Metal Foreign Object Detection Algorithm Based on Multivariate Normal Distribution for Wireless Power Transfer System

Tian Zhou; Ying Sun; Yu Lan; Kai Song

doi:10.1109/WPW54272.2022.9901348

Metal Foreign Object Detection Algorithm Based on Multivariate Normal Distribution for Wireless Power Transfer System

Tian Zhou
, Ying Sun
, Yu Lan
, Kai Song^*

^*Corresponding author for this work

School of Electrical Engineering and Automation, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

When the wirless power transfer system works, the problem of metal foreign object detection needs to be solved urgently. The traditional metal foreign object detection algorithm based on the change of single detection coil's impedance is difficult to detect the metal foreign object at the corner of the detection coil. The metal foreign object detection algorithm based on multivariate normal distribution is proposed in this paper. The output can change more than 50 times when a metal foreign object with a diameter of 19mm is placed at the corner of the detection coil with a size of 32mm×38mm, which can significantly improve the detection effect of the corner area of the detection coil.

Original language	English
Title of host publication	2022 Wireless Power Week, WPW 2022 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	722-727
Number of pages	6
ISBN (Electronic)	9781665484459
DOIs	https://doi.org/10.1109/WPW54272.2022.9901348
State	Published - 2022
Externally published	Yes
Event	2022 Wireless Power Week, WPW 2022 - Bordeaux, France Duration: 5 Jul 2022 → 8 Jul 2022

Publication series

Name	2022 Wireless Power Week, WPW 2022 - Proceedings
Volume	2022-January

Conference

Conference	2022 Wireless Power Week, WPW 2022
Country/Territory	France
City	Bordeaux
Period	5/07/22 → 8/07/22

Keywords

detection algorithm
metal foreign object
multivariate normal distribution
wirless power transfer

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10.1109/WPW54272.2022.9901348

Cite this

Zhou, T., Sun, Y., Lan, Y., & Song, K. (2022). Metal Foreign Object Detection Algorithm Based on Multivariate Normal Distribution for Wireless Power Transfer System. In 2022 Wireless Power Week, WPW 2022 - Proceedings (pp. 722-727). (2022 Wireless Power Week, WPW 2022 - Proceedings; Vol. 2022-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WPW54272.2022.9901348

@inproceedings{fec19710cbd04842ab2c15b7583c35e0,

title = "Metal Foreign Object Detection Algorithm Based on Multivariate Normal Distribution for Wireless Power Transfer System",

abstract = "When the wirless power transfer system works, the problem of metal foreign object detection needs to be solved urgently. The traditional metal foreign object detection algorithm based on the change of single detection coil's impedance is difficult to detect the metal foreign object at the corner of the detection coil. The metal foreign object detection algorithm based on multivariate normal distribution is proposed in this paper. The output can change more than 50 times when a metal foreign object with a diameter of 19mm is placed at the corner of the detection coil with a size of 32mm×38mm, which can significantly improve the detection effect of the corner area of the detection coil.",

keywords = "detection algorithm, metal foreign object, multivariate normal distribution, wirless power transfer",

author = "Tian Zhou and Ying Sun and Yu Lan and Kai Song",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 Wireless Power Week, WPW 2022 ; Conference date: 05-07-2022 Through 08-07-2022",

year = "2022",

doi = "10.1109/WPW54272.2022.9901348",

language = "英语",

series = "2022 Wireless Power Week, WPW 2022 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "722--727",

booktitle = "2022 Wireless Power Week, WPW 2022 - Proceedings",

address = "美国",

}

Zhou, T, Sun, Y, Lan, Y & Song, K 2022, Metal Foreign Object Detection Algorithm Based on Multivariate Normal Distribution for Wireless Power Transfer System. in 2022 Wireless Power Week, WPW 2022 - Proceedings. 2022 Wireless Power Week, WPW 2022 - Proceedings, vol. 2022-January, Institute of Electrical and Electronics Engineers Inc., pp. 722-727, 2022 Wireless Power Week, WPW 2022, Bordeaux, France, 5/07/22. https://doi.org/10.1109/WPW54272.2022.9901348

Metal Foreign Object Detection Algorithm Based on Multivariate Normal Distribution for Wireless Power Transfer System. / Zhou, Tian; Sun, Ying; Lan, Yu et al.
2022 Wireless Power Week, WPW 2022 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2022. p. 722-727 (2022 Wireless Power Week, WPW 2022 - Proceedings; Vol. 2022-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Metal Foreign Object Detection Algorithm Based on Multivariate Normal Distribution for Wireless Power Transfer System

AU - Zhou, Tian

AU - Sun, Ying

AU - Lan, Yu

AU - Song, Kai

PY - 2022

Y1 - 2022

N2 - When the wirless power transfer system works, the problem of metal foreign object detection needs to be solved urgently. The traditional metal foreign object detection algorithm based on the change of single detection coil's impedance is difficult to detect the metal foreign object at the corner of the detection coil. The metal foreign object detection algorithm based on multivariate normal distribution is proposed in this paper. The output can change more than 50 times when a metal foreign object with a diameter of 19mm is placed at the corner of the detection coil with a size of 32mm×38mm, which can significantly improve the detection effect of the corner area of the detection coil.

AB - When the wirless power transfer system works, the problem of metal foreign object detection needs to be solved urgently. The traditional metal foreign object detection algorithm based on the change of single detection coil's impedance is difficult to detect the metal foreign object at the corner of the detection coil. The metal foreign object detection algorithm based on multivariate normal distribution is proposed in this paper. The output can change more than 50 times when a metal foreign object with a diameter of 19mm is placed at the corner of the detection coil with a size of 32mm×38mm, which can significantly improve the detection effect of the corner area of the detection coil.

KW - detection algorithm

KW - metal foreign object

KW - multivariate normal distribution

KW - wirless power transfer

UR - https://www.scopus.com/pages/publications/85139879939

U2 - 10.1109/WPW54272.2022.9901348

DO - 10.1109/WPW54272.2022.9901348

M3 - 会议稿件

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T3 - 2022 Wireless Power Week, WPW 2022 - Proceedings

SP - 722

EP - 727

BT - 2022 Wireless Power Week, WPW 2022 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2022 Wireless Power Week, WPW 2022

Y2 - 5 July 2022 through 8 July 2022

ER -

Metal Foreign Object Detection Algorithm Based on Multivariate Normal Distribution for Wireless Power Transfer System

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