OMILOLI, KOTO ANDREW and Awelewa, A. A. and Samuel, I. A. and OBIAZI, OGHORCHUKWUYEM ORIEKOSE and Katende, James (2023) State of charge estimation based on a modified extended Kalman filter. International Journal of Electrical and Computer Engineering, 13 (5). pp. 5054-5065. ISSN 2088-8708
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Abstract
The global transition from fossil-based automobile systems to their electric-driven counterparts has made the use of a storage device inevitable. Owing to its high energy density, lower self-discharge, and higher cycle lifetime the lithium-ion battery is of significant consideration and usage in electric vehicles. Nevertheless, the state of charge (SOC) of the battery, which cannot be measured directly, must be calculated using an estimator. This paper proposes, by means of a modified priori estimate and a compensating proportional gain, an improved extended Kalman filter (IEKF) for the estimation task due to its nonlinear application and adaptiveness to noise. The improvement was achieved by incorporating the residuals of the previous state matrices to the current state predictor and introducing an attenuating factor in the Kalman gain, which was chosen to counteract the effect of the measurement and process noise resulting in better accuracy performance than the conventional SOC curve fitting-based estimation and ampere hour methods. Simulation results show that the standard EKF estimator results in performance with an error bound of 12.9% due to an unstable start, while the modified EKF reduces the maximum error to within 2.05% demonstrating the quality of the estimator.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Extended Kalman filter Gain Lithium-ion battery Noise State estimate State of charge |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Electronics and Computer Science |
| Depositing User: | Patricia Nwokealisi |
| Date Deposited: | 18 Nov 2024 16:03 |
| Last Modified: | 20 Nov 2024 15:49 |
| URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/18600 |
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