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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Federal Automotive Statistical Tool: Updates to EVSE Reporting (Federal Electric Vehicle Agency Round-table, October 2023) [Slides]

This presentation presents an overview of coming changes to how federal agencies with motor vehicles will submit required information about the electric vehicle supply equipment (EVSE) inventory and planned deployments through the Federal Automotive Statistical Tool (FAST). This presentation is intended for delivery via WebEx/GoToMeeting at the October 2023 meeting of the DOE-organized Federal Electric Vehicle Agency Round-table (FEVAR). FAST is a web-based information management tool developed and maintained by Idaho National Laboratory and funded by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Hydrogen and Electric Charging Infrastructure for Heavy-Duty Trucks: A Nationally Scalable Megaregion Assessment

Decarbonizing regional and long-haul freight is challenging due to the limitations of battery-electric commercial vehicles and infrastructure constraints. Hydrogen fuel cell medium- and heavy-duty vehicles (MHDVs) offer a viable alternative, aligning with the decarbonization goals of the Department of Energy and commercial entities. Historically, alternative fuels like compressed natural gas and liquefied propane gas have faced slow adoption due to barriers like infrastructure availability. To avoid similar issues, effective planning and deploying zero-emission hydrogen fueling infrastructure is crucial. This research develops deployment plans for affordable, accessible, and sustainable hydrogen refueling stations, supporting stakeholders in the decarbonized commercial vehicle freight system. It aims to benefit underserved and rural energy-stressed communities by improving air quality, reducing noise pollution, and enhancing energy resiliency. This research also provides a blueprint for replacing diesel in over-the-road Class 8 freight truck applications with hydrogen fueling solutions. The study focuses on the Texas Triangle Megaregion (I-45, I-35, and I-10), the I-10 corridor between San Antonio, TX, and Los Angeles, CA, and the I-5/CA-99 corridors between Los Angeles, CA, and San Francisco, CA. This area represents a significant portion of U.S. heavy-duty freight movement, carrying ~8.5% of the national freight volume. Using the OR-AGENT (Optimal Regional Architecture Generation for Efficient National Transport) modeling framework, the study conducts an advanced assessment of commercial vehicles, road and freight networks, and energy systems. The framework integrates data on freight mobility, traffic, weather, and energy pathways to deliver a region-specific, optimized vehicles powertrain architectures, infrastructure deployment solutions, operational logistics, and energy pathways. By considering all vehicle origin-destination pairs utilizing these corridors and all feasible fueling station location options, the framework's genetic algorithm identifies the minimum number and optimal locations of hydrogen refueling stations, ensuring no vehicle is stranded. It also determines fuel schedules and quantities at each station. A roadmap for station deployment based on multiple adoption trajectories ensures a strategic rollout of hydrogen refueling infrastructure.

Sujan, Vivek [ORNL] (ORCID:0000000269882342)↗
DOE OSTI2022

Camp Lejeune Federal Fleet Tiger Team EVSE Site Assessment

The National Renewable Energy Laboratory (NREL) was contracted by the Department of Defense (DOD) Environmental Security Technology Certification Program (ESTCP) and the Department of Energy (DOE) Federal Energy Management Program (FEMP) to develop a web tool and complete pilot assessments for the installation of Electric Vehicle Supply Equipment (EVSE). NREL has deployed Tiger Teams comprising engineers and fleet experts to support DOD and DOE on several EVSE site assessments since 2015. However, the advancements developed in support of this report, including a cost-estimation tool and geospatial mapping tool, will enable a user-driven path to assess EVSE needs. This report details the site design recommendations for Camp Lejeune, North Carolina.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2024

Navigating Options for Transportation Electrification and Solar Charging: Steps and Lessons Learned in Montana Communities

