A Genetic-Taguchi Global Design Optimization Strategy for Surface-Mounted PM Machine

被引：0
|
作者：
Dai, Litao [1 ]
Gao, Jian [1 ]
Zhang, Wenjuan [2 ]
Huang, Shoudao [1 ]
机构：
[1] Hunan Univ, Coll Elect & Informat Engn, Changsha, Peoples R China
[2] Changsha Univ, Coll Elect & Elect Engn, Changsha, Peoples R China
来源：
2019 22ND INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS 2019) | 2019年
关键词：
Surface-mounted permanent magnet (PM) machine; design optimization; Taguchi method; genetic algorithm (GA); PERMANENT-MAGNET MACHINE;
D O I：
暂无
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：
This paper presents a novel step-optimization strategy for the multi-objective tradeoffs in surface-mounted permanent magnet synchronous machines (SPMSMs), i.e. genetic-Taguchi global optimization (GTGO). Specifically, the electromagnetic performances are accurately predicted by sub-domain (SD) model, and the objective functions of cost, efficiency and total harmonic distortion (THD) of back electromotive force (emf) are solved by genetic algorithm (GA) based on constraint conditions. Next, the Taguchi method optimizes local variables which are difficult to model by SD model, such as magnetic pole shift, magnet eccentricity and segmentation. The last, the effectiveness of proposed GTGO has been verified by finite-element analysis (FEA).
引用
收藏
页码：2271 / 2276
页数：6
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