基于改进粒子群优化算法的外转子永磁同步电机的多目标优化设计  

Multi-Objective Optimization Design of External Rotor Permanent Magnet Synchronous Motor Based on Improved Particle Swarm Optimization Algorithm

作　　者：乔路宽 张炳义[1] 李岩[1] 冯桂宏[1] QIAO Lukuan;ZHANG Bingyi;LI Yan;FENG Guihong(School of Electrical and Engineering,Shenyang University of Technology,Shenyang 110870,China)

机构地区：[1]沈阳工业大学电气工程学院,辽宁沈阳110870

出　　处：《电机与控制应用》2023年第3期81-87,94,共8页Electric machines & control application

摘　　要：为降低外转子永磁同步电机(ERPMSM)作为皮带输送机驱动电机时的永磁体成本并提高电机性能,提出基于响应面法(RSM)和改进多目标粒子群优化(IMOPSO)算法的优化设计方法。在建立电机基本结构的基础上,将永磁体尺寸、气隙长度、槽口宽度等作为优化参数,将永磁体成本、输出转矩、转矩脉动等作为优化目标。通过参数灵敏度分析筛选出显著参数,基于RSM结合有限元仿真建立样本空间,并拟合出优化目标和优化参数的函数关系,通过IMOPSO寻优。最后对比优化前后的方案结果,所提多目标优化算法准确可靠且具有更好的收敛性和多样性,能够在降低永磁体成本的同时优化电机的性能。In order to reduce the permanent magnet cost and improve the performance of external rotor permanent magnet synchronous motor(ERPMSM) for belt conveyor, an optimization method based on response surface methodology(RSM) and improved multi-objective particle swarm optimization(IMOPSO) algorithm is proposed. Based on the establishment of the motor’s basic structure, the permanent magnet size, the air gap length and the slot width are taken as the optimization parameters, and the permanent magnet cost, the output torque, and the torque ripple are taken as the optimization objectives. The significant parameters are screened by sensitivity analysis. The sample space is established based on RSM and finite element simulation, the function relationship between optimization objectives and parameters is fitted. The scheme is optimized by IMOPSO. Finally, the results of comparison of the schemes before and after optimization show that the multi-objective optimization algorithm is accurate and reliable, it has better convergence and diversity, which can optimize the performance of the motor while reducing the cost of permanent magnet simultaneously.

关 键 词：外转子永磁同步电机 响应面法 改进多目标粒子群优化 

分 类 号：TM351[电气工程—电机]