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Reseach Article

Artificial Neural Networks for Internal Combustion Engine Performance and Emission Analysis

by Anant Bhaskar Garg, Parag Diwan, Mukesh Saxena
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 87 - Number 6
Year of Publication: 2014
Authors: Anant Bhaskar Garg, Parag Diwan, Mukesh Saxena
10.5120/15212-3705

Anant Bhaskar Garg, Parag Diwan, Mukesh Saxena . Artificial Neural Networks for Internal Combustion Engine Performance and Emission Analysis. International Journal of Computer Applications. 87, 6 ( February 2014), 23-27. DOI=10.5120/15212-3705

@article{ 10.5120/15212-3705,
author = { Anant Bhaskar Garg, Parag Diwan, Mukesh Saxena },
title = { Artificial Neural Networks for Internal Combustion Engine Performance and Emission Analysis },
journal = { International Journal of Computer Applications },
issue_date = { February 2014 },
volume = { 87 },
number = { 6 },
month = { February },
year = { 2014 },
issn = { 0975-8887 },
pages = { 23-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume87/number6/15212-3705/ },
doi = { 10.5120/15212-3705 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:05:12.885094+05:30
%A Anant Bhaskar Garg
%A Parag Diwan
%A Mukesh Saxena
%T Artificial Neural Networks for Internal Combustion Engine Performance and Emission Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 87
%N 6
%P 23-27
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents an analytical work for better design system that contributes to the reduction of fuel consumption and emission for vehicle performance. The main technological issue on engines today is to comply with emission standards with cost-effective measures in order to keep the engine price still attractive to customer. The experimental research of engine performance are time consuming and quite expensive. The purpose of this work is to optimize engine performance using artificial neural networks (ANN). Back propagation neural network was used to optimize prediction model performance. The paper analyzed data from various experimental tests in which different engine operating parameters are measured. The paper highlights the framework and suitable model of ANN to optimize several operating parameters of the engine. The optimization includes a range of standards engine-operating conditions, with specified limits in emissions.

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Index Terms

Computer Science
Information Sciences

Keywords

Artificial Neural Networks Engine Operation ANN algorithms architecture