Application of Artificial Intelligence to Predict the Performance and Exhaust Emissions of Diesel Engine using Rapeseed Oil Methyl Ester

Abstract

Artificial neural network (ANN) in artificial intelligence is an implementation of an algorithm inspired by research into the brain. This paper deals with artificial neural network modeling of a diesel engine to predict the engine performance and exhaust emission characteristics. Experiments were conducted on a single cylinder four stroke diesel engine fuelled with diesel as well as various percentages of blends of rapeseed oil methyl ester with diesel at different loads to acquire data for training and testing the proposed ANN. To train the network, biodiesel blend percentage, engine load, specific fuel consumption and exhaust gas temperature were used as the input variables where as the engine performance together with engine exhaust emissions were used as the output variables. Online back-propagation algorithm was used to train the network. ANN model can predict the engine performance and exhaust emissions quite well with correlation coefficients with very low root mean square errors.