CN-121973655-A - Charging control method for wireless charging robot and related equipment

CN121973655ACN 121973655 ACN121973655 ACN 121973655ACN-121973655-A

Abstract

The embodiment of the application provides a charging control method and related equipment for a wireless charging robot, and belongs to the technical field of new energy automobiles. The method comprises the steps of performing visual positioning according to acquired chassis pictures, determining first position deviation of a current position of a wireless charging robot and a wireless charging coil of a vehicle, performing position adjustment on the robot according to the first position deviation, acquiring magnetic induction intensity distribution of the wireless charging coil of the vehicle through a Hall effect sensor array when the first position deviation is smaller than a first preset deviation, performing magnetic positioning according to the magnetic induction intensity distribution, determining second position deviation of the wireless charging coil of the robot and the wireless charging coil of the vehicle, performing position adjustment on the robot according to the second position deviation, and controlling the robot to charge when the second position deviation is smaller than or equal to a second preset deviation. The application can improve the alignment precision of the robot and the wireless charging coil of the vehicle and improve the wireless charging efficiency.

Inventors

QIAN CHUANG
ZENG WANG
YAN XINGYU
SU YI
BI XINYU
LUO XIN
XIONG SHENGGUANG

Assignees

武汉理工大学

Dates

Publication Date: 20260505
Application Date: 20260121

Claims (10)

1. A charging control method for a wireless charging robot, comprising the steps of: Responding to a charging instruction, and collecting a chassis picture of a target vehicle; visual positioning is carried out according to the chassis picture, and the deviation between the current position of the wireless charging robot and the first position of the wireless charging coil of the vehicle is determined; The wireless charging robot is subjected to position adjustment according to the first position deviation, and magnetic induction intensity distribution from a wireless charging coil of the vehicle is collected through a Hall effect sensor array under the condition that the first position deviation is smaller than a first preset deviation; performing magnetic positioning according to the magnetic induction intensity distribution, and determining second position deviation of the wireless charging coil of the robot and the wireless charging coil of the vehicle; and carrying out position adjustment on the wireless charging robot according to the second position deviation, and controlling the wireless charging robot to charge under the condition that the second position deviation is smaller than or equal to a second preset deviation.
2. The charging control method for a wireless charging robot according to claim 1, wherein the performing the visual positioning according to the chassis picture, determining a first positional deviation of a current position of the wireless charging robot from a wireless charging coil of a vehicle, comprises the steps of: Performing chassis identification and classification on the chassis pictures by using a trained convolutional neural network model, determining vehicle type classification, and determining a first relative position of a vehicle wireless charging coil on a vehicle chassis according to the vehicle type classification; Performing visual positioning according to the currently acquired chassis picture, and determining a second relative position of a visual center of the wireless charging robot on the chassis of the vehicle; and determining the deviation between the current position of the wireless charging robot and the first position of the wireless charging coil of the vehicle according to the first relative position and the second relative position.
3. The charge control method for a wireless charging robot according to claim 1, characterized in that the charge control method for a wireless charging robot further comprises the steps of: calculating the average gray value of the acquired chassis picture; Under the condition that the average gray value is smaller than a first gray threshold value, performing image enhancement processing on the chassis picture; And under the condition that the average gray level value is larger than the second gray level threshold value, reducing the brightness of the light supplementing lamp and re-shooting the chassis picture.
4. The charge control method for a wireless charging robot according to claim 2, wherein the convolutional neural network model is trained by: Acquiring chassis pictures of different wireless charging automobiles as sample data; The sample data is subjected to data enhancement processing and sample labeling processing to form a sample database, wherein the label of the sample data comprises a chassis detection frame, vehicle type classification and a first relative position of a vehicle wireless charging coil on a vehicle chassis; And training the convolutional neural network model by using the sample database to obtain a trained convolutional neural network model.
5. The method for charging a wireless charging robot according to claim 1, wherein the magnetic induction intensity distribution includes a plurality of magnetic induction intensities acquired by the hall effect sensor array, wherein the magnetic positioning is performed based on the magnetic induction intensity distribution, and wherein determining the second positional deviation of the wireless charging coil of the robot from the wireless charging coil of the vehicle comprises the steps of: Normalizing each magnetic induction intensity to obtain a plurality of normalized magnetic field intensities; And determining a second position deviation of the wireless charging coil of the robot and the wireless charging coil of the vehicle according to the position distribution of each Hall effect sensor relative to the wireless charging coil of the robot and the normalized magnetic field intensity.
6. The charging control method for a wireless charging robot according to claim 5, wherein the position adjustment of the wireless charging robot according to the second position deviation includes the steps of: Constructing a PID controller according to the second position deviation, and calculating a motion state control quantity according to the PID controller; and carrying out position adjustment on the wireless charging robot on the motion state control quantity.
7. A charging control system for a wireless charging robot, comprising: The first module is used for responding to the charging instruction and collecting chassis pictures of the target vehicle; the second module is used for carrying out visual positioning according to the chassis picture and determining the deviation between the current position of the wireless charging robot and the first position of the wireless charging coil of the vehicle; The third module is used for adjusting the position of the wireless charging robot according to the first position deviation, and collecting magnetic induction intensity distribution from the wireless charging coil of the vehicle through the Hall effect sensor array under the condition that the first position deviation is smaller than a first preset deviation; A fourth module, configured to perform magnetic positioning according to the magnetic induction intensity distribution, and determine a second position deviation between the wireless charging coil of the robot and the wireless charging coil of the vehicle; And the fifth module is used for adjusting the position of the wireless charging robot according to the second position deviation and controlling the wireless charging robot to charge under the condition that the second position deviation is smaller than or equal to a second preset deviation.
8. An electronic device comprising a memory storing a computer program and a processor implementing the method of any of claims 1 to 6 when the computer program is executed by the processor.
9. A computer readable storage medium storing a computer program, characterized in that the computer program, when executed by a processor, implements the method of any one of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when executed by a processor, implements the method of any one of claims 1 to 6.

