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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 343 records · Page 19

PR100: Estimated Medium- and Heavy-Duty Electric Vehicle Adoption and Load Estimation in Puerto Rico through 2050

The 2-year Puerto Rico Grid Resilience and Transition to 100% Renewable Energy Study analyzed stakeholder-driven pathways to Puerto Rico’s clean energy future. Outputs relating to electricity demand modeling were partially informed by estimates of electric vehicle adoption across all classes of medium- and heavy-duty vehicles (MHDVs), and the ensuing charging loads. To create these estimates, the team developed a transportation model for MHDVs in Puerto Rico to estimate the amount and geospatial distribution of energy used. Charging schedules for the different end uses of MHDVs were then used to construct electric load shapes assuming a portion of those vehicles would be replaced by battery electric counterparts. Study results showed that, by 2050, electric vehicles may constitute roughly 50% of the MHDV population in Puerto Rico. The resulting electrical demand curve attributable to MHDV charging showed that, for solar energy-based electrical systems with limited energy storage, this demand may create challenges unless appropriately managed either on the demand or supply side.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Improving the fast-charging capability of NbWO-based Li-ion batteries

The discovery of Nb-W-O materials years ago marks the milestone of charging a lithium-ion battery in minutes. Nevertheless, for many applications, charging lithium-ion battery within one minute is urgently demanded, the bottleneck of which largely lies in the lack of fundamental understanding of Li + storage mechanisms in these materials. Herein, by visualizing Li + intercalated into representative Nb 16 W 5 O 55 , we find that the fast-charging nature of such material originates from an interesting rate-dependent lattice relaxation process associated with the Jahn-Teller effect. Furthermore, in situ electron microscopy further reveals a directional, [010]-preferred Li + transport mechanism in Nb 16 W 5 O 55 crystals being the “bottleneck” toward fast charging that deprives the entry of any desolvated Li + through the prevailing non-(010) surfaces. Hence, we propose a machine learning-assisted interface engineering strategy to swiftly collect desolvated Li + and relocate them to (010) surfaces for their fast intercalation. As a result, a capacity of ≈ 116 mAh g −1 (68.5% of the theoretical capacity) at 80 C (45 s) is achieved when coupled with a Li negative electrode.

batteries↗

Vacancy Control in TiNb 2 O 7 : Implications for Energy Applications

Rapid global electrification, including for transportation, has dramatically increased demand for long-lasting and faster-charging batteries. Titanium niobium oxide (TiNb 2 O 7 ) is one of the most promising anode materials for high-power lithium-ion batteries (LIBs). However, the intrinsic low electronic conductivity of TiNb 2 O 7 is a significant drawback. Herein, an almost 10 orders of magnitude increase in conductivity is achieved via reduction of TiNb 2 O 7 in H 2 at 900 °C. The observed dramatic increase in electron conductivity upon reduction is unprecedented and opens new possibilities to produce niobium-based conductive materials for next-generation energy storage. Upon extended reduction, TiNb 2 O 7 converts into a distorted rutile TiNb 2 O 6 structure, which can be reoxidized back into the crystallographic shear phase. In addition, TiNb 2 O 7 can be thermally reduced in an inert atmosphere and reoxidized by CO 2 with excellent oxygen exchange capacity. Thus, the TiNb 2 O 7 Wadsley–Roth phase demonstrates outstanding potential for solar-driven thermochemical CO 2 splitting at 1400 °C. In conclusion, these findings manifest that controlling defect chemistry paves the way for developing advanced materials for LIBs and solar-driven thermochemical fuel production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

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↗

Online Prediction of Battery Discharge and Estimation of Parasitic Loads for an Electric Aircraft

Predicting whether or not vehicle batteries contain sufficient charge to support operations over the remainder of a given flight plan is critical for electric aircraft. This paper describes an approach for identifying upper and lower uncertainty bounds on predictions that aircraft batteries will continue to meet output power and voltage requirements over the remainder of a flight plan. Battery discharge prediction is considered here in terms of the following components; (i) online battery state of charge estimation; (ii) prediction of future battery power demand as a function of an aircraft flight plan; (iii) online estimation of additional parasitic battery loads; and finally, (iv) estimation of flight plan safety. Substantial uncertainty is considered to be an irremovable part of the battery discharge prediction problem. However, high-confidence estimates of flight plan safety or lack of safety are shown to be generated from even highly uncertain prognostic predictions.

