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A 1.8L turbocharged diesel engine valvetrain friction was investigated, and the effectiveness of using a solid film lubricant (SFL) coating in reducing friction was determined throughout the operable speed range. This valvetrain design features direct acting mechanical bucket valve lifters. Camshaft journal bearing surfaces and all camshaft rubbing surfaces except lobe tips were coated. The direct acting bucket shims were etched with a cross hatch pattern to a depth sufficient to sustain a SFL film coating on the shim rubbing surfaces subjected to high surface loads. The SFL coated valvetrain torque was evaluated and compared with uncoated baseline torque. Coating the cam bearing journal surfaces alone with II-25D SFL reduced valvetrain friction losses 8 to 17% for 250 to 2000 rpm cam speed range (i.e. 500 - 4000 rpm engine speed). When bucket tappet and shims were also coated with the SFL, further significant reductions in coated valvetrain friction were observed.

The demand for improved fuel economy in both cars and trucks has emphasized the need for lighter weight components. The application of high strength steel to wheels, both rim and disc, represents a significant opportunity for the automotive industry. This paper discusses the Ranger HSLA wheel program that achieved a 9.7 lbs. per vehicle weight savings relative to a plain carbon steel wheel of the same design. It describes the Ranger wheel specifications, the material selection, the metallurgical considerations of applying HSLA to wheels, and HSLA arc and flash butt welding. The Ranger wheel design and the development of the manufacturing process is discussed, including design modifications to accommodate the lighter gage. The results demonstrate that wheels can be successfully manufactured from low sulfur 60XK HSLA steel in a conventional high volume process (stamped disc and rolled rim) to meet all wheel performance requirements and achieve a significant weight reduction.

A single cylinder indirect injection diesel engine was used to evaluate the emissions, fuel consumption, and ignition delay of non-petroleum liquid fuels derived from coal, shale, and tar sands. Correlations were made relating fuel properties with exhaust emissions, fuel consumption, and ignition delay. The results of the correlation study showed that the indicated fuel consumption, ignition delay, and CO emissions significantly correlated with the H/C ratio, specific gravity, heat of combustion, aromatics and saturates content, and cetane number, Multiple fuel properties were necessary to correlate the hydrocarbon emissions. The NOx emissions did not correlate well with any fuel property. Because these fuels from various resources were able to correlate succesfully with many of the fuel properties suggests that the degree of refinement or the chemical composition of the fuel is a better predictor of its performance than its resource.

New regulations from the state of California have established, for the first time, reactivity-based exhaust emissions standards for new vehicles and require that any clean alternative fuels needed by these vehicles be made available. Contained in these regulations are provisions for “reactivity adjustment factors” which will provide credit for vehicles which run on reformulated gasoline. The question arises: given two fuels of different chemical composition, but both meeting the criteria for CA Phase 2 gasoline (reformulated gasoline), how different might the specific reactivity of the exhaust hydrocarbons be? In this study we explored this question by examining the engine-out HC emissions from a single-cylinder version of the 5.4 L modular truck engine run on two different CA Phase 2 fuels.

A 1990 Ford Taurus operated on reformulated gasoline was tested under three modes of malfunction: disabled heated exhaust gas oxygen (HEGO) sensor, inactive catalytic converter, and controlled misfire. The vehicle was run for four U.S. EPA UDDS driving schedule (FTP-75) tests at each of the malfunction conditions, as well as under normal operating conditions. An extensive set of emissions data were collected. In addition to the regulated emissions (HC, CO, and NOx), a detailed chemical analysis was carried out to determine the gas- and particle-phase non-regulated emissions. The effect of vehicle malfunction on gas phase emissions was significantly greater than it was on particle phase emissions. For example, CO emissions ranged from 2.57 g/mi (normal operation) to 34.77 g/mi (disable HEGO). Total HCs varied from 0.22 g/mi (normal operation) to 2.21 g/mi (blank catalyst). Emissions of air toxics (1,3-butadiene, benzene, acetaldehyde, and formaldehyde) were also significantly effected.

Available methodologies for model bias identification are mainly regression-based approaches, such as Gaussian process, Bayesian inference-based models and so on. Accuracy and efficiency of these methodologies may degrade for characterizing the model bias when more system inputs are considered in the prediction model due to the curse of dimensionality for regression-based approaches. This paper proposes a copula-based approach for model bias identification without suffering the curse of dimensionality. The main idea is to build general statistical relationships between the model bias and the model prediction including all system inputs using copulas so that possible model bias distributions can be effectively identified at any new design configurations of the system. Two engineering case studies whose dimensionalities range from medium to high will be employed to demonstrate the effectiveness of the copula-based approach.

