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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Ambient Mass Spectrometry Rapid Analysis Methods for Trace Inorganics

The ability to rapidly detect and characterize the chemistry of trace quantities of inorganic species has multiple potential applications, including nuclear safeguards, nuclear forensics, and environmental monitoring. Some mass spectrometric methods currently exist, but they are costly and time-intensive, often destroying chemical information in the process of ionization. Ambient mass spectrometry is a relatively new analytical method in which samples are introduced to the mass spectrometer from atmospheric pressure, rather than from high vacuum. Ambient MS can operate with gentler ionization methods such as electrospray ionization (ESI) and paper-spray ionization (PSI), reducing fragmentation and preserving the chemical information of the analyte. This may be useful for determining the intended purpose of material in a sample. Strontium, part of nuclear fallout, is analyzed here to test these new analytical methods for viability. Electrospray ionization mass spectrometry functions by spraying the sample as a solution through a needle charged to a few kV. A nebulizing gas flows out along with the sample to create the spray before droplets enter a drying chamber with heated drying gas to remove the solvent molecules. From there bare analyte ions enter the mass spectrometer. This method has the advantage of relatively fast sample preparation and stable ionization. More stable ionization produces higher-quality data. Paper-spray ionization mass spectrometry operates by applying sample to a paper triangle. The paper triangle is then electrified in a metal clamp to a few kV before spray solvent is applied. The spray solvent transports analyte in the sample to the tip, where it is ionized and enters the mass spectrometer. One advantage of this method is reduced sample preparation - an analyst can even swipe a surface and cut a triangle directly from the swipe. The data analysis serves to rapidly process tens of samples all at once. The mass spectrometer outputs a file containing a few hundred spectra for each sample. The pipeline processes each one to identify peaks of interest. A full palette of data analysis metrics are generated, including plots of the raw data and plots of calculated values such as isotopic ratios. The pipeline filters the raw data to remove noise and background peaks, as well as peaks representing detector saturation. A heat map is generated to show the overall spectrum in mass-time- intensity space. Post-processing, we obtained the desired calibration curves, demonstrating that both ESI-MS and PSI-MS are viable methods for quantifying trace amounts of inorganics while retaining their chemical speciation information. ESI-MS demonstrated a linear response region of 100 ppb to 20 ppm, with a limit-of-detection of around 100 ppb. At top left is an example spectrum with the {sup 88}SrNO{sub 3} peak identified to show the retention of chemical speciation. PSI-MS showed a linear response region of around 1 ppb to 1 ppm, with a limit-of-detection of near 1 ppb. PSI-MS produced more erratic results than ESI-MS, likely due to the variability in ionization resulting from manual positioning of the paper triangle near the MS inlet. Future efforts will focus on improving the repeatability of PSI-MS as well as analyzing other species of interest such as cerium and uranium. Improvements will also be made to create more reliable data extraction and intelligent data filtering.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Economic feasibility of in-motion wireless power transfer in a high-density traffic corridor

Electricity is expected to become a dominant power source in the transportation sector, but under a stationary recharging model, electric powered vehicles still suffer some disadvantages relative to conventional vehicles. Recent developments in wireless power transfer (WPT) technology can enable an alternative vehicle recharging model wherein power is supplied to vehicles while they are moving, mitigating the need for charging stops and high-capacity on-board energy storage. One of the greatest concerns associated with dynamic WPT is that the required infrastructure costs would be prohibitively high; however, the life-cycle costs and benefits of such a system have been under-researched. Here in this work, we apply a systems-level assessment to a case study of a WPT charging system located on the densely trafficked I-710 corridor in Los Angeles, California. Detailed cost estimates for electronics and implementation, high-fidelity energy consumption modeling, and survey-derived adoption projections are applied to evaluate scenarios of economic feasibility and environmental impact. Results show that a “1st-of-a-kind” system can achieve a payback in 20 years while maintaining operating cost advantages relative to petroleum fueling. System economics are shown to improve substantially with “nth-of-a-kind” capital costs. Discussion focuses on the effect of uptake trajectory on economic viability and detailed economics outcomes for light duty and heavy duty vehicles.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

