Packed bed of spherical particles approach for pressure drop prediction in wall-flow DPFs (diesel particulate filters) under soot loading conditions

José Ramón Serrano, Francisco José Arnau, Pedro Piqueras and Óscar García-Afonso

Energy, 2013, vol. 58, issue C, 644-654

Abstract: The soot loading process in wall-flow DPFs (diesel particulate filters) affects the substrate structure depending on the filtration regime and produces the increase of pressure drop. Deep bed filtration regime produces the decrease of the porous wall permeability because of the soot particulates deposition inside it. Additionally, a layer of soot particulates grows on the porous wall surface when it becomes saturated. As soot loading increases, the pressure drop across the DPF depends on the porous wall and particulate layer permeabilities, which are in turn function of the substrate and soot properties. The need to consider the DPF pressure drop influence on engine performance analysis or DPF regeneration processes requires the use of low-computational effort models describing the structure of the soot deposition and its effect on permeability. This paper presents a model to describe the micro-scale of the porous wall and the particulate layer structure assuming them as packed beds of spherical particles. To assess the model's capability, it is applied to predict the DPF pressure drop under different experimental conditions in soot loading, mass flow and gas temperature.

Keywords: Diesel engines; Aftertreatment; Diesel particulate filter; Soot loading; Micro-scale properties (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544213004714
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:58:y:2013:i:c:p:644-654

DOI: 10.1016/j.energy.2013.05.051

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().