Turbulent Flow Pressure Losses in Gasoline Particulate Filters

Aleksandrova, Svetlana; Saul, Jonathan; Prantoni, Marco; Medina, Humberto; García-Afonso, Óscar; Bevan, M G; Benjamin, Stephen F.

doi:10.4271/03-12-04-0030

Cited by 6 publications

(7 citation statements)

References 47 publications

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“…However, recent investigations have shown that due to the high mass flows in GPFs turbulent friction, losses can also occur in the channels [ 38 ]. These observations have not been considered in this study but will be taken into account in the further development of the simulation model.…”

Section: Simulation Model Designmentioning

confidence: 99%

Modelling the Influence of Different Soot Types on the Radio-Frequency-Based Load Detection of Gasoline Particulate Filters

Walter

Schwanzer

Hagen

et al. 2020

Sensors

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Gasoline particulate filters (GPFs) are an appropriate means to meet today’s emission standards. As for diesel applications, GPFs can be monitored via differential pressure sensors or using a radio-frequency approach (RF sensor). Due to largely differing soot properties and engine operating modes of gasoline compared to diesel engines (e.g., the possibility of incomplete regenerations), the behavior of both sensor systems must be investigated in detail. For this purpose, extensive measurements on engine test benches are usually required. To simplify the sensor development, a simulation model was developed using COMSOL Multiphysics® that not only allowed for calculating the loading and regeneration process of GPFs under different engine operating conditions but also determined the impact on both sensor systems. To simulate the regeneration behavior of gasoline soot accurately, an oxidation model was developed. To identify the influence of different engine operating points on the sensor behavior, various samples generated at an engine test bench were examined regarding their kinetic parameters using thermogravimetric analysis. Thus, this compared the accuracy of soot mass determination using the RF sensor with the differential pressure method. By simulating a typical driving condition with incomplete regenerations, the effects of the soot kinetics on sensor accuracy was demonstrated exemplarily. Thereby, the RF sensor showed an overall smaller mass determination error, as well as a lower dependence on the soot kinetics.

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Section: Simulation Model Designmentioning

confidence: 99%

Modelling the Influence of Different Soot Types on the Radio-Frequency-Based Load Detection of Gasoline Particulate Filters

Walter

Schwanzer

Hagen

et al. 2020

Sensors

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“…A single friction factor correlation covering the laminar, transitional and turbulent regime proposed by Churchill 34 was recently applied to GPFs by Aleksandrova et al 35 A modified form is used here to account for the square shape of the channel…”

Section: Modellingmentioning

confidence: 99%

“…The pressure losses at the entrance of the inlet channel are particularly important due to the high flow rates encountered in the damaged channels. Textbook expressions for contraction have been used in published DPF models; 35–37 however, a special approach is necessary for the channel entrance to account for the phenomena observed in the SEM study. The channel entrance formula includes a typical turbulent flow contraction term and an additional term due to constrictions in the damaged channels only…”

Section: Modellingmentioning

confidence: 99%

Filtration efficiency and pressure drop modelling of particulate filters with rear plug damage

Haralampous

Μαστρόκαλος

Tzorbatzoglou

2020

International Journal of Engine Research

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A model suitable for wall-flow particulate filters with partial rear plug damage is developed and experimentally validated in this work. A ceramic filter with 16% of the rear plugs mechanically removed is tested at steady-state conditions on the engine bench and transient driving cycle conditions on the chassis dynamometer. After decanning of the monolith, destructive analysis is conducted to identify deposit loading variations and scanning electron microscopy is used to study the deposit structures in the channels. It is shown that channels without rear plugs develop distinct deposit structures in the entry zone. Hence, a local pressure loss coefficient is applied to model the effect of entrance flow constrictions, taking also into account deposit restructuring phenomena at higher flow rates. In addition, a deep-bed filtration submodel is used to capture the effect of non-uniform wall velocities on deposit accumulation in the wall. The modified model is first fitted to the engine bench data and then validated in a wider range of conditions using the driving cycle tests. With the exception of prolonged steady-state loading conditions, good pressure drop and filtration efficiency predictions are obtained throughout the tests in conjunction with correct deposit property profiles. Notably, the cold-start worldwide harmonized light vehicles test cycle shows that the current European on-board diagnosis threshold limit for particulate mass is too relaxed to trigger a malfunction indication for moderate filter faults. In conclusion, the model can be applied in damaged particulate filter studies for the assessment of leaked particulate mass, the specification of more effective legislation limits and the development of rigorous on-board diagnosis systems and algorithms.

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“…Experimental curve tting is the most common approach for permeability estimation. It involves tting a linear or quadratic curve to experimental pressure drop data from fullsize lters or cores to determine a suitable value for k, and, if included, the Forchheimer coe cient, β [5,6,17,18,19,20]. However, there is a potential here to under/overestimate the k values due to the di culty in isolating the through-wall losses from other contributions present when testing cores/ full-size lters (e.g., frictional losses along the channels, contraction/expansion losses).…”

Section: Introductionmentioning

confidence: 99%

“…It has been shown that the permeability increases by up to 30% at 450 o C compared to the cold ow. While this e ect is alluded to in some papers and models [6,17,19,20], its in uence is mostly neglected.…”

Section: Introductionmentioning

confidence: 99%

Wall Permeability Estimation in Automotive Particulate Filters

Samuels,

Holtzman,

Benjamin

et al. 2023

SAE Technical Paper Series

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<div class="section abstract"><div class="htmlview paragraph">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.</div><div class="htmlview paragraph">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.</div><div class="htmlview paragraph">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.</div></div>

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Turbulent Flow Pressure Losses in Gasoline Particulate Filters

Abstract: This document is the author's post-print version, incorporating any revisions agreed during the peer-review process. Some differences between the published version and this version may remain and you are advised to consult the published version if you wish to cite from it.

Cited by 6 publications

References 47 publications

Modelling the Influence of Different Soot Types on the Radio-Frequency-Based Load Detection of Gasoline Particulate Filters

Modelling the Influence of Different Soot Types on the Radio-Frequency-Based Load Detection of Gasoline Particulate Filters

Filtration efficiency and pressure drop modelling of particulate filters with rear plug damage

Wall Permeability Estimation in Automotive Particulate Filters

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