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The effects of combining premixed, low temperature combustion (LTC) with biodiesel are relatively unknown to this point. This mode allows simultaneously low soot and NOx emissions by using high rates of EGR and increasing ignition delay. This paper compares engine performance and emissions of neat, soy-based methyl ester biodiesel (B100), B20, B50, pure ultra low sulfur diesel (ULSD) and a Swedish, low aromatic diesel in a multi-cylinder diesel engine operating in a late-injection premixed LTC mode. Using heat release analysis, the progression of LTC combustion was explored by comparing fuel mass fraction burned. B100 had a comparatively long ignition delay compared with Swedish diesel when measured by start of ignition (SOI) to 10% fuel mass fraction burned (CA10). Differences were not as apparent when measured by SOI to start of combustion (SOC) even though their cetane numbers are comparable.

Premixed low temperature combustion (LTC) in diesel engines simultaneously reduces soot and NOx at the expense of increased hydrocarbon (HC) and CO emissions. The use of biodiesel in the LTC regime has been shown to produce lower HC emissions than petroleum diesel; however, unburned methyl esters from biodiesel are more susceptible to particulate matter (PM) formation following atmospheric dilution due to their low volatility. In this study, the efficacy of a production-type diesel oxidation catalyst (DOC) for the conversion of light hydrocarbons species and heavier, semi-volatile species like those in unburned fuel is examined. Experimental data were taken from a high speed direct-injection diesel engine operating in a mid-load, late injection partially premixed LTC mode on ultra-low sulfur diesel (ULSD) and neat soy-based biodiesel (B100). Gaseous emissions were recorded using a conventional suite of analyzers and individual light HCs were measured using an FT-IR analyzer.

Direct injection of natural gas under high pressure conditions has emerged as a promising option for improving engine fuel economy and emissions. However, since the gaseous injection technology is new, limited experience exists as to the optimum configuration of the injection system and associated combustion chamber design. The present study uses KIVA-3 based, multidimensional modeling to improve the understanding and assist the optimization of the gaseous injection process. Compared to standard k-ε models, a Renormalization Group Theory (RNG) based k-ε model [1] has been found to be in better agreement with experiments in predicting gaseous penetration histories for both free and confined jet configurations. Hence, this validated RNG model is adopted here to perform computations in realistic engine geometries.

A detailed chemical kinetic mechanism, consisting of 22 species and 104 elementary reactions, has been used in conjunction with the multi-dimensional reactive flow code KIVA-3 to study autoignition of natural gas injected under compression ignition conditions. Calculations for three different blends of natural gas are performed on a three-dimensional computational grid by modeling both the injection and ignition processes. Ignition delay predictions at pressures and temperatures typical of top-dead-center conditions in compression ignition engines compare well with the measurements of Naber et al. [1] in a combustion bomb. Two different criteria, based on pressure rise and mass of fuel burned, are used to detect the onset of ignition. Parametric studies are conducted to show the effect of additives like ethane and hydrogen peroxide in increasing the fuel consumption rate.

A personal computer-based vehicle powertrain simulation (VPS) is developed to predict fuel economy and performance. This paper summarizes the governing equations used in the model. Then the different simulation techniques are described with emphasis on the more complicated time-dependent simulation. The simulation is validated against constant speed and variable cycle test track data obtained for a 5 ton army truck. Then the simulation is used to compare the performance of the 5 ton truck when powered by a cooled and natually aspirated engine, a cooled and turbocharged engine, and an uncooled and turbocharged engine. Studies of the effect of payload, tire efficiency, and drag coefficient on vehicle performance are also conducted, as well as a performance comparison between manual and automatic transmissions. It is concluded that the VPS code can provide good predictions of vehicle fuel economy, and thus is a useful tool in designing and evaluating vehicle powertrains.

This paper analyzes and compares reactor and engine behavior of a diesel oxidation catalyst (DOC) in the presence of conventional diesel exhaust and low temperature premixed compression ignition (PCI) diesel exhaust. Surrogate exhaust mixtures of n-undecane (C11H24), ethene (C2H4), CO, O2, H2O, NO and N2 are defined for conventional and PCI combustion and used in the gas flow reactor tests. Both engine and reactor tests use a DOC containing platinum, palladium and a hydrocarbon storage component (zeolite). On both the engine and reactor, the composition of PCI exhaust increases light-off temperature relative to conventional combustion. However, while nominal conditions are similar, the catalyst behaves differently on the two experimental setups. The engine DOC shows higher initial apparent HC conversion efficiencies because the engine exhaust contains a higher fraction of trappable (i.e., high boiling point) HC.

