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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Speed Variation Based Power Regulation Concept for Dynamic Wireless Charging

On-road wireless charging of electric vehicles (EVs) in-motion could potentially reduce range anxiety or battery size with wide-spread deployment. The planning and implementation of such systems are greatly complicated due to their susceptibility to load variation inherent to traffic flow. Here, this paper proposes a method for derisking the potential for traffic slowdowns by compensating for reduced vehicle speed and investigates how implementation may affect system performance. A load modeling case study is presented at 200kW for a mile of high-speed roadway employing speed-based power regulation with results indicating average power usage and maximum car hosting capability can be reduced by 20% and increased by 30% respectively. An 85kHz power electronics model is developed based on designs and prototypes for an 11kW, 190m airgap static system and a 200kW dynamic wireless track. The simulation is validated in the 11kW experimental prototype and modified for 200kW operation to compare with simulated performance. Sensitivity studies are performed in MATLAB/Simulink to evaluate how parameters influence system performance and confirm the capability to reduce output power and maintain efficiency at 11 and 200kW. The static 11kW experimental system operates at 93.6% efficiency and multiple options exist to reduce power while maintaining efficiency greater than 90%. The capability to dynamically modify power output from WPT coils, in an experimentally validated simulation, enables techniques to significantly mitigate load variability due to reductions in vehicle speed.

42 ENGINEERING↗
DOE OSTI2023

Electric Vehicle Managed Charging: Estimating the Potential Bulk Power System Value

With more and more electric vehicles (EVs) on the road, the grid of the future can greatly benefit from EV managed charging, which coordinates charging based on people's travel needs, electricity supply, and grid conditions. The added flexibility could be especially valuable for the bulk power system as it transitions to high shares of variable renewable generation, like wind and solar. Numerous studies have estimated the potential value of EV managed charging. In this study, NREL leveraged more detailed modeling of EV adoption, use, charging, and bulk power system operations to understand the potential value. Unique to this study, NREL modeled different charging flexibility types and dispatch mechanisms - as well as participation rates among drivers in having their EV charging managed - starting from vehicle-specific descriptions of charging flexibility. The study is based on a passenger light-duty vehicle adoption scenario with 100% EV sales by 2035 and a New England power system in 2038 with 84% clean generation and 26% of the electric load met by net imports. The 2038 New England light-duty vehicle feet is modeled as 45% electric.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2021

Comparative Analysis of ML Techniques for Data-Driven Anomaly Detection, Classification and Localization in Distribution System

High penetration of Distributed Energy Resources (DERs), fundamental load behavior changes, controllable loads, and significant increase in Electrical Vehicles (EVs) lead to complex dynamic behavior of the electric distribution system. Increasing number of components also means more measurements, more data and more data anomalies. Detecting, classifying and localizing these anomalies are important for situational awareness, and at the same time, very challenging given increasing complexity of the system. Highly accurate and high-resolution analytical techniques are needed to support anomaly detection, classification and localization (AD-C-L) for monitoring, root cause analysis and decision making. This paper provides comprehensive review and analysis of the existing spatio-temporal AD-C-L techniques within the distribution system. Challenges for specific problems in AD-C- L have been also discussed in this paper. Existing AD-C- L techniques have been categorized and synthesized for specific merits and limitations of multiple Machine Learning (ML) methodologies using common developed metrics of performance. The comparative analysis is summarized and presented with the open research challenges and path forward for future research needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Impact Analysis of Future Electric Vehicles Using Model of Real Distribution Feeders

Globally, the number of electric vehicles (EVs) continues to increase. This on-going trend poses challenges for power distribution systems. The inclusion of electric vehicle supply equipment (EVSE) should be compatible with a changing energy system, whose structure is becoming increasingly distributed. The impact of future EVs should be analyzed and considered in the system planning and upgrades. In this study, impact analysis of future EVs is conducted for a utility company of U.S. West Coast. Real data of distribution feeders is converted into the GridLAB-D model for running power flow analysis. An estimation of the additional loading of EVs in 2050 is provided by the utility company. Simple mitigation methods are tested to improve voltage profiles and complete this case study.

