Challenges of the Optimization of a High-Speed Induction Machine for Naval Applications

Abstract

In several industrial sectors, induction machines are being replaced with permanent magnet based alternatives, owing to the potential for higher power density and efficiency. However, high-speed applications feature a wide flux-weakening region, where advanced induction machines could bring benefits in terms of system-level optimization. This paper gives an overview the technological challenges for high-speed drives with induction machines, materials, simulations and future challenges for the power electronics in these applications. The target application is a high-speed induction machine for a naval turbocharging system. The comparison with permanent magnet synchronous machines will demonstrate how the extended flux weakening operation effectively allows for a weight reduction of the overall system.

Full text

energies
Article
Challenges of the Optimization of a High-Speed
Induction Machine for Naval Applications †
Giampaolo Buticchi 1,2 , David Gerada 2, Luigi Alberti 3, Michael Galea 1,2, Pat Wheeler 1,2 ,
Serhiy Bozhko 1,2, Sergei Peresada 4, He Zhang 1,2, *, Chengming Zhang 5and Chris Gerada 1,2
1Key Laboratory of More Electric Aircraft Technology of Zhejiang Province, The University of Nottingham
Ningbo China, Ningbo 315100, China; buticchi@ieee.org (G.B.); michael.galea@nottingham.edu.cn (M.G.);
pat.wheeler@nottingham.ac.uk (P.W.); serhiy.bozhko@nottingham.ac.uk (S.B.);
chris.gerada@nottingham.ac.uk (C.G.)
2
Department of Electrical and Electronic Engineering, The University of Nottingham, Nottingham NG7 2RD,
UK; david.gerada@nottingham.ac.uk
3Department of Industrial Engineering, University of Padova, 35122 Padova, Italy; luigi.alberti@unipd.it
4Automation of Electromechanical Systems and the Electrical Drives Department, National Technical
University of Ukraine, Kyiv 03056, Ukraine; sergei.peresada@gmail.com
5Department of Electrical Engineering, Harbin Institute of Technology, Harbin 150006, China;
cmzhang@hit.edu.cn
*Correspondence: he.zhang@nottingham.edu.cn
† This paper is an extended version of our paper published in Gerada, D.; Xu, Z.; Golovanov, D.; Gerada, C.
Comparison of electrical machines for use with a high-horsepower marine engine turbocharger. In
Proceedings of the 25th International Workshop on Electric Drives: Optimization in Control of Electric
Drives (IWED), Moscow, Russia, 31 January–2 February 2018; pp. 1–6, doi:10.1109/IWED.2018.8321383.
Received: 16 May 2019; Accepted: 17 June 2019; Published: 24 June 2019


Abstract:
In several industrial sectors, induction machines are being replaced with permanent
magnet based alternatives, owing to the potential for higher power density and efficiency. However,
high-speed applications feature a wide flux-weakening region, where advanced induction machines
could bring benefits in terms of system-level optimization. This paper gives an overview the
technological challenges for high-speed drives with induction machines, materials, simulations and
future challenges for the power electronics in these applications. The target application is a high-speed
induction machine for a naval turbocharging system. The comparison with permanent magnet
synchronous machines will demonstrate how the extended flux weakening operation effectively
allows for a weight reduction of the overall system.
Keywords:
induction machine; high speed electrical drive; pulse width modulated inverter; computer
simulation of electrical machines
1. Introduction
Electrification of transport affords a great opportunity to address emission [
1
] and climate
change issues [
2
]. While electrification to date has been mainly concerned with secondary systems,
rapidly extending areas are those of the more electric engine and general electrified traction and drives.
These have been internationally identified as key technology areas by all international transport
agendas and research strategies including ACARE’s FlightPath2050 [
3
], the United Kingdom’s Low
Carbon Vehicle Partnership’s transport roadmaps [
2
] and several Chinese agendas including the
twelfth and thirteenth five-year plans and other initiatives such as the ‘ten cities—thousand vehicles’
programmes. It is for example at the centre of the United Kingdom (UK)-based Aerospace Technology
Institute’s (ATI) current preoccupations, as given in their strategy refresh of July 2016. To emphasize
Energies 2019,12, 2431; doi:10.3390/en12122431 www.mdpi.com/journal/energies

Energies 2019,12, 2431 2 of 20
the magnitude of the opportunity, for the automotive industry, it is expected that approximately 40%
of all vehicles globally will be electrified by 2025. In China alone, the market growth of plug-in electric
vehicles (EVs) increased by almost 2000% between 2009 and 2015, while the Chinese government
expects a nation-wide EV presence ranging upwards of 5 million EVs by 2020.
From an aerospace perspective, the emissions predictions due to jet fuels is growing at an alarming
rate. It is estimated from ongoing market and research studies that electrification activities in aerospace
will comprise an increase to approximately 50% of overall more electric aircraft (MEA) activities, in the
next 10 years [4].
The marine industry on the other hand, aided by the industry-specific, lower importance given to
weight and power density values, has long been experimenting with various forms of electrification,
including the classical turbo-electrical system. Today it is expected that fully-electrical marine vehicles
will comprise more than 50% of all world-wide vehicles by the year 2035.
At the heart of all this effort and push towards electrification is the electrical drive itself.
The importance of controlled electric drives is well known through all sectors of the industry. Electrical
drives and power electronics (PE) have become a very important and significant industrial sector,
currently worth about RMB 200 billion worldwide [
5
]. Electric drives constitute the backbone of
industrial automation and their diffusion has been constantly increasing in every field, especially in
the transportation industry. In fact, the ever-growing push towards more responsible and sustainable
transport is resulting in electrical systems becoming more and more important. The electrical drive
is typically made up of an electrical machine, a power electronics converter, a controller and the
associated control algorithms. While electric drive technology has made huge steps forward in the last
few decades, however many challenges still lie ahead, including adding new functionalities, improving
efficiency and most importantly for transport applications, improving compactness and integration as
well as the overall reliability, increasing power density and ability to operate in extreme temperatures.
Underlying all of this is the push towards lower costs. The technology is advancing rapidly and
new developments in components and customer requirements need to be embraced quickly by all
interested parties.
An important feature of all the above is the need for higher power densities of these drives.
Higher power densities result in lower weight and lower energy consumption and so forth,
and therefore are a much sought after aspect. Traditionally, this has been sought after by implementing
ever-higher rotational operating speeds, automatically resulting and implying the need for machines
that are inherently ideal for high rotational speed operations. Thus, the induction machine with its
super-robust rotor structure and its controllability has been traditionally thought of as the ideal choice
for such applications.
Recently however the spectacular advent of the permanent magnet synchronous machine (PMSM),
with its incomparable torque density and excellent efficiency values has resulted in these machines
becoming more and more popular and wide-spread in the quest for higher power densities [
6
]. Their
excellent torque density values can result in similar power densities as a high speed, Induction Machine
(IM) counterpart, albeit at a much lower speed than that of the IM system. All this is today resulting in
a general perception and feeling in the industry that the end for IMs is nigh.
However, the reality is also that an electric drive cannot and must not be evaluated only on
its power density values. In fact for transport applications, power density is only one of various
important design objective functions. In all transport applications, reliability, efficiency, adaptability
and controllability are all equally important. A very important aspect for electrical drives is also
the natural inclination of response and operation against the required given cycle. For example in
automotive applications, operation at extended ranges is extremely important for the whole system
level. In a review from 2012 [
7
], the authors noted that for automotive application all technologies
of electric machines, IM, PMSM, Reluctance motor (RM) and even some DC motors can be used.
Whereas in 2012 75% of the manufacturers opted for IMs [
7
] for their wider speed range operation,
the other machines presented some advantages. RM is cheap and very robust with the temperature,

