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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Seeding the explosion of a high-current-density conductor in a controlled manner through the addition of micron-scale surface defects

Inhomogeneities in a current-carrying conductor promote non-uniform heating and expansion through the complex feedback between current density, electrical resistivity, Ohmic heating, temperature, and hydrodynamics. Three-dimensional-magnetohydrodynamic (3D-MHD) simulations suggest that μm-scale resistive inclusions or voids seed local overheating and through hydrodynamic explosion generate continuously growing craters which become several times larger than the initial perturbation. The ejected mass is the genesis of an electrothermally driven plasma filament which develops at lower current than plasmas on uniform surfaces adjacent to the defect. This result suggests that 1D or even 2D treatments are largely inadequate for detailed prediction of plasma formation. To test computational predictions, z-pinch experiments driven to 1 MA studied ultra-high-purity aluminum rods which were then machined to include pairs of quasi-hemispherical voids or “engineered defects (ED)” on the current-carrying surface. ED are the dominant current-density perturbation and reproducibly drive local overheating which can be compared with 3D-MHD simulation. Data from high-resolution-gated imagers of visible surface emissions confirm many simulation predictions, including the surface topography of local overheating, and the propensity for neighboring ED to prematurely source plasmas which then connect to form a plasma filament. Results also provide conditional support of theory which suggests heating similarity; that is, heating is independent of ED size for geometrically scaled ED.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

A New Shape Optimization Approach for Lightweighting Electric Machines Inspired by Additive Manufacturing

Minimizing the mass in electric machines while maintaining superior performance is a new requirement for the advancement of drivetrains used in wind energy and electric mobility. Topology optimization (TO) for lightweighting electric machines using traditional approaches typically explores a restricted design space allowed by standard parametrizable geometry and manufacturing, while advanced methods, such as cell-based density approaches, suffer from a lack of robust manufacturability constraints during the optimization process. To overcome these drawbacks, we explore a grid-independent, boundary optimization where the outer shape of the magnet is parameterized using Bezier curves. We conduct a design of experiments (DOE) to study the effect of different magnet shapes on machine performance by varying the control points on the Bezier curves. A machine-learning-based surrogate model is constructed using the data from the DOE to quantify the relationship between the control points, air-gap torque, and mass. The control points are then optimized to maximize the torque density. The approach is used for minimizing electrical steel mass in the International Energy Agency (IEA) 15-MW radial flux direct-drive wind turbine generator. The new approach to shape optimization resulted in smooth and concise shapes that can be easily additively manufactured with up to a 20-ton reduction in electrical steel mass.

additive manufacturing↗
DOE OSTI2022

A New Shape Optimization Approach for Lightweighting Electric Machines Inspired by Additive Manufacturing: Preprint

Minimizing the mass in electric machines while maintaining superior performance is a new requirement for the advancement of drivetrains used in wind energy and electric mobility. Topology optimization (TO) for lightweighting electric machines using traditional approaches typically explores a restricted design space allowed by standard parametrizable geometry and manufacturing, while advanced methods, such as cell-based density approaches, suffer from a lack of robust manufacturability constraints during the optimization process. To overcome these drawbacks, we explore a grid-independent, boundary TO where the outer shape of the magnet is parameterized using Bezier curves. We conduct a design of experiments (DOE) to study the effect of different magnet shapes on machine performance by varying the control points on the Bezier curves. A machine-learning-based surrogate model is constructed using the data from the DOE to quantify the relationship between the control points, air-gap torque, and mass. The control points are then optimized to maximize the torque density. The approach is used for minimizing electrical steel mass in the International Energy Agency (IEA) 15-MW radial flux direct-drive wind turbine generator. The free-form boundary TO resulted in smooth and concise shapes that can be easily additively manufactured with up to a 20-ton reduction in electrical steel mass.

additive manufacturing↗
DOE OSTI2025

Online energy consumption forecast for battery electric buses using a learning-free algebraic method

Accurately predicting the energy consumption plays a vital role in battery electric buses (BEBs) route planning and deployment. Based on the algebraic derivative estimation, we present a novel method to forecast the energy consumption in real time. In contrast to the mainstream machine-learning-based methods, the proposed method does not require access to the historical energy consumption data. It eliminates the time-consuming and computationally expensive offline training. Consequently, its prediction performance is not constrained by the quantity and quality of the training data. Moreover, the method can swiftly adapt to new situations not included in the previous driving cycles, which makes it especially suitable for emerging transport modes, e.g., on-demand transit services. In addition, its online execution only involves algebraic calculations, yielding superior calculation efficiency. Using real-world data, we comprehensively compare the performance of the proposed learning-free algebraic method with multiple representative machine-learning-based methods. Finally, the advantages and limitations of the proposed method are discussed in detail.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Electric Motor Thermal Management

