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The design of integrated exhaust lines that combine particulate and NOx emission control is a multidimensional optimization problem. The present paper demonstrates the use of an exhaust system simulation platform which is composed of well-established multidimensional mathematical models for the transient thermal and chemical phenomena in DOC, DPF and SCR systems as well as connecting pipe heat transfer effects. The analysis is focused on the European Driving Cycle conditions. Illustrative examples on complete driving cycle simulations with and without forced regeneration events are presented for alternative design approaches. The results illustrate the importance of DOC and DPF heat capacity effects and connecting pipe heat losses on the SCR performance. The possibility of combining DPF and SCR functionality on a single wall-flow substrate is studied.

This paper presents experimental and modeling results related to the application of a novel material as a diesel particulate filter substrate. The material, trademarked as INCOFOAM® HighTemp, is a Ni-based superalloy foam. The material can be produced in sheet form with a large range of microstructure parameters. Thanks to the mechanical properties of the sheets, they can be flexibly shaped in various forms. The foam can be washcoated with active catalytic material to promote regeneration. The experimental testing covers flow and pressure drop behavior with air and exhaust gas, filtration efficiency measurements as function of particle size and regeneration rate measurements. The testing starts from mini-scale reactors and proceeds to real exhaust testing on the engine bench as well as vehicle tests with legislated driving cycles. Special emphasis is given to the characterization of the foam as a catalyst substrate.

The objective of this study is to present a particulate filter concept, based on a new porous material: INCOFOAM® HighTemp, a Ni-based superalloy foam. The paper examines the filtration and pressure drop characteristics as well as the regeneration performance of different filter configurations, based on experimental data and modeling. A number of different foam structures with variable pore characteristics are studied. The experimental testing covers flow and pressure drop behavior with air and exhaust gas, filtration efficiency measurements as function of particle size and regeneration rate measurements. The testing starts from mini-scale reactors and proceeds to real exhaust testing on the engine bench as well as vehicle tests on the chassis dynamometer and on-road. In parallel, a previously developed mathematical model is applied to study and understand the filtration and pressure drop mechanisms in the case of clean and soot loaded filters.

This paper presents a mathematical model for the simulation of NOx traps during the storage and the regeneration phases. The objective is to validate the model under realistic exhaust gas conditions during NOx storage and release phases. The model is based on a previous modeling platform developed by Aristotle University which simulates the behavior of 3-way catalysts. The previous model is extended to include the additional reactions taking place on a NOx trap, with particular emphasis on the calculation of thermodynamic equilibrium effects. Moreover, the model includes the necessary reactions to simulate catalyst sulfation and de-sulfation processes. In parallel, a set of measurements are conducted under well controlled conditions with real diesel exhaust to study the storage and release phenomena under various operating conditions. The experimental data are used to calibrate the reaction kinetics and validate the model.

The objective of this paper is to study the parameters affecting the evolution of “uncontrolled” regeneration in diesel particulate filters with fuel-borne catalyst (FBC) support with emphasis on the development of thermal stresses critical for filter durability. The study is based on experiments performed on engine dynamometer, corresponding to “worst-case” scenario, as well as on advanced, multi-dimensional mathematical modeling. A new 2-dimensional mathematical model is presented which introduces an additional dimension across the soot layer and wall. With this dimension it is possible to take into account the variability of catalyst/soot ratio in the layer and to compute intra-layer composition gradients. The latter are important since they induce interesting O2 diffusion phenomena, which affect the regeneration evolution.

The objective of this study is to explain the physical and chemical mechanisms involved in the operation of a catalyzed diesel particulate filter. The study emphasizes on the coupling between reaction and diffusion phenomena (with emphasis on NO2 “back-diffusion”), based on modeling and experimental data obtained on the engine dynamometer. The study is facilitated by a novel multi-dimensional mathematical model able to predict both reaction and diffusion phenomena in the filter channels and through the soot layer and wall. The model is thus able to predict the species concentration gradients in the inlet/outlet channels, in the soot layer and wall, taking into account the effect of NO2 back diffusion. The model is validated versus engine dyno measurements. Two sets of measurements are employed corresponding to low-temperature “controlled” regenerations as well as high-temperature “uncontrolled” conditions.

Computer Aided Engineering (CAE) Methodologies are increasingly being applied to assist the design of SI-engine exhaust aftertreatment systems, in view of the stage III and IV emissions standards. Following this trend, the design of diesel exhaust aftertreatment systems is receiving more attention in view of the capabilities of recently developed mathematical models. The design of diesel exhaust systems must cope with three major aftertreatment categories: (i) diesel oxidation catalysts, (ii) diesel particulate filters and (iii) de-NOx catalytic converters. An integrated CAE methodology that could assist the design of all these classes of systems is described in this paper.

The design of a diesel particulate trap system to fit a specific vehicular application requires significant expenditure, due to the high degree of interaction between the vehicle operation and trap behavior. The assistance of modeling in the design process is already well established. This paper presents the basic principles of a Computer Aided Engineering methodology aimed to assist the selection of the basic parameters of a Diesel Particulate Trap System by reducing the number of the necessary experimental tests. The computational modules currently supporting the CAE methodology are based on fundamental mathematical models, incorporating a small number of semi-empirical relations derived by experimental data on trap loading and catalytic regeneration, exhaust system heat transfer and trap backpressure effect on fuel consumption.