Prediction of Ultra-Lean Spark Ignition Engine Performances by Quasi-Dimensional Combustion Model with a Refined Laminar Flame Speed Correlation

Ratnak Sok*, Kyohei Yamaguchi, Jin Kusaka

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)

Abstract

The turbulent combustion in gasoline engines is highly dependent on laminar flame speed SL. A major issue of the quasi-dimensional (QD) combustion model is an accurate prediction of the SL, which is unstable under low engine speeds and ultra-lean mixture. This work investigates the applicability of the combustion model with a refined SL correlation for evaluating the combustion characteristics of a high-tumble port gasoline engine operated under ultra-lean mixtures. The SL correlation is modified and validated for a five-component gasoline surrogate. Predicted SL values from the conventional and refined functions are compared with measurements taken from a constant-volume chamber under micro-gravity conditions. The SL data are measured at reference and elevated conditions. The results show that the conventional SL overpredicts the flame speeds under all conditions. Moreover, the conventional model predicts negative SL at equivalence ratio φ ≤ 0.3 and φ ≥ 1.9, while the revised SL is well validated against the measurements. The improved SL correlation is incorporated into the QD combustion model by a user-defined function. The engine data are measured at 1000-2000 rpm under engine load net indicated mean effective pressure (IMEPn) = 0.4-0.8 MPa and φ = 0.5. The predicted engine performances and combustions are well validated with the measured data, and the model sensitivity analysis also shows a good agreement with the engine experiments under cycle-by-cycle variations.

Original languageEnglish
Article number032306
JournalJournal of Energy Resources Technology, Transactions of the ASME
Volume143
Issue number3
DOIs
Publication statusPublished - 2021 Mar 1

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • Fuel Technology
  • Energy Engineering and Power Technology
  • Mechanical Engineering
  • Geochemistry and Petrology

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