During FY 2022, NREL efforts focused on supporting collaborations with external research partners within the Electric Drive Technologies research consortium. The poster highlights collaborations with SNL, ORNL, and Georgia Tech. The collaboration with SNL utilized NREL's experimental capabilities to mechanically characterize SNL-provided material samples for motor applications. The collaboration with ORNL supported efforts to refine the design of a high-speed, non-heavy-rare-earth outer-rotor motor. The collaboration with Georgia Tech focused on a novel cooling technique for electric machines. NREL supported the effort by leading the thermal analysis and design of advanced machines.

ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

A Review of Axial Flux Permanent Magnet Machine Technology

Axial flux permanent magnet machines (AFPM) are popular for applications that benefit from high torque density and an axially compact form factor, such as in-wheel traction drives. Although the radial flux permanent magnet machine (RFPM) and the AFPM work based on the same underlying principle, the differences in their geometry introduce complexities in analysis of the AFPM. In this paper, the different AFPM design variants, their sizing approaches, computationally efficient design optimization techniques, and manufacturing techniques reported in literature are reviewed. In addition to classical AFPM machines, emerging variants and research opportunities with potential to push the boundaries of electric machine technology are reviewed. Furthermore, these include bearingless AFPMs, magnetically geared AFPMs, and combined radial-axial flux machines.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Cost Effective 6.5% Silicon Steel Laminate for Electric Machines

Iowa State University teamed with United Technologies Research Center and the University of Delaware and demonstrated a high switching frequency non-rare earth permanent magnet motor. A prototype motor with 400 Hz switching frequency, dummy MnBi permanent magnet with 8 MGOe energy density, and 6.5%Si steel as the laminate materials was designed, built, and tested. The performance of the prototype met the expectations showing a higher frequency motor enabled by 6.5%Si steel is a viable approach to meet DOE 2022 cost and performance targets for electric vehicle drive. Adoption of 6.5%Si steel will result in 3% improvement in energy conversion efficiency of the soft magnetic materials. In addition, the ability to use non-rare earth magnet for high power density application effectively mitigate the risk of EV traction motor from the rising rare earth price.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Domain-wall-mediated polarization switching in ferroelectric AlScN: Strain relief and field-dependent dynamics

While scandium-doped aluminum nitride (AlScN) exhibits robust ferroelectricity and excellent thermal stability, its utility is limited by an exceptionally high coercive field (𝐸 𝑐 ) for polarization switching. Unraveling the atomistic switching dynamics is therefore critical for tailoring 𝐸 𝑐 . Here, in this study, we combine density functional theory and machine-learning molecular dynamics to elucidate the polarization switching mechanisms in AlScN over various Sc concentrations and applied electric fields. We find that excessive lattice strain strictly prohibits collective polarization switching, but the preexisting domain walls relieve strain and lead to a distinct switching dynamics—dictating a field-dependent switching mechanism. At low electric fields, switching occurs via gradual domain-wall propagation consistent with the Kolmogorov-Avrami-Ishibashi model. In contrast, high fields stimulate additional nucleation, driving a rapid, homogeneous reversal process described by the simultaneous nonlinear nucleation and growth model. These findings highlight the critical role of domain-wall dynamics and suggest domain engineering as a viable strategy to tailor coercive fields in AlScN and related ferroelectrics.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Predicting U.S. federal fleet electric vehicle charging patterns using internal combustion engine vehicle fueling transaction statistics

Utilizing fueling transactions from internal combustion engine vehicles (ICEVs), the authors estimated how frequently midday public charging would be required for U.S. federal fleet battery electric vehicles (BEVs). Fueling transaction summary statistics are more widely available than trip-level telematics data, making this methodology more accessible and transferable to other researchers and fleet managers considering BEV replacements. For example, readers can easily apply a linear model using only the count of back-to-back fueling events at gas stations over 57 straight-line miles apart to predict days exceeding range. This linear regression predicted binned days exceeding 250 miles at 80% accuracy on a hold-out test set from the same fleet as the training data and 66 % accuracy on a new fleet displaying different driving behaviors. The authors additionally provide linear equations for days exceeding 200 and 300 miles as alternative range estimates to account for differences in BEV range and temperature impacts. Beyond the single-feature linear models which readers can apply, the authors tuned and trained other machine learning models on a variety of fueling transaction statistics including consecutive transaction distances, transaction distance from garage, estimated miles traveled from fuel economy and fuel quantity, and transaction periodicity. Utilizing a subset of 1678 light-duty federal fleet vehicles which contained daily vehicle miles traveled (VMT) in addition to fueling statistics, the authors determined which fueling transaction statistics were most relevant in predicting driving days exceeding 250 miles (an approximation of BEV rated driving range). In support of the U.S. federal fleet transition to zero-emission vehicles (ZEVs), the authors used these statistics and machine learning models to predict the frequency of BEV midday charging. After training models on the subset with VMT, the authors predicted days exceeding rated range for 112,902 light-duty vehicles operating in similar circumstances in the federal fleet using a Support Vector Regressor (SVR). In conclusion, they then used the projections as part of the ZEV Planning and Charging (ZPAC) tool to identify optimal candidates for BEVs for the federal fleet. An anonymized version of ZPAC is included in the supplementary materials.

