(487ad) Filtration and Pressure Drop Modeling of Diesel Particulate Filters | AIChE

(487ad) Filtration and Pressure Drop Modeling of Diesel Particulate Filters

Authors 

Huang, D. - Presenter, Michigan Technological University


At present, the wall-flow monolith diesel particulate filter (DPF) is one of the most efficient devices to trap and remove particulates from diesel exhaust to meet emissions criteria. The DPF must be regenerated periodically to combust the accumulated particulate matter. If the regeneration is not done properly, the DPF could be damaged and rendered ineffective. For example, during the trapping and regeneration processes within the DPF, flow channeling may occur. This is a dangerous problem because diesel particulate matter entering with the gas flow may continue to accumulate near the entrance of the DPF. When the next regeneration occurs, the large amount of particulate present will lead to a large local heat release which may crack or melt the substrate and render it ineffective to trap particulates. Another issue that a DPF control mechanism must account for is the pressure drop across the trap as it impacts vehicle power output and fuel economy.

As a portion of a project with a long-term goal of the development of a simple control algorithm for DPF regeneration, the focus of this presentation is the development of particulate filtration and pressure drop models for the DPF. The filtration model is used to calculate the filter collection efficiency (a clean DPF substrate itself has a poor filtration efficiency ~ 80%) and to model the formation of a soot cake layer on top of the substrate wall (after which the filtration efficiency approaches 100%). The filtration model is linked with a pressure drop model. This second model calculates the pressure in the inlet and outlet channels for a given temperature and particulate deposit profile. The results of both of these models will ultimately be linked with the regeneration models we have presented previously and used to predict particulate trapping, fuel economy, and particulate regeneration under a wide range of driving conditions.