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

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 (SSL) for...

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Detalles Bibliográficos
Autores principales: Hannan, M. A., How, D. N. T., Lipu, M. S. Hossain, Mansor, M., Ker, Pin Jern, Dong, Z. Y., Sahari, K. S. M., Tiong, S. K., Muttaqi, K. M., Mahlia, T. M. Indra, Blaabjerg, F.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8486825/
https://www.ncbi.nlm.nih.gov/pubmed/34599233
http://dx.doi.org/10.1038/s41598-021-98915-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8486825/
https://www.ncbi.nlm.nih.gov/pubmed/34599233
http://dx.doi.org/10.1038/s41598-021-98915-8

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