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The hybrid Finite Element Analysis (hybrid FEA) has been developed for performing structure-borne computations in automotive vehicle structures [1, 2 and 3]. The hybrid FEA method combines conventional FEA with Energy FEA (EFEA). Conventional FEA models are employed for modeling the behavior of the stiff members in a system. Appropriate damping and spring or mass elements are introduced in the connections between stiff and flexible members in order to capture the presence of the flexible members during the analyses of the stiff ones. The component mode synthesis method is combined with analytical solutions for determining the driving point conductance at joints between stiff and flexible members and for defining the properties of the concentrated elements which represent the flexible members when analyzing the stiff components.

Some of the best teaching methods are laboratory courses in which students experience application of the principles being presented. Preparing young engineering students for a career in the automotive industry challenges us to provide comparable opportunities to explore the dynamic performance of motor vehicles in a controlled environment. Today we are fortunate to have accurate and easy-to-use software programs making it practical for students to simulate the performance of motor vehicles on “virtual” proving grounds. At the University of Michigan the CarSim® vehicle dynamics simulation program has been introduced as such a tool to augment the learning experience. The software is used in the Automotive Engineering course to supplement homework exercises analyzing acceleration, braking, aerodynamics, and cornering performance. This paper provides an overview of the use of simulation in this setting.

An accurate air flow rate model is critical for high-quality air-fuel ratio control in Spark-Ignition engines using a Three-Way-Catalyst. Emerging Variable Valve Timing technology complicates cylinder air charge estimation by increasing the number of independent variables. In our previous study (SAE 2004-01-3054), an Artificial Neural Network (ANN) has been used successfully to represent the air flow rate as a function of four independent variables: intake camshaft position, exhaust camshaft position, engine speed and intake manifold pressure. However, in more general terms the air flow rate also depends on ambient temperature and pressure, the latter being largely a function of altitude. With arbitrary cam phasing combinations, the ambient pressure effects in particular can be very complex. In this study, we propose using a separate neural network to compensate the effects of altitude on the air flow rate.

The transient cone angle of pressure swirl sprays from injectors intended for use in gasoline direct injection engines was measured from 2D Mie scattering images. A variety of injectors with varying nominal cone angle and flow rate were investigated. The general cone angle behavior was found to correlate well qualitatively with the measured fuel line pressure and was affected by the different injector specifications. Experimentally measured modulations in cone angle and injection pressure were forced on a comprehensive spray simulation to understand the sensitivity of pulsating injector boundary conditions on general spray structure. Ignoring the nozzle fluctuations led to a computed spray shape that inadequately replicated the experimental images; hence, demonstrating the importance of quantifying the injector boundary conditions when characterizing a spray using high-fidelity simulation tools.

Near-term energy policy for ground transportation is likely to have a strong focus on both gains in efficiency as well as the use of alternate fuels; as both can reduce crude oil dependence and carbon loading on the environment. Stratified-charge spark-ignition direct-injection (SIDI) engines are capable of achieving significant gains in efficiency. In addition, these engines are likely to be run on alternative fuels. Specifically, lower alcohols such as ethanol and iso-butanol, which can be produced from renewable sources. SIDI engines, particularly the spray-guided variant, tend to be very sensitive to mixture preparation since fuel injection and ignition occur within a short time of each other. This close spacing is necessary to form a flammable mixture near the spark plug while maintaining an overall lean state in the combustion chamber. As a result, the physical properties of the fuel have a large effect on this process.

Sound attenuation and flow loss reduction are often two competing demands in vehicle breathing systems. The present study considers a full vehicle exhaust system and investigates both the sound attenuation and the flow performance of production configurations including the catalyst, the resonator, and the muffler. Dynamometer experiments have been conducted with a firing Ford 3.0L, V-6 engine at wide-open throttle with speeds ranging from 1000 to 5000 rpm. Measurements including the flow rates, the temperatures and the absolute dynamic pressures of the hot exhaust gases at key locations (upstream and downstream of every component) with fast-response, water-cooled piezo-resistive pressure transducers facilitate the calculation of acoustic performance of each component, as well as the determination of flow losses caused by these elements and their influence on the engine performance.

