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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Condition monitoring of permanent magnet AC machines for all-electric transportation systems: State of the art

The current state of the art on emerging and efficient techniques for condition monitoring of permanent magnet (PM) alternating-current (AC) machines deployed in electric vehicle (EV) applications is presented. The discussion includes the most common and specific types of faults in PM motors, such as rotor demagnetisation and stator inter-turn faults, respectively. Fault indicators, such as voltage (v s ) and current (i s ) signals and machine signatures based on motor back electromotive force (EMF) (E B ) and magnetic flux (φ), are taken into account as a measuring quantity in diagnosing motor faults. Other signatures, including thermal analysis, acoustic noise, and vibrations, are also illustrated as some of the emerging techniques in estimating the performance of EV motors while under operations. In addition, various fault modelling methods, condition monitoring techniques, and comprehensive approaches applied in diagnosing the effect of machine faults during its incipient stages are illustrated. Since most of the fault diagnostic techniques discussed here include only machine-based quantities as fault indices/indicators, the provided solutions are therefore found to be more reliable and accurate for diagnosing the motor faults. This comprehensive review study is inclusive of the existing fault diagnostic techniques, which are currently employed in industrial and commercial practices, in addition to the new methodologies proposed by the authors. All the given condition monitoring schemes therefore seem significantly vital in estimating the state of health of PM AC machines while under operation in all-electric transportation systems.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2018

Optimal velocity prediction for fuel economy improvement of connected vehicles

With the advancement of vehicle-to-vehicle and vehicle-to-infrastructure technologies, more and more real-time information regarding traffic and transportation system will be available to vehicles. This paper presents the development of a novel algorithm that uses available velocity bounds and powertrain information to generate an optimal velocity trajectory over a prediction horizon. When utilised by a vehicle, this optimal velocity trajectory reduces fuel consumption. The objective of this optimisation problem is to reduce dynamic losses, required tractive force, and completing trip distance with a given travel time. Sequential quadratic programming method is employed for this nonlinearly constrained optimisation problem. When applied to a GM Volt-2, the generated velocity trajectory saves fuel compared to a real-world drive cycle. The simulation results confirm the fuel consumption reduction with the rule-based mode selection and the energy management strategy of a GM Volt 2 model in Autonomie.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2017

Analyzing the threat of unmanned aerial vehicles (UAV) to nuclear facilities

Unmanned aerial vehicles (UAV) are among the major growing technologies that have many beneficial applications, yet they can also pose a significant threat. Recently, several incidents occurred with UAVs violating privacy of the public and security of sensitive facilities, including several nuclear power plants in France. The threat of UAVs to the security of nuclear facilities is of great importance and is the focus of this work. This paper presents an overview of UAV technology and classification, as well as its applications and potential threats. We show several examples of recent security incidents involving UAVs in France, USA, and United Arab Emirates. Further, the potential threats to nuclear facilities and measures to prevent them are evaluated. The importance of measures for detection, delay, and response (neutralization) of UAVs at nuclear facilities are discussed. An overview of existing technologies along with their strength and weaknesses are shown. Finally, the results of a gap analysis in existing approaches and technologies is presented in the form of potential technological and procedural areas for research and development. Furthermore based on this analysis, directions for future work in the field can be devised and prioritized.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Developing Novel Performance Measures for Traffic Congestion Management and Operational Planning Based on Connected Vehicle Data

