基于电化学阻抗谱的锂离子电池热失控早期预警方法研究进展

doi:10.19799/j.cnki.2095-4239.2025.0577

摘要/Abstract

摘要：

近年来，因锂离子电池热失控引发的事故频繁发生，在热失控发生之前及时发出预警并进行有效干预，对于保障人员安全、减少财产损失具有重要意义。电化学阻抗谱技术作为一种无损、快速的表征方法，在锂离子电池热失控预警领域受到广泛关注和深入研究。首先，介绍了电化学阻抗谱的测量原理和等效电路模型，分析了电化学阻抗谱用于锂离子电池热失控监测预警的原理和特性；其次，重点综述了当前电化学阻抗谱在锂离子电池热失控早期预警方面的应用，包括直接法和内部温度监测、内短路监测、析锂检测在内的间接法等单独使用电化学阻抗谱的热失控预警方法，以及与温度传感器、气体传感器等其他方法联用的热失控预警方法，从参数选择、特征频率确定、预警指标建立等方面论述了各种方法的实际运用效果，并总结出每种方法的优缺点；最后，展望了电化学阻抗谱技术用于锂离子电池热失控早期预警未来的发展方向和趋势，为建立准确普适的预警方法、提高锂离子电池安全性提供参考。

关键词: 锂离子电池, 热失控, 电化学阻抗谱, 早期预警方法

Abstract:

IIn recent years, accidents caused by thermal runaway of lithium-ion batteries have occurred frequently. Timely warning and effective intervention before thermal runaway are of great significance for ensuring personnel safety and reducing property losses. As a non-destructive and rapid characterization method, electrochemical impedance spectroscopy technology has received widespread attention in the field of lithium-ion battery thermal runaway warning. Firstly, the measurement principle and equivalent circuit model of electrochemical impedance spectroscopy were introduced, and the principle and characteristics of using electrochemical impedance spectroscopy for monitoring and early warning of thermal runaway in lithium-ion batteries were analyzed; Secondly, the current application of electrochemical impedance spectroscopy in early warning of thermal runaway in lithium-ion batteries was summarized, including direct methods and indirect methods such as internal temperature monitoring, internal short circuit monitoring, and lithium deposition detection, as well as thermal runaway warning methods combined with temperature sensors, gas sensors, and other methods. The practical application effects of various methods were discussed from the aspects of parameter selection, characteristic frequency determination, and warning index establishment, and the advantages and disadvantages of each method were summarized; Finally, the future development direction and trend of electrochemical impedance spectroscopy technology for early warning of thermal runaway in lithium-ion batteries were discussed, providing reference for establishing accurate and universal warning methods and improving the safety of lithium-ion batteries.

Key words: lithium-ion battery, thermal runaway, electrochemical impedance spectroscopy, early warning methods

中图分类号:

TM912

陈静, 孙杰, 李吉刚, 周添, 卫寿平, 张帆, 肖云海. 基于电化学阻抗谱的锂离子电池热失控早期预警方法研究进展[J]. 储能科学与技术, doi: 10.19799/j.cnki.2095-4239.2025.0577.

Jing CHEN, Jie SUN, Jigang LI, Tian ZHOU, Shouping WEI, Fan ZHANG, Yunhai XIAO. Research Progress of Early Warning Methods for Thermal Runaway of Lithium-ion Batteries Based on Electrochemical Impedance Spectroscopy[J]. Energy Storage Science and Technology, doi: 10.19799/j.cnki.2095-4239.2025.0577.

