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Influence of Blend Ratio and Injection Parameters on Combustion and Emissions Characteristics of Natural Gas-Diesel RCCI Engine
Technical Paper
2017-24-0083
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
RCCI strategy gained popularity in automotive applications due to lower fuel consumption, less emissions formation and higher engine performance in compared with other diesel combustion strategies. This study presents results of an experimental and numerical investigation on RCCI combustion using natural gas as a low reactivity premixed fuel with advanced injection of diesel fuel as a high reactivity fuel in a CI engine. An advanced three dimensional CFD simulation coupled with chemical kinetic developed to examine the effects of diesel injection timing, diesel/natural gas ratio and diesel fuel included spray angle on combustion and emissions formation in various engine loads and speeds, in a heavy duty diesel engine. The computational results of baseline operation was validated with experimental data achieved from a RCCI combustion process and reasonable agreement between calculated and measured mean in-cylinder pressure, rate of heat release and emissions such as NOx, CO and HC was obtained. The results showed that, amount and timing of direct injected diesel fuel is critical factor to control combustion phasing related to engine load and speed and also, increasing diesel fuel quantity leads to decrease HC and CO emissions. In other side, air fuel mixture quality has considerable effects on combustion process. For this reason, the effects of fuel spray angle on engine performance and amounts has been studied. It has been found that, diesel fuel targeting inside the combustion chamber has a simultaneous beneficial effects on emissions formation and engine performance due to more homogeneous air fuel mixture.
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Khatamnejad, H., Khalilarya, S., Jafarmadar, S., Mirsalim, M. et al., "Influence of Blend Ratio and Injection Parameters on Combustion and Emissions Characteristics of Natural Gas-Diesel RCCI Engine," SAE Technical Paper 2017-24-0083, 2017, https://doi.org/10.4271/2017-24-0083.Data Sets - Support Documents
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