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Technical Paper

Combustion Process Investigation in a DISI Engine Fuelled with n-butanol Through Digital Imaging and Chemiluminescence

2015-09-01
2015-01-1887
Direct-injection spark-ignition (DISI) engines have been adopted increasingly by the automotive industry in recent years due to their performance, reduced impact on the environment, and customer demand for advanced technology. However, detailed combustion processes in such engines are still not thoroughly analysed and understood. This work reports on the effects of different control parameters on the combustion process, such as fuel type, ignition timing and exhaust gas recirculation. Pure n-butanol and gasoline were used. All experiments were performed at 2000 rpm and 100 bar injection pressure in a transparent single-cylinder DISI engine equipped with the head of a commercial turbocharged engine with similar geometrical specifications (bore, stroke, compression ratio). Crank angle resolved 2D chemiluminescence in the UV range for OH radical and CO2 detection was performed with an ICCD camera and a high-speed CMOS camera was used for cycle resolved imaging.
Technical Paper

Development of a Sectional Soot Model Based Methodology for the Prediction of Soot Engine-Out Emissions in GDI Units

2020-04-14
2020-01-0239
With the aim of identifying technical solutions to lower the particulate matter emissions, the engine research community made a consistent effort to investigate the root causes leading to soot formation. Nowadays, the computational power increase allows the use of advanced soot emissions models in 3D-CFD turbulent reacting flows simulations. However, the adaptation of soot models originally developed for Diesel applications to gasoline direct injection engines is still an ongoing process. A limited number of studies in literature attempted to model soot produced by gasoline direct injection engines, obtaining a qualitative agreement with the experiments. To the authors’ best knowledge, none of the previous studies provided a methodology to quantitatively match particulate matter, particulate number and particle size distribution function measured at the exhaust without a case-by-case soot model tuning.
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