基于黑洞多目标进化算法的永磁直线同步电机优化设计  

Optimization of a tubular coreless linear PM synchronous machine based on multi-objective blackhole evolutionary algorithm

作　　者：吴涛 商慧丽[1,2] 张煜葵 周颖 WU Tao;SHANG Hui-li;ZHANG Yu-kui;ZHOU Ying(School of Automation,China University of Geosciences(Wuhan),Wuhan 430074,China;Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems,China University of Geosciences(Wuhan),Wuhan 430074,China)

机构地区：[1]中国地质大学(武汉)自动化学院,武汉430074 [2]中国地质大学(武汉)复杂系统先进控制与智能自动化湖北省重点实验室,武汉430074

出　　处：《控制与决策》2022年第6期1567-1572,共6页Control and Decision

基　　金：国家自然科学基金面上项目(62073305);湖北省自然科学基金面上项目(2020CFB556)。

摘　　要：应用一种改进的黑洞多目标进化算法(MOBH),实现对圆筒型无槽无铁芯直线永磁同步电机(LPMSM)的多目标优化设计.黑洞进化算法在不同Pareto区域的收敛速度、种群多样性、种群收敛性和亚种群获取等方面具有良好的性能.在分析无槽无铁芯圆筒直线电机的电磁解析模型和MOBH算法基础上,建立电机推力、推力体积比、铜损(效率)多目标优化模型,为3个目标对应的Pareto占优解空间提供更加全面和直观的最优解空间.可以根据应用需求和目标函数实际物理值分布范围来综合选取最终最优解,探讨单一目标函数情况下Pareto占优解分布与主要设计变量的关系.最后通过样机实验验证主要设计指标的计算准确性.In this paper, an improved multi-?objective black?ho le(MOBH) evolutionary algorithm is applied to optimization of a tubular linear permanent magnet synchronous motor(LPMSM). The MOBH evolutionary algorithm has good performance in convergence rate, population diversity, population convergence and subspecies acquisition in different Pareto regions. Based on the motor model and introduction of the MOBH algorithm, a multi-?objective optimization model regarding to thrust, ratio between thrust and volume and copper loss(efficiency) is established. The Pareto dominated solution space corresponding to the three objectives provides a more comprehensive and intuitive optimal solution space. The final optimal solution can be comprehensively selected according to the application requirements and the actual physical value distribution range. The relationship between the distribution of Pareto dominant solutions and the main design variables under a single objective condition is discussed. Finally, the accuracy of the calculation of the main design indexes is verified by the prototype experiment.

关 键 词：直线永磁电机 多目标算法 多目标优化 黑洞算法 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]