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A microcomputer-based, multichannel data acquisition system has been developed to acquire high frequency transient information typified by, but not limited to, automotive vehicle crash test applications. The system, which has been designed to be mounted on the test vehicle during a vehicle crash, will accommodate up to 240 channels. Each channel is comprised of a stand-alone microcomputer, memory for data storage, signal conditioning for piezoresistive transducers, automatic calibration and zero offsets, and programmable gain amplifier. The microcomputer is based upon a Motorola 6801/68701 microcomputer. The paper describes the design, development, and data processing characteristics of the prototype system.

Computer simulation of the behavior of the automotive cooling system is becoming increasingly common, so as to reduce the dependency on costly testing. The simulation of transient cooling system behavior has become easier with the use of 1-D simulation tools. However, accurate prediction of transient coolant temperature after thermostat operation has been limited by the difficulty in accurately modeling the behavior of the automotive thermostat. Physical models of the thermostat are often inaccurate due to the complexity of the thermostat. Therefore an empirical model has been developed, which can be used to model any automotive thermostat, once a few simple tests have been conducted on the part. This thermostat model can be used in conjunction with a 1-D flow simulation tool to predict coolant transient temperature response during thermostat operation.

This paper presents the application of a proposed fuzzy inference system as part of a stability control design scheme implemented with active steering actuator sets. The fuzzy inference system is used to detect the level of overseer/understeer at the high level and a speed-adaptive activation module determines whether an active front steering, active rear steering, or active 4 wheel steering is suited to improve vehicle handling stability. The resulting model-free system is capable of minimizing the amount of model calibration during the vehicle stability control development process as well as improving vehicle performance and stability over a wide range of vehicle and road conditions. A simulation study will be presented that evaluates the proposed scheme and compares the effectiveness of active front steer (AFS) and active rear steer (ARS) in enhancing the vehicle performance. Both time and frequency domain results are presented.

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.

A finite element analysis method has been developed to assess the design of an automobile body joint. The concept of the coefficient of joint stiffness and the force distribution ratio are proposed accordingly. The coefficient of joint stiffness reveals whether a joint is stiff enough compared to its joining components. In addition, these parameters can be used to estimate the potential and the effectiveness for any further improvement of the joint design. The modeling and analysis of the proposed process are robust. The coefficient of joint stiffness could be further developed to serve as the joint design target.

We have developed a new wall wetting model to predict the transient Air/Fuel ratio excursion in a port fuel injected (PFI) engine due to changes in air or fuel flow. The quasi-dimensional model accounts for fuel films both in the port as well as in the cylinder of a PFI engine and includes the effects of back-flow on the port fuel films to redistribute and vaporize the fuel. A multi-component fuel model is included in the simulation; it gives realistic fuel behavior and allows the effects of different fuel distillation curves to be studied. The multi-component fuel model calculates the changing composition of the fuel puddles in the port and cylinder during the cycle. The inclusion of an in-cylinder fuel film allows the model to be used for cold start conditions down to 290 K. The model uses the Reynold's analogy to calculate the fuel vaporization process and uses a boundary layer calculation to solve for the liquid film flow.

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.

This paper presents a novel low air flow rate measuring device. The device was designed to accurately, easily, and in a repeatable way measure the air flow rate through the in-cabin temperature sensor used in automatic climate control systems. The design of the device is briefly discussed and calibration data are presented. Finally, data from some bench-top tests and from in-vehicle measurements are presented.

In this paper, we introduce a numerically stable 2D computer model for sheet metal forming analysis based on the membrane theory. It simulates both axisymmetrical and plane strain cases with various restraining and friction conditions. We implemented a more realistic material model that accounts for cyclic loading and unloading. Also, the difficult frictional force reversal problem has been overcome. A simulation package released within Ford Motor Company has proven robust and accurate for applications to industrial cases.

An analytical model based on “vortex sound” theory was investigated for predicting the frequency, the relative magnitude, the onset, and the offset of self-sustained interior pressure fluctuations inside a vehicle with an open sunroof. The “buffeting” phenomenon was found to be caused by the flow-excited resonance of the cavity. The model was applied to investigate the optimal sunroof length and width for a mid-size sedan. The input parameters are the cavity volume, the orifice dimensions, the flow velocity, and one coefficient characterizing vortex diffusion. The analytical predictions were compared with experimental results obtained for a system which geometry approximated the one-fifth scale model of a typical vehicle passenger compartment with a rectangular, open sunroof. Predicted and observed frequencies and relative interior pressure levels were in good agreement around the “critical” velocity, at which the cavity response is near resonance.

