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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.

Effects of impact velocity on the crush behavior of aluminum 5052-H38 honeycomb specimens are investigated by experiments. An impact test machine using pressurized nitrogen was designed to perform dynamic crush tests. A test fixture was designed such that inclined loads can be applied to honeycomb specimens in dynamic crush tests. The results of dynamic crush tests indicate that the effects of impact velocity on the normal and inclined crush strengths are significant. The trends of the inclined crush strengths for specimens with different in-plane orientation angles as functions of impact velocity are very similar to that of the normal crush strength. Experimental results show similar progressive folding mechanisms for honeycomb specimens under pure compressive and inclined loads. Under inclined loads, the inclined stacking patterns were observed. The inclined stacking patterns are due to the asymmetric locations of the horizontal plastic hinge lines.

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.

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.

This analytical study examined the potential benefits of applying two embodiments of adaptive lighting to the U.S. and European low-beam patterns: curve lighting that involves shifting the beam horizontally into the curve, and motorway lighting that involves shifting the beam vertically upward. The curve lighting simulations paired 240-m radius left and right curves with a horizontal shift of 10°, and 80-m radius curves with a horizontal beam shift of 15°. The motorway lighting simulations involved upward aim shifts of 0.25° and 0.5°. For both curve and motorway lighting, changes in both seeing and glare illuminance were considered. Market-weighted model year 2000 U.S. and European beam patterns were used. We conclude that curve lighting, as simulated here, would substantially improve seeing performance on curves for both types of beams. On right curves (but not on left curves) there would be an increase in disability glare for oncoming traffic.

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.

Expansion chambers are widely used in the breathing systems of engines due to their desirable broadband noise attenuation characteristics. Following an earlier analytical and computational work of Sahasrabudhe et al. (1992), the present study investigates the effect of the length on the acoustic attenuation performance of concentric expansion chambers. Three approaches are employed to determine the transmission loss: (1) a two-dimensional, axisymmetric analytical solution; (2) a three-dimensional computational solution based on the boundary element method; and (3) experiments on an extended impedance tube setup with nine expansion chambers fabricated with fixed inlet and outlet ducts, fixed chamber diameters, and varying chamber length to diameter ratios from to 3.53. The results from all three approaches are shown to agree well. The effect of multi-dimensional propagation is discussed in comparison with the classical treatment for the breakdown of planar waves.

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.

ADRPM (Acoustic Detection Range Prediction Model) is a software program that models the propagation of acoustic energy through the atmosphere and evaluates detectable distance. ADRPM predicts the distance of detection for a noise source based on the acoustic signature of the source. The acoustic signature of a vehicle is computed by combining BEA and EBEA computations with nearfield measurements. The computed signature is utilized as the input to ADRPM. Once the initial detection range is predicted the main contributors to the acoustic detection are identified by ADRPM and their location on the vehicle is modified in order to assess the corresponding effect to the detectable distance of the vehicle.

A laboratory test reactor has been used to determine the rates of oxidation of carbon monoxide (CO), hydrocarbons (HCs) as a class, and hydrogen (H2). The feed was supplied from the exhaust of a single-cylinder engine, with additions of H2 and CO in some runs. The test reactor was designed to be well mixed, and this was verified experimentally for mixing on macroscopic and microscopic scales. Wall effects were found to be unimportant. Kinetic data from 157 runs were correlated with global reaction rate expressions containing Arrhenius temperature dependence and power law concentration dependence. CO oxidation was found to be approximately 1/4 order in CO with an activation energy of 28,200 cal/g-mole. HC oxidation was found to be approximately 1/4 order in HC and 1/2 order in each of O2, CO, and NO with an activation energy of 29,800 cal/g-mole. H2 oxidation rates were not well correlated, but a zero-order rate with an activation energy of 52,000 cal/g-mole is reasonable.