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The U.S. Environmental Protection Agency’s (EPA’s) Advanced Light-Duty Powertrain and Hybrid Analysis (ALPHA) tool was created to estimate greenhouse gas (GHG) emissions from light-duty vehicles. ALPHA is a physics-based, forward-looking, full vehicle computer simulation capable of analyzing various vehicle types with different powertrain technologies, showing realistic vehicle behavior, and auditing of all energy flows in the model. In preparation for the midterm evaluation (MTE) of the 2017-2025 light-duty GHG emissions rule, ALPHA has been refined and revalidated using newly acquired data from model year 2013-2016 engines and vehicles. The robustness of EPA’s vehicle and engine testing for the MTE coupled with further validation of the ALPHA model has highlighted some areas where additional data can be used to add fidelity to the engine model within ALPHA.

This study uses full drive cycle simulation to compare the fuel consumption of a vehicle with a turbocharged (TC) engine to the same vehicle with an alternative boosting technology, namely, a hybrid supercharger, in which a planetary gear mechanism governs the power split to the supercharger between the crankshaft and a 48 V 5 kW electric motor. Conventional mechanically driven superchargers or electric superchargers have been proposed to improve the dynamic response of boosted engines, but their projected fuel efficiency benefit depends heavily on the engine transient response and driver/cycle aggressiveness. The fuel consumption benefits depend on the closed-loop engine responsiveness, the control tuning, and the torque reserve needed for each technology. To perform drive cycle analyses, a control strategy is designed that minimizes the boost reserve and employs high rates of combustion dilution via exhaust gas recirculation (EGR).

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.

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.

A multi-body dynamics model of the U.S. Army3s High Mobility Multi-purpose Wheeled Vehicle (HMMWV) has been created using commercial software (ADAMS) to simulate and analyze the vehicle3s rollover behavior. However, manual operation of such simulation and analysis for design purposes is prohibitively expensive and time consuming, limiting the engineers3 ability to utilize the model fully and extract from it useful design information in a timely, cost-effective manner. To address this challenge, a commercial system integration and optimization software (OPTIMUS) is utilized in order to automate the simulation processes and to enable the more complex uncertainty-based analysis of the HMMWV rollover behavior under a variety of external conditions. Challenges involved in integrating the software are highlighted and remedies are discussed. Rollover analysis results from using the integrated model and automated simulation are also presented.

Half of the car occupant deaths involved in two-vehicle crashes results from side impact collisions. In an attempt to better understand the role that vehicle mass plays in crashes and injury causation, detailed information from the NASS CDS database on injury source was distributed in three classes: contact with intrusion, contact without intrusion, and restrained acceleration or non-contact. We compared these distributions for belted drivers in side verses frontal crashes. When looking at the type of striking, or bullet, vehicle in near-side impacts, we found that intrusion injuries are more prevalent in cars hit by SUVs and pickups than by other cars. We also looked at the body region injured verses the type of striking vehicle and found head injuries to be slightly more prevalent when the striking vehicle is an SUV or pick-up. Data from the University of Michigan CIREN case studies on side impacts are presented and are consistent with the NASS CDS data.

The Energy Boundary Element Analysis (EBEA) has been utilized in the past for computing the exterior acoustic field at high frequencies (above ∼400Hz) around vehicle structures and numerical results have been compared successfully to test data [1, 2 and 3]. The Energy Finite Element Analysis (EFEA) has been developed for computing the structural vibration of complex structures at high frequencies and validations have been presented in previous publications [4, 5]. In this paper the EBEA is utilized for computing the acoustic field around a vehicle structure due to external acoustic noise sources. The computed exterior acoustic field comprises the excitation for the EFEA analysis. Appropriate loading functions have been developed for representing the exterior acoustic loading in the EFEA simulations, and a formulation has been developed for considering the acoustic treatment applied on the interior side of structural panels.

BACKGROUND: Detailed fatal injury data following fatal motor vehicle crashes (MVC) are necessary to improve occupant safety and promote injury prevention. Autopsy remains the principle source of detailed fatal injury data. However, procedure rates are declining due to a range of technical, ethical and religious concerns. Postmortem computed tomography (PMCT) is a potential alternative or adjunct to autopsy which is increasingly used by forensic researchers. However, there are only limited data regarding the utility of PMCT for analysis of fatal MVC injuries. METHODS: We performed whole body PMCT, autopsy and complete crash reconstruction on 3 subjects fatally injured in MVC in a single county in Michigan. All injuries detected by either PMCT or autopsy were coded using the Abbreviated Injury Scale (AIS). Severe injuries, defined as AIS 3 or higher (AIS 3+), were tallied for each forensic procedure to allow a comparison of relative diagnostic performance.

In this research, off-road vehicle simulation is performed with tire-soil interaction model. The predictive semi-analytical model, which is originally developed for tire-snow interaction model by Lee [4], is applied as a tire-soil interaction model and is implemented to MSC/ADAMS, commercial multi-body dynamic software. It is applied to simulate the handling maneuver of military vehicle HMMWV. Two cases are simulated with Michigan sandy loam soil property. Each case has two maneuvers, straight-line brake and step steer (J-turn). First, tire-soil interaction model and conventional on-road tire model are simulated on the flat road of the same frictional coefficient. The proposed tire-soil interaction model provided larger force under the same slip. Second, the same maneuvers are performed with real off-road frictional coefficient. The proposed tire-soil model can be validated and the behavior of the off-road vehicle can be identified through two simulation cases.

