-differential technique will
be based on Ackerman-Jeantaud geometry. Fig. 11. depicts
the block diagram of electrical differential for a multidrive
system.
POWER
CONVERT ER
&CONTRO LLER
BLDCM
REAR WHEEL
FRONT WHEEL
BLDCM
BLDCM
BLDCM
BATTERY
Figure 11. Block diagram of electrical differential for electric vehicle
C. Water pumping
BLDC motors are preferred for pumping applications due
to their nature of saving energy. The standards are preferred
depending upon the power ranges. IE-1 is preferred for
low-power pumping applications. IE-2 and IE-3 are
preferred for mid and high-power applications. For efficient
usage, these BLDC motors are integrated with renewable
energy sources such as solar energy. In [61] a water
pumping system electrified using a photovoltaic system is
employed. To obtain the maximum amount of energy from
the solar board. Zeta converter, maximum power point
tracking is engaged. These applications are tested for
various dynamic conditions. Since the converter is operated
in continuous current mode, various stresses in switches are
reduced on its components. The MPPT (maximum power
point tracking) is designed using a PI controller in such a
way that it avoids perturbation in the systems. On driving
through solar panels, torque ripples are reduced by
maintaining the solar output voltage constant. In [62] a
pumping system, electrified using solar power is discussed.
When solar power is not used for water pumping, excessive
power is connected to the grid for the utilization of people.
The motor is operated through a three-phase drive and is
connected to a single-phase grid. To control the voltage
source inverter in both directions (supply-side and grid
side), a single phase-phase locked loop control is used. In
addition to this in [63], the power flow control in the grid is
discussed. The power flow control is done using a boost
converter. In [64] a method of controlling solar panels
without a DC-DC converter is discussed in solar water
pumping applications. A diode is connected in series to
avoid the reverse flow of current. The MPPT is controlled
using the voltages and current obtained from the motor
side. The motor signals are converted as the desired signal
for MPPT using a saw-tooth converter. Hence, using the
BLDC motor in water pumping applications not only
increases efficiency but also helps in the efficient cost of
productivity. Fig.12. represents the motor model of the
BLDC motor used in a water pump application.
Rotor fan
Shaft
Stator
Hall effect sensor
Magnets
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Figure 12. Submersible pump motor model
Single rotor
Single rotor
Universal mounting
Optimized stator
Magnet bell
High volume
centrifugal fan
(a) (b) (c)
Shaft
Permanent magnet
Stator slot winding
Mounting
Silicon wire power leads
Bearing
Universal mounting
(d) (e)
Figure 13. (a)Many Single rotors in a drone (b) Single rotor motor model (c) Volume size of motor (d) Motor internal parts (e) Motor mounting
In [65-66] the design of a submersible motor powered by
photovoltaic cells is discussed. The designed motor consists
of a semi-modular dual-stack. In a dual-stack rotor, a semi-
modular rotor means one rotor module is kept fixed at one
end and the other rotor module is kept floating in the other
end. The dual-stack stator helps in increasing the flux
density and decreasing the current density to obtain the
constant torque outputs. For controlling the cogging torque
development, the designed rotor magnets are skewed to a
certain angle. Various parameters are to be considered
while designing a submersible motor such as (i) selection of
rotor magnet heights, (ii) selection of rotor outer radius, (iii)
selection of the slot-pole combination. Submersible motor-
driven using induction motor makes the system rugged and
efficiency is less. Hence, submersible motor-driven using a
brushless direct current motor is preferred for reducing the
torque ripple of the BLDC motor.
D. Drone
The Drone (unmanned aerial vehicles) operation
characteristics are suitable for BLDC motor type single
rotor and multirotor models as shown in Fig.13 and Fig.14.
The flight of drones may operate manually, auto-pilot
assistance, and autonomous aircraft. These drones need
thrust to flow in the air. Hence, we use electric motors for
developing thrust in the air, especially BLDC motors are
used. Mostly IE-2 standard micropower BLDC motors are
preferred for drone application. The main challenge in
drones is to maintain constant torque in the BLDC motor to
maintain high thrust at the base and fault tolerance
capability for improving continuity in operations. In [67]
BLDC motor behavior is analyzed in a time-domain
function drone. A signal based on chaos using the density
of maxima algorithm is used to improve the performance of
the drone instead of a fast Fourier transform. BLDC motor
exhibited extremely good characteristics in the proposed
algorithm of drones. For improving drone stability, the
calculations are made simple. In [68] FOC-controlled motor
drive for drone algorithm is discussed. And FOC-controlled
drone provides less torque and flux ripple compared to
scalar control techniques, when a Fourier transform
function uses vector control technique the computation
intricacy of the machine is reduced. And the response of the
drone is too efficient and the drone runs for more hours. In
[69] the drone characteristic is improvised by using a
Halbach array-based BLDC motor and response surface
method. The Usage of Halbach array magnets and response
face method reduces the losses of BLDC motors and
improves the power characteristics.
E. Industry Applications
In Industry, BLDC motors are preferred for various
applications such as automation robots, hoists, elevators,
conveyor belts, and CNC machines. Since BLDC motor has
the advantage of providing fine torque in static applications
without any ripples in torque compared to other motors
these BLDC motors are preferred a lot. Inherent to the
above advantages BLDC motor provides less inertia, high
torque, and extensive operating speed.
The main challenges of BLDC motors in the industry are
improving fault-tolerant capability, reducing EMI, and
torque and flux ripple control. In this section, how the
reliability of BLDC motor is affected in industry and torque
ripple effects are reviewed. In [70] a sensor less control
algorithm for BLDC motor for reciprocating compressors is
discussed. The peak current magnitude causes the
demagnetization of permanent magnets in the rotor. These
demagnetization currents are measured. The control
algorithm is designed that commutation depends on the
level of phase currents. The proposed technique improves
the power and torque characteristics. In [71] scalar
controlled BLDC motors for industrial applications are
discussed. The realization of PWM signals in the motor
controller is done with help of input and output ports in the
microcontroller.
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VOLUME XX, 2017 37
Multi rotor
Multimotor
Marine Drone
Multirotor
(a) (b) (c)
Universal mounting
Magnet bell
Optimized stator
Bearing
(d)
Figure 14. (a) Multirotor front view (b) Multirotor drone model (c) Multirotor view (d) Multirotor internal part
This simplifies the operation and improves the stability of
the operation. In [72] torque developed in BLDC motors is
reduced by model-based power control schemes. Active
and reactive powers are used to control the torque of the
BLDC machine. Torque is controlled by seven voltage
vectors and flux is controlled by two voltage vectors which
help in efficient control.
F. Household appliances.
Traditionally single-phase induction motors were preferred
for household applications which led to more energy
consumption. Hence, it is necessary to develop a motor
system with high energy efficiency and energy star
requirement. Energy star deals with power reduction,
robustness, and high performance. BLDC motors are used
to save power in many household applications such as
washing machines, water pumping, fan, air conditioner.
These motors provide a good power factor as these motors
run with help of a motor controller. In [73] inverter module
is developed using silicon-controlled rectifiers. Using
silicon-controlled rectifiers reduces the cost by 30 percent.
In [74] space vector-based commutation is used for Fan
application. Using SVPWM decreases the acoustic noise
developed in the machine. In [75] a digital control-based
BLDC motor drive is discussed. The main advantage of
digital control is improving the response of the drive. The
developed torque is also reduced.
2028
2026
20242022
2020
2018
Electric vehicle
Industry Drone
Household appliances
Water pum ping/HVAC
Figure 15. BLDC motor end-user demand future analyze
Fig.15. depicts the end-user demand of BLDC motor on
particular applications. From 2022 to 2028, it is analyzed
that BLDC motors will be used mostly in consumer
electronics, automotive, and industrial applications. Motors
from 500-10000 RPM are preferred a lot. Inner rotor
motors are mostly preferred to outer rotor motors. While
reviewing the various applications of BLDC motors, the
most challenging part is improving the fault-tolerant
capability, reducing the torque ripples, and reducing the
EMI. In the upcoming section, reliability control techniques
and torque ripple mitigation techniques based on BLDC
motor applications are reviewed.
IV. RELIABILITY CONTROL TECHNIQUES
A. Fault-Tolerance Control
Fault tolerance control (FTC) is a censorious process that is
ultimately needed for complicated applications such as
electrical vehicles, robotics, and certain dynamic
applications. The faults in a BLDC motor drive are
classified into four types - (i) power switch open-circuit, (ii)
power switch short circuit fault, (iii) DC-link capacitor
short circuit fault, and (iv) hall-sensor failure. FTC can be
classified into four techniques (1) replication FTC, (2)
Failure oblivious computing FTC, (3) Recovery
shepherding FTC, and (4) circuit breaker FTC. In BLDC
motor drive systems replication FTC method is
implemented. Replication FTC is considered with
providing numerous instances of the system and switching
it into one of the remaining instances in case of any failure
in the system. For efficient fault-tolerant control, a model-
based approach is mostly preferred. This model-based
approach works on the principle of state estimation where
the mathematical model of the system is predicted and the
cost function (CF) estimation is performed. When the
estimated cost function and threshold model are not similar.
Fault code (FC) is generated. Thus, the FTC algorithm is
performed. Fig.16 represents the basic block diagram of
fault tolerance control.
