Search NASA⌕ Search

SEARCH · Search NASA

Results for “EV modeling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Highly Resolved Projections of Passenger Electric Vehicle Charging Loads for the Contiguous United States: Results From and Methods Behind Bottom-Up Simulations of County-Specific Household Electric Vehicle Charging Load (Hourly 8760) Profiles Projected Through 2050 for Differentiated Household and Vehicle Types

This report documents enhancements made to the TEMPO (Transportation Energy & Mobility Pathway Options TM ) model to project spatially, demographically, and temporally resolved national-scale EV charging load profiles and describes three scenarios and corresponding datasets created for the NREL demand-side grid (dsgrid) project in support of bulk power systems modeling. In brief, TEMPO was enhanced to disaggregate national and annual energy demand projections into household and county-level projections of passenger electric vehicle (EV) hourly charging load profiles (8760 profiles), accounting for consumer, travel, and temperature variations that impact EV energy demand. In alignment with NREL's forward-looking grid modeling, three scenarios for EV adoption covering 2020-2050 were created-- Annual Energy Outlook (AEO) Reference Case, Electrification Futures Study (EFS) High Electrification, and All EV Sales by 2035 --and associated datasets have been included in the dsgrid platform for public use.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Sizing Energy Storage System for Energy Arbitrage in Extreme Fast Charging Station

This paper proposes a non-linear programming (NLP) model to optimally size the energy storage system (ESS) and obtain an optimal energy management for energy arbitrage of an extreme fast charging station (XFCS) for electric vehicles (EVs), with minimized total cost of XFCS operation and ESS investment. Different from most reported work on sizing the ESS for EV charging stations, this paper proposes a pragmatic approach to model the ESS life degradation and accurately count the ESS cycles. Moreover, this work incorporates the peak demand charges in the operational cost of the charging station which are often overlooked in the literature. The proposed model is formulated and solved using AIMMS. Finally, a thorough sensitivity analysis is performed to offer insights into how different input parameters impact the ESS sizing and savings from the energy arbitrage perspective.

25 ENERGY STORAGE↗
DOE OSTI2020

How Bulk Sensitive is Hard X-ray Photoelectron Spectroscopy: Accounting for the Cathode–Electrolyte Interface when Addressing Oxygen Redox

Sensitivity to the `bulk' oxygen core orbital makes hard X-ray photoelectron spectroscopy (HAXPES) an appealing technique for studying oxygen redox candidates. Various studies have reported an additional O 1s peak (530-531 eV) at high voltages, which has been considered a direct signature of the bulk oxygen redox process. Here, we find the emergence of a 530.4 eV O 1s HAXPES peak for three model cathodes, Li 2 MnO 3 , Li-rich NMC, and NMC 442, that shows no clear link to oxygen redox. Instead, the 530.4 eV peak for these three systems is attributed to transition metal reduction and electrolyte decomposition in the near-surface region. Claims of oxygen redox relying on photoelectron spectroscopy must explicitly account for the surface sensitivity of this technique and the extent of the cathode degradation layer.

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

Online Energy-optimal Routing for Electric Vehicles with Combinatorial Multi-arm Semi-Bandit

We have seen a rapid growth in the adoption of electric vehicle in today’s commercial mobility service market, from carrying passengers to the delivery of goods. One cardinal issue concerning the operation of EVs is the optimal routing of EV fleets with limited battery capacity. In this study, we investigate the energy-optimal online routing problem for the fleet of EVs, which focuses on identifying real-time minimum electricity consumption paths (MECP) for multiple OD pairs with limited information. We develop a multi-OD combinatorial multi-arm semi-bandit model (MCMAB) that uses the fleet of EVs as sensors in the transportation network and promotes the utilization of common information shared by different OD pairs. We further enrich the model with the path elimination policy to obtain MECP of high confidence while significantly reducing the number of learning iterations and the number of explorations needed. We demonstrate the effectiveness of the MCMAB and the efficiency of the path elimination policy with comprehensive numerical experiments in Manhattan, NYC. The results show that the proposed online routing algorithms can achieve near-optimal MECPs efficiently, and the quality of the solutions is significantly better than using the shortest travel time paths as approximate MECPs.

