IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v187y2023ics136403212300597x.html
   My bibliography  Save this article

Active and passive safety enhancement for batteries from force perspective

Author

Listed:
  • Chen, Siqi
  • Wei, Xuezhe
  • Zhang, Guangxu
  • Rui, Xinyu
  • Xu, Chengshan
  • Feng, Xuning
  • Dai, Haifeng
  • Ouyang, Minggao

Abstract

Thermal runaway (TR) has become a critical issue for Li-ion battery applications in electric vehicles and energy storage stations. To address this issue, early warning and thermal runaway propagation (TRP) mitigation are significant for the active and passive safety of the battery system, respectively. This study proposes the expansion force as a reliable warning signal, which is proven to provide more interval (>500 s) for escape and rescue compared with voltage and temperature signals. Besides, the TR expansion force changing mechanism due to thermal expansion, gas generation/accumulation, and venting is investigated. Furthermore, the TRP expansion force and deformation changing mechanism is explained from the perspective of expansion, squeeze, and venting. The TRP debris deformation trend is verified through mechanical modeling. The maximum TR expansion force increment (ΔFmax)-capacity (Q) equalization and ΔFmax-cell index equations are proposed based on the TR/TRP tests of three types of prismatic batteries. Moreover, a TRP mitigation structure is proposed to amplify the TR expansion force, which is validated to effectively amplify the force, causing the mechanical destruction of the in-line module holder. A TRP mitigation test proves that the first TR cell capsizes the module holder to hinder the heat transfer between the front/back surfaces of the prismatic batteries when the TR expansion force exceeds the preload. Without enough heat transfer, the TR of the following battery cells cannot be triggered even under jet fire impact. This study guides the active and passive safety design for the prismatic battery system.

Suggested Citation

  • Chen, Siqi & Wei, Xuezhe & Zhang, Guangxu & Rui, Xinyu & Xu, Chengshan & Feng, Xuning & Dai, Haifeng & Ouyang, Minggao, 2023. "Active and passive safety enhancement for batteries from force perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
  • Handle: RePEc:eee:rensus:v:187:y:2023:i:c:s136403212300597x
    DOI: 10.1016/j.rser.2023.113740
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S136403212300597X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.rser.2023.113740?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. Jiang, Z.Y. & Qu, Z.G. & Zhang, J.F. & Rao, Z.H., 2020. "Rapid prediction method for thermal runaway propagation in battery pack based on lumped thermal resistance network and electric circuit analogy," Applied Energy, Elsevier, vol. 268(C).
    2. Feng, Xuning & Weng, Caihao & Ouyang, Minggao & Sun, Jing, 2016. "Online internal short circuit detection for a large format lithium ion battery," Applied Energy, Elsevier, vol. 161(C), pages 168-180.
    3. Zhang, Guangxu & Wei, Xuezhe & Tang, Xuan & Zhu, Jiangong & Chen, Siqi & Dai, Haifeng, 2021. "Internal short circuit mechanisms, experimental approaches and detection methods of lithium-ion batteries for electric vehicles: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chen, Siqi & Wei, Xuezhe & Zhu, Zhehui & Wu, Hang & Ou, Yuxin & Zhang, Guangxu & Wang, Xueyuan & Zhu, Jiangong & Feng, Xuning & Dai, Haifeng & Ouyang, Minggao, 2024. "Thermal runaway front propagation characteristics, modeling and judging criteria for multi-jelly roll prismatic lithium-ion battery applications," Renewable Energy, Elsevier, vol. 231(C).
    2. Li, Kuijie & Gao, Xinlei & Peng, Shijian & Wang, Shengshi & Zhang, Weixin & Liu, Peng & Wu, Weixiong & Wang, Huizhi & Wang, Yu & Feng, Xuning & Cao, Yuan-cheng & Wen, Jinyu & Cheng, Shijie & Ouyang, M, 2024. "A comparative study on multidimensional signal evolution during thermal runaway of lithium-ion batteries with various cathode materials," Energy, Elsevier, vol. 300(C).
    3. 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).
    4. Yi, Yahui & Xia, Chengyu & Shi, Lei & Meng, Leifeng & Chi, Qifu & Qian, Liqin & Ma, Tiancai & Chen, Siqi, 2024. "Lithium-ion battery expansion mechanism and Gaussian process regression based state of charge estimation with expansion characteristics," Energy, Elsevier, vol. 292(C).

