A Study of the Regeneration Characteristics of Silicon Carbide and Cordierite Diesel Particulate Filters Using a Copper Fuel Additive

Gantawar, Ajay K.; Opris, Cornelius N.; Johnson, John H.

doi:10.4271/970187

Cited by 25 publications

(7 citation statements)

References 13 publications

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“…The cerium additive is thoroughly discussed by, among others, Summers et al [5] and Pattas et al [6]. The copper additive was discussed recently by Daly et al, [7], and Gantawar et al, [8].…”

mentioning

confidence: 95%

Cerium and Platinum Based Diesel Fuel Additives in the Diesel Soot Abatement Technology

Makkee¹,

Jelles²,

Moulijn³

2002

Catalysis by Ceria and Related Materials

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mentioning

confidence: 95%

Cerium and Platinum Based Diesel Fuel Additives in the Diesel Soot Abatement Technology

Makkee¹,

Jelles²,

Moulijn³

2002

Catalysis by Ceria and Related Materials

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“…Hence, a new pressure for the initial outlet pressure is calculated: Figure 2. Comparison between prior area conserved model that simulated only the cake layer and the deep bed filtration model presented in this effort along with experimental data [16].…”

Section: J Engines / Volume 8 Issue 3 (June 2015)mentioning

confidence: 99%

“…The volume of PM per pore involves the entire PM that is stored in the wall zone that is currently being analyzed, divided by the total number of pores (Np) in the wall at the current location: (15) (16) where the denominator is an equivalent pore volume and Veo is the empty volume of the wall at the location under analysis: (17) It is anticipated that Np is grossly overestimated as it assumes that all pores will be available for PM capture, which is untrue. This is remedied through ρ sw , the packing density of the PM particles in the filter structure.…”

Section: Pm Mass Equationsmentioning

confidence: 99%

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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“…In addition, Gantawar et al (1997) perform a study of regeneration characteristics for SiC and cordierite using fuel additives. Konstandopoulos and Kostoglou (1999) follow in 1999 with one of the first modeling efforts regarding a catalytically coated DPF and model deposit evolution using a local collection efficiency, ( )…”

Section: Particulate Combustionmentioning

confidence: 99%

Catalyzed diesel particulate filter modeling

Koltsakis

Haralampous

Depcik

et al. 2013

Reviews in Chemical Engineering

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An increasing environmental concern for diesel particulate emissions has led to the development of efficient and robust diesel particulate filters (DPF). Although the main function of a DPF is to filter solid particles, the beneficial effects of applying catalytic coatings in the filter walls have been recognized. The catalyzed DPF technology is a unique type of chemical reactor in which a multitude of physicochemical processes simultaneously take place, thus complicating the tasks of design and optimization. To this end, modeling has contributed considerably in reducing the development effort by offering a better understanding of the underlying phenomena and reducing the excessive experimental efforts associated with experimental testing. A comprehensive review of the evolution and the most recent developments in DPF modeling, covering phenomena such as transport, fluid mechanics, filtration, catalysis, and thermal stresses, is presented in this article. A thorough presentation on the mathematical model formulation is given based on literature references and the differences between modeling approaches are discussed. Selected examples of model application and validation versus the experimental data are presented.

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A Study of the Regeneration Characteristics of Silicon Carbide and Cordierite Diesel Particulate Filters Using a Copper Fuel Additive

Cited by 25 publications

References 13 publications

Cerium and Platinum Based Diesel Fuel Additives in the Diesel Soot Abatement Technology

Cerium and Platinum Based Diesel Fuel Additives in the Diesel Soot Abatement Technology

Combining the Classical and Lumped Diesel Particulate Filter Models

Catalyzed diesel particulate filter modeling

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