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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Optimal Managed Fast-Charging Model for Electric Vehicle Fleets with High Utilization and Multiple Charge-Acceptance Curves

A predictive control/scheduling optimization model is proposed for managed charging of an electric vehicle (EV) fleet - under time-of-use energy and demand prices, high vehicle utilization frequency (short dwell times), multiple charge- acceptance curves (configurable charging rates), and flexible vehicle demand. This context is particularly relevant for flight schools (small electric aircraft) or other commercial facilities where an EV fleet performs multiple operating and fast-charging sessions on the same day. The proposed model performs both the operational and charging scheduling of the vehicles, which is not typically done for residential managed charging and significantly increases problem complexity. The problem is formulated as a MILP model and a case study of a small fast-charging station is presented. Results demonstrate a significant reduction in operating cost, mainly from peak shaving during high demand price periods, achieved by coordinating the operation of different vehicles, chargers and charging rates.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2024

Transportation Electrification Impact Study (TEIS)

Recent U.S. Environmental Protection Agency (EPA) notices of proposed rulemakings for GHG emissions standards for light-, medium-, and heavy-duty on-road vehicles would accelerate ongoing advancements already happening in the industry because of private investment, consumer demand, state-level policies, and federal incentives. As the EPA finalizes these regulations, questions persist regarding the cost of the requisite charging infrastructure and associated upgrades to the nation's electric grid. With support from the U.S. Department of Energy, U.S. Joint Office of Energy and Transportation, and the EPA, a multidisciplinary team conducted a Multi-State Transportation Electrification Impact Study that quantitatively assesses the incremental investment necessary to enable the levels of vehicle electrification expected to be induced by pending EPA regulations and to estimate the potential value of deferred investments in electric distribution infrastructure stemming from proactive vehicle-grid integration planning and deployment. This study finds the simulated incremental capital cost of charging infrastructure (including grid upgrades) to be at least 2.5 times smaller than the lifetime net benefits of vehicle electrification (including fuel savings but excluding the value of avoided emissions). Additionally, the incremental distribution grid upgrade cost of the EPA Action-Unmanaged scenario was found to be approximately 3% of existing utility distribution system investments (on an annual basis). Finally, the potential for managed charging to defer distribution grid upgrades was found to be significant with costs found to decrease from $2.3 billion to an incremental cost of $1 billion across five states in the Action-Managed scenario (relative to the No Action-Unmanaged scenario).

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗
DOE OSTI2024

Sustainable Port Operations: Powered by NREL

Seaports are vital economic hubs that allow the United States to compete on a global scale. But the heavy vehicles and cargo equipment that enable their operations also emit harmful air pollutants and greenhouse gas emissions. For nearly two decades, National Renewable Energy Laboratory (NREL) researchers have worked toward comprehensive seaport decarbonization. They fuse world-class analysis with deep vehicle and transportation systems knowledge to guide strategic deployment of low- and zero-emissions vehicles, charging and refueling infrastructure, and grid improvements. Together, these capabilities can enable sustainable port operations. This fact sheet outlines major seaport and airport decarbonization capabilities across the laboratory, including: fleet research, energy data, and insights for decarbonization; comprehensive hydrogen infrastructure deployment; optimized charging through grid integration; strategic blueprinting for clean, optimized technology deployment; and integrating diversity, equity, inclusion, and accessibility considerations into decarbonization efforts.