The cooling system of Series Hybrid Electric Vehicles (SHEVs) is more complicated than that of conventional vehicles due to additional components and various cooling requirements of different components. In this study, a numerical model of the cooling system for a SHEV is developed to investigate the thermal responses and power consumptions of the cooling system. The model is created for a virtual heavy duty tracked SHEV. The powertrain system of the vehicle is also modeled with Vehicle-Engine SIMulation (VESIM) previously developed by the Automotive Research Center at the University of Michigan. VESIM is used for the simulation of powertrain system behaviors under three severe driving conditions and during a realistic driving cycle. The output data from VESIM are fed into the cooling system simulation to provide the operating conditions of powertrain components.

Assessments of reach capability using human figure models are commonly performed by exercising each joint of a kinematic chain, terminating in the hand, through the associated ranges of motion. The result is a reach envelope determined entirely by the segment lengths, joint degrees of freedom, and joint ranges of motion. In this paper, the validity of this approach is assessed by comparing the reach envelopes obtained by this method to those obtained in a laboratory study of men and women. Figures were created in the Jack human modeling software to represent the kinematic linkages of participants in the laboratory study. Maximum reach was predicted using the software's kinematic reach-envelope generation methods and by interactive manipulation. Predictions were compared to maximum reach envelopes obtained experimentally. The findings indicate that several changes to the normal procedures for obtaining maximum reach envelopes for seated tasks are needed.

In this paper, a simulation-based dynamic rollover evaluation procedure is described. This work is based on the worst-case methodology developed at the University of Michigan, and is the result of a collaborated research project between the University of Michigan and TRW Inc. The target vehicle studied in this paper is a large production volume SUV. This vehicle is equipped with a production-intent TRW Vehicle Stability Control (VSC) system. The main goals of this paper are to (i) study the rollover propensity of this SUV, as influenced by vehicle and environment parameters such as vehicle speed, road condition, etc.; and (ii) investigate whether, and by how much, does the VSC system influence the rollover propensity of this SUV. The modeling, evaluation procedure, and preliminary evaluation results are reported.

Motion prediction models may give the average reach for an individual of specified characteristics. The actual reach will vary from this reach in a manner that may depend on both systematic and random factors. We describe a modeling approach that incorporates the variability within the reaches of a given subject and that between subjects. This information is useful to designers in investigating phenomena that may not occur during the average reach but may occur during variants such as collision with an obstacle or injury due to over-exertion.

Developing a new technology requires decision-makers to understand the technology's implications on an organization's objectives, which depend on user needs targeted by the technology. If these needs are common between two organizations, collaboration could result in more efficient technology development. For hybrid truck design, both commercial manufacturers and the military have similar performance needs. As the new technology penetrates the truck market, the commercial enterprise must quantify how the hybrid's superior fuel efficiency will impact consumer purchasing and, thus, future enterprise profits. The Army is also interested in hybrid technology as it continues its transformation to a more fuel-efficient force. Despite having different objectives, maximizing profit and battlefield performance, respectively, the commercial enterprise and Army can take advantage of their mutual needs.

NASS 80-88 passenger side impacts data were analyzed. Location of primary car damage using the CDC classification, the AIS for injury severity studies, and the interior contacts of the various body areas. Drivers alone, or with passengers were studied separately in both left and right side crashes. Direct impacts to the passenger compartment only are less frequent than to other CDC side zones. Driver interior contacts vary by body region but also by side impacted in the crash. The presence of an unrestrained front passenger appears to enhance driver injury level in left side crashes but the presence of a passenger, in right side crashes appears to moderate driver injury severity.

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.

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.

The purpose of this study was to use detailed medical information to evaluate thoracic injuries in elderly patients in real world frontal crashes. In this study, we used analytic morphomics to predict the effect of torso geometry on rib fracture, a major source of injury for the elderly. Analytic morphomics extracts body features from computed tomography (CT) scans of patients in a semi-automated fashion. Thoracic injuries were examined in front row occupants involved in frontal crashes from the International Center for Automotive Medicine (ICAM) database. Among these occupants, two age groups (age < 60 yr. [Nonelderly] and age ≥ 60 yr. [Elderly]) who suffered severe thoracic injury were analyzed. Regression analyses were conducted to investigate injury outcomes using variables for vehicle, demographics, and morphomics. Compared to the nonelderly group, the elderly group sustained more rib fractures.

Using the CDC (SAE J224), a comparison of the NASS data and the UMTRI field accident files (UM series) indicates a similar distribution of offset frontal crashes. Offset frontal damage occurs in 56-61% of crashes, often involving more than one third of the front of the car. Lap-shoulder belted drivers sustain more AIS 2 or greater injuries when there is interior intrusion and occur more often when the offset damage is in front of the driver. However, this may well be due to the severity of the crash. European studies have no uniformity as to offset frontal collision descriptors are difficult to interpret, or to compare one to another.

A research effort was initiated to establish an empirical data base and to develop predictive models of normal human in-vehicle seated reaching motions while driving. A driving simulator was built, in which a variety of targets were positioned at typical locations a driver would possibly reach. Reaching motions towards these targets were performed by demographically representative subjects and measured by a state-of-the-art motion analysis system. This paper describes the experiment conducted to collect the movement data, and the new techniques that are being developed to process, analyze, and model the data. Some initial findings regarding the role of torso assistive motion, the effect of speed used in completing a motion on multi-segment dynamic postures, and illustrative results from kinematic modeling are presented.