Experimental measurement of the filtration efficiency and pressure drop of wall-flow diesel particulate filters (DPF) made of biomorphic Silicon Carbide using laboratory generated particles

Biomorphic Silicon Carbide (bioSiC) has been recently introduced in the scope of porous ceramic substrates for hot gas filtration applications, where it has demonstrated to have good thermal and mechanical properties, and a high potential to meet the requirements for current Diesel Particulate Filters (DPF). In this experimental study, a small wall-flow bioSiC diesel filter was characterized using a soot generator, the particle size distribution of which being similar to the one generated by a diesel engine. The bioSiC samples were manufactured from Medium Density Fiberboard (MDF) following a general manufacturing procedure for bioSiC ceramics, but paying special attention in the mechanizing stage to the geometry and optimal design of the honeycomb structure required for diesel engine applications. The samples had a cell density of 57.59 cell/cm(2) (371.6 cpsi), a square cross section of 9.2 x 9.2 mm, and a length of 31 mm. To generate the particle laden stream and perform the filtration tests, a synthetic Soot Generator (SG) was used. Tests were performed under controlled and reproducible conditions, with a fixed gas flow rate of 5 LPM and a soot mass flow rate of 4 mg/h. The filtration efficiency was determined with the aid of a Scanning Mobility Particle Sizer (SMPS) from the measurements of the particle concentration upstream and downstream the filter samples. During the soot loading process, the pressure drop was also monitored. The results show that, in the initial stage (clean filter), bioSiC wall-flow DPFs may have a filtration efficiency between 0.7 and 0.85 and a pressure drop of around 2 kPa for a normalized wall velocity of 0.01 m/s at ambient temperature. The filtration performance of wall-flow bioSiC particle filters showed in this work can help us to better understand their real potential for automotive applications. (C) 2017 Elsevier Ltd. All rights reserved.