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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.

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.

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.

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.

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.

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.

A general failure criterion for spot welds is proposed with consideration of the plastic anisotropy and the separation speed for crash applications. A lower bound limit load analysis is conducted to account for the failure loads of spot welds under combinations of three forces and three moments. Based on the limit load solution and the experimental results, an engineering failure criterion is proposed with correction factors determined by different spot weld tests. The engineering failure criterion can be used to characterize the failure loads of spot welds with consideration of the effects of the plastic anisotropy, separation speed, sheet thickness, nugget radius and combinations of loads. Spot weld failure loads under uniaxial and biaxial opening loads and those under combined shear and twisting loads from experiments are shown to be characterized well by the engineering failure criterion.

Per California Air Resources Board (CARB) regulations, On-board diagnostic (OBD) of vehicle powertrain systems are required to continuously monitor key powertrain components, such as the circuit discontinuity of actuators, various circuit faults of sensors, and out-of-range faults of sensors. The maturing and clearing of these continuous monitoring faults are critical to simplification of algorithm design, save of engineering cost (i.e., calibration), and reduction of warranty issues. Due to the nature of sensors (to sense different physical quantities) and actuators (to output energy in desired ways), most of OEM and supplies tend to choose different fault maturing and clearing strategy for sensors and actuators with different physics nature, such as timer-based, counter-based, and other physical-quantity-based strategies.

There are several reasons why it can be daunting to apply Six Sigma to product creation. Foremost among them, the functional performance of new technologies is unknown prior to starting a project. Although, Design For Six Sigma (DFSS) was developed to overcome this difficulty, a lack of applicable in-class case studies makes it challenging to train the product creation community. The current paper describes an in-class project which illustrates how Six Sigma is applied to a simulated product creation environment. A toy construction set (TCS) project is used to instruct students how to meet customer expectations without violating cost, packaging volume and design-complexity constraints.

Adhesive bonding technology is playing an increasingly important role in automotive industry. Ultrasonic evaluation of adhesive joints of metal sheets is a challenging problem in Non-Destructive Testing due to the large acoustic impedance mismatch between metal and adhesive, variability in the thickness of metal and adhesive layers, as well as variability in joint geometry. In this paper, we present the results from a matrix array of small flat ultrasonic transducers for evaluation of adhesively bonded joints in both laboratory and production environments. The reverberating waveforms recorded by the array elements are processed to obtain an informative parameter, whose two-dimensional distribution can be presented as a C-scan. Energy of the reflected waveform, normalized with respect to the energy obtained from an area with no adhesive, is a robust parameter for discriminating "adhesive/no-adhesive" regions.

Subjective steering feel tuning and objective verification tests are conducted on vehicle prototypes that are a subset of the total number of buildable combinations of body style, drivetrain and tires. Limited development time, high prototype vehicle cost, and hence limited number of available prototypes are factors that affect the ability to tune and verify all the possible configurations. A new model-based process and a toolset have been developed to enhance the existing steering development process such that steering tuning efficiency and performance robustness can be improved. The innovative method utilizes the existing vehicle dynamics simulation and/or physical test data in conjunction with steering system control models, and provides users with simple interfaces which can be used by either CAE or development engineers to perform virtual tuning of the vehicle steering feel to meet performance targets.

NVH problems are often the result of mechanisms that originate through complex interactions between different physical domains (flow, structural/mechanical, control logic, etc.). Parallel-shaft spur gears subject to light torque loading caused by the dynamic pressure fluctuation of the oil used in engine accessory or transmission pump drives are likely to exhibit unusual gear whine associated with higher order meshing harmonics, even when the tooth profile has a high-quality grade finishing. Therefore, accurate integrated models are becoming a requirement to solve modern NVH problems.

Today's automotive and electronics technologies are evolving so rapidly that educators and industry are both challenged to re-educate the technological workforce in the new area before they are replaced with yet another generation. In early November 2009 Ford's Product Development senior management formally approved a proposal by the University of Detroit Mercy to transform 125 of Ford's “IC Engine Automotive Engineers” into “Advanced Electric Vehicle Automotive Engineers.” Two months later, the first course of the Advanced Electric Vehicle Program began in Dearborn. UDM's response to Ford's needs (and those of other OEM's and suppliers) was not only at the rate of “academic light speed,” but it involved direct collaboration of Ford's electric vehicle leaders and subject matter experts and the UDM AEV Program faculty.

A new strain-based forming limit criterion is proposed to assess the localized necking failure for sheet metal forming simulations when deformation paths deviate significantly from linearity. Different from the traditional strain-based Forming Limit Diagrams (FLD) in terms of major and minor strains, the new FLD is constructed based on effective strains and material flow direction at the end of forming. This new criterion combines the advantages of stress-based FLD for its path-independence and the traditional linear strain path FLD for its easy interpretation. The proposed FLD is validated through both theoretical prediction with Marciniak-Kuczynski (M-K) model and available experimental data in literature, and its relationship with stress-based FLDs is discussed.