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VOLUME XX, 2017 37
Three
phase VSI BLDC
Optimal
switching
table
a
b
c
g1
g2
g3
Cost
function
calculation
Select nearest
voltage space
vectors
a, b, c
α , β
Reference
voltage
calculation
FT
algorithm
Current evaluation
Fault diagnosis
Cf > th
Yes
FC
Cf
Current
prediction FC
Va, b, c
ia, b, c (k+1)
i*a, b, c
FC
λ *
FC
V1-V3
Vref
Cf
Current observer
Speed sensing
Ia
Ib
Ic
ia, b, c (k)
vdc
FC
Ra, b, c (k)
No
Figure 16. Fault-tolerant control technique
In BLDC, failure is considered with sensors out-
performance in providing gate pulses. In [76] LRGF neural
network scheme is implemented for fault diagnosis and
detecting faults are also discussed. The neural algorithm is
compared with the conventional motor drive algorithm, if
any fault is detected the adaptive control system will
manifest a certain signal as output. Using these signals, the
incipient fault of the system is calculated using the incipient
threshold and tolerance time. The neural network used in
this system detects faults such as voltage leaks in drivers,
mechanical and electrical faults of the system can also be
detected. In [77] the failure of the hall-effect sensor in
aerospace BLDC motors is analyzed. The analysis includes
tests such as performance inspection, visual inspection, x-
ray inspection. These tests are done to check the corrosion
content in the corresponding sensor. The validation of the
hall sensors after the corrosion is also discussed.
The ultimate need for fault tolerance diagnosis is also
shown in [77]. In [78] a direct redundant FTC for the three-
phase brushless direct current motor is discussed. The
various instant at which gate pulses are generated are
shown and these instants are compared with the generation
of gate pulse generation with fault. Direct redundant control
is achieved by using two hall sensor modules parallelly.
The algorithm is designed in such a way that when one hall
sensor is faulted. The output generated from other hall
sensor modules is automatically chosen. The method of
producing fault in gate pulse generation is also discussed.
In [79] a method is used to detect the stator inter-turn fault
in the BLDC motor. With help of stator inter currents
during normal conditions is compared with the stator inter
currents during fault conditions, the difference is converted
as the energy spend. This parameter is compared with a
threshold for fault detection. Since this process should be
expeditious wavelet speed controller is used. In [80]
simultaneous faults are taken into account. Simultaneous
faults are classified into four types and hall sensor faults are
classified into six types to attain fast FTC the time
transition for each hall sensor is calculated accurately and
the degree of rotation is also taken into account. When a
mismatch is encountered between threshold time and real-
time signal generation, reconstructed signals are generated
automatically. In [81] FTC for multiphase motors is
discussed. The main purpose of using multiphase motors is
to achieve high torque and power density. FTC is achieved
by controlling the faulty phase currents with the healthy
phase currents. In [82] the FTC is achieved by an additional
phase leg and fault protective circuits. When there is the
detection of open-circuit faults in both buck converter and
inverter region, FTC is achieved by choosing the redundant
switch present in between inverter and motor. In [84] FTC
three-phase BLDC motor is discussed. FTC is achieved by
using a modular architecture where three individual control
loops which regulate the phase current for each phase gate
pulse. The errors are regulated by PI controllers. In [85] a
BLDC motor drive system that has less electromagnetic
interference and FTC is discussed. The EMI is controlled
by using stray capacitance between cables and the ground
plate. FTC is achieved by ten legs and five modules
topology. The FTC capability is investigated using the
meantime failure analysis. The various fault and techniques
are compared in Table VIII.
B. Electromagnetic Interference Control
Electro-Magnetic Interference (EMI) is defined as
electromagnetic signals which interfere with electrical
equipment such as motor, variable frequency drives, power
converters, etc., EMI is an undesirable disturbance to an
electric circuit. EMI affects machine performance,
efficiency, etc., EMI can be classified into (i) radiated EMI
and (ii) conductive EMI. Fig.17. represents the basic block
diagram of the electromagnetic interference algorithm [86].
Conductive EMI is the electromagnetic interference
between the source and victim which is caused through
conductors and Radiative EMI is the electromagnetic
interference between the source and then victim caused
through a wireless medium [87].
Conducted EMI is found to occur at lower frequencies. It
is further classified as differential mode and common mode.
Common mode EMI source is found to be at high source
and low impedance. Differential mode EMI is caused by
pulsating currents.
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VOLUME XX, 2017 37
TABLE VIII Fault diagnosis technology comparative analysis
BLDC motor
drive fault types
FTC topologies
Adopted techniques
FTC ideology
Ref
Power converter
fault
Model predictive control
Direct torque control
Field oriented control
FTC control is attained by
increasing the dc-link bias
voltage and reducing torque
ripple
Bidirectional converters,
motor drive systems
with fast fusing
capability are used
[76],
[83,84]
Permanent Magnet
demagnetization
fault
Predictive control method
Observer method
By maintaining less flux
ripple and torque ripple
Optimizing rotor
magnetic materials and
magnetic circuits
[85]
Sensor fault
1. Current sensor
2. Voltage sensor
3. Speed sensor
Observer method
Impedance salient pole
Fundamental wave model
DC bus sampling method
Algorithms used to re-
evaluate the speed and
current under normal
condition
Speed sensor
redundancy methods
and fault code diagnosis
are used
[77,78]
Stator winding
fault
Minimum torque ripple
principle
Invariance MMF principle
Torque ripples are
minimized using feed-
forward compensation and
decoupling transformation
principle
The star-point of the
motor is connected to
the dc bus of the drive
system and multiphase
motors are used
[79]
Techniques used to mitigate EMI are classified as
follows: 1. EMI filter and shielding
2. Random modulation
3. Chaotic PWM
1.EMI filters and shielding
EMI filters are used to reduce the interference in
transmission lines and power cables. EMI filters provide
high input resistance to control the frequency content. The
main objective of the EMI filter reduces the interference
between other electronic devices. EMI filters are further
classified as (i) Active filters, (ii) Passive filters, and (iii)
Hybrid filters. LISN is used to stabilize the impedance
present in the circuit and pure power without EMI content.
In [88] an organized EMI filter was designed to separate
the unwanted noise in a three-phase inverter. The noise
level was reduced to 40dBµV. In [89] Angle modulated
switching strategy is used to control the EMI in a BLDC
motor drive. The advantage of using this scheme to reduce
the EMI filter size to 50% and the noise level is suppressed
to 10dBµV. In [90] passive filters are designed to control
the EMI generated by the machine. The inductor and
capacitor are connected parallel and controls the dv/dt and
di/dt spikes in the circuit. The stages of LC are increased
depending upon the dv/dt and di/dt changes.
2. Random modulation
In random modulation, the switching frequency is varied
depending upon the given random signals. Whenever
optimal switching frequency is given to the power switch.
The unwanted power losses generated are reduced. The
disadvantages of this technique are (i) computing random
signals makes the control algorithm complex (ii) the
parameter designing complexity increases. In [93] to reduce
the EMI content wait-free phase continuous carrier
frequency modulation (WPCFM) technique is used.
WPCFM and digital synthesizer theory is combined to
obtain a fast response and effective EMI control. In [91]
spectrum modulation technique is used to control the EMI
content. The spectrum modulation techniques reduce the
EMI to 5-10dB.
3. Chaotic PWM
The pulses for various power switches in the inverter are
developed using various PWM techniques. This technique
not only reduces the torque ripple of the machine, but it
also owes to reducing various losses and improving the
reliability of the converter. The development of EMI is also
reduced. In [92] complementary PWM technique is used to
mitigate the electromagnetic emissions in a three-phase
inverter. The common-mode emissions are controlled by
the bipolar PWM technique. Thus, owing to a reduction in
EMI. The various EMI techniques and their suppression
levels are compared in Table IX.
Three phase
Voltage
Source
Inverter
BLDC
AC
Ground
plane
Drive
Cable
Heat
sink
Parasitic capacitance
Acoustic noise
LISN
CL1
CL2
RL2
RL1
Figure 17. Electromagnetic interference control
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TABLE IX Comparison of EMI Control technique and its suppression level
EMI
Topology
Type of converters
Switching frequency
Suppression level
Ref
Chaotic PWM
Three phase VSD using
multi-carrier PWM
algorithm
3KHz
30% improvement than
conventional
[86]
EMI filter
Three Phase inverter fed to
the motor controller
15 KHz
40dB
[88]
Angle modulated
switching strategy
with EMI filter
Single phase fractional
power BLDC motor drive
20 KHz
10dB
[89]
Bipolar PWM
Three phase BLDC motor
drive.
10 KHz
20% improvement than
conventional
[92]
CFMPWM and
CAPWM
Three phase motor drive
150 KHz
4.6dB and 5.6dB
[95]
AC and DC side
EMI filter
Three phase motor drive
system
2-5 MHz
40dB
[94]
WPCFM
Three phase PMSM motor
drive
10-20KHz
10dB
[93]
C. Acoustic Noise Control
Acoustic noise control for motor drive systems is one of the
most researched topics by scholars [96]. Only a few papers
are discussed for BLDC motors. Acoustic noise is caused
due to many reasons. The major reasons are (i) Torque
ripple generation (ii) electromagnetic fluctuation (iii) non-
ideal spatial distribution of flux density between rotor
permanent magnet and the stator slot openings (iv)
generation of the harmonic component due to non-ideal
distortion of radial flux. The intricacy in the algorithm
increases with controlling electromagnetic fluctuation and
torque ripple of the BLDC machine. These acoustic noises
and vibrations affect increasing EMI content and bearing
current generation. The generation of bearing is one of the
most important topics which many researchers focus to
mitigate. Bearing current generation leads to motor bearing
lock [97].