E-transit-bench: simulation platform for analyzing electric public transit bus fleet operations

When electrified transit systems make grid aware choices, improved social welfare is achieved by reducing grid stress, reducing system loss, and minimizing power quality issues. Electrifying transit fleet has numerous challenges like non availability of buses during charging, varying charging costs and so on, that are related the electric grid behavior. However, transit systems do not have access to the information about the co-evolution of the grid's power flow and therefore cannot account for the power grid's needs in its day-to-day operation. In this paper we propose a framework of transportation-grid co-simulation, analyzing the spatio-temporal interaction between the transit operations with electric buses and the power distribution grid. Real-world data for a day's traffic from Chattanooga city's transit system is simulated in SUMO and integrated with a realistic distribution grid simulation (using GridLAB-D) to understand the grid impact due to transit electrification. Charging information is obtained from the transportation simulation to feed into grid simulation to assess the impact of charging. We also discuss the impact to the grid with higher degree of transit electrification that further necessitates such an integrated transportation-grid co-simulation to operate the integrated system optimally. Our future work includes extending the platform for optimizing the charging and trip assignment operations.

Sen, Rishav↗
DOE OSTI2023

Pathways to Carbon Neutrality 2050 in Malaysia and Kuala Lumpur

Malaysia has recently set an ambitious target of achieving carbon neutrality as early as 2050. To accomplish this, the country will need to strategically reduce its emissions across all sectors. In 2020, Malaysia emitted approximately 368 MtCO2e, with the largest sources of emissions including electricity (36% of total emissions), transportation (17%), and industry (15%)1. We find that the greatest reductions in emissions can therefore come from decarbonizing power generation and electrifying end-use sectors. Digitalization, smart technologies, and improved energy efficiency will significantly reduce economy-wide energy consumption. By leveraging efficient technologies, both Malaysia and Kuala Lumpur can address the challenges posed by rapid urbanization and climate change. Digitalization is a broad category that includes a variety of measures; for example, the wide adoption of high-efficiency appliances and lighting or improved building energy codes in the buildings sector. Similarly, technological improvements can advance industrial energy efficiency, and for transportation, smart technologies cover a shift from private to public transportation and the greater use of electric vehicles. While renewable energy (RE) will play a crucial role in decarbonization, achieving carbon neutrality in certain sectors will be difficult without emerging technologies like carbon capture and storage (CCS) and innovative fuel sources such as hydrogen. In order for Malaysia to rely on CCS as a mitigation option, early investment and incentives to the private sector will be critical. This holds for the use of hydrogen as well: investing in the necessary technology, infrastructure, and human capital will allow Malaysia to position itself as an innovator in the region and leverage these advanced technologies as a key part of its climate strategy. Another possible carbon removal option other than CCS would be a land-use sink; however, given that Malaysia is still developing and may deforest in the near-term, this report does not focus on the mitigation potential of land-use change. With its innovative and bold climate plans, Kuala Lumpur is primed to be a leader in regional climate change efforts. Kuala Lumpur is also engaged in several international collaborations to ensure sustainable city development such as the C40 network and the ASEAN Smart Cities Partnership. As such, the city will play a critical role in contributing to Malaysia’s overall climate goals and as a policy trendsetter through ambitious, scalable plans. One key factor in these emissions reductions is that Kuala Lumpur has full control over its building guidelines, allowing for ambitious policies resulting in significant emissions reductions. However, in other sectors, Kuala Lumpur has less direct control over regulations; for example, power generation and integration of RE are largely in the hands of the Malaysian government. With limited and primarily light industry, Kuala Lumpur’s contributions to emissions reductions here are curbed. And, while Kuala Lumpur has control over local transportation policies like increasing access to and quality of public transportation, broad shifts in transportation will stem from national-level policies. As such, multi-level governance is an integral component of Malaysia’s climate strategy and coordination between local and national governments will be essential in reducing emissions and achieving other climate goals. This report addresses these and other key challenges and opportunities Malaysia faces on the road to carbon neutrality.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Selective electrified polyethylene upcycling by pore-modulated pyrolysis

