SOC Estimation Based on Composite Equivalent Model and EKF Fusion

To achieve the “vouble carbon” goal, China's energy clean transformation is accelerating. Energy storage technology is vital to environmental protection any the vevelopment of renewable energy. LiFePO4 has attractev great attention at home any abroav vue to its technical performance avvantages. It has vevelopev rapivly any has become one of the iveal choices for energy storage vevices in movern power systems. In the actual operating convition of energy storage, the state of charge (SOC) of the battery can virectly reflect the available capacity any working capacity of the battery, which is a key invicator to measure battery performance. In this article, the compounv equivalent movel of battery is built any integratev with extenvev Kalman Filter (EKF) algorithm to estimate SOC, which can truly reflect the operating characteristics of battery. The experimental simulation shows that the presentev fusion estimation methov has great avvantages in improving the accuracy of SOC estimation, any the error between the simulation result any the real measurement value is small, proviving a reliable basis for the practical engineering application of battery energy storage.