IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v205y2017icp1327-1344.html
   My bibliography  Save this article

Modelling electro-thermal response of lithium-ion batteries from normal to abuse conditions

Author

Listed:
  • Ping, Ping
  • Wang, Qingsong
  • Chung, Youngmann
  • Wen, Jennifer

Abstract

Insight of thermal behaviour of lithium-ion batteries under various operating conditions is crucial for the development of battery management system (BMS). Although battery thermal behaviour has been studied by published models, the reported modelling normally addresses either normal operation or thermal runaway condition. A comprehensive electro-thermal model which can capture heat generation, voltage and current variation during the whole process from normal cycling to thermal runaway should be of benefit for BMS by evaluating critical factors influencing potential transition to thermal runaway and investigating the evolution process under different cooling and environment conditions. In this study, such a three-dimensional model has been developed within the frame of open source computational fluid dynamics (CFD) code OpenFOAM to study the electrical and thermal behaviour of lithium-ion batteries (LIBs). The equations governing the electric conduction are coupled with heat transfer and energy balance within the cell. Published and new laboratory data for LiNi0.33Co0.33Mn0.33O2/Li1.33Ti1.67O4 (LNCMO/LTO) cells from normal cycling to thermal runaway have been used to provide input parameters as well as model validation. The model has well captured the evolution process of a cell from normal cycling to abnormal behaviour until thermal runaway and achieved reasonably good agreement with the measurements. The validated model has then been used to conduct parametric studies of this particular type of LIB by evaluating the effects of discharging current rates, airflow quantities, ambient temperatures and thickness of airflow channel on the response of the cell. Faster function losses, earlier thermal runaway and higher extreme temperatures were found when cells were discharged under higher current rates. The airflow with specific velocity was found to provide effective mitigation against over-heating when the ambient temperature was below 370K but less effective when the ambient temperature was higher than the critical value of 425K. The thickness of airflow channel was also found to have critical influence on the cell tolerance to elevated temperatures. These parametric studies demonstrate that the model can be used to predict potential LIB transition to thermal runaway under various conditions and aid BMS.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:205:y:2017:i:c:p:1327-1344
    DOI: 10.1016/j.apenergy.2017.08.073
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261917310899
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2017.08.073?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. 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.
    2. Andreas Melcher & Carlos Ziebert & Magnus Rohde & Hans Jürgen Seifert, 2016. "Modeling and Simulation of the Thermal Runaway Behavior of Cylindrical Li-Ion Cells—Computing of Critical Parameters," Energies, MDPI, vol. 9(4), pages 1-19, April.
    3. Jiang, Jiuchun & Ruan, Haijun & Sun, Bingxiang & Zhang, Weige & Gao, Wenzhong & Wang, Le Yi & Zhang, Linjing, 2016. "A reduced low-temperature electro-thermal coupled model for lithium-ion batteries," Applied Energy, Elsevier, vol. 177(C), pages 804-816.
    4. Liu, Rui & Chen, Jixin & Xun, Jingzhi & Jiao, Kui & Du, Qing, 2014. "Numerical investigation of thermal behaviors in lithium-ion battery stack discharge," Applied Energy, Elsevier, vol. 132(C), pages 288-297.
    5. Marzband, Mousa & Sumper, Andreas & Ruiz-Álvarez, Albert & Domínguez-García, José Luis & Tomoiagă, Bogdan, 2013. "Experimental evaluation of a real time energy management system for stand-alone microgrids in day-ahead markets," Applied Energy, Elsevier, vol. 106(C), pages 365-376.
    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. He, Tengfei & Zhang, Teng & Wang, Zhirong & Cai, Qiong, 2022. "A comprehensive numerical study on electrochemical-thermal models of a cylindrical lithium-ion battery during discharge process," Applied Energy, Elsevier, vol. 313(C).
    2. 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).
    3. 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.
    4. Li, Junqiu & Sun, Danni & Jin, Xin & Shi, Wentong & Sun, Chao, 2019. "Lithium-ion battery overcharging thermal characteristics analysis and an impedance-based electro-thermal coupled model simulation," Applied Energy, Elsevier, vol. 254(C).
    5. 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).
    6. Said, Ahmed O. & Lee, Christopher & Stoliarov, Stanislav I. & Marshall, André W., 2019. "Comprehensive analysis of dynamics and hazards associated with cascading failure in 18650 lithium ion cell arrays," Applied Energy, Elsevier, vol. 248(C), pages 415-428.
    7. Wang, Yu & Ren, Dongsheng & Feng, Xuning & Wang, Li & Ouyang, Minggao, 2022. "Thermal runaway modeling of large format high-nickel/silicon-graphite lithium-ion batteries based on reaction sequence and kinetics," Applied Energy, Elsevier, vol. 306(PA).
    8. Lu, Xin & Chen, Ning & Li, Hui & Guo, Shiyu & Chen, Zengtao, 2023. "Simulation of the temperature distribution of lithium-ion battery module considering the time-delay effect of the porous electrodes," Energy, Elsevier, vol. 284(C).
    9. Yang, Yang & Yuan, Wei & Zhang, Xiaoqing & Yuan, Yuhang & Wang, Chun & Ye, Yintong & Huang, Yao & Qiu, Zhiqiang & Tang, Yong, 2020. "Overview on the applications of three-dimensional printing for rechargeable lithium-ion batteries," Applied Energy, Elsevier, vol. 257(C).
    10. Ding, Xiaofeng & Zhang, Donghuai & Cheng, Jiawei & Wang, Binbin & Luk, Patrick Chi Kwong, 2019. "An improved Thevenin model of lithium-ion battery with high accuracy for electric vehicles," Applied Energy, Elsevier, vol. 254(C).
    11. 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.
    12. Fan Zhang & Xiao Zheng & Zixuan Xing & Minghu Wu, 2024. "Fault Diagnosis Method for Lithium-Ion Power Battery Incorporating Multidimensional Fault Features," Energies, MDPI, vol. 17(7), pages 1-21, March.
    13. Huang, Peifeng & Yao, Caixia & Mao, Binbin & Wang, Qingsong & Sun, Jinhua & Bai, Zhonghao, 2020. "The critical characteristics and transition process of lithium-ion battery thermal runaway," Energy, Elsevier, vol. 213(C).
    14. Miranda, D. & Almeida, A.M. & Lanceros-Méndez, S. & Costa, C.M., 2019. "Effect of the active material type and battery geometry on the thermal behavior of lithium-ion batteries," Energy, Elsevier, vol. 185(C), pages 1250-1262.
    15. 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).