Plastic waste is a increasing problem, accumulating in landfills and the environment. Pyrolysis is a promising and industrially relevant approach for transforming plastic waste into value-added chemicals. However, the selectivity and yield of traditional plastic pyrolysis are poor, with products featuring broad molar mass distributions. Here we report a highly selective, energy-efficient and catalyst-free pyrolysis method that can upcycle plastic into value-added chemicals via pore-modulated pyrolysis. Using a Joule-heated carbon column, we demonstrate the pivotal role of the reactor’s graded porous structure in decreasing the polydispersity of the reaction intermediates, enabling high product selectivity and yield. The decreasing pore size of the reactor modulates the mass transport in an apparent gating effect—preventing high-molar-mass species from exiting the reactor before sufficient pyrolysis has occurred. Using polyethylene as a model reactant, we demonstrate a high yield of 65.9 ± 5.2% and up to 80.8% selectivity toward value-added aviation fuel precursor (C8–C18 hydrocarbons) without the use of any catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

RouteE: A Vehicle Energy Consumption Prediction Engine

The emergence of connected and automated vehicles and smart cities technologies create the opportunity for new mobility modes and routing decision tools, among many others. To achieve maximum mobility and minimum energy consumption, it is critical to understand the energy cost of decisions and optimize accordingly. The Route Energy prediction model (RouteE) enables accurate estimation of energy consumption for a variety of vehicle types over trips or sub-trips where detailed drive cycle data are unavailable. Applications include vehicle route selection, energy accounting and optimization in transportation simulation, and corridor energy analyses, among others. The software is a Python package that includes a variety of pre-trained models from the National Renewable Energy Laboratory (NREL). However, RouteE also enables users to train custom models using their own data sets, making it a robust and valuable tool for both fast calculations and rigorous, data-rich research efforts. The pre-trained RouteE models are established using NREL’s Future Automotive Systems Technology Simulator paired with approximately 1 million miles of drive cycle data from the Transportation Secure Data Center, resulting in energy consumption behavior estimates over a representative sample of driving conditions for the United States. Validations have been performed using on-road fuel consumption data for conventional and electrified vehicle powertrains. Transferring the results of the on-road validation to a larger set of real-world origin-destination pairs, it is estimated that implementing the present methodology in a green-routing application would accurately select the route that consumes the least fuel 90% of the time. The novel machine learning techniques used in RouteE make it a flexible and robust tool for a variety of transportation applications.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Trends and 2025 Insights on the Rise of Electric Vehicles in the USA

Plug-in electric vehicles (EVs) are reshaping the transportation energy landscape, providing a practical alternative to petroleum fuels for a growing number of applications. EV sales grew 55x in the past decade (2014-2024) and 6x since 2020, driven by technological progress enabled by policies to reduce transportation emissions as well as industrial plans motivated by strategic value of EVs for global competitiveness, jobs and geopolitics. In 2024, 22% of passenger cars sold globally were EVs and opportunities for EVs beyond on-road applications are growing, including solutions to electrify off-road vehicles, maritime and aviation. This Review updates and expands our 2020 assessment of the scientific literature and describes the current status and future projections of EV markets, charging infrastructures, vehicle-grid integration and supply chains in the USA. EV is the lowest-emission motorized on-road transportation option, with life-cycle emissions decreasing as electricity emissions continue to decrease. Charging infrastructure grew in line with EV adoption but providing ubiquitous reliable and convenient charging remains a challenge. EVs are reducing electricity costs in several US markets and coordinated EV charging can improve grid resilience and reduce electricity costs for all consumers. The current trajectory of technology improvement and industrial investments points to continued acceleration of EVs.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Heavy-Duty Nonroad Material Handler Electrification Part 1: Real-World Drive Cycle Development