Variable geometry turbines (VGT) are of particular interest to advanced diesel powertrains for future conventional trucks, since they can dramatically improve system transient response to sudden changes in speed and load, characteristic of automotive applications. VGT systems are also viewed as the key enabler for the application of the EGR system for reduction of heavy-duty diesel emissions. This paper applies an artificial neural network methodology to VGT modeling in order to enable representation of the VGT characteristics for any blade (nozzle) position. Following validation of the ANN model of the baseline, fixed geometry turbine, the VGT model is integrated with the diesel engine system. The latter is linked to the driveline and the vehicle dynamics module to form a complete, high-fidelity vehicle simulation.

Natural gas quality, in terms of the volume fraction of higher hydrocarbons, strongly affects the auto-ignition characteristics of the air-fuel mixture, the engine performance and its controllability. The influence of natural gas composition on engine operation has been investigated both experimentally and through chemical kinetic based cycle simulation. A range of two component gas mixtures has been tested with methane as the base fuel. The equivalence ratio (0.3), the compression ratio (19.8), and the engine speed (1000 rpm) were held constant in order to isolate the impact of fuel autoignition chemistry. For each fuel mixture, the start of combustion was phased near top dead center (TDC) and then the inlet mixture temperature was reduced. These experimental results have been utilized as a source of data for the validation of a chemical kinetic based full-cycle simulation.

This paper discusses the compression ratio influence on maximum load of a Natural Gas HCCI engine. A modified Volvo TD100 truck engine is controlled in a closed-loop fashion by enriching the Natural Gas mixture with Hydrogen. The first section of the paper illustrates and discusses the potential of using hydrogen enrichment of natural gas to control combustion timing. Cylinder pressure is used as the feedback and the 50 percent burn angle is the controlled parameter. Full-cycle simulation is compared to some of the experimental data and then used to enhance some of the experimental observations dealing with ignition timing, thermal boundary conditions, emissions and how they affect engine stability and performance. High load issues common to HCCI are discussed in light of the inherent performance and emissions tradeoff and the disappearance of feasible operating space at high engine loads.

This work reports the development and application of multi-dimensional ignition, combustion and emissions models that account for detailed chemistry and mixing effects in a direct injection engine simulation. A detailed chemical reaction mechanism, consisting of 24 species and 104 reactions, is used for increased accuracy of emissions predictions. Turbulent combustion is represented using a modified Eddy Dissipation Concept (EDC) model to account for mixing effects. The soot model includes all aspects of soot formation and destruction. Particle transport equations are used to realistically track transport of the soot particles formed. All computational sub-models developed in this work have been implemented in a modified version of the KIVA-3V code. In order to illustrate the behavior of the new models, soot and NO emissions have been predicted at different operating conditions by varying injection timing, exhaust gas recirculation (EGR) and injection pressure.

Degreening is crucial in obtaining a stable catalyst prior to assessing its performance characteristics. This paper characterizes the light-off behavior and conversion efficiency of a Diesel Oxidation Catalyst (DOC) during the degreening process. A platinum DOC is degreened for 16 hours in the presence of actual diesel engine exhaust at 650°C and 10% water (H2O) concentration. The DOC's activity for carbon monoxide (CO) and for total hydrocarbons (THC) conversion is checked at 0, 1, 2, 3, 4, 6, 8, 10, 12, and 16 hours of degreening. Pre-and post-catalyst hydrocarbon species are analyzed via gas chromatography at 0, 4, 8, and 16 hours of degreening. It is found that both light-off temperature and species-resolved conversion efficiencies change rapidly during the first 8 hours of degreening and then stabilize to a large degree. T50, the temperature where the catalyst is 50% active towards a particular species, increases by 14°C for CO and by 11°C for THC through the degreening process.

