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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.

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 main objective of the current paper was to investigate the fluid flow and pressure loss characteristics of DPF substrates with asymmetric channels utilizing 3-D Computational Fluid Dynamics (CFD) methods. The ratio of inlet to outlet channel width is 1.2. First, CFD results of velocity and static pressure distributions inside the inlet and outlet channels are discussed for the baseline case with both forward and reversed exhaust flow. Results were also compared with the regular DPF of same cell structure and wall material properties. It was found that asymmetrical channel design has higher pressure loss. The lowest pressure loss was found for the asymmetrical channel design with smaller inlet channels. Then, the effects of DPF length and filter wall permeability on pressure loss, flow and pressure distributions were investigated.

The main objective of this paper is to investigate the performance of partial filtration DPF substrates using 3-D Computational Fluid Dynamics (CFD) methods. Detailed 3-D CFD simulations were performed for real world sizes of DPF inlet and outlet channel geometries. Two concepts of partial filters were studied. The baseline geometry was a standard DPF with the front plugs removed. The second concept was to eliminate half of outlet plugs in addition to the inlet plugs to improve the pressure drop performance. The total filter efficiency was defined in current study to quantify the overall filter filtration efficiency which combines the effects from wall flow efficiency and flow through efficiency. For baseline case, 45% of total exhaust gas was found to go through the inlet channels, and the total trap efficiency was as high as 60%. However, only a 10% pressure loss reduction was found due to the removal of the outlet channel plugs from the DPF inlet side.

Model validation is a process to assess the validity and predictive capabilities of a computer model by comparing simulation results with test data for its intended use of the model. One of the key difficulties for model validation is to evaluate the quality of a computer model at different test configurations in design space, and interpolate or extrapolate the evaluation results to untested new design configurations. In this paper, an integrated model interpolation and extrapolation framework based on Bayesian inference and Response Surface Models (RSM) is proposed to validate the designs both within and outside of the original design space. Bayesian inference is first applied to quantify the distributions' hyper-parameters of the bias between test and CAE data in the validation domain. Then, the hyper-parameters are extrapolated from the design configurations to untested new design. They are then followed by the prediction interval of responses at the new design points.

An extensive calibration study has been initiated to assess the predictive ability of CFD (Computational Fluid Dynamics) for the aerodynamic design of automotive shapes. Several codes are being checked against a set of detailed wind tunnel measurements on ten car-like shapes. The objective is to assess the ability of numerical analysis to predict the CD (drag coefficient) influence of the rear end configuration. The study also provides a significant base of information for investigating discrepancies between predicted and measured flow fields and for assessing new numerical techniques. This technical report compares STAR-CD predictions to the wind tunnel measurements. The initial results are quite encouraging. Calculated centerline pressure distributions on the front end, underbody and floor compare well for all ten shapes. Wake flow structures are in reasonable agreement for many of the configurations. Drag, lift, and pitching moment trends follow the experimental measurements.

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.

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.

Available methodologies for model bias identification are mainly regression-based approaches, such as Gaussian process, Bayesian inference-based models and so on. Accuracy and efficiency of these methodologies may degrade for characterizing the model bias when more system inputs are considered in the prediction model due to the curse of dimensionality for regression-based approaches. This paper proposes a copula-based approach for model bias identification without suffering the curse of dimensionality. The main idea is to build general statistical relationships between the model bias and the model prediction including all system inputs using copulas so that possible model bias distributions can be effectively identified at any new design configurations of the system. Two engineering case studies whose dimensionalities range from medium to high will be employed to demonstrate the effectiveness of the copula-based approach.

This paper reports the analytical procedure developed for a simulation of knee impact during a barrier crash using a hybrid III dummy lower torso. A finite element model of the instrument panel was generated. The dummy was seated in mid-seat position and was imparted an initial velocity so that the knee velocity at impact corresponded to the secondary impact velocity during a barrier crash. The procedure provided a reasonably accurate simulation of the dummy kinematics. This simulation can be used for understanding the knee bolster energy management system. The methodology developed has been used to simulate impact on knee for an occupant belted or unbelted in a frontal crash. The influence of the vehicle interior on both the dummy kinematics and the impact locations was incorporated into the model. No assumptions have been made for the knee impact locations, eliminating the need to assume knee velocity vectors.

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.

Vehicle sound quality has become an important basic performance requirement. Traditionally, automobile noise studies were focused on quietness. It is now necessary for the automobile to be more than quiet. The sound must be pleasing. This paper describes a development process to improve both vehicle noise level and sound quality. Formal experimental design techniques were utilized to quantify various hardware effects. A-weighted sound pressure level, Speech Intelligibility, and Composite Rating of Preference were the three descriptors used to characterize the vehicle's sound quality. Engineering knowledge augmented with graphical and statistical techniques were utilized during data analysis. The individual component contributions to each of the sound quality descriptors were also quantified in this study.

Four vehicle fleets, consisting of 3 to 4 vehicles each, were emission tested on a 48″ roll chassis dynamometer using both the FTP urban dynamometer driving cycle and the REP05 driving cycle. The REP05 cycle was developed to test vehicles under high speed and high load conditions not included in the FTP. The vehicle fleets consisted of 1989 light-duty gasoline vehicles, 1992-93 limited production FFV/VFV methanol vehicles, 1992-93 compressed natural gas (CNG) vehicles and their gasoline counterparts, and a 1992 production and two prototype ethanol FFV/VFV vehicles. All vehicles (except the dedicated CNG vehicles) were tested using Auto/Oil AQIRP fuels A and C2. Other fuels used were M85 blended from A and C2, E85 blended from C1, which is similar to C2 but without MTBE, and four CNG fuels representing the range of in-use CNG fuels. In addition to bag measurements, tailpipe exhaust concentration and A/F data were collected once per second throughout every test.

A model is presented which incorporates the key mechanisms in the formation and reduction of unburned HC emissions from spark ignited engines. The model includes the effects of piston crevice volume, oil layer absorption / desorption, partial burns, and in-cylinder and exhaust port oxidation. The mechanism for the filling and emptying of the piston crevice takes into account the location of the flame front so that the flow of both burned gas and unburned gas is recognized. Oxidation of unburned fuel is calculated with a global, Arrhenius-type equation. A newly developed submodel is included which calculates the amount of unburned fuel to be added to the cylinder as a result of partial burns. At each crankangle, the submodel compares the rate of change of the burned gas volume to the rate of change of the cylinder volume.

Although there was a safety awareness from the earliest days of the automobile, systematic approaches to designing for safety became more widespread after 1950 when large numbers of vehicles came into use in both the United States and Europe, and governments in both continents undertook a widespread highway development. Industry response to safety objectives and also to government regulation has produced a large number of safety enhancing engineering developments, including radial tires, disc brakes, anti-lock brakes, improved vehicle lighting systems, better highway sign support poles, padded instrument panels, better windshield retention systems, collapsible hood structures, accident sensitive fuel pump shut-off valves, and other items. A significant development was the design of the energy absorbing front structures.

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).

A four-stroke, spark-ignition engine is described that seeks to achieve high expansion ratio and low throttling losses at light load, whilst retaining good knock resistance at full load operation and without the need for expensive mechanical changes to the engine. The engine does, however, incorporate a second inlet (transfer) valve and associated transfer port linked to the intake port. The timing of the transfer valve is different from that of the main inlet valve. Load modulation is achieved by control of the gas outflow from the transfer port. A computer model of the engine is first validated against measured data from a conventional engine. Comparisons are made of incylinder pressure at part load conditions, total air flowrate through the engine and intake port air velocities as a function of crank angle position.