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Experimental and Numerical Analysis of a Pre-Chamber Turbulent Jet Ignition Combustion System
ISSN: 0148-7191, e-ISSN: 2688-3627
Published September 09, 2019 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Recent needs of reducing pollutant emissions of internal combustion engines have pushed the development of non-conventional ignition systems. One of the most promising techniques appears to be the so-called pre-chamber turbulent jet ignition combustion system in which a jet of hot combusting gases is employed to initiate the combustion in the main chamber. In the present study, the combustion process related to this ignition system has been experimentally investigated in an optically accessible single cylinder spark-ignition engine. The pre-chamber was composed of a gas injector and a spark-plug, embedded in a small annular chamber connected to the cylinder through a four-hole pipette. A small amount of methane is injected within the pre-chamber for initiating the combustion. The flame reaches the combustion chamber through four narrow orifices and rapidly consumes a homogeneous mixture of port injected methane and air. Wide open throttle condition at an engine speed of 2000 rpm was considered. The combustion process evolution and engine’s performance were analyzed in terms of 2D-digital imaging measurements as well as pressure and heat release rate traces. In order to provide a more detailed analysis of the phenomena, 3D numerical simulations were also performed, and the results were compared with the experimental ones. The proposed combustion system ensured a stable and faster combustion, as highlighted by the imaging of the flame evolution. Furthermore, higher peaks of pressure and heat release rate demonstrated a faster and more efficient combustion.
CitationDistaso, E., Amirante, R., Cassone, E., Catapano, F. et al., "Experimental and Numerical Analysis of a Pre-Chamber Turbulent Jet Ignition Combustion System," SAE Technical Paper 2019-24-0018, 2019, https://doi.org/10.4271/2019-24-0018.
Data Sets - Support Documents
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