IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v150y2021ics1364032121007206.html
   My bibliography  Save this article

Mitigation strategies for Li-ion battery thermal runaway: A review

Author

Listed:
  • Xu, Bin
  • Lee, Jinwoo
  • Kwon, Daeil
  • Kong, Lingxi
  • Pecht, Michael

Abstract

Li-ion batteries are commercially successful power sources for diverse applications. However, the characteristics of Li-ion batteries make them susceptible to thermal runaway, resulting in fires and explosions. To mitigate safety hazards prior to the occurrence of thermal runaway, various strategies have been applied for battery cells, as well as battery packages. This article reviews safety strategies for Li-ion batteries, including positive temperature coefficient thermistors, positive temperature coefficient electrodes, current interrupt devices, safety vents, protection circuitry, shutdown separators, electrolyte additives, safe electrolytes, passive protection designs in battery packages, and battery management systems. The trigger conditions, protection mechanisms, drawbacks, and applications of representative strategies are discussed, and potential future risk mitigation approaches are explored.

Suggested Citation

  • Xu, Bin & Lee, Jinwoo & Kwon, Daeil & Kong, Lingxi & Pecht, Michael, 2021. "Mitigation strategies for Li-ion battery thermal runaway: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    • Handle: RePEc:eee:rensus:v:150:y:2021:i:c:s1364032121007206
    DOI: 10.1016/j.rser.2021.111437
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032121007206
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.rser.2021.111437?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. Chun-Peng Yang & Ya-Xia Yin & Shuai-Feng Zhang & Nian-Wu Li & Yu-Guo Guo, 2015. "Accommodating lithium into 3D current collectors with a submicron skeleton towards long-life lithium metal anodes," Nature Communications, Nature, vol. 6(1), pages 1-9, November.
    2. Donal P. Finegan & Mario Scheel & James B. Robinson & Bernhard Tjaden & Ian Hunt & Thomas J. Mason & Jason Millichamp & Marco Di Michiel & Gregory J. Offer & Gareth Hinds & Dan J.L. Brett & Paul R. Sh, 2015. "In-operando high-speed tomography of lithium-ion batteries during thermal runaway," Nature Communications, Nature, vol. 6(1), pages 1-10, November.
    3. Nicholas Williard & Wei He & Christopher Hendricks & Michael Pecht, 2013. "Lessons Learned from the 787 Dreamliner Issue on Lithium-Ion Battery Reliability," Energies, MDPI, vol. 6(9), pages 1-14, September.
    4. J.-M. Tarascon & M. Armand, 2001. "Issues and challenges facing rechargeable lithium batteries," Nature, Nature, vol. 414(6861), pages 359-367, November.
    5. Zahid, Taimoor & Xu, Kun & Li, Weimin & Li, Chenming & Li, Hongzhe, 2018. "State of charge estimation for electric vehicle power battery using advanced machine learning algorithm under diversified drive cycles," Energy, Elsevier, vol. 162(C), pages 871-882.
