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Research on Wireless Charging Position Sensing Method Based on Visual Parameters

  • State Grid Electric Power Research Institute Co., Ltd.

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In the field of wireless charging of electric vehicles, the charging efficiency is often reduced due to the offset of coupling mechanism. How to effectively control the offset of coupling mechanism and realize accurate alignment of magnetic coupling mechanism is very important. Based on this problem, the researchers carried out a study on the precise alignment of the wireless charging system. By measuring the characteristic parameters such as electricity, magnetism and vision, the effective charging area was identified in real time and the relative position of the magnetic coupling mechanism was calculated. In this paper, a wireless charging counterpoint method based on monocular vision is proposed for the visual parameters. By establishing the identification and PnP pose detection model, the relative pose of the ground transmitter and the on-board receiver was determined, the alignment of the magnetic coupling mechanism was realized and the experimental error analysis was carried out, which verified the feasibility and accuracy of realizing the precise alignment of the wireless charging system through the machine vision scheme.

Original languageEnglish
Title of host publicationProceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1277-1280
Number of pages4
ISBN (Electronic)9781728163444
DOIs
StatePublished - 24 May 2021
Externally publishedYes
Event12th IEEE Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021 - Virtual, Singapore, Singapore
Duration: 24 May 202127 May 2021

Publication series

NameProceedings of the Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021

Conference

Conference12th IEEE Energy Conversion Congress and Exposition - Asia, ECCE Asia 2021
Country/TerritorySingapore
CityVirtual, Singapore
Period24/05/2127/05/21

Keywords

  • Image Processing
  • Monocular Vision
  • Pose Estimation

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