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When performing vibration analysis of complex vehicle structures, it is often important to be able to evaluate the effects of design changes in one or more substructures (e.g., for design optimization). It may also be convenient to allow different components to be modeled independently by different groups or organizations. For both cases, it is inevitable that some substructures will have non-matching finite element meshes at the interface where they are physically connected. Thus, a key challenge is to be able to handle the dynamic assembly of components with non-matching meshes and the subsequent global vibration analysis in a systematic and efficient manner. To tackle this problem, the enhancement of component mode synthesis methods for handling finite element models partitioned into non-matching substructures is considered in this paper. Some existing methods are reviewed, and new methods are developed.

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.

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.

This paper analyzes and compares reactor and engine behavior of a diesel oxidation catalyst (DOC) in the presence of conventional diesel exhaust and low temperature premixed compression ignition (PCI) diesel exhaust. Surrogate exhaust mixtures of n-undecane (C11H24), ethene (C2H4), CO, O2, H2O, NO and N2 are defined for conventional and PCI combustion and used in the gas flow reactor tests. Both engine and reactor tests use a DOC containing platinum, palladium and a hydrocarbon storage component (zeolite). On both the engine and reactor, the composition of PCI exhaust increases light-off temperature relative to conventional combustion. However, while nominal conditions are similar, the catalyst behaves differently on the two experimental setups. The engine DOC shows higher initial apparent HC conversion efficiencies because the engine exhaust contains a higher fraction of trappable (i.e., high boiling point) HC.

The feature of offered algorithm is that it allows, without record and analysis of the display diagram, to estimate a running cycle of a diesel engine parameters which characterize ecological and economic performances. The mathematical model described in report allows to determine connection of coefficient of filling, pressure and temperature of air boost, factor of excess of air with effectiveness ratio of combustion and contents of soot in exhaust gas and to take into account this connection at a choice initial data for control fuel feed or for elaboration of diesel engine dynamic model. The algorithm incorporated, for example, in the microcontroller of an electronic fuel feed controller allows analyzing the sensors data and theoretically determine of smoke amount in the exhaust gases for chosen cycle of fuel feed. The restriction of smoke is possible by criterion dD/dGT, where D - contents of soot in exhaust gas and GT - fuel cycle submission under the program-adaptive schema.

A summary of the design and development process for a Formula SAE engine is described. The focus is on three fundamental elements on which the entire engine package is based. The first is engine layout and displacement, second is the fuel type, and third is the air induction method. These decisions lead to a design around a 4-cylinder 600cc motorcycle engine, utilizing a turbocharger and ethanol E-85 fuel. Concerns and constraints involved with vehicle integration are also highlighted. The final design was then tested on an engine dynamometer, and finally in the 2007 M-Racing FSAE racecar.

The greatest demand facing the automotive industry has been to provide safer vehicles with high fuel efficiency at minimum cost. Current automotive vehicle structures have one fundamental handicap: a short crumple zone for crash energy absorption. This leaves limited room for further safety improvement, especially for high-speed crashes. Breakthrough technologies are needed. One potential breakthrough is to use active devices instead of conventional passive devices. An innovative inflatable bumper concept [1], called the “I-bumper,” is being developed by the authors for crashworthiness and safety of military and commercial vehicles. The proposed I-bumper has several active structural components, including a morphing mechanism, a movable bumper, two explosive airbags, and a morphing lattice structure with a locking mechanism that provides desired rigidity and energy absorption capability during a vehicular crash.

In the I-bumper (inflatable bumper) concept [1], two explosive airbags are released just before the main body-to-body crash in order to absorb the kinetic energy of colliding vehicles. The release also actuates other components in the I-bumper, including a movable bumper and an energy absorption morphing lattice structure. A small explosive charge will be used to deploy the airbag. A conventional airbag model will be used to reduce the crash energy in a controlled manner and reduce the peak impact force. An analytic model of the explosive airbag is developed in this paper for the I-bumper system and for its optimal design, while the complete system design (I-bumper) will be discussed in a separate paper. Analytical formulations for an explosive airbag will be developed and major design variables will be identified. These are used to determine the required amount of explosive and predict airbag behavior, as well to predict their impact on the I-bumper system.

Computer Aided Engineering (CAE) has been successfully utilized in automotive industries. CAE numerically estimates the performance of automobiles and proposes alternative ideas that lead to the higher performance without building prototypes. Most automotive designers, however, cannot directly use CAE due to the sophisticated operations. In this paper, we propose a new breed of CAE, First Order Analysis (FOA), for automotive body designers. The basic ideas include (1) graphic interfaces using Microsoft/Excel to achieve a product oriented analysis (2) use of mechanics of materials to provide the useful information for designs, (3) the topology optimization method using function oriented elements. Further, some prototypes of software are presented to confirm the method for FOA presented here.

