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Engineering Proceedings
Volume 79
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10.3390/engproc2024079045
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Proceeding Paper

Performance Comparison of the General, the Dual, and the Joint Sigma Point Kalman Filters on State Estimation of Li-Ion Battery Cells for BMSs †

by
Tamás Horváth
* and
Dénes Fodor
Department of Power Electronics and E-Drives, Széchenyi István University, 9026 Győr, Hungary
*
Author to whom correspondence should be addressed.
†
Presented at the Sustainable Mobility and Transportation Symposium 2024, Győr, Hungary, 14–16 October 2024.
Eng. Proc. 2024, 79(1), 45; https://doi.org/10.3390/engproc2024079045
Published: 6 November 2024
(This article belongs to the Proceedings of The Sustainable Mobility and Transportation Symposium 2024)
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Abstract

Li-ion batteries, known for high energy and power density, are widely used in electromobility and stationary applications. In these applications a Battery Management System (BMS) ensures safety and longevity by performing functions like cell balancing and protecting against overcharge and over-discharge. Advanced BMSs estimate the battery’s State of Charge (SOC), crucial for determining remaining operating time and safe range. This study compares three Kalman Filter (KF)-based SOC estimation techniques: the general Sigma Point KF (SPKF), the joint SPKF, and the dual SPKF, for state and parameter estimation of a Samsung 18650INR13L Li-ion battery.
Keywords: SOC and SOH estimation; sigma point Kalman filter (SPKF); joint SPKF; dual SPKF SOC and SOH estimation; sigma point Kalman filter (SPKF); joint SPKF; dual SPKF

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MDPI and ACS Style

Horváth, T.; Fodor, D. Performance Comparison of the General, the Dual, and the Joint Sigma Point Kalman Filters on State Estimation of Li-Ion Battery Cells for BMSs. Eng. Proc. 2024, 79, 45. https://doi.org/10.3390/engproc2024079045

AMA Style

Horváth T, Fodor D. Performance Comparison of the General, the Dual, and the Joint Sigma Point Kalman Filters on State Estimation of Li-Ion Battery Cells for BMSs. Engineering Proceedings. 2024; 79(1):45. https://doi.org/10.3390/engproc2024079045

Chicago/Turabian Style

Horváth, Tamás, and Dénes Fodor. 2024. "Performance Comparison of the General, the Dual, and the Joint Sigma Point Kalman Filters on State Estimation of Li-Ion Battery Cells for BMSs" Engineering Proceedings 79, no. 1: 45. https://doi.org/10.3390/engproc2024079045

APA Style

Horváth, T., & Fodor, D. (2024). Performance Comparison of the General, the Dual, and the Joint Sigma Point Kalman Filters on State Estimation of Li-Ion Battery Cells for BMSs. Engineering Proceedings, 79(1), 45. https://doi.org/10.3390/engproc2024079045

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