A Sparse Learning Machine for Real-Time SOC Estimation of Li-ion Batteries

Zhang, L, Li, K orcid.org/0000-0001-6657-0522, Du, D et al. (3 more authors) (2020) A Sparse Learning Machine for Real-Time SOC Estimation of Li-ion Batteries. IEEE Access, 8. pp. 156165-156176. ISSN 2169-3536

Abstract

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Authors/Creators:
Copyright, Publisher and Additional Information: This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/
Keywords: State of charge, Batteries, Mathematical model, Estimation, Real-time systems, Kalman filters, Support vector machines
Dates:
  • Published: 8 September 2020
  • Accepted: 29 July 2020
  • Published (online): 24 August 2020
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: 28 Aug 2020 11:08
Last Modified: 22 Sep 2020 11:56
Status: Published
Publisher: IEEE
Identification Number: https://doi.org/10.1109/ACCESS.2020.3017774

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