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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 325 records · Page 18

Using Mobile Charging Drones to Mitigate Battery Disruptions of Electric Vehicles on Highways

Our research explores innovative solutions to address the challenge of battery disruptions in electric vehicles (EVs) on highways. We propose a centralized fleet ownership model where a company manages a fleet of Mobile Charging Drones (MCDs) guided by a k-VRP (Vehicle Routing Problem) framework. This model is designed to tackle a multi-objective optimization issue with three primary goals: reduction of the overall operating costs, decrease in the cumulative waiting time, and minimization of the combined operating costs and waiting times. This approach extends beyond the usual VRP constraints, encompassing specific limitations for both MCDs and disrupted EVs (DEVs). Additionally, our study delves into the concept of decentralized fleet ownership through the lens of crowdsourcing. Preliminary numerical analyses indicate that the capital cost of MCDs is a significant factor on the charging service, and the system performance is sensitive to DEV owner's value of time (VOT) when VOTs are relatively low.

battery disruption↗

Ionization Yield in Silicon for eV-Scale Electron-Recoil Processes

The development of single charge resolving, macroscopic silicon detectors has opened a window into rare processes at the O(eV) scale. In order to reconstruct the energy of a given event, or model the charge signal obtained for a given amount of energy absorbed by the electrons in a detector, an accurate charge yield model is needed. In this paper we review existing measurements of charge yield in Silicon, focusing in particular on the region below 1 keV. We highlight a calibration gap between 12-50 eV (referred to as the "UV-gap") and employ a phenomenological model of impact ionization to explore the likely charge yield in this energy regime. Finally, we explore the impact of variations in this model on a test case, that of dark matter scattering off electrons, to illustrate the scientific impact of uncertainties in charge yield.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

BICEP/ Keck XII: Constraints on axionlike polarization oscillations in the cosmic microwave background

Here, we present a search for axionlike polarization oscillations in the cosmic microwave background (CMB) with observations from the Keck Array . A local axion field induces an all-sky, temporally sinusoidal rotation of CMB polarization. A CMB polarimeter can thus function as a direct-detection experiment for axionlike dark matter. We develop techniques to extract an oscillation signal. Many elements of the method are generic to CMB polarimetry experiments and can be adapted for other datasets. As a first demonstration, we process data from the 2012 observing season to set upper limits on the axion-photon coupling constant in the mass range 10 – 21 – 10 – 18 eV , which corresponds to oscillation periods on the order of hours to months. We find no statistically significant deviations from the background model. For periods larger than 24 hr (mass m < 4.8 × 10 – 20 eV ), the median 95% confidence upper limit is equivalent to a rotation amplitude of 0.68°, which constrains the axion-photon coupling constant to g Φ γ < ( 1.1 × 10 – 11 GeV – 1 ) m / ( 10 – 21 eV ) , if axionlike particles constitute all of the dark matter. The constraints can be improved substantially with data already collected by the BICEP series of experiments. Current and future CMB polarimetry experiments are expected to achieve sufficient sensitivity to rule out unexplored regions of the axion parameter space.

79 ASTRONOMY AND ASTROPHYSICS↗

Building Blocks of Electric Vehicle Deployment: A Guide for Developing Countries

Countries can use electric transportation to help fulfill numerous goals, including greenhouse gas (GHG) emissions targets, local air quality goals, mobility objectives, energy security, and transportation resiliency. Vehicle electrification is a promising pathway to achieving clean energy transitions in the transport sector at scale. As vehicles electrify, the traditionally siloed electricity and transport sectors increasingly converge to create technical, institutional, and economic opportunities and challenges. To navigate this transition effectively, we propose the following foundational pillars or “building blocks” that undergird effective electric vehicle (EV) deployment. Jurisdictions with experience and mature EV markets offer useful lessons learned that may enable developing countries to leapfrog over common roadblocks. Nonetheless, developing countries face distinct challenges collectively, and individually, from developed countries that require careful consideration. From our work around the world, the U.S. Agency for International Development (USAID) and National Renewable Energy Laboratory (NREL) have witnessed interest growing in EVs for a variety of reasons. Lao People’s Democratic Republic (PDR), for example, looks toward EVs as a way to use their surplus of hydropower to displace expensive oil. Thailand and Pakistan seek economic development opportunities in EV manufacturing. Cities including Mexico City, Surat, India, and Kingston, Jamaica see the potential of bus electrification to improve local air quality and reduce traffic congestion. Many USAID partner countries in Southeast Asia are trying to understand how to reach ambitious EV deployment targets and implement EV and transportation plans. This pursuit is prompting questions about EV supply equipment (EVSE) standards, tariff design, and business models that affirm the importance of the building blocks outlined in this report.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Development of a Hardware-in-The-Loop Testbed for a Decentralized, Data-Driven Electric Vehicle Charging Control Algorithm

