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Song, H. J.; Chen, L. G.; Sun, F. R. Optimisation of a Model External Combustion Engine with Linear Phenomenological Heat Transfer Law. Journal of the Energy Institute, Volume 82, Number 3, September 2009, pp. 180-183(4).

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Article

Development of External Combustion Engine

1Department of Mechanical Engineering, Trois Rivières University in Quebec, Trois Rivières, Canada

2Department of Internal Combustion Engines, Kharkov National Technical University, Kharkov, Ukraine

3Department of Internal Combustion Engines, Kharkov and Highway University, Kharkov, Ukraine


American Journal of Vehicle Design. 2013, Vol. 1 No. 2, 25-29
DOI: 10.12691/ajvd-1-2-2
Copyright © 2013 Science and Education Publishing

Cite this paper:
Rachid Maamri, Wassily Georgivitsh Dyatshenko, Alexandre Ivanovitsh Varonkov, Oleg Uryevitsh Linkov, Yvan Nikolaevitsh Nikitenko, Yves Dubé, Lotfi Toubal, Agbossou Kodjo. Development of External Combustion Engine. American Journal of Vehicle Design. 2013; 1(2):25-29. doi: 10.12691/ajvd-1-2-2.

Correspondence to: Rachid Maamri, Department of Mechanical Engineering, Trois Rivières University in Quebec, Trois Rivières, Canada. Email: maamri@uqtr.ca

Abstract

The internal combustion engines are generally a major source of air pollution. However the spark ignition engines are recognized by their carbon monoxide and unburned hydrocarbon emission. One of the methods used to reduce the emission of these pollutants is the use of external combustion engine. This paper describes the development of an external combustion engine which uses air in tanks at pressures of 30 - 50 МPа and at ambient temperature as combustion energy carrier, and hydrogen, alcohols or traditional motor fuel from organic minerals as chemical energy carrier. Research workings out are in the field finished to level of practical use. The mathematical and simulation model has been developed, tested, and verified to simulate a 4-stroke cycle of a spark ignition engine fuelled with gasoline. The results obtained from the present study have shown the capability of the model to predict the performance satisfactorily.

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