Search Results

The U.S. Department of Energy (DOE) Office of Advanced Automotive Technologies (OAAT), in partnership with industry, is developing transportation technologies that will improve the energy efficiency of our transportation system. Most OAAT programs are focused exclusively on technology development. However, the twin goals of developing innovative technologies and transferring them to industry led OAAT to realize the growing need for people trained in non-traditional, emerging technologies. The Graduate Automotive Technology Education (GATE) program combines graduate-level education with technology development and transfer by training a new generation of automotive engineers in critical multi-disciplinary technologies, by fostering cooperative research in those technologies, and by transferring those technologies directly to industrial organizations.

This study presents experimental and numerical examination of directly injected (DI) propane and iso-octane, surrogates for liquified petroleum gas (LPG) and gasoline, respectively, at various engine like conditions with the overall objective to establish the baseline with regards to fuel delivery required for future high efficiency DI-LPG fueled heavy-duty engines. Sprays for both iso-octane and propane were characterized and the results from the optical diagnostic techniques including high-speed Schlieren and planar Mie scattering imaging were applied to differentiate the liquid-phase regions and the bulk spray phenomenon from single plume behaviors. The experimental results, coupled with high-fidelity internal nozzle-flow simulations were then used to define best practices in CFD Lagrangian spray models.

A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty diesel engine running with a gasoline fuel that has a research octane number (RON) of 80. The goal was to optimize the gasoline compression ignition (GCI) combustion recipe (piston bowl geometry, injector spray pattern, in-cylinder swirl motion, and thermal boundary conditions) for improved fuel efficiency while maintaining engine-out NOx within a 1-1.5 g/kW-hr window. The numerical model was developed using the multi-dimensional CFD software CONVERGE. A two-stage design of experiments (DoE) approach was employed with the first stage focusing on the piston bowl shape optimization and the second addressing refinement of the combustion recipe. For optimizing the piston bowl geometry, a software tool, CAESES, was utilized to automatically perturb key bowl design parameters. This led to the generation of 256 combustion chamber designs evaluated at several engine operating conditions.

A computational fluid dynamics (CFD) guided combustion system optimization was conducted for a heavy-duty compression-ignition engine with a gasoline-like fuel that has an anti-knock index (AKI) of 58. The primary goal was to design an optimized combustion system utilizing the high volatility and low sooting tendency of the fuel for improved fuel efficiency with minimal hardware modifications to the engine. The CFD model predictions were first validated against experimental results generated using the stock engine hardware. A comprehensive design of experiments (DoE) study was performed at different operating conditions on a world-leading supercomputer, MIRA at Argonne National Laboratory, to accelerate the development of an optimized fuel-efficiency focused design while maintaining the engine-out NOx and soot emissions levels of the baseline production engine.

Gasoline is a complex fuel. Many of the constituents of gasoline that are beneficial for the internal combustion engine (ICE) are expected to be challenging for on-board reformers in fuel-cell vehicles. To address these issues, the autothermal reforming of gasoline and individual components of gasoline has been investigated. The results indicate that aromatic components require higher temperatures and longer contact times to reform than paraffinic components. Napthenic components require higher temperatures to reform, but can be reformed at higher space velocities than paraffinic components. The effects of sulfur are dependent on the catalyst. These results suggest that further evolution of gasoline could reduce the demands on the reformer and provide a better fuel for a fuel-cell vehicle.

Two limited-production hybrid electric vehicles (HEVs) - a 1988 Japanese model Toyota Prius and a 2000 Honda Insight - were tested at Argonne National Laboratory to collect data from vehicle component and systems operation. The test data are used to analyze operation and efficiency and to help validate computer simulation models. Both HEVs have FTP fuel economy greater than 45 miles per gallon and also have attributes very similar to those of conventional gasoline vehicles, even though each HEV has a unique powertrain configuration and operation control strategy. The designs and characteristics of these vehicles are of interest because they represent production technology with all the compromises for production included. This paper will explore both designs, their control strategies, and under what conditions high fuel economy was achieved.

At the current stage of engine technology, diesel engines typically require diesel particulate filter (DPF) systems to meet recent particulate emissions standards. To assure the performance and reliability of DPF systems, profound understanding of filtration and regeneration mechanisms is required. Among extensive efforts for developing advanced DPF systems, the development of effective thermal management strategies, which control the thermal runaway taking place in oxidation of an excess amount of soot deposit in DPF, is quite challenging. This difficulty stems mainly from lack of sufficient knowledge and understanding about DPF regeneration mechanisms, which need detailed information about oxidation of diesel particulate matter (PM). Therefore, this work carried out a series of oxidation experiments of diesel particulates collected from a DPF on a diesel engine, and evaluated the oxidation rates of the samples using a thermo-gravimetric analyzer (TGA).

