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| Research on Overdischarge-Induced Internal Short Circuit Identification of Lithium-Ion Battery Based on Impedance Online Measurement |
| Zhang Chuang1,2, Yang Hao1,2, Liu Suzhen1,2, Xu Zhicheng1,2, Yang Qingxin1 |
1. State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin 300130 China;
2. Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province Hebei University of Technology Tianjin 300130 China |
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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.
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Received: 09 January 2023
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[1] 牛志远, 姜欣, 谢镔, 等. 电动汽车过充燃爆事故模拟及安全防护研究[J]. 电工技术学报, 2022, 37(1): 36-47, 57.
Niu Zhiyuan, Jiang Xin, Xie Bin, et al.Study on simulation and safety protection of electric vehicle overcharge and explosion accident[J]. Transactions of China Electrotechnical Society, 2022, 37(1): 36-47, 57.
[2] 孙丙香, 任鹏博, 陈育哲, 等. 锂离子电池在不同区间下的衰退影响因素分析及任意区间的老化趋势预测[J]. 电工技术学报, 2021, 36(3): 666-674.
Sun Bingxiang, Ren Pengbo, Chen Yuzhe, et al.Analysis of influencing factors of degradation under different interval stress and prediction of aging trend in any interval for lithium-ion battery[J]. Transactions of China Electrotechnical Society, 2021, 36(3): 666-674.
[3] 韩云飞, 谢佳, 蔡涛, 等. 基于自动编码器的锂离子电池状态评估方法[J]. 电力系统自动化, 2021, 45(24): 41-48.
Han Yunfei, Xie Jia, Cai Tao, et al.Autoencoder- based state evaluation method for lithium-ion battery[J]. Automation of Electric Power Systems, 2021, 45(24): 41-48.
[4] Feng Xuning, Ouyang Minggao, Liu Xiang, et al.Thermal runaway mechanism of lithium ion battery for electric vehicles: a review[J]. Energy Storage Materials, 2018, 10: 246-267.
[5] Lü Nawei, Jin Yang, Xiong Rui, et al.Real-time overcharge warning and early thermal runaway prediction of Li-ion battery by online impedance measurement[J]. IEEE Transactions on Industrial Electronics, 2022, 69(2): 1929-1936.
[6] 洪琰, 周龙, 张俊, 等. 锂离子电池充放电机械压力特性研究[J]. 机械工程学报, 2022, 58(20): 410-420.
Hong Yan, Zhou Long, Zhang Jun, et al.Study on the mechanical pressure characteristics of charge and discharge of lithium-ion battery[J]. Journal of Mechanical Engineering, 2022, 58(20): 410-420.
[7] Gao Wei, Li Xiaoyu, Ma Nina, et al.Case study of an electric vehicle battery thermal runaway and online internal short-circuit detection[J]. IEEE Transactions on Power Electronics, 2021, 36(3): 2452-2455.
[8] Wu Jiaming, Chen Zhiqiang.Diagnosis of internal short circuit for lithium ion battery pack under varying temperature[C]//International Electrical and Energy Conference, Beijing, China, 2019: 1091-1095.
[9] Ma Ruifei, He Jin, Deng Yuelin.Investigation and comparison of the electrochemical impedance spectroscopy and internal resistance indicators for early-stage internal short circuit detection through battery aging[J]. Journal of Energy Storage, 2022, 54: 105346.
[10] Feng Xuning, Weng Caihao, Ouyang Minggao, et al.Online internal short circuit detection for a large format lithium ion battery[J]. Applied Energy, 2016, 161: 168-180.
[11] Chen Xu, Li Xiangdong, Wang Yi, et al.A diagnostic method of internal short circuit fault in lithium-ion battery[C]//International Conference on Vehicular Control and Intelligence, Tianjin, China, 2021: 1-5.
[12] 孙丙香, 王家驹, 苏晓佳, 等. 基于阶梯波的锂离子电池电化学阻抗谱低频段在线辨识方法[J]. 电工技术学报, 2022, 38(11): 3064-3072.
Sun Bingxiang, Wang Jiaju, Su Xiaojia, et al.Study on online identification method of low frequency electrochemical impedance spectroscopy for lithium- ion battery based on step wave[J]. Transactions of China Electrotechnical Society, 2022, 38(11): 3064-3072.
