Application of Artificial Intelligence on a CRDI Diesel Engine

The present study explores the potential of artificial neural network to predict the performance and exhaust emissions of an existing single cylinder four-stroke CRDI engine under varying CNG and EGR strategies. Based on the experimental data an ANN model is developed to predict performance and emission parameters of the experimental engine. The study was carried out with 70% of total experimental data selected for training the neural network, 15% for the network's cross-validation and remaining 15% data has been used for testing the performance of the trained network. The developed ANN models were capable of predicting the performance and emissions of the experimental engine with excellent agreement.

Autorentext

Sumit Roy is a young and dynamic exponent in the field of IC engines, alternate fuels & emission modelling with keen research interests on contemporary objectives of emission performance optimization strategies. He obtained PhD in Mechanical Engineering from NIT Agartala, India. He has published more than 10 SCI International Papers.