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Understanding in-use fleet operating behavior is of paramount importance when evaluating the potential of advanced/alternative vehicle technologies. Accurately characterizing real world vehicle operation assists in properly allocating advanced technologies, playing a role in determining initial payback period and return on investment. In addition, this information contributes to the design and deployment of future technologies as the result of increased awareness regarding tractive power requirements associated with typical operating behavior. In this presentation, the concept of vehicle duty cycles and their relation to advanced technologies will be presented and explored. Additionally, current research attempts to characterize school bus operation will be examined, and existing computational analysis and evaluation tools associated with these efforts discussed. Presenter Adam Duran, National Renewable Energy Laboratory

The combined anticipated trends of vehicle sharing (ride-hailing), automated control, and powertrain electrification are poised to disrupt the current paradigm of predominately owner-driven gasoline vehicles with low levels of utilization. Shared, automated, electric vehicle (SAEV) fleets offer the potential for lower cost and emissions and have garnered significant interest among the research community. While promising, unmanaged operation of these fleets may lead to unintended negative consequences. One potentially unintended consequence is a high quantity of SAEVs charging during peak demand hours on the electric grid, potentially increasing the required generation capacity. This research explores the flexibility associated with charging loads demanded by SAEV fleets in response to servicing personal mobility travel demands. Travel demand is synthesized in four major United States metropolitan areas: Detroit, MI; Austin, TX; Washington, DC; and Miami, FL.

Debris in the Orbiter crew compartment of early Shuttle missions created crew health concerns and physiological discomfort, and was the cause of some equipment malfunctions. Debris from Orbiters during flight and processing was analyzed, quantized, and evaluated to determine its source. Records were kept on the amount of debris vacuumed by the crew during on-orbit cleaning and the amount found on air-cooled avionics boxes during ground turnaround. After ground turnaround operations at Kennedy Space Center and Palmdale were reviewed from a facility, materials use, and materials control standpoint, the following remedial steps were taken.

The emergence of connected and automated vehicles and smart cities technologies create the opportunity for new mobility modes and routing decision tools, among many others. To achieve maximum mobility and minimum energy consumption, it is critical to understand the energy cost of decisions and optimize accordingly. The Route Energy prediction model (RouteE) enables accurate estimation of energy consumption for a variety of vehicle types over trips or sub-trips where detailed drive cycle data are unavailable. Applications include vehicle route selection, energy accounting and optimization in transportation simulation, and corridor energy analyses, among others. The software is a Python package that includes a variety of pre-trained models from the National Renewable Energy Laboratory (NREL). However, RouteE also enables users to train custom models using their own data sets, making it a robust and valuable tool for both fast calculations and rigorous, data-rich research efforts.

NASA-JSC is evaluating planetary mission scenarios where plants will provide the majority of the diet for the crew. The requirements of both plants and crew diet need to be integrated in the development of the final food system. Plant growth has limitations in type and quantity of crops to be produced while diets must meet palatability and nutritional requirements as well as limited processing labor, equipment and power. A plan is presented for the development of a food system based heavily on grown crops. Although the steps taken in the development are applicable to the design of any long duration flight food system. The process begins with the development of a food list, followed by preliminary menu design, nutritional analysis and finally menu testing.

Neural networks are massively parallel computational models for knowledge representation and information processing. The capabilities of neural networks, namely learning, noise tolerance, adaptivity, and parallel structure make them good candidates for application to a wide range of engineering problems including diagnostics problems. The general approach in developing neural network based diagnostic methods is described through a case study. The development of an acoustic wayside train inspection system using neural networks is described. The study is aimed at developing a neural network based method for detection defective wheels from acoustic measurements. The actual signals recorded when a train passes a wayside station are used to develop a neural network based wheel defect detector and to study its performance. Signal averaging and scoring techniques are developed to improve the performance of the constructed neural inspection system.

Current vehicle climate control systems are dramatically overpowered because they are designed to condition the cabin air mass in a specified period of time. A more effective and energy efficient objective is to directly achieve thermal comfort of the passengers. NREL is developing numerical and experimental tools to predict human thermal comfort in non-uniform transient thermal environments. These tools include a finite element model of human thermal physiology, a psychological model that predicts both local and global thermal comfort, and a high spatial resolution sweating thermal manikin for testing in actual vehicles.

With support from the U.S. Department of Energy's Vehicle Technologies Office, the National Renewable Energy Laboratory developed BLAST-V-the Battery Lifetime Analysis and Simulation Tool for Vehicles. The addition of high-resolution spatial-temporal travel histories enables BLAST-V to investigate user-defined infrastructure rollouts of publically accessible charging infrastructure, as well as quantify impacts on vehicle and station owners in terms of improved vehicle utility and station throughput. This paper presents simulation outputs from BLAST-V that quantify the utility improvements of multiple distinct rollouts of publically available Level 2 electric vehicle supply equipment (EVSE) in the Seattle, Washington, metropolitan area. Publically available data on existing Level 2 EVSE are also used as an input to BLAST-V. The resulting vehicle utility is compared to a number of mock rollout scenarios.

High strength materials have desirable mechanical properties but often cannot be machined economically, which results in unacceptably high finished component cost. MADI™ (machinable austempered ductile iron) overcomes this difficultly and provides the highly desirable combination of high strength, excellent low temperature toughness, good machinability and attractive finished component cost. The Machine Tool Systems Research Laboratory at the University of Illinois at Urbana-Champaign performed extensive machinability testing and determined the appropriate tools, speeds and feeds for milling and drilling (https://netfiles.uiuc.edu/malkewcz/www/MADI.htm). This paper provides the information necessary for the efficient and economical machining of MADI™ and provides comparative machinability data for common grades of ductile iron (EN-GJS-400-18, 400-15, 450-10, 500-7, 600-3 & 700-2) for comparison.

