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Study of Flash Boiling Spray Combustion in a Spark Ignition Direct Injection Optical Engine Using Digital Image Processing Diagnostics
Technical Paper
2019-01-0252
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Flash boiling spray has been proven to be a useful method in providing finer fuel droplet and stronger evaporation in favor of creating a homogeneous fuel-air mixture. Combustion characteristics of flash boiling spray are thus valuable to be investigated systematically for aiding the development of efficient internal combustion system. An experimental study of flash boiling spray combustion in a SIDI optical engine under early injection has been conducted. The fuel, Iso-octane, was used across all tests. Three fuel spray conditions experimented in the study: normal liquid, transitional flash boiling and flare flash boiling sprays, within each case that Pa/Ps ratio was set in (>1), (0.3~1), and (<0.3) respectively. A small quartz insert on the piston enables optical access for observing combustion process; non-intrusive measurements on flame radicals has been carried out using a high-speed color camera. With the use of digital image processing and color analysis, the imaging system was turned into an abstract multi-spectral system to determine the characteristics of flame emission. In addition, the near infrared region was capable of being discriminated from the rest regions of the flame using HSV color model. The near infrared flame area and diffusion flame region as well as pool fire were found to be reduced, when implementing flash boiling spray under early injection condition. It is found that flash boiling spray contributes the reduction of particulate number (PN) emissions in exhaust gas and makes the improvement of indicated mean effective pressure (IMEP) and cyclic variation, which lead to more efficient combustion in SIDI engine under early injection.
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Sun, Z., Ma, Z., Li, X., and Xu, M., "Study of Flash Boiling Spray Combustion in a Spark Ignition Direct Injection Optical Engine Using Digital Image Processing Diagnostics," SAE Technical Paper 2019-01-0252, 2019, https://doi.org/10.4271/2019-01-0252.Data Sets - Support Documents
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