The acoustic noise generation depends on various
sources such as mechanical noise, noises developed due to
efficient designing, electromagnetic fluctuation, poor
alignment, and aerodynamics of the machine. Fig.18
depicts the various sources of acoustic noises and the
transmission path of the system.
One of the most difficult operations in acoustic noise
control is analyzing the root cause of the issue and
measuring the amount of noise generated [98]. The amount
of noise generated is measured using a microphone and
accelerometer integrated with embedded controllers Fig.19
depicts the block diagram of the methodology used to
analyze the acoustic noise issue.
Many researchers have discussed several topologies to
reduce acoustic noise for BLDC motors both in design and
motor-drive system control algorithm topology. In [99] the
field distribution in between the air gap region of the
permanent magnet is measured instantaneously on various
load conditions and analyzed various remedy actions to
reduce the acoustic noise developed. The effective method
was found to be using slotted stator slots and an embedded
permanent magnet rotor. In [100] optimized pole magnetic
strategy is used to control the field harmonics and analyzed
the origin of the acoustic noise issue. In [101] the torque
and flux ripples are predicted as stator currents. In
sinusoidal commutated BLDC motors, due to field
weakening radial forces developed are reduced. To
optimize this issue, a moving band technique with special
quadrilateral elements is used.
Electroma gnetic noi se
Radial force ripple
Torque ripple
Switching no ise
Combined electrical and
mechanical n oise
Eccentricity
Mechanical noise
Bearing noise
Friction
Aerodynamic noise
Fan
Rotor
Airborne
sound/
acoustic
noise
Structure b orne
sound
Vibrations of stator
Housing
Auxiliaries
Direct
Indirect
Noise sources
Transmissio n path
Perception
Figure 18. Source of acoustic noise
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VOLUME XX, 2017 37
Three phase
Voltage
Source
Inverter
BLDC
X
X
X
FPGA
Controller
Encoder Accelerometer
Microphone
Voltage &
Current sensor
Autotransformer
Three phase
Rectifier
Figure 19. Acoustic noise control
During the analysis, it was found that the developed
technique reduces acoustic noises by 30%. In [102] the
third harmonic component in air gap flux density is
eliminated. The third harmonic component is managed by
forming optical notches in the rotor. Using notches in the
rotor reduces the air gap in the BLDC motor which helps in
reducing the acoustic noise developed by the motor. In
[103] the acoustic noise developed is reduced by using a
voltage regulation circuit for a single-phase BLDC machine
which is used for fan application. Fans generate more noise
due to their aerodynamic design and the humming noise
also increases with variation in speeds. The designed
voltage regulator consists of an inductor connected parallel
to the series resistance and the capacitor element. The
developed technique reduced 16.1% of developed acoustic
noises compared to conventional techniques.
In [104] the acoustic noise development is analyzed by
using a novel digital PWM technique. The digital PWM is
developed for a scalar-controlled BLDC motor drive
system. The odd-order harmonics are reduced. The
developed technique reduces the noise content to 15-30dB.
In [105] a sinusoidal BLDC machine is designed to control
the acoustic noises in machine. Using this method, the
electromagnetic fluctuation is controlled. While analyzing
various acoustic noise control techniques, it found that on
loaded condition increase in toque ripple improves the
acoustic noise generation six times. Reduced torque ripple
and flux ripple reduce the acoustic noise generated in
BLDC machines.
V. TORQUE RIPPLE MITIGATION
A. Sources of Torque ripple
Torque ripples are developed due to several reasons [106].
Various sources for the development of torque ripple are
discussed below and shown in Fig.22.
1. Structure of Motor
The structure of the motor depends on various factors
such as power, speed, loading perspective, etc., these
structure-based factors are constrained with reasons such as
airgap, flux linkage, non-sinusoidal back-EMF.
2. Nature of motor
The motor nature depends on the various materials that we
have used during the construction process. Hence, picking
the correct material is very important. The main factors are
Cogging torque, Reluctance torque, Electromagnetic torque
3. Control of motor
Torque ripples are developed from motor control through
inefficient commutation strategies and internal gate control
schemes.
Ideally, the torque ripple is constant due to the in-phase
back EMF and quasi square wave stator current. But
practically this is not possible due to the nonzero inductance
of the stator winding which leads to the development of
torque ripple. The following graphs represent the effect of
phase currents on torque waveforms.
Fig.20 shows that the incoming current in phase B reaches
a steady-state before current phase A reaches zero. Torque
ripple is due to the commutation of motor current. tr and tf
are the rise time and fall time respectively.
Current Iiaib
tf
tr
-I
Torque
Figure 20. Phase current and Back EMF waveforms
The outgoing current in phase A becomes zero before the
current in phase B reaches a steady state as shown in Fig.
21. Torque dip is due to the commutation of motor current.
Current Iiaib
tf
-I
Torque
tr
Figure 21. Phase current and Back EMF waveforms
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VOLUME XX, 2017 37
Source of torque ripple
Structure of motor Nature of motor Control of motor
Flux
linkage Non
sinusoidal
back EMF
Air gap
Electromagnetic
torque Reluctance
torque Cogging
torque
Free wheeling
diode Commutation
current Conduction
current
Projected
pole Linear PM
motor S-M type
PM motor
PWM
scheme Current
commutation
Figure 22. Sources of torque ripple in BLDC motor
I
-I
Torque
Current tf
iaib
tr
Figure 23. Phase current and Back EMF waveforms
The slope of outgoing current in phase A becomes equal to
the slope of incoming current in phase B. At this
commutation, instant torque remains constant and is
represented in Fig. 23.
Techniques of Torque ripple mitigation: In recent years
many types of research have been done in torque ripple
mitigation in BLDC motors which mainly include (i) Field
orientation control technique, (ii) Direct torque control
technique, (iii) Current shaping techniques, (iv) Controlling
input voltage, (v) Intelligent control, and (vi) Drive-inverter
topology
B. Field Orientation Control Technique
One of the ancient techniques for torque ripple mitigation is
FOC. Fig.24 depicts the block diagram of the FOC control
algorithm of the BLDC motor. In a permanent magnet
motor, the desirable output is obtained when the rotor and
stator flux linkages are 90⁰.
In FOC, the feedbacks are obtained as voltage and
current vectors. The development of space vector pulse
width modulation schemes led many researchers in the
development of the latest inventions in FOC. The stator
currents are mostly characterized as (1) Torque and (2)
Flux. In [106] the difficulties of inserting rotor at correct
angles in a permanent magnet motor is discussed
elaborately. For the implementation of such a system, the
researcher has used a digital signal controller using a
microcontroller (STM32F407). In this technique the rotor
positions are obtained by implementing the encoders, after
inserting the rotor, the encoder pre-set details are reset, and
then for high hold on torque, the duty cycles of PWM
signals are increased. Thus, the step bugging operation is
achieved. In [107], a comparative study of FOC schemes
and DTC schemes for five-phase permanent magnet motor
is discussed. Five phase permanent magnet motors are in
use as they have reduced torque harmonic content
compared to three-phase permanent magnet motors. The
stator flux orientation control is implemented by obtaining
the relative position d-axis and q-axis of stator and rotor
teeth. The development of the dq-axis in the stator is very
important for implementing vector control.
In [108], FOC control for a BLDC machine is discussed.
Cogging torque profile is suitably included in q-axis current
reference, which must be then precisely tracked to mitigate
torque ripple and speed ripple caused by cogging torque.
Voltage
Source
Inverter BLDC
Clarke
Transform
PWM
Generator
PI
Control
PI
Control
ωref
Park
Transform
Inverse
Clarke
Inverse
Clarke
PI
Control
ψref
+
-
+
-
+
-
Battery
Speed
wact
wact
Tref
Tact Vdc
Id
Iq
Vqs
Figure 24. Field orientation control of BLDC motor
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VOLUME XX, 2017 37
Voltage Source
Inverter BLDC
Clarke
Transform
Switching
table
Hysteresis
controller
PI
Control
Inverse
Clarke
Hysteresis
controller
+
-
+
-
Battery
Speed sensing
Tref Tact
Vα,β
ωref
a
b
c
Ia,b
Iα,β
SaSbSc
+
-
ψref
ψact
ωact
Figure 25. Direct torque control of BLDC motor
This technique is also used to mitigate acoustic noise and
vibration. Therefore, the dynamic equations are obtained
using two-pole electrical machines, and then these
equations are converted to two-coordinate system by
realizing them with a reference locking with d-axis
waveforms. In [109], the FOC control system for the BLDC
motor is discussed. FOC control technique to drive BLDC
motor-based compensation torque ripple. By mismatching,
the non-trapezoidal back EMF and stator current the torque
fluctuation can be controlled by an active and reactive
power control loop. Implemented two vector control finite
control set model provides good steady-state and fast torque
response.