ADVANCED PROPULSION SYSTEMS,ENERGY CONSERVATION, C↗
DOE OSTI2025

Northeast Freight Corridor Charging Plan (Roadmap Report)

Final report produced as part of grant awarded to National Grid. The final report is a roadmap of 39 prioritized sites. These sites would create a minimum viable network of charging infrastructure, enabling the electrification of trucks across the Northeast

02 PETROLEUM↗
DOE OSTI2025

A method for modeling battery-temperature-aware EV power profiles utilizing Next-Gen Profile data

With the expected increase in the number of electric vehicles (EVs) on the road in the coming years, it is important that analysis tools are capable of modeling and predicting the expected load on the power grid due to both individual EV charging sessions as well as large populations of vehicles. To do this accurately, the power profile of an EV charge session must be accurately modeled, including for scenarios where the temperature is above or below the ideal, and also take into account the nuances of manufacturer charging preferences. This paper introduces a method that utilizes the data in the Next-Gen Profile (NGP) data collection project to build a model of EV charging that takes into account the variations in charging power that occur due to off-nominal battery temperature and manufacturer preferences that limit power due to cold temperatures or high battery state-of-charge.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

High Efficiency Powertrain for Heavy Duty Trucks Using Silicon Carbide (SiC) Inverter

The objective of the High Efficiency Propulsion (HEP) project is to research, develop, and demonstrate life cycle cost-effective Class 8 battery electric vehicles utilizing an 800 V high efficiency and compact 250 kW continuous power SiC inverter designed to support the commercial operations of the high continuous loads and challenging shock/vibration environment of heavy-duty trucks with an electrified axle specifically designed for high performance and efficiency in battery-electric Class 8 trucks used in medium range (~250 miles) distribution, and compared to the baseline Peterbilt 579 electric truck fleet performance using an IGBT inverter. The project was split into 3 budget periods, with the first two being design and development focused, and the final one is an on-vehicle demonstration phase of the high efficiency SiC traction drive inverter with daily mileage accumulation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Forecasting EV Charging Demand on the Distribution System

The U.S. transportation and electricity sectors have historically operated independently, but the growth of electric vehicles (EVs) is driving their convergence. After decades of stagnant demand, utilities must prepare for rising load growth, driven in part by transportation electrification. Utilities must anticipate when and where these new loads will materialize to effectively manage EV growth and maintain grid reliability. This presentation outlines NREL's approach to developing high-resolution EV load datasets for distribution planning, with insights from the Multi-State Transportation Electrification Impact Study on EV and load forecasting, infrastructure requirements, and managed charging strategies.

25 ENERGY STORAGE↗
DOE OSTI2025

Pricing Strategy of Electric Vehicle Aggregators Based on Locational Marginal Price to Minimize Photovoltaic (PV) Curtailment

The global climate crisis demands urgent action to mitigate global warming. Using renewable energy sources, such as solar and wind power, for electricity generation is crucial. This shift from centralized to distributed power systems, however, brings challenges, including voltage fluctuations and renewable energy curtailment. The rapid growth of the electric vehicle (EV) industry adds complexity, increasing overall electricity demand and straining the power supply during peak charging times. This paper proposes a scheduling strategy for EV aggregators to reduce renewable energy curtailment and stabilize grid operation by strategically scheduling EV charging. Using Multi -Agent Transport Simulation (MATSim), a traffic simulation tool, EV driving data in Denver, Colorado, USA, were modeled. The EV aggregator adjusts charging fees based on locational marginal prices, encouraging EVs to charge at different stations according to pricing. Simulations on an IEEE 33-bus system with distributed energy resources and EV charging stations validate the proposed algorithm, demonstrating its effectiveness in reducing curtailment by 12.55% and stabilizing grid operation.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Managing Workplace Charging: Argonne National Laboratory’s Reservation-Based Smart EV Charging Platform

The Smart Electric Power Alliance (SEPA) partnered with Argonne National Laboratory (Argonne) to produce a case study on Argonne’s workplace electric vehicle (EV) charging program, designed to optimize employees’ ability to reserve EV chargers and allow Argonne to implement a workplace managed charging solution. Formally known as EVrez, the program offers Argonne’s employees access to more than 50 Level 2 chargers and 4 DC fast chargers (DCFC). Employees must reserve and manage their EV sessions through the EVrez mobile app platform. This report outlines the EVrez program, from inception to maturity, highlighting key learnings and best practices from the Argonne team. As other workplaces seek to offer their own workplace charging offerings, this report highlights foundational steps and considerations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Communications Reliability for Vehicle Grid Integration