Energies 2019,12, 2431 3 of 20
which is advisable for automotive applications but the higher torque ripple and noise may constitute
an issue. PMSM drives have been gaining significantly in popularity since 2012 with the advantage
of higher efficiency [
8
], although they present a higher cost and a higher sensitivity to temperature.
Tesla has recently introduced the permanent magnet AC machine for the Model 3 in 2017 [
9
]. However,
the decision regarding the best technology has to take into account many system aspects, including
the driving cycle [
10
], which for electric vehicles always has low-speed (urban) and high-speed
(highway) phases.
In today’s world, meeting several objective functions for an electrical drive, can only be
achieved with system-level optimisation. No matter what the machine technology or the converter
family is, the reality is that system-level optimisation is becoming the most practical way how to
achieve all the required parameters. And it is here that the IM does make another ’spectacular’
comeback. For example, for high-speed machines, where an extended operation range is envisaged,
the requirements of a wide flux-weakening region make the optimization procedure much more
complex than usually required for low-frequency application [11].
The contribution of the presenters of the first Workshop on Induction Machines, held at
The University of Nottingham Ningbo China in 2018, are hereby collected in the present work with the
aim of describing how the IM drive can be designed with advanced optimisation techniques that can
finally guarantee appropriate performance at system level, as expected from the most advanced PM
drive options today. Based on detailed literature reviews and the most recent advances in design and
optimisation techniques, this paper strives to build a case for the continued utilisation of IM drives in
today’s world of transport electrification that is currently being dominated by more modern systems
and drives such as the PM drive [12].
The paper covers the materials and methods used in induction machine in Section 2, the results
are reported in Section 3; the conclusion is reported in Section 4.
2. Materials and Methods
This section presents a brief description of the components for high-speed machines for the
laminations and the windings.
2.1. Electrical Steels
The most common choices for the laminations are Silicon alloys: Silicon Iron (SiFe) and Cobalt Iron
(CoFe). The CoFe saturation point depends on the mechanical characteristics (annealing temperature):
the better the characteristics, the lower the saturation point. Even at the optimal annealing (critical for
the stability at high speed), the advantage of the CoFe is the significantly higher (20%) saturation point
than the SiFe, that comes at the expenses of the higher cost. For high-speed application, the lower
weight of the assembly can bring benefits at system level if compared to the SiFe solution.
In addition to the choice of the material, also the lamination plays a fundamental role for the
reduction of the core losses. This is critical, because high-speed machines have high excitation
frequency. Electrical Steels as thin as 0.05 mm with very low core-losses, tailored specifically for high
frequency applications are commercially available [13].
Figure 1compares the mechanical yield-strength and core-loss characteristics at 1 T 400 Hz of
commercially available grades of SiFe and CoFe under their respective trade-names. Considering the
particular application, lamination thickness thinner than 0.35 mm are used but this comes at the
expenses of the reduced yield strength. The blue (
♦
) represent different commercially-available grades
of Silicon Iron laminations. The brown (

) represent different commercially-available grades of Cobalt
Iron laminations.
Research on Silicon still has proved that the content of Si is correlated with better magnetic
performance of the material and that the optimal point is at 6.5% of Si. From the manufacturing
perspective, such a content makes it impractical to realize thin laminations. By using Chemical Vapour
Deposition (CVD) technique this manufacturing issue has been overcome. SiFe with higher Silicon

Energies 2019,12, 2431 4 of 20
percentage is however brittle, that is undesired at high speed. For this reason, a gradient injection of
the lamination can be adopted, by having higher Silicon concentration towards the edges (to reduce
the high frequency loss) and lower concentration towards the center.
Figure 1.
Comparison ofcore-losses and yield strength for different high-performance electrical steels
(Reproduced from [14] with permission from IEEE).
The research related to the high-strength electrical steel has been recently very active due to the
development of machines that feature bridges to guarantee the mechanical strength of the flux barriers
(as interior permanent magnet machines or synchronous reluctance machines). The bridge should
be designed to be as small as possible in order to not compromise the magnetic flux distribution.
Techniques have been adopted to reach these aims [15].
2.2. Copper Alloys
A high-speed induction machine has strict requirements for the rotor bars and end rings:
•high yield strength
•high temperature
•high stiffness, to increase the critical speed
•high conductivity, to reduce the loss
The high temperature requirement rules out the usage of pure copper, that softens when
the temperature increases. The solution is to create copper allows without compromising the
conductibility. Several different types of high strength copper alloys have been utilized for high
speed induction machines, more typically Copper Zirconium (CuZr) [
16
] and Copper Aluminum
Oxide
(CuAl2O3) [17,18]
. For the highest peripheral speeds, Copper Beryllium (CuBe) was traditionally
considered the material of choice, despite its sensitivity in handling due to the toxic elements involved.
Figure 2presents the different materials in an electrical conductivity/yield strength map. The blue
(
4
) represent different commercially-available grades of pure copper and copper alloys. All other
shapes refer to different high conductivity base materials (ex. silver, aluminum, steel etc.).

Energies 2019,12, 2431 5 of 20
Figure 2.
Comparison of losses and yield strength for different high-performance copper alloys
(Reproduced from [14] with permission from IEEE).
2.3. Computation of IM Performance
The challenge of determining the performance of the IM has always attracted the attention of
many researchers. Several different approaches have been proposed throughout the years considering
analytical models and finite element computations. A precise performance evaluation is nowadays
a mandatory goal for various reasons: international standards have dictated that industries produce
more efficient electrical machines in order to to reduce the global energy consumption. There is
also an economic interest to increasing the power density of a machine: this means to reduce the
machine dimensions for a given power and to increase the performance of a machine of given size.
Best methods adopted today include thermal as well as electromagnetic analysis of the machine. This
is certainly the case for machines operating in severe conditions, such as high-speed, high temperature,
frequent overloads, corrosive or polluted atmosphere, and so on.
Besides these considerations, competition in the global marketplace has shortened the time fame
in which new designs must be completed. In today’s environment a very precise analysis which
requires a long time is no longer acceptable, especially in an iterative design process with some
parametrization or within an optimization cycle. When the finite element model of the motor is
coupled with a complicated system model, the computational effort becomes not compatible with the
industrial development process.
These facts then motivate the necessity for a rapid and accurate model for machine performance
prediction. The model must be rapid enough for daily use in office routine calculation but yet has to
exhibit reasonable accuracy.
The approach here presented consists of a combination of analytical and finite element methods
in novel and original ways. Therefore, the speed of the analytical approach is refined with the accuracy
of the finite element method and the synergy between the two methods is maximized [
19
–
22
]. Figure 3
shows the flowchart of the entire model.
Starting from the IM data and the operating conditions, a minimum set of Finite Element (FE)
simulations is carried out to obtain the parameters of the equivalent circuit of the motor [
20
,
21
]. They
are the no load magnetostatic simulations and locked rotor magneto-dynamic simulations.
Next, a lumped-parameter thermal model of the motor is built.
The magnetic model of the IM is based on the classical equivalent circuit shown in Figure 4and
Table 1gives a description of the adopted variables. In the following, lowercase variables represent the
normalized quantities, whereas uppercase ones refer to a specific machine.
In order to obtain an accurate prediction of the IM features, the equivalent circuit parameters have
to be carefully computed. Hence, FE analysis is a mandatory choice. In order to limit the computational
time, 2-D FE simulations are carried out and 3-D parameters are computed analytically and added to
the equivalent circuit. To further increase the simulation speed, especially in design where a single
lamination is shared among various motors, it is convenient to refer all the integral quantities that are
derived from the FE analysis to a winding with one conductor per slot (i.e.,
ncs
= 1) and a unity stack

