Modeling and Model Predictive Control of a Hybrid DC Transformer

This article proposes a model predictive control (MPC) method to enhance the dynamic performance of a hybrid dc transformer (HDCT) consisting of $LLC$ and dual active bridge (DAB) converters. First, the small-signal model of the HDCT is derived for designing controller parameters. Unlike traditional methods, this method intuitively presents the relationships among different disturbances and accurately derives the control-output transfer function by analyzing equivalent circuits of the HDCT. The accuracy of the derived model is verified by a SIMPLIS simulation. Second, an MPC method for the HDCT is proposed. By utilizing output current, output capacitor current, and the power characteristics of the HDCT, the method calculates the output current of the DAB converter and uses it to predict output voltage, thereby eliminating the need for the additional input current sensor used in the previous MPC method. The dynamic performance of the system can be enhanced by considering the output capacitor current in the MPC method. The optimal phase shift ratio is determined by optimizing the cost function with the predicted output voltage. Finally, experiments were conducted on a 3 kW HDCT prototype to validate the effectiveness of the proposed MPC method.