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基于电化学阻抗谱的热失控预警方法比较"

预警方法		优点	缺点
直接法		大部分方法基于单点频率进行预警，响应迅速；非侵入式测量，不影响电池循环性能；特征信号易于识别，不需要借助复杂的数学模型进行计算	热失控早期相对阻抗变化较小的阶段，在大量并联电池系统中可能无法检测到由单电池引起的有效阻抗变化；阻抗实部、虚部、相移、幅值等参数进行预警的方法通常随电池类型和容量等变化而变化，不具有通用性
间接法	内部温度监测	LIB的内部温度与EIS密切相关，通过EIS的变化可以准确预测内部温度；能够根据模型或校准的关系实现内部温度的监测，响应速度快；非侵入式测量，不影响电池循环性能	EIS受温度、SOC、SOH等影响，需要将其与SOC、SOH等进行解耦，建立EIS与内部温度之间关系的过程比较复杂；受电池类型、容量等因素的影响，用于内部温度检测的特征频率筛选和确定的方法不唯一，需要对大量测试EIS数据进行后处理以确定所需频率；实现电池运行状态下内部温度的实时监测，需要考虑电池施加的电压或电流对激励信号的干扰，以免影响预测结果的准确性
	内短路监测	实时在线测量，灵敏度较高，能够检测到内短路故障初期引起的内部电化学响应的微小变化，及时、准确地诊断出故障	除上述提到的解耦参数外，还需要解耦温度、湿度等使用环境对EIS的影响，以确保识别方法在电池全生命周期内有效使用；电池的内短路是在特定电池类型和实验条件下触发的，无法直接推广到所有类型的锂离子电池或不同的使用条件；多数文献使用Randles模型、P2D模型等来分析电池的电化学阻抗，但模型可能过于简化，未能充分考虑电池内部复杂的物理化学过程
	锂沉积检测	EIS能够对锂离子电池析锂进行快速、非破坏性的定量检测；通过选择激励频率能够分离电池内部各个传输过程，例如电荷转移或离子迁移	析锂程度较低时，EIS可能难以检测到微小的变化，需要一定的析锂量才能够诊断出电池已经发生锂沉积，通常为电池容量值的1%左右，此时已对电池造成不可逆的破坏；电池的荷电状态、温度和老化程度等都可能影响电池内部的电阻和界面特性，EIS可能难以区分析锂和其他电化学过程的影响
与其他方法联用	与温度传感器联用	能够监测内部温度分布情况，提高内部温度测量的精度，增强预警的可靠性	与单一测量相比，检测参数增多、操作流程复杂，增加预警的时间和经济成本
与其他方法联用	与气体传感器联用	弥补了气体传感器响应不够快、检测精度不够高、气体交叉干扰等问题，实现快速、灵敏、高效、准确的测量和预警	与单一测量相比，检测参数增多、操作流程复杂，增加预警的时间和经济成本

