In Situ Optical Fiber Sensing of Internal Temperature Evolution during Lithium-Ion Battery Cycling

The internal temperature of high-capacity lithium-ion batteries (LiBs) plays a crucial role in triggering thermal runaway. Current research on battery thermal runaway primarily relies on external temperature sensors, which are unable to provide real-time temperature distribution data from various sections within the battery cells. Consequently, early detection of thermal runaway in batteries is hindered. To address this limitation, this study investigates arrayed fiber Bragg grating sensors (AFBGs) positioned between two cells to continuously monitor the temperature distribution across different cell sections during operation. The results indicate that in battery charge-discharge tests conducted at rates of 0.2, 0.5, and 0.75 P, the maximum thermal gradient along the cell's vertical axis (from top to bottom) reaches 6.8 °C during 0.75 P, with the geometric center of the jelly roll surface identified as the most temperature-sensitive location. Consequently, the implementation of multipoint monitoring is deemed essential for early thermal runaway detection. The analysis at the battery pack level reveals that during the charging process, a temperature variance of 8.3 °C exists among batteries, highlighting central/peripheral thermal nonuniformity. Additionally, external sensors underestimate the internal temperature by 19.4 °C, further emphasizing the importance of internal monitoring. Linear regression analysis shows a strong linear correlation (<i>R</i> <sup>2</sup> = 0.999) between the maximum internal temperature and the charge-discharge rate, which facilitates predictive monitoring by the battery management system (BMS). Furthermore, this sensor demonstrates compatibility with battery production processes and maintains stability over 500 cycles. These results suggest that this sensing approach could serve as a reliable method for long-term battery monitoring.

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Publication Details

Journal
ACS Omega
Published
2025-10-02
DOI
https://doi.org/10.1021/acsomega.5c07124
Citations
2
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
1.37
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article

In Situ Optical Fiber Sensing of Internal Temperature Evolution during Lithium-Ion Battery Cycling

Fanchao Zeng, Zhenming Li, Chong Xu, Xinglin Tong et al.
2 citations
ACS Omega
Advanced Battery Technologies Research
1.37
article

In Situ Optical Fiber Sensing of Internal Temperature Evolution during Lithium-Ion Battery Cycling

Fanchao Zeng, Zhenming Li, Chong Xu, Xinglin Tong, Zhongfan Liu
article en
2 citations

Abstract

The internal temperature of high-capacity lithium-ion batteries (LiBs) plays a crucial role in triggering thermal runaway. Current research on battery thermal runaway primarily relies on external temperature sensors, which are unable to provide real-time temperature distribution data from various sections within the battery cells. Consequently, early detection of thermal runaway in batteries is hindered. To address this limitation, this study investigates arrayed fiber Bragg grating sensors (AFBGs) positioned between two cells to continuously monitor the temperature distribution across different cell sections during operation. The results indicate that in battery charge-discharge tests conducted at rates of 0.2, 0.5, and 0.75 P, the maximum thermal gradient along the cell's vertical axis (from top to bottom) reaches 6.8 °C during 0.75 P, with the geometric center of the jelly roll surface identified as the most temperature-sensitive location. Consequently, the implementation of multipoint monitoring is deemed essential for early thermal runaway detection. The analysis at the battery pack level reveals that during the charging process, a temperature variance of 8.3 °C exists among batteries, highlighting central/peripheral thermal nonuniformity. Additionally, external sensors underestimate the internal temperature by 19.4 °C, further emphasizing the importance of internal monitoring. Linear regression analysis shows a strong linear correlation (<i>R</i> <sup>2</sup> = 0.999) between the maximum internal temperature and the charge-discharge rate, which facilitates predictive monitoring by the battery management system (BMS). Furthermore, this sensor demonstrates compatibility with battery production processes and maintains stability over 500 cycles. These results suggest that this sensing approach could serve as a reliable method for long-term battery monitoring.

ACS OmegaVol. 10(40)
North China Electric Power University (CN), Wuhan University of Technology (CN), Energy Storage Systems (United States) (US), China Electric Power Research Institute
Openalex Percentile: Top 17%
Advanced Battery Technologies Research
1.37
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