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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.

“There's nothing new under the sun,” the old proverb says. But you only have to read a magazine, scan a periodical, listen to the radio, watch television, or glance at the multitude of ads that promise that such and such product is the latest trend or has up-to-date, state-of-the-art technology, to seemingly prove the old proverb wrong. However, old proverbs become old because they withstand the test of time. In this case, a hasty judgement should be withheld. Currently, as in the past, the above holds true for car radios as well. Whether in the United States, Europe, Canada or Latin America, the public has always been susceptible to last minute technological advances. It is curious then, that as far as car radio styling is concerned, their appearance has been typically rather conservative, and that it is only recently that styling has begun to change to be more in tune with the times.

Electrification is the well-accepted solution to address carbon emissions and modernize vehicle controls. Batteries play a critical in the journey of electrification and modernization with battery voltage prediction as the foundation for safe and efficient operation. Due to its strong dependency on prior information, battery voltage was estimated with recurrent neural network methods in the recent literatures exploring a variety of deep learning techniques to estimate battery behaviors. In these studies, standard recurrent neural networks, gated recurrent units, and long-short term memory are popular neural network architectures under review. However, in most cases, each neural network architecture is individually assessed and therefore the knowledge about comparative study among three neural network architecture is limited. In addition, many literatures only studied either the dynamic voltage response or the voltage relaxation.

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.

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.

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.

A flow network method was developed to predict the underhood temperature distribution of an automobile. The method involves the solution of simplified energy and momentum equations of the air flow in control volumes defined by subdividing the air space between the surfaces of the underhood components and the front-end geometry. The control volumes are interconnected by ducts with branches and bends to form a flow network. Conservation of mass and momentum with appropriate pressure-loss coefficients leads to a system of algebraic equations to be solved for the flow rates through each volume. The computed flow rates are transferred to a thermal model to calculate the temperatures of the air and the major vehicle components that affect the underhood environment. The method was applied to a 1986 3.0L Taurus and compared with vehicle experiments conducted in a windtunnel.

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 hybrid approach to predict road-induced loads in vehicle structures is presented. The technique involves full vehicle dynamic simulation using measured wheel forces, absolute wheel vertical displacements, and steering angle as input. The wheel vertical displacement is derived from the measured wheel acceleration. This approach avoids the use of tire-road interface modeling. It also improves the conventional loads measuring process with minimum instrumentation and data acquisition. Existing load data from a test vehicle is used to validate this approach. Computed component loads show good agreement with measurements.

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.

A Microcomputer Based Eight Channel Data Acquisition System has been developed for customer correlation and routine vehicle field testing applications. The eight channel system includes a self-contained signal conditioning system designed for a variety of transducer types and data frequency requirements. Calibration, signal gain, and channel zero offset adjustments can be performed under software control. The microcomputer system is based on a Motorola M6800 microprocessor and a non-volatile core memory module. The paper describes the design, development, field performance, and data processing characteristics of the system and presents specific automotive applications and field test results.

Drivelines used in modern pickup trucks commonly employ universal joints. This type of joint is responsible for second driveshaft order vibrations in the vehicle. Large displacements of the joint connecting the driveline and the rear axle have a detrimental effect on vehicle NVH. As leaf springs are critical energy absorbing elements that connect to the powertrain, they are used to restrain large axle windup angles. One of the most common types of leaf springs in use today is the multi-stage parabolic leaf spring. A simple SAE 3-link approximation is adequate for preliminary studies but it has been found to be inadequate to study axle windup. A vast body of literature exists on modeling leaf springs using nonlinear FEA and multibody simulations. However, these methods require significant amount of component level detail and measured data. As such, these techniques are not applicable for quick sensitivity studies at design conception stage.

European legislation covering noise, smoke emission and industrial pollution, all seeking to improve the environment are not addressed in this paper, which takes only exhaust emission and fuel complexity as its subjects. It describes how this complexity can inhibit the development capacity, thus restricting the model offering of a major european automobile manufacturer. The paper concludes that general benefit would be derived from genuine pan european emission legislation, particularly if that legislation was established at levels of control that allowed the development and use of modern engine technology.

A portable in-vehicle NVH data acquisition and analysis system is required to support the product development timing necessary to be competitive in today's automotive market. The components of such a system should include rugged hardware and software to support NVH data acquisition and analysis for frequently performed tests. The system should be easy for the vehicle development engineers to operate while producing results with a high confidence level. Once the data has been measured and analyzed, the system should support automated reporting and databasing of the results. The availability of such a system would make it easy for the vehicle development engineers to perform standardized tests with standardized analysis and reporting. Such a system has been successfully developed at Ford Motor Company.

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.

Significant progress could not have been made in the Sound Quality area without the invention and development of engineering tools. For the sound engineer, the binaural recording head is a primary example of one of those tools. The use of the binaural recording head was crucial to the development of the sound characterization process and has become an essential tool in the Sound Quality areas in Ford Motor Company. A similar tool, The Ford Vehicle Vibration Simulator, has been developed for the vibration engineer. The vehicle vibration simulator (VVS) is unique, consisting of vibration of the vehicle seat (6 degrees of freedom), steering wheel (4 DOF), vehicle floorpan section (1 DOF), and the brake or accelerator pedal (1 DOF). Many vibration test systems have been developed to study human response to vibration, especially for military and space applications. To our knowledge, this is the first multi-axis, fully integrated vibration test system to be used for automotive applications.

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.

The determination of size distribution of soot particles and agglomerates in oil samples using a Nanosight LM14 to perform Nanoparticle Tracking Analysis (NTA) is described. This is the first application of the technique to sizing soot-in-oil agglomerates and offers the advantages of relatively high rates of sample analysis and low cost compared to Transmission Electron Microscopy (TEM). Lubricating oil samples were drawn from the sump of automotive diesel engines run under a mix of light duty operating conditions. The oil samples were diluted with heptane before analysing. Results from NTA analysis were compared with the outputs of a more conventional analysis based on Dynamic Light Scattering (DLS). This work shows that soot-in-oil exists as agglomerates with average size of 115 nm. This is also in good agreement with TEM analysis carried out in a previous work. NTA can measure soot particles in polydisperse oil solutions and report the size distribution of soot-in-oil aggregates.

The recent developments in diesel fuel injection equipment coupled with the moves in the US to using ULSD and biodiesel blends has seen an increase in the number of reports from both engine manufacturers and fleet operators regarding fuel system deposit formation issues. These deposits not only form on and within the fuel injectors but they also form elsewhere in the fuel system, due to fuel recirculation. These will eventually accumulate in the fuel filters. Historically, diesel fuel system deposits have been attributed to contamination of the fuel or the degradation of the fuel with age. Such age related degradation has been attributed to oxidation of the fuel via well documented pathways, although the initiation of this process is still poorly understood. Papers at recent SAE meetings in Florence, San Antonio, Rio de Janeiro, San Diego and Kyoto have addressed many of these causes.