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Keywords

supercapacitor; transient model; EKF-AUKF algorithm; parameter identification; state estimation

Abstract

The multi-branch model of a supercap acitor can accurately describe the charge and discharge characteristics of a supercapacitor, but it is difficult to obtain the exact parameters when it is used to estimate the state of the supercapacitor, resulting in large errors in the state estimation results. In order to improve the accuracy of supercapacitor parameter identification and state estimation in the transient process, a state estimation algorithm combining an extended Kalman filter (EKF) and an adaptive unscented Kalman filter (AUKF) based on a transient model is proposed. Firstly, the model simplification feasibility in the case of fast charge and discharge is analyzed, and the multi-branch model is simplified when the feasibility is established. Secondly, the model parameters are added into the state equation as extended states, and the EKF-AUKF algorithm is used to estimate the equivalent circuit parameters and states of the supercapacitor simultaneously. Finally, the accuracy of the EKF-AUKF algorithm is validated by simulation and experiment. The experimental results show that the EKF-AUKF algorithm based on the transient model can achieve accurate parameter identification and state estimation.

DOI

10.19781/j.issn.1673-9140.2026.01.018

First Page

185

Last Page

193

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