Wall Permeability Estimation in Automotive Particulate Filters

Callum Samuels, Ran Holtzman, Stephen Benjamin, Svetlana Aleksandrova, Timothy C Watling, Humberto Medina

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Porous wall permeability is one of the most critical factors for the estimation of backpressure, a key performance indicator in automotive particulate filters. Current experimental and analytical filter models could be calibrated to predict the permeability of a specific filter. However, they fail to provide a reliable estimation for the dependence of the permeability on key parameters such as wall porosity and pore size.

This study presents a novel methodology for experimentally determining the permeability of filter walls. The results from four substrates with different porosities and pore sizes are compared with several popular permeability estimation methods (experimental and analytical), and their validity for this application is assessed. It is shown that none of the assessed methods predict all permeability trends for all substrates, for cold or hot flow, indicating that other wall properties besides porosity and pore size are important.

The hot flow test results show an increase in permeability with temperature, which is attributed to the effects associated with slip-flow. It is shown that the slip-effect magnitude also varies with the filter wall properties. Existing models that account for the effect of slip are assessed and are shown to underpredict the effect considerably for all four substrates. This is important for the prediction of through-wall losses in applications where permeability increase with temperature is a desirable effect. Further investigation is needed to consider the effect of the high temperatures in exhaust applications.
Original languageEnglish
Article number2023-24-0110
Number of pages13
JournalSAE Technical Papers
Early online date28 Aug 2023
Publication statusPublished - 30 Aug 2023
Event16th International Conference on Engines & Vehicles for Sustainable Transport - Naples, Italy
Duration: 10 Sept 202314 Sept 2023

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