Prediction of NO_x Emissions from a Direct Injection Diesel Engine Using Artificial Neural Network

摘要

In the present study, artificial neural network is used to model the relationship between NO_x emissions and operating parameters of a direct injection diesel engine. To provide data for training and testing the network, a 6-inline-cylinder, four-stroke, diesel test engine is used and tested for various engine speeds, mass fuel injection rates, and intake air temperatures. 80% of a total of 144 obtained experimental data is employed for training process. In addition, 10% of the data (randomly selected) is used for network validation and the remaining data is employed for testing the accuracy of the network. The mean square error function is used for evaluating the performance of the network. The results show that the artificial neural network can efficiently be used to predict NO_x emissions from the tested engine with about 10% error.