基于改进鲸鱼算法的永磁同步伺服电机多目标优化设计  

Multi-objective Optimization Design of Permanent Magnet synchronous Servo Motor Based on Improved Whale Algorithm

作　　者：张宏 周大伟 陆丽[2] 康小东 ZAHNG Hong;ZHOU Dawei;LU li;KANG Xiaodong(Shanghai Lingang Science and Technology School,Shanghai 201306,China;School of Electrical Engineering,Shanghai Dianji University,Shanghai 201306,China)

机构地区：[1]上海电机学院附属科技学校(上海市临港科技学校),上海201306 [2]上海电机学院,上海201306

出　　处：《微电机》2024年第12期18-23,共6页Micromotors

基　　金：国家自然科学基金项目(42176194)。

摘　　要：为了提升通用伺服电机的平均转矩以及降低其齿槽转矩峰峰值和空载反电动势总谐波畸变率(Total Harmonic Distortion,THD),提出一种基于改进鲸鱼算法的永磁同步伺服电机的多目标优化设计的方法。通过基于改进BP神经网络建模和改进鲸鱼算法多目标优化的流程对伺服电机进行优化设计。利用有限元软件对比分析了优化前后电机的电磁性能,平均转矩提升了9.67%、齿槽转矩峰峰值降低了37%、空载反电势谐波畸变率降低了39%,证明了所提出的优化设计方法的准确性及高效性。In order to improve the average torque of general servo motors and reduce their peak slot torque and total harmonic distortion(THD)of no-load back electromotive force,a multi-objective optimization design method based on the improved whale algorithm for permanent magnet synchronous servo motors was proposed.The servo motor was optimized based on improved BP neural network modeling and improved whale algorithm multi-objective optimization process.The electromagnetic properties of the motor before and after optimization were compared and analyzed by finite element software.The average torque is increased by 9.67%,the peak value of tooth groove torque is reduced by 37%,and the THD of no-load back electromotive force is reduced by 39%,which proves the accuracy and high efficiency of the proposed optimization design method.

关 键 词：永磁同步电机 BP神经网络 鲸鱼算法 优化设计 

分 类 号：TM351[电气工程—电机] TM341