Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning

Forecasting the state of health and remaining useful life of Li-ion batteries is an unsolved challenge that limits technologies such as consumer electronics and electric vehicles. Here, we build an accurate battery forecasting system by combining electrochemical impedance spectroscopy (EIS)—a real-t...

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Detalles Bibliográficos
Autores principales: Zhang, Yunwei, Tang, Qiaochu, Zhang, Yao, Wang, Jiabin, Stimming, Ulrich, Lee, Alpha A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7136228/
https://www.ncbi.nlm.nih.gov/pubmed/32249782
http://dx.doi.org/10.1038/s41467-020-15235-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7136228/
https://www.ncbi.nlm.nih.gov/pubmed/32249782
http://dx.doi.org/10.1038/s41467-020-15235-7

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