Xie, Jing↗
DOE OSTI2023

Performance and Implementation Requirements for Residential EV Smart Charge Management Strategies

As the electrification of transportation expands, electric vehicle (EV) charging as residential loads will continue to grow. Residential EV charging has the potential to increase feeder peak loads and decrease voltage quality. As a result of this growing energy demand driven by EV, utilities may employ the use of smart charge management (SCM) controls to modify charging load profiles and mitigate these grid impacts. It is important that utilities understand both the potential benefits-as well as possible implementation challenges-before considering this technology as a solution to managing growing EV loads. In order for an SCM strategy to be an effective solution, the potential benefits must outweigh the implementation challenges. This study establishes and tests a novel framework to assess the implementation requirements of different SCM controls. It identifies a range of requirements specific to various SCM controls and implementation approaches to compare the relative challenges associated with the deployment of each. When paired with analysis on the effectiveness of the ability of each control to mitigate grid impacts from EV charging, this assessment is critical in comparing the value potential of different SCM controls.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

A Review and Outlook on Energy Consumption Estimation Models for Electric Vehicles

Electric vehicles (EVs) are critical to the transition to a low-carbon transportation system. The successful adoption of EVs heavily depends on energy consumption models that can accurately and reliably estimate electricity consumption. This paper reviews the state-of-the-art of EV energy consumption models, aiming to provide guidance for future development of EV applications. Here, we summarize influential variables of EV energy consumption into four categories: vehicle component, vehicle dynamics, traffic and environment related factors. We classify and discuss EV energy consumption models in terms of modeling scale (microscopic vs. macroscopic) and methodology (data-driven vs. rule-based). Our review shows trends of increasing macroscopic models that can be used to estimate trip-level EV energy consumption and increasing data-driven models that utilized machine learning technologies to estimate EV energy consumption based on large volume real-world data. We identify research gaps for EV energy consumption models, including the development of energy estimation models for modes other than personal vehicles (e.g., electric buses, electric trucks, and electric non-road vehicles); the development of energy estimation models that are suitable for applications related to vehicle-to-grid integration; and the development of multi-scale energy estimation models as a holistic modeling approach.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Individual Motorist Data - Ohio EV Ownership Trends

The individual motorist dataset contains data and analysis of consumer electric vehicle (EV) ownership trends in rural Appalachian Ohio in comparison with statewide trends. The data span four years, from Q1 2020 to Q2 2023 (partial). They are sourced from the Ohio Bureau of Motor Vehicles registration records and contain detail on drivetrain type (battery-electric vehicle [BEV] or plug-in hybrid electric vehicle [PHEV]); specific vehicle make and model; and registration location at county, city, and ZIP code levels of spatial resolution. Registration data are analyzed at the county level against such indicators as median income, poverty status, urban-rural status, and density of public charging infrastructure. In addition to tabular data, a GIS shapefile with many analysis fields joined is included.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Procedure for Assessing the Suitability of Battery Second Life Applications after EV First Life

Using batteries after their first life in an Electric Vehicle (EV) represents an opportunity to reduce the environmental impact and increase the economic benefits before recycling the battery. Many different second life applications have been proposed, each with multiple criteria that have to be taken into consideration when deciding the most suitable course of action. In this article, a battery assessment procedure is proposed that consolidates and expands upon the approaches in the literature, and facilitates the decision-making process for a battery after it has reached the end of its first life. The procedure is composed of three stages, including an evaluation of the state of the battery, an evaluation of the technical viability and an economic evaluation. Options for battery configurations are explored (pack direct use, stack of battery packs, module direct use, pack refurbish with modules, pack refurbish with cells). By comparing these configurations with the technical requirements for second life applications, a reader can rapidly understand the tradeoffs and practical strategies for how best to implement second life batteries for their specific application. Lastly, an economic evaluation process is developed to determine the cost of implementing various second life battery configurations and the revenue for different end use applications. An example of the battery assessment procedure is included to demonstrate how it could be carried out.

