Technique for automating charging of an electric vehicle based on a Raspberry Pi controller using neural networks

The expansion of Russian market of electric and autonomous vehicles leads to an increase in demand for automation of contactless charging (without driver participation). The article proposes a method of contactless charging of electric vehicles, which involves automatically determining the type of car charging connector, selecting the appropriate charger and connecting it to the charging connector of an electric vehicle through the use of a robot manipulator. A feature of the technique is the determination of the type and coordinates of the location of the charging connector of the car by reading images obtained from the camera of a gas station in real time and processing them with a convolutional neural network model. A study was conducted, and a function was selected that allows optimally solving the problems of classification of charging connectors, which ensures maximum accuracy of the result. The volume of the training sample for the neural network was used in the amount of 10,000 images from a synthetic data set, which was created on the basis of three types of the most popular three-dimensional models of charging connectors on various backgrounds. The proposed technique is implemented in a prototype of a software and hardware control complex for a manipulative robot based on a Raspberry Pi controller.