    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. Jiang, Z.Y. & Qu, Z.G., 2019. "Lithium–ion battery thermal management using heat pipe and phase change material during discharge–charge cycle: A comprehensive numerical study," Applied Energy, Elsevier, vol. 242(C), pages 378-392.
    2. 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).
    3. Zhiguo Tang & Anqi Song & Shoucheng Wang & Jianping Cheng & Changfa Tao, 2020. "Numerical Analysis of Heat Transfer Mechanism of Thermal Runaway Propagation for Cylindrical Lithium-ion Cells in Battery Module," Energies, MDPI, vol. 13(4), pages 1-18, February.
    4. Yuqing Chen & Qiu He & Yun Zhao & Wang Zhou & Peitao Xiao & Peng Gao & Naser Tavajohi & Jian Tu & Baohua Li & Xiangming He & Lidan Xing & Xiulin Fan & Jilei Liu, 2023. "Breaking solvation dominance of ethylene carbonate via molecular charge engineering enables lower temperature battery," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    5. Restrepo, Mauricio & Cañizares, Claudio A. & Simpson-Porco, John W. & Su, Peter & Taruc, John, 2021. "Optimization- and Rule-based Energy Management Systems at the Canadian Renewable Energy Laboratory microgrid facility," Applied Energy, Elsevier, vol. 290(C).
    6. Ostanek, Jason K. & Li, Weisi & Mukherjee, Partha P. & Crompton, K.R. & Hacker, Christopher, 2020. "Simulating onset and evolution of thermal runaway in Li-ion cells using a coupled thermal and venting model," Applied Energy, Elsevier, vol. 268(C).
    7. Kumar, Kartik & Sarkar, Jahar & Mondal, Swasti Sundar, 2024. "Analysis of ternary hybrid nanofluid in microchannel-cooled cylindrical Li-ion battery pack using multi-scale multi-domain framework," Applied Energy, Elsevier, vol. 355(C).
    8. 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).
    9. He, Xitian & Sun, Bingxiang & Zhang, Weige & Su, Xiaojia & Ma, Shichang & Li, Hao & Ruan, Haijun, 2023. "Inconsistency modeling of lithium-ion battery pack based on variational auto-encoder considering multi-parameter correlation," Energy, Elsevier, vol. 277(C).
    10. El-Sharafy, M. Zaki & Farag, Hany E.Z., 2017. "Back-feed power restoration using distributed constraint optimization in smart distribution grids clustered into microgrids," Applied Energy, Elsevier, vol. 206(C), pages 1102-1117.
    11. 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).
    12. Ahmad Khan, Aftab & Naeem, Muhammad & Iqbal, Muhammad & Qaisar, Saad & Anpalagan, Alagan, 2016. "A compendium of optimization objectives, constraints, tools and algorithms for energy management in microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1664-1683.
    13. Korkas, Christos D. & Baldi, Simone & Michailidis, Iakovos & Kosmatopoulos, Elias B., 2015. "Intelligent energy and thermal comfort management in grid-connected microgrids with heterogeneous occupancy schedule," Applied Energy, Elsevier, vol. 149(C), pages 194-203.
    14. Gonzalez de Durana, Jose & Barambones, Oscar, 2018. "Technology-free microgrid modeling with application to demand side management," Applied Energy, Elsevier, vol. 219(C), pages 165-178.
    15. Giaouris, Damian & Papadopoulos, Athanasios I. & Patsios, Charalampos & Walker, Sara & Ziogou, Chrysovalantou & Taylor, Phil & Voutetakis, Spyros & Papadopoulou, Simira & Seferlis, Panos, 2018. "A systems approach for management of microgrids considering multiple energy carriers, stochastic loads, forecasting and demand side response," Applied Energy, Elsevier, vol. 226(C), pages 546-559.
    16. 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).
    17. 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.
    18. 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.
    19. Chengning Zhang & Xin Jin & Junqiu Li, 2017. "PTC Self-Heating Experiments and Thermal Modeling of Lithium-Ion Battery Pack in Electric Vehicles," Energies, MDPI, vol. 10(4), pages 1-21, April.
    20. Velik, Rosemarie & Nicolay, Pascal, 2014. "Grid-price-dependent energy management in microgrids using a modified simulated annealing triple-optimizer," Applied Energy, Elsevier, vol. 130(C), pages 384-395.

    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:205:y:2017:i:c:p:1327-1344. 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.