Flow-pattern switching in a motored spark ignition engine

Abstract

Cycle-to-cycle variability of intake-jet flow in an optical engine was measured using particle image velocimetry, revealing the possibility of two different flow patterns. A phase-dependent proper orthogonal decomposition analysis showed that one or the other flow pattern would appear in the average flow, sampled from test to test or sub-sampled within a single test; each data set contained individual cycles showing one flow pattern or the other. Three-dimensional velocity data from a large-eddy simulation of the engine showed that the particle image velocimetry plane cuts through a region of high shear between the intake jet and another large flow structure. Rotating the measurement plane 610°revealed one or the other flow structure observed in the particle image velocimetry measurements. Thus, it was hypothesized that cycle-to-cycle variations in the swirl ratio result in the two different flow patterns in the particle image velocimetry plane. Having an unambiguous metric to reveal large-scale flow cycle-to-cycle variability, causes for this variability were examined within the possible sources present in the available testing. In particular, variations in intake-port and cylinder pressure, lateral valve oscillations, and engine RPM were examined as potential causes for the cycle-to-cycle flow variations using the phase-dependent proper orthogonal decomposition coefficients. No direct correlation was seen between the intake-port pressure, or the pressure drop across the intake valve, and the in-cylinder flow pattern. A correlation was observed between dominant flow pattern and cycle-to-cycle variations in intake-valve horizontal position. RPM values and in-cylinder flow patterns did not correlate directly. However, a shift in flow pattern was observed between early and late cycles in a 2900-cycle test after an approximately 5 r/min engine speed perturbation.

TCC-III Engine Benchmark for Large-Eddy Simulation of IC Engine Flows

“…A1 of Appendix A) but a different intake system, exhaust system, and valve seat (two angles) compared to the TCC-0. The experimental results from the TCC-II configuration were useful for establishing the LES-toexperimental data-comparison protocols, to identify desired improvements in the hardware and operating procedures, and to assess the impact of engine and system imperfections on the in-cylinder flow [18][19][20]. Based on the TCC-II studies, new results are reported here from a third configuration, TCC-III, which has refurbished valve hardware and the intake/exhaust systems upgraded for fired testing.…”

“…Using randomized sub-samples is an important statistical check since it can be assumed that there might be some correlation in flows from one cycle to the next. In particular, due to slow drifts in the mean flow with time (shown in Fig.7d), caused by changes in swirl ratio [19], the variations are interdependent. The solid black lines show the estimated error in the mean that was determined as sample size divided by COV squared as proposed by [24] and indicate about the 80% confidence interval.…”

Cyclic dispersion in engine combustion—Introduction by the special issue editors

“…Abraham et al 6 extensively analyzed PIV measurements of cyclic variation in large-scale intake-jet flow patterns in a geometrically simple optical engine. Proper orthogonal decomposition (POD) 26 provided an objective metric to distinguish two distinctively different large-scale intake-jet flow patterns in the large PIV data sets.…”

“…Conventional spark-ignition (SI) 6,[9][10][11]14 and compression-ignition (CI) (diesel) engines; 7,12 Spray-guided stratified-charge engines; 4,5 Low-temperature combustion (LTC) engines, 8,9,12,13,15,16 including homogeneous charge compression ignition (HCCI) 8,9,15,16 and reactivitycontrolled compression ignition (RCCI). 12,13 In this introductory overview, we place these articles (which include three invited review papers 4,9,10 ) in the larger context of engine research and offer brief but (we hope) tantalizing summaries.…”

Correlation of CCV Between In-Cylinder Swirl Ratio and Polar Velocity Profile in Valve Seat Region Using LES Under Motored Engine Condition

“…LES captures Cycle-toCycle Variations (CCV) as opposed to cycle-averaged mean computations of RANS, and is therefore more accurate. A recent effort of GM's R&D and other organizations has been to understand and describe the nature of stochastic flows in internal combustion engines through concerted Particle Image Velocimetry (PIV) measurements and LES [2][3][4][5][6][7][8][9].…”