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The 1977 Clean Air Act Amendments allow the U.S. Environmental Protection Agency to set high altitude emission standards for 1981-83, but specify that any such standards may not be more stringent than comparable sea level standards -- relative to 1970 emission levels. Since available high altitude emission data from 1970 models were incomplete and controversial, the Motor Vehicle Manufacturers Association contracted with Automotive Testing Laboratories, Inc. to test a fleet of 25 1970 cars. Results of the test program showed average increases in emissions at Denver's altitude, compared to sea level, to be about 30% for evaporative HC, 57 to 60% for exhaust HC, 215 to 247% for CO and -46 to -47% for NOx. Corresponding HC and CO exhaust emission baselines would be 6.4 to 6.6 and 108 to 118 g/mi respectively.

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 need for efficient space utilization has provided a framework for the design of a 248mm family of torque converters that supports a wide choice of engine and transmission combinations. The axial length of the part and its weight have been substantially reduced while the performance range has been broadened without degradation of efficiency. The new converter operates in an expanded slipping clutch mode. It significantly contributes to the performance and fuel economy improvements of related vehicles. To meet the cost target, the comprehensive lineup and the resulting complexity have required a high level of component interchangeability. During the design phase, the manufacturing core competencies were scrutinized and process redundancies eliminated, both resulting in optimization of material selection and applicable technology.

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.

“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.

One of the primary issues in the interpretation of vehicle impact response data, observed from vehicle crash test events, is coping with variability. This vehicle response inconsistency generally causes test results to be unpredictable and makes CAE test validation work difficult as well. This paper, considering the uncertain characteristics of vehicle impact events, has implemented a stochastic assessment of vehicle NCAP response variation through a CAE vehicle impact model, and it has accomplished the three primary study objectives as stated follows: 1) Identify the response variation causing factors stochastically from various structural and environmental factor candidates and quantify the degree of their influences on crash response, 2) Develop a methodology for interpreting the significance of the factor effects in conjunction with vehicle impact mechanics and physics, and 3) Implement a stochastic improvement of the vehicle NCAP responses and their repeatability

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.

A single cylinder indirect injection diesel engine was used to evaluate the emissions, fuel consumption, and ignition delay of non-petroleum liquid fuels derived from coal, shale, and tar sands. Correlations were made relating fuel properties with exhaust emissions, fuel consumption, and ignition delay. The results of the correlation study showed that the indicated fuel consumption, ignition delay, and CO emissions significantly correlated with the H/C ratio, specific gravity, heat of combustion, aromatics and saturates content, and cetane number, Multiple fuel properties were necessary to correlate the hydrocarbon emissions. The NOx emissions did not correlate well with any fuel property. Because these fuels from various resources were able to correlate succesfully with many of the fuel properties suggests that the degree of refinement or the chemical composition of the fuel is a better predictor of its performance than its resource.

Although concerns have been raised that the performance of activated carbon canisters will decrease when exposed to air at higher humidities, results of a recently conducted test program do not substantiate these concerns. The results show that the purge efficiency and the working capacity of canisters that are purged with air at 75 grains per pound of dry air (GPPDA) humidity are equal or greater than those obtained with 50 GPPDA humidity purging. The results have been submitted to the California Air Resources Board (ARB) for use in aligning their evaporative emission testing regulations with the regulations promulgated by the U. S. Environmental Protection Agency (EPA).

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.

A 1990 Ford Taurus operated on reformulated gasoline was tested under three modes of malfunction: disabled heated exhaust gas oxygen (HEGO) sensor, inactive catalytic converter, and controlled misfire. The vehicle was run for four U.S. EPA UDDS driving schedule (FTP-75) tests at each of the malfunction conditions, as well as under normal operating conditions. An extensive set of emissions data were collected. In addition to the regulated emissions (HC, CO, and NOx), a detailed chemical analysis was carried out to determine the gas- and particle-phase non-regulated emissions. The effect of vehicle malfunction on gas phase emissions was significantly greater than it was on particle phase emissions. For example, CO emissions ranged from 2.57 g/mi (normal operation) to 34.77 g/mi (disable HEGO). Total HCs varied from 0.22 g/mi (normal operation) to 2.21 g/mi (blank catalyst). Emissions of air toxics (1,3-butadiene, benzene, acetaldehyde, and formaldehyde) were also significantly effected.

The objective of this work is to perform a computer model based sensitivity analysis of parameters of an automotive air conditioning system to identify the critical parameters. Design of Experiment (DOE) and Analysis of Variance (ANOVA) techniques have been used to identify the critical parameters and their relative effects on the air conditioning system performance. The sensitivity analysis has been verified by running similar tests on an air conditioning system test stand (AC Test Stand).

This paper presents a method for optimization design of an engine mounting system subjected to some constraints. The engine center of gravity, the mount stiffness rates, the mount locations and/or their orientations with respect to the vehicle can be chosen as design variables, but some of them are given in advance or have limitations because of the packaging constraints on the mount locations, as well as the individual mount rate ratio limitations imposed by manufacturability. A computer program, called DynaMount, has been developed that identifies the optimum design variables for the engine mounting system, including decoupling mode, natural frequency placement, etc.. The degree of decoupling achieved is quantified by kinetic energy distributions calculated for each of the modes. Several application examples are presented to illustrate the validity of this method and the computer program.

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.