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This paper documents the processes and methods used by the Ford GT team to meet aerodynamic targets. Methods included Computational Fluid Dynamics (CFD) analysis, wind tunnel experiments (both full-size and scale model), and on-road experiments and measurements. The goal of the team was to enhance both the high-speed stability and track performance of the GT. As a result of the development process, significant front and rear downforce was achieved while meeting the overall drag target.

The Ford GT Program Team was allocated just 22 months from concept to production to complete the Electrical and Electronics systems of the Ford GT. This reduced vehicle program timing - unlike any other in Ford's history -- demanded that the team streamline the standard development process, which is typically 54 months. This aggressive schedule allowed only 12 weeks to design the entire electrical and electronic system architecture, route the wire harnesses, package the components, and manufacture and/or procure all components necessary for the first three-vehicle prototype build.

The Ford GT powertrain (see Figure 1) is an integrated system developed to preserve the heritage of the LeMans winning car of the past. A team of co-located engineers set out to establish a system that could achieve this result for today's supercar. Multiple variations of engines, transaxles, cooling systems, component locations and innovations were analyzed to meet the project objectives. This paper covers the results and achievements of that team.

The proposed technique is a tailored deep neural network (DNN) training approach which uses an iterative process to support the learning of DNNs by targeting their specific misclassification and missed detections. The process begins with a DNN that is trained on freely available annotated image data, which we will refer to as the Base model, where a subset of the categories for the classifier are related to the automotive theater. A small set of video capture files taken from drives with test vehicles are selected, (based on the diversity of scenes, frequency of vehicles, incidental lighting, etc.), and the Base model is used to detect/classify images within the video files. A software application developed specifically for this work then allows for the capture of frames from the video set where the DNN has made misclassifications. The corresponding annotation files for these images are subsequently corrected to eliminate mislabels.

A CAE SEA-based optimization process for the enhancement of vehicle high frequency NVH applications is developed and validated. The CAE simulation, based on statistical energy analysis (SEA) theory [1], has been used to analyze high frequency NVH responses for the vehicle sound package development. However, engineers have always faced two challenges during the vehicle SEA model development. One is to create a reliable SEA model, which is correlated well with hardware test data. The other is to have a systematic approach by using the correlated model to design effective and cost efficient sound package to improve vehicle interior quietness. The optimization process presented in this paper, which integrates analysis, design sensitivity, and optimization solver, has been developed to address the challenges and to serve the needs. A non-correlated Sport Utility Vehicle (SUV) and a correlated midsize car models were used to demonstrate the capability of the proposed optimization process.

Ford Motor Company has recently implemented a Hardware-In-the-Loop (HIL) testing system for a new, highly complex, hybrid electric vehicle (HEV) Electronic Control Unit (ECU). The implementation of this HIL system has been quick and effective, since it is based on proven Commercial-Off-The-Shelf (COTS) automation tools for real-time that allow for a very flexible and intuitive design process. An overview of the HIL system implementation process and the derived development benefits will be shown in this paper. The initial concept for the use of this HIL system was a complete closed-loop vehicle simulation environment for Vehicle System Controller testing, but the paper will show that this concept has evolved to allow for the use of the HIL system for many facets of the design process.

In automotive body manufacturing the dies for blanking/trimming/piercing are under most severe loading condition involving high contact stress at high impact loading and large number of cycles. With continuous increase in sheet metal strength, the trim die service life becomes a great concern for industries. In this study, competing trim die manufacturing routes were compared, including die raw materials produced by hot-working (wrought) vs. casting, edge-welding (as repaired condition) vs. bulk base metals (representing new tools), and the heat treatment method by induction hardening vs. furnace through-heating. CaldieTM, a Uddeholm trademarked grade was used as trim die material. The mechanical tests are performed using a WSU developed trimming simulator, with fatigue loading applied at cubic die specimen’s cutting edges through a tungsten carbide rod to accelerate the trim edge damage. The tests are periodically interrupted at specified cycles for measurement of die edge damage.

