Large-eddy simulation study of combustion cyclic variation in a lean-burn spark ignition engine
Artikel i vetenskaplig tidskrift, 2019
Multi-cycle large-eddy simulation (LES) was performed to investigate combustion cyclic variability (CCV) in a single-cylinder spark ignition engine with a homogeneous lean ( =1.25) isooctane-air mixture. The aim was to obtain physical insights into the early stage of combustion and its influence on CCV. Propagation of the flame was modeled by a transport equation for the filtered flame surface density within the LES framework. The ignition process was represented by the imposed stretch spark ignition model (ISSIM-LES). Ten consecutive cold flow LES cycles followed by two initialization cycles (12 cycles in total) were used to perform the reactive simulations concurrently. The simulation results were compared with experimental data. Although the number of computed cycles was fairly low, the LES was able to reproduce the cyclic variability observed in experiments both quantitatively and qualitatively. Firstly, validation of the simulation was done by comparing measured pressure traces. Secondly, correlations between the timing of the 10% fuel burnt mass fraction with early flame kernel growth and initial-to-turbulent transition period (in which there was an asymmetric flame kernel that persisted through the early development periods) were determined. Thirdly, calculated results of the flame propagation were analyzed at two cross-sections (in swirl and tumble planes) of the combustion chamber, which highlighted differences in instantaneous flame structures and propagation characteristics between the fastest and slowest cycles. Good overall agreement was obtained between the measurements and simulation data. The results revealed that the instantaneous velocity and fluctuation of flows around the spark vicinity affect growth of the early flame kernel and cause combustion cyclic variability.
ignition modeling
Large-eddy simulation
lean combustion
flame surface denisity
Combustion Cyclic Variability