Lithium-ion battery capacity estimation — A pruned convolutional neural network approach assisted with transfer learning

Li, Y orcid.org/0000-0002-5521-9224, Li, K, Liu, X et al. (2 more authors) (2021) Lithium-ion battery capacity estimation — A pruned convolutional neural network approach assisted with transfer learning. Applied Energy, 285. 116410. ISSN 0306-2619

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2021, Elsevier Ltd. All rights reserved. This is an author produced version of an article published in Applied Energy. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Capacity estimation; Convolutional neural networks; Lithium-ion batteries; Network pruning; Transfer learning
Dates:
  • Accepted: 27 December 2020
  • Published (online): 4 January 2021
  • Published: 1 March 2021
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds)
Funding Information:
FunderGrant number
EPSRC (Engineering and Physical Sciences Research Council)EP/R030243/1
Depositing User: Symplectic Publications
Date Deposited: 05 Jan 2021 17:52
Last Modified: 04 Jan 2022 01:38
Status: Published
Publisher: Elsevier
Identification Number: https://doi.org/10.1016/j.apenergy.2020.116410

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