Deep learning approach towards accurate state of charge estimation for lithium-ion batteries using self-supervised transformer model

Abstract Accurate state of charge (SOC) estimation of lithium-ion (Li-ion) batteries is crucial in prolonging cell lifespan and ensuring its safe operation for electric vehicle applications. In this article, we propose the deep learning-based transformer model trained with self-supervised learning (...

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Autores principales: M. A. Hannan, D. N. T. How, M. S. Hossain Lipu, M. Mansor, Pin Jern Ker, Z. Y. Dong, K. S. M. Sahari, S. K. Tiong, K. M. Muttaqi, T. M. Indra Mahlia, F. Blaabjerg
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/37125291cee749d5afdfff954166db3d
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