Optimization Design of a Dual-Rotor Axial-Flux Permanent Magnet Vernier Machine based on Genetic Algorithm

被引：0

作者：

Yang, Kuang ^{[1
]}

Zhao, Fei ^{[1
]}

Wang, Quanlin ^{[1
]}

Lin, Hai ^{[2
]}

机构：

[1] Harbin Inst Technol Shenzhen, Sch Mech Engn & Automat, Shenzhen, Peoples R China

[2] Changan Univ, Sch Elect & Control Engn, Xian, Peoples R China

来源：

2019 22ND INTERNATIONAL CONFERENCE ON ELECTRICAL MACHINES AND SYSTEMS (ICEMS 2019) | 2019年

基金：

中国国家自然科学基金;

关键词：

axial-flux machine; genetic algorithm; power factor; stator tooth optimization; torque density; LEAKAGE;

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 proposes an optimal design to improve the torque and power factor of a dual-rotor axial-flux aligned permanent magnet vernier machine (DR-AFAPMVM) according to the results of two dimensional finite element analysis (2D-FEA). The stator tooth-slot structure in a vernier machine has the flux modulation effect and determines the main flux path, therefore, the optimal design of stator is an effective choice to achieve larger torque and power factor. Genetic algorithm (GA) is utilized as the basic optimization algorithm to obtain the final optimal result, which is further verified by FEA.

引用

页码：826 / 830

页数：5

共 16 条

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