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Experiments to study the effects of oxygenated fuels on emissions and combustion were performed in a single-cylinder direct-injection (DI) diesel engine. A matrix of oxygen containing fuels assessed the impact of weight percent oxygen content, oxygenate chemical structure, and oxygenate volatility on emissions. Several oxygenated chemicals were blended with an ultra-low sulfur diesel fuel and evaluated at an equivalent energy release and combustion phasing. Additional experiments investigated the effectiveness of oxygenated fuels at a different engine load, a matched fuel/air equivalence ratio, and blended with a diesel fuel from the Fischer-Tropsch process. Interactions between emissions and critical engine operating parameters were also quantified. A scanning mobility particle sizer (SMPS) was used to evaluate particle size distributions, in addition to particulate matter (PM) filter and oxides of nitrogen (NOx) measurements.

A thermodynamic based cycle simulation which uses a thermal boundary layer, either, a fully mixed or layered adiabatic core, and a crevice combustion inefficiency routine has been used to explore the sensitivity of NO concentration predictions to critical physical modeling assumptions. An experimental database, which included measurements of residual gas fraction, was obtained from a 2.0 liter Nissan engine while firing on propane. A model calibration methodology was developed to ensure accurate predictions of in-cylinder pressure and burned gas temperature. Comparisons with experimental NO data then showed that accounting for temperature stratification during combustion with a layered adiabatic core and including a crevice/combustion inefficiency routine, improved the match of modeling predictions to data, in comparison to a fully mixed adiabatic core.

The transportation sector in the United States is a major contributor to global energy consumption and carbon dioxide emission. To assess the future potentials of different technologies in addressing these two issues, we used a family of simulation programs to predict fuel consumption for passenger cars in 2020. The selected technology combinations that have good market potential and could be in mass production include: advanced gasoline and diesel internal combustion engine vehicles with automatically-shifting clutched transmissions, gasoline, diesel, and compressed natural gas hybrid electric vehicles with continuously variable transmissions, direct hydrogen, gasoline and methanol reformer fuel cell hybrid electric vehicles with direct ratio drive, and battery electric vehicle with direct ratio drive.