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Evaluation of the safety standards system of power batteries for electric vehicles in China

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  • Yu, Quanqing
  • Nie, Yuwei
  • Peng, Simin
  • Miao, Yifan
  • Zhai, Chengzhi
  • Zhang, Runfeng
  • Han, Jinsong
  • Zhao, Shuo
  • Pecht, Michael

Abstract

In recent years, electric vehicle safety incidents related to batteries have occurred frequently enough to question the adequacy of the current international safety standards. As the world's leading producer of batteries for electric vehicles, China has thus formulated its own national standards, but there are questions as to the unique value of these standards. This review paper analyzes the Chinese safety standards from the perspective of the battery materials, cells, modules, battery systems, battery management systems, and vehicles. The findings from the analysis of the Chinese standards is used to provide suggestions for building better international battery safety standards with recommendations for different battery levels, battery life cycle design and emerging battery technologies.

Suggested Citation

  • Yu, Quanqing & Nie, Yuwei & Peng, Simin & Miao, Yifan & Zhai, Chengzhi & Zhang, Runfeng & Han, Jinsong & Zhao, Shuo & Pecht, Michael, 2023. "Evaluation of the safety standards system of power batteries for electric vehicles in China," Applied Energy, Elsevier, vol. 349(C).
    • Handle: RePEc:eee:appene:v:349:y:2023:i:c:s0306261923010383
    DOI: 10.1016/j.apenergy.2023.121674
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    References listed on IDEAS

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    1. Feng Zhu & Runzhou Zhou & David J. Sypeck, 2020. "Numerical Modeling and Safety Design for Lithium-Ion Vehicle Battery Modules Subject to Crush Loading," Energies, MDPI, vol. 14(1), pages 1-24, December.
    2. Papoutsoglou, Maria & Rigas, Emmanouil S. & Kapitsaki, Georgia M. & Angelis, Lefteris & Wachs, Johannes, 2022. "Online labour market analytics for the green economy: The case of electric vehicles," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    3. 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.
    4. Krystyna Gomółka & Piotr Kasprzak, 2021. "Directions and Prospects for the Development of the Electric Car Market in Selected ASEAN Countries," Energies, MDPI, vol. 14(22), pages 1-16, November.
    5. Yu, Quanqing & Dai, Lei & Xiong, Rui & Chen, Zeyu & Zhang, Xin & Shen, Weixiang, 2022. "Current sensor fault diagnosis method based on an improved equivalent circuit battery model," Applied Energy, Elsevier, vol. 310(C).
    6. 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).
    7. Aziam, Hasna & Larhrib, Badre & Hakim, Charifa & Sabi, Noha & Ben Youcef, Hicham & Saadoune, Ismael, 2022. "Solid-state electrolytes for beyond lithium-ion batteries: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
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    6. Yuan, Hong & Ma, Minda & Zhou, Nan & Xie, Hui & Ma, Zhili & Xiang, Xiwang & Ma, Xin, 2024. "Battery electric vehicle charging in China: Energy demand and emissions trends in the 2020s," Applied Energy, Elsevier, vol. 365(C).
    7. Gu, Jianqiang & Wu, Zhan & Song, Yubing & Nicolescu, Ana-Cristina, 2024. "A win-win relationship? New evidence on artificial intelligence and new energy vehicles," Energy Economics, Elsevier, vol. 134(C).
    8. Peng, Simin & Sun, Yunxiang & Liu, Dandan & Yu, Quanqing & Kan, Jiarong & Pecht, Michael, 2023. "State of health estimation of lithium-ion batteries based on multi-health features extraction and improved long short-term memory neural network," Energy, Elsevier, vol. 282(C).
    9. Yu, Quanqing & Nie, Yuwei & Guo, Shanshan & Li, Junfu & Zhang, Chengming, 2024. "Machine learning enables rapid state of health estimation of each cell within battery pack," Applied Energy, Elsevier, vol. 375(C).
    10. Yang, Yongsong & Xu, Yuchen & Nie, Yuwei & Li, Jianming & Liu, Shizhuo & Zhao, Lijun & Yu, Quanqing & Zhang, Chengming, 2024. "Deep transfer learning enables battery state of charge and state of health estimation," Energy, Elsevier, vol. 294(C).
    11. Tang, Aihua & Huang, Yukun & Xu, Yuchen & Hu, Yuanzhi & Yan, Fuwu & Tan, Yong & Jin, Xin & Yu, Quanqing, 2024. "Data-physics-driven estimation of battery state of charge and capacity," Energy, Elsevier, vol. 294(C).
    12. Peng, Simin & Zhu, Junchao & Wu, Tiezhou & Yuan, Caichenran & Cang, Junjie & Zhang, Kai & Pecht, Michael, 2024. "Prediction of wind and PV power by fusing the multi-stage feature extraction and a PSO-BiLSTM model," Energy, Elsevier, vol. 298(C).
    13. Peng, Simin & Zhu, Junchao & Wu, Tiezhou & Tang, Aihua & Kan, Jiarong & Pecht, Michael, 2024. "SOH early prediction of lithium-ion batteries based on voltage interval selection and features fusion," Energy, Elsevier, vol. 308(C).
    14. Li, Peimiao & Wang, Shibo & Wang, Hui & Feng, Yun & Li, Hongliang & Xiao, Heye, 2025. "Thermal management of electric vehicle power cabin based on fast zero-dimensional integrating accurate three-dimensional optimization model," Applied Energy, Elsevier, vol. 378(PA).

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