Combustion in modern spark-ignition (SI) engines is increasingly knock-limited with the wide adoption of downsizing and turbocharging technologies. Fuel autoignition conditions are different in these engines compared to the standard Research Octane Number (RON) and Motor Octane Numbers (MON) tests. The Octane Index, OI = RON - K(RON-MON), has been proposed as a means to characterize the actual fuel anti-knock performance in modern engines. The K-factor, by definition equal to 0 and 1 for the RON and MON tests respectively, is intended to characterize the deviation of modern engine operation from these standard octane tests. Accurate knowledge of K is of central importance to the OI model; however, a single method for determining K has not been well accepted in the literature.

As part of the International Lubricant Standardization and Approval Committee's (ILSAC) goal of developing a global automatic transmission fluid (ATF) specification, members have been evaluating test methods that are currently used by various automotive manufacturers for qualifying ATF for use in their respective transmissions. This report deals with comparing test methods used for determining torque capacity in friction systems (shifting clutches). Three test methods were compared, the Plate Friction Test from the General Motors DEXRON®-III Specification, the Friction Durability Test from the Ford MERCON® Specification, and the Japanese Automotive Manufacturers Association Friction Test - JASO Method 348-95. Eight different fluids were evaluated. Friction parameters used in the comparison were breakaway friction, dynamic friction torque at midpoint and the end of engagement, and the ratio of end torque to midpoint torque.

Pressure Sensitive Paint (PSP) has been used for several years by the aircraft industry in transonic wind tunnel testing where the oxygen concentrations are low and the luminescence of the paint is easily recorded. Extending PSP to slower speeds where the oxygen concentrations are closer to atmospheric conditions is much more challenging. For the past few years, work has been underway at both Wright Patterson Air Force Base and Ford Motor Company to advance PSP techniques for testing at slower speeds. The CRADA (Cooperative Research and Development Agreement) provided a way for comparisons to be made of the different PSP systems that were being investigated. This paper will report on PSP tests conducted as part of the CRADA.

As part of an ongoing technical collaboration between Ford and Rouge Steel Company, a comprehensive study of door slam event was undertaken. The experimental phase of the project involved measurements of accelerations at eight locations on the outer panel and strains on six locations of the inner panel. Although slam tests were conducted with window up and window down, results of only one test is presented in this paper. The CAE phase of the project involved the development of suitable “math” model of the door assembly and analysis methodology to capture the dynamics of the event. The predictability of the CAE method is examined through detailed comparison of accelerations and strains. While excellent agreement between CAE and test results of accelerations on the outer panel is obtained, the analysis predicts higher strains on the inner panel than the test. In addition, the tendency of outer panel to elastically buckle is examined.

A correlation of aerodynamic wind tunnels was initiated between Chrysler, Ford and General Motors under the umbrella of the United States Council for Automotive Research (USCAR). The wind tunnels used in this correlation were the open jet tunnel at Chrysler's Aero Acoustic Wind Tunnel (AAWT), the open jet tunnel at the Jacobs Drivability Test Facility (DTF) that Ford uses, and the closed jet tunnel at General Motors Aerodynamics Laboratory (GMAL). Initially, existing non-competitive aerodynamic data was compared to determine the feasibility of facility correlation. Once feasibility was established, a series of standardized tests with six vehicles were conducted at the three wind tunnels. The size and body styles of the six vehicles were selected to cover the spectrum of production vehicles produced by the three companies. All vehicles were tested at EPA loading conditions. Despite the significant differences between the three facilities, the correlation results were very good.

Ride Hailing service and Dynamic Shuttle are two key smart mobility practices, which provide on-demand door-to-door ride-sharing service to customers through smart phone apps. On the other hand, some big companies spend millions of dollars annually in third party vendors to offer shuttle services to pick up and drop off employees at fixed locations and provide them daily commutes for employees to and from work. Efficient fixed routing algorithms and analytics are the key ingredients for operating efficiency behind these services. They can significantly reduce operating costs by shortening bus routes and reducing bus numbers, while maintaining the same quality of service. This study developed an off-line optimization routing method for employee shuttle services including regular work shifts and demand based shifts (e.g. overtime shifts) in some regions.