Energies 2019,12, 2431 6 of 20
length (i.e.,
Lstk
= 1 m). In this way, the result is independent of the voltage and the power rating of the
actual motor.
!"#$%&!'"()'&'*+,!&-(&-.*)/0()'#.0!"1
2
losses, in the inner part of the stator are allowed to increase to
the temperature limit. In addition, an inner rotor fan is mounted
on the shaft so as to force air within ducts to cool the rotor
parts and then to transfer the heat to the external water by
means of a heat exchange system. As a result of these two
cooling systems working in parallel, the power density of the
IM is very high.
It is worth noting that the design of such an IM requires
the thermal and electromagnetic analysis to be carried out at
the same time. A representative thermal network of such a
machine is sketched in Fig. 1(b). The heat is transferred to the
cooling water, flowing around the stator, directly through the
stator contact with the frame and through the air circulation
within the motor. A similar cooling system is used in large
machines designed for traction, wind power generator and/or
elevator systems, often forced oil is used as the external
cooling fluid.
Fig. 1. Example of a ship propulsion induction motor
Another family of machines with a non conventional cooling
system is represented by IMs for submerged pumps. Both
motor and pump are designed with a small diameter and large
length, so as to limit the well diameter. Fig. 2 shows a sketch
of this type of machine. Since the motor operates completely
submerged within the fluid (typically water), it is automatically
cooled by the fluid that is evacuated by the connected pump.
When the well is very deep, the pressure of the external fluid
could deform the motor frame. To avoid deformation the IM
is filled with a mixture of water and antifreeze and thus, can
theoretically work at any depth. However, the presence of the
fluid within the stator influences the choice of the insulating
materials, the internal heat exchange, and consequently the
machine operation. For instance varnish cannot be used to
insulate the winding conductors, and a waterproof insulator
such as PVC has to be used. Such a material exhibits inferior
Fig. 2. A sketch of the structure of a submerged pump
thermal properties to varnish and as such has a large impact
in the IM design process.
Once again, an accurate thermal analysis of the machine
is a key necessity to predicting and maximizing the machine
performance. The representative thermal network of such a
machine is sketched in Fig. 2. The heat is transferred to the
external water by way of flowing through the stator and the
internal fluid.
In light of these considerations the authors strongly con-
clude the necessity of combining the thermal and electro-
magnetic analysis of the machine. The model begins with
the thermal indications found in specialized literature and
depending upon the IM application the thermal network is
suitably modified. In some instances FE simulations are used
to calculate thermal parameters that are then introduced in the
analytical lumped–parameter network. An example of which
is given in Section V.
III. ELECTROMAGNETIC ANALYSIS
The flow–chart of the entire analytical model is sketched in
Fig. 3. Starting from the IM data and the operating conditions,
a minimum set of FE simulations is carried out to obtain
the parameters of the equivalent circuit of the motor. They
are the no load magnetostatic simulations and the locked
rotor magnetodynamic simulations. Next a lumped parameter
thermal model of the motor is built. The thermal computation
is tightly bound to the electromagnetic analysis. A detailed
description of the thermal model and the link between it and
the magnetic model will be given in the next Section.
The magnetic model of the IM is based on the classical
equivalent circuit reported in Fig. 4. In order to obtain an
accurate prediction of the IM features, the equivalent circuit
parameters have to be carefully computed. Hence, FE analysis
is a mandatory choice. In order to limit the computational
time, two–dimensional FE simulations are carried out and
three–dimensional parameters are computed analytically. This
INDUCTION)MOTOR?WITH)THERMAL)MODELING)
3
Fig. 3. Flow chart of the IM thermal–magnetic analysis
choice is supported by the fact that the flux lines in the
lamination geometry are mainly two–dimensional, so that two–
dimensional FE analysis is generally satisfactory, yielding a
substantial reduction of the computational time [9].
Fig. 4. The normalized equivalent circuit of the IM. Lower case letters are
used for the normalized parameters (referring to ncs =1and Lstk =1m)
It is convenient to refer all the integral quantities that are
derived from the FE analysis to a winding with one conductor
per slot (i.e. ncs =1) and a unity stack length (i.e. Lstk =
1m). In this way the result is independent of the voltage
and the power rating of the actual motor [10]. The resulting
equivalent circuits are therefore normalized, in the sense that
they are suitable for any motor adopting the stated lamination
geometry and winding distribution.
The aim of the no–load FE simulations is to investigate the
iron lamination saturation and to compute the corresponding
parameters such as, iron loss resistance r0and magnetizing
inductance lm. The IM is analyzed in the rotor reference
frame: assuming a rotor slip equal to zero, thus yielding a
frequency equal to zero. FE magnetostatic simulations are
carried out, using the slot current density ˆ
Jslot as the field
source.
The flux density in the teeth Btand in the back iron Bbi
are computed to estimate the iron losses. These losses are
synthesized by means of the resistance r0[11].
The normalized magnetizing flux linkage mvs. ampere–
turns is computed by varying the value of ˆ
Jslot. The resulting
curve ˆ
mˆ
Jslot is an intrinsic characteristic of the lamination
and the winding distribution. This curve can be applied to all
motors using the same lamination and winding distribution,
without the need to simulate each motor separately. This
is useful when a series of IMs are investigated. The no–
load characteristic of any actual motor can be achieved by
modifying the normalized flux–linkage and slot current density
according to the actual stack length and number of conductors
per slot.
In the locked rotor FE analysis, linear iron is assumed for
the lamination. Once again the analysis is carried out in the
rotor reference frame, so that the frequency of the simulation
corresponds to the rotor frequency fr. A magnetodynamic
analysis is carried out in order to consider the non–uniform
distribution of the current density within the rotor bars. The
same analysis is repeated at various frequencies, so as to com-
pute the dependence of the rotor parameters on the operating
frequency.
The FE analysis is two–dimensional, however three–
dimensional parameters are computed analytically and added
to the equivalent circuit [8].
They are (i) the stator resistance, (ii) the stator coil end
winding leakage inductance, (iii) the rotor cage ring resistance
and (iv) the rotor cage ring leakage inductance. Effects of
skewed rotor bars are also introduced in the circuit as an
additional leakage inductance.
Once a lamination geometry has been simulated with these
general FE simulations, the normalized equivalent circuit of
Fig. 4 can be constructed. Then the performance of any IM
formed using the same lamination geometry and winding
distribution can be achieved without further FE simulations
simply by rearranging the normalized equivalent circuit ana-
lytically. This yields a real time saving in the development of
an industrial product.
IV. COUPLED THERMAL NETWORK
For the study of the thermal behaviour of an industrial
IM, several lumped parameters thermal networks have been
proposed. For example, in [12] a detailed thermal network is
introduced which describes the temperature in any machine
part, both axial and radially.
Fig. 1 and Fig. 2 show a very simple thermal network, in
actuality analysis networks with more than twenty nodes are
used. Using matrix notation the solution is achieved solving
the system:
[Gth][✓]=[Ploss](1)
where [Gth]is the matrix of the thermal conductances, [✓]is
the column vector of the temperature rise and [Ploss]is the
column vector of the losses.
Using the proposed thermal network, thermal dynamic anal-
ysis can also be performed [12], [13]. In this case thermal
capacitors are added to the network. A generic ith thermal
node is represented as shown in Fig. 5. For each node it is
possible to write the following relation:
4
Fig. 5. Scheme of a generic thermal network node in the dynamic case
✓i(k+1) =✓i(k)+t
Ci2
4PiX
j
Gij (✓i✓j)3
5(2)
Once the thermal network is assembled, it is possible to
compute the temperature behaviour of the motor. Moreover,
the electromagnetic and thermal analysis are strictly correlated.
Starting from the initial value, the motor performance is com-
puted at a given operating point. From the equivalent circuit,
the motor losses are computed and used as heat source in the
thermal model. Solving the thermal network the temperature
rise is computed in the various machine parts and the electrical
parameters of the equivalent circuit are updated. Repeating
this process until convergence, the operating conditions of the
motor are achieved. This process is sketched in Fig. 6.
Fig. 6. Flow chart of the combined electromagnetic–thermal IM analysis
Discontinuous operating cycles of the motor can be also
taken into account. The thermal and electromagnetic models
are solved jointly adjusting power losses and temperatures. An
example will be given in Section VI.
It is worth noticing that each computation is carried out
using the analytical models of the machine. Therefore, each
computation requires a few seconds of both the continuous
and discontinuous operating cycles.
In addition, an advantage of using a normalized model of the
IM is that any variation of stack length and number of winding
turns can be immediately addressed. This is a very useful in
any optimization process, especially from an industrial point
of view.
V. COMPUTATION OF THE THERMAL NETWORK
PARAMET E RS
In order to obtain an accurate thermal prediction, a good
estimation of the thermal parameters is necessary. Many past
works give careful guidelines [12], [14]. For example for the
Fig. 7. A sketch of the stator slot considered in the FE simulation
computation of the convective exchanges, empirical relations
based on adimensional parameters are used. They are based
on experience and experimental test, and there is a wide
variety of relationships which depend both upon the considered
phenomenon (natural convection, forced convection, etc.) and
on the system geometry.
In any event, when information is missing for a particu-
lar application, the finite element analysis can fill the gap.
Therefore suitable FE thermal analyses are carried out for
predicting the necessary thermal parameters. Even in this case,
an FE thermal analysis of the whole machine is avoided, so
as to reduce the computation time. The strategy is to use
the FE analysis to determine the parameters of the thermal
network as precisely as possible, and then use this network
for the computation of IM temperatures under each operating
condition.
In the following, this approach is used for the computation
of the thermal parameters of a submerged pump as sketched in
Fig.2. As the machine for this application is non standard (see
Section II), the thermal network presented in literature has to
be modified. The computation of the particular parameters and
the modifications of the thermal network are now illustrated.
Let us consider the slot winding thermal resistance. In order
to consider the wire insulation in the slot thermal resistance,
in [14] a corrective factor F=/ins is defined, where is
the equivalent thermal conductivity and ins is the insulating
thermal conductivity. In [14] the value of the factor Fis
reported considering conductors with varnish insulation.
When, as is the case in our example, the slot is filled
by cooling water and PVC insulation is used, the factor
proposed in the literature is not suitable. Using FE simulation,
the estimation of the corrective factor Fis updated, for the
actual conditions. Fig. 7 shows the stator slot cross section
considered in the FE simulation together with a sketch of a
single conductor and its PVC insulation. A fixed heat source
(due to the Joule losses) is imposed in each conductor of the
slot. The heat flow Qth through the slot insulation is computed
and the thermal resistance related to the winding in the slot
can be computed as:
Rth =✓cond ✓ins
Qth
(3)
where ✓cond is the average temperature of the conductors in the
slot and ✓ins is the imposed temperature in the slot insulating
sheet. The factor Fis estimated as:
F=1
2⇡LstkRth
(4)
6
means of a winding resistance measurement system. Consider-
ing the variation of the resistance with the temperature, yields
a very good result as reported also in Table I.
Fig. 9. Comparison between prediction (solid line) and measurements
(circles) for the frame and caps temperature
Fig. 10. Comparison between prediction (solid line) and measurements
(circle) for the back iron and slot winding temperature
Furthermore in Table II the predicted and measured mechan-
ical performance of the motor has been reported for various
supply conditions. For all these results the same normalized
equivalent circuit has been used, i.e. the FE simulations are
carried out only one time which yields a considerable time
saving.
After assembling the analytical magnetic and thermal mod-
els, many computations can be carried out rapidly.
B. Intermittent operating cycle
The proposed model also allows the estimation of the motor
performance during intermittent operating cycles. The motor is
supposed to run in subsequent steady state operation. Then the
electrical and thermal models are used to calculate all motor
performance.
TABLE II
COMPARISON OF MEASUREMENTS AND SIMULATION OF MOTOR
PERFORMANCE FOR VARIOUS SUPPLY CONDITIONS.
Test type Torque (Nm)
Measured Simulated error %
22.0 kW 360 V - 50Hz 74.0 74.7 0.97
22.0 kW 400 V - 50Hz 72.9 73.3 0.52
22.8 kW 440 V - 50Hz 75.3 75.7 0.54
Test type Current (A)
Measured Simulated error %
22.0 kW 360 V - 50Hz 49.7 48.3 2.8
22.0 kW 400 V - 50Hz 46.6 45.9 1.5
22.8 kW 440 V - 50Hz 49.7 47.8 3.9
Test type Electrical power (kW)
Measured Simulated error %
22.0 kW 360 V - 50Hz 27.6 27.2 1.4
22.0 kW 400 V - 50Hz 26.7 26.5 0.75
22.8 kW 440 V - 50Hz 28.1 28.0 0.36
In Fig. 11 the motor operates under nominal load for 5
minutes and under half load for the next 5 minutes, the cycle
then repeats. Using the coupled magnetic–thermal model all
of the IM performance data can be calculated. In Fig. 11 the
motor speed and torque are reported and in Fig. 12 the losses
in the various machine parts are shown. Finally, Fig. 13 reports
the temperature in the four main parts of the machine.
Fig. 11. Work cycle of the motor in intermittent operating cycle. Mechanical
characteristics (simulation results).
C. Whole motor thermal transient
In order to illustrate the proposed strategy for a different
motor a four pole servo–ventilated motor is considered in this
subsection. For this case, the whole thermal transient of the
machine is simulated and measured. First the motor is loaded
with nominal power equal to 5.5 kW for one hour and then
the motor is stopped. The motor fan is running the entire time.
The thermal model parameters vary according to the particular
operation of the motor. In particular, when the motor is stopped
the convection coefficient for the airgap and the air in the caps
are recomputed.
7
Fig. 12. Losses in the various machine parts during intermittent operating
cycle (simulation results).
Fig. 13. Temperature behaviour in various machine parts during intermittent
operating cycle (simulation results).
Fig. 14 shows the comparison among the predicted and
measured temperature in the slot winding and in the end
winding of the motor. Predictions are reported with solid lines,
while measurements are reported with squares and circles
(respectively for the stator slot and the endwinding).
Also in this case the combined strategy (magnetic & ther-
mal) yields good prediction of the entire thermal transient of
the motor.
VII. CONCLUSIONS
In this paper, a coupled thermal–electromagnetic analysis
of the three–phase induction motor has been presented. This
analysis involved combining a set of finite element simulations
with an analytical model. In order to achieve rapid prediction,
finite element analysis is used only to estimate some parame-
ters used in the electric equivalent circuit and in the lumped–
parameter thermal network.
Thanks to the accurate choice of the FE simulation quan-
tities, the model can be extended to any motor adopting the
Fig. 14. Whole thermal transient of the 4–pole motor. Comparison between
measurements (circles) and simulations (solid line).
same lamination and winding distribution including those with
different supply conditions. Since the equivalent circuit and
thermal network work in conjunction to predict the tempera-
ture rise and the IM parameters, the proposed strategy proves
to be rapid and accurate at the same time. Taking into account
the temperature rise in the various machine parts, allows the
machine performance to be computed more accurately, even
during severe operating conditions.
Experimental tests confirm the accuracy of the model pre-
dicted results.
REFERENCES
[1] M. J. Duran, J. L. Duran, F. Perez, and J. Fernandez, “Induction-
motor sensorless vector control with online parameter estimation and
overcurrent protection,” IEEE Transactions on Industrial Electronics,
vol. 53, no. 1, pp. 154–161, Dec. 2005.
[2] A. B. Proca and A. Keyhani, “Sliding-mode Flux Observer With Online
Rotor Parameter Estimation for Induction Motors,” IEEE Transactions
on Industrial Electronics, vol. 54, no. 2, pp. 716–723, Apr. 2007.
[3] S. Williamson and J. Ralph, “Finite–element analysis of an induction
motor fed from a constant–voltage source,” IEE Proc., Pt. B, vol. 130,
no. 1, pp. 18–24, Jan. 1983.
[4] S. Williamson, A. Smith, M. Begg, and J. Smith, “General techniques
for the analysis of induction machines using finite elements,” in Proc. of
International Conference on Evolution and Modern Aspect of Induction
Motors, Turin, Italy, July 8–11 1986, pp. 389–395.
[5] C. Veinott, Theory and Dsign of Small Induction Motors. New York:
McGraw–Hill Book Company, 1959.
[6] P. Alger, Induction machines, their behavior and uses, second edition ed.
New York, London, Paris: Gordon and Breach Science Publishers, 1970.
[7] M. Liwschitz-Garik and C. C. Whipple, Electric Machinery, vol.II, A–C
Machines. New York: D. Van Nostrand Company Inc., 1960.
[8] A. Arkkio, “Analysis of induction motors based on the numerical
solution of the magnetic field and circuit equations,” Ph.D. Thesis,
Helsinki University of Technology, Helsinki, Finland, Laboratory of
Electromechanics, 1987, acta Polytechnica Scandinava, Electr. Eng.
Series No.59.
[9] N. Bianchi, S. Bolognani, and G. Comelato, “Finite element analysis of
three-phase induction motors: Comparison of two different approaches,”
IEEE Transactions on Energy Conversion, vol. 14, no. 4, pp. 1523–1528,
Dec 1999.
[10] L. Alberti, N. Bianchi, and S. Bolognani, “A Rapid Prediction of IM
Performance using a combined Analytical and Finite Element Analysis,”
in Proc of IEEE International Electric Machines and Drives Conference,
IEMDC’07, Antalya, Turkey, 3–5 May 2007, pp. 334–340.
[11] S. Williamson and M. Robinson, “Calculation of cage induction motor
equivalent circuit parameters using finite elements,” IEE Proc., Pt. B,
Elect. Power Applications, vol. 138, no. 5, pp. 264–276, September
1991.
Figure 3.
Combined electromagnetic-thermal analysis to compute the IM performance. The normalized
equivalent circuit is coupled with a thermal model to update the machine parameters during analysis.
A Modern
Analysis
Approach of
Induction Motor
Luigi Alberti
Combined
analytical–FE
analysis of IM
Thermal model
FOC IM
Direct drive IM
Others activities
6
Novelty of the proposed strategy
Normalized equivalent circuit
It can be used for any IM with the same lamination
geometry and winding distribution
After the initial FE simulations:
The computation time is very short (only analytical
solution) with a good accuracy
Introduction
Length Increase
Efficiency
Evaluation
Prototype
Experiments
Efficiency Map
Opt. Eff. Trajectory
Along O.E.T.
Higher diameter
Conclusions
15
Combined Analytical–FE IM model
Diagram of the combined analytical–FE procedure
A Modern
Analysis
Approach of
Induction Motor
Luigi Alberti
Combined
analytical–FE
analysis of IM
Thermal model
FOC IM
Direct drive IM
Others activities
6
Novelty of the proposed strategy
Normalized equivalent circuit
It can be used for any IM with the same lamination
geometry and winding distribution
After the initial FE simulations:
The computation time is very short (only analytical
solution) with a good accuracy
Figure 4. Normalized equivalent circuit (stack length 1m, one conductor per slot).
Table 1. Variable description for Figure 4.
rsStator resistance
isStator current
vNormalized Stator voltage
r0Resistor modeling iron loss
lσew Stator leakage resistance
lmMagnetizing inductance
λmStator flux
irRotor current referred to stator
rrRotor resistance referred to stator
sSlip
The resulting equivalent circuit is therefore normalized, that is, it is related to the lamination
geometry and winding distribution rather than to a specific motor design. Its parameters are expressed
as per unit quantities and can be easily scaled to any motor realized with the analysed lamination
adjusting analytically the circuit parameters [21,22].
The FE analysis is 2-D; The following 3-D parameters are computed analytically and added to
the equivalent circuit (Figure 5): (1) stator resistance; (2) stator coil end winding leakage inductance;
(3) rotor cage ring resistance; and (4) rotor cage ring leakage inductance.