Chen, Xiaowei↗
DOE OSTI2025

Prediction of hydration energies of adsorbates at Pt(111) and liquid water interfaces using machine learning

Aqueous phase heterogeneous catalysis is important to various industrial processes, including biomass conversion, Fischer–Tropsch synthesis, and electrocatalysis. Accurate calculation of solvation thermodynamic properties is essential for modeling the performance of catalysts for these processes. Explicit solvation methods employing multiscale modeling, e.g., involving density functional theory and molecular dynamics have emerged for this purpose. Although accurate, these methods are computationally intensive. This study introduces machine learning (ML) models to predict solvation thermodynamics for adsorbates on a Pt(111) surface, aiming to enhance computational efficiency without compromising accuracy. In particular, ML models are developed using a combination of molecular descriptors and fingerprints and trained on previously published water–adsorbate interaction energies, energies of solvation, and free energies of solvation of adsorbates bound to Pt(111). These models achieve root mean square error values of 0.09 eV for interaction energies, 0.04 eV for energies of solvation, and 0.06 eV for free energies of solvation, demonstrating accuracy within the standard error of multiscale modeling. Feature importance analysis reveals that hydrogen bonding, van der Waals interactions, and solvent density, together with the properties of the adsorbate, are critical factors influencing solvation thermodynamics. Furthermore, these findings suggest that ML models can provide rapid and reliable predictions of solvation properties. This approach not only reduces computational costs but also offers insights into the solvation characteristics of adsorbates at Pt(111)–water interfaces.

Adsorption↗
DOE OSTI2022

Finding predictive models for singlet fission by machine learning

Singlet fission (SF), the conversion of one singlet exciton into two triplet excitons, could significantly enhance solar cell efficiency. Molecular crystals that undergo SF are scarce. Computational exploration may accelerate the discovery of SF materials. However, many-body perturbation theory (MBPT) calculations of the excitonic properties of molecular crystals are impractical for large-scale materials screening. We use the sure-independence-screening-and-sparsifying-operator (SISSO) machine-learning algorithm to generate computationally efficient models that can predict the MBPT thermodynamic driving force for SF for a dataset of 101 polycyclic aromatic hydrocarbons (PAH101). SISSO generates models by iteratively combining physical primary features. The best models are selected by linear regression with cross-validation. The SISSO models successfully predict the SF driving force with errors below 0.2 eV. Based on the cost, accuracy, and classification performance of SISSO models, we propose a hierarchical materials screening workflow. Three potential SF candidates are found in the PAH101 set.

36 MATERIALS SCIENCE↗
DOE OSTI2024

An integrated transportation-power system model for a decarbonizing world

Rising demand for electricity from electric vehicles (EVs) will require new paradigms to guarantee reliable and low-cost electricity. This study couples an agent-based travel demand simulator and an electricity grid model to assess the economic costs of supplying power to meet EVs' added demand across the Chicago region. Results suggest that shifting from personal EVs to a fleet of shared, fully-automated all-electric vehicles (SAEVs) could lower per-mile emissions, congestion, and embodied vehicle and charging infrastructure emissions. Further, the results should compel policymakers to shift the cost of providing power onto commercial customers, like electric ride-hail fleets, through price-indexed electricity prices, which can shift charging to off-peak periods or away from resource-scarce hours.

Integrated modeling↗
DOE OSTI2024

Frequency Support From Electric Vehicles for Advancing Renewable Energy Integration

The integration of renewable energy resources (RERs) in the modern power grid is increasing rapidly because of aggressive decarbonization goals, lower costs, and increased government investment. However, higher penetrations of inverter-based generation can lead to frequency stability issues because of reduced system inertia. This paper develops a framework for quantifying the contribution of electric vehicles (EVs) toward providing frequency support to the grid and thus increasing the penetration limit of renewable energy resources (RERs). EVs are considered to provide both inertial response and primary frequency response support to the grid. A stochastic approach incorporating the uncertainties associated with the behavior of EVs is developed to derive the discharge limit of EV aggregators. A multi-machine system frequency response (MM-SFR) model is developed, which incorporates the dynamic virtual inertia and droop coefficients of EV aggregators derived from the EV control modules. Frequency security constraints are developed from this MM-SFR model, which, along with the converter voltage security and low voltage ride-through constraints, are integrated within a nonlinear optimization framework to determine the RER integration limit. Here, the efficacy of the proposed approach is validated using the RTS-GMLC test system.