C. Direct Torque Control Technique
In the direct torque control technique, the variables relating
to the flux linkage and torque are used to select the voltage
vectors. These details are processed and the errors are
obtained. These errors with further reference signals are
processed in a hysteresis controller. Using DTC, the torque
is controlled by controlling the flux of the system. DTC
technique is mostly preferred as it can verify its control
schemes and is easier to operate. Fig.25. depicts the block
diagram of the DTC technique of the BLDC motor. In
[110], [111], a DTC scheme with an active null vector
control strategy is discussed elaborately. In the proposed
strategy the signs of error are determined by the two-level
flux and torque hysteresis comparator. Here the torque
slopes, the switching time is calculated with the above
inputs, and the torque of the motor can be estimated. This
scheme has the advantage of comparing torque and flux
responses of various vectors.
Twelve-step direct torque control is introduced to control
the vectors with help of a five-level hysteresis controller. In
the proposed scheme the vectors are divided into twelve
sectors which means for every thirty degrees of rotation, the
current and voltage parameter is uploaded to the controller
[112]. It has been discussed clearly that torque ripples can
be mitigated by maintaining constant current and varying
the frequency from low to high by using the DTC
technique. Stator fluxes are controlled by using hysteresis
controllers. In [113], the Torque ripple of the induction
motor is reduced by integrating the CSFTC-DTC scheme
with a neutral point clamped multilevel inverter. The
CSFTC maintains the switching frequency constant.
However, the proposed technique reduces the output torque
but the strategy used for controlling is very complex.
D. Current Shaping Technique
The current shaping technique refers to dodging the gate
pulse generation in power switches of VSI when an
abnormal event such as overcurrent, speed up, and
overloading is detected. Fig. 26. depicts the block diagram
of the current shaping technique of the BLDC motor.
Generally, the steps followed by this scheme are sensing
high current, recognizing overcurrent events, turning off
logic, and re-enabling action for high current detection. In
[114], a technique where the torque ripples are reduced by
using the small capacitors is discussed. The charging and
discharging of the capacitor may return high voltage to the
input system which might damage the drive system. A new
turn-off logic scheme is introduced which would not affect
the power switches.
Voltage
Source
Inverter
BLDC
Battery
PI
Controller
Current
shaping
Switching
table
Hystersis
Controller
Summer
Reference
current
Speed
Rotor
Position
Actual current
Figure 26. Current shaping technique of BLDC motor
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VOLUME XX, 2017 37
Voltage
Source
Inverter BLDC
Battery DC-DC
Converter
PI Controller
Encoder
lookup table
Switching
table
PWM
Generator
PI
Controller
Triangular
Wave
generator
wact
+
-
wref
Rotor
Position
Speed
Figure 27. Controlling input voltage of BLDC motor
Changing the turn-off logic means keeping one switch
down during the current limit. In [115], current hysteresis
control to control the BLDC motor current directly is
discussed in detail. In addition, a novel transition control
method is also discussed. The non-commutation phase
should be constant during commutation interval for proper
current hysteresis control. The outgoing phase current
should reduce as quickly as possible. The sum of the
absolute value of the incoming phase and outgoing phase
current should be constant.
By implementing this technique, the switching losses can
be reduced. In [116], torque ripple mitigation using one
cycle control is discussed in detail. This technique explains
a new topology where back EMF and rotor position
information is neglected. One cycle control means each
switch is operating for one-third of the fundamental cycle
which means it is turned on for sixty electrical degrees and
operating in PWM for the next sixty electrical degrees.
Even order harmonics are also reduced using this scheme.
In [117], torque ripple is reduced by finding the correct
commutation point by auto-calibrating the phase shift. The
dc bus details are obtained for processing these details to
the controller.
E. Controlling Input Voltage
BLDC motors are used in several applications as they have
high torque to speed ratio, high efficiency, fast dynamic
response, lesser maintenance, etc., Fig.27 depicts the
control diagram of input voltage controlling technique of
torque ripple mitigation of BLDC motor. The special
features are trapezoidal back EMF and quasi square wave
fed phase current. Torque ripples are generated when there
is in-equivalency predicted between back EMF and quasi
square wave fed phase current. In this phase, we are going
to investigate a technique for controlling torque ripple by
controlling the input voltage. This scheme for controlling
the input voltage has been investigated by several
researchers. Controlling ways of the input voltage can be
categorized as PWM schemes and varying dc-link voltage.
Usually, torque ripple is caused by the commutation of
power switches. This commutation can be controlled using
the PWM scheme. In [118], a neoteric method for reducing
torque ripple during both conduction and commutation
through a closed-loop operation using a PWM scheme with
buck converter is discussed elaborately. The PWM schemes
are categorized into two steps, firstly controlling the
commutation using PWM schemes and secondly by using
buck converter which converts vin to vout.
In [119], a novel PWM scheme using a bootstrap circuit
is discussed. The conventional six-step inverter is
integrated with a bootstrap circuit and a new PWM driving
scheme is introduced. The theoretical results are convincing
with the performance. In [120], the various PWM schemes
are analyzed. Compared to conventional PWM schemes,
digital PWM is economic and more effective proved by
experimental results. In [121], a method for reducing torque
ripple is investigated using the technique of varying input
voltage. In this technique, the diode of the upcoming phase
power switch will switch on during the commutation of the
outgoing phase switch. This may improve the speed of
ripples. To reduce it, the outgoing phase switch is kept on
even after the phase outgoes. In [122], converter topology
for both modified single end primary inductance converter
and three-level neutral point clamped multilevel inverter is
integrated and investigated in detail. These integrated
topologies give good results compared to the previously
discussed topologies.
F. Intelligent Control
Controlling torque and flux without a controller is
impossible. Hence, a controller is necessary for every
mitigation technique Compared to the other techniques,
implementing an advanced controller has the advantage of
analyzing several parameters. Conventional PI and PID
controllers are used in industries and several applications.
Fig.28. depicts the block diagram of intelligent control
technique of torque ripple mitigation of BLDC motor. In
[124], a fuzzy logic estimator (FLE) is investigated to
reduce the torque ripples.
The function of this neural scheme concept-based
controller is to regulate the commutation angle to maintain
the slew
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VOLUME XX, 2017 37
Voltage
Source
Inverter BLDC
Battery
Artificial
neural
network
Algorithm
Prediction
controller
PI
Controller
Speed
wref wact
++
+
--
-
Tref
Tpredict
ƛ ref
ƛ predict
Figure 28. Intelligent controller of BLDC motor
rates of the commutated phase while keeping the non-
commutating phase current constant. In this scheme, both
the motor winding parameters and output parameters such
as torque are analyzed and a new commutation is generated.
In [125], an integrated loss minimization control and a
wavelet speed controller performance are discussed in
detail. The speed errors between actual and command
speeds are given as input to the loss minimization
controller. These outputs are processed using power
processing units which helps us to reduce the torque ripples
of the drive output. In [126], a spider web-based algorithm
integrated with a small capacitor for varying dc-link voltage
is discussed in detail.
The algorithm and feedback are compiled and used to
generate the switching sequences. In [127], the torque
ripple of the BLDC motor is reduced by using a model
predictive control algorithm The learning is done for
varying speed and the gate pulse generating algorithm of
the conventional system. Using this strategy, a new method
is observed and gate pulse is generated. The output of the
concerned technique contains fewer torque ripples.
G. Drive Inverter Topology
Z-source inverters are single-stage power converters with
voltage buck-boost capabilities. The z-source is placed in
between the voltage source and inverter to boost the voltage
from the voltage source. The advancement in this feature
led to the development of quasi-Z-source, switched
inductor z-source, etc., Fig.29. Depicts the block diagram of
drive inverter topology operated motor controller of BLDC
motor. In [128], a drive system integrated with quasi-Z-
source is discussed in detail. Since quasi-Z-source is meant
for increasing the source voltage, a shutdown network is
installed in-between z-source and voltage source for
controlling the output voltages. A new control system for
space vector modulation is also discussed. The torque ripple
mitigation is achieved by a hybrid topology of two
processes predictive control and voltage-based torque ripple
mitigation. The results are evidence that this technique has
more advantages than the conventional technique constant
dc source. [129] discusses the model and design of a
permanent magnet brushless dc motor which is fed by a Z
source inverter. The paper discusses the limitations of
permanent magnet BLDC motor (PMBDCM) and explains
about two techniques to overcome the limitations of
PMBDCM powered by fuel cell, of which one technique is
using Z-source inverter. The paper discusses the advantages
of Z source fed PMBDCM like higher efficiency,
bucked/boosted voltage ability, and feasibility of adjustable
speed drive systems with motors like PMBDCM.
Z-
Source
Inverter
Voltage
Source
Inverter BLDC
Comparator
circuit
Zero cross
Point
detection
PWM
Generator
Speed PI
Controller
Current
Controller
Reference
Current
Controller
Battery
Figure 29. Drive Inverter topological control of BLDC motor
The Z source inverter is coupled with PWM to get 120o
square waveforms which are said to be apt for the system.
