Battery Charge Curve Prediction via Feature Extraction and Supervised Machine Learning.

Su, Laisuo; Zhang, Shuyan; McGaughey, Alan J H; Reeja-Jayan, B; Manthiram, Arumugam

Su, Laisuo; Zhang, Shuyan; McGaughey, Alan J H; Reeja-Jayan, B; Manthiram, Arumugam.

Afiliación

Su L; Materials Science and Engineering Program & Texas Materials Institute, The University of Texas at Austin, Austin, TX, 78712-1591, USA.
Zhang S; Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213, USA.
McGaughey AJH; Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213, USA.
Reeja-Jayan B; Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, 15213, USA.
Manthiram A; Materials Science and Engineering Program & Texas Materials Institute, The University of Texas at Austin, Austin, TX, 78712-1591, USA.

Adv Sci (Weinh) ; 10(26): e2301737, 2023 Sep.

Article en En | MEDLINE | ID: mdl-37394730

Palabras clave

batteries; charge curves; feature extraction; machine learning; prediction

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Aspecto: Patient_preference Idioma: En Revista: Adv Sci (Weinh) Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Alemania

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