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A flexible integrated temperature-pressure sensor for wearable detection of thermal runaway in lithium batteries

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Listed:
  • Zhang, Zike
  • Zhao, Wenjie
  • Ma, Yuechao
  • Yao, Yuan
  • Yu, Taolin
  • Zhang, Wei
  • Guo, Hongquan
  • Duan, Xiaoyang
  • Yan, Ruitian
  • Xu, Dan
  • Chen, Minghua

Abstract

Temperature and pressure variations are the key early warnings for the thermal runaway safety monitoring of lithium batteries. Although flexible temperature and pressure integrated sensors can well address the implantation problem encountered by wearable battery detection, the pressure and temperature dual parameter decoupling is still unsolved. Herein, based on the piezoresistive and heat-sensitive effects, we developed a dual-parameter flexible integrated sensor to continuously monitor the temperature and pressure changes at the same position on the surface of the lithium battery, thus realizing the dual-parameter in-situ decoupling. The coupling mechanism is attributed to the positive and negative resistance temperature coefficients of nickel (Ni) and carbon nanotubes (CNT), and hence a CNT/Ni/PVP/GF pressure-sensitive film with near-zero resistance temperature coefficient was achieved using circular interfinger-electrodes on a glass fiber (GF) substrate. Temperature decoupling was successfully realized in the temperature range of 20–100 °C and the pressure range of ≤200 kPa. The sensor also exhibits a fast response (192 ms) and recovery time (96 ms) with good pressure repeatability. Furthermore, the temperature sensitive points based on graphene (GP) and carbon nanotube (CNT) were prepared at the center of the pressure-sensitive membrane by using structural scale effects and material strain coefficient differences. The wide temperature range of 0–150 °C and the high temperature resolution of 0.5 °C were reached, and the pressure deformation could be decoupled. The sensor was affixed to the aluminum film airbag and embedded in the battery module for the overcharge thermal runaway test analysis. The results verified the feasibility of safety monitoring of the prepared flexible battery wearable sensor and the effectiveness of integrated dual-parameter decoupling.

Suggested Citation

  • Zhang, Zike & Zhao, Wenjie & Ma, Yuechao & Yao, Yuan & Yu, Taolin & Zhang, Wei & Guo, Hongquan & Duan, Xiaoyang & Yan, Ruitian & Xu, Dan & Chen, Minghua, 2025. "A flexible integrated temperature-pressure sensor for wearable detection of thermal runaway in lithium batteries," Applied Energy, Elsevier, vol. 381(C).
  • Handle: RePEc:eee:appene:v:381:y:2025:i:c:s0306261924025753
    DOI: 10.1016/j.apenergy.2024.125191
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    References listed on IDEAS

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    1. C. Gervillié-Mouravieff & C. Boussard-Plédel & Jiaqiang Huang & C. Leau & L. Albero Blanquer & M. Ben Yahia & M.-L. Doublet & S. T. Boles & X. H. Zhang & J. L. Adam & J.-M. Tarascon, 2022. "Unlocking cell chemistry evolution with operando fibre optic infrared spectroscopy in commercial Na(Li)-ion batteries," Nature Energy, Nature, vol. 7(12), pages 1157-1169, December.
    2. Fengjiao Zhang & Yaping Zang & Dazhen Huang & Chong-an Di & Daoben Zhu, 2015. "Flexible and self-powered temperature–pressure dual-parameter sensors using microstructure-frame-supported organic thermoelectric materials," Nature Communications, Nature, vol. 6(1), pages 1-10, December.
    3. Jiaqiang Huang & Laura Albero Blanquer & Julien Bonefacino & E. R. Logan & Daniel Alves Dalla Corte & Charles Delacourt & Betar M. Gallant & Steven T. Boles & J. R. Dahn & Hwa-Yaw Tam & Jean-Marie Tar, 2020. "Operando decoding of chemical and thermal events in commercial Na(Li)-ion cells via optical sensors," Nature Energy, Nature, vol. 5(9), pages 674-683, September.
    4. Wang, Yujie & Zhang, Xingchen & Chen, Zonghai, 2022. "Low temperature preheating techniques for Lithium-ion batteries: Recent advances and future challenges," Applied Energy, Elsevier, vol. 313(C).
    5. Xiong, Rui & Pan, Yue & Shen, Weixiang & Li, Hailong & Sun, Fengchun, 2020. "Lithium-ion battery aging mechanisms and diagnosis method for automotive applications: Recent advances and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    6. Wenxin Mei & Zhi Liu & Chengdong Wang & Chuang Wu & Yubin Liu & Pengjie Liu & Xudong Xia & Xiaobin Xue & Xile Han & Jinhua Sun & Gaozhi Xiao & Hwa-yaw Tam & Jacques Albert & Qingsong Wang & Tuan Guo, 2023. "Operando monitoring of thermal runaway in commercial lithium-ion cells via advanced lab-on-fiber technologies," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
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