期刊文献+

电动汽车永磁同步电机绕组匝间短路故障车载诊断技术研究

Analysis on On-board Diagnosis Technology for PMSM Winding Inter Turn Short Circuit Fault in Electric Vehicles
在线阅读 下载PDF
导出
摘要 电动汽车驱动电机车载诊断系统的研发可以提高行车安全和维护效率,这有助于电动汽车的推广和应用。本文以电动汽车永磁同步电机驱动系统为研究对象,主要研究电动汽车驱动电机车载诊断关键技术。文中以电动汽车驱动系统的电机定子绕组匝间短路故障诊断为任务载体,采用文献法综述了PMSM驱动系统车载诊断技术研究与应用现状,对车载诊断系统的两个重要因素(技术、市场)进行了探讨和评述。对永磁同步电机驱动系统故障诊断技术的未来发展进行总结和展望,提出车载诊断控制方案需要满足的三个基本要求。研究发现,不依赖于外部硬件且需要较少算力的参数辨识算法更适合当今的车载诊断系统。采用在线诊断(反电动势估计)和离线诊断(高频信号注入法)相结合的方法有助于提高故障诊断的准确性。 This paper takes the permanent magnet synchronous motor drive system of electric vehicles as the research object,mainly studying the key technologies of on-board diagnosis for electric vehicle drive motors.In this paper,the diagnosis of inter turn short circuit faults in the motor stator winding of electric vehicle drive systems is used as the task carrier.Firstly,the research and application status of on-board diagnosis and fault tolerance technology in PMSM drive systems are summarized using the literature method.Then,the two important factors(technology and market)of on-board diagnosis and fault tolerance systems are discussed and evaluated.Finally,a summary and outlook were made on the future development of fault diagnosis technology for permanent magnet synchronous motor drive systems,and three basic requirements that need to be met for on-board diagnostic control schemes were proposed.
作者 聂进 何琨 Nie Jin;He Kun(Huanggang Polytechnic College,Huanggang 438002 Hubei)
出处 《黄冈职业技术学院学报》 2024年第4期92-98,共7页 Journal of Huanggang Polytechnic
关键词 电动汽车 电机驱动系统 匝间短路 车载诊断 控制方案 Electric vehicles PMSM Inter turn short circuit On-board diagnosis Control
  • 相关文献

参考文献2

二级参考文献37

  • 1朱刚,周政新,马良.基于贝叶斯网络的电机智能诊断技术研究[J].微计算机信息,2006(01S):166-168. 被引量:5
  • 2黎文锋,邓继忠,沈雷.神经网络在电机故障诊断中的应用综述[J].电气应用,2006,25(3):45-47. 被引量:4
  • 3彭文季,罗兴锜.基于粗糙集和支持向量机的水电机组振动故障诊断[J].电工技术学报,2006,21(10):117-122. 被引量:32
  • 4JosephGiarratano GaryRiley 印鉴 刘星成 汤庸译.专家系统原理与编程[M].北京:机械工业出版社,2000.5.
  • 5Kenneth A Loparo, M L Adams, M Farouk Abdel Magied, et al. Fault detection and diagnosis of rotating machinery [ J I. IEEE Trans. on Industrial Electronics, 2000,47 (5) :1005 - 1014.
  • 6孙振环,朱文.基于神经网络专家系统的电机故障诊断研究[D].天津:天津科技大学,2002.
  • 7M Y Chow, S Almg, H J Trussell. Heuristic constraints enforcement for training of and knowledge extraction from a fuzzy neural architecture part I -II [ J ]. IEEE Transac- tions on Fuzzy Systems, 1999,7 (20) : 143 - 159.
  • 8S Kolla L Varatharasa. Identifying three - phase induction motor faults using artificial neural network [ J 1 ISA. Transaction, 2000,39( 1 ) :433 -439.
  • 9B Li, M Y Chow, Y Tipsuwan, et al. Neural- network based motor rolling bearing fault diagnosis [ J ]. IEEE Transactions on Industrial Electronics, 2000, 47 ( 7 ) : 1060 - 1069.
  • 10B Samanta, K R A1 - Balushi. Artificial neural network- based fault diagnostics of rolling element bearings using time- domain features [ J ]. Mechanical System and Sig- nal Prod, 2003,17(2) :317 -328.

共引文献42

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部