Multi-objective Optimization Design of Inset-surface Permanent Magnet Machine Considering Deterministic and Robust Performances

作     者：Gaohong Xu Zexin Jia Wenxiang Zhao Qian Chen Guohai Liu 

作者机构：School of Electrical and Information EngineeringJiangsu UniversityZhenjiang 212013China 

出 版 物：《Chinese Journal of Electrical Engineering》 (中国电气工程学报（英文）)

年 卷 期：2021年第7卷第3期

页      面：73-87页

核心收录：

学科分类：080801[工学-电机与电器] 0808[工学-电气工程] 08[工学] 

基　　金：Supported by the National Natural Science Foundation of China(51907080) by the Natural Science Foundation of Jiangsu Province(BK20190848) by the China Postdoctoral Science Foundation(2019M661746) 

主　　题：Multi-objective optimization design robust design Design for Six Sigma Monte Carlo simulation barebones multi-objective particle swarm optimization 

摘      要：The inset-surface permanent magnet(ISPM)machine can achieve the desired electromagnetic performance according to the traditional deterministic ***,the reliability and quality of the machine may be affected by the essential manufacturing tolerances and unavoidable noise factors in mass *** address this weakness,a comprehensive multi-objective optimization design method is proposed,in which robust optimization is performed after the deterministic *** response surface method is first adopted to establish the optimization objective ***,the sample points are obtained via Monte Carlo simulation considering the design-variable *** Design for Six Sigma approach is adopted to ensure the robustness of the design ***,the barebones multi-objective particle swarm optimization algorithm is used to obtain a compromise solution.A prototype is manufactured to evaluate the effectiveness of the proposed *** to the finite-element analysis and experimental tests,the electromagnetic performance and reliability of the machine are significantly enhanced with the proposed method.