摘要
本文采用遗传算法来解决电动机的多目标优化问题,主要目标是优化电动机的效率和噪声,让设计出来的电动机更加符合当前市场的需求。以电动机的齿槽转矩和效率为优化目标,拟定合理的优化变量、并设计相应的约束条件,建立多目标优化模型。使用Matlab遗传算法工具箱和Ansoft的电磁模块进行耦合仿真,以一款电动汽车的电动助力转向电动机为优化对象进行优化设计。最后通过Maxwell二维电磁场仿真、瞬态场仿真表明,优化结果能够有效改变电动机齿槽转矩和效率。
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.
作者
黄辉
吴正
邹安安
赵润权
Huang Hui;Wu Zheng;Zou Anan;Zhao Runquan(Intelligent Manufacturing Department of Wuyi University,Jiangmen,Guangdong 529020)
出处
《电气技术》
2019年第2期48-52,共5页
Electrical Engineering
基金
广东省科技计划项目--EPS汽车电动助力转向电机研发(2016B090918102)
关键词
电动助力转向电动机
遗传算法
多目标优化
electric power steering motor
genetic algorithm
multi-objective optimization