[13] Carthy K M, Gullapalli H, Kennedy T.Real-time internal temperature estimation of commercial Li-ion batteries using online impedance measurements[J]. Journal of Power Sources, 2022, 519: 230786.
[14] Kong Xiangdong, Plett G L, Trimboli M S, et al.Pseudo-two-dimensional model and impedance diagnosis of micro internal short circuit in lithium-ion cells[J]. Journal of Energy Storage, 2020, 27: 101085.
[15] Spielbauer M, Berg P, Ringat M, et al.Experimental study of the impedance behavior of 18650 lithium-ion battery cells under deforming mechanical abuse[J]. Journal of Energy Storage, 2019, 26: 101039.
[16] Lai Xin, Jin Changyong, Yi Wei, et al.Mechanism, modeling, detection, and prevention of the internal short circuit in lithium-ion batteries: Recent advances and perspectives[J]. Energy Storage Materials, 2021, 35: 470-499.
[17] 严康为, 龙鑫林, 鲁军勇, 等. 高倍率磷酸铁锂电池简化机理建模与放电特性分析[J]. 电工技术学报, 2022, 37(3): 599-609.
Yan Kangwei, Long Xinlin, Lu Junyong, et al.Simplified mechanism modeling and discharge characteristic analysis of high C-rate LiFePO4 battery[J]. Transactions of China Electrotechnical Society, 2022, 37(3): 599-609.
[18] Fear C, Juarez-Robles D, Jeevarajan J A, et al.Elucidating copper dissolution phenomenon in Li-ion cells under overdischarge extremes[J]. Journal of The Electrochemical Society, 2018, 165(9): A1639-A1647.
[19] Guo Rui, Lu Langguang, Ouyang Minggao, et al.Mechanism of the entire overdischarge process and overdischarge-induced internal short circuit in lithium-ion batteries[J]. Scientific Reports, 2016, 6: 30248.
[20] He Hao, Liu Yadong, Liu Qi, et al.Failure investi- gation of LiFePO4 cells in over-dischargeconditions[J]. Journal of The Electrochemical Society, 2013, 160(6): A793-A804.
[21] Zhang Guangxu, Wei Xuzhe, Tang Xuan, et al.Internal short circuit mechanisms, experimental approaches and detection methods of lithium-ion batteries for electric vehicles: a review[J]. Renewable and Sustainable Energy Reviews, 2021, 141: 110790.
[22] Wang Xueyuan, Wei Xuezhe, Zhu Jiangong, et al.A review of modeling, acquisition, and application of lithium-ion battery impedance for onboard battery management[J]. eTransportation, 2021, 7: 100093.
[23] Carthy K M, Gullapalli H, Kennedy T.Online state of health estimation of Li-ion polymer batteries using real time impedance measurements[J]. Applied Energy, 2022, 307:118210.
[24] Srinivasan R, Demirev P A, Carkhuf B G.Rapid monitoring of impedance phase shifts in lithium-ion batteries for hazard prevention[J]. Journal of Power Sources, 2018, 405: 30-36.
[25] 来鑫, 陈权威, 邓聪, 等. 一种基于电化学阻抗谱的大规模退役锂离子电池的软聚类方法[J]. 电工技术学报, 2022, 37(23): 6054-6064.
Lai Xin, Chen Quanwei, Deng Cong, et al.A soft clustering method for the large-scale retired lithium- ion batteries based on electrochemical impedance spectroscopy[J]. Transactions of China Electro- technical Society, 2022, 37(23): 6054-6064.
[26] 卢恋, 任伟新, 王世东. 基于Kaiser窗的分数阶Fourier变换与时频分析[J/OL]. 振动工程学报, 2022: 1-8.
Lu Lian, Ren Weixin, Wang Shidong.Fractional Fourier transform based Kaiser window and time- frequency analysis[J/OL]. Journal of Vibration Engin- eering, 2022: 1-8.
[27] Nara H, Yokoshima T, Osaka T.Technology of electrochemical impedance spectroscopy for an energy-sustainable society[J]. Current Opinion in Electrochemistry, 2020, 20: 66-77.
