IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v228y2018icp633-644.html
   My bibliography  Save this article

Model-based thermal runaway prediction of lithium-ion batteries from kinetics analysis of cell components

Author

Listed:
  • Ren, Dongsheng
  • Liu, Xiang
  • Feng, Xuning
  • Lu, Languang
  • Ouyang, Minggao
  • Li, Jianqiu
  • He, Xiangming

Abstract

Thermal runaway (TR) is a major safety concern in lithium-ion batteries. Model-based TR prediction is critically needed to optimize safety designs of cells. This paper presents a novel scheme for developing reliable battery TR model from kinetics analysis of cell components. First, differential scanning calorimetry (DSC) tests on the individual cell components and their mixtures are conducted to reveal the TR mechanism and characterize the exothermic reactions, of which the major six (such as the decomposition of solid electrolyte interface (SEI) film) are determined as the dominant heat sources. The kinetics parameters of each exothermic reactions are identified from the DSC tests results at variant heating rates using Kissinger’s method and nonlinear fitting method. A predictive battery TR model is established by superimposing the chemical kinetics equations of the six exothermic reactions. The model fits well with the adiabatic TR test results and the oven tests results of a 24 Ah lithium-ion battery, indicating that the model can well reflect the battery TR mechanism and be trusted to predict battery safety performance without assembling a real battery.