25 ENERGY STORAGE↗
DOE OSTI2024

A Hybrid Heavy Duty Diesel Power System for Off-Road Applications—Concept Validation

A multiyear power system R&D program was completed with the objective of developing an off-road hybrid heavy duty diesel engine with front end accessory drive-integrated energy storage. This system was validated to deliver 10.5–25.6% reduction in fuel consumption over current Tier 4 Final-based 18L diesel engines, over various off-road machine application cycles. The power system consisted of a downsized heavy-duty diesel 13L engine containing advanced combustion technologies, capable of elevated peak cylinder pressures and thermal efficiencies, thermal barrier coatings, exhaust waste heat recovery via SuperTurbo™ turbocompounding, and hybrid energy assisting and recovery through both mechanical and electrical systems. Following the concept definition, design, and analysis phases of the program, the final phase focused on building and validating the performance and efficiency in laboratory tests. While aspects of the system such as start/stop and reduced off-road cooling package energy losses were only analytically evaluated, the main 13L concept engine with full hybrid system was successfully built and tested in steady-state and in transient certification and real-world application cycles. Extensive simulations in Caterpillar's DYNASTY™ software environment utilized the validation test data to assess performance more fully and confidently over varied cycles and strategies. An average fuel consumption reduction of 17.9% was realized, and the majority (~13%) of the benefit stemmed from the core concept 13L engine. In conclusion, a total cost of ownership analysis provides context to commercial viability and where adoption focus should be placed.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Manufacturing and Additive Design of Electric Machines by 3D Printing (MADE3D) (Final Technical Report)

As the U.S clean energy transition hinges on the growth of offshore wind, this is expected to be a major driver for innovations in manufacturing, material and design advancements to enable robust and cost-competitive wind turbines. The race to build larger and taller turbines rated 10 megawatts (MW) and beyond, has intensified pressure on OEMs in terms of logistics of handling and transporting large wind components, securing critical raw material as well as scaling up necessary domestic production infrastructure to meet the demand. There is increased interest in building lightweight, more efficient, and high-power dense drivetrains that will ease the burden on installation, minimize the raw material demand, increasing domestic sourceability. Despite good efficiency and reliability, existing drivetrain technologies such as direct-drive permanent magnet generators are heavy (> 300 tons), expensive, and often rely on large quantities of rare-earth permanent magnets (PMs), steel and copper.

17 WIND ENERGY↗
DOE OSTI2023

Energy Optimization of Light and Heavy-Duty Vehicle Cohorts of Mixed Connectivity, Automation and Propulsion System Capabilities via Meshed V2V-V2I and Expanded Data Sharing (Final Scientific and Technical Report)

Vehicle connectivity and automated driving technologies individually have the potential to decrease energy consumption and/or increase safety on light, medium or heavy duty vehicles to varying degrees depending on the traffic infrastructure and specific driving scenarios. Due to advances in sensing, perception and computing power, research and development emphasis in the mobility sector has shifted away from connectivity. Prior research has shown that driving automation with the absence of connectivity can in certain circumstances increase energy consumption. The effectiveness of synergizing connectivity and driving automation technologies is the focus of this work, specifically applied to vehicle cohorts of mixed composition, light and heavy duty, and powertrains ranging from all electric to conventional internal combustion engine. The project team is led by Michigan Technological University (MTU) and partnered with AVL Mobility Technologies Inc. (AVL), Borg Warner (BW), Traffic Technology Services (TTS), American Center for Mobility (ACM) and Navistar (NAV). The main thrusts for the team are to develop a micro-traffic simulation environment with specific VD&PT system attributes and CAV capabilities, 2) field a vehicle test fleet of mixed classification, propulsion and CAV capacity, 3) develop artificial intelligence (AI) and machine learning (ML) based multi-agent optimization methods for various traffic infrastructures, 4) integrate the virtual environment and the optimization methods then deploy the system as a CAV hardware in the loop (HiL) for the vehicle test fleet and 5) conduct closed track and public road testing to validate simulation and demonstrated energy and mobility improvements at multiple scales. For a cohort of mixed vehicles, the team will demonstrate a reduction of energy consumption of 10-50% at intersection, arterial roadway and limited access highway scenarios through connectivity and automation in simulation and at a closed test track. The energy reduction objectives of the project are summarized in Table 1, indicating the infrastructure and over what distances are relevant considered. Single scenario energy reductions are not relevant and thus, the research team took the approach to vary parameters associated with the infrastructure, vehicle cohort composition and dynamic behavior to generate energy consumption distributions for both unconnected and connected scenarios.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Pulsed-Power Innovations for Next-Generation, High-Current Drivers

