Search Results

The objective of this research is a detailed investigation of multiple injections in a highly-dilute diesel low temperature combustion (LTC) regime. This research concentrates on understanding the performance and emissions benefits of multiple injections via experiments and simulations in a 0.48L signal cylinder light-duty engine operating at 2000 r/min and 5.5 bar IMEP. Controlled experiments in the single-cylinder engine are then combined with three computational tools, namely heat release analysis of measured cylinder pressure, a phenomenological spray model using in-cylinder thermodynamics [1], and KIVA-3V Chemkin CFD computations recently tested at LTC conditions [2]. This study examines the effects of fuel split distribution, injection event timing, rail pressure, and boost pressure which are each explored within a defined operation range in LTC.

The objective of this research is a detailed investigation of unburned hydrocarbon (UHC) in a highly-dilute diesel low temperature combustion (LTC) regime. This research concentrates on understanding the mechanisms that control the formation of UHC via experiments and simulations in a 0.48L signal-cylinder light duty engine operating at 2000 r/min and 5.5 bar IMEP with multiple injections. A multi-gas FTIR along with other gas and smoke emissions instruments are used to measure exhaust UHC species and other emissions. Controlled experiments in the single-cylinder engine are then combined with three computational tools, namely heat release analysis of measured cylinder pressure, analysis of spray trajectory with a phenomenological spray model using in-cylinder thermodynamics [1], and KIVA-3V Chemkin CFD computations recently tested at LTC conditions [2].

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 present study attempted to model experimental results obtained on an optical engine at the Sandia National Laboratory. Measurements of in-cylinder unburned hydrocarbon (UHC) distributions were provided using advanced optical diagnostics on a near production type piston. Previous multidimensional modeling provided accurate pressure profiles and heat release rate (HRR) predictions. However, the experimental UHC distribution was not matched, and the model predicted UHC extending from the bowl into the squish region in the expansion stroke. To explore the causes of this discrepancy a parametric study was performed using a variety of initial conditions, boundary conditions and model constants to explore their effects on the UHC distribution. Of the initial conditions, the swirl ratio was found to have the biggest impact on the UHC distribution.

High fidelity engine simulation requires realistic fuel models. Although typical automotive fuels consist of more than few hundreds of hydrocarbon species, researches show that the physical and chemical properties of the real fuels could be represented by appropriate surrogate fuel models. It is desirable to represent the fuel using the same set of physical and chemical surrogate components. However, when the reaction mechanisms for a certain physical surrogate component is not available, the chemistry of the unmatched physical component is described using that of a similar chemical surrogate component at the expense of accuracy. In order to reduce the prediction error while maintaining the computational efficiency, a method of on-the-fly reactivity adjustment (ReAd) of chemical reaction mechanism along with fuel re-distribution based on reactivity is presented and tested in this study.

In automotive industry it has been a challenge to retain diesel-like thermal efficiency while maintaining low emissions. Numerous studies have shown significant progress in achieving low emissions through the introduction of common-rail injection systems, multiple injections and exhaust gas recirculation and by using a high octane number fuel, like gasoline, to achieve adequate premixing. On the other hand, low temperature combustion strategies, like HCCI and PCCI, have also shown promising results in terms of reducing both NOx and soot emissions simultaneously. With the increasing capacity of computers, multi-dimensional CFD engine modeling enables a reasonably good prediction of combustion characteristics and pollutant emissions, which is the motivation behind the present research. The current research effort presents an optimization study of light-duty compression ignition engine performance, while meeting the emission regulation targets.