Detailed characteristics of morphology, nanostructures, and sizes were analyzed for particulate matter (PM) emissions from low-temperature combustion (LTC) modes of a single-cylinder, light-duty diesel engine. The LTC engines have been widely studied in an effort to achieve high combustion efficiency and low exhaust emissions. Recent reports indicate that the number of nucleation mode particles increased in a broad engine operating range, which implies a negative impact on future PM emissions regulations in terms of the nanoparticle number. However, the size measurement of solid carbon particles by commercial instruments is indeed controversial due to the contribution of volatile organics to small nanoparticles. In this work, an LTC engine was operated with various biofuel blends, such as blends (B20) of soy bean oil (soy methyl ester, SME20) and palm oil (palm methyl ester, PME20), as well as an ultra-low-sulfur diesel fuel.

It is well know that the internal flow field and nozzle geometry affected the spray behavior, but without high-speed microscopic visualization, it is difficult to characterize the spray structure in details. Single-hole diesel injectors have been used in fundamental spray research, while most direct-injection engines use multi-hole nozzle to tailor to the combustion chamber geometry. Recent engine trends also use smaller orifice and higher injection pressure. This paper discussed the quasi-steady near-nozzle diesel spray structures of an axisymmetric single-hole nozzle and a symmetric two-hole nozzle configuration, with a nominal nozzle size of 130 μm, and an attempt to correlate the observed structure to the internal flow structure using computational fluid dynamic (CFD) simulation. The test conditions include variation of injection pressure from 30 to 100 MPa, using both diesel and biodiesel fuels, under atmospheric condition.

This study reports gaseous and particle (ultrafine and black carbon (BC)) emissions from a turbofan engine core on standard Jet A-1 and three alternative fuels, including 100% hydrothermolysis synthetic kerosene with aromatics (CH-SKA), 50% Hydro-processed Esters and Fatty Acid paraffinic kerosene (HEFA-SPK), and 100% Fischer Tropsch (FT-SPK). Gaseous emissions from this engine for various fuels were similar but significant differences in particle emissions were observed. During the idle condition, it was observed that the non-refractory mass fraction in the emitted particles were higher than during higher engine load condition. This observation is consistent for all test fuels. The 100% CH-SKA fuel was found to have noticeable reductions in BC emissions when compared to Jet A-1 by 28-38% by different BC instruments (and 7% in refractory particle number (PN) emissions) at take-off condition.

In Diesel engines, fuel injection plays a critical role in performance, efficiency, and emissions. Altering parameters such as injection quantity, duration, pressure, etc. influences the injector's performance. Changes in the injection system architecture can also affect the spray behavior. Understanding of the flow near the nozzle exit can lead to the establishment of correlation to spray characteristics further downstream, and eventually its combustion behavior in the engine. Because of its high density, the near-nozzle region of the spray is difficult to study using optical techniques. This near-nozzle region of spray from high pressure injectors was studied using the quantitative and time-resolved x-ray radiography technique. This method provides high spatial and temporal resolution without significant scattering effects.

This paper covers the development of a closed loop transaxle synchronization algorithm which was a key deliverable in the control system design for the L3 Enigma, a Battery Dominant Hybrid Electric Vehicle. Background information is provided to help the reader understand the history that lead to this unique solution of the input and output shaft synchronizing that typically takes place in a manual vehicle transmission or transaxle when shifting into a gear from another or into a gear from neutral when at speed. The algorithm stability is discussed as it applies to system stability and how stability impacts the speed at which a shift can take place. Results are simulated in The MathWorks Simulink programming environment and show how traction motor technology can be used to efficiently solve what is often a machine design issue. The vehicle test bed to which this research is applied is a parallel biodiesel hybrid electric vehicle called the Enigma.

Early in 2007 President Bush announced in his State of the Union Address a plan to off-set 20% of gasoline with alternative fuels in the next ten years. Ethanol, due to its excellent fuel properties for example, high octane number, renewable character, etc., appears to be a favorable alternative fuel from an engine perspective. Replacing gasoline with ethanol without any additional measures results in unacceptable disadvantages mainly in terms of vehicle range. This paper summarizes combustion studies performed with gasoline as well as blends of gasoline and ethanol. These tests were performed on a modern, 4-cylinder spark ignition engine with direct fuel injection and exhaust gas recirculation. To evaluate the influence of blending on the combustion behavior the engine was operated on the base gasoline calibration. Cylinder pressure data taken during the testing allowed for detailed analysis of rates of heat release and combustion stability.

The CFR F1 engine is the standard testing apparatus used for rating the research octane number (RON) of gasoline fuels. Unlike the motor octane number (MON) method, where the intake port temperature after the carburetor is controlled by an electric heater, the mixture temperature can vary during the RON test due to the heat of vaporization (HoV) of the fuel. Ethanol is receiving increasing attention as a high octane and high HoV fuel component. This work presents an analysis of the combustion characteristics during the RON rating of ethanol fuel blends according to the standard ASTM D2699 method, highlighting the effects of ethanol concentration and base fuel composition. All fuels were blended to a constant RON of 98. Ethanol levels varied from 0 to 50 vol% and the base fuels were surrogate blends composed of primary reference fuels (PRF), toluene standardization fuels (TSF), and a four component gasoline surrogate.

