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Future diesel emission control systems have to effectively operate under non-conventional low-temperature combustion engine operating conditions. In this work the research and development efforts for the realization of a Multi-Functional catalyst Reactor (MFR) for the exhaust of the upcoming diesel engines is presented. This work is based on recent advances in catalytic nano-structured materials synthesis and coating techniques. Different catalytic functionalities have been carefully distributed in the filter substrate microstructure for maximizing the direct and indirect (NO2-assisted) soot oxidation rate, the HC and CO conversion efficiency as well as the filtration efficiency. Moreover, a novel filter design has been applied to enable internal heat recovery capability by the implementation of heat exchange between the outlet and the inlet to the filter flow paths.

The DEXA Cluster consisted of three closely interlinked projects. In 2003 the DEXA Cluster concluded by demonstrating the successful development of critical technologies for Diesel exhaust particulate after-treatment, without adverse effects on NOx emissions and maintaining the fuel economy advantages of the Diesel engine well beyond the EURO IV (2000) emission standards horizon. In the present paper the most important results of the DEXA Cluster projects in the demonstration of advanced particulate control technologies, the development of a simulation toolkit for the design of diesel exhaust after-treatment systems and the development of novel particulate characterization methodologies, are presented. The motivation for the DEXA Cluster research was to increase the market competitiveness of diesel engine powertrains for passenger cars worldwide, and to accelerate the adoption of particulate control technology.

As demand for wall-flow Diesel Particulate Filters (DPF) increases, accurate predictions of DPF behavior, and in particular their pressure drop, under a wide range of operating conditions bears significant engineering applications. In this work, validation of a model and development of a simulator for predicting the pressure drop of clean and particulate-loaded DPFs are presented. The model, based on a previously developed theory, has been validated extensively in this work. The validation range includes utilizing a large matrix of wall-flow filters varying in their size, cell density and wall thickness, each positioned downstream of light or heavy duty Diesel engines; it also covers a wide range of engine operating conditions such as engine load, flow rate, flow temperature and filter soot loading conditions. The validated model was then incorporated into a DPF pressure drop simulator.

As use of Particulate Filters (PFs) is growing not only for diesel but also for gasoline powered vehicles, the need for better understanding of deposit structure, growth dynamics and evolution arises. In the present paper we address a number of deposit growth and restructuring phenomena within particulate filters with the aim to improve particulate filter soot load estimation. To this end we investigate the dynamic factors that quantify the amount of particles that are stored within the wall and the restructuring of soot deposits. We demonstrate that particle accumulation inside the porous wall is dynamically controlled by the dimensionless Peclet number and provide a procedure for the estimation of parameters of interest such as the loaded filter wall permeability, the wall-stored soot mass at the onset of cake filtration.

Improved understanding and compact descriptions of the pressure drop evolution of Particulate Filters (both for diesel and gasoline powered vehicles) are always in demand for intelligent implementations of exhaust emission system monitoring and control. In the present paper we revisit the loading process of a particulate filter focusing on a parametric description of the deep bed-to-cake transition in the light of recent progress in the understanding of soot deposit structure, growth dynamics and evolution. Combining experimental data, simulation models and information theoretic concepts we provide a closed-form representation of the entire evolution of pressure drop (from the initial clean state up to the evolving linear cake growth regime) parameterized in terms of the physical parameters of the system (filter and particle structure/geometry and flow properties).

The measurement of vehicle particle number emissions and, therefore, regulation, necessitates a rigorous sampling and conditioning technology able to deliver solid emitted particles with minimum particle losses. European legislation follows a solid particle number measurement method with cutoff size at 23 nm proposed by the Particle Measurement Programme (PMP). Accordingly, the raw exhaust is sampled with constant volume, subsequently passes through a volatile particle remover (VPR), and finally is measured with a particle counter. Lowering the 23 nm cutoff size with current VPR technologies introduces measurement uncertainties mainly due to the high particle losses and possible creation of artefacts. This study describes the development and evaluation of a sampling and conditioning particle system, the SCPS, specially designed for sub-23 nm solid particles measurement.

Diesel and gasoline direct injection engines emit nucleation mode particles either under special conditions or as part of their normally emitted size distribution, respectively. Currently, European legislation excludes nucleation mode particles as particle number vehicle emission measurements are limited down to 23 nm. The rationale behind such a cut-off size is based on the avoidance of significant uncertainties inherent in the sampling and measuring of sub-23 nm solid particles. However, the sub-23 nm particles have drawn increased attention since a large fraction of particles emitted by modern vehicles lies in this size range. In this study we investigate the possibility of accurate nucleation mode particles detection by using the Advanced Half Mini Differential Mobility Analyzer (HM-DMA).