Design Optimization of a Novel Axial Flux Ferrite Magnet Assisted Synchronous Reluctance Motor

Author(s):  
Md Tawhid Bin Tarek ◽  
Yilmaz Sozer
2021 ◽  
Vol 35 (11) ◽  
pp. 1372-1373
Author(s):  
A.A. Arkadan ◽  
N. Al Aawar

Multi-objective design optimization environments are used for electric vehicles and other traction applications to arrive at efficient motor drives. Typically, the environment includes characterization modules that involve the use of Electromagnetic Finite Element and State-Space models that require large number of iterations and computational time. This work proposes the utilization of a Taguchi orthogonal arrays method in conjunction with a Particle Swarm Optimization search algorithm to reduce computational time needed in the design optimization of electric motors for traction applications. The effectiveness of the Taguchi method in conjunction with the optimization environment is demonstrated in a case study involving a prototype of a Synchronous Reluctance Motor drive system.


2019 ◽  
Vol 55 (6) ◽  
pp. 1-4
Author(s):  
Jae-Kwang Lee ◽  
Dong-Hoon Jung ◽  
Ki-Doek Lee ◽  
Wonjoon Jin ◽  
Geunho Lee ◽  
...  

Author(s):  
Andrea Credo ◽  
Andrea Cristofari ◽  
Stefano Lucidi ◽  
Francesco Rinaldi ◽  
Francesco Romito ◽  
...  

Author(s):  
Nagarajan V.S. ◽  
Balaji Mahadevan ◽  
Kamaraj V. ◽  
Arumugam R. ◽  
Ganesh Nagarajan ◽  
...  

Purpose The purpose of this paper is performance enhancement of ferrite-assisted synchronous reluctance (FASR) motor using multi-objective differential evolution (MODE) algorithm, considering the significant geometric design parameters. Design/methodology/approach This work illustrates the optimization of FASR motor using MODE algorithm to enhance the performance of the motor considering barrier angular positions, magnet height, magnet axial length, flux barrier angles of the rotor and air gap length. In the optimization routine to determine the performance parameters, generalized regression neural network-based interpolation is used. The results of MODE are validated with multi-objective particle swarm optimization algorithm and multi-objective genetic algorithm. Findings The design optimization procedure developed in this work for FASR motor aims at achieving multiple objectives, namely, average torque, torque ripple and efficiency. With multiple objectives, it is essential to give the designer the tradeoff between different objectives so as to arrive at the best design suitable for the application. The results obtained in this work justify the application of the MODE approach for FASR motor to determine the various feasible solutions within the bounds of the design. Research limitations/implications Analysis, design and optimization of synchronous reluctance motor has been explored in detail to establish its potential for variable speed applications. In recent years, the focus is toward the electromagnetic design of hybrid configurations such as FASR motor. It is in this preview this work aims to achieve optimal design of FASR motor using multi-objective optimization approach. Practical/implications The results of this work will supplement and encourage the application of FASR motor as a viable alternate for variable speed drive applications. In addition, the application of MODE to arrive at better design solutions is demonstrated. Originality/value The approach presented in this work focuses on obtaining enhanced design of FASR motor considering average torque, torque ripple and efficiency as performance measures. The posteriori analysis of optimization provides an insight into the choice of parameters involved and their effects on the design of FASR motor. The efficacy of the optimization routine is justified in comparison with other multi-objective algorithms.


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