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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.

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.

Computational fluid dynamics of gas-fueled large-bore spark ignition engines with pre-chamber ignition can speed up the design process of these engines provided that 1) the reliability of the results is not affected by poor meshing and 2) the time cost of the meshing process does not negatively compensate for the advantages of running a computer simulation. In this work a flame propagation model that runs with arbitrary hybrid meshes was developed and coupled with the KIVA4-MHI CFD solver, in order to address these aims. The solver follows the G-Equation level-set method for turbulent flame propagation by Tan and Reitz, and employs improved numerics to handle meshes featuring different cell types such as hexahedra, tetrahedra, square pyramids and triangular prisms. Detailed reaction kinetics from the SpeedCHEM solver are used to compute the non-equilibrium composition evolution downstream and upstream of the flame surface, where chemical equilibrium is instead assumed.

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.

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].

In the present study a reduced chemical reaction mechanism for biodiesel surrogate fuel was developed and validated for multi-dimensional engine combustion simulations. An existing detailed methyl butanoate mechanism that contained 264 species and 1219 reactions was chosen to represent the oxygenated portion of the fuel. The reduction process included flux analysis, ignition sensitivity analysis, and optimization of reaction rate constants under constant volume conditions. The current reduced mechanism consists of 41 species and 150 reactions and gives predictions in excellent agreement with those of the comprehensive mechanism. In order to validate the mechanism under biodiesel-fueled engine conditions, it was combined with another skeletal mechanism for n-heptane oxidation. This combined reaction mechanism can be used to adjust the energy content of the fuel, and account for diesel/biodiesel blend engine simulations.

Bio-derived fuels are drawing more and more attention in the internal combustion engine (ICE) research field in recent years. Those interests in use of renewable biofuels in ICE applications derive from energy security issues and, more importantly, from environment pollutant emissions concerns. High fidelity numerical study of engine combustion requires advanced computational fluid dynamics (CFD) to be coupled with detailed chemical kinetic models. This task becomes extremely challenging if real fuels are taken into account, as they include a mixture of hundreds of different hydrocarbons, which prohibitively increases computational cost. Therefore, along with employing surrogate fuel models, reduction of detailed kinetic models for multidimensional engine applications is preferred. In the present work, a reduced mechanism was developed for primary reference fuel (PRF) using the directed relation graph (DRG) approach. The mechanism was generated from an existing detailed mechanism.

A computational study using multi-dimensional CFD modeling was performed to investigate the effects of physical properties on diesel engine combustion characteristics with bio-diesel fuels. Properties of typical bio-diesel fuels that were either calculated or measured are used in the study and the simulation results are compared with those of conventional diesel fuels. The sensitivity of the computational results to individual physical properties is also investigated, and the results provide information about the desirable characteristics of the blended fuels. The properties considered in the study include liquid density, vapor pressure, surface tension, liquid viscosity, liquid thermal conductivity, liquid specific heat, latent heat, vapor specific heat, vapor diffusion coefficient, vapor viscosity and vapor thermal conductivity. The results show significant effects of the fuel physical properties on ignition delay and burning rates at various engine operating conditions.

The light-medium load operating range (4-7 bar net IMEP) presents many challenges for advanced low temperature combustion strategies utilizing low cetane fuels (specifically, 87-octane gasoline) in light-duty, high-speed engines. The overly lean overall air-fuel ratio (Φ≺0.4) sometimes requires unrealistically high inlet temperatures and/or high inlet boost conditions to initiate autoignition at engine speeds in excess of 1500 RPM. The objective of this work is to identify and quantify the effects of variation in input parameters on overall engine operation. Input parameters including inlet temperature, inlet pressure, injection timing/duration, injection pressure, and engine speed were varied in a ~0.5L single-cylinder engine based on a production General Motors 1.9L 4-cylinder high-speed diesel engine.

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).

