应用阻抗谱的锂电池模组早期内短路故障诊断

李晓枫; 常益; 杨章; 刘王泽宇; 董明; 雷万钧; 任明; 张崇兴; 王若谷; 郭安祥

doi:10.7652/xjtuxb202411001

您当前的位置：

首页 >

文章列表页 >

应用阻抗谱的锂电池模组早期内短路故障诊断

专题电动车辆先进电池管理 | 更新时间：2025-07-25

- 应用阻抗谱的锂电池模组早期内短路故障诊断
- Early Diagnosis of Internal Short Circuit Faults in Lithium Battery Modules Using Impedance Spectroscopy
- 西安交通大学学报 2024年58卷第11期页码：1-13
- 作者机构：
  
  1. 西安交通大学电工材料电气绝缘全国重点实验室,西安,710048
  2. 国网陕西省电力有限公司电力科学研究院,西安,710005
- 作者简介：
  
  : 2024-04-21。作者简介: 李晓枫(2000—),男,硕士生
  董明(通信作者),男,教授,博士生导师。基金项目: 国家电网公司总部科技资助项目(4000-202499063A-1-1-ZN)。
- 基金信息：
  
  : 2024-04-21。作者简介: 李晓枫(2000—),男,硕士生;董明(通信作者),男,教授,博士生导师。基金项目: 国家电网公司总部科技资助项目(4000-202499063A-1-1-ZN)。
- DOI：10.7652/xjtuxb202411001
  中图分类号： TM912
- 网络首发：2024-11-10，
  
  纸质出版：2024
- 稿件说明：
移动端阅览
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 Xiaofeng, CHANG Yi, YANG Zhang, et al. Early Diagnosis of Internal Short Circuit Faults in Lithium Battery Modules Using Impedance Spectroscopy[J]. 2024, 58(11): 1-13.
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. DOI： 10.7652/xjtuxb202411001.

LI Xiaofeng, CHANG Yi, YANG Zhang, et al. Early Diagnosis of Internal Short Circuit Faults in Lithium Battery Modules Using Impedance Spectroscopy[J]. 2024, 58(11): 1-13. DOI： 10.7652/xjtuxb202411001.

摘要

针对锂电池模组内部内短路故障单体诊断困难、检测效率低下的问题

提出应用电荷传递内阻和固体电解质界面膜内阻比值变化幅度的锂电池模组早期内短路故障诊断方法。所提方法基于电化学阻抗谱对内短路故障演化过程中锂电池内部电化学反应变化进行监测

利用弛豫时间分布方法针对阻抗谱特征进行量化分析。在阻抗谱由单体维度到模组维度正向推衍的基础上

筛选满荷电状态下电荷传递内阻和固体电解质界面膜内阻作为主要的评估指标

并根据阈值诊断模型搭建实验平台进行验证。实验结果表明:欧姆内阻和电荷传递内阻随着内短路故障程度的加深逐渐增大

固体电解质界面膜内阻整体呈现出逐渐减小的趋势; 当模组电池数控制在8节以下时

通过阈值诊断模型对存在故障单体的模组识别准确率可以达到100%。通过对阻抗谱特征的精确辨识与分析

该方法能够有效实现锂电池模组早期内短路故障的准确诊断。

Abstract

To address the challenges of diagnosing internal short-circuit faults in battery modules and improving detection efficiency

a diagnostic method for early detection of internal short-circuit faults in lithium battery modules is proposed. This method leverages the variations in the ratio of charge transfer resistance to solid electrolyte interface resistance. By using electrochemical impedance spectroscopy

the proposed method monitors changes in the internal electrochemical reactions of lithium batteries during the evolution of internal short circuit faults. Through the relaxation time distribution method

impedance spectrum characteristics are analyzed quantitatively. Based on the forward derivation of impedance spectra from the cell level to the module level

the charge transfer resistance and solid electrolyte interface film resistance at full charge state are selected as the main evaluation indicators

and an experimental platform is established for validation according to the threshold diagnosis model. The experimental results show that the Ohmic resistance and charge transfer resistance gradually increase with the severity of internal short circuit faults

while the overall trend of the solid electrolyte interface film resistance decreases gradually. When the number of cells in the module is controlled below 8

the accuracy of identifying faulty cells within the module through the threshold diagnosis model can reach 100%. Through precise identification and analysis of impedance spectrum characteristics

this method can effectively achieve accurate diagnosis of early internal short circuit faults in lithium battery modules.

