A Nonlinear Model Predictive Control for Bidirectional Dual Active Bridge Converter

This paper proposes a novel control strategy for a dual active bridge (DAB) converter, leveraging a nonlinear model predictive control (MPC) framework. Traditional control designs often utilize a linearized version of the system's dynamics, which may not fully capture the converter's nonlinear behavior, especially under disturbances. In contrast, this approach incorporates the nonlinearities inherent to the system, leading to more accurate control. The paper compares the performance of both linear and nonlinear MPCs by introducing disturbances and evaluating their ability to track reference voltages. Simulation results demonstrate that the nonlinear MPC significantly improves tracking accuracy and system stability, particularly during disturbances. These findings suggest that nonlinear MPC offers a more robust control solution for DAB converters in dynamic operating conditions, with potential applications in battery energy storage systems and renewable energy systems.