Metal Object Detection And Coil Alignment For Wireless EV Chargers Using Coil Array

Wireless charging of electric vehicles(EVs)has the characteristics of non-contact,convenient,flexible,safe and reliable,which overcomes the shortcomings of traditional wired charging such as plugging and unplugging the charging cable and unsafe operation.However,there are several problems that need to be solved in the wireless charging process of EVs,including the metal objects detection and the alignment of the transmitting and receiving coils.Due to the eddy current effect,metal objects will reduce the mutual inductance and coupling coefficient between the transmitting and receiving coils,thereby reducing the power transmission efficiency.At the same time,the metal surface will generate heat.If the metal objects contact with inflammables during charging,it may cause a fire.In addition,the misalignment of the coils will greatly affect the charging efficiency.If there are large distance between the coils,the charging process will stop.Therefore,the research on the metal objects detection and coil alignment for the wireless charging is of great significance.In this paper,a low-cost and easy operation approach using the coil array for the metal objects detection and coil alignment of the wireless charging is proposed and investigated.The main contributions of this paper include three folds:1.Based on the characteristics of the metal object detection and coil alignment of the wireless charging system,a low-cost,easy operation coil array sensor for the simultaneous metal objects detection and coil alignment is designed.Through the finite element simulation of the coil array with different structures,it is found that in a 10 cm×10 cm detection area,4×44 coil array can meet the measurement requirements.2.Based on the finite element model(FEM),the sensitivity matrix of conductivity distribution above the coil array sensor is obtained.Then with the induced voltages from detection coils,the reconstruction of metal objects is conducted using the Landweber iterative algorithm.Finally,contour recognition is carried out on the reconstructed images and the number and position of metal objects are calculated.The detection and imaging of metal objects with different numbers and different shapes are carried out using the FEM model.The simulation results show that the average intersection over union(IoU)is 0.55,the average correlation coefficient(CC)is 0.76,and the average centroid deviation is 2.18 mm.In addition,the detection and imaging of metal objects with different materials,different shapes and different quantities are also carried out using a lab-scale wireless charging equipment.The average IoU of the experimental results is 0.61,the average CC is 0.77,and the average centroid deviation is 2.33 mm3.During the coil alignment of the wireless charging process,the receiving coil is switched to the excitation mode using a relay and the induced voltages of the coil array are processed by the spline interpolation.The image can reflect the position of the receiving coil.By recognizing the contour of the image,the feature boundary of the contour is compared with that from the calibrated position.Thus,the offset direction and distance of the receiving coil are determined and the alignment of the receiving coil is realized.The maximum absolute error from simulation results is 0.48 cm and the maximum absolute error from experimental results is 1.79 cm.The maximum absolute error is less than 2 cm in a detection area of 10 cm×10 cm,which maintains acceptable power transmission efficiency(>80%)and meets the alignment requirement of the EV wireless charging system.