Performance and Exhaust Emissions of a Diesel Engine Using Hybrid Fuel with an Artificial Neural Network

This study deals with artificial neural network modeling to predict the performance and exhaust emissions of the diesel engine using hybrid fuel. A single cylinder, four-stroke diesel engine was fueled with hybrid fuel and operated at different load conditions to acquire data for training and testing the proposed artificial neural network model. About 70% of the acquired experimental data were used in the view of training while the other 30% was used for testing the proposed model. The artificial neural network model was developed on the basis of standard back propagation algorithm. The developed artificial neural network model predicts the performance and exhaust emissions of the diesel engine with a correlation coefficient of 0.975-0.999 and a low root mean square error. The present study reveals that the artificial neural network approach could be confidently used to predict the performance and emissions of the diesel engine accurately.