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The effects of different Research Octane Number [RON] fuels on a multi-cylinder light-duty compression ignition [CI] engine were investigated at light load conditions. Experiments were conducted on a GM 1.9L 4-cylinder diesel engine at Argonne National Laboratory, using two different fuels, i.e., 75 RON and 93 RON. Emphasis was placed on 5 bar BMEP load, 2000 rev/min engine operation using two different RON fuels, and 2 bar BMEP load operating at 1500 rev/min using 75 RON gasoline fuel. The experiments reveal difficulty in controlling combustion at low load points using the higher RON fuel. In order to explain the experimental trends, simulations were carried out using the KIVA3V-Chemkin Computational Fluid Dynamics [CFD] Code. The numerical results were validated with the experimental results and provided insights about the engine combustion characteristics at different speeds and low load conditions using different fuels.

Diesel fuels are complex mixtures of thousands of hydrocarbons. Since modeling their combustion characteristics with the inclusion of all hydrocarbon species is not feasible, a hybrid surrogate model approach is used in the present work to represent the physical and chemical properties of three different diesel fuels by using up to 13 and 4 separate hydrocarbon species, respectively. The surrogates are arrived at by matching their distillation profiles and important properties with the real fuel, while the chemistry surrogates are arrived at by using a Group Chemistry Representation (GCR) method wherein the hydrocarbon species in the physical property surrogates are grouped based on their chemical classes, and the chemistry of each class is represented by using up to two hydrocarbon species.

Simultaneous two-component measurements of gas velocity and multi-dimensional numerical simulation are employed to characterize the evolution of the in-cylinder turbulent flow structure in a re-entrant bowl-in-piston engine under motored operation. The evolution of the mean flow field, turbulence energy, turbulent length scales, and the various terms contributing to the production of the turbulence energy are correlated and compared, with the objectives of clarifying the physical mechanisms and flow structures that dominate the turbulence production and of identifying the source of discrepancies between the measured and simulated turbulence fields. Additionally, the applicability of the linear turbulent stress modeling hypothesis employed in the k-ε model is assessed using the experimental mean flow gradients, turbulence energy, and length scales.