Conceptual designs for a space suit Personal Life Support Subsystem (PLSS) were developed and assessed to determine if upgrading the system using new, emerging, or projected technologies to fulfill basic functions would result in mass, volume, or performance improvements. Technologies were identified to satisfy each of the functions of the PLSS in three environments (zero-g, Lunar, and Martian) and in three time frames (2006, 2010, and 2020). The viability of candidate technologies was evaluated using evaluation criteria such as safety, technology readiness, and reliability. System concepts (schematics) were developed for combinations of time frame and environment by assigning specific technologies to each of four key functions of the PLSS -- oxygen supply, waste removal, thermal control, and power. The PLSS concepts were evaluated using the ExtraVehicular Activity System Sizing Analysis Tool, software created by NASA to analyze integrated system mass, volume, power and thermal loads.

Current vehicle climate control systems are dramatically overpowered because they are designed to condition the cabin air mass in a specified period of time. A more effective and energy efficient objective is to directly achieve thermal comfort of the passengers. NREL is developing numerical and experimental tools to predict human thermal comfort in non-uniform transient thermal environments. These tools include a finite element model of human thermal physiology, a psychological model that predicts both local and global thermal comfort, and a high spatial resolution sweating thermal manikin for testing in actual vehicles.

Wheat is a candidate crop for the Advanced Life Support (ALS) system, and cereal grains and their products will be included on long-term space missions beyond low earth orbit. While the exact supply scenario has yet to be determined, some type of post-processing of these grains must occur if they are shipped as bulk ingredients or grown on site for use in foods. Understanding the requirements for processing grains in space is essential for incorporating the process into the ALS food system. The ESM metric developed by NASA describes and compares individual system impact on a closed system in terms of a single parameter, mass. The objective of this study was to compare the impact of grain mill type on the ESM of producing yeast and flat breads. Hard red spring wheat berries were ground using a Brabender Quadrumat Jr. or the Kitchen-Aid grain mill attachment (both are proposed post-harvest technologies for the ALS system) to produce white and whole wheat flour, respectively.

As demand for consumer electric vehicles (EVs) has drastically increased in recent years, manufacturers have been working to bring heavy-duty EVs to market to compete with Class 6-8 diesel-powered trucks. Many high-profile companies have committed to begin electrifying their fleet operations, but have yet to implement EVs at scale due to their limited range, long charging times, sparse charging infrastructure, and lack of data from in-use operation. Thus far, EVs have been disproportionately implemented by larger fleets with more resources. To aid fleet operators, it is imperative to develop tools to evaluate the electrification potential of heavy-duty fleets. However, commercially available tools, designed mostly for light-duty vehicles, are inadequate for making electrification recommendations tailored to a fleet of heavy-duty vehicles.

In the United States, intercity long-haul trucks idle approximately 1,800 hrs per year primarily for sleeper cab hotel loads, consuming 838 million gallons of diesel fuel [1]. The U.S. Department of Energy's National Renewable Energy Laboratory (NREL) is working on solutions to this challenge through the CoolCab project. The objective of the CoolCab project is to work closely with industry to design efficient thermal management systems for long-haul trucks that keep the cab comfortable with minimized engine idling. Truck engine idling is primarily done to heat or cool the cab/sleeper, keep the fuel warm in cold weather, and keep the engine warm for cold temperature startup. Reducing the thermal load on the cab/sleeper will decrease air conditioning system requirements, improve efficiency, and help reduce fuel use. To help assess and improve idle reduction solutions, the CoolCalc software tool was developed.

The Equivalent System Mass (ESM) metric developed by NASA describes and compares individual system impact on a closed system in terms of a single parameter, mass. The food system of a Mars mission may encompass a large percentage of total mission ESM, and decreasing this ESM would be beneficial. Yeast breads were made using three methods (hand & oven, bread machine, mixer with dough hook attachment & oven). Flat breads were made using four methods (hand & oven, hand & griddle, mixer with dough hook attachment & oven, mixer with dough hook attachment & griddle). Two formulations were used for each bread system (scratch ingredients, commercial mix). ESM was calculated for each of these scenarios. The objective of this study was to compare the ESM of yeast and flat bread production for a Martian surface outpost. Method (equipment) for both types of bread production was demonstrated to be the most significant influence of ESM when one equipment use was assumed.

ROPS-TEST is a newly developed, interactive, graphics program that may be used to simulate testing of roll bars. Cross-sections that it currently supports include solid rectangular, rectangular tubing, and circular tubing. ROPS-TEST can be used to simulate testing for crush, rear and side loading. Output from ROPS-TEST includes load-deflection and strain energy-deflection plots. ROPS-TEST does not replace actual testing of prototype roll bars. Rather it serves as a design tool to select the best design options for a particular application prior to actual testing of the prototype roll bars.

Fleet managers need a tool to assist them in assessing their need to comply with EPAct and to provide them with the ability to obtain information that will allow them to make alternative fuel vehicle purchasing decisions. This paper will describe the Web-based tool that will inform a fleet manager, based on their geographic location, the type of fleet they own or operate, and the number and types of vehicles in their fleet, whether or not they need to meet the requirements of EPAct, and, if so, the percentage of new vehicle purchases needed to comply with the law. The tool provides detailed specifications on available OEM alternative fuel vehicles, including the purchase cost of the vehicles, fuel and fuel system characteristics, and incentives and rebates surrounding the purchase of each vehicle. The full set of federal, state, and local incentives is made available through the tool, as well as detailed access to refueling site and dealership locations.