Numerical Simulation Of The Effects Of Different Inject Strategies On The Soot Process In A Diesel Engine

The damage of the soot produced in the cylinder lies on two aspects:the first one is that the soot will exhaust into the atmosphere as PM leading to the air population, and the second one is that the soot may entertainment into the engine oil which results in oil starvation and piston damages. The stricter emission regulation makes the research about the detailed soot formulation and oxidation progress become more important.The major work of the paper is research about the effects of the five different injection strategies on the soot formation and oxidation progress in a light load diesel engine using CONVERGE software. The simulation utilizes the SAGE combustion model which adopts a kinetic mechanism including the polycyclic aromatic hydrocarbon （PAH） mechanism which consists of the 100 species and 432 reactions. The soot model is the Method of Moments and the soot precursor is pyrene （A4）. The five injection strategies are the Inject_Base, Inject_AtLater, Inject₄Times, Inject₂Times and Inject₂TimesAtEarly. The Inject_Base is the baseline case.The Inject_AtLater is the late injection. In the Inject₄Times the main injection will split into four times. In the Inject₂Times the main inject will split into two times, and in the second injection the injection nozzle’s Z coordinate will change from -0.002165 mm to -0.001165 mm and spray cone angle will change from 152 degree to 140 degree. There are also two injections in the Inject₂TimesAtEarly case, and the first injection occurs at -23 CA and the second one occurs at about 0 CA.The soot formulation and oxidation progress is analyzed in four aspects:the soot 1D result analysis, the soot 2D result analysis, the soot 3D result analysis and correlation analysis of the soot related variables.The major difference from the other researches is that the simulation is conducted in the way of the Object-Oriented concept. The paper will create three classes using Python, the PyQt and Pandas libraries:ExpObject, SootObject and ModelDieselSootFormationObject. In this way the management and reconstruction of the data will be convenient and efficient. The simulation results show that:1) Comparison between the experimental and simulated pressure trace shows that the prediction is well. The difference of the peak pressure is 0.01 MPa, which shows the current model could be used in the qualitative prediction.2) There is a compromise between the performance and emission in the five injection strategies. The Inject_Base strategy has the highest IMEP and the lowest exhausted soot emission. The Inject₄Times strategy has the lowest rate of pressure rise. The Inject_AtLater strategy has the lowest exhausted NOx emission.3) In the map of temperature and equivalence ratio, the cells which have the high A4 and C2H2 massfraction both lie in the relative low temperature （< 2000K） and high equivalence ratio region（>1.5）. The highest C2H2 massfraction’s cells are in the highest equivalence ratio region however the highest A4 massfraction’s cells are in the intermediate high equivalence ratio region. On the other hand the high OH massfraction’s cells lie in the relative high temperature （> 2000K） and low equivalence ratio region （< 1）.4) Because of the different injection time and the corresponding in-cylinder flow conditions, the five different injection strategies produce the different temperature and equivalence ratio distribution, which leads to the different A4, C2H2 and soot distribution. The soot and the A4 distribution are similar, and in the contour of the equivalence ratio, temperature, A4 and OH, the intermediate high temperature and high equivalence ratio region produces the high A4, C2H2 and soot.Outside this region is the highest temperature region which is also the high OH massfraction region. This region is the indication of diffusive flame position.5) The soot related variables include the Hiroy_soot, the PM_soot, the A4, the C2H2 and the equiv ratio bin （the fraction of the total mass which has a equivalence ratio within the specified range of the bin）. The bins are 1.0-1.1、 1.1-1.2、1.2-1.3、1.3-1.4、1.4-1.5、1.5-1.6、1.6-1.7、1.7-1.8、1.8-1.9、 1.9-2.0. The correlation analysis focuses on two groups. The first group consists of the Hiroy_soot and the equiv ratio bin, the PM_soot and the equiv ratio bin, the A4 and the equiv ratio bin, and the C2H2 and the equiv ratio bin. The second group consists of the whole 6 pairs of the Hiroy_soot, the PM_soot, the A4 and the C2H2. In the first group the correlation increases with the increasing of the equiv ratio bin and the peak correlativity occurs at the 1.9-2.0 bin. Besides this, the correlativity of the A4 and the equiv ratio bin, and the correlativity of the the C2H2 and the equiv ratio bin both have a rapid increase at 1.9-2.0 bin. In the second group, the correlativity of the Hiroy_soot and the PM_soot, and the correlativity of the A4 and the C2H2 are bigger than other pairs.