Electric Vehicles (EVs) adoption rate has been steadily increasing in the US leading to a growing number of charging stations including faster DC (Direct Current) chargers and slower Level 1 and Level 2 AC (Alternating Current) chargers. This increase in demand for electricity is further exacerbated by recent developments in Artificial Intelligence (AI) technology, advanced manufacturing, and digitization. These factors will require electric utilities to upgrade their infrastructure to keep up with the increasing electrical demand (especially during peak hours). An easy way to counteract the need for these upgrades is to shift a major chunk of active charge sessions (durations where there is energy transfer from charger to EV's propulsion battery) to off-peak hours thereby flattening the load curve and making the infrastructure more resilient. This concept is known as Smart Charge Management (SCM). EV owners also benefit from SCM since it lowers their charging costs and consequently their transportation costs by prioritizing charging during off-peak hours. SCM takes advantage of EV's capability to act as a controllable load or DER (Distributed Energy Resource). This report summarizes the reliability analysis performed on the communication required for two of these SCM use-cases. This analysis only focuses on SCM strategies for unidirectional charging (energy transfer from EVSE to EV or V1G) and not bidirectional charging.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

High-Fidelity Analysis of EV Integration on Real Utility Feeders in Colorado

Residential electric vehicle (EV) charging has the potential to alter long-held assumptions on load characteristics impacting distribution grid planning, operations, and design standards. This study identifies analysis and control methods to increase the affordability of residential EV charging both for Xcel Energy and their customers. The project also provides solutions for more reliable grid interconnection that can support a reliable utility business model prepared for increasing EV charging load in the coming years. For this project, we referenced Level 2 alternating current (AC) onboard charging profiles for various vehicle models and high-fidelity charging data collected at the experimental setup established at the EV Research Infrastructure Laboratory at the National Renewable Energy Laboratory (NREL). Next, we developed EV adoption models for 2030 and 2040 for the Boulder and Aurora regions in Colorado. Moreover, we evaluated different smart charging control algorithms and compared their performance. We developed time-of-use (TOU)-based and grid-aware active EV charging control methods and integrated them within the study region to understand field impacts. Diving deeper, we selected 10 feeders in Boulder and Aurora for high-fidelity grid modeling down to the house level. We executed detailed grid analysis comparing the smart charge management (SCM) algorithms we developed. Finally, we created a novel tool, Electric Vehicle Infrastructure--Distribution System Integration Tool (EVI-DiST), to integrate all the approaches in a single software environment to provide easy integration, fast simulation, and detailed evaluation capability for utility engineers and other stakeholders.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Analyzing Residential Charging Demand for Light-Duty Electric Vehicles in Colorado

The past decade has witnessed a remarkable surge in adoption of electric vehicles (EVs). The momentum is expected to continue with strong support from governments and industry. Rapid EV adoption will add significant electricity demand, making it critical to plan for and manage EV charging to avoid causing additional stress and non-negligible risks to the already-aging power grid. To help power grid operators understand the impacts of residential EV charging and identify risk factors, this study presents a data-driven charging demand analysis for light-duty vehicles. This study considers two real-world grid service regions in Colorado and merges multiple data sources and state-of-the-art tools that characterize EV adoption projections, vehicle travel patterns, seasonal variations, residential charging accessibility, ambient temperature impact, EV charging behaviors, grid utility customers, vehicle registration, and household-level EV charging demand distribution. We characterize potential residential charging demand in 2030 for two regions within the state of Colorado: Boulder and Aurora regions. We project that EVs will be 26% of the light-duty vehicle population in Boulder and 16% in Aurora areas. Charging demand is characterized for ten power grid feeders (five for each study region). Across the ten feeders, peak total EV charging powers during wintertime range from less than 1 MW to more than 4 MW.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Analysis of Electric Heavy-Duty Driving and Infrastructure Requirements

