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There is a great deal of interest in new technologies to assist in reducing the CO2 output of passenger vehicles, as part of the drive to meet the limits agreed by the EU and the European Automobile Manufacturer's Association ACEA, itself a result of the Kyoto Protocol. For the internal combustion engine, the most promising of these include gasoline direct injection, downsizing and fully variable valve trains. While new types of spray-guided gasoline direct injection (GDI) combustion systems are finally set to yield the level of fuel consumption improvement which was originally promised for the so-called ‘first generation’ wall- and air-guided types of GDI, injectors for spray-guided combustion systems are not yet in production to help justify the added complication and cost of the NOx trap necessary with a stratified combustion concept.

Future demands regarding emissions, fuel consumption and driveability lead to complex engine and power train control systems. The calibration of the increasing number of free parameters in the ECU's contradicts the demand for reduced time in the power train development cycle. This paper will focus on the automatic, unmanned closed loop optimization of driveability quality on a high dynamic engine test bed. The collaboration of three advanced methods will be presented: Objective real time driveability assessment, to predict the expected feelings of the buyers of the car Automatic computer assisted variation of ECU parameters on the basis of statistical methods like design of experiments (DoE). Thus data are measured in an automated process allowing an optimization based on models (e.g. neural networks).

A test facility was constructed at University College London to study fuel spray structure within a gasoline direct injection engine. The facility consisted of a single cylinder research engine with extensive optical access and a novel video imaging and analysis system. The engine used an experimental prototype 4-valve cylinder head with direct in-cylinder high pressure fuel injection, provided by a major automotive manufacturer. The fuel spray was illuminated using a pulsed copper-vapour laser. Results are presented that illustrate the spray behaviour within the fired research engine. A laser light sheet provided an insight into the inner spray cone behaviour.

This program examined the PAH emissions from two diesel engines representing state-of-the-art technology. One heavy-duty engine, a DDC Series 60, used in highway trucks, and one medium-duty engine, Navistar DTA-466, used in pick-up and delivery type vehicles. The medium-duty engine was tested for engine out emissions and with two different sized exhaust oxidation catalysts. Both of the catalysts were composed of a ceramic monolith coated with a palladium type catalyst. Both engines were tested according to the US EPA transient emissions test on a series of diesel fuels blended with varying aromatics and PAH contents to determine the impact of fuel quality on emissions. All diesel fuels had a low sulphur content (<0.05%) to minimize the formation of sulphate. The particulate matter was collected on teflon-coated filters, backed up with polyurethane foam filters to capture the vapour phase PAH.