• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2021, Vol. 57 ›› Issue (14): 52-63.doi: 10.3901/JME.2021.14.052

• 特邀专栏:电源系统设计、管理与大数据 • 上一篇    下一篇

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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

王震坡1, 李晓宇1,2, 袁昌贵1, 黎小慧1   

  1. 1. 北京理工大学机械与车辆学院 北京 100081;
    2. 河北工业大学机械工程学院 天津 300401
  • 收稿日期:2020-09-07 修回日期:2020-12-28 出版日期:2021-09-15 发布日期:2021-09-15
  • 通讯作者: 李晓宇(通信作者),男,1991年出生,博士研究生。主要研究方向为锂电池状态估计,故障诊断,电动汽车充电调度及新能源汽车大数据分析。E-mail:xiaoyu_li187@163.com
  • 作者简介:王震坡,男,1976年出生,博士,教授,博士研究生导师。主要研究方向为电动汽车电池管理系统,新能源汽车大数据分析技术。E-mail:wangzhenpo@bit.edu.cn;袁昌贵,男,1995年出生,硕士研究生。主要研究方向为锂电池状态估计,新能源汽车大数据分析。E-mail:yuan_changgui@163.com;黎小慧,女,1994年出生,博士研究生。主要研究方向为新能源汽车大数据分析与智能充电策略。E-mail:13120166823@163.com
  • 基金资助:
    国家重点研发计划资助项目(2019YFB1600800)

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

WANG Zhenpo1, LI Xiaoyu1,2, YUAN Changgui1, LI Xiaohui1   

  1. 1. School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081;
    2. School of Mechanical Engineering, Hebei University of Technology, Tianjin 300401
  • Received:2020-09-07 Revised:2020-12-28 Online:2021-09-15 Published:2021-09-15

摘要: 电动汽车故障诊断技术是汽车安全运行的重要保证,高效精准的故障诊断不仅提高整车的安全性和可靠性,而且有利于促进电动汽车市场的积极健康发展。围绕电池管理系统和热管理系统,综述电池系统状态估计以及冷却技术,在保证电动汽车安全运行方面的最新研究进展;以整车局域网层面和车端云网联层面,分别介绍电池系统运行数据传输安全的先进技术手段;从实车运行大数据视角将故障诊断技术归纳为多尺度数据融合、故障识别、故障预报警三个方面分别展开阐述,剖析当前技术的优势及不足;针对当前故障诊断技术所面临的难点问题,展望未来融合大数据及人工智能技术,车端云智能网联条件下电动汽车故障诊断方法研究发展趋势。

关键词: 大数据, 电池系统, 故障诊断, 安全管理

Abstract: 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.

Key words: big data, battery system, fault diagnosis, safety management

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