Various state-space models such as the impedance source
network and voltage source fed permanent magnet
brushless dc motor are compared and the equivalent circuit
of both the systems are shown to bring in a comparative
difference between the two systems. The simulation
waveforms are also depicted which show that the system
works like a VSI fed permanent magnet BLDC motor.
After the first second when the necessary boosted function
is fed to the system, it displays shoot through intervals, and
the capacitor voltage is boosted up to 400V. Along with
this, the torque and rotor speed also increases to their rated
values. Two boost control methods for a Z source inverter
are shown in [130].
The paper discusses the flaws of a normal voltage source
inverter whose maximum boosted voltage cannot exceed
the DC bus voltage. The system shows the design of boost
control which gives maximum output value for any
modulation index. To reduce the cost of the boost control,
there should be a constant shoot-through duty cycle or duty
ratio which is shown in this paper for five different
modulation curves. A comparison of several control
methods is conducted and it is concluded that the maximum
boost control for the Z source inverter eliminated low-
frequency ripples in the output frequency and voltage
stresses were also minimized. In [131] discusses the control
methods of Z source inverter (ZSI) and compares voltage
boost and modulation index. The paper initially discusses
the PWM technique used in a 3 phase VSI whose gating
sequence for voltage boost can be applied to ZSI with a few
modifications in the shoot through. A few equations of
voltage boost and voltage stress are shown and depicted and
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VOLUME XX, 2017 37
the comparisons are put forward using the equations. The
simulation of maximum boost control shows that the
voltage gain is the same for the same modulation index and
increase modulation index. The paper shows the two
control methods used for extracting the maximum boosted
voltage of the ZSI and also shows a clear study on the
relationship between boosted voltage and modulation index.
VI. CONTROL TECHNIQUES EQUATIONS AND
COMPARISON
The comparison of various torque ripple mitigation
techniques of the BLDC motor is illustrated in Table X.
The above-mentioned topologies are mentioned and
compared in terms of the adopted technique, advantages,
and disadvantages. The topological equations used to
control various torque ripple mitigation techniques are
depicted in Fig.30.
In a comparison of various torque ripple mitigation
techniques dealt with control schemes, it is inferred that
controlling torque ripple at a wide speed range is too
difficult. The input voltage-controlled technique is
favorable with less computational intricacy, easy to
implement, and provides good behavior for dynamic
applications such as electric vehicles, pumping
applications, etc., Compared to the above-mentioned
techniques, vector control techniques such as intelligent
control, current shaping technique, DTC and FOC provides
good dynamic behavior on contrary to computational
intricacy. Multi-level inverter topologies are also
recommended for both scalar and vector control schemes.
The simulation results proving the most efficient control
techniques and motor results are discussed in the upcoming
sections.
TABLE X Comparison of various torque ripple mitigation techniques of BLDC motors
Methods
Adopted Technique
Advantages
Disadvantages
Reference
Field
orientation
control
Analysis of the d-axis and q-axis is
done and these parameters are fed to
the controller for optimization.
Sinusoidal phase current, low
torque ripples, torque control
at a lower speed.
Rotor sensors need to be
used for induction motors,
FOC sensors are less
reliable.
[106-109]
Direct torque
control
The variables relating the flux and
torque are used to select the voltage
vectors. These details are processed
using the controller to the drive
system for analysing the commutation
point.
Fast dynamic response at
high speeds, torque, and
stator flux decouples,
verifying the effectiveness of
control schemes.
Complex calculations are
needed, the poor dynamic
response at slow speed.
[110-113]
Current
shaping
technique
Changing the switching logic
whenever over current, speed up, and
overloading is detected.
Reduced torque ripple, fast
response, reduced voltage
ripple.
Complicated and
Difficult to understand.
[114-117]
Controlling
input voltage
Regulating the PWM schemes by
enhancing the control systems and
regulating the dc-bus voltages by
using DC-DC choppers.
Reduced torque ripple,
possibilities of implementing
hybrid topologies.
Costly, the response at a
slow speed is very bad.
[118-122]
Intelligent
controller
Used for analyzing several parameters
from the motor by main techniques
involving artificial neural network
algorithm.
Reduced harmonic content,
strong self-learning, and
adaptive ability.
Complex computational
algorithms.
[124-127]
Drive Inverter
topology
Uses multilevel inverters and
modified z-source topologies.
Torque ripple reduces,
common-mode voltage
reduces, and implementing
hybrid topologies is possible.
Costly, separate protection
is needed for power
switches.
[128-131]
Sliding mode
control
Sliding mode control theory is used to
design a controller.
Anti-interference maximum
ability is high.
Robustness is less affected
by parameters.
Difficult control to design,
existential chatting, and high
computing power are required.
[132]
Model
adaptive
control
An offline model-based control is
used for speed control resulting in the
reduction of torque ripples.
The gain of the filter is
adapted to reduce torque
ripple.
The high sampling rate,
Maximum precision requires
high computing power,
increasing the cost of digital
controllers.
[133]
Modified
PWM control
PWM chopping method.
Low-cost digital control technique.
Higher output torque lower
ripples, minimum cost, motor
control hardware is complex.
Eliminating only torque
ripple caused by stator
magnetic field.
[134,135]
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VOLUME XX, 2017 37
Field oriented control
Current shaping circuits
Direct torque control
Controlling input voltage
++=0
=
=1
3+2
3
=cos+sin
=sin+cos
=cossin
=sin+cos
=
=1
2+3
2
=1
23
2
=
=( )
|| =
2+
2
= 2
3( )
= =
+++
=
+++
=
+++
=[+ +]
2
=2 +22+(+)
2
=2 +22+(+)
2
= 2()
2
>+2=2+2
= 2()
2= 22
2>0
=2()
2=<0
=1
3( )
=,,
=3 3(3)
3
=1
2sin1
1=(
2)
2=(
2)
3=(
2+)
1=
1
2=
2
3=
3
=2
Drive inverter topology
0=+1
2
=10
120
=1
120
0=
+
=2+2
++
Figure 30. Control techniques mathematical equation
VII. DESIGN PLATFORM FOR BLDC MOTOR
The design and development of high-performance BLDC
motors for various applications are given in [136]. The
technology used to develop the design optimum balanced
solution of various factors like cost, power density, torque
density, max speed, efficiency, simplicity for ease in
manufacturing, etc., are discussed.
Designing of BLDC motor for light electric vehicle
applications is carried out in this section. The 2 kW BLDC
motor design, analysis, and optimization techniques are
using the following steps in Ansys software.
1. BLDC motor sizing
2. Motor architecture
3. Electromagnetics
2D simulation
3D simulation
4. Multiphysics simulations
Thermal
Structural
Modal
Computational fluid mechanics
5. Dyno testing
EM FEA
model
BLDC
Motor design
Thermal FEA
model Structural
model Modal
analysis
Figure 31. Motor design models
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VOLUME XX, 2017 37
Step-1
Drive cycle
analysis
Step-1
Step-2
Motor
specifications
determination
Step-2
Step-1
Electric Eq
circuit
parameter(EEC)
estimation
Step-3
Step-2
Geometric
parameters
estimation
Step-4
Step-2
Magnetic model
analysis(FEA)
Step-5
Step-2
Performance
Evaluation &
Refined EEC
Step-6
Vrated E
Figure 32. Motor Design Step by Step Procedure
1. Electro-magnetic Design: Selection of motor topology,
slot-pole ratio, winding layout, Stator, and rotor geometry
[137].
2. Thermal Design: Selection winding class, Varnish type,
potting material selection. Design of cooling jacket based
on accurate boundary conditions [138].
3. Structural Design: Analysing and optimizing stress
concentration areas in various motor components.
Calculation of various safety factors for structural
components and improvising using geometry optimization
[140].
4. NVH Design: Model results simulation & Mode shapes
validation at both component and assembly levels.
Iterating various Slot-pole configurations to achieve an
optimum natural frequency and sound pressure levels
[139].
The motor sizing procedure starts from the drive duty
cycle calculation based on vehicle speed rpm or motor
speed. The diameter of the wheel and the height of the tire
calculate the motor speed. Here, the motor can be designed
concerning both the outer rotor and inner rotor for
optimized geometry dimensions. The electromagnetic
design was carried out 2D and 3D for analyzing all
Multiphysics simulation parameters for both inner and outer
rotors. The material Neodymium ferrite boron selected for
rotor high-cost rare earth magnet has high coercivity, high
energy density, and high remanence [141].
TABLE XI BLDC Motor Geometry Dimension
Motor geometry
Specifications
Speed
1000rpm
Rated Torque
16Nm
Outer Stator /inner rotor diameter
120/74mm
Outer Rotor /Inner stator diameter
140/120mm
Stack length
65mm
Number of slots
24
Stacking factor
0.95
Power rating
2kW
Voltage
60v
Current
37A
Rotor Magnet
NdFeB
Stator steel
M19-29G
Slot dimension
Optimized
The M19-29grade non-oriented silicon steel material
laminated in the stator side has a high energy density. The
winding connected is whole coiled using Copper with
minimum loss properties.
Motor width bottom, tooth width, back iron length, and
slot depth the optimized geometry parameters are selected
using several iterations that include different dimensions to
get high performance, Multiphysics parameter simulation
output for highly efficient and cost-effective prototype
motor. Fig.31 represents the various steps involved in
designing and Fig.32 represents the procedures involved in
designing BLDC motor.