Energies 2019,12, 2431 7 of 20
A Modern
Analysis
Approach of
Induction Motor
Luigi Alberti
Combined
analytical–FE
analysis of IM
Thermal model
FOC IM
Direct drive IM
Others activities
4
Analytical vs FE analysis
Analytical Analysis
•Allows a fast and
general analysis
•Inevitable
approximations
Finite Element Analysis
•Accurate analysis
•Geometrical complexity
taken into account
•Piece–wise material
property
•Time consuming
Introduction
Length Increase
Efficiency
Evaluation
Prototype
Experiments
Efficiency Map
Opt. Eff. Trajectory
Along O.E.T.
Higher diameter
Conclusions
12
Combined Analytical–FE IM model
Scheme of the combined analytical–FE model
of the three–phase induction machine.
Figure 5.
Combined analytical-FE analysis. 2D FE simulations are used to compute current and
frequency dependent parameters in the circuit. 3D effects are accounted for analytically.
Once a lamination geometry has been simulated with these general FE simulations, the normalized
equivalent circuit of Figure 4can be computed. Then, the performance of any IM formed using the
same lamination geometry and winding distribution can be achieved without further FE simulations
simply by rearranging the normalized equivalent circuit analytically.
As an example, Figure 6shows the torque versus slip characteristic of three IMs with different
power ratings sharing the same lamination geometry. The different power ratings are achieved
lengthening the stack and changing the number of conductors. Besides the torque characteristic,
other relevant quantities, such as losses, power, efficiency and so on, can be computed with good
agreement with experimental results. This simulation strategy has been profitable adopted to analyse
and compute the performance of several three-phase and single phase IMs of various power ratings.
A Modern
Analysis
Approach of
Induction Motor
Luigi Alberti
Combined
analytical–FE
analysis of IM
Thermal model
FOC IM
Direct drive IM
Others activities
8
3–phase IM 2.2–3.0–3.7 kW
0
5
10
15
20
25
0 0.05 0.1
Motor torque (Nm)
slip
100 mm
120 mm
130 mm
Prediction and measurements comparison
A Modern
Analysis
Approach of
Induction Motor
Luigi Alberti
Combined
analytical–FE
analysis of IM
Thermal model
FOC IM
Direct drive IM
Others activities
8
3–phase IM 2.2–3.0–3.7 kW
0
5
10
15
20
25
0 0.05 0.1
Motor torque (Nm)
slip
100 mm
120 mm
130 mm
Prediction and measurements comparison
Figure 6.
Torque vs slip for three IM of different power ratings (2.2, 3.0 and 3.7 kW) designed on the
same lamination. Prediction (solid-line) and experimental measurements (circle marks) comparison.
The coupled thermal model is based on lumped parameters thermal network [
23
]. An example
is shown in Figure 7for an IM with a water jacket. A thermal model of the machine is particularly
important when specific cooling system is adopted. This is the case, for example, of high power density
machines. The thermal model is coupled with the electromagnetic one to update the parameters and
to increase the accuracy of performance prediction. Thermal capacitance can also be included in the
thermal model when dynamic behaviour has to be investigated. Both electric and thermal circuits are
solved jointly in order to update each other iteratively [24].
Some other simulation techniques can be adopted in order to further improve the computation
accuracy. For example it is possible to include eddy current losses in the lamination using
homogenization techniques. Such additional effort requires an additional computational time but could
be of interest in applications where iron losses become important. An example of such computational
techniques applied to IM are reported in References [25,26].

