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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.

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.

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.

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.

When structures may have dynamic instability complex eigenvalue analysis is a useful tool to predict it. Although the accurate prediction itself is significant, it is also crucial to obtain sensitivity of unstable eigensolutions in order to eliminate instability efficiently. Since the mathematical relationship between stiffness matrix and design variables may seldom be found in reality, finite difference method has been typically used to approximate the sensitivity. The novel way to accurately calculate the sensitivity is developed without implementing finite difference method. This paper shows the advantages of analytical sensitivity analysis compared to other methods for choosing the most important components' eigenvalues. It also provides necessary amount of frequency shift for each chosen components' eigenvalue to eliminate unstable eigenvalues.

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.

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.

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.

In this paper, the formability of AA5754 aluminum laser-welded blanks produced by Nd:YAG laser welding is investigated under biaxial straining conditions. The mechanical behavior of the laser-welded blanks is first examined by uniaxial tensile tests conducted with the weld line perpendicular to the tensile axis. Shear failure in the weld metal is observed in the experiments. Finite element simulations under generalized plane strain conditions are then conducted in order to further understand the effects of weld geometry and strength on the shear failure and formability of these welded blanks. The strain histories of the material elements in the weld metal obtained from finite element computations are finally used in a theoretical failure analysis based on the material imperfection approach to predict the failure strains for the laser-welded blanks under biaxial straining conditions.

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.

Combustion flame geometry calculation is a critical task in the design and analysis of combustion engine chamber. Combustion flame directly influences the fuel economy, engine performance and efficiency. Currently, many of the flame geometry calculation methods assume certain specific chamber and piston top shapes and make some approximations to them. Even further, most methods can not handle multiple spark plug set-ups. Consequently, most of the current flame geometry calculation methods do not give accurate results and have some built-in limitations. They are particularly poor for adapting to any kind of new chamber geometry and spark plug set-up design. This report presents a novel methodology which allows the accurate calculation of flame geometry regardless of the chamber geometry and the number of spark plugs. In this methodology, solid models are used to represent the components within the chamber and unique attributes (colors) are attached respectively to these components.

A regenerative braking model for a parallel Hybrid Electric Vehicle (HEV) is developed in this work. This model computes the line and pad pressures for the front and rear brakes, the amount of generator use depending on the state of deceleration (i.e. the brake pedal position), and includes a wheel lock-up avoidance algorithm. The regenerative braking model has been developed in the symbolic programming environment of MATLAB/SIMULINK/STATEFLOW for downloadability to an actual HEV's control system. The regenerative braking model has been incorporated in NREL's HEV system simulation called ADVISOR. Code modules that have been changed to implement the new regenerative model are described. Resulting outputs are compared to the baseline regenerative braking model in the parent code. The behavior of the HEV system (battery state of charge, overall fuel economy, and emissions characteristics) with the baseline and the proposed regenerative braking strategy are first compared.

Automotive exhaust emission regulations are becoming progressively stricter due to increasing awareness of the hazardous effects of exhaust emissions. The main challenge to meet the regulations is to reduce the emissions during cold starts, because catalytic converters are ineffective until they reach a light-off temperature. It has been found that 50% to 80% of the regulated hydrocarbon and carbon monoxide emissions are emitted from the automotive tailpipe during the cold starts. Therefore, understanding the catalytic converter characteristics during the cold starts is important for the improvement of the cold start performances This paper describes a mathematical model that simulates transient performances of catalytic converters. The model considers the effect of heat transfer and catalyst chemical reactions as exhaust gases flow through the catalyst. The heat transfer model includes the heat loss by conduction and convection.

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.

One of the primary reasons that FMVSS 111 currently requires flat rearview mirrors as original equipment on the driver's side of passenger cars is a concern that convex mirrors might reduce safety by causing drivers to overestimate the distances to following vehicles. Several previous studies of the effects of convex rearview mirrors have indicated that they do cause overestimations of distance, but of much lower magnitude than would be expected based on the mirrors' levels of image minification and the resulting visual angles experienced by drivers. Previous studies have investigated mirrors with radiuses of curvature up to 2000 mm. The present empirical study was designed to investigate the effects of mirrors with larger radiuses (up to 8900 mm). Such results are of interest because of the possible use of large radiuses in some aspheric mirror designs, and because of the information they provide about the basic mechanisms by which convex mirrors affect distance perception.

This paper presents a general control module to control the speed of an electric vehicle (EV). This module consists of a microprocessor and several C-programmable micro-controllers. It uses an identification algorithm to estimate the system parameters on-line. With the estimated parameters, control gains are calculated via pole-placement. In order to compensate for the internal errors, a cross-coupling control algorithm is included. To estimate the true velocity and acceleration from measurements, a discrete-time Kalman filter was utilized. The experimental results validate the general control module for EVs.

The LDH (Limiting Dome Height Test) is widely used at Ford Motor Co. stamping plants laboratories to monitor the formability of incoming sheet materials. Although the LDH test is very easy to implement and interpret, variability of the results and poor reproducibility between laboratories limit its acceptance. In this investigation, some of the causes of variability and differences between plant laboratories are discussed. Much of the experimental work was done at plant laboratories and the results are directly applicable to quality control (QC) machines. It was found that the binder force and the binder shape have a big influence on the results, and they should be carefully controlled. The binder cleaning procedure is also relevant to the test variability. Punch temperature has a much greater influence on QC machines than on research machines and a method for controlling the punch temperature in QC machines is presented.

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.

Mathematical models of the automotive system play a valuable role in forecasting and policy analysis, especially in the public sector. However, poor documentation, lack of adequate model evaluation and unfamiliarity with the data and structural limitations of models suggest the possibility of misuse in such policy applications as fuel economy standards and regulatory impact assessments. Findings are illustrated by analysis of two models: the Wharton EFA Automobile Demand Model and the Sweeney Passenger Car Gasoline Demand Model. In addition, 40 world sector models and studies representing more than 75 countries are summarized.