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Battery health monitoring is critical for the efficient and reliable operation of electric vehicles (EVs).
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X. Li, P. Wang, J. Wang, F. Xiu, and Y. Xia, “State of health estimation and prediction of electric vehicle power battery based on operational vehicle data,” Journal of Energy Storage , vol. 72, p. 108247, 11 2023
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C. Bian, X. Han, Z. Duan, C. Deng, S. Yang, and J. Feng, “Hybrid prompt-driven large language model for robust state-of-charge estimation of multi-type li-ion batteries,” IEEE Transactions on Transportation Electrification , 2024
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Cited alongside, same era.
F. Xia, K. Wang, and J. Chen, “State of health and remaining useful life prediction of lithium-ion batteries based on a disturbance-free incremental capacity and differential voltage analysis method,” Journal of Energy Storage , vol. 64, p. 107161, 08 2023
2023
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2024
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2024
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W. Zheng, K. Li, and P. Fu, “Adaptive large language model for predicting lithium-ion battery degradation in energy storage systems,” Available at SSRN 4910174 , n.d
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