Direct Predictive Power Control Strategy to Improve Charging and Power Quality of Autonomous Robotic Electric Vehicle Charging Systems

Emerging wide bandgap (WBG) semiconductors, such as silicon carbide (SiC), will enable chargers to operate at higher switching frequencies to increase efficiency and reduce power density. This paper focuses on modelling SiC technology-based off-board robotic chargers for electric vehicles (EVs) and the design of its robust model predictive control (MPC). The three-phase active front-end (AFE) converter topology is considered on modelling and predictive model-based control design for off-board charger grid-to-vehicle (G2V) and vehicle-to-grid (V2G) modes. The control system consists of active-reactive power control and ensures power conversion for charging and discharging batteries. The aim is to enhance the power quality by achieving the targeted grid current total harmonic distortion (THD) and unity power factor (PF). Predictive model-based simulation is developed in MATLAB for optimum control design to validate the control performances. The 75kW SiC off-board charger simulation results are demonstrated to investigate the dynamic performance. The THD of line current < 2% and PF > 99% are obtained with MPC control.