Bivariate Detection based Dual-Mode Metal Object Detection System for Wireless EV Charging

• Published in: IEEE journal of emerging and selected topics in power electronics 2024-08, p.1-1
• Main Authors: Yang, Ziyue, Xia, Chenyang, Sun, Anran, Zhao, Shuze, Cao, Yuheng
• Format: Article
• Language: English
• Subjects: Coils; Electric vehicle; Equivalent circuits; Frequency modulation; Impedance; Integrated circuit modeling; metal object detection; RLC circuits; Voltage; wireless EV charging; wireless power transfer
• ISSN: 2168-6777; 2168-6785
• DOI: 10.1109/JESTPE.2024.3452186

Metal object detection (MOD) technology is crucial to drive the commercialization of wireless electric vehicle (EV) charging. Previous detection coil-based MOD methods mainly detect metallic foreign objects by the variation of sampling voltage, which may mistake nonmetallic foreign objects for threats. To solve this problem, this paper proposes a bivariate detection based dual-mode MOD system integrating time-division multiplexing (TDM) mode for sensitively detecting foreign objects and frequency-swept resonance (FSR) mode for accurately identifying metallic foreign objects. Firstly, by modeling foreign objects and resonant circuits, it is observed that metallic objects increase the resonant frequency and decrease the sampling voltage at resonant frequencies. Subsequently, the specifications of the detection coil and the intrinsic resonant frequency of the resonant circuit are optimized to enhance the sensitivity of the MOD system. Finally, an experimental platform with an output power of 3.3 kW is built to verify the effectiveness of the MOD system. The experimental results show that the TMD and FSR modes of the MOD system can accurately detect and recognize metallic objects. Furthermore, the TDM mode of the MOD system can achieve 100% probability of detecting all types of coins and 78% probability of detecting 29 mm paper clips through 100 random drop tests.