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The 1977 Clean Air Act Amendments allow the U.S. Environmental Protection Agency to set high altitude emission standards for 1981-83, but specify that any such standards may not be more stringent than comparable sea level standards -- relative to 1970 emission levels. Since available high altitude emission data from 1970 models were incomplete and controversial, the Motor Vehicle Manufacturers Association contracted with Automotive Testing Laboratories, Inc. to test a fleet of 25 1970 cars. Results of the test program showed average increases in emissions at Denver's altitude, compared to sea level, to be about 30% for evaporative HC, 57 to 60% for exhaust HC, 215 to 247% for CO and -46 to -47% for NOx. Corresponding HC and CO exhaust emission baselines would be 6.4 to 6.6 and 108 to 118 g/mi respectively.

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.

The 2005 Ford GT high performance sports car was designed and built in keeping with the heritage of the 1960's LeMans winning GT40 while maintaining the image of the 2002 GT40 concept vehicle. This paper reviews the technical challenges in designing and building a super car in 12 months while meeting customer expectations in performance, styling, quality and regulatory requirements. A team of dedicated and performance inspired engineers and technical specialists from Ford Motor Company Special Vehicle Teams, Research and Advanced Engineering, Mayflower Vehicle Systems, Roush Industries, Lear, and Saleen Special Vehicles was assembled and tasked with designing the production 2005 vehicle in record time.

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.

The cyclic behavior of single overlap aluminum joints joined through a number of different methods has been investigated using Alcan 5754-O, an alloy that potentially could be used in structural applications. Overlap shear tests of spot welded, clinched and riveted joints are compared on the basis of their fatigue performance. The fatigue response of the spot welded joint was the baseline to which the other fasteners were compared. Test results showed an improvement of approximately 25% for both the mechanical clinch joints and aluminum rivets in fatigue strength at 106 cycles. The most significant improvement in fatigue strength of 100% was found for the self piercing rivets at 106 cycles. The failure behavior of the various joining methods is discussed as well as the surface appearance.

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.

A cycle counting algorithm that will reduce a complex history into a series of discrete cycles is presented. The cycles determined by this technique are defined as closed stress-strain hysteresis loops of the type obtained from constant amplitude tests. Using the computer cycle counting algorithm, life predictions were made and compared with experimental results. These predictions were found to be typically within a ±3 factor of error. Also, the computer counting method was found to yield more accurate life predictions when compared to the histogram and range counting methods.

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.

Due to magnesium alloy's poor weldability, other joining techniques such as laser assisted self-piercing rivet (LSPR) are used for joining magnesium alloys. This research investigates the fatigue performance of LSPR for magnesium alloys including AZ31 and AM60. Tensile-shear and coach peel specimens for AZ31 and AM60 were fabricated and tested for understanding joint fatigue performance. A structural stress - life (S-N) method was used to develop the fatigue parameters from load-life test results. In order to validate this approach, test results from multijoint specimens were compared with the predicted fatigue results of these specimens using the structural stress method. The fatigue results predicted using the structural stress method correlate well with the test results.

Recent Federal and California legislation have mandated major improvements in emission control. Tailpipe HC emission must be decreased an order of magnitude for the California Ultra Low Emission Vehicle (ULEV) standard. Present feedback A/F* control systems employ a Heated Exhaust Gas Oxygen sensor (HEGO sensor) upstream of the catalyst to perform A/F feedback control. Limitations on the ultimate accuracy of these switching sensors are well known. To overcome these limitations a linear Universal Exhaust Gas Oxygen sensor (UEGO sensor) placed downstream from the minicatalyst is employed to attain improved A/F control and therefore, higher three-way catalyst (TWC) conversion efficiency. This configuration was granted a patent in 1992 (1**). This study compares performance differences between the two feedback control systems on a Ford Mustang. In initial studies both the UEGO and HEGO sensors were compared at the midposition location downstream of a minicatalyst.

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).

Automakers have the opportunity to utilize bio-based composite materials to lightweight cars while replacing conventional, nonrenewable resource materials. In this study, Life Cycle Assessment (LCA) is used to understand the potential benefits and tradeoffs associated with the implementation of bio-based composite materials in automotive component production. This cradle-to-grave approach quantifies the fiber and resin production as well as material processing, use, and end of life for both a conventional glass-reinforced polypropylene component as well as a cellulose-reinforced polypropylene component. The comparison is calculated for an exterior component on a high performance vehicle. The life cycle primary energy consumption and global warming potential (GWP) are evaluated. Reduced GWP associated with the alternative component are due to the use of biomass as process energy and carbon sequestration, in addition to the alternative material component's lightweighting effect.

Afterburning of a rich exhaust/air mixture ahead of the catalyst has been shown in earlier papers to offer an effective means of achieving catalyst light-off in very short times. Protection of the catalyst from overheating is an important aspect of systems using EGI, and on board diagnostics will be required to check for proper function of EGI. In this paper, some options for these requirements are discussed, using a high temperature linear thermistor.

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.

Although the intent of the SHED test (Sealed Housing for Evaporative Determination) is to measure evaporative fuel losses, the SHED sampling methodology in fact measures hydrocarbons from all vehicle and test equipment sources. Leakage of air conditioning (AC) refrigerant is one possible non-fuel source contributing to the SHED hydrocarbon measurement. This report describes a quick and relatively simple method to identify the contribution of AC refrigerant to the SHED analyzer reading. R134A (CH2FCF3), the hydrofluorocarbon refrigerant used in all current automotive AC systems, as well as its predecessor, the chlorofluorocarbon R12, can be detected using the gas chromatography methods currently in place at many emissions labs for the speciation of exhaust and evaporative hydrocarbon emissions.

A number of analytical tools have been used, without any significant success, in the machine manufacturing industry to predict performance of machining processes. The overall equipment efficiency numbers realized on the plant floors provide the supporting evidence of a need of considerable improvements and offer an opportunity for the development of methodologies to characterize the machining processes before installation on the plant floor. Mechanical vibrations signature analysis approach has been used to characterize machine components on the plant floor, but in a limited capacity and under idle conditions. However, attempts to establish vibration standards in machining process characterization without exercising machining loads can cause a false sense of security. This paper describes a methodology of characterizing a given machining process by considering the machine structure, tooling and spindle, workpiece fixture, and the part as the major elements of the machining process.

This paper describes the fabrication and operation of a low-cost, monolithic silicon mass-air-flow sensor (MAFS) developed for automotive applications. The device is a hot wire anemometer made of two thin single-crystal silicon beams, one being the heated element and the other serving as a temperature reference. Temperature compensation techniques and the design tradeoffs to maximize performance while ensuring durability in the harsh automotive environment are discussed.

This paper presents the application of a proposed fuzzy inference system as part of a stability control design scheme implemented with active steering actuator sets. The fuzzy inference system is used to detect the level of overseer/understeer at the high level and a speed-adaptive activation module determines whether an active front steering, active rear steering, or active 4 wheel steering is suited to improve vehicle handling stability. The resulting model-free system is capable of minimizing the amount of model calibration during the vehicle stability control development process as well as improving vehicle performance and stability over a wide range of vehicle and road conditions. A simulation study will be presented that evaluates the proposed scheme and compares the effectiveness of active front steer (AFS) and active rear steer (ARS) in enhancing the vehicle performance. Both time and frequency domain results are presented.