This study presents the design of an electric vehicle (EV)-grid integration (EVGI) hardware test-bed to implement smart EV charging algorithms. Here, the proposed test-bed also allows to create different grid events via flexible integration of other power hardware (e.g., controllable loads and battery energy storage systems) and test their impacts on EV charging. The design uses a real-time digital simulator to realize a complex distribution grid model with primary and secondary networks. A grid simulator physically realizes the selected nodes of the simulated grid to power an actual EV, forming a hardware-in-the-loop (HIL) test setup. The EV-grid integration is demonstrated based on the custom hardware and software implementation of the J1772 charging protocol using dSPACE MicroLabBox, operating as a custom EV Supply Equipment (EVSE). The HIL test-bed features a novel testing platform for accurate implementation and analysis of scalable charging algorithms. To this end, a data-driven, decentralized, model-free charging controller based on the Additive Increase and Multiplicative Decrease (AIMD) algorithm is presented and validated on an EV using the HIL test-bed. We tested the proposed algorithm under various case studies, and presented a comparison study with an existing droop-based, decentralized charging solution. The results showed that the EV successfully performed charging commands generated by the EVSE and regulated its charging power to effectively reduce the system loading caused by high EV penetration.

33 ADVANCED PROPULSION SYSTEMS↗

A Dynamic Pricing Method to Manage the Impact of EV Charging on the Grid Using RL

This work addresses the challenge of managing electrical vehicle (EV) charging loads on distribution feeders with the increase in deployment of fast charging stations. To mitigate the adverse impacts on feeder health, a novel dynamic grid-informed pricing approach is proposed. This approach leverages reinforcement learning (RL) to determine hourly charging prices based on real-time grid conditions. A synthetic environment was developed to train the reinforcement learning agent. A model of an IEEE 34-bus distribution feeder with EV charging stations has been developed in OpenDSS utilizing Caldera for realistic EV charging profiles. Test cases demonstrate that the dynamic pricing strategy achieves higher energy delivery to the EV end user at a lower cost compared to constant pricing methods, while lowering voltage deviations and congestion. This approach offers more granular price adjustments, responding dynamically to feeder conditions and potentially improving grid stability and efficiency. The communication architecture to implement this dynamic pricing method is described. This research contributes to the development of smart grid-informed charging solutions that can reduce the cost of charging to the end user while also helping the grid.

EV charging, dynamic pricing, grid-informed chargi↗

A dynamic pricing method to manage the impact of EV charging on the grid using RL

This work addresses the challenge of managing electrical vehicle (EV) charging loads on distribution feeders with the increase in deployment of fast charging stations. To mitigate the adverse impacts on feeder health, a novel dynamic grid-informed pricing approach is proposed. This approach leverages reinforcement learning (RL) to determine hourly charging prices based on real-time grid conditions. A synthetic environment was developed to train the reinforcement learning agent. A model of an IEEE 34-bus distribution feeder with EV charging stations has been developed in OpenDSS utilizing Caldera for realistic EV charging profiles. Test cases demonstrate that the dynamic pricing strategy achieves higher energy delivery to the EV end user at a lower cost compared to constant pricing methods, while lowering voltage deviations and congestion. This approach offers more granular price adjustments, responding dynamically to feeder conditions and potentially improving grid stability and efficiency. The communication architecture to implement this dynamic pricing method is described. This research contributes to the development of smart grid-informed charging solutions that can reduce the cost of charging to the end user while also helping the grid.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

Comprehensive characterization of hepatocyte-derived extracellular vesicles identifies direct miRNA-based regulation of hepatic stellate cells and DAMP-based hepatic macrophage IL-1ß and IL-17 upregulation in alcoholic hepatitis mice.

