Fa-SynRM Multi-Objective Optimization Design Based on Genetic Algorithm and Taguchi Method

被引：0
|
作者：
Dong Y. [1 ]
Guo J. [1 ]
Jing K. [1 ]
Sun H. [1 ]
机构：
[1] School of Control Science and Engineering, Hebei University of Technology, Tianjin
来源：
Diangong Jishu Xuebao/Transactions of China Electrotechnical Society | 2019年 / 34卷 / 24期
关键词：
Ferrite-assisted synchronous reluctance motor; Genetic algorithm; Power factor; Taguchi method; Torque ripple;
D O I：
10.19595/j.cnki.1000-6753.tces.181536
中图分类号：
学科分类号：
摘要：
Firstly, the paper analyzed the mathematical model of ferrite-assisted synchronous reluctance motor, and used the equivalent magnetic circuit method to analyze the physical model of the motor, so as to obtain the expression of the relationship between salient pole ratio and motor structural parameters. Then using the power factor as the main objective function, the genetic algorithm was used to optimize the design of the motor parameters, such as the length and width of the ferrite, and the current angle. After that, through the combination of Taguchi method and finite element method, the motor parameters were continuously optimized, and the optimal combination of relevant parameters was obtained. The motor power factor was further improved, the torque ripple and the ferrite volume were reduced. Finally, simulations verified the rationality of the optimization process, the accuracy of the optimization results, and the influence of the split ratio coefficient on the performance. The method could reduce the computational difficulty and cost, effectively improves the power factor, and reduces torque ripple and ferrite volume. © 2019, Electrical Technology Press Co. Ltd. All right reserved.
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页码：5059 / 5069
页数：10
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