No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Measurement of Parameters of BLDC Motor under Various Conditions for Autonomous Vehicles Applications
ResearchGate has not been able to resolve any citations for this publication.
To improve electromagnetic performance, an axial-flux permanent magnet brushless DC motor (AFPMBLDCM) with unequal-thickness arc permanent magnets is proposed in this paper. Firstly, the structure and magnetic circuit of the AFPMBLDCM with unequal-thickness arc permanent magnets were designed. Then, the mathematical models and design method of the main parameters were derived. According to the rated power and rated speed, the main parameters were further designed, and the analytical model was established by using Maxwell 3D. The air-gap flux density, back electromotive force (EMF) and torque under no-load and load conditions were calculated and analyzed to verify the validity of the model and design. Finally, based on a parameter scanning optimization method, the effects of the permanent magnet thickness, pole arc coefficient and permanent magnet radius on cogging torque were analyzed. The optimized parameters of the AFPMBLDCM with unequal-thickness arc permanent magnets were obtained. The results show that the sinusoidal degree of the air-gap magnetic field is improved, and the maximum torque ripple of the AFPMBLDCM is reduced to 2.92%.
This paper investigates the electromagnetic torque by considering back electromagnetic force (back-EMF) trapezoidal degrees of ironless brushless DC (BLDC) motors through the two-dimensional finite element method (2-D FEM). First, the change percentages of the electromagnetic torque with back-EMF trapezoidal degrees, relative to those of PMs without segments, are investigated on the premise of the same back-EMF amplitude. It is found that both PM symmetrically and asymmetrically segmented types influence back-EMF trapezoidal degrees. Second, the corresponding electromagnetic torque, relative to that of PMs without segments, is studied in detail. The results show that the electromagnetic torque can be improved or deteriorated depending on whether the back-EMF trapezoidal degree is lower or higher than that of PMs without segments. Additionally, the electromagnetic torque can easily be improved by increasing the number of PMs’ symmetrical segments. In addition, the electromagnetic torque in PMs with asymmetrical segments is always higher than that of PMs without segments. Finally, two ironless PM BLDC motors with PMs symmetrically segmented into three segments and without segments are manufactured and tested. The experimental results show good agreement with those of the 2-D FEM method. This approach provides significant guidelines to electromagnetic torque improvement without much increase in manufacturing costs and process complexity.
This paper presents a stepwise optimal design (SOD) for an interior permanent magnet synchronous motor (IPMSM) applied to electric vehicle traction, which sequentially utilizes a magnetic equivalent circuit (MEC), finite element analysis (FEA), and a newly proposed optimization algorithm. The design of an IPMSM for the traction motor of a fuel cell electric vehicle (FCEV) is challenging due to its tough requirements, such as high torque density, high efficiency, and low torque ripple; as a result, an iterative trial and error process is required. However, FEA, which is the most generally used analysis technique for electric machine design, has a drawback in terms of the analysis time required when being applied to the entire design process. In this regard, the proposed SOD is presented, which consists of initial, detailed, and optimal design stages, to design an IPMSM with a reasonable design time.
In recent years, there has been an increase in motorization; therefore, the demand for high-efficiency motors in automobiles and aircrafts will further increase. A drone is an aircraft that flies without a human pilot onboard; it has a short flight time because the size of the mounted battery is limited. The magnetic sheet consists of a composite material with magnetic powder and silicone rubber. The eddy current loss and copper loss of the drone motor reduces when the sheet is attached to the coil. This paper reports on the effect of improving the drone motor efficiency by lowering the leakage magnetic flux of the rotor and increasing the heat dissipation in the simulation and the experiment.