Knowing a detailed operating cycle is critical for developing and testing equipment. Operating cycles can be separated by two clear distinctions: (1) regulatory or non-regulatory and (2) application at the engine-only or full machine level. The Environmental Protection Agency’s (EPA) Nonroad Transient Cycle (NRTC) may be a good representation of engine use in many types of equipment, but there is a gap in standardized and validated drive cycles specifically for nonroad material handlers. Lacking a standardized drive cycle makes it difficult to accurately benchmark machine performance and validate new powertrain technologies. The objective of this investigation is to illustrate the development of a custom drive cycle augmented with real-world customer use data that serves multiple purposes: (1) understand the range of operation and utilization that formulated inputs for electrified architecture analysis and (2) develop a repetitive and consistent maneuver to establish baseline energy consumption enabling equivalent comparison to future electrified prototype builds. This article presents a solution specifically for a 23-ton nonroad material handler in which material handling, machine transport, and extended idle were homologated to form representative short cycles defined by machine velocity and hydraulic cylinder position. The most intensive material handling short cycles had a load factor of 40% and an average fuel rate of 16 L/h. Combined with a visual aid, the short cycles exhibited low variability, having less than 5% root mean square (RMS) error in lift and reach position with respect to the average. The machine’s performance on these short cycles at the Advanced Power Systems Research Center (APSRC) was compared to results from two real-world customer locations operating the instrumented test machine in a cyclical manner, and for similar ground conditions were found to be comparable in fuel consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Mobility Energy Productivity and Equity: E-Bike Impacts for Low-Income Essential Workers in Denver

New mobility technologies such as electrified and shared mobility, combined with polices and incentive programs, are emerging to help address sustainability and equity issues in transportation planning. However, it can be difficult to understand the impacts of novel mobility trends and emerging modes on energy-efficient access. This is owing to a lack of (1) open-source tools enabling rapid data collection, and (2) open-source metrics that consider multimodal, multiactivity access and mobility within the contexts of sustainability and equity. Here, this paper addresses the topic of improving evaluation of transportation modes and incentive programs by integrating an open-source platform for tracking human travel data—the Open Platform for Agile Trip Heuristics (OpenPATH)—with a mobility metric that quantifies the efficiency of a region’s transportation system: Mobility Energy Productivity (MEP). Integration is demonstrated in the context of pilot programs in Colorado, where low-income essential workers were provided with electric bikes (e-bikes). OpenPATH-informed MEP calculations showed that several locations in downtown Denver provided comparable time-, cost-, and energy-efficient access to opportunities using e-bikes compared with driving. Additionally, providing e-bikes to low-income essential workers was found to be meaningful, as they utilized e-bikes the most to commute, despite driving still being their most utilized mode and the mode with highest MEP scores in Denver. We show how data collected from open-source tools coupled with robust metrics such as MEP can help evaluate the impacts of emerging mobility options. This could support developing policies to incentivize novel modes to achieve greater levels of sustainable, equitable, and efficient access.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Understanding Subsidies to Achieve Diesel Powertrain Financial Parity for Heavy-Duty Fuel Cell Electric Vehicles

The development of a long-term sustainable hydrogen energy economy for commercial vehicle transportation will need to overcome key critical technical and logistics considerations in the near term. As compared to zero-emission powertrains, fossil-fuel-based powertrains provide mission flexibility and high uptime at a comparatively low total cost of ownership (TCO). While the incumbent carbon-intensive powertrains suffer from poor efficiency and are not sustainable to support global climate change initiatives in transportation decarbonization, techno-economic challenges continue to create complex barriers to the large-scale displacement of these with highly electrified powertrains architectures. Here, this article specifically addresses opportunities that well-targeted subsidies would afford in achieving fuel cell electric powertrain financial parity with diesel powertrains in heavy-duty trucks (HDTs). It shows that a rigorous assessment of system TCO factors will be critical in designing a viable subsidy strategy. Based on powertrain component and fuel price points, subsidy variations (for both capital expenses and operating fuel expenses) are assessed and quantified to determine where and how much subsidies should be leveraged to accelerate achieving diesel system financial parity. It shows that subsidies on hydrogen fuel expenses (and associated constituents) will play an important role in achieving this goal while subsidies on capital expenses (the more typical subsidy formulation) may not always be the preferred subsidy strategy. The results provide subsidy agencies with clear guidance and a database approach to characterize and implement viable HDT hydrogen powertrain system subsidy strategies. The approach may be readily tailored for other applications and system architectures.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Sustainable Public Transport: Providing Responsive, On-Demand Service with Clean Energy