Premixed compression ignition low-temperature diesel combustion (PCI) can simultaneously reduce particulate matter (PM) and oxides of nitrogen (NOx). Carbon monoxide (CO) and total hydrocarbon (THC) emissions increase relative to conventional diesel combustion, however, which may necessitate the use of a diesel oxidation catalyst (DOC). For a better understanding of conventional and PCI combustion, and the operation of a platinum-based production DOC, engine-out and DOC-out exhaust hydrocarbons are speciated using gas chromatography. As combustion mode is changed from lean conventional to lean PCI to rich PCI, engine-out CO and THC emissions increase significantly. The relative contributions of individual species also change; increasing methane/THC, acetylene/THC and CO/THC ratios indicate a richer combustion zone and a reduction in engine-out hydrocarbon incremental reactivity.

The effect of natural gas composition on ignition delay has been investigated numerically by using detailed and reduced chemical kinetic mechanisms. Three different blends of natural gas have been analyzed at pressures and temperatures that are typical of top dead center conditions in compression ignition engines. The predicted ignition delay shows a decrease with temperature in an Arrhenius manner and has a first order dependence on pressure. Similar trends have been observed by Naber et al. [1] in their experimental study of natural gas autoignition in a bomb. It is shown that two kinetic mechanisms (GRI-Mech 1.2 and reduced set DRM22) are best capable of predicting the ignition delay of natural gas under compression ignition conditions. The DRM22 mechanism has been chosen for further studies as t involves lower computational costs compared to the full GRI-Mech 1.2 mechanism.

Medium trucks constitute a large market segment of the commercial transportation sector, and are also used widely for military tactical operations. Recent technological advances in hybrid powertrains and fuel cell auxiliary power units have enabled design alternatives that can improve fuel economy and reduce emissions dramatically. However, deterministic design optimization of these configurations may yield designs that are optimal with respect to performance but raise concerns regarding the reliability of achieving that performance over lifetime. In this article we identify and quantify uncertainties due to modeling approximations or incomplete information. We then model their propagation using Monte Carlo simulation and perform sensitivity analysis to isolate statistically significant uncertainties. Finally, we formulate and solve a series of reliability-based optimization problems and quantify tradeoffs between optimality and reliability.

A regenerative braking model for a parallel Hybrid Electric Vehicle (HEV) is developed in this work. This model computes the line and pad pressures for the front and rear brakes, the amount of generator use depending on the state of deceleration (i.e. the brake pedal position), and includes a wheel lock-up avoidance algorithm. The regenerative braking model has been developed in the symbolic programming environment of MATLAB/SIMULINK/STATEFLOW for downloadability to an actual HEV's control system. The regenerative braking model has been incorporated in NREL's HEV system simulation called ADVISOR. Code modules that have been changed to implement the new regenerative model are described. Resulting outputs are compared to the baseline regenerative braking model in the parent code. The behavior of the HEV system (battery state of charge, overall fuel economy, and emissions characteristics) with the baseline and the proposed regenerative braking strategy are first compared.

The heat release and pollutant formation processes in a direct injection natural gas engine are studied by coupling detailed chemistry with a multi-dimensional reactive flow code. A detailed kinetic mechanism consisting of 22 species and 104 elementary reactions is chosen by comparing ignition delay predictions with measurements in a combustion bomb. The ignition model is then coupled with a turbulent combustion model and extended Zeldovich kinetics to simulate heat release and nitric oxide production in a direct injection engine. Parametric studies are conducted to investigate the effect of engine operating conditions which include speed, load, injection timing and level of boost. It is shown that use of detailed chemistry is extremely important to predict the correct ignition delay period as engine operating conditions change. Use of both time and crank angle as the independent variable reveals interesting details of the heat release process as a function of engine speed.

A computer simulation of the Homogenous Charge Compression Ignition (HCCI) four-stroke engine has been developed for combustion and performance studies. The simulation couples models for mass, species, and energy within a zero-dimensional framework. The combustion process is described via a user-defined chemical kinetic mechanism. The CHEMKIN libraries have been used to formulate a stiff chemical kinetic solver suitable for integration within a complete engine cycle simulation, featuring models of gas exchange, turbulence and wall heat transfer. For illustration, two chemical kinetics schemes describing hydrogen and natural gas chemistry have been implemented in the code. The hydrogen scheme is a reduced one, consisting of 11 species and 23 reactions. The natural gas chemistry is described via the GRI-mechanism 3.0 that considers 53 species and 325 reactions, including NOx chemistry.