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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.

The Kinematic Analysis Methods Computer Program that has been used by Ford Motor Co. to evaluate mechanisms for the past four years has been modified to generate performance curves for windshield wiper linkages directly using a Calcomp Plotter. Problems such as stalling, “jerky” operation, and excessive phase lag between wipers can be detected early in the design stages by careful evaluation of the curves.

The current ability of the Virtual Aerodynamic/ Aeroacoustic Wind Tunnel to predict interior vehicle sound pressure levels is demonstrated using an automobile model which has variable windshield angles. This prediction method uses time-averaged flow solutions from a lattice gas CFD code coupled with wave number-frequency spectra for the various flow regimes to calculate the side window vibration from which the sound pressure level spectrum at the driver's ear is determined. These predictions are compared to experimental wind tunnel data. The results demonstrate the ability of this methodology to correctly predict wind noise spectral trends as well as the overall loudness at the driver's ear. A more sophisticated simulation method employing the same lattice gas code is investigated for prediction of the time-accurate flow field necessary to compute the actual side glass pressure spectra.

A laboratory wear test is used to evaluate the wear protection properties of new and used engine oils formulated for FFV service. Laboratory-blended mixtures of these oils with methanol and water have also been tested. The test consists of a steel ball rotating against three polished cast iron discs. Oil samples are obtained at periodic intervals from a fleet of 3.0L Taurus vehicles operating under controlled go-stop conditions. To account for the effects of fuel dilution, some oils are tested before and after a stripping procedure to eliminate gasoline, methanol and other volatile components. In addition to TAN and TBN measurements, a capillary electrophoresis technique is used to evaluate the formate content in the oils. The results suggest that wear properties of used FFV lubricants change significantly with their degree of usage.

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.

A test cell was developed for evaluating a 6-speed automatic transmission. The target vehicle had an internal combustion 5.4L gasoline V8 engine. An electric dynamometer was used to closely simulate the engine characteristics. This included generating mean torque from the ECU engine map, with a transient capability of 10,000 rpm/second. Engine inertia was simulated with a transient capability of 20,000 rpm/second, and torque pulsation was simulated individually for each piston, with a transient capability of 50,000 rpm/second. Quantitative results are presented for the correlation between the engine driven and the dynamometer driven transmission performance over more than 60 test cycles. Concerns about using the virtual engine in validation testing are discussed, and related to the high frequency transient performance required from the electric dynamometer. Qualitative differences between the fueled engine and electric driven testing are presented.

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.

There is a pressing need to develop accurate and robust approaches for predicting vehicle speed to enhance fuel economy/energy efficiency, drivability and safety of automotive vehicles. This paper details outcomes of research into various methods for the prediction of vehicle velocity. The focus is on short-term predictions over 1 to 10 second prediction horizon. Such short-term predictions can be integrated into a hybrid electric vehicle energy management strategy and have the potential to improve HEV energy efficiency. Several deterministic and stochastic models are considered in this paper for prediction of future vehicle velocity. Deterministic models include an Auto-Regressive Moving Average (ARMA) model, a Nonlinear Auto-Regressive with eXternal input (NARX) shallow neural network and a Long Short-Term Memory (LSTM) deep neural network. Stochastic models include a Markov Chain (MC) model and a Conditional Linear Gaussian (CLG) model.

The 2013 Ford Fusion will be launched with an optional automatic engine start-stop feature. To realize engine start-stop on a vehicle equipped with a conventional powertrain, there are two major challenges in the vehicle system controls. First, the propulsive torque delivery from a stopped engine has to be fast. The vehicle launch delay has to be minimized such that the corporate vehicle attributes can be met. Second, the fuel economy improvement offered by this technology has to justify the cost associated with it. In pursuing fuel economy, the driver's comfort and convenience should be minimally impacted. To tackle these challenges, a vehicle system control strategy has been developed to accurately interpret the driver's intent, monitor the vehicle subsystem's power demands, schedule engine automatic stop and re-start, and coordinate the fast and smooth torque delivery to the wheels.

Throttle tip-in/tip-out maneuvers generate a driveline torque transient which may produce an objectionable disturbance to vehicle occupants. Recent developments in vehicle design have contributed to increased severity in this response, which is known as clunk and shuffle. This paper describes experimental procedures which have been developed to quantify response levels and diagnose cases of concern. These techniques are useful for developing engine control systems which require transient strategies that differ greatly from those required for steady state operation. In addition, specific design and calibration modifications, which control clunk and shuffle, are described.

Mcity at the University of Michigan in Ann Arbor provides a realistic off-roadway environment in which to test vehicles and drivers in complex traffic situations. It is intended for testing of various levels of vehicle automation, from advanced driver assistance systems (ADAS) to fully self-driving vehicles. In a recent human factors study of interfaces for teen drivers, we performed parallel experiments in a driving simulator and Mcity. We implemented driving scenarios of moderate complexity (e.g., passing a vehicle parked on the right side of the road just before a pedestrian crosswalk, with the parked vehicle partially blocking the view of the crosswalk) in both the simulator and at Mcity.

