Data-selection for state estimation of large-scale battery systems

Wang, Z., Gladwin, D.T. orcid.org/0000-0001-7195-5435, Smith, M.J. orcid.org/0000-0002-2329-8220 et al. (1 more author) (2021) Data-selection for state estimation of large-scale battery systems. In: IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society. IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society, 13-16 Oct 2021, Toronto, ON, Canada. IEEE, pp. 1-6. ISBN: 9781665402569. ISSN: 1553-572X. EISSN: 2577-1647.

Abstract

Large-scale battery energy storage systems (BESS) are drawing the attention of researchers as numbers installed globally is rising rapidly. Like single cells, the battery states, most importantly state of charge (SOC) and state of health (SOH) of BESSs are essential for their operation. However, for large-scale battery systems, the data granularity, accuracy and quality are limited compared with the cell-level. To achieve accurate state estimation of battery systems the selection of data used for processing is essential. In this paper, it is shown that how to evaluate and select system-level data for SOC and SOH estimation. These methods are expected to be used for other BESSs.

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Item Type:	Proceedings Paper
Authors/Creators:	Wang, Z. Gladwin, D.T. https://orcid.org/0000-0001-7195-5435 Smith, M.J. https://orcid.org/0000-0002-2329-8220 Fantham, T.L.
Copyright, Publisher and Additional Information:	© 2024 The Authors. Except as otherwise noted, this author-accepted version of a paper published in IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/
Keywords:	Battery System; State of Charge; State of health; Data selection; Invalid Data
Dates:	Published (online): 10 November 2021 Published: 10 November 2021
Institution:	The University of Sheffield
Academic Units:	The University of Sheffield > Faculty of Engineering (Sheffield) > School of Electrical and Electronic Engineering
Funding Information:	Funder Grant number Engineering and Physical Sciences Research Council EP/R512175/1 Engineering and Physical Sciences Research Council 2110436
Date Deposited:	18 Nov 2025 12:48
Last Modified:	18 Nov 2025 12:48
Status:	Published
Publisher:	IEEE
Refereed:	Yes
Identification Number:	10.1109/iecon48115.2021.9589452
Related URLs:	Conference
Sustainable Development Goals:
Open Archives Initiative ID (OAI ID):	oai:eprints.whiterose.ac.uk:234538

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Data-selection for state estimation of large-scale battery systems

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