Abstract

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 in-cylinder 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° to 180°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.

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