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Longevity is one of the great achievements of the twentieth century. This paper will explore ways that elderly people can employ technology to enhance their independence, loosely termed “ElderTech.” ElderTech is designed to establish a sustained, long-term investment in research and development (R&D) for technologies that can provide the largest growing population, Americans over the age of 65, with the tools to ensure active aging (maintaining independence, self-reliance, and an enhanced quality of life). It will also promote aging in place (in the home); and will address and ease Medicare's financial burden on the federal government. ElderTech is aimed to establish a technology framework that will ensure that the United States (U.S.) is ready to meet the needs of its older Americans.

This paper presents a simple method of using Voronoi partitions for estimating vehicle fuel economy from a limited set of engine operating conditions. While one of the overarching goals of engine research is to continually improve vehicle fuel economy, evaluating the impact of a change in engine operating efficiency on the resulting fuel economy is a non-trivial task and typically requires drive cycle simulations with experimental data or engine model predictions and a full suite of engine controllers over a wide range of engine speeds and loads. To avoid the cost of collecting such extensive data, proprietary methods exist to estimate fuel economy from a limited set of engine operating conditions. This study demonstrates the use of Voronoi partitions to cluster and quantize the fuel consumed along a complex trajectory in speed and load to generate fuel consumption estimates based on limited simulation or experimental results.

An optimal energy management strategy (Optimal EMS) can yield significant fuel economy (FE) improvements without vehicle velocity modifications. Thus it has been the subject of numerous research studies spanning decades. One of the most challenging aspects of an Optimal EMS is that FE gains are typically directly related to high fidelity predictions of future vehicle operation. In this research, a comprehensive dataset is exploited which includes internal data (CAN bus) and external data (radar information and V2V) gathered over numerous instances of two highway drive cycles and one urban/highway mixed drive cycle. This dataset is used to derive a prediction model for vehicle velocity for the next 10 seconds, which is a range which has a significant FE improvement potential. This achieved 10 second vehicle velocity prediction is then compared to perfect full drive cycle prediction, perfect 10 second prediction.

CFD (Computational Fluid Dynamics) has been used to analyze vehicle air flow. In cross wind conditions an asymmetrical flow field around the vehicle is present. Under these circumstances, in addition to the forces present with symmetric air flow (drag and lift forces and pitching moment), side forces and moments (rolling and yawing) occur. Issues related to fuel economy, driveability, sealing effects (caused by suction exerted on the door), structural integrity (sun roof, spoiler), water management (rain deposit), and dirt deposit (shear stress) have been investigated. Due to the software developments and computer hardware improvements, results can be obtained within a reasonable time frame with excellent accuracy (both geometry and analytical solution). The flow velocity, streamlines, pressure field, and component forces can be extracted from the analysis results through visualization to identify potential improvement areas.

The search for improvements in occupant protection under vehicle impact is hampered by a real lack of reliable biomechanical data. To help fill this void, General Motors has initiated joint research with independent researchers such as the School of Medicine, U. C. L. A. – in this case to study localized head and facial trauma — and has developed such unique laboratory tools as “Tramasaf,” a human-simulating headform, and “MetNet,” a pressure-sensitive metal foam. Research applied directly to product design also has culminated in developments such as the Side-Guard Beam for side impact protection.

Growing environmental concerns and stringent vehicle emissions regulations has created an urge in the automotive industry to move towards electrified propulsion systems. Reducing and eliminating the emission from public transportation vehicles plays a major role in contributing towards lowering the emission level. Battery electric buses are regarded as a type of promising green mass transportation as they provide the advantage of less greenhouse gas emissions per passenger. However, the electric bus faces a problem of limited range and is not able to drive throughout the day without being recharged. This research studies a public bus transit system example which servicing the city of Ann Arbor in Michigan and investigates the impact of different electrification levels on the final CO2 reduction. Utilizing models of a conventional diesel, hybrid electric, and battery electric bus, the CO2 emission for each type of transportation bus is estimated.

