Abstract
As demand for wall-flow Diesel particulate filters (DPF) increases, accurate predictions of DPF behavior, and in particular of the accumulated soot mass, under a wide range of operating conditions become very important. In this work, the development of a model for predicting the accumulated soot mass in a DPF from a knowledge of its pressure drop is presented. Unique features of the model are the explicit consideration of Diesel particulate packing densities and particulate layer permeabilities, and their systematic dependence on filter operating conditions through discrete particle dynamics simulations. The model is based on first principles and is being validated with different filter materials and engine operating conditions. The formulation is easy to implement on-board for emission system control applications, e.g. for the determination of when to trigger a regeneration event, depending on the current value of the soot mass in the filter.