Vehicle sound quality has become an important basic performance requirement. Traditionally, automobile noise studies were focused on quietness. It is now necessary for the automobile to be more than quiet. The sound must be pleasing. This paper describes a development process to improve both vehicle noise level and sound quality. Formal experimental design techniques were utilized to quantify various hardware effects. A-weighted sound pressure level, Speech Intelligibility, and Composite Rating of Preference were the three descriptors used to characterize the vehicle's sound quality. Engineering knowledge augmented with graphical and statistical techniques were utilized during data analysis. The individual component contributions to each of the sound quality descriptors were also quantified in this study.

Four vehicle fleets, consisting of 3 to 4 vehicles each, were emission tested on a 48″ roll chassis dynamometer using both the FTP urban dynamometer driving cycle and the REP05 driving cycle. The REP05 cycle was developed to test vehicles under high speed and high load conditions not included in the FTP. The vehicle fleets consisted of 1989 light-duty gasoline vehicles, 1992-93 limited production FFV/VFV methanol vehicles, 1992-93 compressed natural gas (CNG) vehicles and their gasoline counterparts, and a 1992 production and two prototype ethanol FFV/VFV vehicles. All vehicles (except the dedicated CNG vehicles) were tested using Auto/Oil AQIRP fuels A and C2. Other fuels used were M85 blended from A and C2, E85 blended from C1, which is similar to C2 but without MTBE, and four CNG fuels representing the range of in-use CNG fuels. In addition to bag measurements, tailpipe exhaust concentration and A/F data were collected once per second throughout every test.

Although there was a safety awareness from the earliest days of the automobile, systematic approaches to designing for safety became more widespread after 1950 when large numbers of vehicles came into use in both the United States and Europe, and governments in both continents undertook a widespread highway development. Industry response to safety objectives and also to government regulation has produced a large number of safety enhancing engineering developments, including radial tires, disc brakes, anti-lock brakes, improved vehicle lighting systems, better highway sign support poles, padded instrument panels, better windshield retention systems, collapsible hood structures, accident sensitive fuel pump shut-off valves, and other items. A significant development was the design of the energy absorbing front structures.

In this paper, a soft computing approach to a model-free vehicle stability control (VSC) algorithm is presented. The objective is to create a fuzzy inference system (FIS) that is robust enough to operate in a multitude of vehicle conditions (load, tire wear, alignment), and road conditions while at the same time providing optimal vehicle stability by detecting and minimizing loss of traction. In this approach, an adaptive neuro-fuzzy inference system (ANFIS) is generated using previously collected data to train and optimize the performance of the fuzzy logic VSC algorithm. This paper outlines the FIS detection algorithm and its benefits over a model-based approach. The performance of the FIS-based VSC is evaluated via a co-simulation of MATLAB/Simulink and CarSim model of the vehicle under various road and load conditions. The results showed that the proposed algorithm is capable of accurately indicating unstable vehicle behavior for two different types of vehicles (SUV and Sedan).

A four-stroke, spark-ignition engine is described that seeks to achieve high expansion ratio and low throttling losses at light load, whilst retaining good knock resistance at full load operation and without the need for expensive mechanical changes to the engine. The engine does, however, incorporate a second inlet (transfer) valve and associated transfer port linked to the intake port. The timing of the transfer valve is different from that of the main inlet valve. Load modulation is achieved by control of the gas outflow from the transfer port. A computer model of the engine is first validated against measured data from a conventional engine. Comparisons are made of incylinder pressure at part load conditions, total air flowrate through the engine and intake port air velocities as a function of crank angle position.

Combustion flame geometry calculation is a critical task in the design and analysis of combustion engine chamber. Combustion flame directly influences the fuel economy, engine performance and efficiency. Currently, many of the flame geometry calculation methods assume certain specific chamber and piston top shapes and make some approximations to them. Even further, most methods can not handle multiple spark plug set-ups. Consequently, most of the current flame geometry calculation methods do not give accurate results and have some built-in limitations. They are particularly poor for adapting to any kind of new chamber geometry and spark plug set-up design. This report presents a novel methodology which allows the accurate calculation of flame geometry regardless of the chamber geometry and the number of spark plugs. In this methodology, solid models are used to represent the components within the chamber and unique attributes (colors) are attached respectively to these components.

There have been many articles published in the last decade or so concerning the components of an electronic stability control (ESC) system, as well as numerous statistical studies that attempt to predict the effectiveness of such systems relative to crash involvement. The literature however is free from papers that discuss how engineers might develop such systems in order to achieve desired steering, handling, and stability performance. This task is complicated by the fact that stability control systems are very complex and their designs and what they can do have changed considerably over the years. These systems also differ from manufacturer to manufacturer and from vehicle to vehicle in a given maker of automobiles. In terms of ESC hardware, differences can include all the components as well as the addition or absence of roll rate sensors or active steering gears to name a few.