An experimental study and analysis was conducted to investigate cold start robustness of an ethanol flex-fuel spark ignition (SI) direct injection (DI) engine. Cold starting with ethanol fuel blends is a known challenge due to the fuel characteristics. The program was performed to investigate strategies to reduce the enrichment requirements for the first firing cycle during a cold start. In this study a single-cylinder SIDI research engine was used to investigate gasoline and E85 fuels which were tested with three piston configurations (CR11F, CR11B, CR15.5B - which includes changes in compression ratio and piston geometry), at three intake cam positions (95, 110, 125 °aTDC), and two fuel pressures (low: 0.4 MPa and high: 3.0 MPa) at 25°C±1°C engine and air temperature, for the first cycle of an engine start.

In this study, the combustion system of a light-duty compression ignition engine running on a market gasoline fuel with Research Octane Number (RON) of 91 was optimized using computational fluid dynamics (CFD) and Machine Learning (ML). This work was focused on optimizing the piston bowl geometry at two compression ratios (CR) (17 and 18:1) and this exercise was carried out at full-load conditions (20 bar indicated mean effective pressure, IMEP). First, a limited manual piston design optimization was performed for CR 17:1, where a couple of pistons were designed and tested. Thereafter, a CFD design of experiments (DoE) optimization was performed where CAESES, a commercial software tool, was used to automatically perturb key bowl design parameters and CONVERGE software was utilized to perform the CFD simulations. At each compression ratio, 128 piston bowl designs were evaluated.

Because of their high efficiency and low emissions, fuel-cell vehicles are undergoing extensive research and development. When considering the introduction of advanced vehicles, a complete well-to-wheel evaluation must be performed to determine the potential impact of a technology on carbon dioxide and Green House Gases (GHGs) emissions. Several modeling tools developed by Argonne National Laboratory (ANL) were used to evaluate the impact of advanced powertrain configurations. The Powertrain System Analysis Toolkit (PSAT) transient vehicle simulation software was used with a variety of fuel cell system models derived from the General Computational Toolkit (GCtool) for pump-to-wheel (PTW) analysis, and GREET (Green house gases, Regulated Emissions and Energy use in Transportation) was used for well-to-pump (WTP) analysis. This paper compares advanced propulsion technologies on a well-to-wheel energy basis by using current technology for conventional, hybrid and fuel cell technologies.

Several studies, conducted from 1997 to 2001, have employed vehicle and powertrain simulation models to estimate fuel economy gains for a variety of fuel-cell powertrains. Many of those studies have attempted to control for the comparability of performance between conventional and fuel-cell vehicles (FCVs), but different sets of performance goals and simulation models have been used. This paper reviews the estimates of fuel economy gain (in mpg) vs. varying measures of performance change for a set of those studies. We examine some of the potential causes for the variability of these estimates - fuel used, powertrain hybridization, vehicle raw energy requirements (load), and variations in analysts' assumptions/estimates - when substituting several types of fuel-cell powertrains. Our study includes development of a database and detailed examination of the relationships among powertrain and vehicle characteristics and fuel economy gain estimates for the selected studies.

The energy density and power density comparison of conventional fuels and batteries is often mentioned as an advantage of conventional vehicles over electric vehicles. Such an analysis often shows that the batteries are at least an order of magnitude behind fuels like gasoline. However this incomplete analysis ignores the impact of powertrain efficiency and mass of the powertrain itself. When we compare the potential of battery electric vehicles (BEVs) as an alternative for conventional vehicles, it is important to include the energy in the fuel and their storage as well as the eventual conversion to mechanical energy. For instance, useful work expected out of a conventional vehicle as well as a BEV is the same (to drive 300 miles with a payload of about 300 lb). However, the test weight of a Conventional vehicle and BEV will differ on the basis of what is needed to convert their respective stored energy to mechanical energy.

The primary objective of the research discussed here was to compare the commercial computational fluid dynamics (CFD) software, CONVERGE, and a prevalent open-source code, OpenFOAM, with regard to their ability to predict spray and combustion characteristics. The high-fidelity data were obtained from the Engine Combustion Network (ECN) at Sandia National Laboratory in a constant-volume combustion vessel under well-defined, controlled conditions. The experiments and simulations were performed by using two diesel surrogate fuels (i.e., n-heptane and n-dodecane) under both non-reacting and reacting conditions. Specifically, ECN data on spray penetration, liquid length, vapor penetration, mixture fraction, ignition delay, and flame lift-off length (LOL) were used to validate both codes. Results indicate that both codes can predict the above experimental characteristics very well.