Research on Electronic Differential System of Electric Vehicle Based on Computer Vision

With the aggravation of the shortage of energy resources and air pollution, electric vehicles have gradually become one of the important development objects of new energy industry. Because the electric wheel drive vehicle eliminates the complex mechanical differential parts and mechanical transmission mechanism of traditional vehicles, and uses the hub motor to directly drive a single wheel, it simplifies the chassis structure and reduces the quality of the whole vehicle. It has the advantages of high transmission efficiency, flexible spatial layout and easy control. At the same time, the electric wheel drive vehicle is also facing an important problem, which is how to realize the speed coordination among electric wheels. In this paper, the dynamics of mechanical differential is analyzed, and the software is designed based on its principle, so as to realize the control scheme of electronic differential. The electric vehicle in this paper adopts the front wheel drive mode. The two hub motor is placed on the two front wheels as the driving wheel, which is controlled by two independent controllers. In addition, the structure and principle of the motor are analyzed, and its mathematical model is established. By analyzing the specific parameter relationship of the motor, the parameters that the controller should control are obtained, and the electronic differential control system is established, a speed regulation scheme suitable for electric vehicle is proposed. The design of electronic differential controller solves the steering problem of electric vehicle driven by hub motor. At the same time, compared with the traditional mechanical differential, it avoids the complex mechanical transmission structure. Moreover, since the problems of road surface and steering angle are not considered, the control calculation method is also simplified, which improves the stability of the control system and makes the vehicle have better turning performance and control response.