Extracellular vesicles (EVs) have been growingly recognized as biomarkers and mediators of alcoholic liver disease (ALD) in human and mice. Here we characterized hepatocyte-derived EVs (HC-EVs) and their cargo for their biological functions in a novel murine model that closely resembles liver pathology observed in patients with alcoholic hepatitis (AH), the most severe spectrum of ALD. The number of circulating EVs and HC-EVs were significantly increased by 10-fold in AH mice compared to control mice. The miRNA(miR)-seq analysis detected 20 up-regulated and 4 down-regulated miRNAs (P < 0.001-0.05) in AH-HC-EVs. Treatment of murine primary hepatic stellate cells (HSCs) with AH-HC-EVs induced ?-SMA (P < 0.05) and Col1a1 (P < 0.001). Smad7, Nr1d2, and Rora genes which regulate HSC activation were predicted targets of 17 miRs up-regulated in AH-HC-EVs. Among them were miR-27a and miR-181 which upon transfection in HSCs, repressed Nr1d2, the HSC quiescence marker. AH-HC-EVs were also enriched in organelle proteins and mitochondrial DNA (10-fold, P < 0.05) and upregulated IL-1??and IL-17 production by hepatic macrophages (HMs) from AH mice in a TLR9-dependent manner. These results demonstrate HC-EV release is intensified in AH and suggest that AH-HC-EVs orchestrate liver fibrogenesis by directly targeting HSC quiescence transcripts via a unique set of miRNAs and by amplifying HSC activation via DAMP-based induction of profibrogenic IL-1? and IL-17 by HMs.

AH, hepatocyte-derived EVs, miRNAs, DAMPs, HSC act↗

Electric-vehicle battery second-life and recycling pathways: How economics depend on chemistry, processing, and application

We assess the economics of repurposing and recycling electric vehicle (EV) batteries by estimating the maximum acquisition price repurposers and recyclers could pay for used EV packs across cathode chemistries, first-life conditions, second-life applications, and recycling processes. We develop a novel open-source process-based cost model of a UL-1974-certified repurposing facility and leverage battery degradation models to estimate the maximum acquisition price repurposers could pay for used EV batteries while producing second-life battery energy storage systems with life-adjusted costs equivalent to new systems. We compare these maximum price estimates to maximum prices for recyclers based on cost and revenue estimates from the EverBatt model. We find that repurposing is more economical than recycling for lithium iron phosphate (LFP) batteries, due to their relatively long life and low value materials; recycling is generally more economical than repurposing for lithium nickel cobalt aluminum oxide (NCA) batteries, due to their shorter life and higher value materials; and the economics for lithium nickel manganese cobalt oxide (NMC) batteries depend more heavily on first life retirement conditions and second life application intensity. These results suggest an overall strategy: reuse LFP, recycle NCA, and sort NMC into recycling or repurposing pathways based on state of health and second-life application.

25 ENERGY STORAGE↗

A modified thermal conductivity for low density plasma magnetic flux tubes

In response to inconsistencies which have arisen in results from a hydrodynamic model in simulation of high ion temperature (1-2 eV) observed in low density, outer plasmasphere flux tubes, we postulate a reduced thermal conductivity coefficient in which only particles in the loss cone of the quasi-collisionless plasma contribute to the thermal conduction. Other particles are assumed to magnetically mirror before they reach the topside ionosphere and therefore not to remove thermal energy from the plasmasphere. This concept is used to formulate a mathematically simple, but physically limiting model for a modified thermal conductivity coefficient. When this modified coefficient is employed in the hydrodynamic model in a case study, the inconsistencies between simulation results and observations are largely resolved. The high simulated ion temperatures are achieved with significantly lower ion temperatures in the topside ionosphere. We suggest that this mechanism may be operative under the limited low density, refilling conditions in which high ion temperatures are observed.

