A General Pattern-Based Design Optimization for Asymmetric Spoke-Type Interior PM Machines

Jiahui Huang, Weinong Fu, Shuangxia Niu (), Xing Zhao, Yanding Bi and Zhenyang Qiao
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Jiahui Huang: Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China
Weinong Fu: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
Shuangxia Niu: Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China
Xing Zhao: Department of Electronic Engineering, University of York, York YO10 5DD, UK
Yanding Bi: Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China
Zhenyang Qiao: Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China

Energies, 2022, vol. 15, issue 24, 1-14

Abstract: A novel asymmetric spoke-type interior permanent magnet (AS-IPM) machine is proposed in this paper. It utilizes the magnetic-field-shifting (MFS) effect to improve the torque performance, which achieves a high utilization ratio of both permanent magnet (PM) torque and reluctance torque. In addition, a general pattern of rotor topologies is proposed to represent all possible machine structures. Various rotor structures can be obtained by changing the design parameters of the general pattern. A non-dominated sorting genetic algorithm II (NSGA-II) is adopted to automatically search for optimal rotor configurations. With the aid of the optimization program, an asymmetric spoke-type rotor structure with improved performance is obtained. To showcase the advantages of the proposed machine, the electromagnetic performance is compared between a conventional spoke-type interior permanent magnet (S-IPM) machine and a proposed AS-IPM machine. The finite-element simulation results show that the optimal design of the AS-IPM performs a 7.7% higher output torque ripple due to the MFS effect while the total PM volume remains the same. Meanwhile, the torque ripple of the proposed structure is significantly reduced by 82.1%.

Keywords: finite element analysis (FEA); optimization; permanent magnet machine; torque (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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