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The Ford Ranger will be a domestically built, small pickup truck engineered to many design objectives typical of a fullsize pickup, yet with four cylinder engine fuel efficiency. Ranger is a full-function on-and-off road pickup truck with a uniquely smooth ride and a capacity to carry up to a 725.7 kg. (1600 lb.) payload. The truck features a three passenger body-on-frame cab and a double wall pickup box with provision for 1.2m × 2.4m (4 ft. × 8 ft.) sheets of construction material. Featured in this comprehensive paper are the engineering highlights and innovations contributing to the accomplishment of these Small Truck objectives.

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.

Ford GT 2005 vehicle was designed for performance, timing, cost, and styling to preserve Ford GT40 vintage look. In this vehicle program, many advanced manufacturing processes and light materials were deployed including aluminum and magnesium. This paper briefly explains one unique design concept for a Ford GT instrument panel comprised of a structural magnesium cross-car beam and other components, i.e. radio box and console top, which is believed to be the industry's first structural I/P from vehicle crash load and path perspectives. The magnesium I/P design criteria include magnesium casting properties, cost, corrosion protection, crashworthiness assessments, noise vibration harshness performance, and durability. Magnesium die casting requirements include high pressure die cast process with low casting porosity and sound quality, casting dimensional stability, corrosion protection and coating strategy, joining and assembly constraints.

The High Voltage Power Distribution Unit (PDU) is constructed of magnesium in support of Fuel Cell Electric Vehicle (FCEV) weight reduction efforts. The PDU distributes and controls a nominal 75 kilowatts of power generated by the Fuel Cell, the primary source of High Voltage power, to all the vehicle loads and accessories. The constraints imposed on the design of the PDU resulted in a component highly susceptible to general and galvanic corrosion. Corrosion abatement was the focus of the PDU redesign. This paper describes the redesign efforts undertaken by Ford personnel to improve the part robustness and corrosion resistance.

Springback is a serious problem in sheet metal stamping. It measures the difference between the final shape of the part and the shape of the forming die. Sheet metal forming simulation has made significant progress in predicting springback and several computer simulation codes are commercially available to predict and compensate for it in tool design. The accurate prediction of springback is important and there is a need to validate and verify those predictions with experimental results. Current validation techniques lack standardized procedures, require measurement fixtures that may impose unrealistic restraint on the part, require profiling equipment such as CMM or laser scanning and for the most part produce small springback which reduces measurement accuracy and increases experimental error. A benchmark test has been developed which addresses all these concerns and compares springback predictions by various numerical simulation codes with each other and with experimental results.

Experimental procedures and results of a benchmark test for springback are reported and a complete suite of obtained data is provided for the validation of forming and springback simulation software. The test is usually referred as the Slit-Ring test where a cylindrical cup is first formed by deep drawing and then a ring is cut from the mid-section of the cup. The opening of the ring upon slitting releases the residual stresses in the formed cup and provides a valuable set of easy-to-measure, easy-to-characterize springback data. The test represents a realistic deep draw stamping operation with stretching and bending deformation, and is highly repeatable in a laboratory environment. In this study, six different automotive materials are evaluated.

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.

Not only well-functioning, but also the way operating everyday items "feel", gauges costumer perception of an automobile robustness. To prevent costumer dissatisfaction with door trim panel movement when operating power windows, deflections must be kept small. Deflections of inner panel are seen through trim panel and are responsible for giving a flimsy idea of the door. In this paper, inner panel movement for a fully stamped door in full glass stall up position is analyzed. Through CAE analyses, inner panel behavior was compared, considering different types of reinforcement for belt region.

A study was conducted using Ford's nine standard CFD calibration models as described in SAE paper 940323. The models are identical from the B-pillar forward but have different back end configurations. These models were created for the purpose of evaluating the effect of back end geometry variations on aerodynamic lift and drag. Detailed experimental data is available for each model in the form of surface pressure data, surface flow visualization, and wake flow field measurements in addition to aerodynamic lift and drag values. This data is extremely useful in analyzing the accuracy of the numerical simulations. The objective of this study was to determine the capability of a digital physics based commercial CFD code, PowerFLOW ® to accurately simulate the physics of the flow field around the car-like benchmark shapes.

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.