B. Inner rotor
The inner rotor BLDC motor inside is acting as rotor
magnet mounted and stator winding is connected outside.
The advantage of the inner rotor magnet is its ability to
dissipate heat, lower inertia ratio, and ability to produce
force impacts on heat [142]. The number of measurements
was carried out both electrical and mechanical dimensions
to fine-tune the data as shown in Table XI. The key
dimensions to design both inner and outer BLDC are stator
outer diameter, stator inner diameter, rotor outer diameter,
rotor inner diameter, magnet thickness, airgap, and slot.
The magnetic flux distribution and flux line pattern are
shown in Fig.33. The static and dynamic characteristics of
the inner rotor are designed using Ansys FEA simulation
for Multiphysics parameters. Maximum flux distribution is
1.66T when the rotor rotates 0 to 360 degrees measured in
each position. The interaction between inner rotor rotation
permanent magnet and stator slot coils results in maximum
torque, rated torque, efficiency, core loss, power, flux
pattern with speed characteristics transient condition.
Figure 33. Inner rotor flux distribution and magnetic flux lines
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The rotor position changes from the initial condition to
attain the peak torque is 39 Nm. When the rotor position
changes torque starts decreasing and at the rated speed it
attains 16Nm.
Figure 34. Inner rotor cogging torque, torque, power, and efficiency
From speed vs power characteristics, speed is increasing
linearly, when it reaches rated speed 1000rpm it reaches the
maximum power of 2 kW. At very low speed the efficiency
starts to increase and it reaches a maximum of 88% at
1800rpm. For rated speed 1500 rpm, efficiency is 82% and
core loss reduced maximum all are depicted in Fig.34.
C. Outer rotor (hub motor)
The outer rotor or in wheel motor stator slot winding is
connected inside and the rotor magnet is mounted outside.
The primary advantage of the hub motor is low cogging
torque compared to the inner rotor. In the design aspect, the
outer rotor when compared to the inner rotor, the minimum
rated current or lower duty cycle occurs at rated speed.
Maximum flux distribution is 1.86 Tesla when the rotor
rotates from 0 to 360 degrees measured in each position as
shown in Fig.35[143]
Figure 35. Outer rotor flux distribution and magnetic flux lines
The optimized geometry simulation output waveform for
the outer rotor is shown in Fig.39. The rotation of motor
rotor position is plotted between cogging torque and speed
characteristics.
The geometry parameters are optimized for the same
dimensions mentioned in Table XI. The interaction between
outer rotor rotation permanent magnet and stator slots coils
maximum torque, rated torque, efficiency, core loss, power,
flux pattern with speed characteristics transient conditions
is discussed in [144]. The outer rotor cogging torque vs
rotor rotation speed, and the outer rotor magnet cogging
torque is very low compared to inner rotor torque as shown
in Fig.36.
Figure 36. Outer rotor cogging torque, torque, power, and efficiency
In output torque vs rotor position graph, at the initial
rotor start position, the torque reaches a maximum is 35
Nm. When the rotor changes the initial position, speed
starts to increase as rated torque decreases, it reaches 14
Nm at a rated speed of 1000 rpm. In the output power vs
rotor speed characteristics at a rated speed of 1000 rpm, the
power reaches 1.75 kW. In the efficiency vs rotor position
speed, at rated 1000 rpm the efficiency reaches 88% and
comparison results of main parameters are listed in Table
XII.
TABLE XII FEA simulation results BLDC 2 kW, 1000 rpm
Rotor structure
Cogging torque
Efficiency%
Inner rotor
High
83
Outer rotor
Low
88
VIII. CONTROL TECHNIQUES SIMULATION RESULTS
The simulation results of various control algorithms such as
FOC, DTC, and intelligent control are verified using
MATLAB software and results are discussed as follows.
The speed parameters are varied to show the difference in
results obtained.
The features of FOC, DTC, and Intelligent control
techniques are compared. And found that intelligent control
schemes are more efficient compared to other techniques.
In intelligent control schemes: (i) dq vector transformation
is obviated, (ii) No traditional PWM algorithms are applied,
(iii) hysteresis controllers aren‘t used as indirect torque
control, and (iv) switching frequency is reduced compared
to other control schemes. The FOC control strategy results
are shown in Fig.37 and Fig.38. BLDC flux and torque are
obtained at 500 rpm, and 1000 rpm respectively. The torque
reference is maintained as 15 Nm during the whole
simulation.
5 5.2 5.4 5.6 5.8 6.0 6.2
0.75
0.8
0.85
5 5.2 5.4 5.6 5.8 6.0 6.2
12
18
24
Flux Torque
Time
Figure 37. FOC fed Torque and flux response at 500 rpm.
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5 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 6
0.75
0.8
0.85
5 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 6
12
18
24
Flux Torque
Time
Figure 38. FOC fed torque and flux response at 1000 rpm.
The DTC control strategy results are shown in Fig.39 and
Fig.40. BLDC flux and torque are obtained at 500 rpm, and
1000 rpm respectively. The torque reference is maintained
as 15 Nm during the whole simulation.
5 5.2 5.4 5.6 5.8 6.0 6.2
0.75
0.8
0.85
5 5.2 5.4 5.6 5.8 6.0 6.2
12
18
24
Flux
Torque
Time
Figure 39. DTC fed torque and flux response at 500 rpm.
5 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 6
0.75
0.8
0.85
5 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 6
12
18
24
Flux Torque
Time
Figure 40. DTC fed torque and flux response at 1000 rpm
The Intelligent control strategy results are shown in
Fig.41 and Fig.42. BLDC flux, speed, and torque are
obtained at 500 rpm, and 1000 rpm respectively. The torque
reference is maintained as 15 Nm during the whole
simulation.
5 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 6
0.75
0.8
0.85
5 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 6
12
18
24
Torque Flux
Time
Figure 41. Intelligent control fed torque and flux response at 500 rpm.
5 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 6
0.75
0.8
0.85
5 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 5.9 6
12
18
24
Flux
Torque
Time
Figure 42. Intelligent control fed Torque and flux response at 1000 rpm.
Table XIII, XIV, XV represent the results and discussion
of torque ripples, flux ripples, and current THD of FOC,
DTC, and Intelligent control. The results are obtained as
standard deviation values. Thus, proving that the intelligent
control technique is more efficient compared to other
techniques.
TABLE XIII Results of FOC
Speed
FOC
Torque ripples
Flux ripples
Current THD
500
1.885
1.0005
16.35
1000
2.005
0.0093
16.61
TABLE XIV Results of DTC
Speed
DTC
Torque ripples
Flux ripples
Current THD
500
1.561
0.0089
15.05
1000
1.774
0.0082
15.93
TABLE XV Results of Intelligent Control
Speed
Intelligent Control
Torque ripples
Flux ripples
Current THD
500
1.091
0.0065
11.67
1000
1.074
0.0066
12.01
IX. BLDC MOTOR HARDWARE RESULTS
The hardware analysis, performance, and designing of the
BLDC motor controller using vector control is done and the
results are verified with help of Altair embed software. The
parameters used for the field orientation control simulation
are shown in Table XVI. To optimize the output, the
proportional-integral controller parameters Kp are changed
from 0.04474 s to 0.015 ms and Ki to 0.04474 ms. These
Altair embed results are obtained during 500 and 1000 rpm
of the motor.
TABLE XVI Motor controller parameters
Parameters
Values
Supply voltage (Vdc)
48 V
Motor voltage
48 V
poles
4
Stator inductance
10.5e-3 H
Mutual inductance
1H
Stator Resistance
1.12 Ω
Power ratings
250 W
Current reference
0.7
The proposed experiment hardware platform is shown in
Fig.43 which includes a BLDC motor, regulated power
supply, Altair embed software, mixed scale oscilloscope,
and DRV C2-H2 motor controller which uses TMS320F280
DSP as a microcontroller. This Altair embed software is an
emulator which can be used for coding various
microcontrollers using visual simulation.
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VOLUME XX, 2017 37
Regulated Power
supply
Mixed Scale
Oscilloscope
BLDC Motor Simulation
Software
Figure 43. Hardware BLDC hub type motor setup
The vector switching states at various speed conditions
are shown in Fig.44 and Fig.45. From the above results, it is
inferred that the analyzed vector control technique produces
minimum vector switching state transition. And hence the
operation happens with less switching frequency.
Figure 44. Vector switching states at low speed
Figure 45. Vector switching states at high speed
Figure 46. Phase current and line-line voltage waveform at medium
speed
Figure 47. Phase current and line-line voltage waveform at High speed.
Figure 48. Current THD and Voltage THD generation.
The motor back EMF and phase current results are
obtained from the analyzed vector control topology by
changing the speed of the BLDC motor from 500 rpm and
1000 rpm and shown in Fig.47 and Fig.48. From the
obtained results, we can observe that the vector control
technique provides a good response. From the hardware
results, we can infer that during the change in speed the
frequency of the switching operation is also varied. The
current THD and voltage THD results of the analyzed
vector control scheme are shown in Fig.52. Since the
switching frequency of the proposed operation is 15 kHz,
the current THD and voltage THD is observed at 15 kHz.
