Search Results

Following the successful market introduction of diesel particulate filters (DPFs), this class of emission control devices is expanding to include additional functionalities such as gas species oxidation (such as CO, HC and NO), storage phenomena (such as NOx and NH3 storage) to the extent that we should today refer not to DPFs but to Multifunctional Reactor Separators. This trend poses many challenges for the modeling of such systems since the complexity of the coupled reaction and transport phenomena makes any direct general numerical approach to require unacceptably high computing times. These multi-functionalities are urgently needed to be incorporated into system level emission control simulation tools in a robust and computationally efficient manner. In the present paper we discuss a new framework and its application for the computationally efficient implementation of such phenomena.

Despite the great effort devoted to the modeling of the operation of catalytic DPFs, even today very simple expressions are used for the soot oxidation rate. In the relevant to DPF operation case of a gas phase rich in oxygen, the structure of the soot-catalyst geometry and its evolution during oxidation determines the reaction rate. An extensive set of controlled experiments (isothermal or with linear temperature increase) using fuel borne catalysts and catalytic coatings has been performed in order to obtain corresponding soot oxidation rate-conversion curves. The shape of the resulting curves cannot be described by the typical theories for solid phase reactions posing the need for microstructural models for the micromechanics of soot catalyst interactions.

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).