The present work focused on modeling turbulent flame propagation combustion process using a direct chemical kinetics model. Firstly, the theory of turbulent flame propagation combustion modeling directly using chemical kinetics is given in detail. Secondly, two important techniques in this approach are described. One technique is the selection of chemical kinetics mechanism, and the other one is the selection of AMR (adaptive mesh refinement) level. A reduced chemical kinetics mechanism with minor modification by the authors of this paper which is suitable for simulating gasoline engine under warm up operating conditions was selected in this work. This mechanism was validated over some operating conditions close to some engine cases. The effect of AMR level on combustion simulation is given, and an optimum AMR level of both velocity and temperature is recommended.

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.

This paper provides an overview of the dual EGO sensor method for OBD-II catalyst efficiency monitoring. The processes governing the relationship between catalyst oxygen storage, HC conversion efficiency, and rear EGO sensor response are reviewed in detail. A simple physical model relating catalyst oxygen storage capacity and rear EGO sensor response is constructed and used in conjunction with experimental data to provide additional insight into the operation of the catalyst monitor. The effect that the catalyst washcoat formulation has in determining the relationship between catalyst oxygen storage capacity and HC conversion efficiency and its impact on the catalyst monitor is also investigated. Lastly, the effects of catalyst failure mode, fuel sulfur, and the fuel additive MMT on the catalyst monitor's ability to properly diagnose catalyst function are discussed.

This paper begins with a comparison of the automotive power supply and loads in the early 1950's (near the end of the six-volt era) to the modern counterpart in the early 1990's (possibly near the end of the 12-volt era). A typical power supply specification sheet is developed based on the in-vehicle performance characteristics. From this summary, two attributes are noted: first, the system voltage is not very stable and second, transient protection is limited. With this awareness and the knowledge that the power supply of the future will need architectural change, a review of the design assumptions using a total system view and a long term outlook is advanced. Using a rule based design process and employing available technology to enhance the power system architecture, a number of elements are proposed for consideration in new designs.

The optimized design of an exhaust emission system in terms of performance, cost, packaging, and engine control strategy will be a key part of competitively meeting future more stringent emission standards. Extensive use of vehicle experiments to evaluate design system tradeoffs is far too time consuming and expensive. Imperative to successfully meeting the challenges of future emission regulations and cost constraints is the development of an exhaust system simulation model which offers the ability to sort through major design alternatives quickly while assisting in the interpretation of experimental data. Previously, detailed catalyst models have been developed which require the specification of intricate kinetic mechanisms to determine overall catalyst performance. While yielding extremely valuable results, these models use complex numerical algorithms to solve multiple partial differential equations which are time consuming and occasionally numerically unstable.

In vehicle design, response surface model (RSM) is commonly used as a surrogate of the high fidelity Finite Element (FE) model to reduce the computational time and improve the efficiency of design process. However, RSM introduces additional sources of uncertainty, such as model bias, which largely affect the reliability and robustness of the prediction results. The bias of RSM need to be addressed before the model is ready for extrapolation and design optimization. This paper further investigates the Bayesian inference based model extrapolation method which is previously proposed by the authors, and provides a systematic and integrated stochastic bias corrected model extrapolation and robustness design process under uncertainty. A real world vehicle design example is used to demonstrate the validity of the proposed method.

Manual Materials Handling has been historically recognized as one of the more prevalent causes for work related lost time injuries. Many manufacturing facilities use Material Handling Systems (lift/ tilt tables, hoists, articulated arms), often to alleviate ‘ergonomic’ stressors as well as to optimize production. If not used appropriately, Material Handling Systems can create new ergonomic concerns, or in some cases increase the physical demands of a job. A strategy designed to optimize the fit between the operator, the appropriate equipment and the operation is addressed in this paper.

This paper presents an enhanced Bayesian based model validation method together with probabilistic principal component analysis (PPCA). The PPCA is employed to address multivariate correlation and to reduce the dimensionality of the multivariate functional responses. The Bayesian hypothesis testing is used to quantitatively assess the quality of a multivariate dynamic system. Unlike the previous approach, the differences between test and CAE results are used for dimension reduction though PPCA and then to assess the model validity. In addition, physics-based thresholds are defined and transformed to the PPCA space for Bayesian hypothesis testing. This new approach resolves some critical drawbacks of the previous method and provides desirable properties of a validation method, e.g., symmetry. A dynamic system with multiple functional responses is used to demonstrate this new approach.