25 ENERGY STORAGE↗
DOE OSTI2024

Increasing Electric Vehicle Adoption Among Disadvantaged Populations: A Case Study in LA

In the shift towards 100% carbon-free energy, ensuring equitable access to clean energy benefits is crucial. The adoption of electric vehicles (EVs), particularly in the personal light-duty vehicle segment, has gained traction, driven by various incentives at the federal, state, and local levels. However, disadvantaged populations face unique challenges in embracing EVs. This paper, using Los Angeles as a case study, explores EV adoption patterns among disadvantaged population groups in both a business-as-usual scenario and an equity scenario. Modeling reveals that by 2035, over half of EV owners will be from low- to middle income backgrounds with limited access to home charging. Strategies such as increasing incentives for used EV purchase from $2500 to $4000, targeted for disadvantaged communities, can boost EV adoption among low-middle income groups by 2%, while providing a $300 annual voucher to households using public charging can further facilitate equitable EV adoption.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

EM Physics

Geant4 provides a comprehensive set of electromagnetic (EM) processes and models for electron/positron, gamma and long-lived charged particles, spanning energies from 100 eV to 100 TeV. Covering diverse energy regions often requires multiple models, which can be constructed using pre-packaged or user-defined EM physics constructors. Geant4 also supports detailed low-energy EM physics through models like Livermore, Penelope, and ICRU73, offering extensive data for elements across a wide energy range (250 eV–100 GeV). Application domains include space, medical, and radiobiology simulations. Additionally, Geant4 provides robust options for simulating complex optical photon production and transportation processes, enhancing its versatility in physics research and applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Optimal Electric Vehicle Charging and Discharging Strategies Under DER Compensation Programs: Preprint

The adoption of electric vehicles (EVs) is becoming increasingly popular because of environmental concerns, the greater availability of models, and increased cost-competitiveness with gas vehicles. Because EVs have both charging and discharging capabilities, they provide great potential to help electric utilities with grid operation. When the grid demand is high, EVs can discharge to the grid to reduce the peak load, and vice versa; therefore, electric utilities have designed different policies to encourage EV charging station operators to charge or discharge at certain time periods. The New York State Public Service Commission established the Value of Distributed Energy Resources (VDER), or the Value Stack, to compensate for energy created by distributed energy resources, including EVs. This paper presents an optimization-based approach to identify the "golden hours" and "golden spots," i.e., the effective time periods and geographic locations for EV charging station operators to charge or discharge under the VDER program that can provide them the highest benefit. The proposed methodology can be applied to other compensation mechanisms and distribution systems as well. By working with industry partner NineDot Energy, realistic charging station information is used in this study, and the proposed approach is tested on a distribution feeder. The results from this study can help electric utilities and EV charging station operators determine the ideal charging/discharging time and the ideal locations for the charging station(s) in their distribution systems to achieve maximized benefit.

electric vehicle↗
DOE OSTI2024

County Electric Vehicle Home Charging Access Shares from the 2030 National Charging Network Study

This file contains modeled county-level home electric vehicle (EV) charging access shares from the study, "The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure" by Wood et al. (2023). These are based on modeling in "There's No Place Like Home: Residential Parking, Electrical Access, and Implications for the Future of Electric Vehicle Charging Infrastructure" by Ge et al. (2021). Wood, Eric, et al. 2023. The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure. Golden, CO: National Renewable Energy Laboratory. NREP/TP-5400-85654. https://www.nlr.gov/docs/fy23osti/85654.pdf . Ge, Yanbo, et al. 2021. There's No Place Like Home: Residential Parking, Electrical Access, and Implications for the Future of Electric Vehicle Charging Infrastructure. Golden, CO: National Renewable Energy Laboratory. NREL/TP-5400-81065. https://www.nlr.gov/docs/fy22osti/81065.pdf .

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Reaction Pathways and Energy Consumption in NH 3 Decomposition for H 2 Production by Low Temperature, Atmospheric Pressure Plasma

Pathways for NH 3 decomposition to N 2 and N 2 H 4 by atmospheric pressure nonthermal plasma are analyzed using a combination of molecular beam mass spectrometry measurements and zero-dimensional kinetic modeling. Experimental measurements show that NH 3 conversion and selectivity towards N 2 formation scale monotonically with the specific energy input into the plasma with ~ 100% selectivity to N 2 formation achieved at specific energy inputs above 0.12 J cm −3 (3.1 eV (molecule NH 3 ) −1 ). The kinetic model recovers these trends, although it underpredicts N 2 selectivity at low specific energy input. These discrepancies can be explained by the underestimation of reaction rate coefficients for reactions that consume N 2 H x species in collisions with H radicals and/or radial nonuniformities in power deposition, gas temperature, and species concentrations that are not represented by the plug flow approximation used in the model. The kinetic model shows that N 2 formation proceeds through N 2 H x decomposition pathways rather than NH x decomposition pathways in low temperature, atmospheric pressure plasma. Higher selectivity toward N 2 production can be achieved by operating at higher NH 3 conversion and with a higher gas temperature. Furthermore, the high energy cost of NH 3 decomposition by atmospheric pressure nonthermal plasma found in this work (25–50 eV (molecule NH 3 converted) −1 ; 17–33 eV (molecule H 2 formed) −1 ) is a result of the energy requirement for electron-impact dissociation of NH 3 and the significant re-formation of NH 3 by three-body recombination reactions between NH 2 and H.

