IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v377y2025ipas030626192401849x.html
   My bibliography  Save this article

Warning lithium-ion battery thermal runaway with 4-min relaxation voltage

Author

Listed:
  • Yu, Kun
  • Liu, Peng
  • Xu, Bin
  • Li, Jinzhong
  • Wang, Xinyu
  • Zhang, Heng
  • Mao, Lei

Abstract

The continued growth of installed lithium-ion battery capacity is accelerating low-carbon energy constructions. However, the concern about battery thermal runaway (TR) spreads due to multi-scale applications of both nickel‑cobalt‑manganese (NCM) ternary lithium-ion batteries and lithium‑iron-phosphate (LFP) batteries, which raises the necessity of identifying battery internal short circuit (ISC) and warning TR. Although various TR warning methods have been proposed, the extra facility requirement and large computational cost hinder their applications in commercial battery scenarios. In this study, focusing on warning TR through lithium-ion battery ISC identification, we derive the correlation between relaxation voltages of ISC battery and normal battery, then a simple but effective approach, i.e., using battery relaxation voltage to obtain battery short-circuit resistance evolution during TR developing process, is proposed to warn TR in both NCM and LFP batteries. With battery ISC substitute experiments and mechanical abuse tests, the performance of proposed method in four brands batteries with different electrode materials and shapes is validated. Furthermore, the proposed method shows great adaptations to ambient temperature and current rate, which can realize ISC detection and TR warning with 4-min relaxation information from practical electric vehicles and energy storage stations.