The National Renewable Energy Laboratory (NREL) uses the Mobility Energy Productivity (MEP) as a metric and a lens to guide applied research into high performance public mobility. In the current initiative to abate global warming, the US needs not only zero-emission vehicles in the transit fleet (such as buses and shuttles) but also time- and cost-effective services to connect people with goods, services and employment toward a high-quality of life. Our current transportation system is overly dependent on personally-owned automobiles for high quality mobility, with public modes being less viable in many areas. Simply electrifying the drivetrains of existing public transit modes will fail to improve the quality of mobility for those that do not have access to private automobiles. The slow rebound by transit from the pandemic reveals the need to reinvent public transit service. Using the MEP lens, NREL researchers have tracked various novel developments in the public mobility space, with the confluence of shared, on-demand transit (ODT) services using light duty vehicles emerging as a key enabler of high-efficiency public mobility. Deployments such as those in Arlington, TX, Dallas, TX, Fort Erie, ON, and Innisfil, ON showcase the use of fleets of light-duty vehicles as the basis for community circulation and first/last mile to intra-regional transit. ODT services have demonstrated improvements in being more time efficient for riders, more energy efficient in operation (even before the introduction of fully electric vehicles), as well as being cost effective. It appears that aspects of the long-awaited promise of Personal Rapid Transit from the 1970s are beginning to be realized through ODT deployments, leveraging transportation network company (TNC) logistics, popularized by Uber and Lyft, but applied to public mobility. Currently, manually driven ODT operations are already cost competitive with traditional transit systems on a cost per ride basis, and full automation promises to reduce costs by 50% while providing additional safety and verified customer service. Connecting these ODT systems with efficient and effective intra-regional backbone transit service is the next step, with transit agencies like DART providing early results. This discussion will walk through the evidence for this postulated outcome and show results from a series of case-studies.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2023

Free-standing membrane incorporating single-atom catalysts for ultrafast electroreduction of low-concentration nitrate

The release of wastewaters containing relatively low levels of nitrate (NO 3 ⁻) results in sufficient contamination to induce harmful algal blooms and to elevate drinking water NO 3 ⁻ concentrations to potentially hazardous levels. In particular, the facile triggering of algal blooms by ultra-low concentrations of NO 3 ⁻ necessitates the development of efficient methods for NO 3 ⁻ destruction. However, promising electrochemical methods suffer from weak mass transport under low reactant concentrations, resulting in long treatment times (on the order of hours) for complete NO 3 ⁻ destruction. In this study, we present flow-through electrofiltration via an electrified membrane incorporating nonprecious metal single-atom catalysts for NO 3 ⁻ reduction activity enhancement and selectivity modification, achieving near-complete removal of ultra-low concentration NO 3 ⁻ (10 mg-N L -1 ) with a residence time of only a few seconds (10 s). By anchoring Cu single atoms supported on N-doped carbon in a carbon nanotube interwoven framework, we fabricate a free-standing carbonaceous membrane featuring high conductivity, permeability, and flexibility. The membrane achieves over 97% NO 3 ⁻ removal with high N 2 selectivity of 86% in a single-pass electrofiltration, which is a significant improvement over flow-by operation (30% NO 3 ⁻ removal with 7% N 2 selectivity). This high NO 3 ⁻ reduction performance is attributed to the greater adsorption and transport of nitric oxide under high molecular collision frequency coupled with a balanced supply of atomic hydrogen through H 2 dissociation during electrofiltration. Overall, our findings provide a paradigm of applying a flow-through electrified membrane incorporating single-atom catalysts to improve the rate and selectivity of NO 3 ⁻ reduction for efficient water purification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Predictive Engineering of Interfaces and Cathodes for High-Performance All Solid-State Lithium-Sulfur Batteries

