Sensor Switching-Based Automatic Misalignment Detection and Correction System for Wireless Power Transfer

Misalignment between the transmitting and receiving coils is an inevitable problem for electric vehicle (EV) wireless power transfer (WPT) systems. Regardless of the WPT system being static or dynamic, coil misalignment reduces the efficiency of the charging system. This paper, focuses on using a combination of computer vision and one of two different misalignment sensors to detect, and further correct lateral misalignment between the EV receiving (Rx) coil and the segmented transmitting (Tx) coils in a charging lane. The vision-based component uses a camera for lane detection and is primarily responsible for detecting larger deviations and making coarse compensations by estimating the lateral shift of the EV, relative to the center of the charging lane. The sensor-based approach relies on Hall effect sensors or detection coils to detect the misalignment in a smaller range, and perform finer corrections. A one-dimensional (1D) actuator moves the receiving coil to correct the coil misalignment, independent of vehicle movements. The vision-based approach showed a wide detection range for misalignment spanning [$-$15,15] cm, with a correction accuracy of $\approx \pm$2 cm. This is juxtaposed with the sensor-based approach which operates on a misalignment range of [$-$3,3] cm, but outperforms the vision-based approach with a correction accuracy of less than $\pm$1 mm. The proposed sensor switching-based approach combines the advantages of the above individual techniques. An experimental setup is developed and tests are performed to evaluate the proposed approach while transferring 108 W of power wirelessly.