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Risk management over the life cycle of lithium-ion batteries in electric vehicles

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  • Christensen, Paul A.
  • Anderson, Paul A.
  • Harper, Gavin D.J.
  • Lambert, Simon M.
  • Mrozik, Wojciech
  • Rajaeifar, Mohammad Ali
  • Wise, Malcolm S.
  • Heidrich, Oliver

Abstract

Lithium-ion Batteries (LIB) are an essential facilitator of the decarbonisation of the transport and energy system, and their high energy densities represent a major technological achievement and resource for humankind. In this research, it has been argued that LIBs have penetrated everyday life faster than our understanding of the risks and challenges associated with them. The current safety standards in the car industry have benefited from over 130 years of evolution and refinement, and Electric Vehicle (EV) and LIB are comparably in their infancy. This paper considers some of the issues of safety over the life cycle of batteries, including: the End of Life disposal of batteries, their potential reuse in a second-life application (e.g. in Battery Energy Storage Systems), recycling and unscheduled End of Life (i.e. accidents). The failure mechanism and reports from a range of global case studies, scenarios and incidents are described to infer potential safety issues and highlight lessons that can be learned. Therefore, the safety risks of LIBs were categorised, and the regularity requirements to create and inform a wider debate on the general safety of LIBs were discussed. From the analysis, a range of gaps in current approaches have been identified and the risk management systems was discussed. Ultimately, it is concluded that robust educational and legal processes are needed to understand and manage the risks for first responders and the public at large to ensure a safe and beneficial transition to low carbon transportation and energy system.

Suggested Citation

  • Christensen, Paul A. & Anderson, Paul A. & Harper, Gavin D.J. & Lambert, Simon M. & Mrozik, Wojciech & Rajaeifar, Mohammad Ali & Wise, Malcolm S. & Heidrich, Oliver, 2021. "Risk management over the life cycle of lithium-ion batteries in electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 148(C).
    • Handle: RePEc:eee:rensus:v:148:y:2021:i:c:s136403212100527x
    DOI: 10.1016/j.rser.2021.111240
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    3. Wang, Huan & Li, Yan-Fu & Zhang, Ying, 2023. "Bioinspired spiking spatiotemporal attention framework for lithium-ion batteries state-of-health estimation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    4. Faissal Jelti & Amine Allouhi & Kheira Anissa Tabet Aoul, 2023. "Transition Paths towards a Sustainable Transportation System: A Literature Review," Sustainability, MDPI, vol. 15(21), pages 1-25, October.
    5. Harper, Gavin D.J. & Kendrick, Emma & Anderson, Paul A. & Mrozik, Wojciech & Christensen, Paul & Lambert, Simon & Greenwood, David & Das, Prodip K. & Ahmeid, Mohamed & Milojevic, Zoran & Du, Wenjia & , 2023. "Roadmap for a sustainable circular economy in lithium-ion and future battery technologies," LSE Research Online Documents on Economics 118420, London School of Economics and Political Science, LSE Library.
    6. Huaqin Zhang & Jichao Hong & Zhezhe Wang & Guodong Wu, 2022. "State-Partial Accurate Voltage Fault Prognosis for Lithium-Ion Batteries Based on Self-Attention Networks," Energies, MDPI, vol. 15(22), pages 1-14, November.
    7. Md Junaed Al Hossain & Md. Zakir Hasan & Md Hasanuzzaman & Md. Ziaur Rahman Khan & Mohammad Ahsan Habib, 2022. "Affordable Electric Three-Wheeler in Bangladesh: Prospects, Challenges, and Sustainable Solutions," Sustainability, MDPI, vol. 15(1), pages 1-26, December.
    8. Giovanni Lucà Trombetta & Salvatore Gianluca Leonardi & Davide Aloisio & Laura Andaloro & Francesco Sergi, 2024. "Lithium-Ion Batteries on Board: A Review on Their Integration for Enabling the Energy Transition in Shipping Industry," Energies, MDPI, vol. 17(5), pages 1-37, February.
    9. Wang, Cong & Chen, Yunxia & Zhang, Qingyuan & Zhu, Jiaxiao, 2023. "Dynamic early recognition of abnormal lithium-ion batteries before capacity drops using self-adaptive quantum clustering," Applied Energy, Elsevier, vol. 336(C).
    10. Li, Chuan & Zhang, Huahua & Ding, Ping & Yang, Shuai & Bai, Yun, 2023. "Deep feature extraction in lifetime prognostics of lithium-ion batteries: Advances, challenges and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).

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