This study is a joint development project between Chrysler Corporation and CFD Research Corporation. The objective of this investigation was to develop a 3D computational flow and heat transfer model for a vehicle windshield de-icing process. The windshield clearing process is a 3D transient, multi-medium, multi-phase heat exchange phenomenon in connection with the air flow distribution in the passenger compartment. The transient windshield de-icing analysis employed conjugate heat transfer methodology and enthalpy method to simulate the velocity distribution near the windshield inside surface, and the time progression of ice-melting pattern on the windshield outside surface. The comparison between the computed results and measured data showed very reasonable agreement, which demonstrated that the developed analysis tool is capable of simulating the vehicle cold room de-icing tests.

Sheet metal forming of automobile body panel consists of two processes performed in series: binder forming and punch forming. Due to differences in deformation characteristics of the two forming processes, their analysis methods are different. The binder wrap surface shape and formed part shape are calculated using different mathematical models and different finite element codes, e.g., WRAPFORM and PANELFORM, respectively. The output of the binder forming analysis may not be directly applicable to the subsequent punch forming analysis. Interpolation, or approximation, of the calculated binder wrap surface geometry is needed. This surface representation requirement is carried out using computer aided geometric design tools. This paper discusses the use of such a tool, SURFPLAN, to link WRAPFORM and PANELFORM calculations.

A research scheme and preliminary results of a pilot study concerning upper body coordination in reach movements is presented. Techniques for multi-joint arm movements were used to obtain the kinematics of each body segment in reach movements to targets spatially distributed in a horizontal plane. Further understanding of the control mechanisms associated with coordination is investigated by combining the information of gaze orientation and body segment movements during reach activities. The implicit sequence of body segments in reach movement can be derived from their kinematic characteristics. Moreover, an identification of phases composing a reach movement is attempted.

This SAE EDGE Research Report explores the many legal issues raised by the advent of automated vehicles. While promised to bring major changes to our lives, there are significant legal challenges that have to be overcome before they can see widespread use. A century’s worth of law and regulation were written with only human drivers in mind, meaning they have to be amended before machines can take the wheel. Everything from key federal safety regulations down to local parking laws will have to shift in the face of AVs. This report undertakes an examination of the AV laws of Nevada, California, Michigan, and Arizona, along with two failed federal AV bills, to better understand how lawmakers have approached the technology. States have traditionally regulated a great deal of what happens on the road, but does that still make sense in a world with AVs? Would the nascent AV industry be able to survive in a world with fifty potential sets of rules?

This SAE EDGE™ Research Report explores how the deployment of automated vehicles (AVs) will affect the insurance industry and the principles of liability that underly the structure of insurance in the US. As we trade human drivers for suites of sensors and computers, who (or what) is responsible when there is a crash? The owner of the vehicle? The automaker that built it? The programmer that wrote the code? Insurers have over 100 years of experience and data covering human drivers, but with only a few years’ worth of information on AVs – how can they properly predict the true risks associated with their deployment? Without an understanding of the nature and risks of AVs, how can the government agencies that regulate the insurance industry provide proper oversight? Do the challenges AVs present require a total reworking of our insurance and liability systems, or can our current structures be adapted to fit them with minor modifications?

Digital human models (DHM) are now widely used to assess worker tasks as part of manufacturing simulation. With current DHM software, the simulation engineer or ergonomist usually makes a manual estimate of the likely worker standing location with respect to the work task. In a small number of cases, the worker standing location is determined through physical testing with one or a few workers. Motion capture technology is sometimes used to aid in quantitative analysis of the resulting posture. Previous research has demonstrated the sensitivity of work task assessment using DHM to the accuracy of the posture prediction. This paper expands on that work by demonstrating the need for a method and model to accurately predict worker standing location. The effect of standing location on work task posture and the resulting assessment is documented through three case studies using the Siemens Jack DHM software.

Historically, the long development time required to produce a new automobile has meant that the electronics in that vehicle might lag the state-of-the-art by several years. For traditional vehicle electronics, this was certainly an appropriate delay, ensuring through extensive testing and qualification that the quality and reliability of the electronic systems met rigorous standards. However, with the growing consumer-oriented electronics content in today's vehicles, it is becoming more difficult for the automotive manufacturers to meet consumers' expectations with older technology. Couple this with the fast-paced consumer product cycle, typically nine to eighteen and the result is increasing pressure on the vehicle manufacturers from after-market electronics suppliers, who can update their product lines as fast as the component manufacturers can produce new models.