[28] 牛凯, 李静如, 李旭晨, 等. 电化学测试技术在锂离子电池中的应用研究[J]. 中国测试, 2020, 46(7): 90-101.
Niu Kai, Li Jingru, Li Xuchen, et al.Research on the applications of electrochemical measurement tech- nologies in lithium-ion batteries[J]. China Measure- ment & Test, 2020, 46(7): 90-101.
[29] Islam S M R, Park S Y. Precise online electro- chemical impedance spectroscopy strategies for Li-ion batteries[J]. IEEE Transactions on Industry Applications, 2020, 56(2): 1661-1669.
[30] Zhu J G, Sun Z C, Wei X Z, et al.A new lithium-ion battery internal temperature on-line estimate method based on electrochemical impedance spectroscopy measurement[J]. Journal of Power Sources, 2015, 274:990-1004.
[31] Carthy K M, Gullapalli H, Ryan K M, et al.Electrochemical impedance correlation analysis for the estimation of Li-ion battery state of charge, state of health and internal temperature[J]. Journal of Energy Storage, 2022, 50: 104608.
[32] Huang Jun.Diffusion impedance of electroactive materials, electrolytic solutions and porous electrodes: Warburg impedance and beyond[J]. Electrochimica Acta, 2018, 281: 170-188.
[33] 袁浩, 戴海峰, 杜润本, 等. 质子交换膜燃料电池电化学阻抗谱弛豫时间分布研究[J]. 机械工程学报, 2020, 56(22): 120-130.
Yuan Hao, Dai Haifeng, Du Runben, et al.Dis- tribution of relaxation times analysis of proton exchange membrane fuel cell electrochemical impedance spectra[J].Journal of Mechanical Engin- eering, 2020, 56(22):120-130.
[34] Yin Tao, Jia Longzhou, Li Xichao, et al.Effect of high-rate cycle aging and over-discharge onNCM811 (LiNi0.8Co0.1Mn0.1O2) batteries[J]. Energies, 2022, 15(8): 2862.
[35] 范文杰, 徐广昊, 余泊宁, 等. 基于电化学阻抗谱的锂离子电池内部温度在线估计方法研究[J]. 中国电机工程学报, 2021, 41(9): 3283-3293.
Fan Wenjie, Xu Guanghao, Yu Boning, et al.On-line estimation method for internal temperature of lithium-ion battery based on electrochemical impe- dance spectroscopy[J]. Proceedings of the CSEE, 2021, 41(9): 3283-3293.
[36] 袁翔, 张毅. 动力锂电池阻抗特性的分析与验证[J].汽车工程学报, 2014, 4(6): 447-454.
Yuan Xiang, Zhang Yi.Analysis and verification of the power lithium battery impedance characteristics[J]. Chinese Journal of Automotive Engineering, 2014, 4(6): 447-454.
[37] Kong Xiangdong, Zheng Yuejiu, Ouyang Minggao, et al.Fault diagnosis and quantitative analysis of micro-short circuits for lithium ion batteries in battery packs[J]. Journal of Power Sources, 2018, 395: 358-368.
[38] 董明, 范文杰, 刘王泽宇, 等. 基于特征频率阻抗的锂离子电池健康状态评估[J]. 中国电机工程学报, 2022, 42(24): 9094-9105.
Dong Ming, Fan Wenjie, Liu Wangzeyu, et al.Health assessment of lithium-ion battery based on characte- ristic frequency impedance[J]. Proceedings of the CSEE, 2022, 42(24): 9094-9105.
[39] Guo Jia, Li Yaqi, Meng Jinhao, et al.Understanding the mechanism of capacity increase during early cycling of commercial NMC/graphite lithium-ion batteries[J]. Journal of Energy Chemistry, 2022, 74: 34-44.
[40] Lai Xin, Zheng Yuejiu, Zhou Long, et al.Electrical behavior of overdischarge-induced internal short circuit in lithium-ion cells[J]. Electrochimica Acta, 2018, 278: 245-254.
[41] Tahmasbi A A, Eikerling M H.Statistical physics- based model of mechanical degradation in lithium ion batteries[J]. Electrochimica Acta, 2018, 283: 75-87. |
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2024, Vol. 39 
