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.
黄辉, 吴正, 邹安安, 赵润权. 基于遗传算法的汽车EPS电动助力转向电动机多目标优化[J]. 电气技术, 2019, 20(2): 48-52.
Huang Hui, Wu Zheng, Zou Anan, Zhao Runquan. Multi-objective optimization of electric power steering motor based on genetic algorithm. Electrical Engineering, 2019, 20(2): 48-52.
2019, Vol. 20 
