Artificial neural network based determination of the performance and emissions of a Diesel engine using ethanol-diesel fuel blends

Authors : Özer CAN, Erkan ÖZTÜRK, Erol ARCAKLIOĞLU

Pages : 43-51

Doi:10.30939/ijastech..805531

View : 16 | Download : 10

Publication Date : 2021-03-31

Article Type : Research Paper

Abstract :In this study, the performance and exhaust emission values in a four-stroke, four-cylinder turbocharged Diesel engine fueled with ethanol-diesel fuel blends insert ignore into journalissuearticles values(10% and 15% in volume); were investigated by using Artificial Neural Network insert ignore into journalissuearticles values(ANN); modeling. The actual data derived from engine test measurements was applied in model training, cross-validation, and testing. To train the network, fuel injection pressures, throttle positions, engine speed, and ethanol fuel blend ratios were used as input layer in the network. The outputs are the engine performance values insert ignore into journalissuearticles values(engine torque, power, brake mean effective pressure, and specific fuel consumption); and exhaust emissions insert ignore into journalissuearticles values(SO2, CO2, NOx, and smoke level insert ignore into journalissuearticles values(N%);); which were measured in the experiments. The back-propagation learning algorithm with three different variants, a single layer, and logistic sigmoid transfer function insert ignore into journalissuearticles values(log-sig); was used in the network. By using the weights of the network, formulations were given for each output. The network for test data yielded the R2 values of 0.999 and the mean % errors for test data are smaller than 3.5% for the performance and 8% for the emissions.
Keywords : Artificial neural network, Diesel engine performance, Ethanol diesel fuel, Exhaust emissions