In this study, the authors present their efforts in exploring a new type of traffic data, referred to as internet-connected vehicle (ICV) data, for traffic congestion management and operational planning. Most currently manufactured vehicles contain onboard GPS and cellular modules, and they constantly connect to automobile manufacturers' clouds via cellular networks and upload their status. Some automobile manufacturers have recently redistributed the nonpersonal part of such data, such as geolocation, to third-party organizations for innovative applications. Compared with the traditional vehicle GPS data, the ICV data contain high-resolution GPS waypoints accompanied with the vehicles' abnormal moving events (e.g., hard braking). The ICV data also have huge potential in congestion management and operational planning. They explore to identify and analyze traffic congestion on both freeways and arterials using the ICV data. The ICV data adopted for this research are redistributed by Wejo Data Service, representing 10%-15% of all moving vehicles in the Dallas-Fort Worth (DFW) area in Texas. Through one case study for a freeway segment and one for an arterial segment, new traffic performance metrics based on the characteristics of ICV data have been presented. The highlights of these efforts are as follows: (I) queue length and propagation at freeway bottlenecks can be directly measured based on where and when most internet-connected vehicles slow down and join the queue; (II) an internet-connected vehicle's actual delay time on arterials can be directly measured according to its slow movement percentage, without assuming the nondelay travel speed; and (III) the ICV data set are also combined with the high-resolution traffic signal events to generate a ground-truth time-space diagram (TSD) on arterials - a common visualization of arterial signal performance for transportation planning and operations.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

A Scale-Dynamic Network Abstraction Approach for Traffic Analysis

The necessary trade-off between accuracy and efficiency of various traffic simulation tools depends on the resolution of the roadway network. While a detailed high-resolution road network could better represent connectivity of real-world road network and ensure an accurate simulation result, a low-resolution network omitting trivial details could reduce computational burden and improve the computational efficiency of traffic simulation. This study focuses on dynamically adjusting the roadway network resolution during the process of simulation-based dynamic traffic assignment (SBDTA) with the objective to expedite both the simulation and the assignment within SBDTA. We propose to divide the whole time horizon into several periods dynamically and to Abstract the network for each period separately. The result showed that half of the CPU time for both the simulation and the assignment is saved, while the network performance remains consistent or near consistent compared with the scenario using the most detailed network.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

A Customizable Metric to Provide a Comprehensive Picture of the Mobility Potential of a Location

Accessibility in a geo-spatial context refers to the ease of reaching a variety of opportunities from a given location. Accessibility theories (and resulting metrics) have traditionally focused on quantifying access to specific opportunities (such as jobs), or focused on specific modes (such as car, bike, etc.). Such approaches often fall short of providing a comprehensive picture of the true accessibility potential of a location as a combination of multiple modes to multiple types of destinations. Addressing this drawback, a novel metric labeled the ‘Mobility Energy Productivity (MEP) Metric’ was developed at the National Renewable Energy Laboratory to quantify the mobility potential of a location to connect people to goods, services, and employment using a variety of modes, while accounting for time, energy, and affordability. The MEP metric has been integrated with advance travel behavior models to compute the changes in mobility potential for various future scenarios, such as introduction of automated vehicles, and/or electric vehicles—but does so at the aggregate, or average-citizen level. The MEP in its initial iteration is not customized to the particular socio-economic contingents, or even to an individual whose modal availability or pattern of trip making may substantially differ from the average. Addressing this gap, this research effort extends the MEP framework from a static state to a more tailored and dynamic state, one in which an individual, or group can customize the metric for their unique characteristics, such as modes, activity patterns, and time-of-day preferences. The extended MEP metric framework can now be integrated to assess the customized mobility energy productivity of an individual.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2022

Concept of Operations of Next-Generation Traffic Control Utilizing Infrastructure-Based Cooperative Perception

This paper provides a system architecture for an infrastructure-based cooperative perception fusion engine for next-generation traffic control. This engine will provide a complete state-space digital representation with measurable accuracy to support a wide-range of applications. The architecture includes inputs, functional flow, data standardization recommendations, outputs, and supported applications. The cooperative perception engine addresses critical needs with respect to accelerating the benefits of automation through intelligent roadway infrastructure, which complements and accelerates connected and automated vehicle (CAV) technology. The cooperative perception acquires and fuses information from sensors (radar, LiDAR, and cameras) and CAVs to perceive roadway traffic states of moving objects, creates a complete 3D digital representation of that state-space, and communicates it to downstream application such as intelligent signal control, safety and energy applications, and cooperate driving applications. The intelligent roadway infrastructure approach, as opposed to a vehicle-centric approach, is more scalable because it can be deployed to the roughly 300,000 signalized intersections more readily than over 300 million vehicles in the United States, and accrues early-stage benefits equitable to all roadway users addressing safety, equity, fuel efficiency, and greenhouse gas reduction.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Quantifying Movement Motivations, Demand, and Inflow-Outflow Dynamics in Four Cities (New York, Chicago, Austin, and San Diego) During COVID-19

