Model Predictive Current Control for Grid-Connected Bi-directional EV Battery Charging System

This paper proposes a finite-set model predictive control (FSMPC) for a bi-directional electric vehicle (EV) battery charging system. The proposed solution consists of two cascaded-controllers, the first is responsible for producing the current reference signal based on the DC link voltage error during grid-to-vehicle (G2V) operation. During vehicle-to-grid (V2G), the reference current is computed based on the rated power of the EV’s battery. The second controller receives the generated reference current and uses it to regulate the grid currents. The main objective of the proposed controller is to achieve V2G and G2V functionalities, to regulate the grid currents with a unity power factor, reactive power injection to the grid, balanced grid currents, control the DC link voltage while charging the battery, and rapidly and precisely track the applied reference signals, all with a single controller. Simulation results are curried out to show that the proposed control technique can meet the control goals including grid’s support and can offer rapid tracking with almost zero steady-state error.