An adaptive fractional-order unscented Kalman filter for Li-ion batteries in the energy storage system

Accurate estimation of the state charge (SOC) can prolong working life and enhance safety energy storage system. Considering influence noise parameter changes in operating environment, an adaptive fractional-order unscented Kalman filter algorithm is introduced to strengthen accuracy SOC estimation. To verify effectiveness robustness algorithm, simulation carried out under UDDS complex conditions. The experimental results indicate that proposed has highest precision among four algorithms, RMSE 1.37%, indicating superiority modeling joint algorithm. online identification full parameters solve shortcoming long time obtain open-circuit voltage experiment, filtering overcome problem divergence improve flexibility