Online Monitoring of Batteries in Modular Multilevel Energy Storage Systems Without Disturbing the Electrical Network

Accurate monitoring of battery parameters is essential for optimizing the performance, safety and longevity of grid scale battery energy storage systems (BESSs). Conventionally, equivalent circuit model (ECM) parameter identification is per formed through offline testing, which results in costly downtime, or through online perturbation-based methods, which disturb the grid undesirably. In contrast, this paper proposes a method for online ECM parameter identification in modular multilevel cascaded converter (MMCC)-based BESSs that introduces no disturbances into the electrical grid. The proposed technique injects controlled current harmonic perturbations into the battery terminals while using a novel control strategy to cancel the net effect of these harmonics at the grid interface. This is enabled by leveraging the inherent interleaving capability of the MMCC-based BESS. This control-based solution eliminates the need for oversized buffer capacitors or extra hardware, and can be integrated seamlessly within existing control schemes. Validation is performed using a 3.84-kW/3.46-kWh lab prototype under various grid conditions, demonstrating accurate real-time ECM parameter estimation via recursive least squares without distorting the grid current.