Model Predictive Control for Misalignment Compensation in Dynamic Wireless Charging of Electric Vehicles

Dynamic wireless charging (DWC) of electric vehicles (EVs) offers a promising solution to mitigate range anxiety and enhance the feasibility of electrified transportation; however, achieving optimal power transfer requires precise alignment between the primary coil embedded in the roadway and the secondary coil mounted on the vehicle. In practice, lateral misalignment (LTM) frequently occurs, leading to reduced efficiency. Although conventional controllers can partially compensate for these losses, their performance degrades under significant misalignment, resulting in overshoot and steady-state error (SSE). To overcome these limitations, this paper proposes a model predictive control (MPC)-based approach to mitigate the effects of LTM and restore efficient power transfer. A comparative study between the proposed MPC and a conventional proportional–integral (PI) controller is conducted to assess performance and suitability. The MPC utilizes an optimization framework to determine optimal control actions over a prediction horizon, thereby minimizing SSE and reducing overshoot under varying misalignment conditions. The effectiveness of the proposed method is validated through MATLAB/Simulink simulations and experimental testing. The results demonstrate that the MPC maintains stable operation over a wide LTM range, achieving a maximum power transfer efficiency of 93% at zero misalignment, which decreases to 83% at severe misalignment (LTM = 0.5). Compared to the PI controller, the MPC improves average efficiency by approximately 8–12%, leading to improved robustness and smoother dynamic response. These results confirm the effectiveness of the proposed MPC approach in maintaining high efficiency and stable operation in misaligned DWC systems.