Engine performance and emission analysis of LPG-SI engine with the aid of artificial neural network

Yusaf, T. and Saleh, K. H. and Said, M. A. (2011) Engine performance and emission analysis of LPG-SI engine with the aid of artificial neural network. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 225 (5). pp. 591-600. ISSN 0957-6509


Artificial neural network (ANN) technique is used in this analysis to estimate the performance and emission concentration of liquefied petroleum gas (LPG) spark-ignition (SI) engine. The performance indicators include fuel consumption and brake thermal efficiency while
the emission components are NOx, CO, CO2, O2, and unburned hydrocarbon (UHC). Data of engine body temperature and exhaust gas temperature are also simulated. The first part of this study involves experimental works where a single-cylinder four-stroke SI engine was modified to allow the intake of LPG and operated at variable loadings with constant speed. The experimental results show that LPG produces comparable performance at high loads while significant reduction takes place in NOx, CO, CO2, O2, and UHC concentrations. The second part of this study involves the use of back-propagation algorithm for the training of the ANN model. The result of the simulation reveals that ANNmodel is appropriate to estimate the engine performance and gas exhaust emissions with correlation coefficient ranging from 0.9 to 0.99 with low root meansquared error and low mean relative error.

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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to paper due to publisher copyright policy.
Faculty / Department / School: Historic - Faculty of Engineering and Surveying - Department of Mechanical and Mechatronic Engineering
Date Deposited: 28 Jul 2011 04:13
Last Modified: 25 Aug 2014 03:24
Uncontrolled Keywords: artificial neural network; liquefied petroleum gas; spark-ignition engine; performance; emission
Fields of Research : 09 Engineering > 0913 Mechanical Engineering > 091305 Energy Generation, Conversion and Storage Engineering
09 Engineering > 0902 Automotive Engineering > 090203 Automotive Mechatronics
09 Engineering > 0902 Automotive Engineering > 090201 Automotive Combustion and Fuel Engineering (incl. Alternative/Renewable Fuels)
Socio-Economic Objective: E Expanding Knowledge > 97 Expanding Knowledge > 970109 Expanding Knowledge in Engineering
Identification Number or DOI: 10.1177/0957650911402546
URI: http://eprints.usq.edu.au/id/eprint/19356

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