Kadem, O. orcid.org/0000-0002-4192-1047 and Kim, J. orcid.org/0000-0002-3456-6614 (2024) Mitigation of state of charge estimation error due to noisy current input measurement. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 238 (1). 34 -46. ISSN 0959-6518
Abstract
The key indicator to assess the performance of a battery management system is the state of charge (SoC). Although various SoC estimation algorithms have been developed to increase the estimation accuracy, the effect of the current input measurement error on the SoC estimation has not been adequately considered in these algorithms. The majority of SoC estimation algorithms are based on noiseless current measurement models in the literature. More realistic battery models must include the current measurement modelled with the bias noise and the white noise. We present a novel method for mitigating noise in current input measurements to reduce the SoC estimation error. The proposed algorithm is validated by computer simulations and battery experiments. The results show that the proposed method reduces the maximum SoC estimation error from around 11.3% to 0.56% in computer simulations and it is reduced from 1.74% to 1.17% in the battery experiment.
Metadata
Item Type: | Article |
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Authors/Creators: | |
Copyright, Publisher and Additional Information: | © IMechE 2023. This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
Keywords: | State of charge estimation error, noisy current input measurement, online parameter estimation, adaptive Kalman filtering, current noise mitigation |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) > Institute of Engineering Systems and Design (iESD) (Leeds) The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Mechanical Engineering (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 03 Aug 2023 10:32 |
Last Modified: | 22 Nov 2024 10:29 |
Status: | Published |
Publisher: | SAGE |
Identification Number: | 10.1177/09596518231182308 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:201359 |