基于阻抗在线测量的锂离子电池过放电诱发内短路识别研究

doi:10.19595/j.cnki.1000-6753.tces.230026

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摘要锂离子电池的过放电行为可诱发内短路进而可能导致热失控。由于单体电池一致性差异和过放电导致的内短路初期电、热特征不明显,使得电压和温度等常规物理参数难以可靠实现故障预警,而阻抗可以反映电池内部信息,对故障状态具有较好的指示能力。该文通过分析锂离子电池过放电诱发内短路引起阻抗变化的机理,基于设计的阻抗在线测量装置,确定用于监测电池内短路故障的特征阻抗频率为70 Hz,获取过放电诱发内短路过程中特征频率下动态阻抗及阻抗变化率,提出一种基于动态阻抗特征的内短路在线识别方法并验证了方法的可靠性。实验结果表明,锂离子电池放电过程中动态阻抗半正弦变化特征可提前约144 s实现过放电预警,动态阻抗针状变化特征可提前约152 s实现内短路故障预警,动态阻抗明显回升特征可作为内短路发生的标志。此外,阻抗变化率特征有助于实现锂离子电池故障识别及预警,该方法在锂离子电池故障在线快速诊断中具有重要的应用潜力。

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关键词 ：过放电, 阻抗在线测量, 内短路在线识别, 故障预警

Abstract：The over-discharge behavior of lithium-ion batteries can induce internal short circuits, which may lead to thermal runaway. Early detection of internal short circuits is crucial for preventing catastrophic accidents. However, the consistency of the single cell is different, and obvious electrical and thermal characteristics are lacking at the initial stage of the internal short circuit caused by over-discharge. It is difficult to reliably realize fault warnings with conventional physical parameters such as voltage and temperature. The impedance can reflect the internal information of the battery and has a good indication of the fault state. More research is needed on the impedance-based online diagnosis of internal short circuits in lithium-ion batteries. Acknowledging the complexity associated with modelling and identifying electrochemical impedance spectroscopy (EIS) parameters, this paper proposes anonline identification method for lithium-ion battery internal short circuits under a frequency of 70 Hz induced by over-discharge. This method does not involve complex mathematical models or parameter identification, ensuring accurate identification of internal short circuits caused by over-discharge with fault warning capabilities.
Firstly, the mechanism of internal short circuits induced by over-discharge in lithium-ion batteries was studied, and the dynamic impedance change characteristics during the internal short circuit were analyzed. Secondly, an online impedance measurement device for lithium-ion batteries was designed, and an experimental platform was built to simulate internal short circuits through overdischarge. EIS under different temperature environments and state of charge conditions was obtained, and the characteristic impedance frequency for internal short circuit fault identification was determined. The dynamic impedance was measured during normal charging/discharging and over-discharge processes of lithium-ion batteries. The dynamic impedance and its change rate were analyzed for internal short-circuit fault identification. Based on the dynamic impedance characteristics, an internal short-circuit online identification method was proposed. Finally, according to the irreversible capacity loss and self-discharge characteristics of the internal short circuit battery and battery disassembly, the reliability of the proposed identification method was verified.
The experimental results show that the dynamic impedance of lithium-ion batteries during discharge exhibits a semi-sinusoidal characteristic change, which can provide an early warning for over-discharge by about 144 seconds in advance. The needle-like characteristic change of dynamic impedance can provide an early warning of internal short circuit faults by about 152 seconds. The significant rebound feature of dynamic impedance can be used as a sign of internal short circuit occurrence. In addition, the feature of impedance change rate helps realize fault identification and warning of lithium-ion batteries. Experimental verification shows that batteries with a significant rebound characteristic of dynamic impedance experience a sharp increase in irreversible and self-discharge capacity loss up on cessation of discharging. Moreover, after disassembling, the positive electrode has copper metal deposition, the negative electrode graphite layer is damaged, the copper foil is dissolved, and the separator is sparse and shows signs of damage, demonstrating the reliability of the proposed method.

Key words： Overdischarge impedance online measurement internal short circuit online identification fault warning

收稿日期: 2023-01-09

PACS:

TM911

基金资助:国家自然科学基金项目（51977058）、河北省中央引导地方科技发展专项（216Z4406G）和电力系统国家重点实验室课题（SKLD21KZ04）资助

通讯作者: 张闯男,1982年生,教授,博士生导师,研究方向为储能装置的安全状态评价与预警、电工装备电磁无损检测与评估。E-mail: czhang@hebut.edu.cn

作者简介: 杨浩男,1996年生,硕士研究生,研究方向为锂离子电池无损检测技术。E-mail: 202121401101@stu.hebut.edu.cn

引用本文:

张闯, 杨浩, 刘素贞, 徐志成, 杨庆新. 基于阻抗在线测量的锂离子电池过放电诱发内短路识别研究[J]. 电工技术学报, 2024, 39(6): 1656-1670. Zhang Chuang, Yang Hao, Liu Suzhen, Xu Zhicheng, Yang Qingxin. Research on Overdischarge-Induced Internal Short Circuit Identification of Lithium-Ion Battery Based on Impedance Online Measurement. Transactions of China Electrotechnical Society, 2024, 39(6): 1656-1670.

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