    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. Qiao, Dongdong & Wei, Xuezhe & Fan, Wenjun & Jiang, Bo & Lai, Xin & Zheng, Yuejiu & Tang, Xiaolin & Dai, Haifeng, 2022. "Toward safe carbon–neutral transportation: Battery internal short circuit diagnosis based on cloud data for electric vehicles," Applied Energy, Elsevier, vol. 317(C).
    2. 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).
    3. Mohammadmahdi Ghiji & Vasily Novozhilov & Khalid Moinuddin & Paul Joseph & Ian Burch & Brigitta Suendermann & Grant Gamble, 2020. "A Review of Lithium-Ion Battery Fire Suppression," Energies, MDPI, vol. 13(19), pages 1-30, October.
    4. Cui, Binghan & Wang, Han & Li, Renlong & Xiang, Lizhi & Zhao, Huaian & Xiao, Rang & Li, Sai & Liu, Zheng & Yin, Geping & Cheng, Xinqun & Ma, Yulin & Huo, Hua & Zuo, Pengjian & Lu, Taolin & Xie, Jingyi, 2024. "Ultra-early prediction of lithium-ion battery performance using mechanism and data-driven fusion model," Applied Energy, Elsevier, vol. 353(PA).
    5. 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).
    6. Xu, Jun & Liu, Binghe & Wang, Xinyi & Hu, Dayong, 2016. "Computational model of 18650 lithium-ion battery with coupled strain rate and SOC dependencies," Applied Energy, Elsevier, vol. 172(C), pages 180-189.
    7. 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).
    8. Deng, Jian & Huang, Qiqiu & Li, Xinxi & Zhang, Guoqing & Li, Canbing & Li, Songbo, 2024. "Influence mechanism of battery thermal management with flexible flame retardant composite phase change materials by temperature aging," Renewable Energy, Elsevier, vol. 222(C).
    9. Yang, Ruixin & Xiong, Rui & Ma, Suxiao & Lin, Xinfan, 2020. "Characterization of external short circuit faults in electric vehicle Li-ion battery packs and prediction using artificial neural networks," Applied Energy, Elsevier, vol. 260(C).
    10. Wang, Gongquan & Kong, Depeng & Ping, Ping & He, Xiaoqin & Lv, Hongpeng & Zhao, Hengle & Hong, Wanru, 2023. "Modeling venting behavior of lithium-ion batteries during thermal runaway propagation by coupling CFD and thermal resistance network," Applied Energy, Elsevier, vol. 334(C).
    11. Xinwei Cong & Caiping Zhang & Jiuchun Jiang & Weige Zhang & Yan Jiang & Linjing Zhang, 2021. "A Comprehensive Signal-Based Fault Diagnosis Method for Lithium-Ion Batteries in Electric Vehicles," Energies, MDPI, vol. 14(5), pages 1-21, February.
    12. Yu, Quanqing & Dai, Lei & Xiong, Rui & Chen, Zeyu & Zhang, Xin & Shen, Weixiang, 2022. "Current sensor fault diagnosis method based on an improved equivalent circuit battery model," Applied Energy, Elsevier, vol. 310(C).
    13. 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).
    14. Jin, Changyong & Sun, Yuedong & Wang, Huaibin & Zheng, Yuejiu & Wang, Shuyu & Rui, Xinyu & Xu, Chengshan & Feng, Xuning & Wang, Hewu & Ouyang, Minggao, 2022. "Heating power and heating energy effect on the thermal runaway propagation characteristics of lithium-ion battery module: Experiments and modeling," Applied Energy, Elsevier, vol. 312(C).
    15. 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).
    16. Bingxiang Sun & Xianjie Qi & Donglin Song & Haijun Ruan, 2023. "Review of Low-Temperature Performance, Modeling and Heating for Lithium-Ion Batteries," Energies, MDPI, vol. 16(20), pages 1-37, October.
    17. Chen, Mingyi & Yu, Yue & Ouyang, Dongxu & Weng, Jingwen & Zhao, Luyao & Wang, Jian & Chen, Yin, 2024. "Research progress of enhancing battery safety with phase change materials," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    18. Chen, Zeyu & Zhang, Bo & Xiong, Rui & Shen, Weixiang & Yu, Quanqing, 2021. "Electro-thermal coupling model of lithium-ion batteries under external short circuit," Applied Energy, Elsevier, vol. 293(C).
    19. Zhang, Guangxu & Wei, Xuezhe & Tang, Xuan & Zhu, Jiangong & Chen, Siqi & Dai, Haifeng, 2021. "Internal short circuit mechanisms, experimental approaches and detection methods of lithium-ion batteries for electric vehicles: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 141(C).
    20. Ouyang, Nan & Zhang, Wencan & Yin, Xiuxing & Li, Xingyao & Xie, Yi & He, Hancheng & Long, Zhuoru, 2023. "A data-driven method for predicting thermal runaway propagation of battery modules considering uncertain conditions," Energy, Elsevier, vol. 273(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:rensus:v:187:y:2023:i:c:s136403212300597x. 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/600126/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.