Rezaei, O., Alinejad, M., Nejati, S.A. et al. (1 more author) (2021) An optimized adaptive estimation of state of charge for Lithium-ion battery based on sliding mode observer for electric vehicle application. In: Proceedings of 2020 8th International Conference on Intelligent and Advanced Systems (ICIAS). 2020 8th International Conference on Intelligent and Advanced Systems (ICIAS), 13-15 Jul 2021, Kuching, Malaysia. Institute of Electrical and Electronics Engineers (IEEE) ISBN 978-1-7281-7666-6
Abstract
As lithium-ion batteries have nonlinearities and also uncertainties in parameter identification in their dynamical model, accurate estimation of SoC requires robust and nonlinear estimators. Using a sliding mode observer, this paper presents an optimal adaptive estimator to measure the state of charge (SoC) of lithium-ion batteries (LIB). The conventional sliding mode observers have chattering phenomena and prolong convergence time in their performance, but the sliding mode observer proposed in this paper includes an adaptive gain which causes less chattering and convergence time. The simulation results and software in the loop (SIL) validation confirm the effectiveness of the proposed estimation method of SoC.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Keywords: | State of charge, Estimation, Lithium-ion battery, Robust observer, Optimization |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 02 Jun 2025 10:38 |
Last Modified: | 02 Jun 2025 10:38 |
Status: | Published |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Identification Number: | 10.1109/icias49414.2021.9642675 |
Related URLs: | |
Sustainable Development Goals: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:227253 |