There are proposals to build larger high-current drivers to be used for high-energy-density physics (HEDP), inertial confinement fusion (ICF), radiation effects testing, and basic science. Drivers significantly larger than the Z Machine at Sandia National Laboratories, Albuquerque, NM, USA, encounter increasing difficulties in water power flow, insulator performance, and vacuum power flow. The physics requirements of imploding loads limit a designer’s flexibility in choosing machine parameters, such as current rise time, driving impedance, and total inductance. This article enumerates these physics constraints and shows how they impact driver design. Here, we conclude that advances in pulsed-power capabilities are needed to control risk and to build a cost-effective driver at peak currents of ~60 MA.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

A Double-side Cooled SiC MOSFET Power Module with Sintered-silver Interposers: I. Design, Simulation, Fabrication, and Performance Characterization

Planar, double-side cooled power modules are emerging in electric-drive inverters because of their low profile, better heat extraction, and lower package parasitic inductances. However, there is still concern about their reliability due to the rigid interconnection between the device chips and two substrates of the power module. In this paper, a porous interposer made of low-temperature sintered silver is introduced to reduce the thermo-mechanical stresses in the module. A double-side cooled half-bridge module consisting of two 1200 V, 149 A SiC MOSFETs was designed, fabricated, and characterized. By using the sintered-Ag instead of solid copper interposers, our simulation results showed that at a total power loss of 200 W, the thermo-mechanical stress at the most vulnerable interfaces (interposer-attach layer) was reduced by 42 % and in the SiC MOSFET by 50 % with a trade-off of only 3.6 % increase in junction temperature. The sintered-Ag interposers were readily fabricated into desired dimensions without post-machining and did not require any surface finishing for die-bonding and substrate interconnection by silver sintering. Here, the porous interposers were also deformable under a low force or pressure, which helped to accommodate chip thickness and/or substrate-to-substrate gap variations in the planar module structure, thus simplifying module fabrication. Experimental results on the electrical performance of the fabricated SiC modules validated the success of using the porous silver interposers for fabricating planar, double-side cooled power modules.

