Current-sensorless model predictive control for DAB converter based on back-flow power optimization

Abstract

To solve problems such as high back-flow power, low system efficiency and poor dynamic properties of dual-active-full-bridge DC-DC converters in energy routers under traditional single-phase-shift modulation, the present paper introduces a current-sensorless-based model predictive control method combining back-flow power optimization based on Extended-Phase-Shift (EPS) modulation strategy. The transmission power model of the DAB converter is analyzed, taking into account the extended phase shift and the optimal shift comparison combination is found by the Lagrange multiplier method with the return power as the objective function. Then, the cost function is constructed to track the output voltage to achieve model predictive control without a current sensor. Finally, the accuracy and efficiency of the proposed strategy are verified by simulation. The results demonstrate the efficacy of this approach in mitigating system back-flow power and enhancing dynamic performance.