The analysis discussed in this report was performed as part of DOE award DE-EE0009232 to model the effects of charging Heavy Duty Battery Electric Trucks (HDBETs) on the grid. This project combines best in class freight modeling by the National Renewable Energy Laboratory (NREL) with advanced distribution modeling by EPRI using detailed data from Xcel Energy and Salt River Project to analyze the effects of depot charging and utility-grade transmission modeling by Tri-State Transmission and Generation Association Inc. to analyze the effects of en-route charging.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Wireless Pulse-Width Modulation Control of Power Converters Using Ultra-Wideband Technology for Distributed High-Voltage Systems: Preprint

In this study, we present a new approach for wireless pulse-width modulation (PWM) control of a power converter, applicable to numerous power converters within a complex electrical distribution system. This method eliminates the need for multiple physical connections of gating/PWM signals among distributed converter modules. By using ultra-wideband-based communication, the PWM control signals can be wirelessly transmitted from a central controller to multiple converters simultaneously and seamlessly. System stability is thoroughly analyzed, and experimental results validate the efficacy of the wireless control scheme for a buck converter operating at a 50-kHz switching frequency. The minimum latency obtained from this setup is 5.38 mus. This control concept offers easier implementation of distributed control in high-voltage power systems, especially in multilevel architectures, even under harsh conditions with ambient noise.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Wireless Pulse-Width Modulation Control of Power Converters Using Ultra-Wideband Technology for Distributed High-Voltage Systems

In this study, we present a new approach for wireless pulse-width modulation (PWM) control of a power converter, applicable to numerous power converters within a complex electrical distribution system. This method eliminates the need for multiple physical connections of gating/PWM signals among distributed converter modules. By using ultra-wideband-based communication, the PWM control signals can be wirelessly transmitted from a central controller to multiple converters simultaneously and seamlessly. System stability is thoroughly analyzed, and experimental results validate the efficacy of the wireless control scheme for a buck converter operating at a 50-kHz switching frequency. The minimum latency obtained from this setup is 5.38 ..mu..s. This control concept offers easier implementation of distributed control in high-voltage power systems, especially in multilevel architectures, even under harsh conditions with ambient noise.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

The State of Electric Vehicle Adoption in Colorado for Multifamily versus Single-Family Dwellings: A Methodology for Quantifying Deviation from Parity

Given that electric vehicle adoption is well underway, the spatial distribution of electric vehicle owners by housing type—single-family or multifamily— shows whether parity (equal adoption rates) is being achieved or to what extent adoption by housing type is over or undersaturated (i.e., over- or under-adoption). We use a proprietary dataset of vehicle registrations with modeled housing type to analyze saturation ratios in Colorado in 2022. We found significant single-family oversaturation and multifamily undersaturation in 14% and 23% of ZIP codes, respectively, suggesting Colorado can still mitigate disparities in electric vehicle adoption by housing type through accessible vehicles and charging.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

EV Forecasting-Based Model Predictive Control for Distribution System Congestion Mitigation

The uncoordinated charging of electric vehicles (EVs) in time and space brings congestion issues to the distribution network. This paper proposes an EV charging demand forecasting-based model predictive control (MPC) method for distribution system congestion management. To effectively forecast the time-series EV station charging demand, a hybrid forecasting model that integrates the long short-term memory network (LSTM) and Transformer is proposed. The Transformer-LSTM model is trained using a one-year real historical charging dataset of EV stations to forecast future charging demand in 15-minute intervals. This informs the MPC for distribution network congestion management and minimization of PV curtailment. Numerical results carried out on the modified IEEE 123-bus distribution system demonstrate that the proposed method can effectively resolve line congestion issues through EV smart charging and PV curtailment while outperforming other benchmarks.

ADVANCED PROPULSION SYSTEMS,SOLAR ENERGY↗