关键词

Keywords

references

WU Feixiang, MAIER J, YU Yan. Guidelines and trends for next-generation rechargeable lithium and lithium-ion batteries [J]. Chemical Society Reviews, 2020, 49(5): 1569-1614.

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.

WU M S, LIN C Y, WANG Y Y, et al. Numerical simulation for the discharge behaviors of batteries in series and/or parallel-connected battery pack [J]. Electrochimica Acta, 2006, 52(3): 1349-1357.

ZHANG Guangxu, WEI Xuezhe, 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.

LU Languang, HAN Xuebing, LI Jianqiu, et al. A review on the key issues for lithium-ion battery management in electric vehicles [J]. Journal of Power Sources, 2013, 226: 272-288.

刘力硕, 张明轩, 卢兰光, 等. 锂离子电池内短路机理与检测研究进展 [J]. 储能科学与技术, 2018, 7(6): 1003-1015.

LIU Lishuo, ZHANG Mingxuan, LU Languang, et al. Recent progress on mechanism and detection of internal short circuit in lithium-ion batteries [J]. Energy Storage Science and Technology, 2018, 7(6): 1003-1015.

SAZHIN S V, DUFEK E J, GERING K L. Enhancing li-ion battery safety by early detection of nascent internal shorts [J]. Journal of the Electrochemical Society, 2017, 164(1): A6281-A6287.

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.

YANG Ruixin, XIONG Rui, SHEN Weixiang. On-board diagnosis of soft short circuit fault in lithium-ion battery packs for electric vehicles using an extended Kalman filter [J]. CSEE Journal of Power and Energy Systems, 2022, 8(1): 258-270.

杨晴霞, 曹秉刚, 徐俊, 等. 一种估计锂电池充电状态的分数阶阻抗模型 [J]. 西安交通大学学报, 2015, 49(8): 128-132.

YANG Qingxia, CAO Binggang, XU Jun, et al. A fractional impedance model for charge state estimation of lithium battery [J]. Journal of Xi'an Jiaotong University, 2015, 49(8): 128-132.

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): 9094-9104.

DONG Ming, FAN Wenjie, LIU Wangzeyu, et al. Health assessment of lithium-ion batteries based on characteristic frequency impedance [J]. Proceedings of the CSEE, 2022, 42(24): 9094-9104.

FU Yumeng, XU Jun, SHI Mingjie, et al. A fast impedance calculation-based battery state-of-health estimation method [J]. IEEE Transactions on Industrial Electronics, 2022, 69(7): 7019-7028.

赵云飞, 徐俊, 王海涛, 等. 采用Morlet小波的锂电池相对健康状态估计 [J]. 西安交通大学学报, 2019, 53(12): 97-103.

ZHAO Yunfei, XU Jun, WANG Haitao, et al. An estimation method of relative state-of-health for lithium-ion batteries using Morlet wavelet [J]. Journal of Xi'an Jiaotong University, 2019, 53(12): 97-103.

李凌峰, 宫明辉, 乌江. 采用多模模型的锂离子电池荷电状态联合估计算法 [J]. 西安交通大学学报, 2021, 55(1): 78-85.

LI Lingfeng, GONG Minghui, WU Jiang. Joint estimation algorithm for state of charge of li-ion battery with multi-mode model [J]. Journal of Xi'an Jiaotong University, 2021, 55(1): 78-85.

范文杰, 徐广昊, 于泊宁, 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): 3283-3292.

FAN Wenjie, XU Guanghao, YU Boning, et al. On-line estimation method for internal temperature of lithium-ion battery based on electrochemical impedance spectroscopy [J]. Proceedings of the CSEE, 2021, 41(9): 3283-3292.

XIAO Feiyu, XING Bobin, KONG Lingzhao, et al. Impedance-based diagnosis of internal mechanical damage for large-format lithium-ion batteries [J]. Energy, 2021, 230: 120855.

MA Ruifei, HE Jin, DENG Yelin. 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.

LIU Yadong, LIU Qi, LI Zhefei, et al. Failure study of commercial LiFePO4 cells in over-discharge conditions using electrochemical impedance spectroscopy [J]. Journal of the Electrochemical Society, 2014, 161(4): A620-A632.

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): 6279-6291.

