Influence of Fuel Injection Timing and Pressure on In-Flame Soot Particles in an Automotive-Size Diesel Engine

Abstract

The current understanding of soot particle morphology in diesel engines and their dependency on the fuel injection timing and pressure is limited to those sampled from the exhaust. In this study, a thermophoretic sampling and subsequent transmission electron microscope imaging were applied to the in-flame soot particles inside the cylinder of a working diesel engine for various fuel injection timings and pressures. The results show that the number count of soot particles per image decreases by more than 80% when the injection timing is retarded from −12 to −2 crank angle degrees after the top dead center. The late injection also results in over 90% reduction of the projection area of soot particles on the TEM image and the size of soot aggregates also become smaller. The primary particle size, however, is found to be insensitive to the variations in fuel injection timing. For injection pressure variations, both the size of primary particles and soot aggregates are found to decrease with increasing injection pressure, demonstrating the benefits of high injection velocity and momentum. Detailed analysis shows that the number count of soot particles per image increases with increasing injection pressure up to 130 MPa, primarily due to the increased small particle aggregates that are less than 40 nm in the radius of gyration. The fractal dimension shows an overall decrease with the increasing injection pressure. However, there is a case that the fractal dimension shows an unexpected increase between 100 and 130 MPa injection pressure. It is because the small aggregates with more compact and agglomerated structures outnumber the large aggregates with more stretched chain-like structures.

Sensitivity Analysis of Key Parameters for Population Balance Based Soot Model for Low-Speed Diffusion Flames

“…The fractal dimension of a fractal object could be quantified based on the morphological information that was obtained experimentally by examining the TEM image and is derived by least-square regression fittings to the power law relationship [55,56]:…”

External irradiation effect on the growth and evolution of in-flame soot species

“…It is noted that the fine background structure of the carbon film permits good background contrast to be produced and is therefore typically used for high-resolution diagnostics. The sampling grid, along with the deposited particulates, are then placed underneath a transmission electron microscope (TEM), whereby energised electrons from the microscope are used to interact with the particulate [71,72]. The electrons, which have transmitted through the particulates and grid, are subsequently directed and focused onto a photo-sensor to form an image, which can be used for morphology analysis.…”

“…The slopes of the least-square linear fits of ( ) and ( / ) were subsequently used to yield the values. Only aggregates with more than three primaries are considered for fractal analysis, as aggregates with less than three primary particles (e.g., monomers and dimers) do not have fractal structures [71].…”

“…in Equation 3 refers to the average projection area of the primary particles within the aggregate. The values of the empirical constant ( ) and exponent ( ) of the equation are taken as 1 and 1.09, respectively, as proposed by Megaridis and Dobbins[58], given that the soot particles are observed to have low overlapping mechanisms[71] in the TEM images(Figure 4.6). A summary of the , and values obtained at different heights above burner for the NI-flame and I-flame is provided inTable 4-1.…”

Evaluation of a Lagrangian Soot Tracking Method for the prediction of primary soot particle size under engine-like conditions

“…Such information is expected to provide a better understanding of the formation, growth and oxidation of soot particles since the morphology of soot is shown to be dependent on fuel type or composition (Aizawa, Takahata, Okabe, & Mizutani, 2015;Merchan-Merchan, Sanmiguel, & McCollam, 2012;Savic et al, 2016;J. Song & Lee, 2007) and operating conditions (Hadavi et al, 2012;Kuribayashi, Mizutani, Ishizuka, Taki, & Aizawa, 2014;Lapuerta, Ballesteros, & Martos, 2009;Lu, Cheung, & Huang, 2012;Vishwanathan & Reitz, 2015;R. Zhang & Kook, 2014;Zhu, Lee, Yozgatligil, & Choi, 2005).…”