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Multiphysical field measurement and fusion for battery electric-thermal-contour performance analysis

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  • Li, Xiaoyu
  • Zhang, Zuguang
  • Wang, Wenhui
  • Tian, Yong
  • Li, Dong
  • Tian, Jindong

Abstract

A battery often exhibits a coupling change in electric, thermal and battery surface topography during operation, especially under abuse conditions. Analysis of the coupling relationship among the multiphysical field parameters is necessary for battery physical structure optimization, failure mechanism analysis and fault prognostics method design. However, there are few multiphysical data acquisition and analysis systems for batteries at present. In this context, a novel battery multiphysical field measurement system with a data fusion model for battery performance analysis is proposed in this paper. The measurement system consists of a three-dimensional scanner, an infrared thermal imager, and an integrated battery charger and discharger. In order to accurately acquire the relationship between the battery surface topography and the battery surface temperature, a data fusion model is proposed, and a joint calibration method is accordingly introduced for the parameter identification of the data fusion model. The results show that the multiphysical measurement system can achieve the position matching deviation of 0.19 mm with high resolution and high data acquisition speed. The functionality of the multiphysical measurement system and the data fusion model are verified by the experimental results of different tests, including a 1 C rate charging/discharging test, a high rate charging/discharging test, and two battery abuse operation tests. It will provide key tools for battery thermal runaway mechanism analysis and battery fault diagnosis method design.

Suggested Citation

  • Li, Xiaoyu & Zhang, Zuguang & Wang, Wenhui & Tian, Yong & Li, Dong & Tian, Jindong, 2020. "Multiphysical field measurement and fusion for battery electric-thermal-contour performance analysis," Applied Energy, Elsevier, vol. 262(C).
    • Handle: RePEc:eee:appene:v:262:y:2020:i:c:s0306261920300301
    DOI: 10.1016/j.apenergy.2020.114518
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    References listed on IDEAS

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    2. Chen, Haosen & Fan, Jinbao & Zhang, Mingliang & Feng, Xiaolong & Zhong, Ximing & He, Jianchao & Ai, Shigang, 2023. "Mechanism of inhomogeneous deformation and equal-stiffness design of large-format prismatic lithium-ion batteries," Applied Energy, Elsevier, vol. 332(C).
    3. Li, Xiaoyu & Huang, Zhijia & Tian, Jindong & Tian, Yong, 2021. "State-of-charge estimation tolerant of battery aging based on a physics-based model and an adaptive cubature Kalman filter," Energy, Elsevier, vol. 220(C).
    4. Xia, Quan & Ren, Yi & Wang, Zili & Yang, Dezhen & Yan, Peiyu & Wu, Zeyu & Sun, Bo & Feng, Qiang & Qian, Cheng, 2023. "Safety risk assessment method for thermal abuse of lithium-ion battery pack based on multiphysics simulation and improved bisection method," Energy, Elsevier, vol. 264(C).

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