ZHANG Chuang, WANG Zeshan, LIU Suzhen, et al. Detection method of overdischarge-induced internal short circuit in lithium-ion batteries based on electrochemical impedance spectroscopy [J]. Transactions of China Electrotechnical Society, 2023, 38(23): 6279-6291.

KIM G H, SMITH K, IRELAND J, et al. Fail-safe design for large capacity lithium-ion battery systems [J]. Journal of Power Sources, 2012, 210: 243-253.

王春林, 朱广焱, 张鹏博, 等. 弛豫时间分布函数应用于电化学阻抗谱分析 [J]. 电源技术, 2021, 45(12): 1569-1572.

WANG Chunlin, ZHU Guangyan, ZHANG Pengbo, et al. Application of distribution function of relaxation time in analyzing electrochemical impedance spectroscopy [J]. Chinese Journal of Power Sources, 2021, 45(12): 1569-1572.

IURILLI P, BRIVIO C, CARRILLO R E, et al. EIS2Mod: a DRT-based modeling framework for li-ion cells [J]. IEEE Transactions on Industry Applications, 2022, 58(2): 1429-1439.

HAHN M, SCHINDLER S, TRIEBS L C, et al. Optimized process parameters for a reproducible distribution of relaxation times analysis of electrochemical systems [J]. Batteries, 2019, 5(2): 43.

ZHOU Xing, HUANG Jun, PAN Zhengqiang, et al. Impedance characterization of lithium-ion batteries aging under high-temperature cycling: Importance of electrolyte-phase diffusion [J]. Journal of Power Sources, 2019, 426: 216-222.

CHEN Xiang, LI Liangyu, LIU Mengmeng, et al. Detection of lithium plating in lithium-ion batteries by distribution of relaxation times [J]. Journal of Power Sources, 2021, 496: 229867.

MANIKANDAN B, RAMAR V, YAP C, et al. Investigation of physico-chemical processes in lithium-ion batteries by deconvolution of electrochemical impedance spectra [J]. Journal of Power Sources, 2017, 361: 300-309.

SHAFIEI SABET P, WARNECKE A J, MEIER F, et al. Non-invasive yet separate investigation of anode/cathode degradation of lithium-ion batteries(nickel-cobalt-manganese vs. graphite)due to accelerated aging [J]. Journal of Power Sources, 2020, 449: 227369.

ZHANG Lingling, MA Yulin, CHENG Xinqun, et al. Capacity fading mechanism during long-term cycling of over-discharged LiCoO2/mesocarbon microbeads battery [J]. Journal of Power Sources, 2015, 293: 1006-1015.

KIM Y S, LEE S H, SON M Y, et al. Succinonitrile as a corrosion inhibitor of copper current collectors for overdischarge protection of lithium ion batteries [J]. ACS Applied Materials Interfaces, 2014, 6(3): 2039-2043.

GUO Rui, LU Languang, 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.

FEAR C, JUAREZ-ROBLES D, JEEVARAJANJ 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.

JUAREZ-ROBLES D, VYAS A A, FEAR C, et al. Overdischarge and aging analytics of li-ion cells [J]. Journal of the Electrochemical Society, 2020, 167(9): 090558.

庄全超, 徐守冬, 邱祥云, 等. 锂离子电池的电化学阻抗谱分析 [J]. 化学进展, 2010, 22(6): 1044-1057.

ZHUANG Quanchao, XU Shoudong, QIU Xiangyun, et al. Diagnosis of electrochemical impedance spectroscopy in lithium ion batteries [J]. Progress in Chemistry, 2010, 22(6): 1044-1057.

LI Huifang, GAO Junkui, ZHANG Shaoli. Effect of overdischarge on swelling and recharge performance of lithium ion cells [J]. Chinese Journal of Chemistry, 2008, 26(9): 1585-1588.

XIE Yuanyuan, KIM J, LEE M, et al. An impedance behavior study of commercial NCA cylindrical battery cells at different SOCs [J]. Journal of the Electrochemical Society, 2021, 168(9): 090548.

浏览量

下载量

CSCD

文章被引用时，请邮件提醒。

提交

工具集

关联资源

质子交换膜燃料电池在不同放电状态下的阻抗分析

采用Morlet小波的锂电池相对健康状态估计

冷库水平空气幕热湿阻隔性能数值模拟研究

多工况下离心压气机叶轮-机匣一体联合设计优化

超临界水异常区域热力学特性研究