25 ENERGY STORAGE↗
DOE OSTI2021

Heavy-Duty Truck Electrification and the Impacts of Depot Charging on Electricity Distribution Systems

Major technological advancements and recent policy support are improving the outlook for heavy-duty truck electrification in the United States. In particular, short-haul operations (=200 miles (=322 km)) are prevalent and early candidates for plug-in electric vehicles (EVs) given their short, predictable routes and return-to-base applications, which allows vehicles to recharge when off shift at their depots. Although previous studies investigated the impacts of added electrical loads on distribution systems, which included light-duty EVs, the implications for heavy-duty EV charging are underexplored. Here we summarize the causes, costs and lead times of distribution system upgrades anticipated for depot charging. We also developed synthetic depot charging load profiles for heavy-duty trucks from real-world operating schedules, and found that charging requirements are met at common light-duty EV charging rates (=100 kW per vehicle). Finally, we applied depot charging load profiles to 36 distribution real-world substations, which showed that most can accommodate high levels of heavy-duty EV charging without upgrades.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Customer Experience at Public Charging Stations and Its Effects on the Purchase and Use of Electric Vehicles

To support the ChargeX Consortium’s mission to measure and significantly improve the reliability and usability of public charging infrastructure in North America, researchers in the consortium from the University of Washington (UW) reviewed the published literature and data from consortium members to evaluate how the consumer experience at public fast charging stations influences electric vehicle (EV) adoption.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Power-to-Gas Systems for Active Load Management at EV Charging Sites with High DER Penetration

Intermittent renewable systems and increasing electric vehicle (EV) penetrations increase load intermittency—and will require expensive distribution system infrastructure upgrades. Power-to-gas (P2G) systems are highly controllable loads that can be modulated to regulate the net load behind the meter. In this work, we present an active load management approach using P2G systems to regulate the net load for an EV charging station with high penetrations of renewable generation. The system also validates the feasibility of the proposed approach using a 750-kW electrolyzer operated with the distribution system in a real-time power-hardware-in-the-loop test. Finally, we evaluate the impact of the size of the P2G system on its ability to regulate the net load.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗
DOE OSTI2022

Tri-level hybrid interval-stochastic optimal scheduling for flexible residential loads under GAN-assisted multiple uncertainties

Various building loads, such as heating, ventilation, and air conditioners (HVACs), electric water heaters (EWHs), and electric vehicles (EVs), can introduce opportunities for improving the flexibility of electricity consumption while satisfying the needs of building owners as well as benefiting the resilience of distribution system. To utilize such flexibility, a tri-level distribution market framework is established, including residential consumers, load aggregators (LAs), and the distribution system operator (DSO). In this work, the uncertainties from all three levels are considered. The random consumption behavior at the consumer level is modeled as a Gaussian noise that is also aggregated and transmitted to the LA level. The weather temperature in the LA level is forecasted as an interval, and the photovoltaic (PV) power in the market-clearing level is modeled by a set of power scenarios generated by Generative Adversarial Networks (GANs). Then, a hybrid interval-stochastic programming is proposed to transform the uncertain problems in the first two levels into deterministic ones. For real-time implementations, a rolling horizon optimization (RHO) scheme is employed to continuously optimize the power consumption based on the latest operating information. Finally, case studies on a modified IEEE 69-bus system validate the effectiveness of the proposed uncertainty modeling strategies and the RHO scheme.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Vertically assembled nanosheet networks for high-density thick battery electrodes

As one of the prevailing energy storage systems, lithium-ion batteries (LIBs) have become an essential pillar in electric vehicles (EVs) during the past decade, contributing significantly to a carbon-neutral future. However, the complete transition to electric vehicles requires LIBs with yet higher energy and power densities. Here, we propose an effective methodology via controlled nanosheet self-assembly to prepare low-tortuosity yet high-density and high-toughness thick electrodes. By introducing a delicate densification in a three-dimensionally interconnected nanosheet network to maintain its vertical architecture, facile electron and ion transports are enabled despite their high packing density. This dense and thick electrode is capable of delivering a high volumetric capacity >1,600 mAh cm −3 , with an areal capacity up to 32 mAh cm −2 , which is among the best reported in the literature. The high-performance electrodes with superior mechanical and electrochemical properties demonstrated in this work provide a potentially universal methodology in designing advanced battery electrodes with versatile anisotropic properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Scaling Demand Flexibility: Building on 30 Years of Energy Efficiency Success

