Mass load prediction for lithium-ion battery electrode clean production: a machine learning approach

Liu, K, Wei, Z, Yang, Z et al. (1 more author) (2021) Mass load prediction for lithium-ion battery electrode clean production: a machine learning approach. Journal of Cleaner Production, 289. 125159. ISSN 0959-6526

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: © 2020 Elsevier Ltd. This is an author produced version of a paper published in Journal of Cleaner Production. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Battery electrode production; data-driven model; mass load prediction; efficient energy storage system; cleaner production
Dates:
  • Accepted: 14 November 2020
  • Published (online): 18 November 2020
  • Published: 20 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) > Institute of Communication & Power Networks (Leeds)
Funding Information:
FunderGrant number
EPSRC (Engineering and Physical Sciences Research Council)EP/R030243/1
Depositing User: Symplectic Publications
Date Deposited: 25 Nov 2020 11:54
Last Modified: 18 Nov 2021 01:38
Status: Published
Publisher: Elsevier
Identification Number: https://doi.org/10.1016/j.jclepro.2020.125159

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