Joint Estimation of State of Charge and State of Health and Fault Early Warning for Energy Storage Power Station based on Double Unscented Kalman Filter Algorithm

The state of charge (SOC) and state of health (SOH) of a lithium battery are important core parameters for the battery management system. During operation of an energy storage power station, the on-line SOC and SOH of each single cell in the battery energy storage system must be estimated accurately to allow these parameters to play roles in providing early warning of energy storage power station failure, avoiding overcharging or discharging of the battery, and enabling timely battery replacement following aging. This ensures safe and stable operation of the energy storage power station. Therefore, to improve the estimation accuracy of the lithium battery SOC and SOH, based on a second-order resistor-capacitor equivalent circuit model, the double unscented Kalman filter algorithm is used to estimate the lithium battery SOC and SOH jointly online. The accuracy and stability of the proposed method are verified under DST conditions.