Battery Discharge Prediction↗

Challenges and Opportunities of Integrating Electric Vehicles in Electricity Distribution Systems

Increased charging needs from widespread adoption of battery electric vehicles (EVs) will impact electricity demand. This will likely require a combination of potentially costly distribution infrastructure upgrades and synergistic grid-transportation solutions such as managed charging and strategic charger placement. Fully implementing such strategic planning and control methods - including business models and mechanisms to engage and compensate consumers - can minimize or even eliminate required grid upgrades. Moreover, there are also opportunities for EV charging to support the grid by helping solve existing and emerging distribution system challenges associated with increasing distributed energy resources (DERs) such as solar generation and battery energy storage. This paper reviews the potential impacts of EV charging on electricity distribution systems and describes methods from the literature to efficiently integrate EVs into distribution systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Power System Operational Impacts of Electric Vehicle Dynamic Wireless Charging

The electrification of the transportation sector poses an opportunity for reducing greenhouse gas (GHG) emissions from passenger vehicles. Electric vehicle (EV) charging through dynamic wireless power transfer (DWPT), known as roadway electrification, could shift EV demand profiles to better coincide with renewable electricity generation. However, this would be a very large new load and few studies evaluate the regional impacts of DWPT charging in a power transmission system. This paper defines methods that address dataset generation for passenger vehicle trips and models to evaluate regional impacts for this emerging technology. Household vehicle miles traveled (VMT) data form localized EV demand profiles through discrete-event simulation. This data serves as exogenous inputs for a Production Cost Model (PCM) of a synthetic transmission system based on the Electric Reliability Council of Texas's (ERCOT) network. EV charging methods are compared for both a 2018 baseline generation mixture and a high-renewable generation case incorporating 20 GW of installed solar photovoltaic (PV) capacity. The PCM employs unit commitment and economic dispatch (UC&ED) models to compare financial, environmental, and grid reliability impacts from EV charging across passenger EV adoption levels. In-transit charging could reduce grid operational costs by as much as 1.49%, with up to $13.7B saved in annual vehicle operational costs for consumers compared to gas-powered vehicles. Health impacts analysis from power plant and vehicle tailpipe emissions from this study show net health benefits increase by 40% for in-transit charging coupled with high renewable generation. Renewable resources provide an avenue for cost-effective in-transit charging with reduced emissions. The combination of dataset generation and open-source power system modeling establish a foundation for the holistic evaluation of regional DWPT impacts.

dynamic wireless power transfer↗

3D‐Mapping and Manipulation of Photocurrent in an Optoelectronic Diamond Device

Abstract Establishing connections between material impurities and charge transport properties in emerging electronic and quantum materials, such as wide‐bandgap semiconductors, demands new diagnostic methods tailored to these unique systems. Many such materials host optically‐active defect centers which offer a powerful in situ characterization system, but one that typically relies on the weak spin‐electric field coupling to measure electronic phenomena. In this work, charge‐state sensitive optical microscopy is combined with photoelectric detection of an array of nitrogen‐vacancy (NV) centers to directly image the flow of charge carriers inside a diamond optoelectronic device, in 3D and with temporal resolution. Optical control is used to change the charge state of background impurities inside the diamond on‐demand, resulting in drastically different current flow such as filamentary channels nucleating from specific, defective regions of the device. Conducting channels that control carrier flow, key steps toward optically reconfigurable, wide‐bandgap optoelectronics are then engineered using light. This work might be extended to probe other wide‐bandgap semiconductors (SiC, GaN) relevant to present and emerging electronic and quantum technologies.

