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A self-attention-based CNN-Bi-LSTM model for accurate state-of-charge estimation of lithium-ion batteries

Zeinab Sherkatghanad, Amin Ghazanfari and Vladimir Makarenkov

Article (2024)

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Department: Department of Electrical Engineering
PolyPublie URL: https://publications.polymtl.ca/58059/
Journal Title: Journal of Energy Storage (vol. 88)
Publisher: Elsevier
DOI: 10.1016/j.est.2024.111524
Official URL: https://doi.org/10.1016/j.est.2024.111524
Date Deposited: 30 Apr 2024 12:41
Last Modified: 30 Apr 2024 12:41
Cite in APA 7: Sherkatghanad, Z., Ghazanfari, A., & Makarenkov, V. (2024). A self-attention-based CNN-Bi-LSTM model for accurate state-of-charge estimation of lithium-ion batteries. Journal of Energy Storage, 88, 111524 (10 pages). https://doi.org/10.1016/j.est.2024.111524

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