Disturbance Robust Predictive Repetitive Direct Power Control Applied to an Electric Vehicle Charger Grid-Side Converter

Abstract

The large adoption of electric vehicles (EVs) to reduce carbon emissions in the transportation sector presents various technological obstacles that need to be addressed, such as improving power quality when operating in vehicle-to-grid (V2G) mode as a distributed energy resource for the electricity grid. Model predictive control (MPC) is an advanced control technique gaining popularity in power electronics applications, particularly in EV chargers. MPC uses the plant's mathematical model to predict the future behavior of the state variables. Predictive repetitive control (PRC) combines MPC and repetitive control to increase robustness against disturbances, such as parametric errors or significant perturbations in grid voltage. This article proposes a robust PRC direct power control (PRC-DPC) of an EV charger grid-side converter operating under disturbed conditions. An explicit stability and robustness analysis is provided using the robust margins derived from the structured singular value decomposition (SVD). The analyses highlight the impact of the PRC-DPC controller tuning on its robustness. Experimental tests were conducted on a 2 kW prototype EV charger in V2G operation mode to validate the robustness of the proposed PRC-DPC controller. The proposed controller presented superior robustness compared to the conventional MPC.