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This paper presents a novel real-time hybrid battery state of charge (SoC) and state of health (SoH) estimation technique with less computational effort for optimal operation in renewable energy integrated microgrid applications. The proposed SoC estimation technique utilizes battery terminal voltage and current information along with stress factors like battery charge–discharge rates and temperature effects to accurately estimate the SoC. In addition, it considers the open-circuit voltage (OCV) and SoC relation to dynamically recalibrate the SoC during idle conditions. The proposed SoH estimation technique uses a modified coulomb counting method and variation of battery capacity at different charge–discharge rates to precisely estimate the SoH of the battery. Simulation studies are carried out by considering the aging factor, temperature effect, and charge–discharge rates to analyze the performance of the proposed techniques under various dynamic conditions. A LabVIEW-based application is developed, and experimental verification in terms of estimation accuracy, real-time monitoring is carried out to verify the efficacy of the proposed technique. A comparative analysis with state-of-the-art estimation techniques is presented for validating the effectiveness and usefulness in real-time applications.

A real-time hybrid battery state of charge and state of health estimation technique in renewable energy integrated microgrid applications