电工技术学报  2025, Vol. 40 Issue (3): 941-963    DOI: 10.19595/j.cnki.1000-6753.tces.232137
电能存储与应用 |
锂离子电池智能传感监测及预警技术
马敬轩1, 赖铱麟2, 吕娜伟1, 姜欣1, 金阳1
1.郑州大学电气与信息工程学院 郑州 450001;
2.中国电力科学研究院有限公司 北京 100192
Lithium-Ion Battery Intelligent Sensing Monitoring and Early Warning Technology
Ma Jingxuan1, Lai Yilin2, Lü Nawei1, Jiang Xin1, Jin Yang1
1. School of Electrical and Information Engineering Zhengzhou University Zhengzhou 450001 China;
2. China Electric Power Research Institute Beijing 100192 China
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摘要 先进电池技术是人类应对全球气候变化难题和能源危机的重要技术手段,特别是近年来电动汽车产业和规模储能的快速发展给锂离子电池产业带来了巨大的市场。然而,锂电池高速发展的同时伴随着诸多难题和挑战,高能量密度的电极材料造成了较差的热稳定性,导致锂电池在使用或储存过程中会出现一定概率的失效,包括容量衰减、自放电加速、循环寿命缩短、热失控等,严重影响锂离子电池使用的一致性、可靠性及安全性。近年来,国内外发生多起电动汽车、储能电站等各种规模储能系统的起火、爆炸事故,这说明现有的锂离子电池安全状态监测手段不足,亟须监测维度更加广泛、检测力度更加可靠的智能化传感及预警技术。因此,利用智能传感技术对电池故障早期表征的多维度物化特征(电、热、气、声、光、压、磁等)进行识别感知,在线监测和诊断电池安全状态,提前预警电池故障,能够大大降低电池的失效率和事故发生率。该文对现有研究进行全面综述,通过电池故障不同阶段内外部多维特征信号的演变机理,引出基于电、热、气、声、光、压、磁多维度智能传感及预警技术,分别介绍了它们的检测原理和特点,并对比了不同预警技术的优劣。最后,在调研的基础上,提出锂离子电池智能传感监测及预警技术发展面临的挑战和未来的研究方向,对锂离子电池性能提升、技术改进和故障防范具有一定意义。
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关键词 锂离子电池智能传感技术状态监测早期预警    
Abstract:Advanced battery technology is an important technical means for human beings to cope with the global climate change challenges and energy crisis, especially in recent years, the rapid development of the electric vehicle industry and large-scale energy storage has brought a huge market for the lithium-ion battery industry. However, the rapid development of lithium batteries is accompanied by many problems and challenges. The high energy density of electrode materials creates poor thermal stability, resulting in a certain probability of failure of lithium batteries during use or storage, including capacity degradation, accelerated self-discharge, shortened cycle life, thermal runaway, etc., which seriously affects the consistency, reliability, and safety of the batteries in use. In recent years, there have been a number of fire and explosion accidents in various scales of energy storage systems, such as electric vehicles and energy storage power stations at home and abroad, which indicates that the existing means of monitoring the safety status of batteries are insufficient, and there is an urgent need for intelligent sensing and early warning technologies with a wider range of monitoring dimensions and more reliable detection strength. Therefore, the use of intelligent sensing technology to identify and sense the multi-dimensional physical and chemical characteristics (electric, thermal, gas, acoustic, optical, pressure, magnetic, etc.) of the early characterisation of battery failures, online monitoring and diagnosis of the battery safety status, and early warning of battery failures can greatly reduce the rate of battery failures and the incidence of accidents.
Firstly, based on the investigation of lithium-ion battery degradation and failure process, the generation and evolution mechanism of multi-dimensional characteristic signals of lithium batteries are outlined. Li-ion batteries are prone to a series of failures such as lithium precipitation, temperature rise, gas production, diaphragm puncture, short circuit, etc., and exhibit typical failure behaviours such as external battery deformation, temperature rise, gas production, liquid leakage, safety valve opening, thermal runaway and other typical failure behaviours under the abusive conditions such as overcharging, overheating, short-circuiting, and collision, which result in the uninterrupted failure of the battery's internal material structure with the continuous degradation and aging of the battery's performance. Taking the thermal runaway overcharge of commercial lithium-ion batteries as an example, the deterioration process of lithium batteries is described in four stages and the generation mechanism of multi-dimensional physical and chemical characteristic parameters, such as electrical signals, temperature signals, gas signals, sound signals, light signals, pressure signals, magnetic signals, etc., is elaborated.
Based on this, multi-dimensional sensing technologies such as electrical, temperature, gas, sound, optical, pressure, electromagnetic, etc. are introduced, existing research results are comprehensively researched and reviewed, and their advantages and disadvantages in terms of lithium-ion battery fault early warning time, realisation technological difficulty, identification accuracy, monitoring range, cost, etc. are compared.
From the above analysis and discussion, the main challenges facing the development of intelligent sensing monitoring and early warning technology for lithium-ion batteries are summarised, such as the difficulty of sensor implantation, the vulnerability of sensors to damage, the integration of multi-parameter sensing technology, etc. Meanwhile, it is proposed that the future development of lithium-ion batteries' intelligent sensing monitoring and early warning technology should be directed towards the development of multi-parameter integration, the development of smarter sensors, the enhancement of the implantation of sensors and the packaging of batteries, and the strengthening of the implementation of multi-parameter sensing technology. We also propose that the future development of lithium-ion battery intelligent sensing monitoring and early warning technology should be towards multi-parameter integration, develop smarter sensors, improve sensor implantation and battery packaging technology, and strengthen the implementation of multi-parameter sensing technology.
Key wordsLithium-ion battery    intelligent sensing technology    condition monitoring    early warning   
收稿日期: 2023-12-21     
PACS: TM912  
基金资助:国网电网有限公司总部科技项目资助(4000-202355090A-1-1-ZN)
通讯作者: 金 阳 男,1989年生,教授,国家优青,博士生导师,研究方向为储能技术。Email:yangjin@zzu.edu.cn   
作者简介: 马敬轩 男,1999年生,硕士研究生,研究方向储能安全与技术。Email:majingxuan6585@163.com
引用本文:   
马敬轩, 赖铱麟, 吕娜伟, 姜欣, 金阳. 锂离子电池智能传感监测及预警技术[J]. 电工技术学报, 2025, 40(3): 941-963. Ma Jingxuan, Lai Yilin, Lü Nawei, Jiang Xin, Jin Yang. Lithium-Ion Battery Intelligent Sensing Monitoring and Early Warning Technology. Transactions of China Electrotechnical Society, 2025, 40(3): 941-963.
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