The voltage THD value rises to 4 volts and the current THD
value rises to 200 mA. Hence the obtained hardware results
provide a good response over various conditions and the
THD values are less for the smooth operation of the
machine. Table XVII depicts the torque ripple, flux ripple,
and THD generated by the proposed algorithm. The values
are obtained as standard deviation values. In the upcoming
sections, the future scopes of BLDC motor researches are
discussed from the result findings.
TABLE XVII Hardware results of vector control
Speed
Intelligent Control
Torque
ripples
Flux ripples
Current
THD
Average
switching
frequency
500
2.965
2.051
23.35
1.712
1000
3.625
3.256
26.16
1.914
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VOLUME XX, 2017 37
X. FUTURE CHALLENGES AND OPPORTUNITIES
A. Literature Work
The BLDC motor designing and the analysis of BLDC
motor controllers are discussed in this paper. During the
initial stages, BLDC motors were controlled using scalar
control techniques. Nowadays researchers prefer vector
control techniques such as FOC, DTC, and intelligent
control techniques such as PSO optimization, MPC, etc.,
These techniques provide good response over various static
and dynamic conditions and produce less torque and flux
ripples. These vector control techniques increase the
structural and computational complexity which is realized
that these vector control techniques are practically difficult
[145].
Thus, nowadays researchers are trying to reduce these
complexities. Researchers are trying to reduce the
generated torque and flux ripple generated in each vector
control technique such as controlling input voltage, current
shaping techniques, and drive inverter topology [146]. In
controlling the input voltage technique, researchers are
trying to reduce the torque ripples by reducing the spikes in
DC-DC converter output, and in the PWM-based technique,
researchers are trying to use the space vector PWM
technique with more vectors. In the current shaping
technique researchers are trying to improve the response of
the drive-by excluding the hysteresis controller. In the
conventional drive inverter topology-based research papers,
3L-neutral point clamped inverters are controlled using the
scalar control technique, and Z-source inverters are used to
reduce the torque ripples [147]. Nowadays, Researchers are
trying to reduce the torque ripples of 3L-NPC MLI by using
MCPWM and SVPWM techniques for BLDC motors.
TABLE XIX Review of various torque ripple mitigation techniques
Ref
Advanced control
technique
Inference
[148]
Field orientation
control
An indirect FOC control scheme is
designed which uses a back EMF
structure for controlling the flux
parameters. This developed control
algorithm is used for UAVs.
[149]
Direct torque
control
The DTC developed the maximum torque
per ampere concept for controlling the
control variables. The iron loss concepts
in BLDC motors are excluded while
controlling the variables.
[150]
Current shaping
technique
A predictive current control technique is
discussed where current control is
achieved by injecting square phase current
through the control algorithm ensuring
maximum torque per ampere.
[151]
Controlling input
voltage
Quadral-duty digital PWM-based pulses
are generated to control the inverter part
of the motor controller which efficiently
controls the torque and flux parameters of
the BLDC motor.
[152]
Intelligent control
A BLDC motor controller is designed in
which the outer torque controller is
developed with the help of a model
predictive algorithm. The designed
control algorithm works in offline mode.
[153]
Drive inverter
topology
A torque ripple reduction concept is
discussed with help of NPCMLI and
SEPIC converter. T-shaped NPC MLI are
discussed and the effects are analyzed.
[154]
Fault tolerance
control
A model-based FTC topology is discussed
for the BLDC motor drive system. Open
switch fault control is concentrated and
the control algorithm is discussed for
online mode.
[155]
Electromagnetic
interference.
The effect of load parasitic on common-
mode conducted elements is analyzed.
While analyzing bipolar PWM operated
BLDC motors are taken into account
B. Future Trends
The motor vibrations and torque ripple of the
BLDC motor should be reduced significantly
without obvious torque decline and reduction
inefficiency.
Reducing the cost of the BLDC motor using
alternate ferrite magnet material to improve
efficiency.
Analysis of control schemes should be improved
for a wide speed range.
Hybrid control topologies such as Predictive
torque control and DTC clubbed or predictive
current control and FOC should be developed and
analysed.
Direct torque control topology can be developed
with help of reference voltage vectors for BLDC
motor and its complexity can be reduced.
Multi-level inverter topologies can be developed
using vector control technique for BLDC motor.
BLDC motor drives can be developed with
SVPWM and MLI concepts. SVPWM concepts
can be initiated with fewer vectors.
Intelligent control concepts can be developed with
less complexity by reducing the torque and flux
control vectors in control schemes.
BLDC motor controllers should be developed in
such a manner that it produces less torque ripple
during faulty conditions with extra power
switches.
Bearing current reduction can be given more
importance while discussing EMI reduction for
BLDC motor drive system
FTC algorithm for inverter multiple switch tube
problems should be approached.
FTC based Artificial neural network algorithm
must be discussed for various faults such as stator
intern fault and demagnetization fault.
XI. CONCLUSION
The automobile industry is migrating towards eco-
friendly transportation with less pollution, hence attention
towards electric vehicles and hybrid electric vehicles is
increasing. BLDC motors are gaining more interest in EV
applications due to their simple, robust, and high-efficiency
ability. This paper reviews various types of BLDC motors,
their standards, applications, torque ripple mitigation
techniques, and BLDC motor control techniques, in
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10.1109/ACCESS.2022.3175011, IEEE Access
VOLUME XX, 2017 37
addition to a discussion on the development of a design
platform for BLDC motors. A current study reveals that,
The study reveals that currently, outer surface rotor-
type BLDC motors such as Hub motors are used
widely for commercial applications.
The BLDC motor control drive is used to overcome
fault-tolerant control, electromagnetic interference
control, and acoustic noise control techniques are
discussed.
Outer surface rotor-type motors are more popular due
to the minimum cogging torque leading to high
loading effect, high power, and increased efficiency.
These motors have a lower requirement of cooling for
the rotor as they are exposed to the outer atmosphere
receiving ambient air cooling.
Torque ripples in BLDC motors are more at low
speeds and less at high speeds. However, Axial-type
BLDC motors have higher efficiency and higher
torque than the other types of EV motors. Hub motor
is used in EV due to its advantage of compact size and
retrofitting type model.
Intelligent controller stands superior amongst the
various control techniques used for BLDC motors as it
reduces torque ripples better than the other types of
controllers.
Design and FEA analysis of an inner rotor type BLDC
motor and an outer rotor type BLDC motor have been
presented in this paper. The simulation results
substantiate the effectiveness of the outer surface
rotor-type BLDC motor. Hardware results also
confirm the simulation results.
Finally, the challenges in BLDC motor current control
techniques and future opportunities are discussed for
future researchers.
APPENDIX
c
A
= cross-sectional area of a conductor in mm
cu
A
= area of a copper conductor in a slot in m2
g
B
= Air gap flux density in the middle 1200 of a poles
Wb/m2
max
B
= Maximum flux density in Wb/m2
c
D
= Diameter of the conductor in mm
s
d
= slot depth in mm
steel
D
= Density of steel in kg/m3
b
E
= Back EMF of the motor in volts
c
E
= EMF induced per conductor in volts
t
E
= EMF induced in a turn in volts
g= air gap in mm
c
I
= current through a conductor in amps
phase
I
= phase current in amps.
s
I
= current in a DC source in amps
J= maximum current density in Amps/m2
fill
K
= slot fill factor
L= active length of the motor in mm
t
l
= length of turn in m
ph
N
= several phases.
s
n
= total number of turns in a slot
s
N
= number of slots
P= number of poles
loss cu
P
= copper loss in watts
loss core
P
= core loss in watts
s
= flux in slot pitch in Wb.
t
= flux in the tooth in Wb
cu
= resistivity of copper in ohm-cm
Rph= Resistance of phase in ohms.
Rro= Rotor outer radius in mm.
Rsi= stator inner radius in mm.
Rso= stator outer radius in mm.
Rt= Resistance of a turn in ohms
SPP= slot pole phase.
c
= coil pitch.
s
= slot pitch.
