Real-time peak power prediction for zinc nickel single flow batteries

Li, X orcid.org/0000-0002-1536-4195, Kang, LI, Xiao, E et al. (2 more authors) (2020) Real-time peak power prediction for zinc nickel single flow batteries. Journal of Power Sources, 448. 227346. ISSN 0378-7753

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Copyright, Publisher and Additional Information: (c) 2019, Elsevier Ltd. All rights reserved. This is an author produced version of a paper published in Journal of Power Sources. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: online model identification; Real-time estimation; Peak power prediction; Zinc nickel single assisted flow batteries
Dates:
  • Published: 1 February 2020
  • Accepted: 22 October 2019
  • Published (online): 17 November 2019
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 Nov 2019 12:39
Last Modified: 17 Nov 2020 01:39
Status: Published
Publisher: Elsevier
Identification Number: https://doi.org/10.1016/j.jpowsour.2019.227346

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