表 2

参考文献 87

[1]	PENG R, KONG D, PING P, et al. Thermal runaway modeling of lithium-ion batteries at different scales: Recent advances and perspectives[J]. Energy Storage Materials, 2024: 103417.
[2]	MA H, HE Q, ZHANG F, et al. Research progress on early warning method and suppression technology of thermal runaway of lithium battery[J]. Journal of Energy Storage, 2025, 119: 116377.
[3]	AZUAJE–BERBECÍ B J, ERTAN H B. A model for the prediction of thermal runaway in lithium–ion batteries[J]. Journal of Energy Storage, 2024, 90: 111831.
[4]	Zhang L, Liu L, Terekhov A, et al. Thermal runaway of Li-ion battery with different aging histories[J]. Process Safety and Environmental Protection, 2024, 185: 910-917.
[5]	FENG X, ZHENG S, REN D, et al. Investigating the thermal runaway mechanisms of lithium-ion batteries based on thermal analysis database [J]. Applied Energy, 2019, 246: 53-64.
[6]	FENG X, OUYANG M, LIU X, et al. Thermal runaway mechanism of lithium ion battery for electric vehicles: A review [J]. Energy Storage Materials, 2018, 10: 246-67.
[7]	LIU H-M, SAIKIA D, WU H-C, et al. Towards an understanding of the role of hyper-branched oligomers coated on cathodes, in the safety mechanism of lithium-ion batteries [J]. RSC Adv, 2014, 4(99): 56147-55.
[8]	LIU X, KUSAWAKE H, KUWAJIMA S. Preparation of a PVdF-HFP/polyethylene composite gel electrolyte with shutdown function for lithium-ion secondary battery[J]. Journal of power sources, 2001, 97: 661-663.
[9]	HOU J, LU L, WANG L, et al. Thermal runaway of Lithium-ion batteries employing LiN(SO2F)2-based concentrated electrolytes [J]. Nature Communications, 2020, 11(1).
[10]	MEI W, LIU Z, WANG C, et al. Operando monitoring of thermal runaway in commercial lithium-ion cells via advanced lab-on-fiber technologies [J]. Nature Communications, 2023, 14(1).
[11]	SCHMITT J, KRAFT B, SCHMIDT J P, et al. Measurement of gas pressure inside large-format prismatic lithium-ion cells during operation and cycle aging [J]. Journal of Power Sources, 2020, 478.
[12]	SONG Y, LYU N, SHI S, et al. Safety warning for lithium-ion batteries by module-space air-pressure variation under thermal runaway conditions [J]. Journal of Energy Storage, 2022, 56.
[13]	ZHANG Y, WANG H, WANG Y, et al. Thermal abusive experimental research on the large-format lithium-ion battery using a buried dual-sensor [J]. Journal of Energy Storage, 2021, 33.
[14]	JIN Y, ZHENG Z, WEI D, et al. Detection of micro-scale li dendrite via h2 gas capture for early safety warning [J]. Joule, 2020, 4(8): 1714-29.
[15]	KOCH S, BIRKE K, KUHN R. Fast thermal runaway detection for lithium-ion cells in large scale traction batteries [J]. Batteries, 2018, 4(2).
[16]	LI K J, CHEN L, HAN X, et al. Early warning for thermal runaway in lithium-ion batteries during various charging rates: insights from expansion force analysis[J]. Journal of Cleaner Production, 2024, 457: 142422.
[17]	ZHANG X, CHEN S, ZHU J, et al. A critical review of thermal runaway prediction and early-warning methods for lithium-ion batteries [J]. Energy Material Advances, 2023, 4.
[18]	DU X, MENG J, XUE Z, et al. Revolutionizing battery safety: real-time insights with dynamic electrochemical impedance spectroscopy[J]. ACS Energy Letters, 2025, 10(5): 2292-2304.
[19]	SATHYANARAYANA S, VENUGOPALAN S, GOPIKANTH M L. Impedance parameters and the state-of charge. I. Nickel-cadmium battery[J]. Journal of applied electrochemistry, 1979, 9: 125-139.
[20]	XIA B, QIN Z, FU H. Rapid estimation of battery state of health using partial electrochemical impedance spectra and interpretable machine learning [J]. Journal of Power Sources, 2024, 603.
[21]	ZHANG S S, XU K, JOW T R. Electrochemical impedance study on the low temperature of Li-ion batteries [J]. Electrochimica Acta, 2004, 49(7): 1057-61.
[22]	SURESH P, SHUKLA A K, MUNICHANDRAIAH N. Temperature dependence studies of ac impedance of lithium-ion cells[J]. Journal of applied electrochemistry, 2002, 32: 267-273.
[23]	吴磊, 吕桃林, 陈启忠, 等. 电化学阻抗谱测量与应用研究综述[J]. 电源技术, 2021, 45(9): 1227-1230.
	WU L, LV TL, CHEN QZ, et al. Review of measurement and application of electrochemical impedance spectroscopy[J]. Chinese Journal of Power Sources, 2021, 45(9): 1227-1230.