    6. Yifei Yuan & Khalil Amine & Jun Lu & Reza Shahbazian-Yassar, 2017. "Understanding materials challenges for rechargeable ion batteries with in situ transmission electron microscopy," Nature Communications, Nature, vol. 8(1), pages 1-14, August.
    7. Hannan, M.A. & Lipu, M.S.H. & Hussain, A. & Mohamed, A., 2017. "A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 834-854.
    8. Yangying Zhu & Jin Xie & Allen Pei & Bofei Liu & Yecun Wu & Dingchang Lin & Jun Li & Hansen Wang & Hao Chen & Jinwei Xu & Ankun Yang & Chun-Lan Wu & Hongxia Wang & Wei Chen & Yi Cui, 2019. "Fast lithium growth and short circuit induced by localized-temperature hotspots in lithium batteries," Nature Communications, Nature, vol. 10(1), pages 1-7, December.
    9. Nicholas Williard & Christopher Hendricks & Bhanu Sood & Jae Sik Chung & Michael Pecht, 2016. "Evaluation of Batteries for Safe Air Transport," Energies, MDPI, vol. 9(5), pages 1-13, May.
    10. Yi Wu & Saurabh Saxena & Yinjiao Xing & Youren Wang & Chuan Li & Winco K. C. Yung & Michael Pecht, 2018. "Analysis of Manufacturing-Induced Defects and Structural Deformations in Lithium-Ion Batteries Using Computed Tomography," Energies, MDPI, vol. 11(4), pages 1-22, April.
    11. Deyu Cui & Bizhong Xia & Ruifeng Zhang & Zhen Sun & Zizhou Lao & Wei Wang & Wei Sun & Yongzhi Lai & Mingwang Wang, 2018. "A Novel Intelligent Method for the State of Charge Estimation of Lithium-Ion Batteries Using a Discrete Wavelet Transform-Based Wavelet Neural Network," Energies, MDPI, vol. 11(4), pages 1-18, April.
    12. Deng, Zhongwei & Hu, Xiaosong & Lin, Xianke & Che, Yunhong & Xu, Le & Guo, Wenchao, 2020. "Data-driven state of charge estimation for lithium-ion battery packs based on Gaussian process regression," Energy, Elsevier, vol. 205(C).
    13. Lingxi Kong & Chuan Li & Jiuchun Jiang & Michael G. Pecht, 2018. "Li-Ion Battery Fire Hazards and Safety Strategies," Energies, MDPI, vol. 11(9), pages 1-11, August.
    14. Xing, Yinjiao & He, Wei & Pecht, Michael & Tsui, Kwok Leung, 2014. "State of charge estimation of lithium-ion batteries using the open-circuit voltage at various ambient temperatures," Applied Energy, Elsevier, vol. 113(C), pages 106-115.
    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. Lingappan, Niranjanmurthi & Lee, Wonoh & Passerini, Stefano & Pecht, Michael, 2023. "A comprehensive review of separator membranes in lithium-ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    2. Liu, Yanhui & Zhang, Lei & Ding, Yifei & Huang, Xianjia & Huang, Xinyan, 2024. "Effect of thermal impact on the onset and propagation of thermal runaway over cylindrical Li-ion batteries," Renewable Energy, Elsevier, vol. 222(C).
