Numerical Investigation on the Cause-and-Effect Chain for Cycle-to-Cycle Variation of Direct-Injection Spark-Ignition Engine 2023-24-0035

Due to increasingly strict emission regulations, lean combustion concept has become an essential direction of internal combustion engine development to reduce engine emissions. However, lean combustion will lead high combustion instability and unpredictive engine emissions. The combustion instability is represented as the high cycle-to-cycle variation. Therefore, understanding the mechanism of cycle-to-cycle variation is crucial for the internal combustion engine design. This paper investigates the cause-and-effect chain of cycle-to-cycle variation of spark ignition engines using 3D CFD simulations with CONVERGE v3.0. The cyclic variations were simulated through Large Eddy Simulations, and the simulations based on Reynolds-averaged Navier–Stokes were used as supplements. The analysis focuses on two key factors that determine the combustion process: the turbulent intensity and the homogeneity of the air/fuel mixture. It is found that the turbulent intensity varies in combustion phase, and the reasons can be traced back to the tumble variation in the intake phase. The homogeneity of the air/fuel mixture will worsen with higher air-to-fuel equivalence ratio (lambda), which also leads to increased fluctuations in homogeneity. Furthermore, the correlation between homogeneity and tumble intensity enhances with higher lambda, e.g., the correlation coefficient increases from 0.13 to 0.67 as the lambda increases from 0.79 to 1.5. Additionally, the illustrated differences in the flame kernel development between cycles indicated that the local flow conditions play an essential role in the propagation of flame kernel. For example, as the flame kernel is trapped between the electrodes of the spark plug, higher local velocity will blow it across electrodes in a shorter time. Finally, despite the random variations in the flow conditions near the spark plug, an approach was developed to predict the range of local value variations based on the global values. It is significant for the further 0D/1D modeling of cycle-to-cycle variation.