Microstructural Properties of Soot Deposits in Diesel Particulate Traps

Konstandopoulos, Athanasios G.; Skaperdas, Evangelos; Masoudi, Mansour

doi:10.4271/2002-01-1015

Cited by 142 publications

(106 citation statements)

References 11 publications

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“…In our last several papers [7][8][9][10][11], we have simulated the soot trap and regeneration of the filter. Due to the computational costs, it must be impractical to consider the real geometry of the diesel soot, because it is carbonaceous agglomerates with several-micrometer primary soot [3,27,28]. For an alternative approach, our model only describes the soot mass fraction in the gas phase, by which the growth of the deposited soot layer is numerically reproduced.…”

Section: Soot Deposition Modelmentioning

confidence: 99%

Effect of Pore Structure on Soot Deposition in Diesel Particulate Filter

Yamamoto

Sakai

2016

Computation

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Nowadays, in the after-treatment of diesel exhaust gas, a diesel particulate filter (DPF) has been used to trap nano-particles of the diesel soot. However, as there are more particles inside the filter, the pressure which corresponds to the filter backpressure increases, which worsens the fuel consumption rate, together with the abatement of the available torque. Thus, a filter with lower backpressure would be needed. To achieve this, it is necessary to utilize the information on the phenomena including both the soot transport and its removal inside the DPF, and optimize the filter substrate structure. In this paper, to obtain useful information for optimization of the filter structure, we tested seven filters with different porosities and pore sizes. The porosity and pore size were changed systematically. To consider the soot filtration, the particle-laden flow was simulated by a lattice Boltzmann method (LBM). Then, the flow field and the pressure change were discussed during the filtration process.

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Section: Soot Deposition Modelmentioning

confidence: 99%

Effect of Pore Structure on Soot Deposition in Diesel Particulate Filter

Yamamoto

Sakai

2016

Computation

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“…Of note, for the temperature exiting the DPF, this is the same boundary condition utilized in the previous effort. Now, from this information, the temperature derivative between the boundaries can be specified as: (8) This will act as a constant within the ODE solver for the channel equations, effectively removing the need to employ the conservation of energy in the solver. In other words, the lumped model will provide the temperature profile through the DPF and the channel equations will simply employ this result.…”

Section: Filter and Gas Energy Equationsmentioning

confidence: 99%

“…This has been expanded here based on the unit collector model pioneered by Konstandopoulos and Johnson [6] and later updated by Konstandopoulos et al [7,8,9,10]. This effort slightly modifies this model for inclusion in the lumped zone approach.…”

Section: Pm Mass Equationsmentioning

confidence: 99%

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Combining the Classical and Lumped Diesel Particulate Filter Models

Depcik¹

2015

SAE Int. J. Engines

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The control of PM that emanates from SIDI and CI engines is of significant concern for the automotive industry. This is because PM can infiltrate the alveoli in humans and transport toxic chemicals absorbed on the surface of the particle, subsequently leading to lung related illnesses [1]. As a result, the automotive industry now widely implements PM filtration in the exhaust. In particular, DPFs are used for CI engine exhaust with GPFs currently being considered for SIDI engines.The operation of a DPF (or analogous GPF) includes the storage of PM in and on top of a porous wall with its eventual regeneration in an oxidative environment. This can be accomplished actively utilizing O 2 or passively by employing NO 2 ; often through synchronization with an upstream Oxidation Catalyst. This need to modulate device operation has led to the development of simulation tools in order to reduce the number of experiments needed by predicting the pressure drop through the device and its temperature evolution. Broadly speaking, the models typically fall into one of two categories; those designated to operate within an Engine Control Unit (ECU) [2] and the classical two-channel approach [3].The ECU approach is designed for computational speed and is still often based on the two-channel model originally posed by Bissett [4]. In a previous effort by the author, the research in this area was reviewed and a derived model was generated that used dynamically incompressible flow to simulate the flow through the device while creating lumped zones in order to predict the temperature evolution. Utilizing a high-level coding language that runs significantly slower than traditional programming languages [5], the filter temperature evolution could be predicted relatively accurately in a faster than real time manner. This was because only one term in the governing energy equations was influenced by compressible flow. However, decoupling temperature and pressure by using dynamically incompressible flow (effectively negating the ideal gas law), the model was unable to simulate the pressure drop during warm-up and PM regeneration experiments.As a result, this effort seeks to merge the two models by simulating temperature using the ECU approach while estimating the pressure drop using the two-channel methodology. In specific, the temperature profile through the device is generated by the ECU version that is then utilized as a constant within the two-channel model removing the need to solve for the channel temperatures. Moreover, deep bed filtration is included in the model formulation in order to simulate the pressure drop evolution in the device more accurately. Finally, model run times are given in order to document the computational expense of the combined model. DPF MODEL DERIVATIONIn a previous effort, instead of simulating both the inlet and outlet channels along with a porous wall, model derivation followed a lumped approach through the creation of a variable number of zones Combining the Classical and Lumped Diesel Particulate Filter M...

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“…Their model was based on Kuwabara, Lee and Gieseke [9,10]. The model was later modified and outlined in Konstandopoulos [5,11]. Currently it has been used in most of DPF simulation software packages.…”

Section: Introductionmentioning

confidence: 99%

Sensitivities Of Diesel Particulate Filter Clean And Loading Models

Thiengkaew

Khongsup

Wirojsakunchai

2015

MATEC Web of Conferences

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ABSTRACT.A comparison of two mathematical models from two cycle simulation software packages predicting a cold flow and filtration process of a Diesel Particulate Filter (DPF) is studied extensively. Three Cordierite Diesel Particulate Filters (DPF) models, with variations in washcoats (bare, washcoat-only, and catalyzed washcoat), are built and validated to experimental data. The goal is to estimate the values of wall permeability ( ) and friction loss coefficient ( ) from the flow bench test and the values of soot permeability ( ) from the filtration process. Good agreements are found comparing between experimental data and simulation. The values of those parameters obtained from each software packages show the same trend among all tested DPF samples. However, they are different when comparing cases by cases because of the methodology lies in each mathematical model.

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Microstructural Properties of Soot Deposits in Diesel Particulate Traps

Cited by 142 publications

References 11 publications

Effect of Pore Structure on Soot Deposition in Diesel Particulate Filter

Effect of Pore Structure on Soot Deposition in Diesel Particulate Filter

Combining the Classical and Lumped Diesel Particulate Filter Models

Sensitivities Of Diesel Particulate Filter Clean And Loading Models

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