摘要
建立了外转子永磁力矩电机的有限元分析模型,并以转矩密度和转矩波动为优化目标,建立了电机多目标优化问题的数学模型。通过电机结构参数样本空间设计,利用支持向量机(support vector machine,SVM)对电机进行非线性回归建模,利用带精英策略的快速非支配排序遗传算法(nondominated sorting genetic algorithm Ⅱ,NSGA-Ⅱ)进行参数寻优。通过有限元仿真验证,NSGA-Ⅱ与变权数加权的网格搜索法寻优的对比结果,表明了NSGA-Ⅱ寻优的准确性、有效性及全局性。
Finite element model(FEM)of external-rotor permanent magnet torque motor was presented.The mathe-matical model of multi-objective optimization problem was established based on torque density and torque ripple.Nonlinear regression modeling of the motor was set up,which is based on the sample space of motor structure parameters,and the parameter optimization of the motor is based on the nondominated sorting genetic algorithm II(NSGA-II).After the finite element simulation,the results of NSGA-II and variable weighted grid search method were compared,which shows that the NSGA-II search is accurate,effective and global.
作者
李振
陈进华
张驰
刘亮
Li Zhen;Chen Jin-hua;Zhang Chi;Liu Liang(Shanghai University,Shanghai 200072,China;Laboratory of Robotics and Intelligent Manufacturing Equipment Technology,Ningbo Institute of Materials Technology and Engineering,CAS,Ningbo 315201,China)
出处
《微特电机》
2018年第11期46-50,共5页
Small & Special Electrical Machines
基金
国家自然科学基金-浙江两化融合联合基金(U1509202)
宁波市重大专项(2017B10014)
浙江省基础公益研究计划(LGG18E070007)
关键词
外转子永磁力矩电机
多目标优化
转矩密度
转矩波动
支持向量机
带精英策略的快速非支配排序遗传算法
external-rotor permanent magnet torque motor
multi-objective optimazation
torque density
torque ripple
support vector machines(SVM)
improved non-dominated sorting genetic algorithm(NSGA-域)
