Search Results

The findings presented in this paper result from a collaboration between two Federal Laboratories in Switzerland. In this research project the characteristics of the particulates from internal combustion engines were investigated in detail. Measurements were carried out on a single-cylinder research engine focusing on exhaust particulate matter emissions. The single-cylinder diesel engine is supercharged and features a common-rail direct injection system. This work analyzes the influence of fuel properties and injection parameters on the particulate number size distribution. For the fuel composition, five different fuels including low sulfur diesel, zero-sulfur and zero-aromatics diesel, two blending portions of oxygenated diesel additive and rapeseedmethylester were used. For the injection parameters the injection pressure, the start of injection and the fuel amount in the pilot- and in the post-injection phases were varied.

Oxygenated fuel additives are currently an important research topic for particulate emissions reduction in diesel engines with direct injection (DI) to meet future emission regulations. In this work more than twenty oxygenated hydrocarbons from the literature were considered as diesel fuel additives. Butylal (an acetal compound, chemical formula C9H20O2) offers significant advantages over most other oxygenates in that its physical properties are very close to those of common diesel fuel. Wear scar measurements were conducted to evaluate the lubricity characteristics of diglyme (C6H14O3), ethyldiglyme (C8H18O3), butylal and different diesel-butylal mixtures. The results reveal the low lubricity of all oxygenated compounds. Thus, for the engine tests, a lubricity improver has been added to the diesel-butylal mixtures.

A new approach within the well-known trade-off in combustion process simulations between computational efforts (and thus the capability for engine operating map calculations) on the one hand, and accuracy of predictions on the other, has been developed and applied successfully to diesel combustion, in particular to energy release and pollutant formation. Using phenomenological models in combination with bio-inspired algorithms (for parameter identification), it is now possible to predict thermal, chemical and injection related engine characteristics over an entire operating map including different types of fuel (e.g. diesel, water-in-diesel emulsions and oxygenated diesel).