|
|
|
| Multi-objective optimization of electric power steering motor based on genetic algorithm |
| Huang Hui, Wu Zheng, Zou Anan, Zhao Runquan |
| Intelligent Manufacturing Department of Wuyi University, Jiangmen, Guangdong 529020 |
|
|
|
|
Abstract This paper mainly uses genetic algorithm to solve the multi-objective optimization problem of the motor. The main goal is to optimize the efficiency and noise of the motor, so that the designed motor is more in line with the needs of the current market. Taking the cogging torque and efficiency of the motor as the optimization goal, formulating reasonable optimization variables, and designing corresponding constraints, establish a multi-objective optimization model. Using Matlab genetic algorithm toolbox and Ansoft's electromagnetic module for coupling simulation, an electric vehicle fan is optimized for optimal design. Finally, Maxwell's two-dimensional electromagnetic field simulation and transient field simulation show that the optimization results can effectively change the cogging torque and efficiency of the motor.
|
|
Received: 20 July 2018
Published: 18 February 2019
|
|
|
|
| Cite this article: |
|
Huang Hui,Wu Zheng,Zou Anan等. Multi-objective optimization of electric power steering motor based on genetic algorithm[J]. Electrical Engineering, 2019, 20(2): 48-52.
|
|
|
|
| URL: |
|
http://dqjs.cesmedia.cn/EN/Y2019/V20/I2/48
|
[1] 丁旭炜, 林瑞金. Ansoft软件在无刷永磁直流电动机优化设计中的应用[J]. 机电技术, 2010(2): 130-132.
[2] 余莉, 刘合祥, 胡虔生. 高速永磁无刷直流电动机优化设计[J]. 机械制造与自动化, 2009(6): 117-119.
[3] 钱强. 永磁无刷直流电动机优化设计和转矩脉动抑制[D]. 太原: 太原理工大学, 2010: 2-51.
[4] 王大为, 徐洋波, 臧云峰, 等. 电动汽车大功率快速充电机的全数字一体化设计[J]. 电气技术, 2015, 16(2): 95-98.
[5] 张科, 史祥翠. 永磁无刷直流电机齿槽转矩削弱方法[J]. 煤矿机电, 2009(6): 38-39.
[6] 陈征, 肖湘宁, 路欣怡, 等. 含光伏发电系统的电动汽车充电站多目标容量优化配置方法[J]. 电工技术学报, 2013, 28(6): 238-248.
[7] 陈世坤. 电机设计[M]. 北京: 机械工业出版社, 1982.
[8] 龙永文. 基于遗传算法的永磁无刷直流电动机优化设计研究[D]. 南京: 东南大学, 2005: 1-11.
[9] Bianch N, Bolognai S.Brushless DC motor design: an opimization procedure based on genetic algorithms[C]// Proceedings of the 41st IEEE Corerence on Decision and Cotrol Las Vegas, Nevada USA, 1997: 16-18.
[10] 李振波, 张琛. 遗传算法在超微电动机参数优化设计中的应用[J]. 上海交通大学学报, 1999(10): 1288-1291. |
|
|
|
2019, Vol. 20 
