Particle Emissions and Soot Reactivity using Renewable Fuels in a Diesel Engine
Poster (konferens), 2019
The Internal combustion engine is a well-established technology for transportation of people and goods. Due to the global warming effect, fossil fuels need to be replaced by renewable fuels. Moreover, local emissions and especially particulate emissions pose serious concerns because of the associated health issues. The particulate matter (PM) emitted by the engine is efficiently trapped in the Diesel Particulate Filter (DPF). However, the performance of the DPF depends on the characteristics of the PM emissions which in turn, depends on the properties of the fuel used. The characterization of the PM emissions is important to understand the performance of exhaust gas aftertreatment system (EATS) as well as the contribution to health issues.
In this experimental study, a methodology was developed to sample PM from the exhaust flow. By controlling the evaporation of volatile components in an upstream oxidation catalyst, the solid particles were captured in a miniaturized diesel particulate filter (DPF). The sampling flow was high in order to enable short engine operation. The captured PM was subsequently oxidized using O2 and NO2 in order to extract the soot reactivity.
By running a heavy-duty diesel engine using different fuels, both the particle size distribution and the soot reactivity could be compared. The results presented here compares traditional diesel fuel and an oxygenated fuel (5% oxygen). The oxygenated fuel was a mixture of Propylheptanol (46%), HVO (34%) and diesel fuel (20%). Both fuels had the same cetane number and very similar combustion.
The soot reactivity was similar when oxidized by NO2 (passive regeneration) whereas the reactivity with O2 (active regeneration) was higher for the oxygenated fuel. This can be attributed to the smaller particles and higher surface area.
By capturing PM in a mini-DPF and oxidizing in a controlled way, useful information about the PM emissions was obtained. This type of information is very useful when evaluating renewable fuels to be used in the future.