Energies 2019,12, 2431 8 of 20
A Modern
Analysis
Approach of
Induction Motor
Luigi Alberti
Combined
analytical–FE
analysis of IM
Thermal model
FOC IM
Direct drive IM
Others activities
12
High demanding applications
Figure 7.
Example (simplified) of IM thermal model: thanks to the linearity of the problem
a lumped-parameters thermal network can be profitably adopted. Some parameters in the network can
be estimated via FE simulations (Reproduced from [23] with permission from IEEE).
2.4. Power Electronics
The main objective of the power electronics for a high-speed drive is to synthesize a low-distortion
sinusoidal current waveform with high fundamental frequency. Considering that:
•
the ratio between the switching and sampling frequency and the fundamental frequency
constitutes one of the main control parameters for the drive,
•
the switching frequency of the silicon power devices is limited, a high-speed drive is operating with
a switching/fundamental ratio quite low. For the majority of the applications that rely on standard
time-continuous control design, recommended values for this ratio is 15–20. This leads to switching
frequencies in the order of 50 kHz for high-speed applications in the range of tens of kW.
In this framework, wide-bandgap devices have received increasing attention from both industry
and academia because of their attractive characteristics in terms of low conduction and switching losses,
higher thermal conductivity (for SiC), higher switching frequency capability and possible operation at
higher temperatures. One of the first attempts towards the evaluation of wide-bandgap devices for
electric drives was to substitute the silicon devices in the actual designs and evaluate the performance.
Marked increase in the efficiency was demonstrated by several researchers [
27
], Figure 8. SiC MOSFETs
showed also a better stability of their characteristics with increased temperature. Higher efficiency
with the same operational parameters can be exploited either by reducing the cooling requirements
or by increasing the switching frequency to decrease the size and cost of the magnetic components.
In particular, if the same point of operation were chosen for both Si and SiC, the higher efficiency of
the latter would lead to a reduced thermal stress and possibly longer lifetime.
It has been shown that with the advancement of the technology and of the increased market
penetration of variable frequency drives, the concerns in terms of reliability are growing and special
design procedures as the design for reliability based on the physics of failure approach are attracting
the interest. In this framework, it has been already demonstrated that SiC devices can offer efficient
and high switching frequency operation for the high-speed drives, however, how these characteristics

