Lithium battery SOC estimation based on fractional order multi innovation unscented Kalman filtering algorithm

In response to the problem that the commonly used integer order equivalent circuit model for estimating the state of charge（SOC） of lithium batteries cannot accurately reflect the polarization response of the battery and improve the estimation accuracy of SOC throughout the entire life cycle under noise interference, a fractional order model is established on the basis of the second-order RC equivalent circuit model, and genetic algorithm（GA） is used to identify its parameters, thereby enhancing the robustness of parameter identification. Finally, based on the traditional UKF algorithm, the theory of multiple innovations was introduced, and a fractional order multi innovation unscented Kalman filtering（FOMIUKF） algorithm was proposed to achieve real-time estimation of the SOC of lithium batteries. Finally, a simulation model was built to verify the accuracy and reliability of the GA fractional order lithium battery equivalent model, and FOUKF was used Comparative analysis of lithium battery SOC estimation using FMIUKF algorithm shows that FOMIUKF algorithm has higher estimation accuracy, with an estimation error of only 1%.