摘要
为了解决传统双段Halbach轴向永磁联轴器转矩性能较低的问题,提出一种新型双段Halbach轴向永磁联轴器,并以转矩性能为优化目标进行多目标优化。采用3D有限元法对新型双段HAMC进行建模,主要分析新型阵列的每个关键参数对新型双段HAMC转矩和转矩密度的影响。通过参数分析,发现转矩和转矩密度不能同时达到最优,需要对提出的新型双段HAMC进行多目标优化,则建立转矩和转矩密度的多项式回归模型和非支配排序遗传算法Ⅱ,以获得转矩和转矩密度的极大值。优化之后的新型双段HAMC,转矩提高了5.60%,转矩密度提高了4.19%。通过气隙磁密与转矩性能分析,进一步验证了新型结构的合理性和多目标优化方法的有效性。
In order to solve the problem of low torque performance of the axial magnetic couplings with traditional two-segment Halbach array(HAMC),the axial magnetic couplings with two-segment Halbach array is proposed,and the multi-objective optimization algorithm is used to improve torque performance of the two-segment HAMC.The two-segment HAMC was modeled by the 3D finite element method,and the influence of each key parameter of the array on the torque and torque density of the two-segment HAMC was mainly analyzed.Through parametric study,it is found that torque and torque density can not reach the optimal simultaneously.Then the proposed two-segment HAMC was optimized using the polynomial regression model of torque and torque density and the non-dominated sorting genetic algorithm II(NSGA II)to obtain both relative maximum of torque and torque density.The output torque of the optimized two-segment HAMC was increased by 5.60%and the torque density was increased by 4.19%.The rationality of the structure and the effectiveness of the multi-objective optimization algorithm are further verified through the analysis of air gap magnetic density and torque performance.
作者
刘晓
肖罗鹏
崔鹤松
黄守道
LIU Xiao;XIAO Luo-peng;CUI He-song;HUANG Shou-dao(College of Electrical and Information Engineering,Hunan University,Changsha 410082,China;Machinery Industry Beijing Electrotechnical Institute of Economic Research,Beijing 100070,China)
出处
《电机与控制学报》
EI
CSCD
北大核心
2021年第6期63-71,共9页
Electric Machines and Control
基金
国家自然科学基金(51877074)
湖南省杰出青年科学基金(2020JJ2005)。
关键词
新型双段Halbach轴向永磁联轴器
3D有限元法
多项式回归模型
多目标优化
非支配排序遗传算法Ⅱ
axial magnetic couplings with two-segment Halbach array
3D finite element method
polynomial regression model
multi-objective optimization
non-dominated sorting genetic algorithmⅡ