This document is intended to assist communities who are considering investing in electric transportation. It can assist communities engage stakeholders, prioritize community goals, assess electric transportation options, and navigate complex decisions about deploying zero emission electric transportation in their community. It covers technological, economic and environmental aspects of the transition to electric vehicles (EV), and highlights the specific considerations related to the deployment of renewable energy technologies (e.g., distributed solar) in combination with EV supply equipment (EVSE, e.g., charging stations). There are many important decisions to make and questions for communities to ask themselves as they consider electric vehicle types, charging infrastructure, and electricity generation options. This guide will help communities assess: (1) Which stage in the decision-making process they are in with respect to EV deployment; (2) Questions they can explore to guide their decisions about EV deployment; (3) How to engage key stakeholders on EV deployment options; (4) Tradeoffs and benefits of various electric transportation options and; (5) Synergies of pairing electric vehicle charging and renewable energy generation technologies. The analysis and lessons learned presented in this roadmap are intended to serve as a template and guide for similarly situated communities across the country who want to prepare for and play a role in the electrified transportation future.

14 SOLAR ENERGY↗
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 OSTI2024

Impact of Electric Vehicle Charging Station Reliability, Resilience, and Location on Electric Vehicle Adoption

While the majority of electric vehicle (EV) charging events in the United States occur at home, issues with public charging stations are consistently found to be a top reason that potential EV buyers do not purchase an EV, demonstrating that both EVSE reliability and availability impacts EV adoption. This report explores multiple parameters that impact EVSE reliability and deployment, which in turn impact EV sales. These include extreme weather, codes and standards, region (urban vs. rural), and grid network type. Grid reliability was not found to impact EV adoption. The relationships between EV station reliability, station resilience, grid resilience, and EV adoption are largely outside the scope of the National Renewable Energy Laboratory's (NREL's) Automotive Deployment Options Projection Tool (ADOPT) and other vehicle adoption models, so the methodology of this report is varied. Section 2 sets the baseline for infrastructure reliability, user satisfaction, and maintenance practices. Section 3 explores the ways that electric vehicle supply equipment (EVSE) reliability impacts the relationship between EVSE and EV adoption. Section 4 shows how geographical categories such as urban, rural, large grid, off-grid, or microgrid can be helpful in EVSE deployment strategies, as well as how the relationship between EVSE and EV adoption differs among these categories. Section 5 investigates the impacts of grid reliability and infrastructure resilience on EV adoption. Finally, Section 6 reverses the perspective to examine the impact that EVs and EVSE have on grid resilience and reliability. As recent funding initiatives result in an expansion of public chargers across the United States, as well as an increase in the uptime of existing chargers, EV adoption will likely grow.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Electric Vehicle Charging Demand in the Chicago Metropolitan Area through 2030

This report outlines the collaborative efforts between Argonne National Laboratory and Exelon in advancing the Agent-Based Transportation Energy Analysis Model (ATEAM). Aligning with ComEd’s beneficial electrification plan, this study developed eight scenarios to access the temporal and spatial distribution of charging load and demand stemming from the widespread adoption of battery electric vehicles (BEV) adoption, augmented public charging infrastructure deployment, and increased multi-unit dwelling (MUD) charging availability. Enhancements to the ATEAM model encompassed the simulation of multiple days of travel behavior, estimation of total public charging infrastructure needs, user interface refinements, and output tracking at both vehicle and charging station levels. The total electricity consumption for residential and public charging to support over 800,000 BEVs in Chicago in 2029 is projected at approximately 10.2 GWh. Enhanced MUD home charging accessibility (70%) amplifies the home charging load in the study area by 1.5% compared to the baseline scenario (10%). The widespread adoption of BEVs reduces peak charging loads, owing to their inclusion across households with diverse income levels, thus fostering a more dispersed charging activity pattern. However, widespread BEV adoption increases the peak home charging load in areas with lower median household incomes, reflecting a higher BEV concentration in these locales and, subsequently, heightened peak charging demands. In the Widespread BEV adoption scenario, fewer census tracts exhibit elevated peak loads for combined home and public charging, indicating a more even distribution of charging demand across the study area. Predominantly, peak loads for combined charging—both home and public— occur between 2 p.m. and 10 p.m. across all scenarios, encompassing the majority of census tracts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

