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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.

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.

Squeak and rattle has become a primary source of undesired noise in automobiles due to the continual diminishment of engine, power train and tire noise levels. This article presents a finite-element-based methodology for the improvement of rattle performance of vehicle components. For implementation purposes, it has been applied to study the rattle of a glove compartment latch and corner rubber bumpers. Results from the glove compartment study are summarized herein. Extensions to other rattle problems are also highlighted.

A mathematical model is developed which describes the operation of an A/F control system containing an engine, an exhaust gas oxygen sensor, and a feedback controller. The dependence of model parameters on engine operating conditions is discussed, and the model is used to compare integral and proportional/integral control algorithms. Actual data obtained on an engine-dynamometer are presented to test the validity of the model.

Vehicle restraint system design is a difficult optimization problem to solve because (1) the nature of the problem is highly nonlinear, non-convex, noisy, and discontinuous; (2) there are large numbers of discrete and continuous design variables; (3) a design has to meet safety performance requirements for multiple crash modes simultaneously, hence there are a large number of design constraints. Based on the above knowledge of the problem, it is understandable why design of experiment (DOE) does not produce a high-percentage of feasible solutions, and it is difficult for response surface methods (RSM) to capture the true landscape of the problem. Furthermore, in order to keep the restraint system more robust, the complexity of restraint system content needs to be minimized in addition to minimizing the relative risk score to achieve New Car Assessment Program (NCAP) 5-star rating.

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.

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.

In this paper, a soft computing approach to a model-free vehicle stability control (VSC) algorithm is presented. The objective is to create a fuzzy inference system (FIS) that is robust enough to operate in a multitude of vehicle conditions (load, tire wear, alignment), and road conditions while at the same time providing optimal vehicle stability by detecting and minimizing loss of traction. In this approach, an adaptive neuro-fuzzy inference system (ANFIS) is generated using previously collected data to train and optimize the performance of the fuzzy logic VSC algorithm. This paper outlines the FIS detection algorithm and its benefits over a model-based approach. The performance of the FIS-based VSC is evaluated via a co-simulation of MATLAB/Simulink and CarSim model of the vehicle under various road and load conditions. The results showed that the proposed algorithm is capable of accurately indicating unstable vehicle behavior for two different types of vehicles (SUV and Sedan).

Topology optimization is used for obtaining the best layout of vehicle structural components to achieve predetermined performance goals. Unlike the most common approach which uses the optimality criteria methods, the topology design problem is formulated as a general optimization problem and is solved by the mathematical programming method. One of the major advantages of this approach is its generality; thus it can solve various problems, e.g. multi-objective and multi-constraint problems. The MSC/NASTRAN finite element code is employed for response analyses. Two automotive examples including a simplified truck frame and a truck frame crossmember are presented.

This paper presents a simplified concept of the cab-over-engine tractor ride problem. It discusses ways ride can be improved and the reasons cab suspension was chosen as the preferred solution. It describes the Ford CL-9000 cab suspension, explains why it improves ride and includes some data to indicate the benefits that are realized.

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.

This paper focuses on the role and significance of linear momentum and kinetic energy in controlling air bags aboard vehicles. Among the results of the study are analytic and geometric models that characterize crash behavior and control algorithms that quantify crash severity and identify crash configurations. These results constitute an effective basis for crash-data design and air-bag control.

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.

A new, systematic, sensitivity based design process for weight reduction is presented. Traditionally, a trial and error method is used when a design fails to meet the weight and the design criteria, which often conflict. This old approach not only is time and cost consuming but also does not provide insight into structural behavior. This proposed process uses state-of-the-art technologies such as design sensitivity analysis, numerical optimization, graphical user interface, etc. It handles multi-discipline design criteria simultaneously and provides design engineers insight into structural responses for frequency, durability, and stiffness concerns and a means for systematic weight reduction and quality improvement. The new design process has been applied for the weight reduction of advanced truck frame designs. Results show that a significant weight savings has been achieved while all design criteria are met.