With electricity consumption across the United States (US) and Canada anticipated to grow, energy efficiency program administrators have a key role to play in helping to ensure energy affordability and reliability in support of the broader economic systems utilities and grid support. Connected, demand side load balancing solutions, such as load shifting heating, ventilation and air conditioning (HVAC) systems and managed charging for electric vehicles (EVs), can dynamically manage energy, allowing for more volumetric electricity consumption without incurring the expense of upgraded transmission and distribution capabilities. When combined, or aggregated, many small loads can be managed to have meaningful impact on energy demand on the grid. Utilities and their partners have an opportunity to leverage decades of experience and the infrastructure needed to assess, design, implement, and measure programs to scale up the adoption of equipment with built-in load flexibility capabilities. Current efforts among a wide variety of electricity system service providers, utilities, standards agencies, regulators, national labs and private industry stakeholders aim to identify common standards, metrics, and methodologies for valuing grid services offered by demand side equipment. By combining those efforts with decades of proven energy efficiency resources, utilities are poised to effectuate a scaling up of equipment with energy management capabilities installed in homes and businesses across the US and Canada. This paper will provide an overview of how utilities are approaching this era of load growth and new peak demands across the United States and Canada. It will highlight the specific strategies that program administrators are employing to advance market transformation for grid-enabled products and devices that have the greatest potential to reduce energy use and increase load flexibility.

Grant, Peter↗
DOE OSTI2025

Evaluating Direct and Indirect Influence on EV Charging Stations Across the US

The adoption of new technology for electric vehicles (EV) and mobility applications can bring underappreciated vulnerabilities to the power grid. One area of potential fraud and adversarial influence is through the business ecosystem of startups that own and deploy EV technology. Yet, there are no models or analyses that map the network of organizations and people that have direct and indirect influence over technologies currently deployed in the grid. To fill this gap, we develop a multilayer network model to measure direct and indirect influence on EV charging stations. First, we create and adversarial socio-technical network (ASTN) model via a data fusion pipeline for different US regions of interest (ROI). Then, we develop an integrated ASTN for Chicago, Los Angeles, New York, and Philadelphia. We rank EV charging companies direct influence within each geographic region as well as indirect influence via social network analysis. While some companies have strong direct and indirect influence (i.e., ChargePoint) others show a mismatch between their influence over charging stations and their position within the social network. For example, Tesla has strong direct influence on stations and weak indirect influence over competitors. In contrast, 7Charge has weak direct influence over stations, but strong indirect influence over competitors.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗
DOE OSTI2022

Aligning Electric Vehicle Customer Charging with Grid Needs

This talk to the National Association of Regulatory Utility Commissioners (NARUC) focuses on "Aligning Electric Vehicle Customer Charging with Grid Needs" to highlight the opportunities associated with managed electric vehicle charging and its value for consumers and the power system. Electric vehicles (EVs) are experiencing a rapid rise in popularity and adoption, and growing EV adoption offers an opportunity to increase electricity demand. With expected widespread EV adoption, supporting charging will require investments in generation, transmission, and distribution systems. Uncoordinated charging of EVs will lead to increased system peak load, possibly exceeding the maximum power that can be supported by distribution systems and generally increasing power system stress. However, vehicles are underutilized assets parked ~96% of the time: managed EV charging can satisfy mobility needs while also supporting the grid. EVs are not a burden for the grid, but a resource: The demand-side flexibility provided by managed EV charging offers significant potential benefits for the grid over multiple timescales and applications., especially for high-renewable systems. Managed charging can support power system planning and operations during normal and extreme conditions, benefitting EV owners and other electricity consumers. Managed charging is shown to consistently provide hundreds of dollars in cost savings per EV each year.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Electric Vehicle Charging Infrastructure Trends from the Alternative Fueling Station Locator (Third Quarter 2023)

Electric vehicle (EV) charging infrastructure continues to rapidly change and grow. Using data from the U.S. Department of Energy's (DOE's) Alternative Fueling Station Locator, this report provides a snapshot of the state of EV charging infrastructure in the United States in the third calendar quarter of 2023 (Q3 2023) by charging level, network, and location. Additionally, this report measures the current state of charging infrastructure compared to the infrastructure requirement scenario outlined in the National Renewable Energy Laboratory (NREL) report, The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure. This information is intended to help transportation planners, policymakers, researchers, infrastructure developers, and others understand the rapidly changing landscape of EV charging infrastructure. This is the fifteenth report in a series. Reports from previous quarters can be found in the Alternative Fuels Data Center (AFDC) and NREL publication databases, as well as the AFDC Charging Infrastructure Trends page (https://afdc.energy.gov/fuels/electricity_infrastructure_trends.html).

33 ADVANCED PROPULSION SYSTEMS↗