IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v229y2026ics1364032125012961.html

The impact of high ambient temperatures on lithium-ion batteries in electric vehicles: An in-depth review of thermal performance and chemistry-specific response

Author

Listed:
  • Harasis, Salman
  • Khan, Irfan
  • Massoud, Ahmed

Abstract

Temperature is a critical parameter that significantly influences the performance, lifespan, and safety of lithium-ion batteries. It influences electrochemical reaction kinetics, internal resistance, and lithium inventory, which together determine capacity degradation, cycling efficiency, and state of health. High operating temperatures accelerate degradation by promoting the formation of undesirable byproducts, damaging electrode materials, and increasing the risk of thermal runaway. This paper presents a comprehensive review of LIB behavior under high-temperature conditions, focusing on automotive applications. It investigates the thermal characteristics, degradation mechanisms, and effectiveness of various thermal management strategies. The study distinguishes between hot and cold climatic conditions and examines temperature-induced capacity fade, cyclic degradation, and accelerated calendar aging. It also discusses the implications of high-temperature fast charging, considering both short-term and long-term impacts. Furthermore, temperature-based assessments and comparisons are performed at both the cell and pack levels for different lithium-ion chemistries. The aim is to provide a technical evaluation of the long-term viability of electric vehicles operating in hot and desert climates, to identify existing research gaps, and to highlight emerging directions in high-temperature battery technology.