    3. Weng, Jingwen & Xiao, Changren & Yang, Xiaoqing & Ouyang, Dongxu & Chen, Mingyi & Zhang, Guoqing & Lee Waiming, Eric & Kit Yuen, Richard Kwowk & Wang, Jian, 2022. "An energy-saving battery thermal management strategy coupling tubular phase-change-material with dynamic liquid cooling under different ambient temperatures," Renewable Energy, Elsevier, vol. 195(C), pages 918-930.
    4. Zhou, Zhizuan & Zhou, Xiaodong & Cao, Bei & Yang, Lizhong & Liew, K.M., 2022. "Investigating the relationship between heating temperature and thermal runaway of prismatic lithium-ion battery with LiFePO4 as cathode," Energy, Elsevier, vol. 256(C).
    5. Zhou, Zhizuan & Zhou, Xiaodong & Ju, Xiaoyu & Li, Maoyu & Cao, Bei & Yang, Lizhong, 2023. "Experimental study of thermal runaway propagation along horizontal and vertical directions for LiFePO4 electrical energy storage modules," Renewable Energy, Elsevier, vol. 207(C), pages 13-26.
    6. Arjan F. Kirkels & Jeroen Bleker & Henny A. Romijn, 2022. "Ready for the Road? A Socio-Technical Investigation of Fire Safety Improvement Options for Lithium-Ion Traction Batteries," Energies, MDPI, vol. 15(9), pages 1-22, May.
    7. Zhou, Zhizuan & Zhou, Xiaodong & Li, Maoyu & Cao, Bei & Liew, K.M. & Yang, Lizhong, 2022. "Experimentally exploring prevention of thermal runaway propagation of large-format prismatic lithium-ion battery module," Applied Energy, Elsevier, vol. 327(C).
    8. Xie, Jiale & Xu, Jingfan & Wei, Zhongbao & Li, Xiaoyu, 2023. "Fault isolating and grading for li-ion battery packs based on pseudo images and convolutional neural network," Energy, Elsevier, vol. 263(PD).
    9. Huang, Zhiliang & Wang, Huaixing & Yang, Tongguang & Chen, Zeye & Li, Hangyang & Chen, Jie & Wu, Shengben, 2023. "An efficient multi-state evaluation approach for lithium-ion pouch cells under dynamic conditions in pressure/current/temperature," Applied Energy, Elsevier, vol. 340(C).
    10. Ma, Ying & Yang, Heng & Zuo, Hongyan & Zuo, Qingsong & He, Xiaoxiang & Chen, Wei & Wei, Rongrong, 2023. "EG@Bi-MOF derived porous carbon/lauric acid composite phase change materials for thermal management of batteries," Energy, Elsevier, vol. 272(C).
    11. Lu, Fenglian & Chen, Weiye & Hu, Shuzhi & Chen, Lei & Sharshir, Swellam W. & Dong, Chuanshuai & Zhang, Lizhi, 2024. "Achieving a smart thermal management for lithium-ion batteries by electrically-controlled crystallization of supercooled calcium chloride hexahydrate solution," Applied Energy, Elsevier, vol. 364(C).
    12. Cui, Zhaopeng & Du, Shuai & Wang, Ruzhu & Cheng, Chao & Wei, Liuzhu & Wang, Xuejiao, 2024. "Development and experimental study of a small-scale adsorption cold storage prototype with stable and tunable output for off-grid cooling," Energy, Elsevier, vol. 300(C).
    13. 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).
    14. Martina Cianciullo & Giorgio Vilardi & Barbara Mazzarotta & Roberto Bubbico, 2022. "Simulation of the Thermal Runaway Onset in Li-Ion Cells—Influence of Cathode Materials and Operating Conditions," Energies, MDPI, vol. 15(11), pages 1-24, June.

