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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).