Abstract
Wireless Power Transfer (WPT) systems have become vital technology for electric vehicle (EV) charging, offering convenience, automation, and resilience in harsh environments. However, the safety and efficiency of these systems are threatened by the presence of foreign objects (FOs) such as metallic debris and biological entities near the power transfer zone. These intrusions can lead to electromagnetic interference, excessive heating, or even hazardous failures. This review comprehensively analyzes Foreign Object Detection (FOD) techniques used in inductive WPT systems, particularly for EV applications. The paper categorizes detection strategies into Metal Object Detection (MOD) and Living Object Detection (LOD). It further classifies them by sensing principles: electrical parameter monitoring, magnetic field sensing, thermal detection, capacitive methods, ultrasonic systems, vision based approaches, and hybrid techniques. A comparative performance evaluation is based on detection accuracy, cost, environmental robustness, and real-time suitability. Additionally, original conceptual figures are included to support understanding of the impact of misalignment and foreign object interference on WPT behavior.Moreover, a finite element modeling based analysis demonstrates the impact of various foreign materials, such as cast iron, steel, aluminum, and water, on coil parameters and WPT efficiency. The paper outlines current challenges, integration issues, and future research directions, including AI driven sensor fusion and the need for standardized validation platforms to enable safe, intelligent, and scalable EV WPT systems.
| Original language | English |
|---|---|
| Journal | IEEE Access |
| DOIs | |
| Publication status | Accepted/In press - 2025 |
Keywords
- Capacitive Detection
- Electric vehicle charging
- Foreign Object Detection
- Inductive Power Transfer
- Living Object Detection
- Magnetic coupling
- Metal Object Detection
- Thermal Imaging
- Wireless power transfer
ASJC Scopus subject areas
- General Computer Science
- General Materials Science
- General Engineering
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