In this paper, Multi-Objective Optimization (MOO) techniques namely: Weighted Sum Method (WSM), Multi Objective Genetic Algorithm (MOGA) and Niched Pareto Genetic Algorithm (NPGA) are proposed for the design optimization and analysis of magnetic flux distribution for a slotless permanent magnet Brushless DC (BLDC) motor. The sensitivity analysis is carried out to identify the design variables of BLDC motor which influence the objective function. The objective functions are conflicting in nature (maximization of output torque and minimization of total volume and losses), hence, are optimized simultaneously by means of MOO algorithms. The proposed MOOs account for four kinds of design variables namely: rotor radius, stator/ rotor axial length, magnet thickness and winding thickness simultaneously to maximize the output torque and to reduce the total volume and total power loss. The conventional MOO such as WSM gives single pareto optimal solution. However, the proposed MOGA and NPGA algorithms create accurate and well-distributed pareto front set with few function evaluations. The performances of the three MOOs are evaluated and compared using the four performance metrics namely: Hyper Volume (HV), Generational Distance (GD), Inverted Generational Distance (IGD) and Spread. From the comparison, it is observed that NPGA gives better results. Using the design parameter obtained from NPGA, the magnetic flux distribution analysis of the BLDC motor is carried out to analyze variation of flux distribution in the different parts of the motor. The results thus obtained are compared with those obtained through Partial differential equation and single objective GA optimization. The detailed thermal analysis is also carried out to analyze the thermal behavior at different parts of the machine for different working conditions in the continuous operation mode and hence, the results obtained are compared with single objective GA optimization. The advantages of MOOs in the design optimization of slotless permanent magnet BLDC motor are highlighted.
Quadcopters are unmanned Ariel Vehicle (UAV), generally small helicopter that is lifted and propelled by four rotors. Initially they were used as toys, later they gained importance and recent research on multi-copters have received growing attention for military, agriculture, photography, surveillance, news, sports, search/rescue missions and much more. The widespread use of unmanned vehicles and its growing applications in various domains can be attributed to their ability to operate in inaccessible areas, thus decreasing the human loss in major accidents, and making access easy to dangerous conditions. We have proposed an idea about how quadcopter can be used for the application of fire detecting and extinguishing. The target of this paper is to explain briefly to prepare a quadcopter so that it could be used for firefighting and can help our society.
Aim of this work is the design and realization of a driving system for monitoring and controlling of a BLDC motor with Hall sensors embedded. The realized system is composed by three principal blocks: the control electronic board, the power driving board and the BLDC motor. The first block is based on the STM32 Nucleo development board assembled with the second one, the ST-X-Nucleo-IHM07M1 motor driver expansion board which integrates an L6230 IC driver. The used BLDC motor is the DF45M024053-A2 model provided by Nanotec. The firmware, needed to properly control motor operation, was developed in ARM mbed environment, a development tool available on cloud which allows to send the .bin file (obtained after firmware compilation) directly to the STM32 development board, regarded from operating system, once connected via USB to PC, simply as an external memory. By PC connected via USB with STM32 board, the user can choose the motor rotation direction, set the desired rpm value and, by varying potentiometer value located on board, change the rotation speed. Furthermore, different controls are performed during motor operation such as on PWM duty-cycle value (if it is equal to 100% , then power supply is removed), on temperature value of L6230 IC driver and a control of motor rotation; in this latter case, if BLDC motor is stalled for a time period higher than 3 seconds, then the power supply is interrupted in order to safeguard the motor/system integrity.
Quadrotors are Vertical Take-Off and Landing aerial vehicles with many potential applications ranging from mapping to supporting rescue operations. This paper aims to provide an overview on various works carried out on the quadrotor, from the perspective of control and dynamic modelling. Also in this paper, based on the information summarized from 160 researches available, different control targets and flight missions are analysed and classified, and according to it, a general flight mission map is introduced. In addition, history of advances in development of quadrotors and set-ups proposed when performing experimental researches on quadrotors is presented.
A simple, effective method to realize the integrated control of motoring and regenerative braking of brushless DC motor is proposed in this paper. This method can automatically switch between the two states of motoring and regenerative braking according to the change of load without a braking command and current discontinuity, and can realize steady speed control. For the convenience of analysis, first, the model of the brushless DC motor and the methods of the existing motoring and regenerative braking are briefly explained. Then, the working principle of the proposed method under the two states of motoring and regenerative braking is analyzed. Finally, the effectiveness of the proposed method is verified by experiments.
In this study, Artificial Neural Networks, Extreme Machine Learning and Support Vector Machine (SVM) are used to estimate power consumption of Brushless DC motor in Unmanned Aerial Vehicle (UAV). Durafly 3648 Brushless DC motor of UAV is modelled with the Finite Element Analysis software. Then it is simulated with Ansys-Rmxprt according to pulse degree, speed and battery voltage of the UAV. The training times and Mean Absolute Percentage Errors (MAPE) of the Artificial Intelligence Techniques (AITs) are calculated for motor input power estimation. The best result among the implemented AITs is achieved with the MAPE of 0.269% by the SVM model. Then the graphical user interface (GUI) is developed to easily obtain information about how efficient the battery can be used, and the flight time of UAVs. Thanks to the proposed GUI software, the input power of the motor can be estimated via input parameters without the long-time consuming simulations.
