The use of compressed natural gas (CNG) as a fuel in internal combustion engines brings significant advantages in terms of reduction of CO2-emissions and fuel consumption. Compared to standard gasoline combustion, the CO2-production can be clearly reduced by using a methane-based fuel as it has a beneficial H/C ratio. The high knock resistance of methane allows higher compression ratios so that the thermodynamic efficiency is enhanced. Furthermore, the realization of a stratified mixture formation concept shows great potential to further increase fuel savings due to the reduced throttling losses. In the present work, an URANS-based simulation strategy using the commercial code AVL Fire for the direct injection (DI) of CNG and the mixture formation, including a discretisation of the full nozzle and cylinder geometry is presented. High pressure ratios between the injector and the cylinder lead to a choked flow inside the nozzle. A supersonic region, including shock-occurrence follows as the jet is expanded further downstream the orifice. To successfully resolve the multi-scale flow phenomena the mesh generation process involves the design of a fine hexahedral mesh for the injector, which is merged to the moving cylinder mesh by an arbitrary interface. Turbulence is modelled using the k-ζ-f model. To estimate the grid-induced error of the simulation, a set of calculations was performed on meshes of decreasing cell dimension. Different nozzle geometries are investigated and evaluated with regard to their mixture formation suitability as well as the effect of increasing rail pressure. Variations include an inward opening multi-hole injector and an outward opening annular ring injector. The results show a strong tendency of the gas jets to interact with each other and with the surrounding walls.
CITATION STYLE
Twellmeyer, A., Köpple, F., & Weigand, B. (2016). A novel CFD approach for modelling the high-pressure direct injection and mixture formation in a spark-ignited CNG engine. International Journal of Computational Methods and Experimental Measurements, 4(4), 424–433. https://doi.org/10.2495/CMEM-V4-N4-424-433
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