A phenomenological model for particle number and size distributions of a diesel engine with a diesel oxidation catalyst

Abstract

Particle number is a key index for evaluating particulate emissions, and diesel oxidation catalysts (DOCs) are one of the most important technologies for controlling the particulate emissions of a diesel engine. In this paper, a novel phenomenological one-dimensional model was established to predict particle number and size distributions at a DOC outlet with the aim of investigating the effects of DOC on particle number emissions. The phenomenological model consisted of two submodels: submodel-1, a global kinetic model for calculating particle size in particle number and size distributions after particles had passed through the DOC, and submodel-2, an original global parametric model for calculating the particle number at the DOC outlet. The effects of the sampling process, fuel properties, and the engine operating condition were considered in submodel-2. An 8.8 L, direct-injection, heavy-duty diesel engine was tested. The particle number and size distributions at the DOC inlet and outlet were determined using an engine exhaust particle sizer. The test data, coupled with literature results, were used to calibrate and validate the phenomenological model. This model was then applied to investigate the influence of various factors on particle number and size distributions at the DOC outlet. It was found that dilution temperature, fuel sulfur content, exhaust gas temperature, and gas hourly space velocity (GHSV) played a key role in the particle number after DOC oxidation. The particle number concentration at the DOC outlet increased as fuel sulfur content and exhaust gas temperature increased and decreased as GHSV and dilution temperature increased. In general, results proved that this phenomenological model was accurate enough to predict particle number and size distributions at a DOC outlet under most operating conditions. It may serve as a useful tool for research and development focusing on PM reduction of diesel engines and air pollution control.