Energies 2019,12, 2431 9 of 20
can be fully exploited depends on the machine itself. Among the possible failures of the electrical
machines are the bearing faults and the stator insulation fault. The bearing faults can be accelerated
by the high-frequency currents due to the common-mode PWM harmonics because of the capacitive
coupling between the windings and the ground. Lower machine inductance and higher switching
frequency, that represents the key aspects of high-speed drives, increase the magnitude of this current.
A possibility to reduce the leakage current with a conventional power electronics topology is to
employ an optimized modulation strategy [
28
]. In fact, considering a three-phase converter, there are
8 possible switching states: six active vectors (
V1−V6
) and two zero vectors (
V7
,
V8
). Each vector
implies a different value of common mode voltage and the commutation between one vector to the
other causes high-frequency common mode voltage variation that originates the leakage current.
A possibility to mitigate the phenomenon is to choose between vectors with the same common mode
voltage. This normally leads to the avoidance of the zero vectors and to high switching harmonics in
the motor current.
Figure 8.
Efficiency improvement in the case of Si and SiC devices for the three-phase converter (top)
and for the H8 architecture (bottom) (Reproduced from [27] with permission from IEEE).
Some topologies [
29
,
30
] tried to address the common-mode voltage generation with SiC power
converter by modifying the three-phase bridge. This is shown in Figure 9, where additional devices are
placed in the DC rails to decouple the DC and AC side of the converter during the free-wheeling phases.
Proper space vector modulation ensures a reduction of the common-mode voltage. The peculiarity
of this converter is that it allows to use the zero vectors with the same common mode voltage of the
active vectors, as highlighted in Table 2, where the normalized output voltage (
Vuvw N /VDC
) together
with the normalized common mode voltage
VCM/VDC
of the conventional three-phase converter (H6)
and the H8 converter is listed.
As discussed, the voltage stress causes the inter-turn insulation failure. Both the dv/dt and the
switching frequency contribute to this effect and WBG-based drives for high-speed machines fall
into this worst case for the machine. The basic problem is that the full characteristics of the WBG
devices cannot be exploited if this leads to an over-designed machine in terms of insulation thickness

Energies 2019,12, 2431 10 of 20
to meet the reliability requirements. Technological solutions to adapt the voltage stress depending
on the design targets require the use of active gate drivers, as the one proposed in Reference [
31
],
where the voltage and the current of the gate can be modified to control the dv/dt of a SiC MOSFET
power module. An effective possibility to realize this voltage derivative control is shown in Figure 10,
where an array of gate driver resistors is adopted, allowing to select among different transients.
This would give the designers an additional degree of freedom to perform global converter/machine
optimization. The reduced voltage stress of multi-level inverters could be exploited in this application
to reduce the voltage stress of the electrical machines and, at the same time, improve the power quality
and reduce the machine losses [32].
Table 2. Common-mode voltage (VCM ) values [30].
Vector VuN
VDC
VvN
VDC
VwN
VDC
VCM /VD C
H6 H8
V11 0 0 1/3 1/3
V21 1 0 2/3 2/3
V30 1 0 1/3 1/3
V40 1 1 2/3 2/3
V50 0 1 1/3 1/3
V61 0 1 2/3 2/3
H6 V70 0 0 0
V81 1 1 1
H8 V71/3 1/3 1/3 1/3
V82/3 2/3 2/3 2/3
Figure 9.
H8 converter based on the three-phase bridge for the common mode voltage reduction
(Reproduced from [29] with permission from IEEE).
Figure 10. Possibilities for adaptive dv/dt (Reproduced from [31] with permission from IEEE).