Nonthermal plasma↗
DOE OSTI2020

TMAP modeling of D release from baked multi-layer Be–D co-deposits

Single-layer Beryllium–Deuterium (Be–D) co-deposits were analyzed using Thermal Desorption mass Spectrometry (TDS) as outlined in the companion paper. This work details the TMAP modeling and the analysis of selected samples that received double-layer (DL) coatings to study co-deposit thickness and prior bake effects. Here, TDS data were simulated with detrap energies 0.8, 0.9, and 1.0 eV. In DLs formed at 393 K, modeling revealed that under-layers baked at 623 K for either 2 or 20 h had little pumping effect on over-layers, suggesting empty trap removal during bake. Extrapolated to ITER, data and analysis suggest less impact on the ongoing ITER bake efficiency than previously predicted.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Hydrodynamic expansion and near-infrared absorption of x-ray heated aluminum plasmas

We use x-ray pulses from dense argon plasmas at the Z Machine (Sandia National Laboratories) to generate hypersonic aluminum plasmas akin to material ejecta during proposed planetary defense missions, fusion reactor wall excursions, and other high-energy density processes. Near-infrared absorption is used to diagnose the controlled expansion of the plasmas through cylindrical cavities following their generation from x-ray heating of solid aluminum 7075 alloy. The data are compared to multidimensional radiation hydrodynamics simulations utilizing the ALEGRA multiphysics code, accounting for the dynamics of radiation scattering, material phase change, plasma expansion, thermal re-irradiation, and interactions with the cavity and with the infrared beams. To allow for accurate simulation, density functional theory is used to apply the Hagen–Rubens relation for the far-infrared and is adjoined with a detailed configuration accounting model using the Propaceos code, producing opacities spanning 10 −1 –10 4 eV photon energy for aluminum 7075 alloy, and in comparison with pure aluminum. The model is found to agree with experimental data in the higher-fluence regime when the Hagen–Rubens relation is applied. The ejected material, which is observed to travel up to 55 km/s, is comprised of a strongly ionized, non-LTE plasma front at ∼10 eV temperature followed by a weakly ionized LTE gas at higher density. The present findings lend some confidence to the broad-range equation of state and infrared opacity models for weakly ionized aluminum plasmas while demonstrating an approach to their future refinement, with potential application to astrophysical plasmas and other extreme processes.

Adiabatic process↗
DOE OSTI2025

Constraints on neutrino physics from DESI DR2 BAO and DR1 full shape

The Dark Energy Spectroscopic Instrument (DESI) Collaboration has obtained robust measurements of baryon acoustic oscillations in the redshift range 0.1 < 𝑧 < 4.2, based on the Lyman-𝛼 forest and galaxies from data release 2. We combine these measurements with cosmic microwave background (CMB) data from Planck and the Atacama Cosmology Telescope to place our tightest constraints yet on the sum of neutrino masses. Assuming the cosmological Λ⁢ CDM model and three degenerate neutrino states, we find ∑𝑚 𝜈 < 0.0642 eV (95%) with a marginalized error of 𝜎⁡(∑𝑚 𝜈 ) = 0.020 eV. We also constrain the effective number of neutrino species, finding 𝑁 eff = 3.2⁢3$^{+0.35}_{−0.34}$ (95%), in line with the Standard Model prediction. When accounting for neutrino oscillation constraints, we find a preference for the normal mass ordering and an upper limit on the lightest neutrino mass of 𝑚 𝑙 < 0.023 eV (95%). However, we determine using frequentist and Bayesian methods that our constraints are in tension with the lower limits derived from neutrino oscillations. Correcting for the physical boundary at zero mass, we report a 95% Feldman-Cousins upper limit of ∑𝑚 𝜈 < 0.053 eV, breaching the lower limit from neutrino oscillations. Considering a more general Bayesian analysis with an effective cosmological neutrino mass parameter, ∑𝑚 𝜈,eff , that allows for negative energy densities and removes unsatisfactory prior weight effects, we derive constraints that are in 3⁢𝜎 tension with the same oscillation limit, while the error rises to 𝜎⁡(∑𝑚 𝜈,eff ) = 0.053 eV. In the absence of unknown systematics, this finding could be interpreted as a hint of new physics not necessarily related to neutrinos. The preference of DESI and CMB data for an evolving dark energy model offers one possible solution. In the 𝑤 0 ⁢𝑤 𝑎 ⁢CDM model, we find ∑𝑚 𝜈 < 0.163 eV (95%), relaxing the neutrino tension. These constraints all rely on the effects of neutrinos on the cosmic expansion history. Using full-shape power spectrum measurements of data release 1 galaxies, we place complementary constraints that rely on neutrino free streaming. Our strongest such limit in Λ ⁢CDM, using selected CMB priors, is ∑𝑚 𝜈 < 0.193 eV (95%).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Demand-Side Grid (dsgrid) TEMPO Light-Duty Vehicle Charging Profiles v2022

