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Advancing Smart Lithium-Ion Batteries: A Review on Multi-Physical Sensing Technologies for Lithium-Ion Batteries

Author

Listed:
  • Wenwei Wang

    (National Engineering Research Center for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
    Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen 518118, China)

  • Shuaibang Liu

    (National Engineering Research Center for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
    Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen 518118, China)

  • Xiao-Ying Ma

    (National Engineering Research Center for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China)

  • Jiuchun Jiang

    (Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen 518118, China)

  • Xiao-Guang Yang

    (National Engineering Research Center for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
    Shenzhen Automotive Research Institute, Beijing Institute of Technology, Shenzhen 518118, China)

Abstract

Traditional battery management systems (BMS) encounter significant challenges, including low precision in predicting battery states and complexities in managing batteries, primarily due to the scarcity of collected signals. The advancement towards a “smart battery”, equipped with diverse sensor types, promises to mitigate these issues. This review highlights the latest developments in smart sensing technologies for batteries, encompassing electrical, thermal, mechanical, acoustic, and gas sensors. Specifically, we address how these different signals are perceived and how these varied signals could enhance our comprehension of battery aging, failure, and thermal runaway mechanisms, contributing to the creation of BMS that are safer and more reliable. Moreover, we analyze the limitations and challenges faced by different sensor applications and discuss the advantages and disadvantages of each sensing technology. Conclusively, we present a perspective on overcoming future hurdles in smart battery development, focusing on appropriate sensor design, optimized integration processes, efficient signal transmission, and advanced management systems.

Suggested Citation

  • Wenwei Wang & Shuaibang Liu & Xiao-Ying Ma & Jiuchun Jiang & Xiao-Guang Yang, 2024. "Advancing Smart Lithium-Ion Batteries: A Review on Multi-Physical Sensing Technologies for Lithium-Ion Batteries," Energies, MDPI, vol. 17(10), pages 1-15, May.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:10:p:2273-:d:1390700
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    References listed on IDEAS

    as
    1. Xinwei Cong & Caiping Zhang & Jiuchun Jiang & Weige Zhang & Yan Jiang & Linjing Zhang, 2021. "A Comprehensive Signal-Based Fault Diagnosis Method for Lithium-Ion Batteries in Electric Vehicles," Energies, MDPI, vol. 14(5), pages 1-21, February.
    2. Ostanek, Jason K. & Li, Weisi & Mukherjee, Partha P. & Crompton, K.R. & Hacker, Christopher, 2020. "Simulating onset and evolution of thermal runaway in Li-ion cells using a coupled thermal and venting model," Applied Energy, Elsevier, vol. 268(C).
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