Recovering large-scale battery aging dataset with machine learning

Tang, X, Liu, K, Li, K et al. (3 more authors) (2021) Recovering large-scale battery aging dataset with machine learning. Patterns, 2. 100302. ISSN 2666-3899



Copyright, Publisher and Additional Information: © 2021 The Authors. This is an open access article under the CC BY-NC-ND license (
Keywords: battery aging assessment; battery aging dataset generation; lithium-ion battery management; incremental capacity analysis; model migration; machine learning; accelerated battery aging experiments
  • Accepted: 8 June 2021
  • Published (online): 30 June 2021
  • Published: 13 August 2021
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 02 Jul 2021 09:15
Last Modified: 02 Jul 2021 09:21
Status: Published
Publisher: Cell Press
Identification Number: