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

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.