Wood, Alexander A.↗

Hybrid Energy Management with Real-Time Control of a High-Power EV Charging Site

Decarbonization of transportation systems is driving higher capacity energy storage and faster charging power requirements in electric vehicles (EVs). Given the potential advantages - such as increased efficiency, reduced inverter capacity, and less total cable mass - there is a demand in the industry for more DC distribution for high-power charging (HPC) hubs. However, the cost-effective, adaptive, and robust operation of the DC-coupled HPC hub necessitates a robust site energy management system (SEMS). Validating SEMS operation using a digital twin of an HPC hub in a real-time simulator (RTS) platform is crucial before field deployment. In this study, we propose a hybrid energy management site controller designed to achieve high-level, long-term operational objectives while managing low-level power sharing control between hub assets. We develop a centralized model predictive controller (MPC) to optimize hub operating points and use these points to update the droop parameters of the site energy storage system (ESS). This approach ensures the hub follows an optimal operating point while maintaining the flexibility to respond to load surges. We tested and verified our proposed approach both offline and on a Controller Hardware-in-the-loop (C-HIL) simulation platform integrated with a SEMS framework, demonstrating real-time site operation and validating a cost-effective and robust site controller.

ADVANCED PROPULSION SYSTEMS↗

Learning electric vehicle driver range anxiety with an initial state of charge-oriented gradient boosting approach

This manuscript focuses on the modeling of electric vehicle (EV) driver’s range anxiety, a fear that a vehicle does not have sufficient range, or state of charge (SOC) of the battery pack, to reach its destination and would strand its occupants. Despite numerous research studies on the modeling of charging behaviors, modeling efforts to understand at what battery percentages do EV drivers charge their vehicles, and what are the associated contributing factors, are rather limited. To this end, an ensemble learning model based on gradient boosting is developed. The model sequentially fits new predictors to new residuals of the previous prediction and, then, minimizes the loss when adding the latest prediction. A total of 18 features are defined and extracted from the multisource data, which cover information on driver, vehicles, stations, traffic conditions, as well as spatial-temporal context information of the charging events. The analyzed dataset includes 4.5-year’s charging event log data from 3,096 users and 468 public charging stations in Kansas City Missouri, and the macroscopic travel demand model maintained by the metropolitan planning organization. Here, the result shows the proposed model achieved a satisfactory result with a R square value of 0.54 and root mean square error of 0.14, both better than multiple linear regression model and random forest model. To reduce range anxiety, it is suggested that the priorities of deploying new charging facilities should be given to the areas with higher daily traffic prediction, with more conservative EV users or that are further from residential areas.

33 ADVANCED PROPULSION SYSTEMS↗

Valuing EV Managed Charging for Bulk Power Systems

When and where electric vehicle (EV) charging occurs has significant implications for power systems supporting widespread EV adoption, especially with high shares of wind and solar generation. This study extends previous works by leveraging detailed simulation models for EV adoption, EV use, EV charging, and bulk power system operations, and by linking them with methods for describing charging flexibility at both the individual vehicle and aggregate levels. This technical potential study focuses on how the value of EV managed charging (EVMC) changes depending on charging flexibility type (within-charging session or within-week scheduling), dispatch mechanism (direct load control or one of several price-based mechanisms), and managed charging participation rate. We show that naively aggregating EV charging flexibility from individual vehicles into megawatt-scale resources grossly overestimates the flexibility of the fleet, because such aggregate models can unrealistically pair, e.g., one already-fully-charged vehicle's ability to increase load with another already-charging vehicle's ability to accept more charge, effectively requesting a charging rate that is infeasible for the latter vehicle. We find per-vehicle bulk system value is highest at low participation rates for all dispatch mechanisms. Factoring in production cost savings, avoided firm capacity savings, and combustion-related power sector emissions savings, we estimate the value of EVMC at low participation rates (5%) to be $33/vehicle-year to $69/vehicle-yr for within-session charging flexibility and $40/vehicle-yr to $120/vehicle-yr for within-week charging flexibility in an envisioned 2038 New England power system and monetary value reported in 2016 U.S. dollars. At 100% participation, per-vehicle value declines to $25/vehicle-yr to $31/vehicle-yr for within-session charging flexibility and to $29/vehicle-yr to $36/vehicle-yr for within-week charging flexibility; however, 100% participation yields the highest total system savings.

