Modeling of Soot Deposition and Active Regeneration in Wall-flow DPF and Experimental Validation 2020-01-2180
Growing concerns about the emissions of internal combustion engines have forced the adoption of aftertreatment devices to reduce the adverse impact of diesel engines on health and environment.
Diesel particulate filters are considered as an effective means to reduce the particle emissions and comply with the regulations. Research activity in this field focuses on filter configuration, materials and aging, on understanding the variation of soot layer properties during time, on defining of the optimal strategy of DPF management for on-board control applications.
A model was implemented in order to simulate the filtration and regeneration processes of a wall-flow particulate filter, taking into account the emission characteristic of the engine, whose architecture and operating conditions deeply affect the size distribution of soot particles. The model is based on a lumped parameter approach able to be used for on-board monitoring and control, in order to provide knowledge of DPF status versus time.
The filtration model is based on the ‘unit collector’ and fluid dynamic approaches to predict trapped mass and filter backpressure evolution during time. The model accounts for the size distribution of soot particles in the engine exhaust and for its impact on the DPF properties during loading process. Regeneration model is based on a O2 non-catalytic oxidation approach of the trapped soot.
The model was applied to simulate the loading/regeneration processes of a wall-flow DPF under real engine operation condition. Experimental tests were carried out and measurements were used to validate the proposed model.
Citation: Chiavola, O., Chiatti, G., Cavallo, D., Mancaruso, E. et al., "Modeling of Soot Deposition and Active Regeneration in Wall-flow DPF and Experimental Validation," SAE Technical Paper 2020-01-2180, 2020, https://doi.org/10.4271/2020-01-2180. Download Citation
Ornella Chiavola, Giancarlo Chiatti, Domenico Mario Cavallo, Ezio Mancaruso, Bianca Maria Vaglieco
ROMA TRE University, Istituto Motori CNR