Energies 2019,12, 2431 11 of 20
3. Results and Discussion
In this section, an application example showing how an IM machine can constitute the optimal
solution for a marine high-speed drive for Electrically-assisted turbocharging (EAT).
3.1. Application Description
Many published research on increased engine electrification focuses on the automotive spectrum
of transportation [
33
,
34
]. However similar challenges exist with marine engines. For large vessels half
of the total operational costs are fuel costs and ports worldwide are putting increasingly stringent
legislations on emissions. High-efficiency propellers, engine waste-heat recovery and friction-reduction
systems are among the researched technologies. With the recent first practical application and
successful trials of a hybrid marine turbocharger on the freight ship Shin Koho [
35
,
36
], this technology
is amongst the most promising to meet the emissions and fuel efficiency targets.
Within hybrid turbocharging, an electrical machine is placed on the same shaft as the compressor
and turbine wheel of a turbocharger. On high engine loads, when there is high exhaust energy,
the machine is used as a generator, and from the aforesaid trials on the Shin-Koho, it can continuously
provide the vessels entire electrical load [35].
Under low-load operation, such as when slow-steaming, (<30% full-engine load), there is
low energy in the exhaust, resulting in sub-optimal air-intake into the engine. In such instances,
the electrical machine within the hybrid turbocharger can be used as a motor, replacing the traditional
constant speed auxiliary air blower (typically a constant speed Induction Motor), thus resulting in
lower electric power consumption and increased reliability.
The machine is 150 kW with a base speed of 25,000 r/min and a maximum speed of 50,000 r/min
and is integrated between turbine and compressor. This translates to a Constant Power Speed Range
(CPSR) of 2.
As a reference, a 3 MW marine engine is considered for the power-speed requirements.
The minimum dimension for the airgap is set to be 0.5 mm and the engine coolant is used for the
machine cooling as well.
While there are many electrical machine types, only a select few are capable of operating at very
high speeds. A reliable starting guide is the r/min
√kW
figure of merit [
37
], based on which the the
Surface PM Machine and the laminated rotor IM are chosen as the topologies to be compared in more
detail as shown in Figure 11. The candidates are the Permanent Magnet Synchronous Machine (PMSM)
with Distributed Windings (DW) and Concentrated Windings (CW) and the Induction Machine.
(a) (b) (c)
Figure 11.
Machines selected for detailed EAT comparison: (
a
) Distributed Winding (DW) Surface PM,
(b) Concentrated Winding (CW) Surface PM, (c) laminated IM.
Table 3details the charachteristics of the materials considered. All machine share the same kind of
0.1 mm JNEX laminations for the stator. For the rotor of the IM, 0.35 mm-thick high-strength HXT780T
are employed. Insulation class C is considered for all machines.

Energies 2019,12, 2431 12 of 20
Table 3. Electrical Machine Base Selection.
SPM-DW SPM-CW IM
poles 4 4 2
slots 36 6 18 stator 24 rotor
stator lam. 10 JNEX 10 JNEX 10 JNEX
rotor lam. - - HXT780T
other materials Sm2Co17 Sm2Co17, CuCrZc
Inconel718 Inconel718 CuCrZc
3.2. Machine Design
The torque-speed characteristic of the Surface- PM Machine is shown in Figure 12. Due to the lack
of saliency, the field-weakening is severely limited and this implies higher power rating for the power
electronics and an additiona cost.
The intrinsic field control operation of the IM allows to easily meet the power-speed
charachteristics. However, the challenge lies in the materials, since high temperature, high conducibility
and high strenght copper must be used into the HXT780T laminations. For the configuration, 18 slots in
the stator and 24 slots in the rotor are selected, the optimization technique proposed in Reference [
17
]
is therefore applied. One of the key features is to use a drop-shaped bar instead of a circular one to
increase the rotor current density.
The results of the thermal analysis are reported in Figure 13 for the PM and the IM machine at the
rated poewr and base speed. The different sections are denoted as ’Sec 1-5’, turbine and compressor
are denoted by ’Turb’ and ’Comp’ whereas ’EW’ denotes the end windings. Figure 13a shows the
results for the CW surface PM. A very high temperature for the magnets is evident. Remarkably,
a tempearture gradient exists in the machine due to the high temperature of the turbine. Figure 13b
is related to the IM and shows that a continuous rotor operation temperature of 360 C is is achieved.
The high thermal conductivity of the IM rotor helps averaging the rotor temperature, so no gradient
is observerd.
Figure 12. Torque-speed capability for DW Surface PM and Surface Inset PM Machines [38].

Energies 2019,12, 2431 13 of 20
Figure 13.
36-slot, 4-pole CW Surface PM (
a
) and induction machine (
b
) nodal axial temperature
distribution for magnets, rotor sleeve, windings and stator back iron (Reproduced from [
38
] with
permission from IEEE). The
x
-axis represents the section of the machine where the temperature sensor
was placed.
3.3. Cost Comparison, Overall Comparison and Selection
The comparison of the electrical machines considered in this analysis is shown in Table 4. As a note,
only the efficiency of the machine without bearing and power electronics is considered. Since meeting
the cost target is an important engineering task, also the cost anlysis is performed. A constant cost for
the power electronics of $15/kVA is considered.
The permanent magnet machines must comply with the stringent requirement of maximum
magnet temperature. The distributed-wound machine has a simple construction and presents the
maximum efficiency among the selected electrical machine. From the temperature analysis, standard
Sm2Co17 could be employed. However, the reduced field-weaking capbailtiy implies an increased
size of the power electronics. The concentrated winding machine allows to meet the power-speed
requirement thanks to a superior field weakening, however, as shown in Figure 13, the rotor
tempearture above 450 C is too high for the magnets. The construction of the Induction Machine is
complex but it allows better value for money in achieving the performance target. The copper bars of