ADVANCED PROPULSION SYSTEMS↗

EV Hosting Capacity Analysis on Distribution Grids: Preprint

Increasing electric vehicle (EV) charging loads can increase the magnitude and duration of conventional peaks in demand profiles and even shift them significantly, causing operational violations in the distribution grid. It is important to develop tools to quantify the impacts of injecting large number of EV charging loads and determine the available capacity of the existing distribution feeder for the safe operation of the grid. Such tools would enable utilities to better prepare for grid operations in the near future while exploring the impact and effectiveness of strategies such as peak pricing and smart charging in managing these loads. This paper evaluates the hosting capacity of some real-world feeders to accommodate EV charging loads, including extreme fast-charging (xFC) options.

47 OTHER INSTRUMENTATION↗

Carbon decorated Li 3 V 2 (PO 4 ) 3 for high-rate lithium-ion batteries: Electrochemical performance and charge compensation mechanism

Fast charging and high-power delivering batteries are highly demanded in mobile electronics, electric vehicles and grid energy storage, but there are full of challenges. The star-material Li 3 V 2 (PO 4 ) 3 is demonstrated as a promising high-rate cathode material meeting the above requirements. Herein, we report the carbon decorated Li 3 V 2 (PO 4 ) 3 (LVP/C) cathode prepared via a facile method, which displays a remarkable high-rate capability and long-term cycling performance. Briefly, the prepared LVP/C delivers a high discharge capacity of 122 mAh g -1 (~93% of the theoretical capacity) at a high rate up to 20 C and a superior capacity retention of 87.1% after 1000 cycles. Importantly, by applying a combination of X-ray absorption spectroscopy and full-range mapping of resonant inelastic X-ray scattering, we clearly elucidate the structural and chemical evolutions of LVP upon various potentials and cycle numbers. Furthermore, we show unambiguous spectroscopic evidences that the evolution of the hybridization strength between V and O in LVP/C as a consequence of lithiation/delithiation is highly reversible both in the bulk and on the surface during the discharge-charge processes even over extended cycles, which should be responsible for the remarkable electrochemical performance of LVP/C. Our present study provides not only an effective synthesis strategy but also deeper insights into the surface and bulk electrochemical reaction mechanism of LVP, which should be beneficial for the further design of high-performance LVP electrode materials.

25 ENERGY STORAGE↗

Ultrafast charging of energy-dense lithium-ion batteries for urban air mobility

Urban air mobility (UAM) demands batteries with high energy density, long cycle life, and fast rechargeability. In this paper, we demonstrate an energy-dense lithium-ion battery (LiB) with ultralong cycle life under ultrafast charging. By using the asymmetric temperature modulation (ATM) method, i.e., charging at an elevated temperature and discharging around the ambient temperature, it is experimentally shown that the 209 Wh/kg LiB is charged to 88% state of charge (SOC) in ~5 min under UAM cycling while retaining 97.7% capacity after 1,000 cycles. Moreover, an experimentally validated electrochemical-thermal (ECT) model is developed to elucidate the fast charging process and the degradation mode of UAM batteries, quantitatively capturing lithium plating during fast charging. We find that the LiBs for UAM applications are most prone to lithium plating due to their higher initial SOC required as the reserve for safety; nevertheless, the ATM method is effective in minimizing or preventing lithium plating in the high SOC range of 30-90%. In addition to slowing down capacity fade, the ATM method also raises the usable capacity by 10%, which boosts the battery energy density and ensures the battery to perform full UAM cycles even at the end of life.

25 ENERGY STORAGE↗

Verification of Prognostic Algorithms to Predict Remaining Flying Time for Electric Unmanned Vehicles

This paper addresses the problem of building trust in the online prediction of a eUAV’s remaining available flying time powered by lithium-ion polymer batteries. A series of ground tests are described that make use of an electric unmanned aerial vehicle (eUAV) to verify the performance of remaining flying time predictions. The algorithm verification procedure described is implemented on a fully functional vehicle that is restrained to a platform for repeated run-to-functional-failure (charge depletion) experiments. The vehicle under test is commanded to follow a predefined propeller RPM profile in order to create battery demand profiles similar to those expected during flight. The eUAV is repeatedly operated until the charge stored in powertrain batteries falls below a specified limit threshold. The time at which the limit threshold on battery charge is crossed is then used to measure the accuracy of the remaining flying time prediction. In our earlier work battery aging was not included. In this work we take into account aging of the batteries where the parameters were updated to make predictions. Accuracy requirements are considered for an alarm that warns operators when remaining flying time is estimated to fall below the specified limit threshold.

