Challenge and Prospects for Fault Diagnosis of Power Battery System for Electrical Vehicles Based on Big-data

被引：0
|
作者：
Wang Z. [1 ]
Li X. [1 ,2 ]
Yuan C. [1 ]
Li X. [1 ,2 ]
机构：
[1] School of Mechanical Engineering, Beijing Institute of Technology, Beijing
[2] School of Mechanical Engineering, Hebei University of Technology, Tianjin
来源：
Jixie Gongcheng Xuebao/Journal of Mechanical Engineering | 2021年 / 57卷 / 14期
关键词：
Battery system; Big data; Fault diagnosis; Safety management;
D O I：
10.3901/JME.2021.14.052
中图分类号：
学科分类号：
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. © 2021 Journal of Mechanical Engineering.
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页码：52 / 63
页数：11
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