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基于响应面法的轴向磁场永磁记忆电机多目标优化设计
引用本文:曹永娟,冯亮亮.基于响应面法的轴向磁场永磁记忆电机多目标优化设计[J].南京信息工程大学学报,2021,13(5):620-627.
作者姓名:曹永娟  冯亮亮
作者单位:南京信息工程大学 自动化学院, 南京, 210044;南京信息工程大学 大气环境与装备技术协同创新中心, 南京, 210044
基金项目:国家自然科学基金(51507082)
摘    要:针对新型轴向磁场永磁记忆电机的结构优化问题,采用响应面法对电机进行优化设计.通过电磁性能方程和正交实验,初步分析了电机关键参数的影响.为了有效地设计该电机,初步选取了软磁占比、转子极数、气隙长度三个影响因素作为正交试验的设计因子,再采用响应面优化方法,将所选的感应电动势、感应电动势的总谐波畸变率和齿槽转矩三个性能作为优化目标.使用有限元软件Ansoft Maxwell和响应面设计软件Design Expert建立响应面实验,得到电机的不同影响因素组合模型下的仿真参数和拟合曲线.本文结合不同的优化方法,以满足具体的设计要求,理论分析和实验结果都验证了所提出的电机和优化方法的可行性和有效性.通过对试验数据分析对比,得出了优化方案,结果表明:优化设计之后的电机在缩减了永磁材料成本的情况下,还保证了比原电机更优的感应电动势、更小的感应电动势总谐波畸变率和齿槽转矩.

关 键 词:记忆电机  响应面法  多目标优化  有限元分析
收稿时间:2020/9/14 0:00:00

Multi-objective optimization design of axial-flux permanent magnet memory motor based on response surface method
CAO Yongjuan,FENG Liangliang.Multi-objective optimization design of axial-flux permanent magnet memory motor based on response surface method[J].Journal of Nanjing University of Information Science & Technology,2021,13(5):620-627.
Authors:CAO Yongjuan  FENG Liangliang
Affiliation:School of Automation, Nanjing University of Information Science & Technology, Nanjing 210044;Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing 210044
Abstract:Here, the Response Surface Method (RSM) is used to optimize the structure of a new Axial-Flux Permanent Magnet Memory Motor (AFPMMM) proposed in this paper.Main influencing parameters of the motor are preliminarily determined based on analysis of the electromagnetic performance equation and Orthogonal Experiment (OE), among which, three factors including soft magnetic ratio, number of rotor poles and air gap length, are selected as the design factors of OE.Then Electromotive Force(EMF), Total Harmonic Distortion (THD) and cogging torque are determined as the optimization factors, and the RSM is used as the optimization method.The Response Surface (RS) experiment is established by using the finite element software Ansoft Maxwell and the RS design software Design Expert.The simulation parameters and fitting curves of the motor under the combination model of different design factors are obtained.Different optimization methods are combined to meet the specific design requirements in this paper.Theoretical analysis and experimental results verify the feasibility and effectiveness of the proposed motor and optimization method.Then the optimization scheme is obtained through comparative analysis of the test data.The results show that the optimized motor not only reduces the cost of permanent magnet material, but also ensures good EMF and small axial force fluctuation.
Keywords:memory motor  response surface method(RSM)  multi-objective optimization  finite element analysis(FEA)
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