[24]	YANG S, WANG X, ZHOU S, et al. Multi-scenario failure diagnosis for lithium-ion battery based on coupling PSO-SA-DBSCAN algorithm[J]. Journal of Energy Storage, 2024, 99: 113393.
[25]	LYU N, JIN Y, XIONG R, 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, 2021.
[26]	田爱娜, 潘壮壮, 吴铁洲等. 基于单频阻抗的锂离子电池热失控分级预警[J]. 电池, 2024, 54(2): 194-199.
	TIAN A N, PAN Z Z, WU T Z, et al. Thermal runaway graded warning of Li-ion battery based on single-frequency impedance[J]. Battery Bimonthly, 2024, 54(2): 194-199.
[27]	袁奥特, 蔡涛, 刘政辰, 等. 基于电化学阻抗谱的锂离子电池电滥用失效预警研究[J]. 电工技术学报, 2025, 40(7): 2306-2321.
	YUAN AT, CAI T, LIU ZC, et al. Study of electrical abuse failure early warning of lithium-ion batteries based on electrochemical impedance spectroscopy[J]. Transactions of China ElectrotechnicalL Society, 2025, 40(7): 2306-2321.
[28]	PENG D, ZHONGXIAO L, PENG W, et al. Reliable and early warning of lithium-ion battery thermal runaway based on electrochemical impedance spectrum [J]. Journal of The Electrochemical Society, 2021.
[29]	SRINIVASAN R, DEMIREV P A, CARKHUFF B G. Rapid monitoring of impedance phase shifts in lithium-ion batteries for hazard prevention [J]. Journal of Power Sources, 2018.
[30]	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.
[31]	LI Y, JIANG L, ZHANG N, et al. Early warning method for thermal runaway of lithium-ion batteries under thermal abuse condition based on online electrochemical impedance monitoring[J]. Journal of Energy Chemistry, 2024, 92: 74-86.
[32]	ZHANG G, CAO L, GE S, et al. In situ measurement of radial temperature distributions in cylindrical li-ion cells [J]. Journal of The Electrochemical Society, 2014, 161(10): A1499-A507.
[33]	GULSOY B, VINCENT T A, SANSOM J E H, et al. In-situ temperature monitoring of a lithium-ion battery using an embedded thermocouple for smart battery applications [J]. Journal of Energy Storage, 2022, 54.
[34]	XU C, FENG X, HUANG W, et al. Internal temperature detection of thermal runaway in lithium-ion cells tested by extended-volume accelerating rate calorimetry [J]. Journal of Energy Storage, 2020, 31.
[35]	FLEMING J, AMIETSZAJEW T, CHARMET J, et al. The design and impact of in-situ and operando thermal sensing for smart energy storage [J]. Journal of Energy Storage, 2019, 22: 36-43.
[36]	VINCENT T A, GULSOY B, SANSOM J E H, et al. Development of an in-vehicle power line communication network with in-situ instrumented smart cells [J]. Transportation Engineering, 2021, 6.
[37]	YANG L, LI N, HU L, et al. Internal field study of 21700 battery based on long-life embedded wireless temperature sensor [J]. Acta Mechanica Sinica, 2021, 37(6): 895-901.
[38]	NOVAIS S, NASCIMENTO M, GRANDE L, et al. Internal and External Temperature Monitoring of a Li-Ion Battery with Fiber Bragg Grating Sensors [J]. Sensors, 2016, 16(9).
[39]	HUANG J, ALBERO BLANQUER L, BONEFACINO J, et al. Operando decoding of chemical and thermal events in commercial Na(Li)-ion cells via optical sensors [J]. Nature Energy, 2020, 5(9): 674-83.
[40]	SRINIVASAN R, CARKHUFF B G, BUTLER M H, et al. Instantaneous measurement of the internal temperature in lithium-ion rechargeable cells [J]. Electrochimica Acta, 2011, 56(17): 6198-204.
[41]	SCHMIDT J P, ARNOLD S, LOGES A, et al. Measurement of the internal cell temperature via impedance: Evaluation and application of a new method [J]. Journal of Power Sources, 2013, 243: 110-7.
[42]	OUYANG K, FAN Y, YAZDI M, et al. Data-driven-based internal temperature estimation for lithium-ion battery under variant state-of-charge via electrochemical impedance spectroscopy [J]. Energy Technology, 2022, 10(3).
[43]	MC CARTHY K, 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.
[44]	SPINNER N S, LOVE C T, ROSE-PEHRSSON S L, et al. Expanding the operational limits of the single-point impedance diagnostic for internal temperature monitoring of lithium-ion batteries [J]. Electrochimica Acta, 2015, 174: 488-93.
[45]	MC CARTHY K, 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.
[46]	DONG M, LI X, YANG Z, et al. State of health (SOH) assessment for LIBs based on characteristic electrochemical impedance [J]. Journal of Power Sources, 2024, 603.
