A Coordination Control Algorithm as an Automobile Application for Wheel Torque of Parallel Hybrid Vehicles in Industry 4.0

Abstract

Abstract In Industry 4.0, everything is automated for utilizing the advantages of AI and Internet of Things (IoT). The automation is required for robotics based operations in the industries. The automobile industries are attempting to utilize the computational algorithms for improving the performance of the automobiles and for improving the performance of production lines. Innovative methods are demanded to resolve the automation problems in industry 4.0. In this paper a coordination control algorithm is proposed for wheel torque for parallel hybrid vehicles. Based on the fuzzy adaptive PID principle (proportional integral derivative), the wheel torque of a parallel hybrid vehicle is coordinated and controlled in the proposed work. To overcome the existing coordination problems of wheel torque, a new coordination control algorithm is designed for parallel hybrid vehicles. In wheel torque drive control, the feedforward and feedback joint control method of the wheel drive torque is utilized. The wheel braking torque control algorithm is used with the fuzzy PID controller to obtain the wheel braking torque; the engine output torque is compensated based on the PID control method of wheel angular speed difference, and a dynamic coordination controller is designed to keep an eye on the performance of the vehicle. The compensatory torque is provided by the motor, and the difference between the actual and intended angular velocity is changed in real time to provide dynamic coordination of the wheel under mode switching control. To assess the performance of the proposed control algorithm, the results are compared to those of the present system. As a result of implementing the proposed algorithm, the total output torque of a parallel hybrid vehicle in the industry 4.0 context can be reduced to 0.08 seconds, the accuracy of torque control can be increased by 11.1% over the existing system, the accuracy of the speed at which the vehicle tracks its speed can be increased by 8.0% over the existing system, and the vehicle dynamics can be improved by 4.4% during the switching process.