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Today numerical models are a major part of the diesel engine development. They are applied during several stages of the development process to perform extensive parameter studies and to investigate flow and combustion phenomena in detail. The models are divided by complexity and computational costs since one has to decide what the best choice for the task is. 0D models are suitable for problems with large parameter spaces and multiple operating points, e.g. engine map simulation and parameter sweeps. Therefore, it is necessary to incorporate physical models to improve the predictive capability of these models. This work focuses on turbulence and mixing modeling within a 0D direct injection stochastic reactor model. The model is based on a probability density function approach and incorporates submodels for direct fuel injection, vaporization, heat transfer, turbulent mixing and detailed chemistry.

CAI combustion has the potential to be the most clean combustion technology in internal combustion engines and is being intensively researched. Following the previous research on CAI combustion of gasoline fuel, systematic investigation is being carried out on the application of bio-fuels in CAI combustion. As part of an on-going research project, CAI combustion of methanol and ethanol was studied on a single-cylinder direct gasoline engine with an air-assisted injector. The CAI combustion was achieved by trapping part of burnt gas within the cylinder through using short-duration camshafts and early closure of the exhaust valves. During the experiment the engine speed was varied from 1200rpm to 2100rpm and the air/fuel ratio was altered from the stoichiometry to the misfire limit. Their combustion characteristics were obtained by analysing cylinder pressure trace.

A novel 0-D Probability Density Function (PDF) based approach for the modelling of Diesel combustion using tabulated chemistry is presented. The Direct Injection Stochastic Reactor Model (DI-SRM) by Pasternak et al. has been extended with a progress variable based framework allowing the use of a pre-calculated auto-ignition table. Auto-ignition is tabulated through adiabatic constant pressure reactor calculations. The tabulated chemistry based implementation has been assessed against the previously presented DI-SRM version by Pasternak et al. where chemical reactions are solved online. The chemical mechanism used in this work for both, online chemistry run and table generation, is an extended version of the scheme presented by Nawdial et al. The main fuel species are n-decane, α-methylnaphthalene and methyl-decanoate giving a size of 463 species and 7600 reactions.