Traditional reliability assessment methods based on physical testing can require prohibitively large sample sizes in many applications. This has led manufacturers to employ virtual testing using CAE models in place of physical testing. However, when the CAE models are not valid, the resulting reliability assessment may be unreliable. In this paper we develop theory and methodology in which traditional physical testing can be used in conjunction with CAE models to create a new type of accelerated testing that requires smaller sample sizes than traditional test plans while exhibiting robustness with respect to inaccuracies in the CAE models. These test plans are implemented by physically testing a biased sample of products and employing a variance reduction technique such as importance sampling. The CAE model is used as a prior belief for failure probability from which one can derive the sampling plan which minimizes the variance.

The purpose of this study was to determine the optimal location of the shoulder belts for a suspender style four-point safety belt system. This optimal location must satisfy two conditions. First, the shoulder belts must properly fit over the occupant’s shoulders for safety performance. Second, the shoulder belts location on the occupant’s body must be acceptable to the occupant. To determine the optimal acceptable location of the shoulder belts, forty-four subjects were recruited by height and tested in a reconfigurable test seat. The results showed that avoiding an interaction between the shoulder belts and the occupant’s neck improved the acceptability of the system. Variables that affected this interaction included the horizontal and vertical position of the shoulder belts and the occupant’s weight, clothing, and gender.

Intake and exhaust valve control has been combined with engine calibration control by an on-board computer to achieve a Variable Displacement Engine with improved BSFC during part throttle operation. The advent of the on-board computer, with its ability to provide integrated algorithms for the fast accurate flexible control of the entire powertrain, has allowed practical application of the valve disabler mechanism. The engine calibration basis and the displacement selection criteria are discussed, as are the fuel economy, emissions and behavior of a research vehicle on selected drive cycles ( Metro, Highway and Steady State ). Additionally, the impact upon vehicle driveability and other related subsystems ( e.g., transmission ) is addressed.

Locations of key body segments of Hybrid III dummies used in FMVSS 208 compliance tests and NCAP tests were measured and subjected to statistical analysis. Mean clearance dimensions and their standard deviations for selected body segments of driver and passenger occupants with respect to selected vehicle surfaces were determined for several classes of vehicles. These occupant locations were then investigated for correlation with impact responses measured in crash tests and by using a three dimensional human-dummy mathematical model in comparable settings. Based on these data, the importance of some of the clearance dimensions between the dummy and the vehicle surfaces was determined. The study also compares observed Hybrid III dummy positions within selected vehicles with real world occupant positions reported in published literature.

As vehicle tailpipe emission levels decrease with improvements in emission control technology and reformulation of gasolines, exhaust hydrocarbon levels begin to approach the levels in ambient air. Hydrocarbon speciation at these low levels requires high sensitivity capillary gas chromatography methods. In this study, a mixture of “synthetic” exhaust was prepared at two concentration levels (approximately 5 ppm C and 10 ppm C), and was analyzed by the widely-used Auto/Oil Air Quality Improvement Research Program (AQIRP) Phase II (gas chromatography) speciation method with a sensitivity of 0.005 ppm C for individual species. The mixture at each concentration level, along with a sample of ambient air, was analyzed a total of 20 times on 10 separate days over a 2½ week period. Concentrations of total hydrocarbons (HCs) and individual species (using the AQIRP library) were measured; averages and standard deviations were calculated.

The Human Motion Simulation Framework is a hierarchical set of algorithms for physical task simulation and analysis. The Framework is capable of simulating a wide range of tasks, including standing and seated reaches, walking and carrying objects, and vehicle ingress and egress. In this paper, model predictions for the terminal postures of standing object transfer tasks are compared to data from 20 subjects with a wide range of body dimensions. Whole body postures were recorded using optical motion capture for one-handed and two-handed object transfers to target destinations at three angles from straight ahead and three heights. The hand and foot locations from the data were input to the HUMOSIM Framework Reference Implementation (HFRI) in the Jack human modeling software. The whole-body postures predicted by the HFRI were compared to the measured postures using a set of measures selected for their importance to ergonomic analysis.

The worldwide automotive industry is currently preparing for a market introduction of hydrogen-fueled powertrains. These powertrains in fuel cell electric vehicles (FCEVs) offer many advantages: high efficiency, zero tailpipe emissions, reduced greenhouse gas footprint, and use of domestic and renewable energy sources. To realize these benefits, hydrogen vehicles must be competitive with conventional vehicles with regards to fueling time and vehicle range. A key to maximizing the vehicle's driving range is to ensure that the fueling process achieves a complete fill to the rated Compressed Hydrogen Storage System (CHSS) capacity. An optimal process will safely transfer the maximum amount of hydrogen to the vehicle in the shortest amount of time, while staying within the prescribed pressure, temperature, and density limits. The SAE J2601 light duty vehicle fueling standard has been developed to meet these performance objectives under all practical conditions.

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.