Application of ANN for Reduction of Nitrogen Oxides in C.I. engine coupled with EGR

Biodiesel is a fuel alternative for diesel and promises energy security in transportation system. Various studies shows that biodiesel-fuelled engines produce less carbon monoxide, unburned hydrocarbon, and smoke compared to diesel fuel but higher nitrogen oxide emissions. Exhaust gas recirculation (EGR) is effective to reduce NO_X from diesel engines because it lowers the flame temperature and the oxygen concentration in the combustion chamber. The present study explores the potential of artificial neural network to predict the NO_X emission of single cylinder four stroke C.I. engine fuelled with biodiesel under varying percentage of EGR. The major objective of this paper is to illustrate how ANN technique might play an important role in modeling and optimization of the NO_X emission of CI engine fuelled with Jatropha seed oil and also to understand the effect of varying percentage of EGR on CI engine emission.