Examples of Problems with Estimating the State of Charge of Batteries for Micro Energy Systems

Marian Kampik (), Marcin Fice (), Krzysztof Sztymelski, Wojciech Oliwa and Grzegorz Wieczorek
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Marian Kampik: Department of Measurement Science, Electronics and Control, Faculty of Electrical Engineering, Silesian University of Technology, 44-100 Gliwice, Poland
Marcin Fice: Department of Electrical Engineering and Computer Science, Faculty of Electrical Engineering, Silesian University of Technology, 44-100 Gliwice, Poland
Krzysztof Sztymelski: Department of Electrical Engineering and Computer Science, Faculty of Electrical Engineering, Silesian University of Technology, 44-100 Gliwice, Poland
Wojciech Oliwa: Department of Electronics, Electrical Engineering, and Microelectronics, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, 44-100 Gliwice, Poland
Grzegorz Wieczorek: Department of Electronics, Electrical Engineering, and Microelectronics, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, 44-100 Gliwice, Poland

Energies, 2025, vol. 18, issue 11, 1-25

Abstract: Accurate estimation of the state of charge (SOC) is important for the effective management and utilization of lithium-ion battery packs. While advanced estimation methods present in scientific literature commonly rely on detailed cell parameters and laboratory-controlled conditions, practical engineering applications often require solutions applicable to battery packs with unknown or limited internal characteristics. In this context, this study compares three different SOC estimation strategies—voltage-based, coulomb counting, and charge balance methods—implemented in an independent telemetry module (TIO) and their performance against a commercial battery management system (Orion BMS2). Experimental results demonstrate that the voltage-based method provides insufficient accuracy due to its inherent sensitivity to voltage thresholds and internal resistance under load conditions. Conversely, coulomb counting, with periodic recalibration through full charging cycles, showed significantly improved accuracy, closely matching the Orion BMS2 outputs when properly initialized. The results confirm the viability of coulomb counting as a pragmatic approach for battery packs lacking detailed cell data. Future research should address reducing dependency on periodic full-charge resets by incorporating adaptive estimation techniques, such as Kalman filtering or observers, and leveraging open-circuit voltage measurements and temperature compensation to further enhance accuracy while maintaining the simplicity and external applicability of the monitoring system.

Keywords: lithium-ion battery; state of charge estimation; coulomb counting; battery management system; telemetry module; voltage-based estimation; practical engineering methods; battery pack monitoring (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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