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The demand for improved fuel economy in both cars and trucks has emphasized the need for lighter weight components. The application of high strength steel to wheels, both rim and disc, represents a significant opportunity for the automotive industry. This paper discusses the Ranger HSLA wheel program that achieved a 9.7 lbs. per vehicle weight savings relative to a plain carbon steel wheel of the same design. It describes the Ranger wheel specifications, the material selection, the metallurgical considerations of applying HSLA to wheels, and HSLA arc and flash butt welding. The Ranger wheel design and the development of the manufacturing process is discussed, including design modifications to accommodate the lighter gage. The results demonstrate that wheels can be successfully manufactured from low sulfur 60XK HSLA steel in a conventional high volume process (stamped disc and rolled rim) to meet all wheel performance requirements and achieve a significant weight reduction.

This paper describes Programmed Ride Control (PRC), the automatic adjustable shock absorber system designed and patented by Ford Motor Company. The system utilizes low shock absorber damping under normal driving conditions to provide soft boulevard ride, automatically switching to firm damping when required for improved handling. The system's microprocessor control module “learns” where the straight ahead steering wheel position is, allowing the system to respond to absolute steering wheel angle. A closed loop control strategy is used to improve system reliability and to notify the driver in the event of a system malfunction. Fast acting rotary solenoids control the damping rate of the shock absorbers.

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.

This paper describes a new concept for a Ford GT instrument panel (IP) based on structural magnesium components, which resulted in what may be the industry's first structural IP (primary load path). Two US-patent applications are ongoing. Design criteria included cost, corrosion protection, crashworthiness assessments, noise vibration harshness (NVH) performance, and durability. Die casting requirements included feasibility for production, coating strategy and assembly constraints. The magnesium die-cast crosscar beam, radio box and console top help meet the vehicle weight target. The casting components use an AM60 alloy that has the necessary elongation properties required for crashworthiness. The resulting IP design has many unique features and the flexibility present in die-casting that would not be possible using conventional steel stampings and assembly techniques.

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.

An integrated engineering approach using computer modeling, laboratory and vehicle testing enabled the Ford GT engineering team to achieve supercar thermal management performance within the aggressive program timing. Theoretical and empirical test data was used during the design and development of the engine cooling system. The information was used to verify design assumptions and validate engineering efforts. This design approach allowed the team to define a system solution quickly and minimized the need for extensive vehicle level testing. The result of this approach was the development of an engine cooling system that adequately controls air, oil and coolant temperatures during all driving and environmental conditions.

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.

The performance of three way and NOx catalysts was evaluated on vehicles utilizing non-feedback fuel control and electronic feedback fuel control. The vehicles accumulated 80,450 km (50,000 miles) using fuels representing the extremes in hydrogen-carbon ratio available for commercial use. Feedback carburetion compared to non-feedback carburetion improved highway fuel economy by about 0.4 km/l (1 mpg) and reduced deterioration of NOx with mileage accumulation. NOx emissions were higher with the low H/C fuel in the three way catalyst system; feedback reduced the fuel effect on NOx in these cars by improving conversion efficiency with the low H/C fuel. Feedback had no measureable effect on HC and CO catalyst efficiency. Hydrocarbon emissions were lower with the low H/C fuel in all cars. Unleaded gasoline octane improver, MMT, at 0.015g Mn/l (0.06 g/gal) increased tailpipe hydrocarbon emissions by 0.05 g/km (0.08 g/mile).

This paper reports on the injuries to the head, neck and thorax of fifteen child surrogates, subjected to varying levels of sudden acceleration. Measured response data in the child surrogate tests and in matched tests with a three-year-old child test dummy are compared to the observed child surrogates injury levels to develop preliminary tolerance data for the child surrogate. The data are compared with already published data in the literature.

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.

“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.

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.

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.

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.

Frequency domain testing has had limited use in the past for durability evaluations of automotive components. Recent advances and new perspectives now make it a viable option. Using frequency domain testing for components, test times can be greatly reduced, resulting in considerable savings of time, money, and resources. Quality can be built into the component, thus making real-time subsystem and full vehicle testing and development more meaningful. Time domain testing historically started with block cycle histogram tests. Improved capabilities of computers, controllers, math procedures, and algorithms have led to real time simulation in the laboratory. Real time simulation is a time domain technique for duplicating real world environments using computer controlled multi-axial load inputs. It contains all phase information as in the recorded proving ground data. However, normal equipment limitations prevent the operation at higher frequencies.

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.

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.

In a recent study, quantitative measurements were presented of in-cylinder spatial distributions of mixture equivalence ratio in a single-cylinder light-duty optical diesel engine, operated with a non-reactive mixture at conditions similar to an early injection low-temperature combustion mode. In the experiments a planar laser-induced fluorescence (PLIF) methodology was used to obtain local mixture equivalence ratio values based on a diesel fuel surrogate (75% n-heptane, 25% iso-octane), with a small fraction of toluene as fluorescing tracer (0.5% by mass). Significant changes in the mixture's structure and composition at the walls were observed due to increased charge motion at high swirl and injection pressure levels. This suggested a non-negligible impact on wall heat transfer and, ultimately, on efficiency and engine-out emissions.

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.