On the combination of complex chemistry with a 0-D coherent flame model to account for the fuel properties in spark ignition engines simulations: Application to methane-air-diluents mixtures

Abstract A promising way to reduce green house gases emissions of spark ignition (SI) engines is to burn alternative fuels like bio-mass-derived products, hydrogen or compressed natural gas. However, their use strongly impacts combustion processes in terms of burning velocities and emissions. Specific engine architectures as well as dedicated control strategies should then be optimized to take advantage of these fuels. Such developments are today increasingly performed using complete engine simulators running in times close to the real time and thus requiring very CPU efficient models. For this purpose, 0-dimensional models are commonly used to describe combustion processes in the cylinders. However, these models should reproduce the engine response for all possible fuels, which is not an obvious task regarding the evocated CPU constraints. This paper deals with the extension of a 0-dimensional coherent flame model (CFM), called CFM1D, to integrate chemical effects related to the fuel composition at low computational costs. Improvements have been carried out using an innovative approach based on a priori simulations of 1D premixed flames with a complex chemistry code. Databases of laminar flame speeds and thicknesses as well as burned gases compositions in engine-like conditions are generated from these simulations, all these information being required as inputs in CFM1D. The proposed approach is here applied to methane-air-diluents mixtures to simulate a large range of operating conditions of a spark ignition (SI) engine. A new laminar flame speed correlation adapted to engine thermodynamic conditions is also developed to save CPU time. Comparisons are made with experiments and with simulations performed using the original version of CFM1D based on a simple chemistry. The achieved results evidence the advantage of this new approach to account for the fuel composition effects on the engine behavior.

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