MaDEVIoT: Cyberattacks on EV Charging Can Disrupt Power Grid Operation

Extensive roll-out of electric vehicles (EVs) requires large-scale deployment of high-power EV Charging Stations (EVCSs). EVCSs are connected to the internet using Internetof- Things (IoT) such as smartphones, to improve the charging experience of users and increase their profitability. This paper studies the feasibility of demand-side cyberattacks launched on power grids via such internet-connected highpower EVCSs. The attack mechanism distorts power grid frequency and voltage, and has the potential to trigger systemwide outages. The case study, based on the power grid and EV deployment plans in Manhattan, New York, illustrates potential impacts of such attacks. The results show that such attacks will become feasible in Manhattan, New York in 2030, as EV adoption increases. Furthermore, the attacks in 2030 are feasible even compromising a single company’s EVCS server in Manhattan, New York. The attacks can cause line overloads and trip over-frequency protection relays, causing system-side blackout in the power grid in Manhattan, New York. The paper informs planning authorities and power grid operators involved with the roll-out of EV charging infrastructure about potential cyberthreats to power grids via manipulating internet-connected high-power EVCSs.

Acharya, Samrat S.↗
DOE OSTI2022

rfasst: An R tool to estimate air pollution impacts on health and agriculture

Existing scientific literature shows that health and agricultural impacts attributable to air pollution are significant and should be considered in the integrated analysis of human and Earth-system interactions. The implementation of policies that affect the power sector, the composition of the vehicle fleet or the investments and deployment of different energy sources will in turn result in different levels of air pollution. Even though the various methodologies for estimating the impacts of air pollution, such as exposure-response functions, are extensively applied by the scientific community, they are normally not included in integrated assessment modeling outputs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Federal Automotive Statistical Tool: Federal Vehicle Fleet Reporting Update (Combined FedFleet/FEVAR/INTERFUEL Meeting, November 2023) [Slides]

This presentation presents an overview of coming changes to how federal agencies with motor vehicles will submit required information about the electric vehicle supply equipment (EVSE) inventory and planned deployments through the Federal Automotive Statistical Tool (FAST), as well as updates on fleet reporting in general. This presentation is intended for delivery via WebEx/GoToMeeting at the November 2023 meeting of the DOE/GSA jointly-organized combined meeting of the Federal Electric Vehicle Agency Round-table (FEVAR), FedFleet, and INTERFUEL working groups. FAST is a web-based information management tool developed and maintained by Idaho National Laboratory and funded by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Zero Emission Cargo Transport (ZECT) II Demonstration: South Coast Air Quality Management District (Final Report)

