A detailed understanding of Gasoline Direct Injection (GDI) techniques applied to spark-ignition (SI) engines is necessary as they allow for many technical advantages such as increased power output, higher fuel efficiency and better cold start performances. Within this context, the extensive validation of multi-dimensional models against experimental data is a fundamental task in order to achieve an accurate reproduction of the physical phenomena characterizing the injected fuel spray. In this work, simulations of different Engine Combustion Network (ECN) Spray G conditions were performed with the Lib-ICE code, which is based on the open source OpenFOAM technology, by using a RANS Eulerian-Lagrangian approach to model the ambient gas-fuel spray interaction. Foremost, the main scope of the activity was to identify the most accurate numerical set-up in terms of atomization ad secondary break-up models, thanks to a validation of the computed results against experimental data available for the ECN Spray G baseline condition. Specifically, attention was focused on spray penetration along with an analysis of spray morphology and effects of plume-to-plume interaction. Afterwards, the reference set-up was tested and validated under different operating conditions, characterized by detailed experimental measurements specifically provided for this work. In particular, Mie scattering and Schlieren techniques allowed the quasi-simultaneous acquisition of both vapor and liquid penetrations, while a customized image-processing procedure, developed in Matlab environment, was used for the outline of the spray contours of both fuel phases to measure the parameters characterizing the jet development. A robust reference numerical set-up was identified, capable to reproduce with good accuracy the injection process of a multi-hole GDI spray under the wide range of tested operating conditions.

Combined Experimental and Numerical Investigation of the ECN Spray G under Different Engine-Like Conditions

Paredi, Davide;Lucchini, Tommaso;D'Errico, Gianluca;Onorati, Angelo;
2018-01-01

Abstract

A detailed understanding of Gasoline Direct Injection (GDI) techniques applied to spark-ignition (SI) engines is necessary as they allow for many technical advantages such as increased power output, higher fuel efficiency and better cold start performances. Within this context, the extensive validation of multi-dimensional models against experimental data is a fundamental task in order to achieve an accurate reproduction of the physical phenomena characterizing the injected fuel spray. In this work, simulations of different Engine Combustion Network (ECN) Spray G conditions were performed with the Lib-ICE code, which is based on the open source OpenFOAM technology, by using a RANS Eulerian-Lagrangian approach to model the ambient gas-fuel spray interaction. Foremost, the main scope of the activity was to identify the most accurate numerical set-up in terms of atomization ad secondary break-up models, thanks to a validation of the computed results against experimental data available for the ECN Spray G baseline condition. Specifically, attention was focused on spray penetration along with an analysis of spray morphology and effects of plume-to-plume interaction. Afterwards, the reference set-up was tested and validated under different operating conditions, characterized by detailed experimental measurements specifically provided for this work. In particular, Mie scattering and Schlieren techniques allowed the quasi-simultaneous acquisition of both vapor and liquid penetrations, while a customized image-processing procedure, developed in Matlab environment, was used for the outline of the spray contours of both fuel phases to measure the parameters characterizing the jet development. A robust reference numerical set-up was identified, capable to reproduce with good accuracy the injection process of a multi-hole GDI spray under the wide range of tested operating conditions.
2018
SAE Technical Paper
Automotive Engineering; Safety, Risk, Reliability and Quality; Pollution; Industrial and Manufacturing Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1081819
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