Edward F. Hogge↗

Ultraefficient resistance switching between charge ordered phases in 1 T -TaS 2 with a single picosecond electrical pulse

Progress in high-performance computing demands significant advances in memory technology. Among novel memory technologies that promise efficient device operation on a sub-ns timescale, resistance switching between charge ordered phases of 1T-TaS 2 has shown to be potentially useful for development of high-speed, energy efficient nonvolatile memory devices. Measurement of the electrical operation of such devices in the picosecond regime is technically challenging and hitherto still largely unexplored. Here, we use an optoelectronic “laboratory-on-a-chip” experiment for measurement of ultrafast memory switching, enabling accurate measurement of electrical switching parameters with 100 fs temporal resolution. Photoexcitation and electro-optic sampling on a (Cd,Mn)Te substrate are used to generate and, subsequently, measure electrical pulse propagation with intra-band excitation and sub-gap probing, respectively. We demonstrate high contrast nonvolatile resistance switching from high to low resistance states of a 1T-TaS 2 device using single sub-2ps electrical pulses. Using detailed modeling, we find that the switching energy density per unit area is exceptionally small, E A =9.4 fJ/μm 2 . Finally, the speed and energy efficiency of an electronic “write” process place the 1T-TaS 2 devices into a category of their own among new generation nonvolatile memory devices.

42 ENGINEERING↗

Electrification Futures Study: Power Systems Operation with Newly Electrified and Flexible Loads

The Electrification Futures Study (EFS) is a multi-year study designed to analyze the impacts of widespread electrification in the U.S. energy system. In this webinar we present the detailed power systems operational analysis from the final report in the EFS series. For this analysis, we simulate multiple 2050 power systems for the conterminous United States to assess how variations in the magnitude and shape of electricity demand driven by electrification, and the extent of load participation to more-actively provide grid services, might impact the hourly operation, operational costs, and emissions of various power systems in 2050. The impacts of electrification and demand flexibility are overlayed across systems with significantly greater penetrations of variable renewable energy than today. Overall, we find that the high electrification scenarios envisioned in the EFS with significant VRE penetration (66% of annual national generation) can be operated to meet future increased levels of electrified demand. We also find that demand-side flexibility can enhance operational efficiency and reduce overall annual production costs by $5-$10 billion. The complementary relationship between flexible electric vehicle charging loads and solar generation is particularly pronounced, but in the absence of demand-side flexibility electrification can lead to increased wind and solar curtailment. By helping to reduce renewable curtailment, flexibility can also reduce power sector CO2 emissions. The analysis highlights the value of increased integration and coordination of demand- and supply-side resources in future electric system planning and operations—particularly under high electrification futures.

43 PARTICLE ACCELERATORS↗

EVs@Scale Next-Gen Profiles - Fleet Utilization 2024

As part of the U.S. Department of Energy’s EVs@Scale initiative, the Next-Gen Profiles (NGP) project provides a comprehensive, data-driven analysis of electric vehicle (EV) and electric vehicle supply equipment (EVSE) operations across real-world fleet deployments. This paper presents findings from the NGP’s Fleet Utilization study, which investigates operational behavior and asset usage across seventeen EV fleets and two EVSE fleets, encompassing a wide range of vehicle types and use cases. Data collected from diverse sources—varying in format and temporal resolution—are first reformatted into a unified structure. From this harmonized dataset, a suite of rigorously defined performance metrics is calculated at an hourly cadence, enabling consistent cross-comparison of charging, routing, and other key operational behaviors. Amid rapidly increasing EV adoption and growing demands for energy-efficient fleet operations, the analysis reveals clear utilization trends—including diurnal and weekly activity cycles, differences in short versus long charging session dependencies, and route-specific energy usage patterns. These findings highlight the need for tailored infrastructure strategies and the deployment of advanced energy management systems, such as Distributed Energy Resource Management Systems (DERMS) and Site Energy Management Systems (SEMS), which can optimize charging schedules and mitigate peak loads. By leveraging anonymized, harmonized datasets and standardized metrics, this study offers critical insights into fleet behavior and performance, providing a foundation to improve operational efficiency, reduce costs, and enable the scalable deployment of electrified transportation.

Wells, Landon↗