Suggested Citation

  • Ren, Dongsheng & Liu, Xiang & Feng, Xuning & Lu, Languang & Ouyang, Minggao & Li, Jianqiu & He, Xiangming, 2018. "Model-based thermal runaway prediction of lithium-ion batteries from kinetics analysis of cell components," Applied Energy, Elsevier, vol. 228(C), pages 633-644.
    • Handle: RePEc:eee:appene:v:228:y:2018:i:c:p:633-644
    DOI: 10.1016/j.apenergy.2018.06.126
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261918309954
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2018.06.126?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. Ping, Ping & Wang, Qingsong & Huang, Peifeng & Sun, Jinhua & Chen, Chunhua, 2014. "Thermal behaviour analysis of lithium-ion battery at elevated temperature using deconvolution method," Applied Energy, Elsevier, vol. 129(C), pages 261-273.
    2. Chen, Zeyu & Xiong, Rui & Lu, Jiahuan & Li, Xinggang, 2018. "Temperature rise prediction of lithium-ion battery suffering external short circuit for all-climate electric vehicles application," Applied Energy, Elsevier, vol. 213(C), pages 375-383.
    3. Feng, Xuning & He, Xiangming & Ouyang, Minggao & Lu, Languang & Wu, Peng & Kulp, Christian & Prasser, Stefan, 2015. "Thermal runaway propagation model for designing a safer battery pack with 25Ah LiNixCoyMnzO2 large format lithium ion battery," Applied Energy, Elsevier, vol. 154(C), pages 74-91.
    4. 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.
    5. Coman, Paul T. & Darcy, Eric C. & Veje, Christian T. & White, Ralph E., 2017. "Numerical analysis of heat propagation in a battery pack using a novel technology for triggering thermal runaway," Applied Energy, Elsevier, vol. 203(C), pages 189-200.
    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. Ding, Yin & Mu, Daobin & Wu, Borong & Wang, Rui & Zhao, Zhikun & Wu, Feng, 2017. "Recent progresses on nickel-rich layered oxide positive electrode materials used in lithium-ion batteries for electric vehicles," Applied Energy, Elsevier, vol. 195(C), pages 586-599.
    8. Ouyang, Minggao & Feng, Xuning & Han, Xuebing & Lu, Languang & Li, Zhe & He, Xiangming, 2016. "A dynamic capacity degradation model and its applications considering varying load for a large format Li-ion battery," Applied Energy, Elsevier, vol. 165(C), pages 48-59.
    9. Ping, Ping & Wang, Qingsong & Chung, Youngmann & Wen, Jennifer, 2017. "Modelling electro-thermal response of lithium-ion batteries from normal to abuse conditions," Applied Energy, Elsevier, vol. 205(C), pages 1327-1344.
    10. Zhao, Rui & Liu, Jie & Gu, Junjie, 2016. "Simulation and experimental study on lithium ion battery short circuit," Applied Energy, Elsevier, vol. 173(C), pages 29-39.
    11. Du, Jiuyu & Ouyang, Danhua, 2017. "Progress of Chinese electric vehicles industrialization in 2015: A review," Applied Energy, Elsevier, vol. 188(C), pages 529-546.
    12. Liu, Binghe & Yin, Sha & Xu, Jun, 2016. "Integrated computation model of lithium-ion battery subject to nail penetration," Applied Energy, Elsevier, vol. 183(C), pages 278-289.
    13. Huang, Peifeng & Ping, Ping & Li, Ke & Chen, Haodong & Wang, Qingsong & Wen, Jennifer & Sun, Jinhua, 2016. "Experimental and modeling analysis of thermal runaway propagation over the large format energy storage battery module with Li4Ti5O12 anode," Applied Energy, Elsevier, vol. 183(C), pages 659-673.
    14. Ye, Jiana & Chen, Haodong & Wang, Qingsong & Huang, Peifeng & Sun, Jinhua & Lo, Siuming, 2016. "Thermal behavior and failure mechanism of lithium ion cells during overcharge under adiabatic conditions," Applied Energy, Elsevier, vol. 182(C), pages 464-474.
    15. Ruiz, V. & Pfrang, A. & Kriston, A. & Omar, N. & Van den Bossche, P. & Boon-Brett, L., 2018. "A review of international abuse testing standards and regulations for lithium ion batteries in electric and hybrid electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P1), pages 1427-1452.
    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. Ren, Dongsheng & Feng, Xuning & Lu, Languang & He, Xiangming & Ouyang, Minggao, 2019. "Overcharge behaviors and failure mechanism of lithium-ion batteries under different test conditions," Applied Energy, Elsevier, vol. 250(C), pages 323-332.
    2. 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).
    3. Huang, Zonghou & Zhao, Chunpeng & Li, Huang & Peng, Wen & Zhang, Zheng & Wang, Qingsong, 2020. "Experimental study on thermal runaway and its propagation in the large format lithium ion battery module with two electrical connection modes," Energy, Elsevier, vol. 205(C).
    4. 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).
    5. Chen, Jie & Ren, Dongsheng & Hsu, Hungjen & Wang, Li & He, Xiangming & Zhang, Caiping & Feng, Xuning & Ouyang, Minggao, 2021. "Investigating the thermal runaway features of lithium-ion batteries using a thermal resistance network model," Applied Energy, Elsevier, vol. 295(C).
    6. 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).
    7. Gandoman, Foad H. & Jaguemont, Joris & Goutam, Shovon & Gopalakrishnan, Rahul & Firouz, Yousef & Kalogiannis, Theodoros & Omar, Noshin & Van Mierlo, Joeri, 2019. "Concept of reliability and safety assessment of lithium-ion batteries in electric vehicles: Basics, progress, and challenges," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    8. Liu, Binghe & Yin, Sha & Xu, Jun, 2016. "Integrated computation model of lithium-ion battery subject to nail penetration," Applied Energy, Elsevier, vol. 183(C), pages 278-289.
    9. 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).
    10. Zhu, Juner & Zhang, Xiaowei & Luo, Hailing & Sahraei, Elham, 2018. "Investigation of the deformation mechanisms of lithium-ion battery components using in-situ micro tests," Applied Energy, Elsevier, vol. 224(C), pages 251-266.
    11. Chen, Zeyu & Xiong, Rui & Tian, Jinpeng & Shang, Xiong & Lu, Jiahuan, 2016. "Model-based fault diagnosis approach on external short circuit of lithium-ion battery used in electric vehicles," Applied Energy, Elsevier, vol. 184(C), pages 365-374.
    12. Wang, Zhi & Wang, Jian, 2020. "Investigation of external heating-induced failure propagation behaviors in large-size cell modules with different phase change materials," Energy, Elsevier, vol. 204(C).
    13. 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.
    14. 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).
    15. Feng, Xuning & Lu, Languang & Ouyang, Minggao & Li, Jiangqiu & He, Xiangming, 2016. "A 3D thermal runaway propagation model for a large format lithium ion battery module," Energy, Elsevier, vol. 115(P1), pages 194-208.
    16. Kang, Yongzhe & Duan, Bin & Zhou, Zhongkai & Shang, Yunlong & Zhang, Chenghui, 2020. "Online multi-fault detection and diagnosis for battery packs in electric vehicles," Applied Energy, Elsevier, vol. 259(C).
    17. JiYang Xu & Jian Ma & Xuan Zhao & Hao Chen & Bin Xu & XueQin Wu, 2020. "Detection Technology for Battery Safety in Electric Vehicles: A Review," Energies, MDPI, vol. 13(18), pages 1-19, September.
    18. Feng, Xuning & Zheng, Siqi & Ren, Dongsheng & He, Xiangming & Wang, Li & Cui, Hao & Liu, Xiang & Jin, Changyong & Zhang, Fangshu & Xu, Chengshan & Hsu, Hungjen & Gao, Shang & Chen, Tianyu & Li, Yalun , 2019. "Investigating the thermal runaway mechanisms of lithium-ion batteries based on thermal analysis database," Applied Energy, Elsevier, vol. 246(C), pages 53-64.
    19. Li, Xiaoyu & Zhang, Zuguang & Wang, Wenhui & Tian, Yong & Li, Dong & Tian, Jindong, 2020. "Multiphysical field measurement and fusion for battery electric-thermal-contour performance analysis," Applied Energy, Elsevier, vol. 262(C).
    20. Ma, Mina & Wang, Yu & Duan, Qiangling & Wu, Tangqin & Sun, Jinhua & Wang, Qingsong, 2018. "Fault detection of the connection of lithium-ion power batteries in series for electric vehicles based on statistical analysis," Energy, Elsevier, vol. 164(C), pages 745-756.

    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:228:y:2018:i:c:p:633-644. 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.