Effects of fuel composition and engine operating conditions on particle number index in a direct injection spark ignition engine

The present research was conducted to propose an index for predicting particle number (PN) emissions from a direct injection spark ignition engine for various fuel compositions and injection strategies based on the demonstrated correlation between PN emissions and various parameters by using PN measurements and incylinder visualization. Experiments were conducted using a single-cylinder engine equipped with a direct injection system and visualization system. Three types of fuel were tested: indolene, indolene blended with 9.95% dodecane, and indolene blended with 9.2% divinylbenzene. The injection timing was varied from 330 degrees to 180 degrees CA BTDC during the intake process with injection pressures of 10, 20, and 35 MPa. The PN and particle size distributions were measured simultaneously using PPS-M and EEPS. Spray development and flame images were captured through a side quartz window placed on the upper side of the liner and a bottom quartz window installed in the center of the piston. When the dodecane blended fuel interacted with the piston, the presence of dodecane (with a higher viscosity and lower vapor pressure than indolene) increased the fuel mass adhered to the piston and deteriorated fuel film evaporation, thereby enlarging the diffusion flame and increasing PN emissions. Soot precursor molecules generated by the thermal dissociation of divinylbenzene, which contains multiple bonds, promoted the inception of particulate matter and particle growth, increasing the number of particles emitted and the average particle size for the divinylbenzene blend. A PN index was proposed as a function of the chemical structure, vapor pressure of the fuel components, and injection pressure. This index showed high predictability, with a correlation coefficient of 0.9354 for various fuel compositions and injection strategies.

Automated summary

The research proposed an index for predicting particle number (PN) emissions from a direct injection spark ignition engine for various fuel compositions and injection strategies based on the correlation between PN emissions and various parameters. Experiments were conducted using a single-cylinder engine with different fuel blends and injection timings, showing that dodecane blended fuel increased PN emissions due to its higher viscosity, while divinylbenzene blend promoted particle growth leading to increased particles emitted. The proposed PN index showed high predictability with a correlation coefficient of 0.9354.