Suggested Citation

  • Harasis, Salman & Khan, Irfan & Massoud, Ahmed, 2026. "The impact of high ambient temperatures on lithium-ion batteries in electric vehicles: An in-depth review of thermal performance and chemistry-specific response," Renewable and Sustainable Energy Reviews, Elsevier, vol. 229(C).
  • Handle: RePEc:eee:rensus:v:229:y:2026:i:c:s1364032125012961
    DOI: 10.1016/j.rser.2025.116623
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032125012961
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.rser.2025.116623?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Dan Dan & Yihang Zhao & Mingshan Wei & Xuehui Wang, 2023. "Review of Thermal Management Technology for Electric Vehicles," Energies, MDPI, vol. 16(12), pages 1-38, June.
    2. Wang, Yaxuan & Guo, Shilong & Cui, Yue & Deng, Liang & Zhao, Lei & Li, Junfu & Wang, Zhenbo, 2025. "A comprehensive review of machine learning-based state of health estimation for lithium-ion batteries: data, features, algorithms, and future challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 224(C).
    3. Vykhodtsev, Anton V. & Jang, Darren & Wang, Qianpu & Rosehart, William & Zareipour, Hamidreza, 2022. "A review of modelling approaches to characterize lithium-ion battery energy storage systems in techno-economic analyses of power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    4. Ngoy, Kitalu Ricin & Lukong, Valantine Takwa & Yoro, Kelvin O. & Makambo, John Beya & Chukwuati, Nonso Christopher & Ibegbulam, Chinedu & Eterigho-Ikelegbe, Orevaoghene & Ukoba, Kingsley & Jen, Tien-C, 2025. "Lithium-ion batteries and the future of sustainable energy: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 223(C).
    5. Khan, Ayesha & Naqvi, Ijaz Haider & Bhargava, Cherry & Lin, Chun-Pang & Boles, Steven Tyler & Kong, Lingxi & Pecht, Michael, 2025. "Safety and reliability analysis of lithium-ion batteries with real-time health monitoring," Renewable and Sustainable Energy Reviews, Elsevier, vol. 212(C).
    6. Enrico, De Santis & Vanessa, Pennazzi & Massimiliano, Luzi & Antonello, Rizzi, 2025. "Degradation mechanisms and differential curve modeling for non-invasive diagnostics of lithium cells: An overview," Renewable and Sustainable Energy Reviews, Elsevier, vol. 211(C).
    7. Yang, Bo & Qian, Yucun & Li, Qiang & Chen, Qian & Wu, Jiyang & Luo, Enbo & Xie, Rui & Zheng, Ruyi & Yan, Yunfeng & Su, Shi & Wang, Jingbo, 2024. "Critical summary and perspectives on state-of-health of lithium-ion battery," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PA).
    8. Zhai, Qiangxiang & Jiang, Hongmin & Long, Nengbing & Kang, Qiaoling & Meng, Xianhe & Zhou, Mingjiong & Yan, Lijing & Ma, Tingli, 2024. "Machine learning for full lifecycle management of lithium-ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 202(C).
    9. Wang, Yongzhen & Liu, Qi & Hao, Shengli & Cheng, Liqiang & Zhang, Wei & Han, Kai & Wang, Enhua & Ouyang, Minggao & Lu, Languang & Li, Xinxi, 2025. "Low temperature heating methods for lithium-ion batteries: A state-of-art review based on knowledge graph," Renewable and Sustainable Energy Reviews, Elsevier, vol. 213(C).
    10. Liu, Kailong & Ashwin, T.R. & Hu, Xiaosong & Lucu, Mattin & Widanage, W. Dhammika, 2020. "An evaluation study of different modelling techniques for calendar ageing prediction of lithium-ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    11. Xiong, Rui & Pan, Yue & Shen, Weixiang & Li, Hailong & Sun, Fengchun, 2020. "Lithium-ion battery aging mechanisms and diagnosis method for automotive applications: Recent advances and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    12. Li, Yifan & Jiang, Chen & Zhao, Chenggong & Zhu, Dahai & Wang, Lingling & Xie, Huaqing & Yu, Wei, 2025. "A comprehensive review for the heat traceability in lithium-ion batteries: From generation and transfer to thermal management," Renewable and Sustainable Energy Reviews, Elsevier, vol. 216(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. Das, Kaushik & Kumar, Roushan & Krishna, Anurup, 2024. "Analyzing electric vehicle battery health performance using supervised machine learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    2. Li, Alan G. & West, Alan C. & Preindl, Matthias, 2022. "Towards unified machine learning characterization of lithium-ion battery degradation across multiple levels: A critical review," Applied Energy, Elsevier, vol. 316(C).
    3. Jiang, Bo & Zhu, Jiangong & Wang, Xueyuan & Wei, Xuezhe & Shang, Wenlong & Dai, Haifeng, 2022. "A comparative study of different features extracted from electrochemical impedance spectroscopy in state of health estimation for lithium-ion batteries," Applied Energy, Elsevier, vol. 322(C).
