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PIER PIER B PIER C PIER M PIER Letters
2022-10-10
Robust Multi-Objective Optimization for BEESM Based on Improved Climbing Algorithm
By
Naxi Xu,

    Dr. Naxi Xu

    Automotive Engineering Research Institute

    Jiangsu University

    China

    Homepage

Xiaodong Sun,

    Professor Xiaodong Sun

    Automotive Engineering Research Institute

    Jiangsu University

    China

    Homepage

Ke Li,

    Dr. Ke Li

    School of Electrical and Information Engineering

    Jiangsu University

    China

    Homepage

Ming Yao

    Dr. Ming Yao

    School of Automotive and Traffic Engineering

    Jiangsu University

    China

    Homepage

Progress In Electromagnetics Research B, Vol. 97, 1-18, 2022
doi:10.2528/PIERB22080901
Abstract
Robust optimization design of brushless electrically excited synchronous machines (BEESMs) is a problem that has received extensive attention. The increase in finite element calculation cost due to the increase in the number of motor parameters is one of the main problems faced by optimization. In this paper, a robust multi-objective optimization design method of BEESM based on an improved hill-climbing algorithm is proposed. All design parameters are divided into three subspaces according to the sensitivity by the sensitivity analysis method combined with Kendall's rank coefficient, thereby reducing the consumption required for FEM calculation. The screening problem of Pareto frontier solutions is solved by an improved hill-climbing algorithm. The candidate points to be optimized are screened through the improved climbing algorithm, and only the candidate points located on the Pareto frontier will be optimized, which ensures the high performance of the candidate points. Based on the noise problems that may occur in actual production and processing, the candidate points are robustly analyzed, and the optimal design is screened out. The robust optimization design method proposed in this paper can reduce the computational cost and improve the robustness of the motor based on improving the performance of the motor.
Citation
Naxi Xu, Xiaodong Sun, Ke Li, and Ming Yao, "Robust Multi-Objective Optimization for BEESM Based on Improved Climbing Algorithm," Progress In Electromagnetics Research B, Vol. 97, 1-18, 2022.
doi:10.2528/PIERB22080901
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