A Model Predictive Voltage Control for Dual-active-bridge DC-DC Converter Using Generalized Averaging Model

This paper proposes a model predictive voltage control (MPVC) for dual-active-bridge (DAB) DC-DC converters using the generalized averaging model (GAM). Based on the GAM, the high-frequency transformer current can be approximated by two current components in the real and imaginary axes. Since the averaging model just considers the dominant term in the Fourier series, there is an inevitable model mismatch in the output voltage dynamics. Therefore, a disturbance representing the model uncertainty is lumped into the output current channel, allowing the design of the state observer. The output of state estimation matches well with the actual transformer current waveform through FFT analysis at the steady-state condition. Using the estimated state, an MPVC is designed based on the state-feedback law with a constant controller gain. Finding an optimal controller gain is accomplished by a systematic tuning method. The proposed MPVC’s performance is compared with an improved fast voltage control and quadratic programming solver-based MPC in the simulation results.