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An Optical Characterization of Dual-Fuel Combustion in a Heavy-Duty Diesel Engine
Technical Paper
2018-01-0252
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Dual fuel (DF) combustion technology as a feasible approach controlling engine-out emissions facilitates the concept of fuel flexibility in diesel engines. The abundance of natural gas (90-95% methane) and its relatively low-price and the clean-burning characteristic has attracted the interest of engine manufacturers. Moreover, with the low C/H ratio and very low soot producing tendency of methane combined with high engine efficiency makes it a viable primary fuel for diesel engines. However, the fundamental knowledge on in-cylinder combustion phenomena still remains limited and needs to be studied for further advances in the research on DF technology. The objective of this study is to investigate the ignition delay with the effect of, 1) methane equivalence ratio, 2) intake air temperature and 3) pilot ratio on the diesel-methane DF-combustion. Combustion phenomenon was visualized in a single cylinder heavy-duty diesel engine modified for DF operations with an optical access. The high-speed natural luminosity (NL) imaging technique was employed to record the temporally resolved in-cylinder combustion event at an operating load of approx. 10 bar IMEP at 1400 rpm. The results show that flame propagation becomes stable and sustained with an increase in either of the methane equivalence ratio, intake air temperature, or diesel amount. However, the sensitivity of each effect on the flame propagation and ignition delay was observed to be different. The effect of these parameters on DF combustion has been characterized with the help of NL images and corresponding cylinder pressure and net heat-release rate (HRR) data. The study also presents a detailed discussion on the analyzed ignition delay trends.
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Ahmad, Z., Aryal, J., Ranta, O., Kaario, O. et al., "An Optical Characterization of Dual-Fuel Combustion in a Heavy-Duty Diesel Engine," SAE Technical Paper 2018-01-0252, 2018, https://doi.org/10.4271/2018-01-0252.Data Sets - Support Documents
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