Since road roughness is an important source of vehicle vibration, a system model for NVH analysis requires a tire model which accurately predicts spindle response to road input. Most tire models currently used in the auto industry do not meet this requirement, because they are based on static stiffness of the tire and do not produce realistic response to input at the patch. This paper investigates a new modal tire model with patch input capability as a component within a vehicle system model. Comparisons are also presented between the behavior of the new tire model and a conventional spring model. To validate the performance of the tire model for NVH analysis, simulated vehicle responses to bump input are compared to chassis roll test results. Good correlation between the model prediction and the chassis roll measurements is observed.

As automakers strategize approaches to sustainable vehicle technologies, alternative powertrains must be considered to reduce future fleet vehicle emissions and improve energy security. These alternative vehicles include different fuels and electrification. The ultimate for on-road CO2 reductions is a zero emission vehicle, which can be achieved by either a hydrogen fuel cell or battery electric vehicle. These vehicles would also require a renewable energy source to provide their propulsion energy in order to achieve maximum sustainability for both CO2 reduction and energy security. Renewable energy sources such as wind or solar result in heat or electricity that needs to be generated into an energy carrier such as hydrogen or stored in a battery. When examining these options based strictly on the efficiency path, previous analysis have concluded fuel cell vehicles may not be an appropriate suitability strategy in comparison to battery electric vehicles.

Various algorithms such as a direct computation approach, maximization requirement criteria method established by Chou and Nyquist, and a partitioning technique, for computing HIC are reviewed in this paper. An evaluation has been conducted considering both the accuracy and efficiency of these algorithms using theoretical pulses and experimental resultant head accelerations of a dummy obtained from the literature, Hyge sled and frontal barrier impact tests. Using results obtained from direct computations as “exact” values for comparison, all the algorithms evaluated provide HIC estimates in close agreement with the “exact” values. The CPU times, which are used as a measure for the assessment of computational efficiency, vary from algorithm to algorithm. Methods using a partitioning logic developed by Mentzer and a faster algorithm developed by Holstein and Alem are found to be very efficient, and are recommended for use in the computation of HIC.

In vehicle crash tests, an unbelted occupant's kinetic energy is absorbed by the restraints such as an air bag and/or knee bolster and by the vehicle structure during occupant ride-down with the deforming structure. Both the restraint energy absorbed by the restraints and the ride-down energy absorbed by the structure through restraint coupling were studied in time and displacement domains using crash test data and a simple vehicle-occupant model. Using the vehicle and occupant accelerometers and/or load cell data from the 31 mph barrier crash tests, the restraint and ride-down energy components were computed for the lower extremity, such as the femur, for the light truck and passenger car respectively.

This paper contains a technical description of the Ford Motor Co.'s ACT system which has been designed to meet transportation needs in a wide variety of urban applications. The discussion covers the systems design features and operation of the driverless rubber-tired vehicles, the guideway, and the system's ability to meet expanding needs by a modular approach to the command and control design. Descriptions of Ford's new Cherry Hill Test Track and the first installations at the Fairlane Town Center in Dearborn, Mich., and the Bradley International Airport, Hartford, Conn., are also presented.

This paper proposes a novel algorithm. This algorithm is called Self-Organizing Fuzzy Neural Network (SOFNN). SOFNN revolutionizes how researchers apply control theories, image/signal processing on control systems and other applications. In general, SOFNN is an identification technique that automatically initiates, builds and fine-tunes the required network parameters. SOFNN evaluates required structures without predefined parameters or expressions regarding systems. SOFNN sets out to learn and configure a system's characteristics. Self-constructing and self-tuning features enable SOFNN to handle complex, non-linear, and time-varying systems with higher accuracy, making systems identification easier. SOFNN constructs and fine-tunes the system parameter through two phases. The two phases are the construction and the parameter-tuning phase. The two phases run concurrently allowing SOFNN to identify systems on-line.