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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 current test methods are insufficient to evaluate and ensure the safety and reliability of vehicle system for all possible dynamic situations including the worst cases such as rollover, spin-out and so on. Although the known NHTSA J-turn and Fish-hook steering maneuvers are applied for the vehicle performance assessment, they are not enough to predict other possible worst case scenarios. Therefore, it is crucial to search for the various worst cases including the existing severe steering maneuvers. This paper includes the procedure to search for other useful worst case based upon the existing worst case scenarios in terms of rollover and its application in simulation basis. The human steering angle is selected as a design variable and optimized to maximize the index function to be expressed in terms of vehicle roll angle. The obtained scenarios were enough to generate the worse cases than NHTSA ones.

Warpage is the distortion induced by inhomogeneous shrinkage during injection molding of plastic parts. Uncontrolled warpage will result in dimensional instability and bring a lot of challenges to the mold design and part assembly. Current commercial simulation software for injection molding cannot provide consistently accurate warpage prediction, especially for semi-crystalline thermoplastics. In this study, the root cause of inconsistency in warpage prediction has been investigated by using injection molded polypropylene plaques with a wide range of process conditions. The warpage of injection molded plaques are measured and compared to the numerical predictions from Moldex3D. The study shows that with considering cooling rate effect on crystallization kinetics and using of the improved material model for residual stress calculations, good agreements are obtained between experiment and simulation results.

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 GT-SUITE vehicle-aftertreatment model has been developed to examine the cold-start emissions reduction capabilities of a Vacuum Insulated Catalytic Converter (VICC). This converter features a thermal management system to maintain the catalyst monolith above its light-off temperature between trips so that most of a vehicle’s cold-start exhaust emissions are avoided. The VICC thermal management system uses vacuum insulation around the monoliths. To further boost its heat retention capacity, a metal phase-change material (PCM) is packaged between the monoliths and vacuum insulation. To prevent overheating of the converter during periods of long, heavy engine use, a few grams of metal hydride charged with hydrogen are attached to the hot side of the vacuum insulation. The GT-SUITE model successfully incorporated the transient heat transfer effects of the PCM using the effective heat capacity method.

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.

The implications of restricting axle loads to preserve pavements while at the same time allowing gross combination weights over 80,000 pounds are examined with respect to the design qualities of the types of heavy trucks that might be developed. The proposed vehicles would have more axles than current designs thereby achieving higher gross combination weights with smaller axle loads. Design factors influencing mobility, productivity, preservation of the highway infrastructure, and performance in safety-related maneuvers are discussed.

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.

A round-robin center of gravity height measurement study was conducted to assess current practice in the measurement of the vertical position of the center of gravity (c.g.) of light truck-type vehicles. The study was performed by UMTRI for the Motor Vehicle Manufacturers Association. The laboratories participating in the study were those of Chrysler Corporation, Ford Motor Company, General Motors Corporation, and the National Highway Traffic Safety Administration. The primary objectives of this study were (i) to determine to what extent the differing experimental procedures used by the participating laboratories at the time of the study result in significant differences in the measured vertical position of the center of mass of light truck-type vehicles, and (ii) to gain insight into the physical causes of such differences.

To date, model validation metric is prominently designed for non-dynamic model responses. Though metrics for dynamic responses are also available, they are specifically designed for the vehicle impact application and uncertainties are not considered in the metric. This paper proposes the validation metric for general dynamic system responses under uncertainty. The metric makes use of the popular U-pooling approach and extends it for dynamic responses. Furthermore, shape deviation metric was proposed to be included in the validation metric with the capability of considering multiple dynamic test data. One vehicle impact model is presented to demonstrate the proposed validation metric.

The emerging Variable Valve Timing (VVT) technology complicates the estimation of air flow rate because both intake and exhaust valve timings significantly affect engine's gas exchange and air flow rate. In this paper, we propose to use Artificial Neural Networks (ANN) to model the air flow rate through a 2.4 liter VVT engine with independent intake and exhaust camshaft phasers. The procedure for selecting the network architecture and size is combined with the appropriate training methodology to maximize accuracy and prevent overfitting. After completing the ANN training based on a large set of dynamometer test data, the multi-layer feedforward network demonstrates the ability to represent air flow rate accurately over a wide range of operating conditions. The ANN model is implemented in a vehicle with the same 2.4 L engine using a Rapid Prototype Controller.

In a review of 540 crashes in which the steering-wheel airbag deployed, 38% of the drivers sustained some level of upper extremity injury. The majority of these were AIS-1 injuries including abrasions, contusions and small lacerations. In 18 crashes the drivers sustained AIS-2 or-3 level upper extremity injuries, including fractures of the radius and/or ulna, or of the metacarpal bones, all related to airbag deployments. It was determined that six drivers sustained the fracture(s) directly from the deploying airbag or the airbag module cover. The remaining 12 drivers had fractures from the extremity being flung into interior vehicle structures, usually the instrument panel. Most drivers were taller than 170 cm and, of the 18 drivers, 10 were males.

