Neural Computing and Applications, ( ISI ), Volume (20), No (3), Year (2011-3) , Pages (303-308)

Title : ( Soot emission prediction of a waste gated waste-gated turbo- Charged DI diesel engine using artificial neural network )

Authors: Mohsen Ghazikhani , Iman Mirzaee kakhki ,

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Abstract

Abstract This study is about soot emission prediction of a waste-gated turbo-charged DI diesel engine using Artificial Neural Network (ANN). For training the ANN model, six ranges of experimental data in previous study were used and one range of data was kept for testing the accuracy of ANN predictions. The input parameters for the ANN are inlet manifold pressure, inlet manifold temperature, inlet air mass flow rate, fuel consumption, engine torque and speed. Output parameter is the density of soot in the exhaust. The results show the ANN approach can be used to accurately predict soot emission of a turbo-charged diesel engine in different Opening Ranges of Waste-Gate (ORWG). Root mean squared-error (RMSE), fraction of variance (R^2) and mean absolute percentage error (MAPE) for predictions were found to be 1.19(mg/m^3 ), 0.9998 and 6.4% respectively.

Keywords

, Keywords Artificial neural network, DI Diesel engine, waste-gated turbocharger and soot emission.
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@article{paperid:1018870,
author = {Ghazikhani, Mohsen and Mirzaee Kakhki, Iman},
title = {Soot emission prediction of a waste gated waste-gated turbo- Charged DI diesel engine using artificial neural network},
journal = {Neural Computing and Applications},
year = {2011},
volume = {20},
number = {3},
month = {March},
issn = {0941-0643},
pages = {303--308},
numpages = {5},
keywords = {Keywords Artificial neural network; DI Diesel engine; waste-gated turbocharger and soot emission.},
}

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%0 Journal Article
%T Soot emission prediction of a waste gated waste-gated turbo- Charged DI diesel engine using artificial neural network
%A Ghazikhani, Mohsen
%A Mirzaee Kakhki, Iman
%J Neural Computing and Applications
%@ 0941-0643
%D 2011

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