[47]	EZAHEDI S E, KHARRICH M, KIM J. Multi-cell sensorless internal temperature estimation based on electrochemical impedance spectroscopy with Gaussian process regression for lithium-ion batteries safety [J]. Journal of Energy Storage, 2024.
[48]	WANG L, LU D, SONG M, et al. Instantaneous estimation of internal temperature in lithium-ion battery by impedance measurement [J]. International Journal of Energy Research, 2020, 44(4): 3082-97.
[49]	BHOIR S S, THENAISIE G, BRIVIO C, et al. Li-ion cells internal temperature estimation using medium-frequency measurements of impedance argument [J]. Journal of Energy Storage, 2024.
[50]	YANG R, LI K, XIE Y, et al. A phase-based method for estimating the internal temperature of solid-state battery [J]. Journal of Energy Storage, 2024, 85.
[51]	RAIJMAKERS L H J, DANILOV D L, LAMMEREN J P M V, et al. Non-Zero Intercept Frequency: An Accurate Method to Determine the Integral Temperature of Li-Ion Batteries [J]. IEEE Transactions on Industrial Electronics, 2016, 63(5): 3168-78.
[52]	RAIJMAKERS L H J, DANILOV D L, VAN LAMMEREN J P M, et al. Sensorless battery temperature measurements based on electrochemical impedance spectroscopy [J]. Journal of Power Sources, 2014, 247: 539-44.
[53]	LI J, LI T, QIAO Y, et al. Internal temperature estimation method for lithium-ion battery based on multi-frequency imaginary part impedance and GPR model[J]. Journal of Energy Storage, 2025, 118: 116287.
[54]	冯旭宁. 车用锂离子动力电池热失控诱发与扩展机理、建模与防控[D]. 北京: 清华大学, 2016.
	FENG X N. Thermal runaway initiation and propagation of lithium-ion traction battery for electric vehicle: test, modeling and prevention[D]. Beijing: Tsinghua University, 2016.
[55]	LIU L, FENG X, RAHE C, et al. Internal short circuit evaluation and corresponding failure mode analysis for lithium-ion batteries [J]. Journal of Energy Chemistry, 2021.
[56]	耿莉敏, 赵扬, 高楠等. 锂离子电池内短路形成机理及检测方法综述[J]. 汽车工程学报, 2023, 13(4): 481-495.
	GENG L M, ZHAO Y, GAO N, et al. Review of short-circuit formation mechanisms and diagnostic methods in lithium-ion batteries[J]. Chinese Journal of Automotive Engineering, 2023, 13(4): 481-495.
[57]	VYAS M, PAREEK K, SAPRE S, et al. Single point diagnosis of short circuit abuse condition in lithium-ion battery through impedance data [J]. International Journal of Energy Research, 2021.
[58]	LIU Y, XIE J. Failure study of commercial LiFePO4cells in overcharge conditions using electrochemical impedance spectroscopy [J]. Journal of The Electrochemical Society, 2015, 162(10): A2208-A17.
[59]	张闯, 王泽山, 刘素贞等. 基于电化学阻抗谱的锂离子电池过放电诱发内短路的检测方法[J]. 电工技术学报, 2023, 38(23): 6278-6291.
	ZHANG C, WANG Z S, LIU S Z, et al. Detection method of overdischarge-induced internal short circuit in lithium-ion batteries based on electrochemical impedance spectroscopy[J]. Transactions of China ElectrotechnicalL Society, 2023, 38(23): 6278-6291.
[60]	张闯, 杨浩, 刘素贞等. 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 C, YANG H, LIU S Z, et al. Research on overdischarge-induced internal short circuit identification of lithium-ion battery based on impedance online measurement[J]. Transactions of China ElectrotechnicalL Society, 2024, 39(6): 1656-1670.
[61]	THANGAVEL N K, MUNDHE S, ISLAM M M, et al. Probing of internal short circuit in lithium-ion pouch cells by electrochemical impedance spectroscopy under mechanical abusive conditions [J]. Journal of The Electrochemical Society, 2021.
[62]	KONG X, PLETT G L, SCOTT TRIMBOLI M, et al. Pseudo-two-dimensional model and impedance diagnosis of micro internal short circuit in lithium-ion cells [J]. Journal of Energy Storage, 2019.
[63]	FEAR C, ADHIKARY T, CARTER R, et al. In operando detection of the onset and mapping of lithium plating regimes during fast charging of lithium-ion batteries [J]. ACS Applied Materials & Interfaces, 2020, 12(27): 30438-48.
[64]	XU L, YANG Y, XIAO Y, et al. In-situ determination of onset lithium plating for safe Li-ion batteries [J]. Journal of Energy Chemistry, 2022, 67: 255-62.
[65]	KATZER F, DANZER M A. Analysis and detection of lithium deposition after fast charging of lithium-ion batteries by investigating the impedance relaxation [J]. Journal of Power Sources, 2021, 503.
[66]	GAO T, HAN Y, FRAGGEDAKIS D, et al. Interplay of lithium intercalation and plating on a single graphite particle [J]. Joule, 2021, 5(2): 393-414.