Energies 2019,12, 2431 14 of 20
the rotor also contribute to making the rotor stiff and equalizing the axial tempearture. After taking all
the elements into consideration, the induction machine emerges as a winner for this application.
Table 4. Comparison between machine topologies for 150 kW EAT Application.
DW SPM CW SPM IM
Electrical steel mass (kg) 15 13 21
Copper mass (kg) 5.8 6.6 9.1
Magnet/Copper Alloy mass (kg) 1.4 1.6 2.7
Torque Ripple (Nmpkpk) 1.6 4.1 6.2
Stator Cu loss (W) 1005 880 1380
Stator Fe loss (W) 1756 1799 1036
Rotor loss (W) 130 620 1404
Total Loss (W) 2891 3299 3820
Peak Rotor Temperature (C) 286 528 369
Inverter Rating (kVA) 330 184 186
Electrical Drive cost ($/kW) 48.2 30.4 26.6
The prototyped 150 kW, 50,000 r/min induction machine is shown in Figure 14. A fabricated rotor
is used instead of casting (that could be used for series production) and extrusion from solid CuCrZr
is performed for the fabbrication of the drop-shaped bars, which are inserted into the wire-cut rotor
lamination stack. A silver alloy is used for brazing the copper bars to the end-rings.
Figure 14.
Prototyped 150 kW, 25,000–50,000 r/min high speed induction machine for marine EAT
application (Reproduced from [14] with permission from IEEE).
3.4. Experimental Results
The first level of testing consists of performing the no-load and locked-rotor tests as described in
IEEE112-2004 [
39
] standard, in order to obtain the equivalent circuit parameters shown in Figure 15.
The parameters here are the stator resistance
Rs
, rotor resistance
Rr
, stator leakage reactance
Xs
,
rotor leakage reactance Xrand the magnetizing reactance Xm.
Figure 15. Induction Machine equivalent circuit [39].
In carrying out the no-load test, a variable frequency programmable supply, achieving almost
pure sinusoidal waveforms is used. The supply frequency is increased in steps till the rated frequency.
The reactive power of the motor at no load, Q0is calculated from:

Energies 2019,12, 2431 15 of 20
Q0=q(3V0I0)2−P2
0(1)
where
V0
is the applied per-phase no-load rms voltage [V],
I0
is the no-load rms current [A] and
P0
is
the no-load input power [W].
The total reactance at no-load X0is then calculated from :
X0=3V2
0
Q0
(2)
Referring to Figure 15, since the slip is 0 (or very small due to the no-load losses) at no-load,
the reactance
X0
measured includes the stator leakage reactance
Xs
as well as the magnetizing reactance
Xm
.
X0=Xs+Xm(3)
In order to compare the experimentally obtained magnetizing inductance with that predicted
analytically as well as that obtained from the indirect FEA tests, the stator leakage component of the
inductance, as computed analytically,
Ls
= 0.1
×
10
−3
H, is subtracted from the experimental values.
The results are summarized in Table 5, showing close matching between the three methods for the
unsaturated values of magnetizing inductance.
Table 5.
Magnetising inductance: measurement and prediction for unsaturated condition. Note:
analytically obtained value of
Ls
= 0.1
×
10
−3
H , subtracted from
Lm
+
Ls
determined experimentally.
Lm(H)
experimental (see note) 3.50 ×10−3
analytical formulation 3.69 ×10−3(+5.1%)
FE analysis 3.62 ×10−3(+3.3%)
The rotor is then locked into position by suitable mechanical means as shown in Figure 16 and
the locked rotor tests are performed. Simultaneous readings of voltage and current in all phases and of
power input at several levels of voltage are taken in order to establish the value in the neighborhood
of rated current. Referring to Figure 15, since the rotor is locked into position the slip is equal to 1.
An approximate calculation of locked rotor impedance can be carried-out on the assumption that the
magnetizing branch is open-circuited. Based on the aforesaid assumption, the rotor resistance
Rr
is
estimated from :
Rr=PL
3I2
L−Rs(4)
where
PL
and
IL
represent the power and the current measured from the locked rotor test. The total
leakage reactance Xs+Xrfrom:
Rr=sVL
IL2
−Vlcosϕ
IL2
(5)
where
VL
,
IL
are the phase voltage and current at locked rotor condition respectively. The comparison
between the FEA and the experiment for the magnetizing inductance is shown in Table 6.
Table 6. Leakage inductance: measurement and prediction at rated current.
Method Ls+Lr(H)
experimental 0.00018
FE analysis 0.00016 (−11%)

Energies 2019,12, 2431 16 of 20
Figure 16. Locked rotor test setup on 150 kW IM.
The rotor resistance has been measured against the frequency and the result is shown in Figure 17.
The orange line shows the actual experimentally-measured value of the rotor resistance and its increase
with slip frequency due to skin effect. This is compared to the Finite-Element-Analysis (FEA) computed
one (blue line) and the difference can be partially attributed to the temperature variation, since at high
slip higher rates of heating are involved, and it is difficult to predict accurately the rotor temperature
when the rotor resistance is measured.
Figure 17. Rotor resistance variation with frequency: experimentally measured and FEA predictions.
The second level of testing is performed on a high speed dynamometer in order to check the
performance on-load. In Figure 18 left, the measured current and torque are compared to the FEA
predictions near the base speed of 25,000 r/min. Closer matching is observed at lower speeds
(i.e., higher slip), due to the reduction of rotor slot leakage with the increased current. For a given
speed the maximum difference between measured and predicted current is 9%. Figure 18 right shows
similar experimental results near the maximum speed of 50,000 r/min.

Energies 2019,12, 2431 17 of 20
Figure 18.
Comparison of measured and predicted performance near the base speed, 25,000 r/min,
f = 416 Hz
(
left
) and near the maximum speed, 50,000 r/min, f = 833 Hz (
right
) (Reproduced from [
11
]
with permission from IEEE).
4. Conclusions
The induction machine has had a safe place in the global market because of its ease of use, reliable
construction and low cost. The global changes in terms of industry modernization and the tight
international regulation regarding the efficiency are pushing the designers towards new approaches.
In this manuscript, it has been shown how the induction machine, despite having lower rated
efficiency than the permanent magnet or the synchronous machines, can still constitute the optimal
solution for some high speed applications. Needless to be say, this kind of induction machine is not the
low-cost/low-efficiency and easy to use kind that contributed to the success of this type of machine
but it is a new design with high-performance materials and advanced power electronics. Although the
traditional low cost machine is slowly being abandoned, these advanced design are just starting to
make their appearance.
A case study for a high-performance naval application has been analyzed to support these
statements and it has demonstrated that a solution based on an induction machine can outperform
a solution based on permanent magnet machine. Although this result cannot have a general validity in
the global context, it demonstrates that a holistic design that considers all the aspects of an electric
drive must be performed to reach an optimized solution. To this aim, a comprehensive set of tools,
including numerical simulation, finite element analysis, special power electronics must be considered.
Author Contributions:
Investigation, G.B., D.G., L.A., M.G., P.W., S.B., S.P., H.Z., C.Z., C.G.; conceptualization,
H.Z., P.W., C.G.; supervision, C.G., P.W.
Funding:
This research was funded by the Ningbo Science & Technology Beauro under Grant 2017D10031,
2017D10029 and 2018B10002.
Acknowledgments:
The authors would like to thank Cummins Generator Technologies (UK) for their continued
support with high speed machine research, IBC Alloys (USA) for providing and supporting with advanced copper
alloys, JFE Steel (Japan) for their support with low loss electrical steels and Nippon Steel Sumitomo Metal Corp.
(Japan), for providing and supporting with high strength HXT780T electrical steel sheets.
Conflicts of Interest: The authors declare no conflict of interest.
Acronyms
EV Electric Vehicle
PE Power Electronics
IM Induction Machine
PM Permanent Magnet
PMSM Permanent Magnet Synchronous Motor

Energies 2019,12, 2431 18 of 20
RM Reluctance Machine
EAT Electrically-assisted Turbocharging
CVD Chemical Vapour Deposition
WBG Wide Band Gap
CPSR Constant Power Speed Range
DW Distributed Windings
CW Concentrated Windings
FEA Finite Elements Analysis
SVM Space Vector modulation
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