CFD Modelling of Down-Sized GDI Engines: Fuel Injection, In-Cylinder Phenomena and Correlation to Engine-Out PN Emissions
type: CreativeWork
description: This PhD thesis aims to contribute improved knowledge and understanding of the particulate matter formation process in modern-design Gasoline Direct Injection engines. It does that through the development of a comprehensive 3D-CFD in-cylinder modelling tool that enables a robust and accurate insight into the pre-combustion mechanisms potentially leading to PM formation. The results presented refer to standard gasoline fuel, but remain fully relevant to synthetic hydrocarbons (efuels); the modelling approaches, on the other hand, are applicable to a wider range of modern and future fuels, including zero-carbon ones (particularly H2 and NH3). A 50-point engine testing matrix was designed and used as the basis to explore the impact of six relevant engine control variables on PN production. The randomised DoE approach enabled assessing a wide region of the typical passenger car operating envelope: engine load was varied between 20 and 140 Nm; engine speed in the range 2000 – 3500 rpm; injection pressure was varied between 60 and 250 bar; start of injection timing between 180 and 340 CAD BTCD; ignition timing was varied between 0 and 40 CAD BTDC, and finally intake valve opening timing in the range 0 – 40 CAD BTDCi. An extensive CFD modelling campaign was conducted based on this test matrix, and parallel experimental tests used to measure cylinder-out PN and to collect data as simulation input and for the purpose of calibrating and/or validating the models. The CFD model was developed targeting, wherever possible, ease of implementation and industrial utilisation, using approaches, sub-models and data that should be available to large corporations in the automotive sector. The whole model was developed using commercial CFD software Siemens Star-CD version 2021.1-436008. Fuel injection was modelled using a combination of initial Rosin-Rammler droplet size distribution and the Reitz-Diwaker secondary break-up model. An initial statistical variable screening methodology was…
abstract: This PhD thesis aims to contribute improved knowledge and understanding of the particulate matter formation process in modern-design Gasoline Direct Injection engines. It does that through the development of a comprehensive 3D-CFD in-cylinder modelling tool that enables a robust and accurate insight into the pre-combustion mechanisms potentially leading to PM formation. The results presented refer to standard gasoline fuel, but remain fully relevant to synthetic hydrocarbons (efuels); the modelling approaches, on the other hand, are applicable to a wider range of modern and future fuels, including zero-carbon ones (particularly H2 and NH3). A 50-point engine testing matrix was designed and used as the basis to explore the impact of six relevant engine control variables on PN production. The randomised DoE approach enabled assessing a wide region of the typical passenger car operating envelope: engine load was varied between 20 and 140 Nm; engine speed in the range 2000 – 3500 rpm; injection pressure was varied between 60 and 250 bar; start of injection timing between 180 and 340 CAD BTCD; ignition timing was varied between 0 and 40 CAD BTDC, and finally intake valve opening timing in the range 0 – 40 CAD BTDCi. An extensive CFD modelling campaign was conducted based on this test matrix, and parallel experimental tests used to measure cylinder-out PN and to collect data as simulation input and for the purpose of calibrating and/or validating the models. The CFD model was developed targeting, wherever possible, ease of implementation and industrial utilisation, using approaches, sub-models and data that should be available to large corporations in the automotive sector. The whole model was developed using commercial CFD software Siemens Star-CD version 2021.1-436008. Fuel injection was modelled using a combination of initial Rosin-Rammler droplet size distribution and the Reitz-Diwaker secondary break-up model. An initial statistical variable screening methodology was…
author: Hopkins, Edward
language: en
date modified: 2026-07-24T03:42:15Z
provider: Oxford Brookes University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Oxford Brookes University

PropertyValue
property ID: DOI
value: 10.24384/5a1b-9b39