[67]	XU L, XIAO Y, YANG Y, et al. Operando quantified lithium plating determination enabled by dynamic capacitance measurement in working li‐ion batteries [J]. Angewandte Chemie International Edition, 2022, 61(39).
[68]	SCHINDLER S, BAUER M, PETZL M, et al. Voltage relaxation and impedance spectroscopy as in-operando methods for the detection of lithium plating on graphitic anodes in commercial lithium-ion cells [J]. Journal of Power Sources, 2016, 304: 170-80.
[69]	STRAßER A, ADAM A, LI J. In operando detection of Lithium plating via electrochemical impedance spectroscopy for automotive batteries [J]. Journal of Power Sources, 2023, 580.
[70]	KOSEOGLOU M, TSIOUMAS E, FERENTINOU D, et al. Lithium plating detection using dynamic electrochemical impedance spectroscopy in lithium-ion batteries [J]. Journal of Power Sources, 2021, 512.
[71]	KOLETI U R, DINH T Q, MARCO J. A new on-line method for lithium plating detection in lithium-ion batteries [J]. Journal of Power Sources, 2020, 451.
[72]	SUN T, LI Z, ZHU G, et al. Impedance-based online detection of lithium plating for lithium-ion batteries: Mechanism and sensitivity analysis [J]. Electrochimica Acta, 2024, 496.
[73]	ISHIKAWA K, KOMAGATA S, MORIMOTO R, et al. High-frequency electrochemical impedance spectroscopy for detecting li deposition toward assessing thermal stability in libs[J]. ECS Transactions, 2024, 113(1): 9.
[74]	LENG X, LI Y, XU G, et al. Prediction of lithium-ion battery internal temperature using the imaginary part of electrochemical impedance spectroscopy[J]. International Journal of Heat and Mass Transfer, 2025, 240: 126664.
[75]	HUSSEIN A A, FARDOUN A A. An adaptive sensorless measurement technique for internal temperature of Li-ion batteries using impedance phase spectroscopy[J]. IEEE Transactions on Industry Applications, 2020, 56(3): 3043-3051.
[76]	CHEN L R, WEI S H, HSIEH H Y, et al. Estimation of battery internal temperature using electrochemical impedance spectroscopy[J]. International Journal of Electrochemical Science, 2025: 101070.
[77]	QIAN G, ZHU Z, SUN Y, et al. Cross-capacity internal temperature estimation in lithium-ion batteries using multiple impedance features from the negative electrode[J]. Applied Energy, 2025, 396: 126259.
[78]	李晓枫, 常益, 杨章等. 应用阻抗谱的锂电池模组早期内短路故障诊断[J]. 西安交通大学学报, 2024, 58(11):1-13
	LI X F, CHANG Y, YANG Z, et al. Early diagnosis of internal short circuit faults in lthium battern modules using impedance spectroscopy[J]. Journal of Xi'an Jiaotong University, 2024, 58(11):1-13
[79]	RICHARDSON R R, IRELAND P T, HOWEY D A. Battery internal temperature estimation by combined impedance and surface temperature measurement [J]. Journal of Power Sources, 2014, 265: 254-61.
[80]	WANG Z, ZHU L, LIU J, et al. Gas sensing technology for the detection and early warning of battery thermal runaway: a review [J]. Energy & Fuels, 2022, 36(12): 6038-57.
[81]	KAUR P, BAGCHI S, POL V G, et al. Early detection of mixed volatile organic compounds to circumvent calamitous li-ion battery thermal runaway [J]. The Journal of Physical Chemistry C, 2023.
[82]	KAUR P, BAGCHI S, GRIBBLE D, et al. Impedimetric chemosensing of volatile organic compounds released from li-ion batteries [J]. ACS Sensors, 2022.
[83]	CAI T, VALECHA P, TRAN V, et al. Detection of Li-ion battery failure and venting with Carbon Dioxide sensors [J]. eTransportation, 2021, 7.
[84]	SCHMIEGEL J-P, LEIßING M, WEDDELING F, et al. Novel in situ gas formation analysis technique using a multilayer pouch bag lithium ion cell equipped with gas sampling port [J]. Journal of The Electrochemical Society, 2020, 167(6).
[85]	LYU S, LI N, SUN L, et al. Rapid operando gas monitor for commercial lithium ion batteries: Gas evolution and relation with electrode materials [J]. Journal of Energy Chemistry, 2022, 72: 14-25.
[86]	SUN J, LI J G, ZHOU T, et al. Toxicity, a serious concern of thermal runaway from commercial Li-ion battery [J]. Nano Energy, 2016, 27: 313-9.
[87]	TORRES-CASTRO L, BATES A M, JOHNSON N B, et al. Early detection of li-ion battery thermal runaway using commercial diagnostic technologies [J]. Journal of The Electrochemical Society, 2024, 171(2).

