Hybrid State of Charge Estimation of Lithium-Ion Battery Using the Coulomb Counting Method and an Adaptive Unscented Kalman Filter

Fahmy, Hend M.; Swief, Rania A.; Hasanien, Hany M.; Alharbi, Mohammed; Maldonado, José Luis; Jurado, Francisco

doi:10.3390/en16145558

Cited by 26Advanced Battery Technologies ResearchControl Systems and IdentificationAdvancements in Battery Materials

Hybrid State of Charge Estimation of Lithium-Ion Battery Using the Coulomb Counting Method and an Adaptive Unscented Kalman Filter

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Fahmy, Hend M., Swief, Rania A., Hasanien, Hany M., Alharbi, Mohammed, Maldonado, José Luis, Jurado, Francisco·2023·Energies

DOI 10.3390/en16145558

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Abstract

This paper establishes an accurate and reliable study for estimating the lithium-ion battery’s State of Charge (SoC). An accurate state space model is used to determine the parameters of the battery’s nonlinear model. African Vultures Optimizers (AVOA) are used to solve the issue of identifying the battery parameters to accurately estimate SoC. A hybrid approach consists of the Coulomb Counting Method (CCM) with an Adaptive Unscented Kalman Filter (AUKF) to estimate the SoC of the battery. At different temperatures, four approaches are applied to the battery, varying between including load and battery fading or not. Numerical simulations are applied to a 2.6 Ahr Panasonic Li-ion battery to demonstrate the hybrid method’s effectiveness for the State of Charge estimate. In comparison to existing hybrid approaches, the suggested method is very accurate. Compared to other strategies, the proposed hybrid method achieves the least error of different methods.

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Adaptive filtering techniques entail high computational cost in complex systems, including high-dimensional, high-volume systems.
“This station enjoys numerous benefits, but adaptive filtering techniques do entail high computational cost in systems that are complex, including high-dimensional, high-volume systems [82].”
From Review Paper for SOC Estimation Techniques: Challenges and Future Areas for Improvement (2024) · cites this paper as [82]
Filter performance depends on the quality of the initial model and the calibration of adaptive parameters, which poses problems in some processes.
“Moreover, the filter's filter performance also depends on the quality of the first model and the calibration of adaptable parameters, which poses problems in some processes.”
From Review Paper for SOC Estimation Techniques: Challenges and Future Areas for Improvement (2024) · cites this paper as [82]

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Authors: Fahmy, H. M., Swief, R. A., Hasanien, H. M., Alharbi, M., Maldonado, J. L., & Jurado, F.
Affiliations: Ain Shams University (EG)
King Saud University (SA)
Universidad de Jaén (ES)
Corresponding author: Hasanien, Hany M.
ORCID: Fahmy, Hend M.
Swief, Rania A.
Hasanien, Hany M.
Alharbi, Mohammed
Maldonado, José Luis
Jurado, Francisco
Venue: Energies
Publisher: MDPI AG
Published: 2023-07-22
Volume: 16
Issue: 14
Pages: 5558
ISSN: 1996-1073 (ISSN-L)
DOI: 10.3390/en16145558
OpenAlex: W4385161877
Cited by: 25
References: 32
Citations by year: 2026: 9 · 2025: 5 · 2024: 11
FWCI: 1.81
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (vor)
Locations: Energies (publishedVersion, cc-by)
RUJA. Institutional Repository of Scientific Production of the University of Jaén (University of Jaén) (acceptedVersion, cc-by-nc-nd)
RePEc: Research Papers in Economics (submittedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders: King Saud University, Riyadh, Saudi Arabia
Topics: Physical Sciences › Engineering › Automotive Engineering › Advanced Battery Technologies Research
Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
Physical Sciences › Engineering › Electrical and Electronic Engineering › Advancements in Battery Materials
Keywords: lithium-ion batteries, state of charge estimation, Coulomb counting, adaptive unscented Kalman filter, parameter estimation, state-space model, temperature effects, hybrid estimation

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Hybrid State of Charge Estimation of Lithium-Ion Battery Using the Coulomb Counting Method and an Adaptive Unscented Kalman Filter

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