Simulated hourly electric vehicle charging profiles for light-duty household passenger vehicles in the contiguous United States, 2018-2050. Profiles are differentiated by scenario, county, household and vehicle types, and charging type. Data was produced in 2022 using the Transportation Energy & Mobility Pathway Options (TEMPO) model and published in demand-side grid (dsgrid) toolkit format. Data are available for three adoption scenarios: "AEO Reference Case", which is aligned with the U.S. EIA Annual Energy Outlook 2018 (linked below), "EFS High Electrification", which is aligned with the High Electrification scenario of the Electrification Futures Study (linked below), and "All EV Sales by 2035", which assumes that average passenger light-duty EV sales reach 50% in 2030 and 100% in 2035. The charging shapes are derived from two key assumptions of which data users should be aware: "ubiquitous charger access", meaning that drivers of vehicles are assumed to have access to a charger whenever a trip is not in progress, and "immediate charging", meaning that immediately after trip completion, vehicles are plugged in and charge until they are either fully recharged or taken on another trip. These assumptions result in a bounding case in which vehicles' state of charge is maximized at all times. This bounding case would minimize range anxiety, but is unrealistic from the point of view of both electric vehicle service equipment (EVSE) (i.e., charger) access, and plug-in behavior as it can result in dozens of charging sessions per week for battery electric vehicles (BEVs) that in reality are often only plugged in a few times per week.

Array↗
DOE OSTI2022

A reduced model for the ITER divertor based on SOLPS solutions for ITER Q = 10 baseline conditions: A. identifying options for the control parameters*

Edge codes such as SOLPS coupled to neutral codes such as EIRENE have become so comprehensive and sophisticated that they now constitute, in effect, 'code-experiments' that, as for actual experiments, can benefit from interpretation using simple models and conceptual frameworks, i.e. reduced models. The first task is the identification of options for the reduced model control parameters that are best suited for control of the action of the divertor, i.e. for control of target power loading and sputter-erosion, primarily. A strong correlation between the electron temperature at the divertor target, T e,t , and the neutral deuterium D 2 density at the target, n D2,t , flux-tube resolved, has recently been reported for a number of code studies including SOLPS-4.3 modeling of a set of ~50 ITER baseline cases: Q DT = 10, q 95 = 3, P SOL = 100 MW, metallic walls, and Ne seeding. This part A of the present study reports new results for largely the same ITER cases, confirming the strong correlations reported earlier between local values of T e,t , and (i) n D2,t , and (ii) normalized volumetric losses of power and pressure in the divertor. Strong correlations have now also been found, and are reported here for the first time, between T e,t and all of the divertor target quantities of practical interest. A physical explanation for this surprising result has not been fully identified; nevertheless it has encouraging implications for reduced modeling of the ITER divertor. For such ITER conditions, (i) the global Ne injection rate, Inj Ne [Ne/s], and (ii) the electron temperature at the location on the target where the peak power deposition occurs, T e,t @q ⊥,pk (eV), are found to be promising reduced model control parameters. In the companion report, part B, a reduced model for the ITER divertor is developed and described in detail, based on reversed-direction 2 point modelling, Rev2PM. The input to the reduced model is a value of the variable pair (T et @q ⟂,pk ,Inj Ne ) and the output are values of the various target as well as divertor-entrance quantities of practical interest, e.g. q ⊥,pk , n e,Xpt (the electron density at the poloidal location of the X-point), etc. In part B the reduced model is quantitatively characterized using one half of the code cases; it is then used to successfully predict (replicate) the code values of e.g. n e,Xpt for the other half of the cases.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