The South Coast Air Quality Management District (South Coast AQMD), California Air Resources Board (CARB) and Southern California Association of Governments (SCAG) — the agencies responsible for preparing the State Implementation Plan required under the federal Clean Air Act — have agreed that attainment of federal air quality standards for the region will require a transition to the broad use of zero and near-zero emission energy sources in cars, trucks and other equipment. Accordingly, the 2012 South Coast AQMD Air Quality Management Plan, the SCAG 2012 Regional Transportation Plan, and the “Vision for Clean Air: A Framework for Air Quality and Climate Control Planning” all identify the need to immediately enact a phasing in of zero and near-zero emission technologies to meet air quality goals. In 2014, South Coast AQMD was awarded grant funding under the US Department of Energy Zero Emission Cargo Transport (ZECT) II Demonstration program to develop and demonstrate zero-emission drayage trucks for goods movement operations between the Port of Los Angeles (POLA) and Port of Long Beach (POLB) near dock rail yards and warehouses: 1) development and demonstration of zero-emission fuel cell range extended electric drayage trucks and 2) development and demonstration of hybrid electric drayage trucks. The purpose of this project was to accelerate deployment of zero emission cargo transport technologies to reduce harmful diesel emissions, petroleum consumption and greenhouse gases in the surrounding communities along the goods movement corridors that are impacted by heavy diesel traffic and the associated air pollution. Between 2014 – 2024, six ZECT II zero-emission fuel cell drayage truck platforms, including fuel cell range extended and CNG hybrid trucks, were successfully designed, developed, integrated, built, tested, and demonstrated with drayage fleet operators in transportation corridors within areas of the South Coast AQMD jurisdiction in Southern California such as in and around POLA and POLB. Portable hydrogen refueling was deployed to support the fuel cell vehicles. The project had real-time improvement with on-going debugging and optimizations while the vehicles were under demonstration. All platforms demonstrated sufficient or excess power, torque, and energy to support 82,000lbs Gross Vehicle Weight Rating and gradeability to perform their daily duty cycles. Collectively, the trucks drove over 23,000 miles during their respective demonstration phases. The ZECT II project was the first of its kind to demonstrate the commercial viability that supported the additional technology breakthroughs for Class 8 zero emission trucks and validations as well as the regulatory basis for all the zero-emission regulation that we know today, such as the Innovative Clean Transit regulation, Advanced Clean Trucks and Clean Fleet regulations.

08 HYDROGEN↗
DOE OSTI2022

Deploying Traffic Smoothing Cruise Controllers Learned from Trajectory Data

Autonomous vehicle-based traffic smoothing con- trollers are often not transferred to real-world use due to challenges in calibrating many-agent traffic simulators. We show a pipeline to sidestep such calibration issues by collecting trajectory data and learning controllers directly from trajectory data that are then deployed zero-shot onto the highway. We construct a dataset of 772.3 kilometers of recorded drives on the I-24. We then construct a simple simulator using the recorded drives as the lead vehicle in front of a simulated platoon consisting of one autonomous vehicle and five human followers. Using policy-gradient methods with an asymmetric critic to learn the controller, we show that we are able to improve average MPG by 11% in simulation on congested trajectories. We deploy this controller to a mixed platoon of 4 autonomous Toyota RAV-4’s and 7 human drivers in a validation experiment and demonstrate that the expected time-gap of the controller is maintained in the real world test. Finally, we release the driving dataset [1], the simulator, and the trained controller at https://github.com/nathanlct/trajectory-training-icra.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

FedFleet 2023: FAST - What's New, What's Coming, What's Next?

This presentation presents an overview and demonstration of new capabilities being incorporated into the Federal Automotive Statistical Tool (FAST) to gather information from Federal agencies about electric vehicle supply equipment (EVSE) they are planning to deploy in support of EO 14057 and its implementing instructions. It also includes an overview other related changes being made to FAST over FY 2023 and following years. FAST is a web-based information system sponsored by GSA's Office of Government-wide Policy and DOE's Federal Energy Management Program to collect information about the US federal government's fleet of motor vehicles; FAST is developed, maintained, and supported by DOE's Idaho National Laboratory (INL).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

An integrated computational materials engineering framework to analyze the failure behaviors of carbon fiber reinforced polymer composites for lightweight vehicle applications

