Vision-Based Rapid Power Control for a Dynamic Wireless Power Transfer System of Electric Vehicles

Abstract

Dynamic wireless power transfer brings a refreshing way for charging electric vehicles (EVs) in motion, which can help reduce the amount and bulk of onboard batteries and prolong the vehicle mileage. However, the misalignment between the transmitter coil and receiver coil varies randomly as the vehicle moves, reducing the stability of the output power and the system efficiency. Therefore, a guiding approach is imperative to maintain the coil alignment within an acceptable range. In this paper, a vision-based misalignment detection method is proposed to improve the stability of the system output power and the efficiency. First, the relationships among the system efficiency, output power and mutual inductance were derived in theory. Second, the relationship between the mutual inductance and the misalignment was modeled and simulated using ANSYS Maxwell software. Third, image detection of the ground guideline was used to locate the transmitter coil, and thus obtain the accurate misalignments online. Based on the acquired misalignments, the output power can be rapidly and precisely regulated to the desired value. Finally, the experimental results show that the proposed method can accurately acquire the coil misalignments and then rapidly regulate the system output power in comparison with the conventional discrete proportional-integral control algorithm.

Keywords

• Dynamic wireless power transfer
• machine vision
• power control
• mutual inductance estimation