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

Niu, Songyan1,2; Niu, Shuangxia1; Zhang, Cheng2; Jian, Linni2

2022-11-01

10.1016/j.egyr.2022.08.122

Energy Reports   影响因子和分区

2352-4847

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. (C) 2022 Published by Elsevier Ltd.

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

SCI ; EI

英语

通讯

Science and Technology Innovation Committee of Shenzhen, China[20200925154042003]

Energy & Fuels

Energy & Fuels

WOS:000841664500042

ELSEVIER

20223412607846

Charging (batteries) ; Energy transfer ; Inductive power transmission ; Object detection ; Object recognition ; Poles

Structural Members and Shapes:408.2 ; Secondary Batteries:702.1.2 ; Electric Power Transmission:706.1.1 ; Data Processing and Image Processing:723.2

Web of Science

1.Hong Kong Polytech Univ, Kowloon, Hong Kong 999077, Peoples R China
2.Southern Univ Sci & Technol, Shenzhen 518055, Peoples R China

Niu, Songyan,Niu, Shuangxia,Zhang, Cheng,et al. A super-sensitive metal object detection method for DD-coil-engaged wireless EV chargers by passive electromagnetic sensing[J]. Energy Reports,2022,8:370-379.

Niu, Songyan,Niu, Shuangxia,Zhang, Cheng,&Jian, Linni.(2022).A super-sensitive metal object detection method for DD-coil-engaged wireless EV chargers by passive electromagnetic sensing.Energy Reports,8,370-379.

Niu, Songyan,et al."A super-sensitive metal object detection method for DD-coil-engaged wireless EV chargers by passive electromagnetic sensing".Energy Reports 8(2022):370-379.