化工学报 ›› 2022, Vol. 73 ›› Issue (8): 3394-3405.DOI: 10.11949/0438-1157.20220265

• 综述与专论 • 上一篇    下一篇

电池系统的故障特征以及多故障的诊断与识别

杨静(), 林振康, 汤君, 樊铖(), 孙克宁()   

  1. 北京理工大学化学与化工学院,北京 100081
  • 收稿日期:2022-03-01 修回日期:2022-07-14 出版日期:2022-08-05 发布日期:2022-09-06
  • 通讯作者: 樊铖,孙克宁
  • 作者简介:杨静(1997—),女,硕士研究生,3120211315@bit.edu.cn
  • 基金资助:
    国家自然科学基金项目(42020619)

A review of fault characteristics, fault diagnosis and identification for lithium-ion battery systems

Jing YANG(), Zhenkang LIN, Jun TANG, Cheng FAN(), Kening SUN()   

  1. School of Chemistry and Chemical Engineering, Beijing Institute of Technology, Beijing 100081, China
  • Received:2022-03-01 Revised:2022-07-14 Online:2022-08-05 Published:2022-09-06
  • Contact: Cheng FAN, Kening SUN

摘要:

高比能的锂电池系统广泛应用于储能与动力电源,电池系统的故障诊断技术是其安全、长效工作的重要保障。但锂电池化学性质特殊,故障类型难以识别,增加了电池系统的安全风险。为提高故障诊断与类型识别的准确性,提高电池系统安全性,需要认识发生不同故障时的电、热、化学特征。综述了电池系统的故障类型,并系统地总结和分析了电池系统单电池、连接、传感器等故障的电、热、化学信号特征。提出了内部电化学参数是可靠判别传感器故障与各种电池早期故障的关键特征,电化学阻抗谱是获取内部特征参数的有效方法;从电压波动性出发,电流与电压相关系数是判别传感器故障与连接故障的关键;此外,电池系统的特殊连接结构也是区分不同故障的重要手段。

关键词: 电池系统, 故障特征, 多故障诊断, 参数估计, 瞬态响应, 预测

Abstract:

Lithium-ion battery systems with high specific energy are widely used in energy storage and power supplies. Fault diagnosis technology for battery systems is an important guarantee for safe and long-lasting operation. However, the chemical properties of lithium batteries are special, and the type of failure is difficult to identify, which increases the safety risk of the battery system. In order to improve the accuracy of fault diagnosis and type identification, and to improve the safety of battery systems, it is necessary to recognize the electrical, thermal and chemical characteristics when different faults occur. Herein, the aim of this review is to introduce the types of faults in battery system and to systematically summarize the electrical, thermal and chemical characteristics of battery system, including battery faults, connection faults and sensor faults. It is proposed that internal electrochemical parameters are key features to reliably discriminate between sensor faults and various battery faults, and that electrochemical impedance spectroscopy is an effective method to obtain internal characteristic parameters. In terms of the voltage fluctuation, current and voltage correlation coefficients are regarded as main factors to discriminate between sensor faults and connection faults. The special connection structure of the battery system can be used as an important means to distinguish between different faults.

Key words: battery system, fault characteristics, multiple faults diagnosis, parameter estimation, transient response, prediction

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