From our crash investigations of air bag equipped passenger cars, a subset of upper extremity injuries are presented that are related to air bag deployments. Minor hand, wrist or forearm injuries-contusions, abrasions, and sprains are not uncommonly reported. Infrequently, hand fractures have been sustained and, in isolated cases, fractures of the forearm bones or of the thumb and/or adjacent hand. The close proximity of the forearm or hand to the air bag module door is related to most of the fractures identified. Steering wheel air bag deployments can fling the hand-forearm into the instrument panel, rearview mirror or windshield as indicated by contact scuffs or tissue debris or the star burst (spider web) pattern of windshield breakage in front of the steering wheel.

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?

An experimental study is performed for homogeneous charge compression ignition (HCCI) combustion focusing on late phasing conditions with high cyclic variability (CV) approaching misfire. High CV limits the feasible operating range and the objective is to understand and quantify the dominating effects of the CV in order to enable controls for widening the operating range of HCCI. A combustion analysis method is developed for explaining the dynamic coupling in sequences of combustion cycles where important variables are residual gas temperature, combustion efficiency, heat release during re-compression, and unburned fuel mass. The results show that the unburned fuel mass carries over to the re-compression and to the next cycle creating a coupling between cycles, in addition to the well known temperature coupling, that is essential for understanding and predicting the HCCI behavior at lean conditions with high CV.

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.

For the 1997 data year, UMTRI's Center for National Truck Statistics collected data on rear underride as part of its Trucks Involved in Fatal Accidents (TIFA) survey. Data collected included whether the truck had a rear underride guard, whether the striking vehicle underrode the truck, and how much underride occurred. A primary goal was to evaluate rear underride of straight trucks. Overall, 453 medium and heavy trucks were struck in the rear by a nontruck vehicle in a fatal crash in 1997. Some underride occurred in at least 272 (60.0%) of the rear-end crashes. For straight trucks, there was some underride in 77 (52.0%) of the crashes, no underride occurred in 43 (29.1%) of the fatal rear-end crashes, and underride could not be determined in the remaining 28 (18.9%) straight truck rear-end crashes. Despite the fact that three-fourths of tractor combinations had an underride guard on the trailer, underride was more common for tractor combinations.

Advanced features in automotive systems often necessitate the management of complex interactions between subsystems. Existing control strategies are designed for certain levels of robustness, however their performance can unexpectedly deteriorate in the presence of significant uncertainties, resulting in undesirable system behaviors. This limitation is further amplified in systems with complex nonlinear dynamics. Hydro-mechanical clutch actuators are among those systems whose behaviors are highly sensitive to variations in subsystem characteristics and operating environments. In a P2 hybrid propulsion system, a wet clutch is utilized for cranking the engine during an EV-HEV mode switching event. It is critical that the hydro-mechanical clutch actuator is stroked as quickly and as consistently as possible despite the existence of uncertainties. Thus, the quantification of uncertainties on clutch actuator behaviors is important for enabling smooth EV-HEV transitions.

This paper discusses techniques developed and used by the Biosciences Group at the University of Michigan Transportation Research Institute (UMTRI) for measuring three-dimensional head motion, skull bone strain, epidural pressure, and internal brain motion of repressurized cadavers and Rhesus monkeys during head impact. In the experimental design, a stationary test subject is struck by a guided moving impactor of 10 kg (monkeys) and 25 or 65 kg (cadavers). The impactor striking surface is fitted with padding to vary the contact force-time characteristics. The experimental technique uses a nine-accelerometer system rigidly affixed to the skull to measure head motion, transducers placed at specific points below the skull to record epidural pressure, repressurization of both the vascular and cerebrospinal systems, and high-speed cineradiography (at 1000 frames per second) of radiopaque targets.

Developing a complete understanding of the structure and behavior of the near-wall region (NWR) in reciprocating, internal combustion (IC) engines and of its interaction with the core flow is needed to support the implementation of advanced combustion and engine operation strategies, as well as predictive computational models. The NWR in IC engines is fundamentally different from the canonical steady-state turbulent boundary layers (BL), whose structure, similarity and dynamics have been thoroughly documented in the technical literature. Motivated by this need, this paper presents results from the analysis of two-component velocity data measured with particle image velocimetry near the head of a single-cylinder, optical engine. The interaction between the NWR and the core flow was quantified via statistical moments and two-point velocity correlations, determined at multiple distances from the wall and piston positions.