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Vehicle motions can adversely affect the ability of a driver or occupant to quickly and accurately push control buttons located in many advanced vehicle control, navigation and communications systems. A pilot study was conducted using the U.S. Army Tank Automotive and Armaments Command (TACOM) Ride Motion Simulator (RMS) to assess the effects of vertical ride motion on the kinematics of reaching. The RMS was programmed to produce 0.5 g and 0.8 g peak-to-peak sinusoidal inputs at the seat-sitter interface over a range of frequencies. Two participants performed seated reaching tasks to locations typical of in-vehicle controls under static conditions and with single-frequency inputs between 0 and 10 Hz. The participants also held terminal reach postures during 0.5 to 32 Hz sine sweeps. Reach kinematics were recorded using a 10-camera VICON motion capture system. The effects of vertical ride motion on movement time, accuracy, and subjective responses were assessed.

Current automotive design practices related to driver visibility are based on static laboratory studies of mostly straight ahead viewing that were conducted by Meldrum and others beginning in 1962. These individual studies have never been replicated either in the lab or in actual driving situations to determine the validity of their procedures. After a thorough review of the literature related to driver eye location and a statistical analysis of previous static eye location data, an experimental design is proposed to determine dynamic eye location distribution characteristics. This design will provide information on: (a) the relationship of static anthropometric measurements to dynamic eye location; (b) the difference between dynamic on-the-road eye location versus static in-the-lab eye location distributions: (c) the effect of different types of vehicle seating package parameters on eye location; and, (d) a validation of previous static eye location studies.

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.

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.

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.

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.

Aircraft used for business (executive corporate transportation or personal business) and utility purposes now represent about one-third of the total United States aircraft inventory. Data from accident investigation of business aircraft involved in survivable accidents indicate serious injuries and fatality to the occupants occur most frequently as a result of the unprotected head and neck or chest flailing in contact with aircraft controls, instrument panel, or structure. Improvement of current aircraft to provide increased occupant safety and survival during crash impacts is both necessary and feasible. Design considerations include folding seat back locks to prevent collapse, increased seat tie-down to structure, instrument panels and glare shields designed to absorb energy through structural design and padding, stronger seat structure, lateral protection, design and packaging of knobs and projections to minimize injury in contact, and installation of upper torso restraint.

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.

Effective computer-aided design of engineering systems requires comprehensive computer-application software that conveniently adapts to the particular engineering design considered. This paper discusses the theoretical background and initial experience with a program intended for computer-aided design of machine-like mechanical systems, and outlines the use of a time-shared graphic terminal for schematic display of program output. The program is applicable to three types of mechanical systems: linear and nonlinear unconstrained dynamic systems, kinematic systems (that is, constrained systems), and multifreedom, constrained systems.

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.

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.

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.

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.

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.