Discrete sliding mode control method for particle swarm optimization-based brushless DC motor of electric vehicle

IF 0.7 Q4 ENGINEERING, MECHANICAL Journal of Vibroengineering Pub Date : 2023-04-10 DOI:10.21595/jve.2023.22978

Fei Wang, Qiongzhen Mei, Xiaolei Xin

{"title":"Discrete sliding mode control method for particle swarm optimization-based brushless DC motor of electric vehicle","authors":"Fei Wang, Qiongzhen Mei, Xiaolei Xin","doi":"10.21595/jve.2023.22978","DOIUrl":null,"url":null,"abstract":"Brushless DC motor (BLDCM) is a multivariable nonlinear time-varying system, which is difficult to control. The discrete sliding mode control method for BLDCM of electric vehicle on the basis of particle swarm optimization (PSO) is studied to improve the application of BLDCM in electric vehicle. The mathematical model of BLDCM of electric vehicle is established using the state formula. Based on the mathematical model of BLDCM, through the analysis of electromagnetic torque control of BLDCM, it is clear that controlling the angle between rotor flux and stator flux can accurately control the electromagnetic torque of BLDCM. The adaptive discrete sliding mode controller (SMC) is set to control the electromagnetic torque of BLDCM of electric vehicle, and the PSO algorithm is adopted to obtain the optimal parameters of the adaptive discrete SMC to realize the discrete sliding mode control of BLDCM of electric vehicle. According to experimental results, the proposed method can achieve the accurate control of torque and speed of BLDCM of electric vehicle, and increase the application of BLDCM in electric vehicle.","PeriodicalId":49956,"journal":{"name":"Journal of Vibroengineering","volume":" ","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Vibroengineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21595/jve.2023.22978","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}

引用次数: 1

Abstract

Brushless DC motor (BLDCM) is a multivariable nonlinear time-varying system, which is difficult to control. The discrete sliding mode control method for BLDCM of electric vehicle on the basis of particle swarm optimization (PSO) is studied to improve the application of BLDCM in electric vehicle. The mathematical model of BLDCM of electric vehicle is established using the state formula. Based on the mathematical model of BLDCM, through the analysis of electromagnetic torque control of BLDCM, it is clear that controlling the angle between rotor flux and stator flux can accurately control the electromagnetic torque of BLDCM. The adaptive discrete sliding mode controller (SMC) is set to control the electromagnetic torque of BLDCM of electric vehicle, and the PSO algorithm is adopted to obtain the optimal parameters of the adaptive discrete SMC to realize the discrete sliding mode control of BLDCM of electric vehicle. According to experimental results, the proposed method can achieve the accurate control of torque and speed of BLDCM of electric vehicle, and increase the application of BLDCM in electric vehicle.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

基于粒子群优化的电动汽车无刷直流电机离散滑模控制方法

无刷直流电动机(BLDCM)是一个多变量非线性时变系统，控制困难。研究了基于粒子群优化(PSO)的电动汽车无刷电机离散滑模控制方法，以提高无刷电机在电动汽车中的应用。利用状态公式建立了电动汽车无刷直流电机的数学模型。在建立无刷直流电机数学模型的基础上，通过对无刷直流电机电磁转矩控制的分析，明确了控制转子磁链与定子磁链的夹角可以精确控制无刷直流电机的电磁转矩。设置自适应离散滑模控制器(SMC)来控制电动汽车无刷电机的电磁转矩，采用粒子群算法获得自适应离散滑模控制器的最优参数，实现电动汽车无刷电机的离散滑模控制。实验结果表明，该方法可以实现电动汽车无刷直流电机转矩和转速的精确控制，增加了无刷直流电机在电动汽车上的应用。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

Journal of Vibroengineering 工程技术-工程：机械

CiteScore

1.70

自引率

0.00%

发文量

审稿时长

4.5 months

期刊介绍： Journal of VIBROENGINEERING (JVE) ISSN 1392-8716 is a prestigious peer reviewed International Journal specializing in theoretical and practical aspects of Vibration Engineering. It is indexed in ESCI and other major databases. Published every 1.5 months (8 times yearly), the journal attracts attention from the International Engineering Community.