Implementation of ANN for Predication of Performance and Emission Characteristics in CI Engine

Over the past few years, Global warming and huge Depletion of Petroleum resources have increased the need for alternate fuels for Internal Combustion (IC) Engine. In recent years, bio-diesel extracted from vegetable oil is becoming popular since it is renewable and environment friendly. There are multiple parameters involved in determining the performance of IC engines and these parameters are linked to each other. Since multiple inter-related factors are involved, optimizing the performance of IC engines is a challenging task. Existing methods show poor performance and also they are time consuming. Due to the ability to analyze complex and huge volume of data, Applications of Machine Learning and Deep Learning algorithms is increasingly used in various fields. Artificial Neural Network (ANN) is used in the field of optimizing the performance of IC engines. In this paper, recent developments have been analyzed and the use of ANN in predicting various parameters is discussed. Three different blends of diesel, jatropha oil and neem oil was taken and the input parameter load is varied to predict the output parameters. Experiments shows that ANN has produced better optimization.