    4. Jia Guo & Yaqi Li & Kjeld Pedersen & Daniel-Ioan Stroe, 2021. "Lithium-Ion Battery Operation, Degradation, and Aging Mechanism in Electric Vehicles: An Overview," Energies, MDPI, vol. 14(17), pages 1-22, August.
    5. Zhao, Jingyuan & Qu, Xudong & Li, Yuqi & Nan, Jinrui & Burke, Andrew F., 2025. "Real-time prediction of battery remaining useful life using hybrid-fusion deep neural networks," Energy, Elsevier, vol. 328(C).
    6. Shunli Wang & Pu Ren & Paul Takyi-Aninakwa & Siyu Jin & Carlos Fernandez, 2022. "A Critical Review of Improved Deep Convolutional Neural Network for Multi-Timescale State Prediction of Lithium-Ion Batteries," Energies, MDPI, vol. 15(14), pages 1-27, July.
    7. Liu, Yunong & Liu, Yuefeng & Bao, Xiang & Shen, Hongyu, 2025. "Estimation of battery state of health and open circuit voltage at various depths of discharge based on deep learning and relaxation voltage," Energy, Elsevier, vol. 328(C).
    8. Rauf, Huzaifa & Khalid, Muhammad & Arshad, Naveed, 2022. "Machine learning in state of health and remaining useful life estimation: Theoretical and technological development in battery degradation modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    9. Zhao, Shiwen & Peng, Qiao & Du, Dajun & Fei, Minrui & Peng, Chen & Li, Heng & Wu, Yue & Li, Kang & Liu, Kailong, 2026. "Enhancing safety of lithium-ion batteries in sustainable energy systems through intelligent minor short-circuits fault detection," Renewable and Sustainable Energy Reviews, Elsevier, vol. 229(C).
    10. Kalaikkanal, K. & Gobinath, N., 2025. "A review on Lithium-ion battery failure risks and mitigation indices for electric vehicle applications," Applied Energy, Elsevier, vol. 393(C).
    11. Zhang, Junwei & Zhang, Weige & Sun, Bingxiang & Zhang, Yanru & Fan, Xinyuan & Zhao, Bo, 2024. "A novel method of battery pack energy health estimation based on visual feature learning," Energy, Elsevier, vol. 293(C).
    12. Gu, Xubo & Bai, Hanyu & Cui, Xiaofan & Zhu, Juner & Zhuang, Weichao & Li, Zhaojian & Hu, Xiaosong & Song, Ziyou, 2024. "Challenges and opportunities for second-life batteries: Key technologies and economy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    13. Rakshith Subramanya & Matti Yli-Ojanperä & Seppo Sierla & Taneli Hölttä & Jori Valtakari & Valeriy Vyatkin, 2021. "A Virtual Power Plant Solution for Aggregating Photovoltaic Systems and Other Distributed Energy Resources for Northern European Primary Frequency Reserves," Energies, MDPI, vol. 14(5), pages 1-23, February.
    14. Xiong, Rui & Wang, Peng & Jia, Yanbo & Shen, Weixiang & Sun, Fengchun, 2025. "Multi-factor aging in Lithium Iron phosphate batteries: Mechanisms and insights," Applied Energy, Elsevier, vol. 382(C).
    15. Tang, Xiaopeng & Liu, Kailong & Lu, Jingyi & Liu, Boyang & Wang, Xin & Gao, Furong, 2020. "Battery incremental capacity curve extraction by a two-dimensional Luenberger–Gaussian-moving-average filter," Applied Energy, Elsevier, vol. 280(C).
    16. Shahjalal, Mohammad & Roy, Probir Kumar & Shams, Tamanna & Fly, Ashley & Chowdhury, Jahedul Islam & Ahmed, Md. Rishad & Liu, Kailong, 2022. "A review on second-life of Li-ion batteries: prospects, challenges, and issues," Energy, Elsevier, vol. 241(C).
    17. Li, Yong & Wang, Liye & Feng, Yanbiao & Liao, Chenglin & Yang, Jue, 2024. "An online state-of-health estimation method for lithium-ion battery based on linear parameter-varying modeling framework," Energy, Elsevier, vol. 298(C).
    18. S, Vignesh & Che, Hang Seng & Selvaraj, Jeyraj & Tey, Kok Soon & Lee, Jia Woon & Shareef, Hussain & Errouissi, Rachid, 2024. "State of Health (SoH) estimation methods for second life lithium-ion battery—Review and challenges," Applied Energy, Elsevier, vol. 369(C).
    19. Li, Penghua & Zhang, Zijian & Grosu, Radu & Deng, Zhongwei & Hou, Jie & Rong, Yujun & Wu, Rui, 2022. "An end-to-end neural network framework for state-of-health estimation and remaining useful life prediction of electric vehicle lithium batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    20. Li, Jingjing & Qiao, Lulu & Chen, Meng & Song, Dafeng & Zeng, Xiaohua, 2025. "Metal oxide nanofluid-enhanced closed-loop pulsating heat pipes considering the characteristics of base solution: Thermal performance improvement for battery thermal management in cryogenics," Energy, Elsevier, vol. 333(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:229:y:2026:i:c:s1364032125012961. 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.