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Influence of possible future fuel formulations and after-treatment technology on diesel engine pollutants

Ziel

The objectives of this project are :
1) to investigate the influence of possible future fuel formulations on diesel pollutant emissions especially when the engine is run in severe conditions (cold starting, low ambient temperature and transient operation);
2) to study how changes in fuel or engine parameters may act on the efficiency of NOx reduction catalysts.


The work programme is split into three main phases.
The first two phases aim to study the effect of fuel formulations on diesel emissions. The third part is devoted to the efficiency of NOx reduction catalysts.

1. Fuel Processing
Ten fuels will be processed to investigate the influence of chemical structure on emissions and also the reliability of the cetane number as an indicator of fuel cleanliness. In this matrix, possible future fuels with very specific characteristics are included:
- a straight-run fuel fully desulfurized (cetane 50);
- a highly hydrotreated fuel (cetane 60);
- a Fischer-Tropsch fuel (cetane 70);
- two oxygenated fuels (cetane respectively 50 and 60);
- an oligomerisation fuel (cetane 40);
- four fuels (2 of cetane 50, 2 of cetane 60) obtained from the others by blending.

2. Influence on emissions
These fuels will be tested in different engine configurations (HD and LD of DI and IDI type) and for running conditions including low temperature operation and transient phases supposed to enhance the sensitivity of the engine to fuel quality.

3. NOx reduction catalyst
The performance of reduction catalyst may be improved with a high HC exhaust content. The influence on the catalyst efficiency of an increase in this HC level obtained by changes in combustion system design or engine tuning will be examined. As fuel may also influence the level and the nature of the hydrocarbons emitted, these tests will be performed with two fuels differing by their cetane number and their chemical structure.

Wissenschaftliches Gebiet

CORDIS klassifiziert Projekte mit EuroSciVoc, einer mehrsprachigen Taxonomie der Wissenschaftsbereiche, durch einen halbautomatischen Prozess, der auf Verfahren der Verarbeitung natürlicher Sprache beruht.

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