Prediction of Cyclic Variability and Knock-Limited Spark Advance in a Spark-Ignition Engine

Zongyu Yue, K. Dean Edwards, C. Scott Sluders, Sibendu Som

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Engine knock remains one of the major barriers to further improve the thermal efficiency of spark-ignition (SI) engines. SI engine is usually operated at knock-limited spark advance (KLSA) to achieve possibly maximum efficiency with given engine hardware and fuel properties. Co-optimization of fuels and engines is promising to improve engine efficiency, and predictive computational fluid dynamics (CFD) models can be used to facilitate this process. However, cyclic variability of SI engine demands that multicycle results are required to capture the extreme conditions. In addition, Mach Courant-Friedrichs-Lewy (CFL) number of 1 is desired to accurately predict the knock intensity (KI), resulting in unaffordable computational cost. In this study, a new approach to numerically predict KLSA using large Mach CFL of 50 with ten consecutive cycle simulation is proposed. This approach is validated against the experimental data for a boosted SI engine at multiple loads and spark timings with good agreements in terms of cylinder pressure, combustion phasing, and cyclic variation. Engine knock is predicted with early spark timing, indicated by significant pressure oscillation and end-gas heat release. Maximum amplitude of pressure oscillation analysis is performed to quantify the KI, and the slope change point in KI extrema is used to indicate the KLSA accurately. Using a smaller Mach CFL number of 5 also results in the same conclusions, thus demonstrating that this approach is insensitive to the Mach CFL number. The use of large Mach CFL number allows us to achieve fast turn-around time for multicycle engine CFD simulations.

Original languageEnglish
Article number102201
JournalJournal of Energy Resources Technology, Transactions of the ASME
Volume141
Issue number10
DOIs
StatePublished - Oct 1 2019

Funding

and Renewable Energy under Contract No. DE-AC02-06CH11357. The authors wish to thank Gurpreet Singh, Michael Weismiller, and Kevin Stork, program managers at DOE, for their support. This research was conducted as part of the Co-Optimization of Fuels & Engines (Co-Optima) project sponsored by the U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy (EERE), Bioenergy Technologies and Vehicle Technologies Offices.  UChicago Argonne, LLC, operator of Argonne National Laboratory (“Argonne”), a U.S. Department of Energy Office of Science laboratory, is operated under Contract No. DE-AC02-06CH11357. The U.S. Government retains for itself, and others acting on its behalf, a paid-up nonexclu-sive, irrevocable worldwide license in said article to reproduce, prepare derivative works, distribute copies to the public, and perform publicly and display publicly, by or on behalf of the Government. This research was partially funded by DOEs Office of Vehicle Technologies, Office of Energy Efficiency

Fingerprint

Dive into the research topics of 'Prediction of Cyclic Variability and Knock-Limited Spark Advance in a Spark-Ignition Engine'. Together they form a unique fingerprint.

Cite this