大数据下电动汽车动力电池故障诊断技术挑战与发展趋势

Zhenpo Wang, Xiaoyu Li*, Changgui Yuan, Xiaohui Li

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

13 引用 (Scopus)

摘要

Battery fault diagnosis techniques are regarded as significant means for guaranteeing safe operation of electric vehicles (EVs). Precise and effective techniques not only can improve safety and reliability of EVs but also accelerate the progress of EVs' market. Firstly, focusing on the battery management system and thermal management system, the latest research progress of battery state estimation and cooling technology in ensuring the safe operation of EVs is reviewed; Secondly, advanced technical means of data transmission security of battery system operation are introduced respectively at the vehicle local level and the vehicle terminal cloud network level; Additionally, from the perspective of big data, the fault diagnosis technology is summarized into three aspects: multi-scale data fusion, fault identification, and fault pre-alarming, and the advantages and disadvantages of the current technology are analyzed; Finally, in view of the difficulties faced by current fault diagnosis technology, the future research trend of EV's fault diagnosis method combining big data and artificial intelligence technology is prospected.

投稿的翻译标题Challenge and Prospects for Fault Diagnosis of Power Battery System for Electrical Vehicles Based on Big-data
源语言繁体中文
页(从-至)52-63
页数12
期刊Jixie Gongcheng Xuebao/Chinese Journal of Mechanical Engineering
57
14
DOI
出版状态已出版 - 20 7月 2021

关键词

  • Battery system
  • Big data
  • Fault diagnosis
  • Safety management

指纹

探究 '大数据下电动汽车动力电池故障诊断技术挑战与发展趋势' 的科研主题。它们共同构成独一无二的指纹。

引用此