Plenoptic particle tracking velocimetry (PTV) shows great potential for three-dimensional, three-component (3D3C) flow measurement with a simple single-camera setup. It is therefore especially promising for applications in systems with limited optical access, such as internal combustion engines. The 3D visualization of a plenoptic imaging system is achieved by inserting a micro-lens array directly anterior to the camera sensor. The depth is calculated from reconstruction of the resulting multi-angle view sub-images. With the present study, we demonstrate the application of a plenoptic system for 3D3C PTV measurement of engine-like air flow in a steady-state engine flow bench. This system consists of a plenoptic camera and a dual-cavity pulsed laser. The accuracy of the plenoptic PTV system was assessed using a dot target moved by a known displacement between two PTV frames.

A computer code for predicting cooling air flow through the radiator and the condenser has been developed. The Reynolds-averaged Navier-Stokes equations, together with the porous flow model for the radiator and the condenser, were solved to simulate front end air flow and the engine compartment flow simultaneously. These transport equations were discretized based on a finite-volume method in a transformed domain. The computational results for a simplified engine compartment showed overall flow information, such as the cooling air flow through the radiator and the condenser, the effects of an air dam, and the effects of fresh air vents near the top of the radiator and the condenser. Comparison of the available experimental data with the analysis showed excellent prediction of the cooling air flow through the radiator and the condenser.

Suspension design is influenced by many factors, especially by vehicle dynamics performance in ride, handling and durability. In the global automotive industry it is common to “customize” or tune suspension parameters so that a vehicle is more acceptable to a different customer base and in a different driving environment. This paper seeks to objectively quantify certain aspects of tuning via ride optimization, taking account of market differences in road surface spectral properties and loading conditions. A computationally efficient methodology for suspension optimization is developed using stochastic techniques. A small (B-class) vehicle is chosen for the study and the following main suspension parameters are selected for optimization - spring stiffness, damping rate and vertical tire stiffness. The road is characterized as a stationary random process, using scaling and shaping filters representative of comparable roads in India and the USA.

The potential of digital human modeling to improve the design of products and workspaces has been limited by the time-consuming manual manipulation of figures that is required to perform simulations. Moreover, the inaccuracies in posture and motion that result from manual procedures compromise the fidelity of the resulting analyses. This paper presents a new approach to the control of human figure models and the analysis of simulated tasks. The new methods are embodied in an algorithmic framework developed in the Human Motion Simulation (HUMOSIM) laboratory at the University of Michigan. The framework consists of an interconnected, hierarchical set of posture and motion modules that control aspects of human behavior, such as gaze or upper-extremity motion. Analysis modules, addressing issues such as shoulder stress and balance, are integrated into the framework.

Extending engine-oil-change intervals is of interest from the standpoint of reducing used oil disposal and reducing time and expense of maintenance. However, the oil must be changed before serious oil degradation and engine damage occur. Three variables which influence oil degradation were chosen for investigation: base oil composition (synthetic oil versus mineral oil), trip length (short trips versus long trips), and driving schedule (degrading an oil during a given type of service, then changing to another type of service without an intervening oil change). Analysis of oil samples taken throughout the testing program indicated that type of service (freeway compared to short trip) influenced oil degradation to a greater extent than oil type. That is, API SG-quality synthetic oil in short-trip service degraded faster than borderline SG-quality mineral oil in long-trip service.

Possible mechanisms for smoke formation in the diesel engine are discussed. Emphasis is placed on the effects of some engine and fuel factors on carbon formation during the course of combustion, including cetane number, fuel volatility, air charge temperature, and after-injection. The tests were made with a single-cylinder, open chamber research engine, with three fuels, covering a wide range of inlet air temperatures and pressures. There is evidence that smoke intensity increased with increase in the cetaine number of the fuels with inlet air temperatures near atmospheric. Increase in the air charge temperature caused an increase in smoke intensity for volatile fuels and had an opposite effect on less volatile fuels for the open chamber engine used. The smoke intensity was found to increase dramatically with after-injection, with all other parameters kept constant. The concept that flame cooling is the main cause for smoke formation is examined.