Resonant frequencies of a resonant bending system with notched crankshaft sections are obtained experimentally and numerically in order to investigate the effect of notch depth on the drop of the resonant frequency of the system. Notches with the depths ranging from 1 to 5 mm, machined by an EDM (Electrical-Discharging Machining) system, were introduced in crankshaft sections at the fillet between the main crank pin and crank cheek. The resonant frequencies of the resonant bending system with the crankshaft sections with various notch depths were first obtained from the experiments. Three-dimensional finite element models of the resonant bending system with the crankshafts sections with various notch depths are then generated. The resonant frequencies based on the finite element computations are in good agreement with those based on the experimental results.

Support Vector Machines (SVMs) have been gaining popularity as classifiers with good generalization ability. In an attempt to study their applicability to typical automotive problems, this paper investigates the modeling of the operating envelope for a direct injection gasoline (GDI) engine. This envelope defines the admissible ranges for key engine operating variables so that specified conditions on engine roughness and misfire are satisfied. The SVM model of the operating envelope is subsequently used by the engine control strategy to set engine operating variables such as spark and injection timing to avoid excessive engine roughness and misfire. Findings and conclusions from this study related to generalization ability and complexity of the SVM classifier models are summarized.

Posture selection during standing exertions is a complex process involving tradeoffs between muscle strength and balance. Bodyweight utilization reduces the amount of upper-body strength required to perform a high force push/pull exertion but shifts the center-of-gravity towards the limits of the functional stability region. Thus balance constraints limit the extent to which bodyweight can be used to generate push/pull forces. This paper examines a two-handed sagittal plane pulling exertion performed during a battery maintenance task on a member of the family of medium-sized tactical vehicles (FMTV). Percent capable strength predictions and functional balance capabilities were determined for various two-handed pulling postures using the University of Michigan's 3D Static Strength Prediction Program (3DSSPP). Through this simulation study, preferred postures that minimize joint torques while maintaining balance were identified.

Simulation of human motions in virtual environments is an essential component of human CAD (Computer-aided Design) systems. In our earlier SAE papers, we introduced a novel motion simulation approach termed Memory-based Motion Simulation (MBMS). MBMS utilizes existing motion databases and predicts novel motions by modifying existing ‘root’ motions through the use of the motion modification algorithm. MBMS overcomes some limitations of existing motion simulation models, as 1) it simulates different types of motions on a single, unified framework, 2) it simulates motions based on alternative movement techniques, and 3) like real humans, it can learn new movement skills continually over time. The current study evaluates the prediction accuracy of MBMS to prove its utility as a predictive tool for computer-aided ergonomics. A total of 627 whole-body one-handed load transfer motions predicted by the algorithm are compared with actual human motions obtained in a motion capture experiment.

Resistance spot welding (RWS) guns driven by servomotors instead of pneumatic cylinders are called servo guns. They bring many new features to RWS process. In this study, the influences of servo guns on RSW process are systematically investigated based on comparative experiments. In addition, the costs of servo guns are also analyzed. The long-term applications of servo guns will be cost effective due to their technical features and savings on pneumatic systems although the acquisition cost of servo guns is high. Therefore, servo gun is an excellent alternative RSW machine for sheet metal assembly.

This paper describes a computer simulation of the front suspension of a 1973 Chevrolet Malibu using the ADAMS (Automatic Dynamic Analysis of Mechanical Systems) computer program. The model was proposed by the SAE Fatigue Design and Evaluation Committee for evaluating the speed, economy and accuracy of various computer simulations in predicting displacements and loads in a suspension system. A comparison between experimental and simulated results is given.

Workstation design is one of the most essential components of proactive ergonomics, and digital human models have gained increasing popularity in the analysis and design of current and future workstations (Chaffin 2001). Using digital human technology, it is possible to simulate interactions between humans and current or planned workstations, and conduct quantitative ergonomic analyses based on realistic human postures and motions. Motion capture has served as the primary means by which to acquire and visualize human motions in a digital environment. However, motion capture only provides motions for a specific person performing specific tasks. Albeit useful, at best this allows for the analysis of current or mocked-up workstations only. The ability to subsequently modify these motions is required to efficiently evaluate alternative design possibilities and thus improve design layouts.

In a laboratory study and in a mathematical modeling effort, we evaluated the effects of rearview mirror reflectivity on older and younger subjects' seeing ability under conditions designed to simulate night driving with headlamp glare present in the mirror. Rearview mirror reflectivity was varied while observers were required to detect both rearward stimuli seen through the mirror and forward stimuli seen directly. Lower reflectivity resulted in improved ability to see forward and reduced ability to see to the rear. The reduction in ability to see to the rear was much larger than the improvement in forward seeing. The results of the modeling and the laboratory study were in broad agreement, although there were some significant discrepancies. Although the present results cannot be used to make specific recommendations for rearview mirror reflectivity, they suggest that the reduction in rearward vision as reflectivity is lowered should be considered carefully.

