Transfer learning prediction on lithium-ion battery heat release under thermal runaway condition
), Abstract
Accurately predicting the variability of thermal runaway (TR) behavior in lithium-ion (Li-ion) batteries is critical for designing safe and reliable energy storage systems. Unfortunately, traditional calorimetry-based experiments to measure heat release during TR are time-consuming and expensive. Herein, we highlight an exciting transfer learning approach that leverages mass ejection data and metadata from cells to predict heat output variability during TR events. This approach significantly reduces the effort and time to assess thermal risks associated with Li-ion batteries.
References
Chen, Y. Q.; Kang, Y. Q.; Zhao, Y.; Wang, L.; Liu, J. L.; Li, Y. X.; Liang, Z.; He, X. M.; Li, X.; Tavajohi, N. et al. A review of lithium-ion battery safety concerns: The issues, strategies, and testing standards. J. Energy Chem. 2021, 59, 83–99.
Jaguemont, J.; Bardé, F. A critical review of lithium-ion battery safety testing and standards. Appl. Therm. Eng. 2023, 231, 121014.
Shi, C. M.; Wang, T. Y.; Liao, X. B.; Qie, B. Y.; Yang, P. F.; Chen, M. J.; Wang, X.; Srinivasan, A.; Cheng, Q.; Ye, Q. et al. Accordion-like stretchable Li-ion batteries with high energy density. Energy Storage Mater. 2019, 17, 136–142.
Wu, P. H.; Lyu, N. W.; Song, Y. H.; Jiang, X.; Jin, Y. Li-ion battery failure warning methods for energy-storage systems. Chin. J. Electr. Eng. 2024, 10, 86–100.
Srinivasan, R.; Thomas, M. E.; Airola, M. B.; Carkhuff, B. G.; Frizzell-Makowski, L. J.; Alkandry, H.; Reuster, J. G.; Oguz, H. N.; Green, P. W.; La Favors, J. et al. Preventing cell-to-cell propagation of thermal runaway in lithium-ion batteries. J. Electrochem. Soc. 2020, 167, 020559.
Mallick, S.; Gayen, D. J. Thermal behaviour and thermal runaway propagation in lithium-ion battery systems–A critical review. J. Energy Storage 2023, 62, 106894.
Zhang, L. W.; Yang, S. Y.; Liu, L.; Zhao, P. Cell-to-cell variability in Li-ion battery thermal runaway: Experimental testing, statistical analysis, and kinetic modeling. J. Energy Storage 2022, 56, 106024.
Masalkovaitė, K.; Gasper, P.; Finegan, D. P. Predicting the heat release variability of Li-ion cells under thermal runaway with few or no calorimetry data. Nat. Commun. 2024, 15, 8399.
Finegan, D. P.; Billman, J.; Darst, J.; Hughes, P.; Trillo, J.; Sharp, M.; Benson, A.; Pham, M.; Kesuma, I.; Buckwell, M. The battery failure databank: Insights from an open-access database of thermal runaway behaviors of Li-ion cells and a resource for benchmarking risks. J. Power Sources 2024, 597, 234106.
Essl, C.; Golubkov, A. W.; Fuchs, A. Comparing different thermal runaway triggers for two automotive lithium-ion battery cell types. J. Electrochem. Soc. 2020, 167, 130542.
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