永磁无刷直流空心轴电机定子槽参数减振优化

为了保证永磁无刷直流空心轴电机的输出性能和抑制电磁振动,提出了一种基于非线性多元回归的修正代理模型优化方法.首先,通过AE(Audze-Elglajs)准则确定最优空间填充抽样,并采用核主成分分析(Kernel Principal Components Analysis,KPCA)算法筛选出4个主要变量用于构建代理模型;其次,采用非线性多元回归构建代理模型,决定系数R²值均大于0.9,验证了代理模型的精度;最后,采用鲁棒多目标遗传算法求解代理模型,获得了最优定子槽参数.结果表明,通过优化定子槽参数,电机平均转矩降低了1.3%,不影响输出性能,电机空载、额定负载时最大振动加速度分别降低19%和34.5%,有效地降低了电磁振动,验证了优化方法的有效性和可靠性.

Optimization of stator slot parameters for vibration reduction of hollow shafted permanent magnet brushless DC motor

To ensure the output performance and suppress electromagnetic vibration of a Hollow Shafted Permanent Magnet Brushless DC Motor (HSPMBLDCM),a surrogate-assisted model optimization method based on nonlinear multiple regression is proposed.First,the optimal space-filling sampling was determined by the Audze-Eglajs (AE) criterion,and four main variables were selected by the Kernel Principal Components Analysis (KPCA) algorithm to construct the surrogate model.Next,the surrogate model was constructed using nonlinear multiple regression,and the R² values of the coefficients of determination were all greater than 0.9,which verified the accuracy of the surrogate model.Finally,the Robust Multiobjective Optimization Evolutionary Algorithms (RMOEA) were used to solve the surrogate model,and the optimal stator slot parameters were obtained.The results show that by optimizing the stator slot parameters,the average torque of the motor is reduced by 1.3%,which does not affect the output performance,and the maximum vibration acceleration of the motor at no load and rated load is reduced by 19% and 34.5%,respectively,which effectively reduces the electromagnetic vibration and proves the effectiveness and reliability of the optimization method.It provides an alternative means for motor vibration damping design optimization with practical significance.