A parametric study for specific fuel consumption of an intercooled diesel engine using a neural network

► Parametric study is executed to investigate on the engine specific fuel consumption. ► These data were used to enhance train and test a NN model using a MATLAB program. ► NN based model were found to be convincing by the experimental results. Turbocharging is a process wherein the amount of oxygen...

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Published in:	Fuel (Guildford) Vol. 93; pp. 189 - 199
Main Author:	Uzun, Abdullah
Format:	Journal Article
Language:	English
Published:	Kidlington Elsevier Ltd 01.03.2012 Elsevier
Subjects:	air Applied sciences combustion Diesel engine diesel engines Energy energy use and consumption Energy. Thermal use of fuels Engines and turbines Equipments for energy generation and conversion: thermal, electrical, mechanical energy, etc Exact sciences and technology Fuels Intercooling Neural networks oxygen research projects Scaled conjugate gradient algorithm Specific fuel consumption temperature Diesel engine Scaled conjugate gradient algorithm Specific fuel consumption Neural networks Intercooling Combustion Neural network Experimental study Algorithm Project Model test Thermal efficiency Performance
ISSN:	0016-2361, 1873-7153
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Abstract	► Parametric study is executed to investigate on the engine specific fuel consumption. ► These data were used to enhance train and test a NN model using a MATLAB program. ► NN based model were found to be convincing by the experimental results. Turbocharging is a process wherein the amount of oxygen used in a combustion reaction is increased to raise output and decrease specific fuel consumption. On account of this, fuel economy and thermal efficiency are more important for all engines. The use of an intercooler reduces the temperature of intake air to the engine, and this cooler and denser air increases thermal and volumetric efficiency. Most research projects on engineering problems usually take the form of experimental studies. However, experimental research is relatively expensive and time consuming. In recent years, Neural Networks (NNs) have increasingly been used in a diverse range of engineering applications. In this study, various parametric studies are executed to investigate the interrelationship between a single variable and two steadies and two constant parameters on the brake specific fuel consumption (BSFC, g/kWh). The variables selected are engine speed, load and Crankshaft Angel (CA). The data used in the present study were obtained from previous experimental research by the author. These data were used to enhance, train and test a NN model using a MATLAB-based program. The results of the NN based model were found to be convincing and were consistent with the experimental results. The trained NN based model was then used to perform the parametric studies. The performance of the NN based model and the results of parametric studies are presented in graphical form and evaluated.
AbstractList	Turbocharging is a process wherein the amount of oxygen used in a combustion reaction is increased to raise output and decrease specific fuel consumption. On account of this, fuel economy and thermal efficiency are more important for all engines. The use of an intercooler reduces the temperature of intake air to the engine, and this cooler and denser air increases thermal and volumetric efficiency. Most research projects on engineering problems usually take the form of experimental studies. However, experimental research is relatively expensive and time consuming. In recent years, Neural Networks (NNs) have increasingly been used in a diverse range of engineering applications. In this study, various parametric studies are executed to investigate the interrelationship between a single variable and two steadies and two constant parameters on the brake specific fuel consumption (BSFC, g/kW h). The variables selected are engine speed, load and Crankshaft Angel (CA). The data used in the present study were obtained from previous experimental research by the author. These data were used to enhance, train and test a NN model using a MATLAB-based program. The results of the NN based model were found to be convincing and were consistent with the experimental results. The trained NN based model was then used to perform the parametric studies. The performance of the NN based model and the results of parametric studies are presented in graphical form and evaluated. Turbocharging is a process wherein the amount of oxygen used in a combustion reaction is increased to raise output and decrease specific fuel consumption. On account of this, fuel economy and thermal efficiency are more important for all engines. The use of an intercooler reduces the temperature of intake air to the engine, and this cooler and denser air increases thermal and volumetric efficiency. Most research projects on engineering problems usually take the form of experimental studies. However, experimental research is relatively expensive and time consuming. In recent years, Neural Networks (NNs) have increasingly been used in a diverse range of engineering applications. In this study, various parametric studies are executed to investigate the interrelationship between a single variable and two steadies and two constant parameters on the brake specific fuel consumption (BSFC, g/kWh). The variables selected are engine speed, load and Crankshaft Angel (CA). The data used in the present study were obtained from previous experimental research by the author. These data were used to enhance, train and test a NN model using a MATLAB-based program. The results of the NN based model were found to be convincing and were consistent with the experimental results. The trained NN based model was then used to perform the parametric studies. The performance of the NN based model and the results of parametric studies are presented in graphical form and evaluated. ► Parametric study is executed to investigate on the engine specific fuel consumption. ► These data were used to enhance train and test a NN model using a MATLAB program. ► NN based model were found to be convincing by the experimental results. Turbocharging is a process wherein the amount of oxygen used in a combustion reaction is increased to raise output and decrease specific fuel consumption. On account of this, fuel economy and thermal efficiency are more important for all engines. The use of an intercooler reduces the temperature of intake air to the engine, and this cooler and denser air increases thermal and volumetric efficiency. Most research projects on engineering problems usually take the form of experimental studies. However, experimental research is relatively expensive and time consuming. In recent years, Neural Networks (NNs) have increasingly been used in a diverse range of engineering applications. In this study, various parametric studies are executed to investigate the interrelationship between a single variable and two steadies and two constant parameters on the brake specific fuel consumption (BSFC, g/kWh). The variables selected are engine speed, load and Crankshaft Angel (CA). The data used in the present study were obtained from previous experimental research by the author. These data were used to enhance, train and test a NN model using a MATLAB-based program. The results of the NN based model were found to be convincing and were consistent with the experimental results. The trained NN based model was then used to perform the parametric studies. The performance of the NN based model and the results of parametric studies are presented in graphical form and evaluated.
Author	Uzun, Abdullah
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Keywords	Diesel engine Scaled conjugate gradient algorithm Specific fuel consumption Neural networks Intercooling Combustion Neural network Experimental study Algorithm Project Model test Thermal efficiency Performance
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Snippet	► Parametric study is executed to investigate on the engine specific fuel consumption. ► These data were used to enhance train and test a NN model using a... Turbocharging is a process wherein the amount of oxygen used in a combustion reaction is increased to raise output and decrease specific fuel consumption. On...
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SubjectTerms	air Applied sciences combustion Diesel engine diesel engines Energy energy use and consumption Energy. Thermal use of fuels Engines and turbines Equipments for energy generation and conversion: thermal, electrical, mechanical energy, etc Exact sciences and technology Fuels Intercooling Neural networks oxygen research projects Scaled conjugate gradient algorithm Specific fuel consumption temperature
Title	A parametric study for specific fuel consumption of an intercooled diesel engine using a neural network
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