State estimation method of supercapacitor based on EKF-AUKF algorithm and transient model

The multi branch model of supercapacitors can accurately describe the charging and discharging characteristics of supercapacitors, but when using it for supercapacitor state estimation, it is difficult to obtain accurate parameters, resulting in significant errors in the state estimation results. In order to improve the accuracy of parameter identification and state estimation of supercapacitors during transient processes, an EKF-AUKF state estimation algorithm based on transient models is proposed. Firstly, the feasibility of model simplification under fast charging and discharging conditions was analyzed, and the multi branch model was simplified under the condition of feasibility; Secondly, the model parameters are added as extended states to the state equation, and the EKF-AUKF algorithm is used to simultaneously estimate the equivalent circuit parameters and states of the supercapacitor; Finally, the accuracy of the proposed method was verified through simulation. The experimental results show that the EKF-AUKF algorithm based on transient models can achieve accurate parameter identification and state estimation.