Purpose
The purpose of this paper is to perform an optimal design of a single-phase permanent magnet brushless DC motor (SPBLDCM) by using efficiency of the motor as an objective function. In the design procedure of the motor, a cuckoo search (CS) algorithm is used as an optimization tool.
Design/methodology/approach
For the purpose of this research work, a computer program for optimal design of electrical machines based on the CS optimization has been developed. Based on the design characteristics of SPBLDCM, some of the motor parameters are chosen to be constant and others variable. A comparative analysis of the initial motor model and the CS model based on the value of the objective function, as well as the values of the optimization parameters, is performed and presented.
Findings
Based on the comparative data analysis of both motor models, it can be concluded that the main objective of the optimization is realized, and it is achieved by an improvement of the efficiency of the motor.
Practical implications
The optimal design approach of SPBLDCM presented in this research work can be also implemented on other electrical machines and devices using the same or even other objective functions.
Originality/value
An optimization technique using CS as an optimization tool has been developed and applied in the design procedure of SPBLDCM. According to the results, it can be concluded that the CS algorithm is a suitable tool for design optimization of SPBLDCM and electromagnetic devices in general. The quality of the CS model has been proved through the data analysis of the initial and optimized solution. The quality of the CS solution has been also proved by comparative analysis of the two motor models using FEM as a performance analysis tool.
The intention of this research is to analyze the thermal behavior and estimate the performance of an inner rotor brushless direct current (BLDC) motor with corroded magnets employed in electric vehicle (EV) applications, using SPEED software. High-speed BLDC motors are widely used for vehicle propulsion, and are mechanically coupled with a transaxle at fixed gear ratios. Such high-speed, low-torque motors are very sensitive to changes in speed and very small change will have a high impact on wheel rotation. However, magnet corrosion has an extremely strong influence on the speed of the motor due to diluted flux density. Here, a detailed analysis of how magnetic corrosion affects the speed, torque and performance of the motor is given. EV motors are employed in open environments and are thus affected by moisture and water. The measurement of performance losses has been studied in detail. The thermal behaviors of the various motor parts are analyzed.
Although there exist a number of accurate unmanned aerial vehicle (UAV) thruster models, these models require the precise measurements of several motor and propeller characteristics. This paper presents a simple motor and propeller model that relies solely upon data provided by manufacturers. The model is validated by comparing theoretical motor and propeller behavior to experimental results obtained from thrust tests in a wind tunnel. The objective is to provide an accurate yet simple model to facilitate the selection of appropriate brushless DC motor and propeller combinations for flight applications.
This paper presents a method for the optimal design of a slotless permanent magnet brushless DC (BLDC) motor with surface mounted magnets using an improved bee algorithm (IBA). The characteristics of the motor are expressed as functions of motor geometries. The objective function is a combination of losses, volume and cost to be minimized simultaneously. This method is based on the capability of swarm-based algorithms in finding the optimal solution. One sample case is used to illustrate the performance of the design approach and optimization technique. The IBA has a better performance and speed of convergence compared with bee algorithm (BA). Simulation results show that the proposed method has a very high/efficient performance.
Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
We have applied multiobjective optimal design to a brushless dc wheel motor. The resulting axial-flux permanent-magnet motor has high torque-to-weight ratio and motor efficiency and is suitable for direct-driven wheel applications. Because the disk-type wheel motor is built into the hub of the wheel, no transmission gears or mechanical differentials are necessary and overall efficiency is thereby increased and weight is reduced. The dedicated motor was modeled in magnetic circuits and designed to meet the specifications of an optimization scheme, subject to constraints such as limited space, current density, flux saturation, and driving voltage. In this paper, two different motor configurations of three and four phases are illustrated. Finite-element analyses are then carried out to obtain the electromagnetic, thermal, and modal characteristics of the motor for modification and verification of the preliminary design. The back-electromotive forces of prototypes are examined for control strategies of current driving waveforms.
Multiobjective design optimization and analysis of magnetic flux distribution for slotless permanent magnet brushless DC motor using evolutionary algorithms
- K Chakkarapani
Analysis of Slotted and Slotless Permanent Magnet DC Motor for Drone Applications. Evolution in Electrical and Electronic Engineering
- A Johari
- E Sulaiman