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      The development of machine learning-based remaining useful life prediction for lithium-ion batteries

      Author(s): , , ,
      Publication date Created:
      Publication date (Print):
      Journal: Journal of Energy Chemistry
      Publisher: Elsevier BV

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          Data-driven prediction of battery cycle life before capacity degradation

          Kristen A. Severson, Peter Attia, Norman Jin … (2019)
          Article 0 comments Cited 296 times – based on 0 reviews     Review now
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            Closed-loop optimization of fast-charging protocols for batteries with machine learning

            Peter Attia, Aditya Grover, Norman Jin … (2020)
            Article 0 comments Cited 159 times – based on 0 reviews     Review now
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              Long Short-Term Memory Recurrent Neural Network for Remaining Useful Life Prediction of Lithium-Ion Batteries

              Yongzhi Zhang, Rui Xiong, Hongwen He … (2018)
              Article 0 comments Cited 124 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Title: Journal of Energy Chemistry
                Abbreviated Title: Journal of Energy Chemistry
                Publisher: Elsevier BV
                ISSN (Print): 20954956
                Publication date Created: July 2023
                Publication date (Print): July 2023
                Volume: 82
                Pages: 103-121
                Article
                DOI: 10.1016/j.jechem.2023.03.026
                SO-VID: aee6d5ae-60f8-4e92-b412-a0a664d009e0
                Copyright © © 2023
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                https://www.elsevier.com/tdm/userlicense/1.0/

                http://creativecommons.org/licenses/by/4.0/

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