An empirical model for the carbon dioxide emissions of a diesel engine

A. Pennycott, Q. Zhang, C. J. Brace, R. Burke, Sam Akehurst

Research output: Contribution to journalArticle

Abstract

Carbon dioxide emissions from vehicles are a particular focus and challenge for automotive designers and manufacturers due to increasingly stringent engine emissions legislation. In addition to the potential environmental impacts, the rate of carbon dioxide production is strongly indicative of the efficiency and therefore fuel economy of an engine at its different operating conditions.

In this paper, a neural network model is developed in order to predict the carbon dioxide production rate from a number of engine variables including engine speed, torque, temperature and parameters controlling fuel injection timing. The model structure accurately predicts the rate of carbon dioxide production and has applications in future efficiency and emissions optimisation during engine design and also in online engine control
LanguageEnglish
Pages1507-1513
Number of pages7
JournalProceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering
Volume226
Issue number11
Early online date16 May 2012
DOIs
StatusPublished - Nov 2012

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Diesel engines
Carbon dioxide
Engines
Fuel injection
Fuel economy
Model structures
Environmental impact
Torque
Neural networks
Temperature

Cite this

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