An investigation of high speed direct injection (DI) compression ignition (CI) engine combustion fueled with gasoline injected using a triple-pulse strategy in the low temperature combustion (LTC) regime is presented. This work aims to extend the operation ranges for a light-duty diesel engine, operating on gasoline, that have been identified in previous work via extended controllability of the injection process. The single-cylinder engine (SCE) was operated at full load (16 bar IMEP, 2500 rev/min) and computational simulations of the in-cylinder processes were performed using 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 chosen to match ignition characteristics of the gasoline fuel used for the SCE experiments.

The incorporation of detailed chemistry models in internal combustion engine simulations is becoming mandatory as local, globally lean, low-temperature combustion strategies are setting the path towards a more efficient and environmentally sustainable use of energy resources in transportation. In this paper, we assessed the computational efficiency of a recently developed sparse analytical Jacobian chemistry solver, namely ‘SpeedCHEM’, that features both direct and Krylov-subspace solution methods for maximum efficiency for both small and large mechanism sizes. The code was coupled with a high-dimensional clustering algorithm for grouping homogeneous reactors into clusters with similar states and reactivities, to speed-up the chemical kinetics solution in multi-dimensional combustion simulations.

There is a significant global effort to study low temperature combustion (LTC) as a tool to achieve stringent emission standards with future light duty diesel engines. LTC utilizes high levels of dilution (i.e., EGR > 60% with <10%O2 in the intake charge) to reduce overall combustion temperatures and to lengthen ignition delay, This increased ignition delay provides time for fuel evaporation and reduces in-homogeneities in the reactant mixture, thus reducing NOx formation from local temperature spikes and soot formation from locally rich mixtures. However, as dilution is increased to the limits, HC and CO can significantly increase. Recent research suggests that CO emissions during LTC result from the incomplete combustion of under-mixed fuel and charge gas occurring after the premixed burn period [1, 2]1. The objective of the present work was to increase understanding of the HC/CO emission mechanisms in LTC at part-load.

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 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.

A vaporization model for realistic multi-component fuel sprays is described. The equilibrium at the interface between liquid droplets and the surrounding gas is obtained based on the UNIFAC method, which considers non-ideal molecular interactions that can greatly enhance or suppress the vaporization of the components in the system compared to predictions from ideal mixing using Raoult's Law, especially for polar fuels. The present results using the UNIFAC method are shown to be able to capture the azeotropic behaviors of polar molecule blends, such as mixtures of benzene and ethanol, benzene and iso-propanol, and ethanol and water [1]. Predicted distillation curves of mixtures of ethanol and multi-component gasoline surrogates are compared to those from experiments, and the model gives good improvements on predictions of the distillation curves for initial ethanol volume fractions ranging from 0% to 100%.

Homogeneous or partially premixed charge compression ignition combustion is considered to be an attractive alternative to traditional internal combustion engine operation because of its extremely low levels of pollutant emissions. However, since it is difficult to control the start of combustion timing, direct injection of fuel into the combustion chamber is often used for combustion phasing control, as well as charge preparation. In this paper, numerical simulations of compression ignition processes using gasoline fuel directly injected using a low pressure, hollow cone injector are presented. The multi-dimensional CFD code, KIVA3V, that incorporates various advanced sub-models and is coupled with CHEMKIN for modeling detailed chemistry, was used for the study. Simulation results of the spray behavior at various injection conditions were validated with available experimental data.

Homogeneous charge compression ignition (HCCI) combustion is considered to be an attractive alternative to traditional internal combustion engine operation because of its extremely low levels of pollutant emissions. However, there are several difficulties that must be overcome for HCCI practical use, such as difficult ignition timing controllability. Indeed, too early or too late ignition can occur with obvious drawbacks. In addition, the increase in cyclic variation caused by the ignition timing uncertainty can lead to uneven engine operation. As a way to solve the combustion phasing control problem, dual-fuel combustion has been proposed. It consists of a diesel pilot injection used to ignite a pre-mixture of gasoline (or other high octane fuel) and air. Although dual-fuel combustion is an attractive way to achieve controllable HCCI operation, few studies are available to help the understanding of its in-cylinder combustion behavior.

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.

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.