ENGINE SPEED CONTROL USING ONLINE ANN FOR VEHICLE WITH EMDAP-CVT
Keywords:
Artificial neural network, CVT control, electromechanical CVT, engine speed control.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
Dual Acting Pulley Continuously Variable Transmission (EMDAP-CVT),
maintaining 'constant engine speed based on either its optimum control line or maximum
engine power 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 Centre, 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 engine speed.
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