Engine speed control using artificial neutral network for vehicle equipped with electromechanical CVT

Abstract

Controlling engine speed corresponding to load variations and road condition has always been a challenge to automotive engineers. However, with the introduction of electromechanical CVT, maintaining constant engine speed based on its optimum control line characteristic could be made possible. This paper describes the simulation work in this area carried out by the Drivetrain Research Group at the Automotive Development Center, Universiti Teknologi Malaysia, Skudai Johor. The developed drive train model is highly non-linear, it could not be controlled satisfactorily by common linear control strategy such as PID controller. To overcome the problem, the use of Artificial Neural Network (ANN) is employed to indirectly control the engine speed by adjusting pulley CVT ratio. Computer simulations showed that applying artificial neural network (ANN) into drive train model could select a proper transmission ratio where the engine could be maintained to run at certain desired speed.