Although much has been learned in recent years about the atmospheric reactivity of the hydrocarbon (HC) emissions from gasoline-fueled vehicles, there is only a limited database of corresponding information for exhaust emissions from diesel-fueled vehicles. An assessment of exhaust reactivity requires “speciation”, or measurement of the individual species of the HC fraction. The HC exhaust emissions are a complex mixture of unburned and partially burned fuel components. Because diesel fuel contains a much higher molecular weight range (typically C9-C26) than gasoline (typically C5-C12), new methodology was required to accommodate the collection and analysis of the >C12 fraction of the HC exhaust. As part of a study of the effects of fuel and other factors on the chemical nature of diesel emissions, we have developed a method for the collection and analysis of the semivolatile or heavy HC (>C12) fraction of the exhaust.

A finite element analysis method has been developed to assess the design of an automobile body joint. The concept of the coefficient of joint stiffness and the force distribution ratio are proposed accordingly. The coefficient of joint stiffness reveals whether a joint is stiff enough compared to its joining components. In addition, these parameters can be used to estimate the potential and the effectiveness for any further improvement of the joint design. The modeling and analysis of the proposed process are robust. The coefficient of joint stiffness could be further developed to serve as the joint design target.

Exhaust gas air-fuel ratio (A/F) sensors are common devices in powertrain feedback control systems aimed at minimizing emissions. Both resistive (using TiO2) and electrochemical (using ZrO2) mechanisms are used in the high temperature ceramic devices now being employed. In this work a new mechanism for making the measurement is presented based on the change in the workfunction of a Pt film in interaction with the exhaust gas. In particular it is found that the workfunction of Pt increases reversibly by approximately 0.7 V at that point (the stoichiometric ratio) where the exhaust changes from rich to lean conditions. This increase arises from the adsorption of O2 on the Pt surface. On returning to rich conditions, catalytic reaction of the adsorbed oxygen with reducing species returns the workfunction to its original value. Two methods, one capacitive and one thermionic, for electrically sensing this workfunction change and thus providing for a practical device are discussed.

The crush performance of lightweight composite automotive structures varies significantly between static and dynamic test conditions. This paper discusses the development of a new dynamic testing facility that can be used to characterize crash performance at high loads and constant speed. Previous research results from the Energy Management Working Group (EMWG) of the Automotive Composites Consortium (ACC) showed that the static crush resistance of composite tubes can be significantly greater than dynamic crush results at speeds greater than 2 m/s. The new testing facility will provide the unique capability to crush structures at high loads in the intermediate velocity range. A novel machine control system was designed and projections of the machine performance indicate its compliance with the desired test tolerances. The test machine will be part of a national user facility at the Oak Ridge National Laboratory (ORNL) and will be available for use in the summer of 2002.

As automakers strategize approaches to sustainable vehicle technologies, alternative powertrains must be considered to reduce future fleet vehicle emissions and improve energy security. These alternative vehicles include different fuels and electrification. The ultimate for on-road CO2 reductions is a zero emission vehicle, which can be achieved by either a hydrogen fuel cell or battery electric vehicle. These vehicles would also require a renewable energy source to provide their propulsion energy in order to achieve maximum sustainability for both CO2 reduction and energy security. Renewable energy sources such as wind or solar result in heat or electricity that needs to be generated into an energy carrier such as hydrogen or stored in a battery. When examining these options based strictly on the efficiency path, previous analysis have concluded fuel cell vehicles may not be an appropriate suitability strategy in comparison to battery electric vehicles.

New vehicle control algorithms are needed to meet future emissions and fuel economy mandates that are quite likely to require a measurement of ambient specific humidity (SH). Current practice is to obtain the SH by measurement of relative humidity (RH), temperature and barometric pressure with physical sensors, and then to estimate the SH using a fit equation. In this paper a novel approach is described: a system of neural networks trained to estimate the SH using data that already exists on the vehicle bus. The neural network system, which is referred to as a virtual SH sensor, incorporates information from the global navigation satellite system such as longitude, latitude, time and date, and from the vehicle climate control system such as temperature and barometric pressure, and outputs an estimate of SH. The conclusion of this preliminary study is that neural networks have the potential of being used as a virtual sensor for estimating ambient and intake manifold's SH.

About 10 years ago in the US, an automotive OEM consortium formed the Oxygenated Fuels Task Force which in turn created the SAE Cooperative Research Project Group 2 to develop a simple rational method for qualifying materials. At that time the focus was Methanol/Gasoline blends. This work resulted in SAE J1681, Gasoline/Methanol Mixtures for Materials Testing. Recently this document was rewritten to make it the single, worldwide, generic source for fuel system test fluids. The paper will describe the rationale for selecting the fuel surrogate fluids and why this new SAE standard should replace all existing test fuel or test fluid standards for fuel system materials testing.