42 ENGINEERING↗
DOE OSTI2025

Synchronous Machine Governor Upgrade

Conventional generation sources play a critical role in the stability and reliability of the electrical grid, particularly as we transition towards more renewable energy sources. To understand and accurately emulate their behavior for optimizing grid operations and ensuring seamless integration with renewable technologies, it is essential to better emulate the grid- and plant-level impacts of conventional generation sources, such as natural gas (NG) driven heat recovery steam generators (HRSGs) and combustion turbines (CTs). Therefore, a governor model is developed in a programmable logic controller (PLC) to investigate the performance of the conventional generator under various dynamic operating conditions and to identify the impact on grid stability in a controlled environment. The governor model aims to enable the hardware-in-the-loop (HIL) based emulation of these conventional generation sources using the existing 2 MVA synchronous machine/generator that is driven by a flexible 2.5 MW variable speed drive. This setup will allow us to replicate the dynamic characteristics and response behaviors of NG-driven HRSGs and CTs. The controls for the emulated conventional plants follow the industry standard and are adjustable, ensuring they accurately reflect the operational capabilities and limitations of real-world systems. These controls include load-following capabilities, ramp rates, startup and shutdown sequences, and emissions characteristics. By incorporating these adjustable controls, we aim to capture the nuanced impacts of conventional generation, such as their ability to provide ancillary services like frequency regulation, voltage support, and spinning reserve. In this report, we simulate two types of dynamic operations: grid-connected and islanding. For each dynamic operation, representative starting sequences are tested, including turbine purge, ignition, speed ramping up, generator excitation and synchronizing, and breaker close. The HIL based tests provides insights for field deployment, specifically the high-fidelity governor model provides results to predict the potential stability and reliability risk and suggest possible integration measures (e.g., generation and load balancing, tuning of governor control parameters). Ultimately, this enhanced emulation capability will be integrated into our Advanced Research on Integrated Energy Systems (ARIES), enabling us to conduct comprehensive studies on the interactions between conventional and renewable energy sources. By better understanding these interactions, we can develop strategies to optimize the overall performance and reliability of the grid. This will support the deployment of advanced grid management techniques, such as demand response, grid-forming inverters, and energy storage systems. The main contributions are summarized as follows: (1) This report introduces a PLC-based governor model for gas turbines. This model accurately simulates the dynamic behavior of conventional generation sources under various operational scenarios; (2) The model is integrated with an HIL testbed that includes a 2.5 MW variable speed drive and a 2 MVA synchronous machine. This setup enables realistic, real-time emulation of conventional power plants, particularly NG driven HRSGs and CTs; (3) The developed model is adaptable to various gas turbine configurations and allows for precise control over parameters such as MW ramp rates. This flexibility makes it a valuable tool for future research and industry collaboration; and (4) By incorporating the model into the National Renewable Energy Laboratory's Advanced Research on Integrated Energy Systems, the report lays the groundwork for future studies on interactions between conventional and renewable energy sources, enhancing the ability to develop advanced grid management strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Studying the Richtmyer–Meshkov instability in convergent geometry under high energy density conditions using the Decel platform

The “Decel” platform at Sandia National Laboratories investigates the Richtmyer–Meshkov instability (RMI) in converging geometry under high energy density conditions [Knapp et al., Phys. Plasmas 27, 092707 (2020)]. In Decel, the Z machine magnetically implodes a cylindrical beryllium liner filled with liquid deuterium, launching a converging shock toward an on-axis beryllium rod machined with sinusoidal perturbations. The passage of the shock deposits vorticity along the Be/D2 interface, causing the perturbations to grow. Here, we present platform improvements along with recent experimental results. To improve the stability of the imploding liner to the magneto Rayleigh–Taylor instability, we modified its acceleration history by shortening the Z electrical current pulse. Next, we introduce a “split rod” configuration that allows two axial modes to be fielded simultaneously in different axial locations along the rod, doubling our data per experiment. We then demonstrate that asymmetric slots in the return current structure modify the magnetic drive pressure on the surface of the liner, advancing the evolution on one side of the rod by multiple ns compared to its 180° counterpart. This effectively enables two snapshots of the instability at different stages of evolution per radiograph with small deviations of the cross-sectional profile of the rod from the circular. Using this platform, we acquired RMI data at 272 and 157 μm wavelengths during the single shock stage. Finally, we demonstrate the utility of these data for benchmarking simulations by comparing calculations using ALEGRA MHD and RageRunner.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Epitaxial oxide ionotronics: Interfaces and oxygen vacancies

Oxide ionotronics is an interdisciplinary field in which systems and devices rely on the migration of ions/ionic defects to alter or drive functionality. In this perspective, we focus on epitaxial oxide heterostructures and the contributing roles of oxygen vacancies and interfaces in ionotronics. We begin with a description of oxygen vacancy behavior, with a focus on vacancy ordering and the effects of interfaces and electric fields on particular epitaxial oxide systems. We then emphasize the use of synchrotron x-ray techniques for investigating system structure and dynamics in situ at interfaces and surfaces. Finally, an outlook on the future of epitaxial oxide ionotronics is provided, and several key areas for research are identified, such as freestanding heterostructures, combinatorial synthesis and machine learning, and next-generation synchrotron x-ray characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Design, Optimization, and Control of a 100 kW Electric Traction Motor Meeting or Exceeding DOE 2025 Targets

The overall objective of the electric motor portion of the Electric Drives Technology consortium is to research, develop, and test electric motors for use in electric vehicle applications capable of a peak power greater than 100 kW, power density greater than or equal to 50 kW/l, and a cost less than 3.3 $/kW. To meet the electric traction motor power density and cost targets a number of approaches were pursued simultaneously throughout the course of this project which address all of the major volumetric power density variables. The specific research thrusts at the Illinois Institute of Technology (IIT) are the following: multiphysics design for increased power density through maximum utilization of active materials, synthesis of electric machine windings and PM flux barriers with controlled space harmonics, high slot fill windings for increased current loadings or efficiency, aggressive cooling strategies, and design studies and prototype construction of candidate electric machines.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