This paper presents the real time implementation of detection filters for the diagnosis of incipient failures in electronically controlled internal combustion (IC) engines. The detection filters are implemented in a production vehicle. Recent results [1] have demonstrated the feasibility of a model-based failure detection and isolation (FDI) methodology for detecting partially failed components in electronically controlled vehicle subsystems. The present paper describes the real time application of the FDI concept to the detection of faults in sensors associated with the engine/controller In a detection filter, the performance of the engine/controller system is continuously compared to a prediction based on sensor measurements and an analytical model (typically a control model) of the system. Any discrepancy between actual and predicted performance is analyzed to identify the unique failure signatures related to specific system components.

A semi-empirical engine piston/ring assembly friction model based on the concept of the Stribeck diagram and similarity analysis is described. The model was constructed by forming non-dimensional parameters based on design and operating conditions. Friction data collected by the Fixed-Sleeve method described in [1]* at one condition, were used to correlate the coefficient of friction of the assembly and the other non-dimensional parameters. Then, using the instantaneous cylinder pressure as input together with measured and calculated design and operating parameters, reasonable assembly friction and fmep predictions were obtained for a variety of additional conditions, some of which could be compared with experimental values. Model inputs are component dimensions, ring tensions, piston skirt spring constant, piston skirt thermal expansion, engine temperatures, speed, load and oil viscosity.

Direct injection of natural gas under high pressure conditions has emerged as a promising option for improving engine fuel economy and emissions. However, since the gaseous injection technology is new, limited experience exists as to the optimum configuration of the injection system and associated combustion chamber design. The present study uses KIVA-3 based, multidimensional modeling to improve the understanding and assist the optimization of the gaseous injection process. Compared to standard k-ε models, a Renormalization Group Theory (RNG) based k-ε model [1] has been found to be in better agreement with experiments in predicting gaseous penetration histories for both free and confined jet configurations. Hence, this validated RNG model is adopted here to perform computations in realistic engine geometries.

Compact heat exchangers have been widely used in various applications in thermal fluid systems including automotive thermal management systems. Radiators for engine cooling systems, evaporators and condensers for HVAC systems, oil coolers, and intercoolers are typical examples of the compact heat exchangers that can be found in ground vehicles. Among the different types of heat exchangers for engine cooling applications, cross flow compact heat exchangers with louvered fins are of special interest because of their higher heat rejection capability with the lower flow resistance. In this study, a predictive numerical model for the cross flow type heat exchanger with louvered fins has been developed based on the thermal resistance concept and the finite difference method in order to provide a design and development tool for the heat exchanger. The model was validated with the experimental data from an engine cooling radiator.

A quasi-dimensional, multi-zone, direct injection (DI) diesel combustion model has been developed and implemented in a full cycle simulation of a turbocharged engine. The combustion model accounts for transient fuel spray evolution, fuel-air mixing, ignition, combustion and NO and soot pollutant formation. In the model, the fuel spray is divided into a number of zones, which are treated as open systems. While mass and energy equations are solved for each zone, a simplified momentum conservation equation is used to calculate the amount of air entrained into each zone. Details of the DI spray, combustion model and its implementation into the cycle simulation of Assanis and Heywood [1] are described in this paper. The model is validated with experimental data obtained in a constant volume chamber and engines. First, predictions of spray penetration and spray angle are validated against measurements in a pressurized constant volume chamber.

Interference between physical objects in the workspace and the moving human body may cause serious problems, including errors in manual operation, physical damage and trauma from the collision, and increased biomechanical stresses due to movement reorganization for avoiding the obstacles. Therefore, a computer algorithm to detect possible collisions and simulate human motions to avoid obstacles will be an important tool for computer-aided ergonomics and optimization of system design in the early stage of a design process. In the present study, we present a method of modifying motions for obstacle avoidance when the object intrudes near the center of the planned motion. We take the motion modification approach, as we believe that for a certain class of obstacle avoidance problems, a person would modify a pre-planned motion that would result in a collision to a new one that is collision-free, as opposed to organizing a totally unique motion pattern.