Multiobjective optimization method based on a genetic algorithm for switched reluctance motor design

被引：80
|
作者：
Mirzaeian, B [1 ]
Moallem, M
Tahani, V
Lucas, C
机构：
[1] Isfahan Univ Technol, Dept Elect Engn, Esfahan 84154, Iran
[2] Univ Tehran, Dept Elect Engn, Tehran, Iran
来源：
IEEE TRANSACTIONS ON MAGNETICS | 2002年 / 38卷 / 03期
关键词：
multiobjective optimization; SRM design;
D O I：
10.1109/20.999126
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：
In this paper, a novel multiobjective optimization method based on a genetic-fuzzy algorithm (GFA) is proposed. The new GFA method is used for optimal design of a switched reluctance motor (SRM) with two objective functions: high efficiency and low torque ripple. The results of the optimal design for an 8/6, four-phase, 4 kW, 250 V, 1500 rpm SRM show improvement in both efficiency and torque ripple of the motor.
引用
收藏
页码：1524 / 1527
页数：4
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