Model Predictive Control Strategy Based on Kalman Filter for Dual Active Bridge Converter

Abstract

With the widespread use of electric vehicles, the large disturbance caused by the uncertainty of the AC side of the power grid will adversely affect the voltage stability of the DC side of the charging pile, which will threaten the charging safety of electric vehicles. In order to achieve fast and adaptive DC voltage regulation under large disturbance, this paper proposes a dual active bridge (DAB) converter control strategy based on Kalman Filter (KF) and Model Predictive Control (MPC). The improved Euler method is used to obtain a more accurate DAB discrete model, and the MPC control system is designed to improve the control accuracy. The best observation results of KF are used as feedforward compensation to improve the accuracy of output voltage regulation and ensure the stability of electric vehicles in the face of various disturbance problems. Finally, the effectiveness of the control strategy is verified by experiment.