A Novel Foreign Object Detection and Classification Algorithm for Capacitive Wireless Charging Systems

被引:2
作者
Soto, Raquel Sarabia [1 ]
Maji, Sounak [1 ]
Etta, Dheeraj [1 ]
Afridi, Khurram K. [1 ]
机构
[1] Cornell Univ, Dept Elect & Comp Engn, Ithaca, NY 14850 USA
来源
2023 IEEE WIRELESS POWER TECHNOLOGY CONFERENCE AND EXPO, WPTCE | 2023年
关键词
capacitive wireless power transfer; high-frequency; foreign object detection; living object; machine learning; POWER TRANSFER;
D O I
10.1109/WPTCE56855.2023.10215656
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Wireless power transfer (WPT) systems have gained widespread adoption in recent years owing to their wide application range and high performance. However, these resonant systems are designed to operate at a fixed operating point and the presence of foreign objects may degrade their performance considerably, even potentially damaging the charger. This paper proposes a simple foreign object detection (FOD) algorithm for capacitive WPT systems using a machine learning-based classifier. This FOD technique does not require any additional sensing circuitry and uses the inherent WPT system components for sensing. A Machine Learning classifier is used to systematically categorize the foreign objects into categories. The proposed algorithm is tested with a wide set of foreign objects and is shown to have a good detection accuracy of 89%.
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页数:5
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