The COVID-19 pandemic has impacted a wide range of human activities, from food delivery habits to major moving and travel decisions. Results indicate multiple pandemic-related factors have influenced millions of relocation decisions by Americans (e.g., health risk, financial pressures, more space, and employment), and there are various positive economic and social outcomes of this influence (e.g., remote work and education), enabling more affordable living and opportunity. This paper addresses COVID-19 impacts on mobility, especially involving permanent relocations. Survey design and data analysis with U-Haul targeted customers in Austin, New York, San Diego, and Chicago to understand mobility, new moving dynamics, and motivations.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2022

Sustainability, Scalability, and Resiliency of the Town of Innisfil Mobility-on-Demand Experiment: Preliminary Results, Analyses, and Lessons Learned

In 2017, the town of Innisfil, Ontario, launched Innisfil Transit in partnership with Uber, a transportation network company, to provide a subsidized on-demand public mobility service as an alternative to investing in a new fixed-route bus service. The performance of Innisfil Transit is documented in a 2021 Ryerson University report by Sweet, Mitra, and Benaroya, which shows greater cost effectiveness of the mobility provided over the proposed bus alternative. This paper expands on those findings by assessing Innisfil Transit with respect to sustainability, scalability, and resiliency. First, we quantify the energy and emissions of this program relative to traditional transit and driving alone across varying powertrains. We then characterize a conservative first-order estimate of the percentage of US communities that fall within a similar spatial-demographic tier as Innisfil. Replicability also hinges on service cost and performance in comparison to average values for low-density transit in the US. Lastly, most transit agencies experienced a significant drop in demand (as much as 90%) with slowly rebounding ridership since the onset of the COVID-19 pandemic. The resiliency of the Innisfil program to the pressures induced by the pandemic is examined in comparison to other transit operations. The lessons learned across these three dimensions complement prior work to better understand the efficiency and sustainability of on-demand public mobility service for low-density communities like Innisfil.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Passenger Boarding Station and Curbfront Configuration Concepts for On-Demand Services with Small Automated Vehicles

This paper explores the various configurations of off-line stations and vehicle berthing that have been found to be fundamentally important parameters in the analysis of system performance, operations, and capacity. The proposed automated transit network system concept, which provides a direct ride between a passenger's origin and destination station, is applicable to both fixed guideway automated transit and to systems with self-driving vehicles. Addressed at a conceptual level is the vehicle/station interface in terms of Americans with Disability Act compliance and station capacity concerns. The concept of open-edge platforms monitored by advanced sensing technology combined with artificial intelligence-powered perception for the purpose of protecting passengers from entering the active vehicle lanes is also discussed. Finally, the paper draws initial conclusions on how these station configurations, operational complexities, and associated costs can be better understood through appropriate research and development.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

The Convergence of Vehicle Electrification and Automation - Enabling Sustainable Automated Mobility Districts

The transportation industry is entering a new frontier with three major simultaneous transformations: electrification, automation, and on-demand services. All three directly affect the same spaces of vehicle technology, infrastructure, and system operational performance. Further, each area of change adds its own driving forces of complexity to the others' design challenges. This paper explores these transformations, framing the implications for vehicle technology and infrastructure and their impact on operating concepts and strategies, which in turn impact the sustainability of the transportation infrastructure in the built environment. Specifically, this paper examines battery-electric vehicles operating in a fully automated fleet within an "automated mobility district" (AMD) setting with multiple on-demand services. From this examination, the paper assesses the implications for transportation electrification, comparing and contrasting traditional fixed-route services with those of on-demand transit and automated transit networks, including the trade-offs between vehicle range (battery capacity), charging parameters, power availability, and operations predictability with respect to policy and infrastructure configurations. The paper also addresses the configuration and management of boarding and alighting zones (also called pickup and drop-off zones), and the need for complementary infrastructure intelligence at intersections and curbs. Finally, conclusions are drawn with respect to the system integration and analysis needs for AMDs regarding resilience and sustainability of mobility infrastructure.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Analysis of Automated Transit Network Systems with Battery-Electric Vehicles in Automated Mobility Districts: Preprint

