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An investigation of high speed direct injection (DI) compression ignition (CI) engine combustion fueled with gasoline (termed GDICI for Gasoline Direct-Injection Compression Ignition) in the low temperature combustion (LTC) regime is presented. As an aid to plan engine experiments at full load (16 bar IMEP, 2500 rev/min), exploration of operating conditions was first performed numerically employing a multi-dimensional CFD code, KIVA-ERC-Chemkin, that features improved sub-models and the Chemkin library. The oxidation chemistry of the fuel was calculated using a reduced mechanism for primary reference fuel combustion. Operation ranges of a light-duty diesel engine operating with GDICI combustion with constraints of combustion efficiency, noise level (pressure rise rate) and emissions were identified as functions of injection timings, exhaust gas recirculation rate and the fuel split ratio of double-pulse injections.

Biodiesel-fueled engine simulations were performed using the KIVA3v-Release 2 code coupled with Chemkin-II for detailed chemistry. The model incorporates a reduced mechanism that was created from a methyl decanoate/methyl-9-decenoate mechanism developed at the Lawrence Livermore National Laboratory. A combination of Directed Relation Graph, chemical lumping, and limited reaction rate tuning was used to reduce the detailed mechanism from 3299 species and 10806 reactions to 77 species and 209 reactions. The mechanism was validated against its detailed counterpart and predicted accurate ignition delay times over a range of relevant operating conditions. The mechanism was then combined with the ERC PRF mechanism to include n-heptane as an additional fuel component. The biodiesel mechanism was applied in KIVA using a discrete multi-component model with accurate physical properties for the five common components of real biodiesel fuel.

Real transportation fuels, such as gasoline and diesel, are mixtures of thousands of different hydrocarbons. For multidimensional engine applications, numerical simulations of combustion of real fuels with all of the hydrocarbon species included exceeds present computational capabilities. Consequently, surrogate fuel models are normally utilized. A good surrogate fuel model should approximate the essential physical and chemical properties of the real fuel. In this work, we present a novel methodology for the formulation of surrogate fuel models based on local optimization and sensitivity analysis technologies. Within the proposed approach, several important fuel properties are considered. Under the physical properties, we focus on volatility, density, lower heating value (LHV), and viscosity, while the chemical properties relate to the chemical composition, hydrogen to carbon (H/C) ratio, and ignition behavior. An error tolerance is assigned to each property for convergence checking.

The objective of this study is to increase fundamental understanding of the effects of fuel composition and properties on low temperature combustion (LTC) and to identify major properties that could enable engine performance and emission improvements, especially under high load conditions. A series of experiments and computational simulations were conducted under LTC conditions using 67% EGR with 9.5% inlet O₂ concentration on a single-cylinder version of the General Motors Corporation 1.9L direct injection diesel engine. This research investigated the effects of Cetane number (CN), volatility and total aromatic content of diesel fuels on LTC operation. The values of CN, volatility, and total aromatic content studied were selected in a DOE (Design of Experiments) fashion with each variable having a base value as well as a lower and higher level. Timing sweeps were performed for all fuels at a lower load condition of 5.5 bar net IMEP at 2000 rpm using a single-pulse injection strategy.

The low temperature combustion concept is very attractive for reducing NOx and soot emissions in diesel engines. However, it has potential limitations due to higher combustion noise, CO and HC emissions. A multiple injection strategy is an effective way to reduce unburned emissions and noise in LTC. In this paper, the effect of multiple injection strategies was investigated to reduce combustion noise and unburned emissions in LTC conditions. A hybrid surrogate fuel model was developed and validated, and was used to improve LTC predictions. Triple injection strategies were considered to find the role of each pulse and then optimized. The split ratio of the 1st and 2nd pulses fuel was found to determine the ignition delay. Increasing mass of the 1st pulse reduced unburned emissions and an increase of the 3rd pulse fuel amount reduced noise. It is concluded that the pulse distribution can be used as a control factor for emissions and noise.

The light-medium load operating regime (4-8 bar net IMEP) presents many challenges for advanced low temperature combustion strategies (e.g. HCCI, PPC) in light-duty, high speed engines. In this operating regime, lean global equivalence ratios (Φ<0.4) present challenges with respect to autoignition of gasoline-like fuels. Considering this intake temperature sensitivity, the objective of this work was to investigate, both experimentally and computationally, gasoline compression ignition (GCI) combustion operating sensitivity to inlet swirl ratio (Rs) variations when using a single fuel (87-octane gasoline) in a 0.475-liter single-cylinder engine based on a production GM 1.9-liter high speed diesel engine. For the first part of this investigation, an experimental matrix was developed to determine how changing inlet swirl affected GCI operation at various fixed load and engine speed operating conditions (4 and 8 bar net IMEP; 1300 and 2000 RPM).