A bottom-up multi-scale modeling approach is used to develop an Integrated Computational Materials Engineering (ICME) framework for carbon fiber reinforced polymer (CFRP) composites, which has the potential to reduce development to deployment lead time for structural applications in lightweight vehicles. In this work, we develop and integrate computational models comprising of four size scales to fully describe and characterize three types of CFRP composites. In detail, the properties of the interphase region are determined by an analytical gradient model and molecular dynamics analysis at the nano-scale, which is then incorporated into micro-scale unidirectional (UD) representative volume element (RVE) models to characterize the failure strengths and envelopes of UD CFRP composites. Then, the results are leveraged to propose an elasto-plastic-damage constitutive law for UD composites to study the fiber tows of woven composites as well as the chips of sheet molding compound (SMC) composites. Subsequently, the failure mechanisms and failure strengths of woven and SMC composites are predicted by the meso-scale RVE models. Finally, building upon the models and results from lower scales, we show that a homogenized macro-scale model can capture the mechanical performance of a hat-section-shaped part under four-point bending. Along with the model integration, we will also demonstrate that the computational results are in good agreement with experiments conducted at different scales. The present work illustrates the potential and significance of integrated multi-scale computational modeling tools that can virtually evaluate the performance of CFRP composites and provide design guidance for CFRP composites used in structural applications.

36 MATERIALS SCIENCE↗
DOE OSTI2022

EVs@Scale Lab Consortium Bi-Annual Stakeholder Meeting, 17 August 2022, Golden, Colorado [Slides]

The U.S. Department of Energy (DOE) Electric Vehicles at Scale Lab Consortium (EVs@Scale Lab Consortium) is accelerating research to support the establishment of a secure and scalable national network of charging infrastructure. This network will be critical to support tens of millions of light-, medium-, and heavy-duty EVs on American roads by 2030. The EVs@Scale Lab Consortium brings together national laboratories and key stakeholders to conduct infrastructure research and development (R&D) that advances innovations in, and sets unified standards for, high-power and wireless charging. The effort will also develop technologies to integrate vehicle charging with the power grid, and develop cybersecurity measures to protect drivers, vehicles, equipment, and the grid. The first hybrid EVs@Scale Lab Consortium Biannual Stakeholder Meeting was held at NREL on August 17, 2022, to identify research, development, and deployment needs to accelerate technology development for electric vehicles at scale and explore opportunities for collaboration across government, academia, and industry.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

EVs@Scale Lab Consortium Semi-Annual Stakeholder Meeting

The U.S. Department of Energy (DOE) Electric Vehicles at Scale Lab Consortium (EVs@Scale Lab Consortium) is accelerating research to support the establishment of a secure and scalable national network of charging infrastructure. This network will be critical to support tens of millions of light-, medium-, and heavy-duty EVs on American roads by 2030. The EVs@Scale Lab Consortium brings together national laboratories and key stakeholders to conduct infrastructure research and development (R&D) that advances innovations in, and sets unified standards for, high-power and wireless charging. The effort will also develop technologies to integrate vehicle charging with the power grid, and develop cybersecurity measures to protect drivers, vehicles, equipment, and the grid. The first hybrid EVs@Scale Lab Consortium Semiannual Stakeholder Meeting was held at ANL on September 27-28, 2023, to identify research, development, and deployment needs to accelerate technology development for electric vehicles at scale and explore opportunities for collaboration across government, academia, and industry.

advanced charging and grid interface technologies↗
DOE OSTI2024

2024 Electric Vehicles at Scale Semiannual Stakeholder Meeting

The U.S. Department of Energy (DOE) Electric Vehicles at Scale Lab Consortium (EVs@Scale Lab Consortium) is accelerating research to support the establishment of a secure and scalable national network of charging infrastructure. This network will be critical to support tens of millions of light-, medium-, and heavy-duty EVs on American roads by 2030. The EVs@Scale Lab Consortium brings together national laboratories and key stakeholders to conduct infrastructure research and development (R&D) that advances innovations in, and sets unified standards for, high-power and wireless charging. The effort will also develop technologies to integrate vehicle charging with the power grid, and develop cybersecurity measures to protect drivers, vehicles, equipment, and the grid. The first hybrid EVs@Scale Lab Consortium Semiannual Stakeholder Meeting was held at ANL on September 27-28, 2023, to identify research, development, and deployment needs to accelerate technology development for electric vehicles at scale and explore opportunities for collaboration across government, academia, and industry.

advanced charging and grid interface technologies↗