An improved forgetting factor recursive least square and extended particle filtering algorithm for accurate lithium-ion battery state of energy estimation
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11581-024-05698-9.pdf
Reference48 articles.
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3. Xu M, Zhang E, Wang S, Shen Y, Zou B, Li H, Wan Y, Wang K, Jiang K (2024) Dynamic ultrasonic response modeling and accurate state of charge estimation for lithium ion batteries under various load profiles and temperatures. Appl Energy 355:122210. https://doi.org/10.1016/j.apenergy.2023.122210
4. Wei M, Ye M, Zhang C, Lian G, Xia B, Wang Q (2024) Robust state of charge estimation of LiFePO4 batteries based on Sage_Husa adaptive Kalman filter and dynamic neural network. Electrochim Acta 477:143778. https://doi.org/10.1016/j.electacta.2024.143778
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