Comprehensive Analysis of Foreign Object Detection Techniques for Safe Electric Vehicle Charging

The adoption of electric vehicles (EVs) has grown exponentially in recent years, making EV charging infrastructure an essential aspect of modern transportation. The safety and reliability of EV charging stations are crucial factors for their widespread adoption. Foreign object detection (FOD) technology is critical in detecting and preventing foreign objects from entering charging interface. This can cause damage, safety hazards and downtime of charging station. This research paper presents a comprehensive survey of FOD for EV charging, highlighting various techniques and technologies used for FOD, their advantages, limitations, recent advancements and references from several research papers. The different types of FOD detection, such as mechanical, visual, electrical, thermodynamic and magnetic detection of foreign objects are reviewed in detail. This includes their working principles, performance and suitability for different objects and environments. In addition, impact of various factors on FOD performance, such as temperature, living objects, magnetic fields and electromagnetic interference, is discussed and methods to mitigate their effects are explored. The survey concludes by summarizing all information gathered from various papers for EV charging and highlighting the direction towards which this research is headed for future. The survey provides a valuable reference for researchers, practitioners and policymakers in the field of EV charging infrastructure. The insights obtained from this study can help stakeholders draft better products, policies and optimized solutions for EV charging domain.

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Publication Details

Journal
Metallurgical and Materials Engineering
Published
2025-04-16
DOI
https://doi.org/10.63278/1499
Citations
1
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
1.24
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article

Comprehensive Analysis of Foreign Object Detection Techniques for Safe Electric Vehicle Charging

Abdulaziz Alshammari
1 citations
Metallurgical and Materials Engineering
Industrial Vision Systems and Defect Detection
1.24
article

Comprehensive Analysis of Foreign Object Detection Techniques for Safe Electric Vehicle Charging

Abdulaziz Alshammari
article en
1 citations

Abstract

The adoption of electric vehicles (EVs) has grown exponentially in recent years, making EV charging infrastructure an essential aspect of modern transportation. The safety and reliability of EV charging stations are crucial factors for their widespread adoption. Foreign object detection (FOD) technology is critical in detecting and preventing foreign objects from entering charging interface. This can cause damage, safety hazards and downtime of charging station. This research paper presents a comprehensive survey of FOD for EV charging, highlighting various techniques and technologies used for FOD, their advantages, limitations, recent advancements and references from several research papers. The different types of FOD detection, such as mechanical, visual, electrical, thermodynamic and magnetic detection of foreign objects are reviewed in detail. This includes their working principles, performance and suitability for different objects and environments. In addition, impact of various factors on FOD performance, such as temperature, living objects, magnetic fields and electromagnetic interference, is discussed and methods to mitigate their effects are explored. The survey concludes by summarizing all information gathered from various papers for EV charging and highlighting the direction towards which this research is headed for future. The survey provides a valuable reference for researchers, practitioners and policymakers in the field of EV charging infrastructure. The insights obtained from this study can help stakeholders draft better products, policies and optimized solutions for EV charging domain.

Metallurgical and Materials EngineeringVol. 31(4)
Imam Mohammad ibn Saud Islamic University (SA)
Openalex Percentile: Top 20%
Industrial Vision Systems and Defect Detection
1.24
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