A formulation that accounts for manufacturing variability in the analysis of structural/acoustic systems is presented. The methodology incorporates the concept of fast probability integration with finite element (FEA) and boundary element analysis (BEA) for producing the probabilistic acoustic response of a structural/acoustic system. The advanced mean value method is used for integrating the system probability density function. FEA and BEA are combined for producing the acoustic response that constitutes the performance function. The probabilistic acoustic response is calculated in terms of a cumulative distribution function. The new methodology is used to illustrate the difference between the results from a probabilistic analysis that accounts for manufacturing uncertainty, and an equivalent deterministic simulation through applications. The probabilistic computations are validated by comparison to Monte Carlo simulations.

A hybrid electric vehicle simulation tool (HE-VESIM) has been developed at the Automotive Research Center of the University of Michigan to study the fuel economy potential of hybrid military/civilian trucks. In this paper, the fundamental architecture of the feed-forward parallel hybrid-electric vehicle system is described, together with dynamic equations and basic features of sub-system modules. Two vehicle-level power management control algorithms are assessed, a rule-based algorithm, which mainly explores engine efficiency in an intuitive manner, and a dynamic-programming optimization algorithm. Simulation results over the urban driving cycle demonstrate the potential of the selected hybrid system to significantly improve vehicle fuel economy, the improvement being greater when the dynamic-programming power management algorithm is applied.

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.

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.

Advances in electronic countermeasures for lane-change crashes, including both camera-based rear vision systems and object-detection systems, have provided more options for meeting driver needs than were previously available with rearview mirrors. To some extent, human factors principles can be used to determine what countermeasures would best meet driver needs. However, it is also important to examine sets of crash data as closely as possible for the information they may provide. We review previous analyses of crash data and attempt to reconcile the implications of these analyses with each other as well as with general human factors principles. We argue that the data seem to indicate that the contribution of blind zones to lane-change crashes is substantial.

Although biomechanics models can predict the stress on the musculoskeletal system, they cannot predict how the muscle load associated with exertion is perceived. The short-term goal of the present study was to model the perception of effort in lifting and reaching tasks. The long-term goal is to determine the correlation between objective and subjective measures of effort and use this information to predict fatigue or the risk of injury. Lifting and reaching tasks were performed in seated and standing situations. A cylindrical object and a box were moved with one hand and two hands, respectively, from a home location to shelves distributed in the space around the subject. The shoulder and torso effort required to perform these tasks were rated on a ten point visual analog scale.

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.

This paper assesses the potential for car and light truck fuel economy improvements by 2010-15. We examine a range of refinements to body systems and powertrain, reflecting current best practice as well as emerging technologies such as advanced engine and transmission, lightweight materials, integrated starter-generators, and hybrid drive. Engine options are restricted to those already known to meet upcoming California emissions standards. Our approach is to apply a state-of-art vehicle system simulation model to assess vehicle fuel economy gains and performance levels. We select a set of baseline vehicles representing five major classes - Small and Standard Cars, Pickup Trucks, SUVs and Minivans - and analyze design changes likely to be commercially viable within the coming decade. Results vary by vehicle type.

Experiments to obtain the failure loads of spot welds are first reviewed under combined opening and shear loading conditions. A failure criterion is then presented for spot welds under combined opening and shear loading conditions based on the results from the experiments and a lower bound limit load analysis. In order to account for spot welds under more complex loading conditions, another lower bound limit load solution is presented to characterize the failure loads of spot welds under combinations of three forces and three moments. Based on the limit load solution, an engineering failure criterion is proposed with correction factors determined by different spot weld tests. The engineering failure criterion can be used to characterize the failure loads of spot welds with consideration of the effects of sheet thickness, nugget radius and combinations of loads.

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.

Night vision enhancement systems (NVES), which use infrared (IR) cameras, are designed to supplement the visibility provided by standard headlamps. There are two main NVES systems: active, near infrared (NIR) systems, which require an IR source but give a complete picture of the scene in front of the driver, and passive, far infrared (FIR) systems, which do not need an IR source but only enhance relatively warm objects (such as people and animals). There are three main display alternatives: a head-up display (HUD) superimposed on the direct view of the road, a HUD just above the dashboard but separated from the direct view, and a conventional display somewhere in the dashboard. This paper analyzes what a NVES should do to improve night visibility based on night crash statistics, driver vision and visibility conditions in night driving, driver tasks and behavior, and the options offered by various technological approaches. Potential problems with using NVES are also discussed.