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An investigation of engine performance parameters and artificial intelligent emission prediction of hydrogen powered car


Ho, NT and Karri, V and Lim, D and Barrett, DT, An investigation of engine performance parameters and artificial intelligent emission prediction of hydrogen powered car, International Journal of Hydrogen Energy, 33, (14) pp. 3837-3846. ISSN 0360-3199 (2008) [Refereed Article]

DOI: doi:10.1016/j.ijhydene.2008.04.037


With the depletion of fossil fuel resources and the potential consequences of climate change due to fossil fuel use, much effort has been put into the search for alternative fuels for transportation. Although there are several potential alternative fuels, which have low impact on the environment, none of these fuels have the ability to be used as the sole "fuel of the future". One fuel which is likely to become a part of the over all solution to the transportation fuel dilemma is hydrogen. In this paper, The Toyota Corolla four cylinder, 1.8 l engine running on petrol is systematically converted to run on hydrogen. Several ancillary instruments for measuring various engine operating parameters and emissions are fitted to appraise the performance of the hydrogen car. The effect of hydrogen as a fuel compares with gasoline on engine operating parameters and effect of engine operating parameters on emission characteristics is discussed. Based on the experimental setup, a suite of neural network models were tested to accurately predict the effect of major engine operating conditions on the hydrogen car emissions. Predictions were found to be ±4% to the experimental values. This work provided better understanding of the effect of engine process parameters on emissions. © 2008 International Association for Hydrogen Energy.

Item Details

Item Type:Refereed Article
Research Division:Engineering
Research Group:Automotive engineering
Research Field:Automotive combustion and fuel engineering
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in engineering
UTAS Author:Ho, NT (Dr Tien Ho)
UTAS Author:Karri, V (Associate Professor Vishy Karri)
UTAS Author:Lim, D (Mr Daniel Lim)
UTAS Author:Barrett, DT (Mr Danny-Shay Barrett)
ID Code:55348
Year Published:2008
Web of Science® Times Cited:24
Deposited By:Centre for Renewable Power Energy Systems
Deposited On:2009-03-09
Last Modified:2009-09-03

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