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The interaction of fuel sprays and in-cylinder flow in direct-injection engines is expected to alter kinetic energy and integral length scales at least during some portions of the engine cycle. High-speed particle image velocimetry was implemented in an optical four-valve, pent-roof spark-ignition direct-injection single-cylinder engine to quantify this effect. Non-firing motored engine tests were performed at 1300 RPM with and without fuel injection. Two fuel injection timings were investigated: injection in early intake stroke represents quasi-homogenous engine condition; and injection in mid compression stroke mimics the stratified combustion strategy. Two-dimensional crank angle resolved velocity fields were measured to examine the kinetic energy and integral length scale through critical portions of the engine cycle. Reynolds decomposition was applied on the obtained engine flow fields to extract the fluctuations as an indicator for the turbulent flow.

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 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.

This paper reports the development of a model of diesel combustion and NO emissions, based on a modified eddy dissipation concept (EDC), and its implementation into the KIVA-3V multidimensional simulation. The EDC model allows for more realistic representation of the thin sub-grid scale reaction zone as well as the small-scale molecular mixing processes. Realistic chemical kinetic mechanisms for n-heptane combustion and NOx formation processes are fully incorporated. A model based on the normalized fuel mass fraction is implemented to transition between ignition and combustion. The modeling approach has been validated by comparison with experimental data for a range of operating conditions. Predicted cylinder pressure and heat release rates agree well with measurements. The predictions for NO concentration show a consistent trend with experiments. Overall, the results demonstrate the improved capability of the model for predictions of the combustion process.

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.

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.

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.

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.

The spark process has previously been shown to heavily influence ignition stability, particularly in direct-injected gasoline engines. Despite this influence, few studies have addressed spark behavior in direct-injected engines. This study examines the role of environmental factors on the behavior of the spark. Through measurement of the spark duration, by way of the ignition current trace, several observations are made on the influence of external factors on the behavior of the spark. Changing the level of nitrogen in the cylinder (to simulate EGR), the level of wetting and velocity imparted by the spray, the ignition dwell time and the orientation of the ground strap, observations are made as to which conditions are likely to produce unfavorable (shorter) spark durations. Through collection of a statistically significant number of sample spark lengths under each condition, histograms have been assembled and compared under each case.

Cam-phasing is increasingly considered as a feasible Variable Valve Timing (VVT) technology for production engines. Additional independent control variables in a dual-independent VVT engine increase the complexity of the system, and achieving its full benefit depends critically on devising an optimum control strategy. A traditional approach relying on hardware experiments to generate set-point maps for all independent control variables leads to an exponential increase in the number of required tests and prohibitive cost. Instead, this work formulates the task of defining actuator set-points as an optimization problem. In our previous study, an optimization framework was developed and demonstrated with the objective of maximizing torque at full load. This study extends the technique and uses the optimization framework to minimize fuel consumption of a VVT engine at part load.

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.

The distribution of fuel-air mixtures in many L-head engines is not homogeneous. If local mixture is too rich or lean, incomplete combustion occurs. This can play a major role in unburned hydrocarbon and carbon monoxide emissions. Fuel-air mixture distribution depends on in-cylinder swirl and turbulence and is directly related to intake manifold configuration, fuel delivery system design and combustion chamber shape. Understanding the spatial mixture distribution may help improve the design of these aforementioned components. Consequently, a more complete combustion process may result, and emissions reduced. A method that measures the emission of CH and C2 radicals via the use of an optical fiber bundle was used in this research to map the mixture uniformity in the combustion chamber. The intensity ratio (IC2/ICH) was correlated to the fuel-air equivalence ratio. The mixture distribution measured was then correlated with the hydrocarbon emission sequence.

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.

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.

Five small two-stroke engine designs were tested at different air/fuel ratios, under steady state and transient cycles. The effects of combustion chamber design, carburetor design, lean burning, and fuel composition on performance, hydrocarbon and carbon monoxide emissions were studied. All tested engines had been designed to run richer than stoichiometric in order to obtain satisfactory cooling and higher power. While hydrocarbon and carbon monoxide emissions could be greatly reduced with lean burning, engine durability would be worsened. However, it was shown that the use of a catalytic converter with acceptably lean combustion was an effective method of reducing emissions. Replacing carburetion with in-cylinder fuel injection in one of the engines resulted in a significant reduction of hydrocarbon and carbon monoxide emissions.