In order to maximize customer satisfaction in today's global market place, the quality of products and services need to be improved continually. Increased focus on quality, with the attendant proliferation of methods and tools, has created the need for a comprehensive framework to guide the selection of the tools. Individuals within an organization need to know what tools are appropriate in a given situation, and when, where and how the knowledge gained from an effort should be documented. In addition, a common nomenclature to convey quality related information to each other would avoid confusion and improve the communication process thus improving the effectiveness and productivity of the organization. This paper integrates tools that have evolved recently with the old tools that have been in use for a number of years.

In this paper, we proposed a distributed Engineering Computer Aided Learning System. Instead of attending engineering teaching sessions, engineering students are able to interact with the software to gain the same amount of teaching materials. Besides, they will interact with other engineering students from other Engineering schools. The proposed software has the ability to examine the student step by step to reach certain goals. The training and the examination will be different based on the student level and his learning process. Using this system the role of excellent professor can be achieved. The software will have two sessions, i.e. test session and learning session. The software provides the capability of knowledge sharing between multi schools and different educational systems that can provide the students with a large set of training materials. The system was built using JAVA programming language.

Brake squeal has been a chronic customer complaint, often appearing high on the list of items that reduce customers' satisfaction with their vehicles. Brake squeal can emanate from either a drum brake or a disc brake even though the geometry of the two systems is significantly different. A drum brake generates friction within a cylindrical drum interacting with two semi-circular linings. A disc brake consists of a flat disc and two flat pads. The observed squeal behavior in a vehicle differs somewhat between drum and disc brakes. A drum brake may have a loud noise coming from three or more squeal frequencies, whereas a disc brake typically has one or two major squeal frequencies making up the noise. A good understanding of the operational deflection shapes of the brake components during noise events will definitely aid in design to reduce squeal occurrences and improve product quality.

Contemporary manufacturing systems are still evolving. The system elements, layouts, and integration methods are changing continuously, and ‘collaborative robots’ (CoBots) are now being considered as practical industrial solutions. CoBots, unlike traditional CoBots, are safe and flexible enough to work with humans. Although CoBots have the potential to become standard in production systems, there is no strong foundation for systems design and development. The focus of this research is to provide a foundation and four tier framework to facilitate the design, development and integration of CoBots. The framework consists of the system level, work-cell level, machine level, and worker level. Sixty-five percent of traditional robots are installed in the automobile industry and it takes 200 hours to program (and reprogram) them.

An eight-group taxonomy was created to classify real-world frontal crashes from the Crashworthiness Data System (CDS) component of the National Automotive Sampling System (NASS). Three steps were taken to develop the taxonomy: (1) frontal-impact towaway crashes were identified by examining 1985-2005 model year light passenger vehicles with Collision Deformation Classification (CDC) data from the 1995-2005 calendar years of NASS; (2) case reviews, engineering judgments, and categorization assessments were conducted on these data to produce the eight-group taxonomy; and (3) two subsets of the NASS dataset were analyzed to assess the consistency of the resulting taxonomic-group frequencies. “Full-engagement” and “Offset” crashes were the most frequent crash types, each contributing approximately 33% to the total. The group identified as “D, Y, Z No-Rail” was the most over-represented crash type for vehicles with at least one seriously-injured occupant.

Variant modeling techniques have been developed to allow systems engineers to model multiple similar variants in a product line as a single variant model. In this paper, we expand on this past work to explore the extent to which variant modeling in SysML can be applied to a broad range of dissimilar systems, covering the entire domain of ground vehicles, in single reference architecture model. Traditionally, a system’s structure is decomposed into subsystems and components. However, this method is found to be ineffective when modeling variants that are functionally similar but structurally different. We propose to address this challenge by first decomposing the system not only by subsystem but also by high-level function. This pattern is particularly useful for situations where two variants perform the same function, but one variant performs the function using one subsystem, whereas the other variant performs the same function using one or more different subsystems.

Many descriptions of product development are based on a timeline of activity. Timelines typically do not characterize the underlying strategy and flexibility embodied in the technical activity that actually takes place between activity nodes. Timelines alone will inhibit evolving to a more rational approach to product development. The view of engineering described in this paper is a functional view of engineering. It is what engineers do. It is aligned with the technical tools used by engineers. It applies to both product development and manufacturing. It's purpose is to enhance understanding of the function of engineering activities, including reliability.