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Resolving the Combustion Zones of Bio-hybrid Fuels in Reactivity Controlled Compression Ignition Combustion Using Tracer-Activated Luminescence Imaging

Journal Article
04-16-01-0004
ISSN: 1946-3952, e-ISSN: 1946-3960
Published October 17, 2022 by SAE International in United States
Resolving the Combustion Zones of Bio-hybrid Fuels in Reactivity
                    Controlled Compression Ignition Combustion Using Tracer-Activated Luminescence
                    Imaging
Sector:
Citation: Dewor, R., Fleischmann, M., Brands, T., Pischinger, S. et al., "Resolving the Combustion Zones of Bio-hybrid Fuels in Reactivity Controlled Compression Ignition Combustion Using Tracer-Activated Luminescence Imaging," SAE Int. J. Fuels Lubr. 16(1):37-48, 2023, https://doi.org/10.4271/04-16-01-0004.
Language: English

Abstract:

A major reduction of greenhouse gas emissions, as well as other toxic emissions, is required to reduce the environmental impact of transportation systems. Renewable fuels, in combination with new internal combustion processes, such as reactivity controlled compression ignition (RCCI), are promising measures to enable this reduction. By combining two fuels with different reactivity, RCCI offers high efficiency and low emissions through homogeneous low-temperature combustion. However, a two-fuel RCCI approach leads to an increased number of adjustable operation parameters, such as injection timing. Optimizing these operation parameters to ensure homogenous combustion is challenging. To that end, optical methods provide temporally and spatially resolved information on mixture formation and combustion to analyze the homogeneity of the process. However, established methods, such as OH* imaging, cannot differentiate between multiple fuels. Therefore, we propose the usage of sodium as a tracer that is added to one of the fuels. Based on this approach, we present a combination of one-dimensional (1D) and two-dimensional (2D) luminescence imaging to investigate two-fuel RCCI combustion in a high-pressure vessel. The method allows for an accelerated optimization of injection parameters by visually accessing the homogeneity of combustion processes. The optimized parameters can then be transferred and further tested in engine applications.