The primary goal of this project is to leverage data-driven methods and machine learning strategies to develop accurate multi-physics models for all-solid-state Li-S battery (ASLSB) materials that can capture electrochemical and transport phenomena over atomic to mesoscopic length/timescales. These models will be rigorously validated by synthesis and advanced characterization experiments. The team will leverage the predictive power of these models, alongside synthesis/characterization experiments and battery fabrication to address longstanding issues at the electrode/electrolyte interfaces in ASLSBs. The project’s proposed technology involves the following: (1) halide-doped solid sulfide electrolytes that can concurrently provide high Li + ion conductivity and suppress dendrite growth; (2) novel mesoporous cathode composed of super-P and carbon nanotubes co-infiltrated with sulfur and sulfide electrolyte, which hold potential to allow high sulfur loading and optimal ion/electron pathways; and (3) functionalization of sulfide electrolyte with ionic liquids to improve physical contact and minimize impedance at the cathode/electrolyte interface. Successful development of proposed predictive models (at multiple scales) will bridge this knowledge gap and will advance fundamental understanding of reaction chemistry, kinetics, charge transfer, and dendrite growth at electrified SSIs. This will enable predictive design of effective strategies to mitigate interfacial problems in ASSLSBs, including poor interfacial contact, interfacial impedance to Li + ion transport, and poor electron/ion conduction within cathodes. Ultimately, the fundamental knowledge gained will lead to development of high-performance ASSLSBs.

25 ENERGY STORAGE↗
DOE OSTI2021

Future Cost Benefits Analysis for Electrified Vehicles from Advances Due to U.S. Department of Energy Targets

The U.S. Department of Energy’s Vehicle Technologies Office (DOE-VTO) supports research and development (R&D), as well as deployment of efficient and sustainable transportation technologies, that will improve energy efficiency and fuel economy and enable America to use less petroleum. To accelerate the creation and adoption of new technologies, DOE-VTO has developed specific targets for a wide range of powertrain technologies (e.g., engine, battery, electric machine, lightweighting, etc.). This paper quantifies the impact of VTO R&D on vehicle energy consumption and cost compared to expected historical improvements across vehicle classes, powertrains, component technologies and timeframes. We have implemented a large scale simulation process to develop and simulate tens of thousands of vehicles on U.S. standard driving cycles using Autonomie, a vehicle simulation tool developed by Argonne National Laboratory. Results demonstrate significant additional reductions in both cost and energy consumption due to the existence of VTO R&D targets compared to predicted historical trends. It is observed that, over time, the fuel consumption of different electrified vehicles is expected to decrease by 40–50% and a reduction of 45–55% for vehicle manufacturing costs owing to significant improvements through various VTO R&D targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Reactive capture and electrochemical conversion of CO 2 with ionic liquids and deep eutectic solvents

Ionic liquids (ILs) and deep eutectic solvents (DESs) have tremendous potential for reactive capture and conversion (RCC) of CO 2 due to their wide electrochemical stability window, low volatility, and high CO 2 solubility. There is environmental and economic interest in the direct utilization of the captured CO 2 using electrified and modular processes that forgo the thermal- or pressure-swing regeneration steps to concentrate CO 2 , eliminating the need to compress, transport, or store the gas. The conventional electrochemical conversion of CO 2 with aqueous electrolytes presents limited CO 2 solubility and high energy requirement to achieve industrially relevant products. Additionally, aqueous systems have competitive hydrogen evolution. In the past decade, there has been significant progress toward the design of ILs and DESs, and their composites to separate CO 2 from dilute streams. In parallel, but not necessarily in synergy, there have been studies focused on a few select ILs and DESs for electrochemical reduction of CO 2 , often diluting them with aqueous or non-aqueous solvents. The resulting electrode–electrolyte interfaces present a complex speciation for RCC. In this review, we describe how the ILs and DESs are tuned for RCC and specifically address the CO 2 chemisorption and electroreduction mechanisms. Critical bulk and interfacial properties of ILs and DESs are discussed in the context of RCC, and the potential of these electrolytes are presented through a techno-economic evaluation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

