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Experimental Testing of a Low Temperature Regenerating Catalytic DPF at the Exhaust of a Light-Duty Diesel Engine
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 03, 2018 by SAE International in United States
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The wall-flow Diesel Particulate Filter (DPF) is currently the most common after-treatment system used to meet the particulate emission limits imposed by government regulations. Today’s technology shows the best balance between filtration efficiency and back-pressure in the engine exhaust pipe. Conventional filters consist in alternately plugged parallel square channels, so that the exhaust gases flow through the porous inner walls leading to particles trapping. During the accumulation phase the pressure drop across the filter increases, thus requiring periodic regeneration of the DPF through after and post fuel injection strategies.
This paper deals with the experimental testing of a catalytic silicon carbide (SiC) wall flow DPFs with CuFe2O4 loading. The filter was built following an optimized procedure based on a preliminary controlled chemical erosion of the SiC porous structure. Such method allows increasing the initial average pore diameter of the bare filters and consequently the deposition of higher catalyst load without affecting the pressure drop.
The experimental tests were performed at the exhaust of a EURO V light-duty Diesel engine, operating at different speed/load conditions. The results exhibit a filtration efficiency higher than 96% throughout the soot accumulation phase and a threshold catalyst temperature for the regeneration lower than 450 °C, with a duration of about 15 minutes. These values, if compared with those related to the uncatalysed commercial filter (600 °C and 25 minutes), evidence the possibility to achieve significant fuel saving along with shorter and thus flexible regeneration transients.
CitationRossomando, B., Arsie, I., Meloni, E., Palma, V. et al., "Experimental Testing of a Low Temperature Regenerating Catalytic DPF at the Exhaust of a Light-Duty Diesel Engine," SAE Technical Paper 2018-01-0351, 2018, https://doi.org/10.4271/2018-01-0351.
Data Sets - Support Documents
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