Journal Article


Numerical investigation of particulate matter processes in gasoline direct injection engines through integrated computational fluid dynamics−chemical kinetic modeling

Abstract

Despite improvements in thermal efficiency and fuel economy, gasoline direct injection (GDI) engines have been identified as a prominent source of ultrafine particulate matter (PM) in the atmosphere. Adverse impacts caused by PM on the environment and public health motivate the need to deepen the understanding of PM emissions from GDI engines. Hence, an integrated modeling approach is formulated to investigate PM processes in a wall-guided GDI engine by bridging the gap between computational fluid dynamics (CFD) and chemical kinetics. Serving as the gasoline surrogate, a reduced and validated toluene reference mechanism is selected. Spray, turbulence, fuel impingement, liquid film, spark ignition, combustion, and PM emissions are modeled by a complete set of CFD submodels. The dynamic multizone partitioning is introduced within the CFD framework for computational expenditure while soot modeling is addressed through the sectional method. In-cylinder pressures, number density, and mass density of PM are reproduced across engine speeds of 1600–3000 rpm and loads with torques of 60–120 N m. Under a homogeneous stoichiometric mode, dominant formation mechanisms of PM are highlighted as the emergence of fuel-rich regions and the presence of residual liquid fuel droplets at the spark timing. The former is attributed to film stripping and evaporation due to spray-wall interactions while the latter stems from poor droplet vaporization from fuel injected, rebounded, splashed, and/or stripped from the liquid film. Optimized control strategies for GDI engine operations should target to minimize these sources for effective PM abatement.

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Authors

Yang Tan, Jing
Bonatesta, Fabrizio
Kiat Ng, Hoon
Gan, Suyin

Oxford Brookes departments

School of Engineering, Computing and Mathematics

Dates

Year of publication: 2020
Date of RADAR deposit: 2020-10-27


Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License


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This RADAR resource is the Accepted Manuscript of Numerical investigation of particulate matter processes in gasoline direct injection engines through integrated computational fluid dynamics−chemical kinetic modeling

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