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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.

The main objective of the current paper was to investigate the fluid flow and pressure loss characteristics of DPF substrates with asymmetric channels utilizing 3-D Computational Fluid Dynamics (CFD) methods. The ratio of inlet to outlet channel width is 1.2. First, CFD results of velocity and static pressure distributions inside the inlet and outlet channels are discussed for the baseline case with both forward and reversed exhaust flow. Results were also compared with the regular DPF of same cell structure and wall material properties. It was found that asymmetrical channel design has higher pressure loss. The lowest pressure loss was found for the asymmetrical channel design with smaller inlet channels. Then, the effects of DPF length and filter wall permeability on pressure loss, flow and pressure distributions were investigated.

With the advent of this new era of electric-driven automobiles, the simulation and virtual digital twin modeling world is now embarking on new sets of challenges. Getting key insights into electric motor behavior has a significant impact on the net output and range of electric vehicles. In this paper, a complete 3D CFD model of an Electric Motor is developed to understand its churning losses at different operating speeds. The simulation study details how the flow field develops inside this electric motor at different operating speeds and oil temperatures. The contributions of the crown and weld endrings, crown and weld end-windings, and airgap to the net churning loss are also analyzed. The oil distribution patterns on the end-windings show the effect of the centrifugal effect in scrapping oil from the inner structures at higher speeds. Also, the effect of the sump height with higher operating speeds are also analyzed.

“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.

Performance testing and evaluation always plays an important role in the developmental process of a vehicle, which also applies to autonomous vehicles. The complex nature of an autonomous vehicle from architecture to functionality demands even more quality-and-quantity controlled testing and evaluation than ever before. Most of the existing testing methodologies are task-or-scenario based and can only support single or partial functional testing. These approaches may be helpful at the initial stage of autonomous vehicle development. However, as the integrated autonomous system gets mature, these approaches fall short of supporting comprehensive performance evaluation. This paper proposes a novel hierarchical and systematic testing and evaluation approach to bridge the above-mentioned gap.

This paper presents a computational fluid dynamics (CFD) model for predicting power losses associated with churning of oil by gears or other similar rotating components. The modeling approach and parameters are optimized to ensure the accuracy, robustness, and computational efficiency of these predictions. These studies include a look at two types of mesh and a turbulence model selection. The focus is on multiple reference frame (MRF) modeling technique for its computational efficiency advantage. Model predictions are compared to previously published experimental data [1] under varying operating conditions typical for an automotive transmission application. The model shows good agreement with the hardware both quantitatively and qualitatively, capturing the trends with speed and submersion level. The paper concludes with presenting some key lessons learned, and recommendation for future work to ultimately build a highly reliable tool as part of the virtual product development.

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.

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.

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.

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.

Fuel chemistry plays a crucial role in the continued reduction of particulate emissions (PE) and cleaner air quality from vehicles and equipment powered by internal combustion engines (ICE). Over the past ten years, there have been great improvements in predictive particulate emissions indices (correlative mathematical models) based on the fuel’s composition. Examples of these particulate indices (PI) are the Honda Particulate Matter Index (PMI) and the General Motors Particulate Evaluation Index (PEI). However, the analytical chemistry lab methods used to generate data for these two PI indices are very time-consuming. Because gasoline can be mixtures of hundreds of hydrocarbon compounds, these lab methods typically include the use of the high resolution chromatographic separation techniques such as detailed hydrocarbon analysis (DHA), with 100m chromatography columns and long (3 - 4 hours) analysis times per sample.

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 pumping system used in a step ratio automatic transmission can consume up to 20% of the total power required to operate a typical automotive transmission through the EPA city cycle. As such, it represents an area manufacturers have focused their efforts towards in their quest to obtain improved transmission efficiency. This paper will discuss the history of automatic transmission pumps that develop up to 300 psi along with a description of the factors used to size pumps and establish pump flow requirements. The various types of pumps used in current automatic transmissions will be described with a discussion of their characteristics including a comparison based upon observations of their performance. Specific attention will be focused on comparing the volumetric efficiency, mechanical efficiency, overall efficiency, pumping torque and discharge flow.

A feedgas hydrocarbon emissions model that extends the usefulness of fully-warmed steady-state engine maps to the cold transient regime was developed for use within a vehicle simulation program that focuses on the powertrain control system (Virtual Powertrain and Control System, VPACS). The formulation considers three main sources of hydrocarbon. The primary component originates from in-cylinder crevice effects which are correlated with engine coolant temperature. The second component includes the mass of fuel that enters the cylinder but remains unavailable for combustion (liquid phase) and subsequently vaporizes during the exhaust portion of the cycle. The third component includes any fuel that remains from a slow or incomplete burn as predicted by a crank angle resolved combustion model.