V= linear velocity of a rotor in m/sec.
cu
V
=volume of copper in m3.
rotor
V
= volume of the rotor in m3.
stator
V
= volume of stator in m3.
bi
w
= back iron length in mm
cu
w
= weight of copper in Kg
m
= Angular velocity of the rotor in m/sec
motor
W
= weight of motor in Kg
/stator rotor
W
Weight of stator/ rotor in Kg
t
W
=tooth width in mm
A. Design BLDC motor torque Equation
Force on a current-carrying conductor in a magnetic field
*F IL B
sinF BIL
Force on one conductor
c g c
F B I L
Torque on one turn
c g c si
T B I LR
Torque on one coil
2
t g c si
T B I LR
2
coil g c s si
T B I n LR
Torque on one phase
2
phase g c s si
T B I n LR
Torque developed in Motor
22 g c s si
T pB I n LR
c phase s
I I I
2g c s si
T PB I n LR
Therefore P=2p
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VOLUME XX, 2017 37
L -Length of the conductor
B- Magnetic flux density
I-Current through conductor
ө- Angle between L and B
B. BLDC Back EMF expression
EMF in one conductor
cg
E B Lv
c g m si
E B Lw R
EMF in one turn
2
t g m si
E B Lw R
EMF in one Coil
2
coil g s m si
E B Ln W R
EMF in one phase
phase g s m si
E PB Ln W R
Back EMF in BLDC motor
2
b g s m si
E PB Ln W R
C. Stator winding design
Maximum current density in a conductor
;2
cc
cc
IA
AD
j
Coil pitch
1
22
si s
c
R d l
P
22
tc
lL
D. Stator slot design
Slot area
cu
s
fill
A
AK
Slot fill factor
;
ro si s ph
R R g N P N
2si
s
s
R
N
Slot pitch
st
maxs g t
LB w L B
Trapezoidal slot area
max
;
g
t s sb s t
B
W w w
B
1
2
s st sb s
A w w d
2si s
st t
Rd
ww
N
Stator back iron
max
max
2;
2
g si
si g bi bi
BR
RLB w LB w
p B P
so si s bi
R R d w
Weight of the BLDC motor
Rotor
2
rotor ro
V R L
rotor steel rotor
W D V
Stator
22
stator so si s s
V R R L N A L
stator steel stator
W D V
Windings
cu ph s t c
V N pn l A
cu cu rotor
W D V
Overall weight
motor rotor stator cu
W W W W
;
cu t
t ph s t
c
l
R R n R
A
E. BLDC Losses
Copper losses
2
2
loss cu s ph
P I R
Core losses
/
loss core stator
P coreloss Kg W
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VOLUME XX, 2017 37
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BIBLIOGRAPHY
DEEPAK MOHANRAJ has
completed bachelor‘s degree in
electrical and electronics engineering
with distinction from Anna
University in the year 2007, and
obtained master degree in power
electronics and drives from Anna
University in the year 2011. He has
gained 11years of teaching experience in engineering
colleges. He is currently pursuing Ph.D. degree in SRM
Institute of Science and Technology, Chennai, India.
Currently doing his research work in E-Mobility research
centre, Department of electrical and electronics
engineering, SRM Institute of science and technology,
Chennai. His area of research includes electric vehicle, e-
motor design, motor controllers and power converters for
electric vehicles.
Ranjeev Aruldavid has completed
his undergraduate education from
SRM Institute of Science and
Technology, Tamil Nādu, India in
the year 2021.He is currently
pursuing Internship DST SERB Core
Research Grant, File no.:
CRG/2019/005483 at E-Mobility
research centre, Department of electrical and electronics
engineering, SRM Institute of science and technology,
Chennai. His area of research includes electric vehicle, e-
motor design, motor controllers and power converters for
EVs.
Dr. Rajesh Verma is an Associate
Professor in the Department of
Electrical Engineering at the King
Khalid University, Abha, KSA. He
has work experience of more than
20 years of teaching and
administration at many reputed
institutes in India including MNNIT-Prayagraj and many
others. He also worked in Telecom industry for 4 years at
New delhi, India. He completed his B.E., M.E. and PhD in
Electronics and Communication Engineering from MNNIT,
Prayagraj in 1994, 2001 and 2011 respectively. His
research interests include computer network, MAC
protocols, wireless and mobile communication systems,
sensor networks, peer-to-peer networks, M-2-M Networks.
Dr. Abdulwasa Bakr Barnawi,
Assistant Professor, Department of
Electrical Engineering, Collage of
Engineering, King Khalid
University, Abha, KSA. He has
been awarded Ph.D. degree in
electrical engineering from the
Department of Electrical
Engineering and Computer Science at the University of
Toledo, Toledo, OH, USA, Master degree in electrical
engineering from University of New Haven, USA, West
Haven, Connecticut and BSc. Degree in electrical power
engineering from Yanbu Industrial College. His current
research interests include renewable energy integration,
power system planning, generation adequacy evaluation,
energy management (applying priced based demand
response strategies), smart grid, and dynamic electricity
pricing such as Time of Use (TOU), Critical Peak Pricing
(CPP) and Real-Time Pricing (RTP).
Dr. Sathiyasekar K was born in
Erode, TamilNadu, India. He received
the B.E. degree in Electrical and
Electronics Engineering from Madras
University in 1999 and M.Tech.
degree in High Volltage Engineering
from SASTRA University, Tanjore in
2002. He received Ph.D. in High
Voltage Engineering from Anna
university, Chennai in 2010. He is currently a professor in
the department of Electronics and Communication
Engineering, Prathyusha Engineering College, Chennai,
India. Thirteen scholars had completed their Doctorate
degree under his guidance and Eight others are currently
pursuing Ph. D. at Anna University. He has been an Expert
Member for Ph.D. Viva-Voce Examination (University
Nominee). He received a fund of Rs 2.5 crores from
Ministry of MSME for Business Incubation Cell and also
received fund from MNRE, Government of India for FDP
Programme. He received an award of ‗Certificate of
Outstanding Contribution in Reviewing‘ from International
Journal of Electrical Power and Energy Systems, Elsevier,
Amsterdam, The Netherlands. He is reviewer for reputed
journals like IEEE, Elsevier, Technical Gazette and
Australian journals etc. He is Editorial Board Member in
International Journal of Advanced Research in Electrical,
Electronics and Instrumentation Engineering. He got Best
Paper Award in the International Conference on Digital
Factory – 2008, held at CIT, Coimbatore. (e-mail:
ksathiyasekar@gmail.com)
This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Citation information: DOI
10.1109/ACCESS.2022.3175011, IEEE Access
VOLUME XX, 2017 37
Dr.Bharatiraja Chokkalingam
(SM‘19) received the Bachelor of
engineering in Electrical and
Electronics Engineering from
Kumaraguru College of
Engineering, Coimbatore, India, in
2002 and the Master of engineering
degree in Power Electronics
Engineering from Government College of Technology,
Coimbatore, India, in 2006. He received Ph.D. at 2015. He
completed his 1st Postdoctoral Fellowship at Centre for
Energy and Electric Power, Faculty of Engineering and the
Built Environment, Tshwane University of technology,
South Africa in 2016 with National Research Foundation
funding. He was the award recipient of DST; Indo-U.S
Bhaskara Advanced Solar Energy at 2017 and through he
completed his 2nd Postdoctoral Fellowship at Department
of Electrical and Computer Engineering, Northeastern
University, USA. He is a Visiting Researcher Scientist at
Northeastern University, Boston, USA. He is a Visiting
Researcher at University of South Africa. He is also an
Award recipient of Young Scientists Fellowship, Tamil
Nadu State Council for Science and Technology at 2018.
He is also an Award recipient of Young Scientists
Fellowship, Tamil Nadu State Council for Science and
Technology at 2018. He was collaborated with leading
Indian overseas universities for both teaching and research.
He has completed six sponsored projects from various
government and private agencies. He also singed MoU with
various industries. Currently he is running two funded
research projects in wrirelss chagring of EV and UAV
under DST SERB Core Research Grant, Govt. of india. He
is a senior Member IEEE, IEI, and IET. Dr.C. Bharatiraja
is currently working as an Associate Professor at
Department of Electrical and Electronics Engineering, SRM
Institute of Science and Technology, Kattankulathur
Campus, Chennai, India. His research interest includes
power electronics converter topologies, and controls for PV
and EV applications, PWM techniques for power
converters and adjustable speed drives, wireless power
transfer and smart grid. He has authored more than 110
research papers, which are published in international
journal including various IEEE transactions. (e-mail:
bharatic@srmist.edu.in)
Prof. Lucian Mihet-Popa (Senior
Member, IEEE) was born in 1969. He
received the bachelor‘s degree in
electrical engineering, the master‘s
degree in electric drives and power
electronics, and the Ph.D. and
Habilitation degrees in electrical
engineering from the Politehnica
University of Timisoara, Romania, in
1999, 2000, 2002, and 2015, respectively. Since 2016, he
has been working as a Full Professor in energy technology
with the Østfold University College, Norway. From 1999 to
2016, he was with the Politehnica University of Timisoara.
He has also worked as a Research Scientist with Danish
Technical University from 2011 to 2014, and also with
Aalborg University, Denmark, from 2000 to 2002. He held
a postdoctoral position with Siegen University, Germany, in
2004. He is also the Head of the Research Lab ‗‗Intelligent
Control of Energy Conversion and Storage Systems‘‘ and is
one of the Coordinators of the Master‘s degree Program in
‗‗Green Energy Technology‘‘ with the Faculty of
Engineering, Østfold University College. He has published
more than 130 papers in national and international journals
and conference proceedings, and ten books. He has served
as a scientific and technical program committee member for
many IEEE conferences. He has participated in more than
15 international grants/projects, such as FP7, EEA, and
Horizon 2020. He has been awarded more than ten national
research grants. His research interests include modeling,
simulation, control, and testing of energy conversion
systems, and distributed energy resources (DER)
components and systems, including battery storage systems
(BSS) [for electric vehicles and hybrid cars and vanadium
redox batteries (VRB)] and energy efficiency in smart
buildings and smart grids. He was invited to join the Energy
and Automotive Committees by the President and the
Honorary President of the Atomium European Institute,
working in close cooperation with—under the umbrella—
the EC and EU Parliament, and was also appointed as the
Chairman of AI4People, Energy Section. Since 2017, he
has been a Guest Editor of five special issues of Energies
(MDPI), Applied Sciences, Majlesi Journal of Electrical
Engineering, and Advances in Meteorology journals. (e-
mail:lucian.mihet@hiof.