Dent resistance is an important attribute in the automotive panel design, and the ability to accurately predict a panel's dentability requires careful considerations of sheet metal properties, including property changes from stamping process. The material is often work-hardened significantly during forming, and its thickness is reduced somewhat. With increased demand for weight reduction, vehicle designers are seriously pushing to use thinner-gauged advanced high-strength steels (AHSS) as outer body panels such as fenders, hoods and decklids, with the expectation that its higher strength will offset reduced thickness in its dentability. A comparative study is conducted in this paper for a BH210 steel fender as baseline design and thinner DP500 steel as the new design.

In future vehicles (e.g. fuel cell vehicles, hybrid electric vehicles), the electrical system will have an important impact on the mechanical systems in the car (e.g. powertrain, steering). Furthermore, this coupling will become increasingly important over time. In order to develop effective designs and appropriate control systems for these systems, it is important that the plant models capture the detailed physical behavior in the system. This paper will describe models of two electrical components, a battery and a supercapacitor, which have been modeled in two ways: (i) modeling the plant and controller using block diagrams in Simulink and (ii) modeling the plant and controller in Dymola followed by compiling this model to an S-function for simulation in Simulink. Both the battery and supercapacitor model are based on impedance spectroscopy measurements and can be used for highly dynamic simulations.

Described in this paper is a component test methodology to evaluate the door trim armrest performance in an Insurance Institute for Highway Safety (IIHS) side impact test and to predict the SID-IIs abdomen injury metrics (rib deflection, deflection rate and V*C). The test methodology consisted of a sub-assembly of two SID-IIs abdomen ribs with spine box, mounted on a linear bearing and allowed to translate in the direction of impact. The spine box with the assembly of two abdominal ribs was rigidly attached to the sliding test fixture, and is stationary at the start of the test. The door trim armrest was mounted on the impactor, which was prescribed the door velocity profile obtained from full-vehicle test. The location and orientation of the armrest relative to the dummy abdomen ribs was maintained the same as in the full-vehicle test.

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.

Self-piercing rivet (SPR) joints are a key joining technology for lightweight materials, and they have been widely used in automobile manufacturing. Manual visual crack inspection of SPR joints could be time-consuming and relies on high-level training for engineers to distinguish features subjectively. This paper presents a novel machine learning-based crack detection method for SPR joint button images. Firstly, sub-images are cropped from the button images and preprocessed into three categories (i.e., cracks, edges and smooth regions) as training samples. Then, the Artificial Neural Network (ANN) is chosen as the classification algorithm for sub-images. In the training of ANN, three pattern descriptors are proposed as feature extractors of sub-images, and compared with validation samples. Lastly, a search algorithm is developed to extend the application of the learned model from sub-images into the original button images.

Three pickup truck variants of the Generic Truck Utility (GTU) are evaluated and compared using wind tunnel test data and computational fluid dynamics (CFD) simulations. The configurations analyzed are the short cab/long box, medium cab/medium box, and long cab/short box geometries, which all share a common vehicle length and wheelbase. Both cab and box length are known to influence the total bluff body drag through the interaction of the cab wake in the pickup box with the total vehicle wake, and the GTU provides an excellent test box to investigate the details of these interactions. Experimental testing was conducted at the WindShear wind tunnel on a full-scale GTU model, while transient CFD simulations were carried out with IconCFD®, an open-source based solver. Experimental and CFD results are used to describe the general flow field around the vehicle, and a comparison is made with the wind tunnel integral force data as well as centerline pressure tap data.

In this study the finite element method is used to simulate a light truck multi-leaf spring system and its interaction with a driven axle, u-bolts, and interface brackets. In the first part of the study, a detailed 3-D FE model is statically loaded by fastener pre-tension to determine stress, strain, and contact pressure. The FE results are then compared and correlated to both strain gage and interface pressure measurements from vehicle hardware test. Irregular contact conditions between the axle seat and leaf spring are investigated using a design of experiments (DOE) approach for both convex and discrete step geometries. In the second part of the study, the system FE model is loaded by both fastener pre-tension and external wheel end loads in order to obtain the twist motion response. Torsional deflection, slip onset, and subsequent slip motion at the critical contact plane are calculated as a function of external load over a range of Coulomb friction coefficients.

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.