Comfort, R. H.↗

High Pressure Synthesis of Pr 2 O 5 – A Unique Lanthanoid(IV) Oxide Peroxide

Abstract Reacting praseodymium(IV) oxide with oxygen at 27 GPa in a diamond anvil cell yielded the oxide peroxide Pr 2 IV (O 2 )O 3 , which was characterized by single crystal X‐ray diffraction on multi‐grain samples, Raman spectroscopy and quantum theoretical calculations at various pressure points. The presence of tetravalent praseodymium ions is supported by electronic structure calculations, showing a band gap of ca. 1.2 eV, which is consistent with the anticipated chemical model of an ionic solid. Pr 2 (O 2 )O 3 thus far represents the most oxygen rich phase of any binary compound of a lanthanoid and oxygen and is the first example of a peroxide anion next to Pr 4+ . Additionally, these results demonstrate that instead of oxidizing the praseodymium ions past their +IV oxidation state, oxygen undergoes a comproportionation to form peroxide anions. Direct oxidation of the oxide anions by Pr 4+ ‐ions was ruled out by a control experiment in argon instead of oxygen, where no oxidation of oxide ions was observed.

Chemistry↗

Multiscale geographically and temporally weighted regression (MGTWR): exploring the spatiotemporal heterogeneity of EV market adoption

As an innovative vehicle technology, electric vehicles are experiencing growing sales and have made significant inroads into the traditional automotive market in the United States and around the world. However, EV adoption rates vary significantly across space and over time, influenced by a complex interplay of socio-economic and infrastructural factors alongside federal and state policies. Here, this paper presents a comprehensive spatial–temporal investigation of EV market adoption within one city in the US, that of Chicago, utilizing Multiscale Geographically and Temporally Weighted Regression (MGTWR) alongside Multiscale Geographically Weighted Regression (MGWR). The aim is to unravel the spatial and temporal dynamics affecting EV adoption and to explore how the influence of various determinants of EV adoption, such as demographic factors and economic conditions, vary spatially. Moreover, by utilizing MGTWR, we provide insights into the evolution of these relationships over time, offering a predictive outlook on future EV market growth. Our findings, with an 86.6% prediction accuracy for EV market adoption, tailored policy measures to support accelerated EV adoption. Methodologically, this work advances MGWR frameworks by integrating temporal dynamics to examine nonstationary processes in spatially disaggregated contexts. These findings offer evidence–based guidance for policymakers, urban planners, and stakeholders in the automotive industry, supporting the transition toward a more sustainable and efficient transportation system.

EV Market Adoption↗

Understanding the effects of radiative preheat and self-emission from shock heating on equation of state measurement at 100s of Mbar using spherically converging shock waves in a NIF hohlraum

Over the last six years many experiments have been done at the National Ignition Facility to measure the Hugoniot of materials, such as CH plastic at extreme pressures, up to 800 Mbar. The “Gbar” design employs a strong spherically converging shock launched through a solid ball of material using a hohlraum radiation drive. Here, the shock front conditions are characterized using x-ray radiography. In this paper we examine the role of radiation in heating the unshocked material in front of the shock to understand the impact it has on equation of state measurements and how it drives the measured data off the theoretical Hugoniot curve. In particular, the two main sources of radiation heating are the preheating of the unshocked material by the high-energy kilo-electron-volt x-rays in the hohlraum and the heating of the material in front of the shock, as the shocked material becomes hot enough to radiate significantly. Using our model, we estimate that preheating can reach 4 eV in unshocked material, and that radiation heating can begin to drive data off the Hugoniot significantly, as pressures reach above 400 Mb.

