A super-sensitive metal object detection method for DD-coil-engaged wireless EV chargers by passive electromagnetic sensing

Songyan Niu, Shuangxia Niu, Cheng Zhang, Linni Jian

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

Metal object detection (MOD) is very important to guarantee the thermal safety of wireless charging systems for electric vehicles (EVs). Regarding the MOD methods based on passive sensing coils, most previous designs are targeted at the systems employing unpolarized coils, and the detection criteria are voltage-difference-based (VDB). Unfortunately, they are unsuitable for those employing DD coils due to the fundamental difference of field pattern. In addition, the VDB method has an inherent problem of low sensitivity. To fix these two problems, in this work, a set of field-oriented sensing coils is devised, which successfully realizes blind-zone elimination and super-high sensitivity. The arrangement of sensing coils accords with the pole-to-pole field distribution of DD coils to highlight the influence of MOs. The blind zone caused by the axial symmetry of the coupling field is removed by a non-symmetric patch coil. Moreover, a MOD mechanism with new criteria for MO identification is developed, which is the core of super-high sensitivity. Tested by ten positions where MOs might intrude using a 3 kW prototype, the optimized sensing coils can entirely remove the y-axis blind zones. The average sensitivity for the charging area reaches up to 16.

Original languageEnglish
Pages (from-to)370-379
Number of pages10
JournalEnergy Reports
Volume8
DOIs
Publication statusPublished - Nov 2022

Keywords

  • DD coil
  • Electric vehicle (EV)
  • Inductive power transfer
  • Metal object detection (MOD)
  • Sensing coils

ASJC Scopus subject areas

  • General Energy

Fingerprint

Dive into the research topics of 'A super-sensitive metal object detection method for DD-coil-engaged wireless EV chargers by passive electromagnetic sensing'. Together they form a unique fingerprint.

Cite this