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- W3048178352 abstract "This paper proposes a neural network model for state-of-charge (SOC) estimation in lithium-ion battery cells. The proposed deep neural network model is a cycle-based recurrent model that leverages relevant information from historical cycles to provide reliable estimates of the state-of-charge of on-going cycles within a mean-absolute error (MAE) of 1%. In addition, the proposed model can be trained in a relatively short time. Details on the model followed by experimental verification are provided." @default.
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- W3048178352 date "2020-06-01" @default.
- W3048178352 modified "2023-09-24" @default.
- W3048178352 title "A Cycle-based Recurrent Neural Network for State-of-Charge Estimation of Li-ion Battery Cells" @default.
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- W3048178352 doi "https://doi.org/10.1109/itec48692.2020.9161587" @default.
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