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Experimental Investigation of Fuel Impingement and Spray-Cooling on the Piston of a GDI Engine via Instantaneous Surface Temperature Measurements
ISSN: 1946-3936, e-ISSN: 1946-3944
Published April 01, 2014 by SAE International in United States
Citation: Köpple, F., Seboldt, D., Jochmann, P., Hettinger, A. et al., "Experimental Investigation of Fuel Impingement and Spray-Cooling on the Piston of a GDI Engine via Instantaneous Surface Temperature Measurements," SAE Int. J. Engines 7(3):1178-1194, 2014, https://doi.org/10.4271/2014-01-1447.
In order to comply with more and more stringent emission standards, like EU6 which will be mandatory starting in September 2014, GDI engines have to be further optimized particularly in regard of PN emissions. It is generally accepted that the deposition of liquid fuel wall films in the combustion chamber is a significant source of particulate formation in GDI engines. Particularly the wall surface temperature and the temperature drop due to the interaction with liquid fuel spray were identified as important parameters influencing the spray-wall interaction .
In order to quantify this temperature drop at combustion chamber surfaces, surface temperature measurements on the piston of a single-cylinder engine were conducted. Therefore, eight fast-response thermocouples were embedded 0.3 μm beneath the piston surface and the signals were transmitted from the moving piston to the data acquisition system via telemetry.
Extensive parameter variations were performed, in order to investigate the influence of e.g. the rail pressure, the engine load and the engine speed on the surface temperature of the piston. In particular the very slow increase of the piston surface temperature in comparison to the fast increase of the engine load could be determined as the main cause of the rise in particulate emissions during dynamic engine operation.
The shown studies can be used as a database from which, important measures to reduce particulate emissions can be derived. Additionally, the numerical simulation can be improved significantly based on the extensive measurement data, representing another important step towards the prediction of particulate emissions by numerical simulation.