Equations of state↗

USAID Colombia Young Leaders Workforce Training Program Action Plans: Planning for Electric Vehicle Charging Infrastructure in Bogotá

As part of the U.S. Agency for International Development (USAID)-National Renewable Energy Laboratory (NREL) Young Leaders Workforce Training Program in Colombia, the Grupo Energía Bogotá (GEB) participants leveraged their training and professional experience to develop an action plan for modeling and evaluating Bogotá's projected electric vehicle (EV) charging needs to meet future demand. This case study summarizes the collaboration between USAID-NREL, GEB, and the Bogotá Department of Transportation Mobility Secretariat (SDM) to estimate EV charging station needs to meet projected future EV sales in the city of Bogotá and determine high-priority locations within the greater Bogotá metropolitan area for planning and applying EVSE investment and installation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Electronic Structure and Mechanical Properties of Solvated Montmorillonite Clay Using Large-Scale DFT Method

Montmorillonite clay (MMT) has been widely used in engineering and environmental applications as a landfill barrier and toxic waste repository due to its unique property as an expandable clay mineral that can absorb water easily. This absorption process rendered MMT to be highly exothermic due to electrostatic interactions among molecules and hydrogen bonds between surface atoms. A detailed study of a large supercell model of structural clay enables us to predict long-term nuclear waste storage. Herein, a large solvent MMT model with 4071 atoms is studied using ab initio density functional theory. The DFT calculation and analysis clarify the important issues, such as bond strength, solvation effect, elasticity, and seismic wave velocities. These results are compared to our previous study on crystalline MMT (dry). The solvated MMT has reduced shear modulus (G), bulk modulus (K), and Young’s modulus (E). We observe that the conduction band (CB) in the density of states (DOS) of solvated MMT model has a single, conspicuous peak at –8.5 eV. Moreover, the atom-resolved partial density of states (PDOS) summarizes the roles played by each atom in the DOS. These findings illuminate numerous potential sophisticated applications of MMT clay.

36 MATERIALS SCIENCE↗

Enhanced indirect optical absorption in AlAs and GaP.

Measurement and analysis of indirect interband optical absorption in GaP. Deviations from a simple indirect absorption law are shown to be consistent with those given by a model which takes into account both the variation of the energy denominators with photon energy and indirect absorption to higher-energy conduction-band valleys. The analysis of the GaP data indicates that such an analysis on data of limited absorption-constant range can provide reasonably accurate values of the direct band gap. The value of the direct band gap best fitting this model for AlAs at 6 K is 3.13 eV. In GaP and AlAs there is evidence of a higher set of extrema giving rise to an additional indirect absorption component 0.34 and 0.20 eV, respectively, above that due to the lowest-energy conduction-band minima. The strength of the absorption due to these higher-energy valleys indicates that they contain states of X sub 3 symmetry.

Dumke, W. P.↗

Model potentials for electron scattering - Converged close coupling calculations for the differential cross section for e/-/N2 at 30-50 eV

A calculation has been made of the elastic scattering and rotational excitation cross sections for e(-)-N2 scattering at 30 and 50 eV using quantum chemical techniques specially designed to be applicable to elastic and inelastic electron scattering by general polyatomic molecules. The angle dependence of the sum of the elastic and rotational excitation differential cross sections is in good agreement with experiment at all scattering angles at both energies, but at 50 eV the difference from experiment exceeds the experimental uncertainty at small scattering angles and near the minimum of the differential cross section. At large scattering angles the rotational excitation cross sections are predicted to exceed the elastic scattering cross sections. The absolute cross sections agree with experiment at some angles but at other angles are as much as 51% (30 eV) or 90% (50 eV) higher; this may be due at least in part to the difficulty of putting the experimental results on an absolute scale.

Onda, K.↗

Energetic binary collisions in rare gas plasmas

Calculations have been made of cross sections for energy and momentum transfer in binary collisions between like pairs of Ar, Kr, and Xe atoms in the energy range from about 1 to 1000 eV. These calculations were made using a classical model with pair interaction potentials for the rare gases developed from experimental sources, e.g., investigations of specific heats, viscosities, solid-state parameters, and scattering data. Cross sections in this energy range have not been available. The cross sections exhibit a rapid decrease from accepted values at thermal energies as the interaction energy increases. This behavior can be used to understand directed beam propagation limits as well as particle propagation within a plasma. Experimental data have also been fit to a theoretical expression for the Ar resonance charge exchange cross section over the same energy range.

Robinson, R. S.↗