基于表面响应模型法的城市轨道交通用直线感应电机次级结构优化

中国机械工程 ›› 2010, Vol. 21 ›› Issue (15): 1825-1830.

基于表面响应模型法的城市轨道交通用直线感应电机次级结构优化

王立强;卢琴芬;叶云岳

浙江大学,杭州,310027

出版日期:2010-08-10 发布日期:2010-09-19
基金资助:
国家自然科学基金资助项目(50607016)
National Natural Science Foundation of China（No. 50607016）

Optimization of Secondary Structure of Linear Induction Motor in Urban Rail Transit Based on Response Surface Methodology

Wang Liqiang;Lu Qinfen;Ye Yunyue

Zhejiang University, Hangzhou, 310027

Online:2010-08-10 Published:2010-09-19
Supported by:
National Natural Science Foundation of China（No. 50607016）

摘要/Abstract

摘要：

建立了城市轨道交通用单边直线感应电机（SLIM）的3D有限元模型,通过次级结构参数化分析研究了次级结构参数对电机启动力特性的影响,找出了两个对启动力特性影响较大的参数,即次级铝板厚度与次级宽度。建立了仅需少量3D参数化有限元的分析结果,以及基于神经网络的SLIM启动力特性的表面响应模型。基于SLIM的表面响应模型,以次级铝板厚度与次级宽度为设计变量,以获得最大启动推力及最小法向力为优化目标,利用多目标遗传算法对SLIM次级结构参数进行了优化。提出了结合直线电机综合力性能指标进行最佳次级结构参数选择的方法。仿真与实验结果验证了电机表面响应模型以及优化方法的有效性。

关键词:

单边直线感应电机, 多目标优化, 表面响应模型, 次级结构参数, 神经网络

Abstract:

A 3D finite element model (FEM) of SLIM in urban rail transit was built. The influence between the secondary structural parameters and starting force characteristics of SLIM was analyzed by parametric analysis of secondary structural parameters. Two parameters, secondary aluminum thickness and secondary width, were selected, which greatly influenced on the starting force characteristics of SLIM. The RSM of starting force characteristics was built based on NN, which only needed few parametric analysis of 3D FEM. Based on the RSM of SLIM, a multi-objective optimization of secondary structural parameters was carried out via multi-objective genetic algorithm (MOGA), which choosen secondary aluminum thickness and secondary width as design variables, and choosen maximum starting thrust force and minimum normal force as optimization goals. Then the selection method of the secondary structural parameters was proposed. The effectiveness of the method was verified by simulations and experiments.

Key words: single-sided linear induction motor (SLIM), multi-objective optimization, response surface model (RSM), secondary structural parameter, neuron network (NN)

中图分类号:

TM359.3

王立强, 卢琴芬, 叶云岳.

基于表面响应模型法的城市轨道交通用直线感应电机次级结构优化

[J]. 中国机械工程, 2010, 21(15): 1825-1830.

WANG Li-Jiang, LEI Qin-Fen, XIE Yun-Yue.

Optimization of Secondary Structure of Linear Induction Motor in Urban Rail Transit Based on Response Surface Methodology

[J]. China Mechanical Engineering, 2010, 21(15): 1825-1830.

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