Statistical Model of Foreign Object Detection for Wireless EV Charger

Safety problem is of great importance for the wireless EV charger since a paperclip is overheated in several minutes for 6.6 kW wireless power transfer (WPT). In this paper, a statistical model of foreign object detection (FOD) is proposed to improve the sensitivity of metal detector and to reduce false alarm. The basic detection principle is to use the induced voltage signal of differential coils placed on the surface of ground side (GA). A pair of DQ coils was fabricated for collecting signal. A normal distribution is assigned to the signal while generalized likelihood ratio test (GLRT) is applied to figure out the detector with the best performance. Based on the proposed model, the effect of power swing originated from maximum efficiency point tracking can be effectively eliminated. In the experiment, many hazardous metallic objects can be well detected on the surface of GA. It is proved that this model is suitable for FOD function in high power WPT system.