Description

Charging control method for wireless charging robot and related equipment Technical Field The application relates to the technical field of new energy automobiles, in particular to a charging control method and related equipment for a wireless charging robot. Background With the development of wireless charging technology of new energy automobiles, an automatic charging robot is gradually applied to scenes such as underground garages, outdoor parking lots and the like. The wireless charging at the bottom of the car has extremely high requirements on the alignment precision of the coil, however, the current charging docking technology relies on visual coarse positioning, and in the environment with limited space at the bottom of the car and insufficient illumination, the millimeter-level positioning precision is difficult to realize, and the docking failure and the charging efficiency reduction are easy to cause. Disclosure of Invention The embodiment of the application mainly aims to provide a charging control method for a wireless charging robot and related equipment, aiming at improving the alignment precision of the wireless charging robot and a wireless charging coil of a vehicle and improving the wireless charging efficiency. To achieve the above object, an aspect of an embodiment of the present application provides a charging control method for a wireless charging robot, including the steps of: Responding to a charging instruction, and collecting a chassis picture of a target vehicle; visual positioning is carried out according to the chassis picture, and the deviation between the current position of the wireless charging robot and the first position of the wireless charging coil of the vehicle is determined; The wireless charging robot is subjected to position adjustment according to the first position deviation, and magnetic induction intensity distribution from a wireless charging coil of the vehicle is collected through a Hall effect sensor array under the condition that the first position deviation is smaller than a first preset deviation; performing magnetic positioning according to the magnetic induction intensity distribution, and determining second position deviation of the wireless charging coil of the robot and the wireless charging coil of the vehicle; and carrying out position adjustment on the wireless charging robot according to the second position deviation, and controlling the wireless charging robot to charge under the condition that the second position deviation is smaller than or equal to a second preset deviation. In some embodiments, the performing visual positioning according to the chassis picture, determining a first position deviation between a current position of the wireless charging robot and a wireless charging coil of the vehicle, includes the following steps: Performing chassis identification and classification on the chassis pictures by using a trained convolutional neural network model, determining vehicle type classification, and determining a first relative position of a vehicle wireless charging coil on a vehicle chassis according to the vehicle type classification; Performing visual positioning according to the currently acquired chassis picture, and determining a second relative position of a visual center of the wireless charging robot on the chassis of the vehicle; and determining the deviation between the current position of the wireless charging robot and the first position of the wireless charging coil of the vehicle according to the first relative position and the second relative position. In some embodiments, the charging control method for a wireless charging robot further includes the steps of: calculating the average gray value of the acquired chassis picture; Under the condition that the average gray value is smaller than a first gray threshold value, performing image enhancement processing on the chassis picture; And under the condition that the average gray level value is larger than the second gray level threshold value, reducing the brightness of the light supplementing lamp and re-shooting the chassis picture. In some embodiments, the convolutional neural network model is trained by: Acquiring chassis pictures of different wireless charging automobiles as sample data; The sample data is subjected to data enhancement processing and sample labeling processing to form a sample database, wherein the label of the sample data comprises a chassis detection frame, vehicle type classification and a first relative position of a vehicle wireless charging coil on a vehicle chassis; And training the convolutional neural network model by using the sample database to obtain a trained convolutional neural network model. In some embodiments, the magnetic induction profile includes a plurality of magnetic induction profiles acquired by the Hall effect sensor array, the magnetically locating based on the magnetic induction profile, determining a second positional of