RouteE: A Vehicle Energy Consumption Prediction Engine

The emergence of connected and automated vehicles and smart cities technologies create the opportunity for new mobility modes and routing decision tools, among many others. To achieve maximum mobility and minimum energy consumption, it is critical to understand the energy cost of decisions and optimize accordingly. The Route Energy prediction model (RouteE) enables accurate estimation of energy consumption for a variety of vehicle types over trips or sub-trips where detailed drive cycle data are unavailable. Applications include vehicle route selection, energy accounting and optimization in transportation simulation, and corridor energy analyses, among others. The software is a Python package that includes a variety of pre-trained models from the National Renewable Energy Laboratory (NREL). However, RouteE also enables users to train custom models using their own data sets, making it a robust and valuable tool for both fast calculations and rigorous, data-rich research efforts. The pre-trained RouteE models are established using NREL's Future Automotive Systems Technology Simulator paired with approximately 1 million miles of drive cycle data from the Transportation Secure Data Center, resulting in energy consumption behavior estimates over a representative sample of driving conditions for the United States. Validations have been performed using on-road fuel consumption data for conventional and electrified vehicle powertrains. Transferring the results of the on-road validation to a larger set of real-world origin-destination pairs, it is estimated that implementing the present methodology in a green-routing application would accurately select the route that consumes the least fuel 90% of the time. The novel machine learning techniques used in RouteE make it a flexible and robust tool for a variety of transportation applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Energy consumption and charging load profiles from long-haul truck electrification in the United States

Abstract The urgent need to decarbonize the transportation sector combined with falling battery prices has spurred industry and policy interest in long-haul truck electrification. The charging behavior and resulting loads from electrified long-haul freight trucks are crucial for the smooth operation of the electric grid and have far-reaching environmental impacts (e.g., greenhouse gas and other air pollutant emissions). However, the aggregate energy impact of a fleetwide shift to electrified long-haul freight trucking has not been explored. This study combines electric truck design scenarios, bottom-up truck weight modeling, vehicle energy modeling, large-scale truck traffic data, and simulation of likely operation and charging behaviors to estimate end-use energy consumption and location-specific hourly charging loads for a national fleet of long-haul electric trucks. Relative to a fleet of future diesel trucks, electrification would reduce direct end-use energy consumption by 0.9 × 10 18 J (0.9 quadrillion BTU), but electrification might increase life cycle energy consumption depending on the electricity source. The electricity required to charge long-haul electric trucks is equivalent to five percent of annual electricity consumption in the United States (US). The simulated truck charging loads peak during the day across the US grid regions, but the charging peaks’ exact timing is sensitive to when trucks are dispatched for operation. The load shapes suggest that electric trucks’ charging loads can coincide with peaks in solar power generation, and planning could enable on- or off-site integration between truck charging stations and renewable electricity generation.

Tong, Fan (ORCID:0000000346613956)↗
DOE OSTI2025

Trapping and imaging dynamic battery nanointerfaces via electrified cryo-EM

The electrified interface between a liquid and a solid underpins diverse phenomena, from ion-transfer during battery operation to action potentials enabling biological communication. However, conventional tools are blind to the nanoscale dynamics of this metastable interface. Here, we leverage electrified cryo–electron microscopy (eCryo-EM), a technique that rapidly freezes and kinetically traps these dynamic, nonequilibrium states during battery operation for nanoscale characterization. Collective snapshots of the electrified interface at controlled time intervals quantifies early-stage growth kinetics of the solid electrolyte interphase (SEI), a passivation film that governs electron and ion transport. Unexpectedly, the diffusivity of charged species of the two SEI films with differing chemistry and performance are estimated to be within 10% of the other, indicated by the slope of their diffusion-limited SEI growth regimes. Instead, the slope of the reaction-limited SEI growth regimes differs by a factor of 3, suggesting that lowered reactivity of the high-performance electrolyte is largely responsible for its high coulombic efficiency.

Science & Technology - Other Topics↗