A numerical investigation on the injection timing of boot injection rate-shapes in a kerosene-diesel engine with a clustered dynamic adaptive chemistry method

Dezhi Zhou, Kun Lin Tay, Yaojie Tu, Jing Li, Wenming Yang, Dan Zhao

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

In this study, we conducted a numerical investigation on the effect of injection timing of boot injection rate shape on the combustion and emission characteristics in a direct injection compression ignition (DICI) engine fueled with kerosene/diesel blending. Considering the complex surrogate in kerosene chemical mechanisms and the huge computational workload in multi-dimensional engine simulations, we employed a clustered dynamic adaptive chemistry method (CDAC) to accelerate the chemistry integration process. This study firstly specified the user-defined parameters in this CDAC method by sensitivity analysis in a HCCI and DICI engine with different user-defined parameter combinations. With these specified parameters, CDAC is then validated by comparing its predicted in-cylinder pressure with the full chemistry ones. It is found that the current CDAC method could reduce the computational time by more than 60% compared with the full chemistry CPU time. CDAC, subsequently, is used to conduct the numerical investigation on the injection timing of boot injection rate shapes. Four different boot injection rate shapes are simulated and compared with the normal rectangular injection. The effect injection timing of the boot injection rate on the engine performance and combustion/emission characteristic is then analyzed in detail. It is found that the change of start of injection (SOI) in boot injection has little influence of the ignition delay in the DICI engine fuelled with diesel and kerosene blending due to the high cetane number of diesel and better volatility of kerosene. In addition, with kerosene addition into the diesel combustion, it is observed that the CO emission could be reduced at all the varied SOI.

Original languageEnglish
Pages (from-to)117-126
Number of pages10
JournalApplied Energy
Volume220
DOIs
StatePublished - 15 Jun 2018

Keywords

  • Clustered dynamic adaptive chemistry
  • Diesel engine
  • Kerosene

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