类型	预警/监测指标		变化机制	文献
内部温度	阻抗虚部	中频、高频，预测温度范围广	电池内部电化学反应动力学和离子传输过程随温度发生变化，其中中频区阻抗受SOC影响较小，常用于内部温度监测；通过阿伦尼乌斯方程、高斯过程回归、线性、多项式等建立阻抗参数与内部温度之间的关系	[42, 44, 53, 74, 76]
	阻抗实部	预测温度范围较小，不适用于热失控预警		[41, 76]
	相位角	中频		[49, 76, 77]
	阻抗幅值	中频		[76]
	非/零截距频率	/		[51, 75]
	阻抗幅值相位角	中频		[31, 47, 76]
内短路	阻抗实部	过充：增大，且随内短路程度加深而增加	电极材料损坏，电解液分解形成更多导电性差的成分，同时SEI膜结构和组成发生变化	[57, 58, 78]
	阻抗实部	机械滥用：先增加后减小	电池在机械滥用条件下受到挤压，电池组件建距离改变，接触面积减小；随着程度加深，电极直接接触，活性材料发生重构，电荷转移过程发生变化	[30, 61]
	阻抗模值	过放电：针状变化	SEI膜的持续分解和铜集流体溶解前电极材料的结构损伤，使得电池内部状态不稳定，表现为阻抗的急剧变化	[60]
锂沉积	阻抗实部	下降	过充、高倍率或低温充电析锂导致内部电流路径发生变化，形成新的并联阻抗分支	[69, 70, 73]
锂沉积	阻抗模值	下降	过充、高倍率或低温充电析锂导致内部电流路径发生变化，形成新的并联阻抗分支	[71, 72]