The paper provides an overview of the insights and findings of the National Renewable Energy Laboratory's (NREL) ongoing research on the implementation of automated mobility districts (AMDs). AMD is a term coined by NREL to describe a geographically defined district or major activity center located in a dense urban setting with mobility applications provided by automated/autonomous vehicle (AV) systems spanning internal circulation and first-mile/last-mile connections to regional transportation hubs. Research over the past five years has focused on understanding the evolution of AMDs, beginning with demonstrations of automated shuttles prior to the pandemic, to more integrated on-demand mobility systems currently in initial stages of deployment. Initial insights and findings from earlier studies include the need for designation of a "jurisdiction having authority," a clear vision of a complete system to provide end-to-end mobility services, and the requisite intelligent infrastructure to complement AV technology. NREL's most recent Phase III research investigates station boarding/alighting (curb) issues, the full electrification of fleets, and the need for a systems engineering methodology (SEM) to properly analyze the complexities resulting from the convergence of automation, on-demand mobility, and electrification of the transit systems within the AMD. The paper reviews the findings of AMD research conducted during Phase I, II, and III, with special emphasis on Phase III results with respect to a descriptive example of the proposed SEM when a "digital twin" analytical model is used to simulate the transport fleet's battery-electric vehicle miles of travel and associated duty cycles through a rigorous analytical assessment with a comprehensive modeling process.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Calibrating Microscopic Car-Following Models for Adaptive Cruise Control Vehicles: Multiobjective Approach

Adaptive cruise control (ACC) vehicles are the first step toward comprehensive vehicle automation. However, the impacts of such vehicles on the underlying traffic flow are not yet clear. Therefore, it is of interest to accurately model vehicle-level dynamics of commercially available ACC vehicles so that they may be used in further modeling efforts to quantify the impact of commercially available ACC vehicles on traffic flow. Importantly, not only model selection but also the calibration approach and error metric used for calibration are critical to accurately model ACC vehicle behavior. In this work, we explore the question of how to calibrate car following models to describe ACC vehicle dynamics. Specifically, we apply a multi-objective calibration approach to understand the tradeoff between calibrating model parameters to minimize speed error vs. spacing error. Three different car-following models are calibrated for data from six vehicles. The results are in line with recent literature and verify that targeting a low spacing error does not compromise the speed accuracy whether the opposite is not true for modeling ACC vehicle dynamics.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Improving Resilience of Bus Bunching Holding Strategy through a Rolling Horizon Approach

Providing public transportation with quality service is critical to attracting more passengers to the system. However, high-demand routes are prone to the so-called bus bunching -- a tendency of buses to group as a consequence of variations in travel times and demands. Bus holding is applied to overcome this effect. In this study, we present a novel method for bus holding in which the control law is based only on the buses' position using a computationally efficient rolling horizon approach. The method uses similar inputs as linear control approaches while not increasing significantly the computational time. However, the method overcomes key a weakness of the linear control approach thanks to the explicit constraint handling that always ensures the control action effectiveness. Simulation experiments in a validation case and a model-specific for a bus rapid transit line in Curitiba, Brazil showed a reduced holding time and improved resilience, delivering more than 20% reduction in delay time accounting for the on-board and station delays.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Parking Strategies and Outcomes for Shared Autonomous Vehicle Fleet Operations

