화학공학소재연구정보센터
International Journal of Hydrogen Energy, Vol.35, No.10, 4687-4701, 2010
A quasi-dimensional combustion model for performance and emissions of SI engines running on hydrogen-methane blends
The development of a predictive two-zone, quasi-dimensional model for the simulation of the combustion process in spark ignited engines fueled with hydrogen, methane, or hydrogen-methane blends is presented. The code is based on a general-purpose thermodynamic framework for the simulation of the power cycle of internal combustion engines. Quasi-dimensional modelling describes the flame front development assuming a simplified spherical geometry, as well as infinitesimal thickness. The flame front subdivides the in-cylinder volume into a zone of unburned mixture, and a second zone of burned gases. As far as the combustion process is concerned, attention is paid to the description of the physical and chemical phenomena controlling the flame development and the formation of combustion products. First of all, an empirical correlation has been defined for estimating the laminar burning velocity. The equation, tailored for arbitrary fuel blendings and equivalence ratios, has been validated against detailed experimental data. Furthermore, the influence of turbulence on flame evolution has been implemented according to a fractal-based model. Then, a physical and chemical computing environment for evaluating both gaseous mixtures' thermodynamic properties, and equilibrium species concentrations of combustion products has been developed and coupled to the code. The validation has been performed by comparing numerical pressure traces against literature experimental data, on a standard CFR single-cylinder engine. A unique set-up of the model parameters has been obtained, suitable for both pure hydrogen and pure methane fuelings; finally, the predictive capabilities of the model have been applied to analyze different fuel blends and equivalence ratios: the comparison against experimental pollutant emissions (NO and CO) shows a reasonable accuracy. (C) 2010 Professor T. Nejat Veziroglu. Published by Elsevier Ltd. All rights reserved.