    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. Kuo Yang & Yugui Tang & Zhen Zhang, 2021. "Parameter Identification and State-of-Charge Estimation for Lithium-Ion Batteries Using Separated Time Scales and Extended Kalman Filter," Energies, MDPI, vol. 14(4), pages 1-15, February.
    2. Chen, Zheng & Zhao, Hongqian & Shu, Xing & Zhang, Yuanjian & Shen, Jiangwei & Liu, Yonggang, 2021. "Synthetic state of charge estimation for lithium-ion batteries based on long short-term memory network modeling and adaptive H-Infinity filter," Energy, Elsevier, vol. 228(C).
    3. Li, Feng & Zuo, Wei & Zhou, Kun & Li, Qingqing & Huang, Yuhan & Zhang, Guangde, 2024. "State-of-charge estimation of lithium-ion battery based on second order resistor-capacitance circuit-PSO-TCN model," Energy, Elsevier, vol. 289(C).
    4. 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).
    5. Zuo, Hongyan & Zhang, Bin & Huang, Zhonghua & Wei, Kexiang & Zhu, Hong & Tan, Jiqiu, 2022. "Effect analysis on SOC values of the power lithium manganate battery during discharging process and its intelligent estimation," Energy, Elsevier, vol. 238(PB).
    6. Li, Yi & Liu, Kailong & Foley, Aoife M. & Zülke, Alana & Berecibar, Maitane & Nanini-Maury, Elise & Van Mierlo, Joeri & Hoster, Harry E., 2019. "Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    7. Hu, Chunsheng & Ma, Liang & Guo, Shanshan & Guo, Gangsheng & Han, Zhiqiang, 2022. "Deep learning enabled state-of-charge estimation of LiFePO4 batteries: A systematic validation on state-of-the-art charging protocols," Energy, Elsevier, vol. 246(C).
    8. Thomas F. Landinger & Guenter Schwarzberger & Guenter Hofer & Matthias Rose & Andreas Jossen, 2021. "Power Line Communications for Automotive High Voltage Battery Systems: Channel Modeling and Coexistence Study with Battery Monitoring," Energies, MDPI, vol. 14(7), pages 1-26, March.
    9. Guo, Feng & Hu, Guangdi & Xiang, Shun & Zhou, Pengkai & Hong, Ru & Xiong, Neng, 2019. "A multi-scale parameter adaptive method for state of charge and parameter estimation of lithium-ion batteries using dual Kalman filters," Energy, Elsevier, vol. 178(C), pages 79-88.
    10. Benedikt Rzepka & Simon Bischof & Thomas Blank, 2021. "Implementing an Extended Kalman Filter for SoC Estimation of a Li-Ion Battery with Hysteresis: A Step-by-Step Guide," Energies, MDPI, vol. 14(13), pages 1-17, June.
    11. Muhammad Umair Ali & Amad Zafar & Sarvar Hussain Nengroo & Sadam Hussain & Muhammad Junaid Alvi & Hee-Je Kim, 2019. "Towards a Smarter Battery Management System for Electric Vehicle Applications: A Critical Review of Lithium-Ion Battery State of Charge Estimation," Energies, MDPI, vol. 12(3), pages 1-33, January.
    12. Wang, Ya-Xiong & Chen, Zhenhang & Zhang, Wei, 2022. "Lithium-ion battery state-of-charge estimation for small target sample sets using the improved GRU-based transfer learning," Energy, Elsevier, vol. 244(PB).
    13. Minhwan Seo & Taedong Goh & Minjun Park & Sang Woo Kim, 2018. "Detection Method for Soft Internal Short Circuit in Lithium-Ion Battery Pack by Extracting Open Circuit Voltage of Faulted Cell," Energies, MDPI, vol. 11(7), pages 1-18, June.
    14. Tian, Yong & Lai, Rucong & Li, Xiaoyu & Xiang, Lijuan & Tian, Jindong, 2020. "A combined method for state-of-charge estimation for lithium-ion batteries using a long short-term memory network and an adaptive cubature Kalman filter," Applied Energy, Elsevier, vol. 265(C).
    15. Yigeng Huangfu & Jiani Xu & Dongdong Zhao & Yuntian Liu & Fei Gao, 2018. "A Novel Battery State of Charge Estimation Method Based on a Super-Twisting Sliding Mode Observer," Energies, MDPI, vol. 11(5), pages 1-21, May.
    16. 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.
    17. Shuai Wang & Lingling Zhao & Xiaohong Su & Peijun Ma, 2014. "Prognostics of Lithium-Ion Batteries Based on Battery Performance Analysis and Flexible Support Vector Regression," Energies, MDPI, vol. 7(10), pages 1-17, October.
    18. Yang, Fangfang & Zhang, Shaohui & Li, Weihua & Miao, Qiang, 2020. "State-of-charge estimation of lithium-ion batteries using LSTM and UKF," Energy, Elsevier, vol. 201(C).
    19. Yang, Lin & Cai, Yishan & Yang, Yixin & Deng, Zhongwei, 2020. "Supervisory long-term prediction of state of available power for lithium-ion batteries in electric vehicles," Applied Energy, Elsevier, vol. 257(C).
    20. Minsung Baek & Jinyoung Kim & Kwanghoon Jeong & Seonmo Yang & Heejin Kim & Jimin Lee & Minkwan Kim & Ki Jae Kim & Jang Wook Choi, 2023. "Naked metallic skin for homo-epitaxial deposition in lithium metal batteries," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

    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:150:y:2021:i:c:s1364032121007206. 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.