Parking spots are a premium commodity, especially in dense downtown settings, so this study examines the service impacts of shared autonomous vehicles (SAVs) parking in legal on- or off-street locations when idle across Travis County in Austin, Texas. Here, using an agent-based activity-based travel demand model with dynamic traffic simulation, two restricted-parking strategies for SAVs were simulated. SAVs either found the nearest available parking spot or the lowest-cost spot (via a tradeoff of parking fees and distance-based costs). Two comparisons were conducted to analyze the impacts of these strategies. First, two restricted parking strategies were compared, where SAVs park without competition with private human-driven vehicles (HVs) for parking locations. Second, a more realistic analysis compared two SAV parking strategies with a scenario where SAVs remain idle in place. Private HVs in all scenarios and strategies of this comparison park at the closest designated location unless they opt for private parking. Using a supply of 8,400 aggregated parking locations in Austin, this study simulated fleet performance under different trip demands, with SAV fares of $\$0.62$ per kilometer ($\$1$ per mile) plus a $\$1$ fixed pickup fee with dynamic ridesharing permitted. Parking costs were negligible in both SAV parking search strategies applied to the Austin network because of the region’s provision of mostly free parking. Requiring SAVs to park on designated on- and off-street parking locations and parking lots (restricted parking) also increased parking costs for HV drivers by up to 22% since SAVs occupied some free parking spaces, especially in the least-cost parking search strategy.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

Probing the failure mechanism of nanoscale LiFePO{sub 4} for Li-ion batteries

LiFePO{sub 4} is a high power rate cathode material for lithium ion battery and shows remarkable capacity retention, featuring a 91% capacity retention after 3300 cycles. In this work, we use high-resolution transmission electron microscopy and electron energy loss spectroscopy to study the gradual capacity fading mechanism of LiFePO{sub 4} materials. We found that upon prolonged electrochemical cycling of the battery, the LiFePO{sub 4} cathode shows surface amorphization and loss of oxygen species, which directly contribute to the gradual capacity fading of the battery. The finding can guide the design and improvement of LiFePO{sub 4} cathode for high-energy and high-power rechargeable battery for electric transportation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Life cycle air quality impacts of conventional and alternative light-duty transportation in the United States

Significance Our assessment of the life cycle air quality impacts on human health of 10 alternatives to conventional gasoline vehicles finds that electric vehicles (EVs) powered by electricity from natural gas or wind, water, or solar power are best for improving air quality, whereas vehicles powered by corn ethanol and EVs powered by coal are the worst. This work advances the current debate over the environmental impacts of conventional versus alternative transportation options by combining detailed spatially and temporally explicit emissions inventories with state-of-the-science air quality impact analysis using advanced chemical transport modeling. Our results reinforce previous findings that air quality-related health damages from transportation are generally comparable to or larger than climate change-related damages.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

Highly efficient nonprecious metal catalyst prepared with metal–organic framework in a continuous carbon nanofibrous network

Fuel cell vehicles, the only all-electric technology with a demonstrated >300 miles per fill travel range, use Pt as the electrode catalyst. The high price of Pt creates a major cost barrier for large-scale implementation of polymer electrolyte membrane fuel cells. Nonprecious metal catalysts (NPMCs) represent attractive low-cost alternatives. However, a significantly lower turnover frequency at the individual catalytic site renders the traditional carbon-supported NPMCs inadequate in reaching the desired performance afforded by Pt. Unconventional catalyst design aiming at maximizing the active site density at much improved mass and charge transports is essential for the next-generation NPMC. We report here a method of preparing highly efficient, nanofibrous NPMC for cathodic oxygen reduction reaction by electrospinning a polymer solution containing ferrous organometallics and zeolitic imidazolate framework followed by thermal activation. The catalyst offers a carbon nanonetwork architecture made of microporous nanofibers decorated by uniformly distributed high-density active sites. In a single-cell test, the membrane electrode containing such a catalyst delivered unprecedented volumetric activities of 3.3 A∙cm -3 at 0.9 V or 450 A∙cm -3 extrapolated at 0.8 V, representing the highest reported value in the literature. Improved fuel cell durability was also observed.

30 DIRECT ENERGY CONVERSION↗