Model predictive control of bidirectional isolated DC–DC converter for energy conversion system

Abstract

Model predictive control (MPC) is a powerful and emerging control algorithm in the field of power converters and energy conversion systems. This paper proposes a model predictive algorithm to control the power flow between the high-voltage and low-voltage DC buses of a bidirectional isolated full-bridge DC–DC converter. The predictive control algorithm utilises the discrete nature of the power converters and predicts the future nature of the system, which are compared with the references to calculate the cost function. The switching state that minimises the cost function is selected for firing the converter in the next sampling time period. The proposed MPC bidirectional DC–DC converter is simulated with MATLAB/Simulink and further verified with a 2.5 kW experimental configuration. Both the simulation and experimental results confirm that the proposed MPC algorithm of the DC–DC converter reduces reactive power by avoiding the phase shift between primary and secondary sides of the high-frequency transformer and allow power transfer with unity power factor. Finally, an efficiency comparison is performed between the MPC and dual-phase-shift-based pulse-width modulation controlled DC–DC converter which ensures the effectiveness of the MPC controller.