Identification of Metal Object Types by High and Low Frequencies Detection for Wireless EV Charger

Metal object detection (MOD) is an important part of wireless charging system for electric vehicles. To focus on the problem of detection blind zone caused by material parameters and the method of foreign object-type identification, an identification method of metal object (MO) types using high and low frequencies detection is proposed. First, the effects of electrical and magnetic permeability on the excitation magnetic field of MOD are analyzed, and a detection sensitivity model for all types of MO is constructed. Second, a detection blind spot caused by the material parameters of ferromagnetic metals is found, the detection blind spot frequency is defined and the mechanism of the blind spot is explained. Third, the identification principle of MO types by high and low frequencies is analyzed. The relationship between the sensitivity and the material parameters of ferromagnetic metals is simulated, and the blind spot detection frequency is 19 kHz when an iron of size 40 × 40 mm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> is placed at the center of a checkerboard grid. Finally, an experimental platform for MO-type identification by high and low frequency detection is built, and it successfully identifies ferromagnetic metals, nonferromagnetic metals and ferrites.

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Publication Details

Journal
IEEE Transactions on Power Electronics
Published
2024-10-02
DOI
https://doi.org/10.1109/tpel.2024.3472691
Citations
5
Primary Topic
Sensor Technology and Measurement Systems
Type
article
Field-Weighted Citation Impact
1.74
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article

Identification of Metal Object Types by High and Low Frequencies Detection for Wireless EV Charger

Chenyang Xia, Shuze Zhao, Ziyue Yang, Anran Sun et al.
5 citations
IEEE Transactions on Power Electronics
Sensor Technology and Measurement Systems
1.74
article

Identification of Metal Object Types by High and Low Frequencies Detection for Wireless EV Charger

Chenyang Xia, Shuze Zhao, Ziyue Yang, Anran Sun, Chenhao Lu
article en
5 citations

Abstract

Metal object detection (MOD) is an important part of wireless charging system for electric vehicles. To focus on the problem of detection blind zone caused by material parameters and the method of foreign object-type identification, an identification method of metal object (MO) types using high and low frequencies detection is proposed. First, the effects of electrical and magnetic permeability on the excitation magnetic field of MOD are analyzed, and a detection sensitivity model for all types of MO is constructed. Second, a detection blind spot caused by the material parameters of ferromagnetic metals is found, the detection blind spot frequency is defined and the mechanism of the blind spot is explained. Third, the identification principle of MO types by high and low frequencies is analyzed. The relationship between the sensitivity and the material parameters of ferromagnetic metals is simulated, and the blind spot detection frequency is 19 kHz when an iron of size 40 × 40 mm<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> is placed at the center of a checkerboard grid. Finally, an experimental platform for MO-type identification by high and low frequency detection is built, and it successfully identifies ferromagnetic metals, nonferromagnetic metals and ferrites.

IEEE Transactions on Power ElectronicsVol. 40(1)
China University of Mining and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 14%
Sensor Technology and Measurement Systems
1.74
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