* " /> * "/> * " />
Browse Publications Technical Papers 2004-01-0646
2004-03-08

Emissions Prediction of CNG/Diesel Dual Fuel Engine Based on RBF Neural Network * 2004-01-0646

Compressed Natural Gas (CNG)/diesel Dual Fuel Engine(DFE) was one of the best choices for solving energy crisis and environment pollution. In order to study and improve the emission performance of the CNG/diesel DFE, an emission model by means of Radial Basis Function neural network was established. The model identified as a black box model with input-output training data didn't require priori knowledge. There were 100 group experimental data over the operation conditions from low load and low rotate speed to heavy load and high rotate speed using for training the neural network, and 20 group test data using for verifying the model.
The study results showed that the predicted results were good agreement with the experimental data. This proves that the developed emission model can be used to successfully predict and optimize the emission performance of DFE.

SAE MOBILUS

Subscribers can view annotate, and download all of SAE's content. Learn More »

Access SAE MOBILUS »

Members save up to 16% off list price.
Login to see discount.
Special Offer: Download multiple Technical Papers each year? TechSelect is a cost-effective subscription option to select and download 12-100 full-text Technical Papers per year. Find more information here.
We also recommend:
TECHNICAL PAPER

Effect of LPG Intake Temperature, Pilot Fuel and Injection Timing on the Combustion Characteristics and Emission of a LPG - Diesel Dual Fuel Engine

2001-28-0028

View Details

TECHNICAL PAPER

Lubricity of Volatile Fuels for Compression Ignition Engines

2000-01-1804

View Details

TECHNICAL PAPER

Prediction of Autoignition and Flame Properties for Multicomponent Fuels Using Machine Learning Techniques

2019-01-1049

View Details

X