基于解析-遗传算法的永磁电机齿槽转矩优化

Cogging Torque Optimization of Permanent Magnet Motor Based on Analytic Genetic Algorithm

研究了一种基于解析算法的遗传优化算法优化电机,分别以不同的电机参数作为优化变量实现对齿槽转矩的定量分析优化,并求得电机参数的最佳取值。通过直接解析法建立表贴式永磁电机模型,利用麦克斯韦应力张量法建立了齿槽转矩的表达式,选取极弧系数和定子槽口宽度作为优化变量并以齿槽转矩的幅值作为优化的目标,采用遗传算法优化电机的齿槽转矩,得到最优参数组合。将优化后的齿槽转矩和原电机模型的齿槽转矩进行比较,结果显示,优化后电机的齿槽转矩显著降低。该结论表明采用遗传算法得到电机参数最优解从而优化电机性能是可行的。

A genetic optimization algorithm based on analytic algorithm was proposed to optimize the cogging torque.Different motor parameters could be used as optimization variables to realize quantitative analysis and optimization of cogging torque,and the optimal value of motor parameters could be obtained.On the basis of the motor model established by direct analytic method in the table-mounted permanent magnet motor,by using Maxwell's stress tensor method,the expression of cogging torque was established,the polar arc coefficient and the width of the stator slot were chosen as the optimization variables,the amplitude of cogging torque was used as the optimization target,and genetic algorithm was used to optimize the cogging torque of the motor.The optimal parameter combination was obtained.After comparing the optimized cogging torque with the cogging torque of the original motor model,the results showed that the cogging torque of the motor was significantly reduced after optimization.The conclusion showed that it was feasible to get the optimal solution of motor parameters by using genetic algorithm to optimize motor performance.