SOC Estimation of Lithium Battery Based on Fractional Order AUKF Algorithm

With the advancement of electric vehicles and energy storage and other fields, the precise determination of lithium-ion batteries’ State of Charge (SOC) has transformed into one of the main issues restricting its sophisticated development. This paper introduces a fractional-order model (FOM) derived from the common used second-order equivalent circuit model (ECM), and the model parameters are determined by particle swarm optimization (PSO). For the purpose of solving filter divergence caused by nonlinear noise during SOC estimation, the Adaptive Unscented Kalman Filter (AUKF) algorithm was introduced to calculate lithium-ion batteries’ SOC. As a test of the algorithm's effectiveness and robustness, two different complex working conditions are simulated and keep AUKF in comparison with other algorithms. The experimental results demonstrate that the estimation of SOC using FOAUKF has high estimation accuracy.