Suggested Citation

  • Yu, Kun & Liu, Peng & Xu, Bin & Li, Jinzhong & Wang, Xinyu & Zhang, Heng & Mao, Lei, 2025. "Warning lithium-ion battery thermal runaway with 4-min relaxation voltage," Applied Energy, Elsevier, vol. 377(PA).
  • Handle: RePEc:eee:appene:v:377:y:2025:i:pa:s030626192401849x
    DOI: 10.1016/j.apenergy.2024.124466
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030626192401849X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2024.124466?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Qiao, Dongdong & Wang, Xueyuan & Lai, Xin & Zheng, Yuejiu & Wei, Xuezhe & Dai, Haifeng, 2022. "Online quantitative diagnosis of internal short circuit for lithium-ion batteries using incremental capacity method," Energy, Elsevier, vol. 243(C).
    2. Song, Youngbin & Park, Shina & Kim, Sang Woo, 2023. "Model-free quantitative diagnosis of internal short circuit for lithium-ion battery packs under diverse operating conditions," Applied Energy, Elsevier, vol. 352(C).
    3. Arno Kwade & Wolfgang Haselrieder & Ruben Leithoff & Armin Modlinger & Franz Dietrich & Klaus Droeder, 2018. "Current status and challenges for automotive battery production technologies," Nature Energy, Nature, vol. 3(4), pages 290-300, April.
    4. Wenxin Mei & Zhi Liu & Chengdong Wang & Chuang Wu & Yubin Liu & Pengjie Liu & Xudong Xia & Xiaobin Xue & Xile Han & Jinhua Sun & Gaozhi Xiao & Hwa-yaw Tam & Jacques Albert & Qingsong Wang & Tuan Guo, 2023. "Operando monitoring of thermal runaway in commercial lithium-ion cells via advanced lab-on-fiber technologies," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    5. Zachary A. Needell & James McNerney & Michael T. Chang & Jessika E. Trancik, 2016. "Potential for widespread electrification of personal vehicle travel in the United States," Nature Energy, Nature, vol. 1(9), pages 1-7, September.
    6. Dai, Haifeng & Xu, Tianjiao & Zhu, Letao & Wei, Xuezhe & Sun, Zechang, 2016. "Adaptive model parameter identification for large capacity Li-ion batteries on separated time scales," Applied Energy, Elsevier, vol. 184(C), pages 119-131.
    7. T. M. M. Heenan & I. Mombrini & A. Llewellyn & S. Checchia & C. Tan & M. J. Johnson & A. Jnawali & G. Garbarino & R. Jervis & D. J. L. Brett & M. Michiel & P. R. Shearing, 2023. "Mapping internal temperatures during high-rate battery applications," Nature, Nature, vol. 617(7961), pages 507-512, May.
    8. Wei, Gang & Huang, Ranjun & Zhang, Guangxu & Jiang, Bo & Zhu, Jiangong & Guo, Yangyang & Han, Guangshuai & Wei, Xuezhe & Dai, Haifeng, 2023. "A comprehensive insight into the thermal runaway issues in the view of lithium-ion battery intrinsic safety performance and venting gas explosion hazards," Applied Energy, Elsevier, vol. 349(C).
    9. Liu, Lishuo & Feng, Xuning & Zhang, Mingxuan & Lu, Languang & Han, Xuebing & He, Xiangming & Ouyang, Minggao, 2020. "Comparative study on substitute triggering approaches for internal short circuit in lithium-ion batteries," Applied Energy, Elsevier, vol. 259(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hou, Liubin & Dong, Ao & Ma, Ruifei & Lin, Hejie & Deng, Yelin, 2024. "The sensitive detection of the early-stage internal short circuit triggered by lithium plating through the simplified electrochemical model at various working conditions," Energy, Elsevier, vol. 304(C).
    2. Gao, Renjing & Liang, Hong & Zhang, Yunfei & Zhao, Haihe & Chen, Zeyu, 2024. "Characterization of lithium-ion batteries after suffering micro short circuit induced by mechanical stress abuse," Applied Energy, Elsevier, vol. 374(C).
    3. Pan, Yue & Kong, Xiangdong & Yuan, Yuebo & Sun, Yukun & Han, Xuebing & Yang, Hongxin & Zhang, Jianbiao & Liu, Xiaoan & Gao, Panlong & Li, Yihui & Lu, Languang & Ouyang, Minggao, 2023. "Detecting the foreign matter defect in lithium-ion batteries based on battery pilot manufacturing line data analyses," Energy, Elsevier, vol. 262(PB).
    4. Yang, Qifan & Sun, Jinlei & Kang, Yongzhe & Ma, Hongzhong & Duan, Dawei, 2023. "Internal short circuit detection and evaluation in battery packs based on transformation matrix and an improved state-space model," Energy, Elsevier, vol. 276(C).
    5. Li, Kuijie & Gao, Xinlei & Wang, Shengshi & Peng, Shijian & Zhang, Weixin & Wu, Weixiong & Wang, Huizhi & Liu, Peng & Han, Xuebing & Cao, Yuan-cheng & Wen, Jinyu & Cheng, Shijie & Ouyang, Minggao, 2024. "Comparative analysis of multidimensional signals evolution in prismatic and pouch LiFePO4 batteries under thermal abuse," Applied Energy, Elsevier, vol. 372(C).
    6. Shi, Haotian & Wang, Shunli & Huang, Qi & Fernandez, Carlos & Liang, Jianhong & Zhang, Mengyun & Qi, Chuangshi & Wang, Liping, 2024. "Improved electric-thermal-aging multi-physics domain coupling modeling and identification decoupling of complex kinetic processes based on timescale quantification in lithium-ion batteries," Applied Energy, Elsevier, vol. 353(PB).
    7. Ma, Zhikai & Huo, Qian & Wang, Wei & Zhang, Tao, 2023. "Voltage-temperature aware thermal runaway alarming framework for electric vehicles via deep learning with attention mechanism in time-frequency domain," Energy, Elsevier, vol. 278(C).
    8. Wenxian Duan & Chuanxue Song & Silun Peng & Feng Xiao & Yulong Shao & Shixin Song, 2020. "An Improved Gated Recurrent Unit Network Model for State-of-Charge Estimation of Lithium-Ion Battery," Energies, MDPI, vol. 13(23), pages 1-19, December.
    9. Yixin Liu & Ao Lei & Chunyang Yu & Tengfei Huang & Yuanbin Yu, 2024. "An Improved Collaborative Estimation Method for Determining The SOC and SOH of Lithium-Ion Power Batteries for Electric Vehicles," Energies, MDPI, vol. 17(13), pages 1-22, July.
    10. Abdollahifar, M. & Molaiyan, P. & Lassi, U. & Wu, N.L. & Kwade, A., 2022. "Multifunctional behaviour of graphite in lithium–sulfur batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    11. Daniels, Rojo Kurian & Kumar, Vikas & Chouhan, Satyendra Singh & Prabhakar, Aneesh, 2024. "Thermal runaway fault prediction in air-cooled lithium-ion battery modules using machine learning through temperature sensors placement optimization," Applied Energy, Elsevier, vol. 355(C).
    12. Neaimeh, Myriam & Salisbury, Shawn D. & Hill, Graeme A. & Blythe, Philip T. & Scoffield, Don R. & Francfort, James E., 2017. "Analysing the usage and evidencing the importance of fast chargers for the adoption of battery electric vehicles," Energy Policy, Elsevier, vol. 108(C), pages 474-486.
    13. Entwistle, Jake & Ge, Ruihuan & Pardikar, Kunal & Smith, Rachel & Cumming, Denis, 2022. "Carbon binder domain networks and electrical conductivity in lithium-ion battery electrodes: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    14. E, Jiaqiang & Xiao, Hanxu & Tian, Sicheng & Huang, Yuxin, 2024. "A comprehensive review on thermal runaway model of a lithium-ion battery: Mechanism, thermal, mechanical, propagation, gas venting and combustion," Renewable Energy, Elsevier, vol. 229(C).
    15. Gutsch, Moritz & Leker, Jens, 2024. "Costs, carbon footprint, and environmental impacts of lithium-ion batteries – From cathode active material synthesis to cell manufacturing and recycling," Applied Energy, Elsevier, vol. 353(PB).
    16. Zhang, Yue & Song, Laifeng & Tian, Jiamin & Mei, Wenxin & Jiang, Lihua & Sun, Jinhua & Wang, Qingsong, 2024. "Modeling the propagation of internal thermal runaway in lithium-ion battery," Applied Energy, Elsevier, vol. 362(C).
    17. Wei, Gang & Huang, Ranjun & Zhang, Guangxu & Jiang, Bo & Zhu, Jiangong & Guo, Yangyang & Han, Guangshuai & Wei, Xuezhe & Dai, Haifeng, 2023. "A comprehensive insight into the thermal runaway issues in the view of lithium-ion battery intrinsic safety performance and venting gas explosion hazards," Applied Energy, Elsevier, vol. 349(C).
    18. Zia Wadud & Muhammad Adeel & Jillian Anable, 2024. "Understanding the large role of long-distance travel in carbon emissions from passenger travel," Nature Energy, Nature, vol. 9(9), pages 1129-1138, September.
    19. Wei, Zhongbao & Zhao, Jiyun & Ji, Dongxu & Tseng, King Jet, 2017. "A multi-timescale estimator for battery state of charge and capacity dual estimation based on an online identified model," Applied Energy, Elsevier, vol. 204(C), pages 1264-1274.
    20. Jin, Chengwei & Xu, Jun & Jia, Zhenyu & Xie, Yanmin & Zhang, Xianggong & Mei, Xuesong, 2024. "Expansion force signal based rapid detection of early thermal runaway for pouch batteries," Energy, Elsevier, vol. 312(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:377:y:2025:i:pa:s030626192401849x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.