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

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Listed:
  • 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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    Cited by:

    1. Tang, Aihua & Wu, Xinyu & Xu, Tingting & Hu, Yuanzhi & Long, Shengwen & Yu, Quanqing, 2024. "State of health estimation based on inconsistent evolution for lithium-ion battery module," Energy, Elsevier, vol. 286(C).
    2. Liu, Huimin & Lin, Cheng & Yu, Xiao & Tao, Zhenyi & Xu, Jiaqi, 2024. "Variable horizon multivariate driving pattern recognition framework based on vehicle-road two-dimensional information for electric vehicle," Applied Energy, Elsevier, vol. 365(C).
    3. Peng, Simin & Miao, Yifan & Xiong, Rui & Bai, Jiawei & Cheng, Mengzeng & Pecht, Michael, 2024. "State of charge estimation for a parallel battery pack jointly by fuzzy-PI model regulator and adaptive unscented Kalman filter," Applied Energy, Elsevier, vol. 360(C).
    4. 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).
    5. 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).
    6. 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).
    7. 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).
    8. 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).

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