Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/101771
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Title: A super-sensitive metal object detection method for DD-coil-engaged wireless EV chargers by passive electromagnetic sensing
Authors: Niu, S 
Niu, S 
Zhang, C
Jian, L
Issue Date: Nov-2022
Source: Energy Reports, Nov. 2022, v. 8, suppl. 13, p. 370-379
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.
Keywords: DD coil
Electric vehicle (EV)
Inductive power transfer
Metal object detection (MOD)
Sensing coils
Publisher: Elsevier Ltd
Journal: Energy reports 
EISSN: 2352-4847
DOI: 10.1016/j.egyr.2022.08.122
Rights: ©2022 Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
The following publication Niu, S., Niu, S., Zhang, C., & Jian, L. (2022). A super-sensitive metal object detection method for DD-coil-engaged wireless EV chargers by passive electromagnetic sensing. Energy Reports, 8, 370-379 is available at https://doi.org/10.1016/j.egyr.2022.08.122.
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