Surrogate Assisted Contour Algorithm for Optimal Design of Interior Permanent Magnet Synchronous Motor for Electric Vehicles

被引：0
作者：
Wi, Chang-Hyun [1 ]
Lim, Dong-Kuk [1 ]
机构：
[1] Univ Ulsan, Dept Elect Elect & Comp Engn, Ulsan, South Korea
来源：
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY | 2022年 / 17卷 / 06期
关键词：
Electric vehicles; Interior permanent magnet synchronous motor; Multimodal; Optimal design; Surrogate model;
D O I：
10.1007/s42835-022-01176-2
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this paper, to solve the multimodal optimization problem of electric motors, the surrogate assisted contour algorithm (SACA) is proposed. The surrogate models of SACA are generated and updated with fewer number of function calls by using the added samples of the proposed algorithm. By utilizing the contour region, SACA efficiently adds samples to generate surrogate model. The outstanding performance of the proposed algorithm is verified by comparison with niching genetic algorithm at two mathematical test functions. Finally, the SACA is applied to the optimal design of the interior permanent magnet synchronous motor for electric vehicles.
引用
收藏
页码：3297 / 3303
页数：7
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