Optimized multi-hidden layer long short-term memory modeling and suboptimal fading extended Kalman filtering strategies for the synthetic state of charge estimation of lithium-ion batteries

doi:10.1016/j.apenergy.2023.120866

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Optimized multi-hidden layer long short-term memory modeling and suboptimal fading extended Kalman filtering strategies for the synthetic state of charge estimation of lithium-ion batteries (2023) | RDL Network

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Optimized multi-hidden layer long short-term memory modeling and suboptimal fading extended Kalman filtering strategies for the synthetic state of charge estimation of lithium-ion batteries

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Frede Blaabjerg

Aalborg University

Optimized multi-hidden layer long short-term memory modeling and suboptimal fading extended Kalman filtering strategies for the synthetic state of charge estimation of lithium-ion batteries

Article 2023 en

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Publication Info

DOI: 10.1016/j.apenergy.2023.120866
Year: 2023
Published: —
Language: en

Article Details

Volume: 336
Link Of The Paper: https://doi.org/10.1016/j.apenergy.2023.120866

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Created:June 19, 2026

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