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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Structural Design Optimization of Doubly-Fed Induction Generators Using GeneratorSE

A wind turbine with a larger rotor swept area can generate more electricity, however, this increases costs disproportionately for manufacturing, transportation, and installation. This poster presents analytical models for optimizing doubly-fed induction generators (DFIGs), with the objective of reducing the costs and mass of wind turbine drivetrains. The structural design for the induction machine includes models for the casing, stator, rotor, and high-speed shaft developed within the DFIG module in the National Renewable Energy Laboratory's wind turbine sizing tool, GeneratorSE. The mechanical integrity of the machine is verified by examining stresses, structural deflections, and modal properties. The optimization results are then validated using finite element analysis (FEA). The results suggest that our analytical model correlates with the FEA in some areas, such as radial deflection, differing by less than 20 percent. But the analytical model requires further development for axial deflections, torsional deflections, and stress calculations.

17 WIND ENERGY↗
DOE OSTI2023

Wind Turbine Drivetrain Reliability Research - Gearbox Bearing Axial Cracking Failure Mode Example

The U.S. Department of Energy's National Renewable Energy Laboratory and Argonne National Laboratory have been conducting wind turbine drivetrain (formerly gearbox) reliability research for many years. Although the drivetrain focus has not changed, detailed projects are adjusted every few years based on dynamic needs seen in the field across the wind industry. This webinar will walk through the research methodology by using wind turbine gearbox bearing axial cracking failure mode as an example. The detailed steps include: 1) top failure mode identification based on actual failure data collected from project partners, 2) bench-top testing to identify possible contributing factors and formulate a damage metric, 3) physics domain modeling and validation through testing, 4) reliability assessment and prognosis based on the physics domain model and data domain inputs, and further enhancement through machine learning algorithms, using actual wind plant operational and failure event data. Hopefully, the presented work is of interest to the IISE community, and some members can apply their expertise to wind turbine and plant applications, helping enhance wind power generation technology advancement and its broader deployment.

axial cracking↗
DOE OSTI2019

Wind Energy Modeling and Simulation, Volume 2: Turbine and System

In order to optimise the yield of wind power from existing and future wind plants, the entire breadth of the system of a plant, from the wind field to the turbine components, needs to be modelled in the design process. The modelling and simulation approaches used in each subsystem as well as the system-wide solution methods to optimize across subsystem boundaries are described in this reference. Chapters are written by technical experts in each field, describing the current state of the art in modelling and simulation for wind plant design. This comprehensive, two-volume research reference will provide long-lasting insight into the methods that will need to be developed for the technology to advance into its next generation. Volume 2 covers turbine level aerodynamics, aeroelasticity, rotors drivetrains and electrical systems, wind turbine control, offshore foundations, system optimization, and grid modelling.

17 WIND ENERGY↗
DOE OSTI2026

High-Torque Heavy-Rare-Earth-Free Electric Motor Thermal Management

This project is part of a multi-lab Next-Generation Reliable Electric Drive Systems for Medium and Heavy-Duty Vehicles (NEXT-DRIVE) project led by Oak Ridge National Laboratory (ORNL), and including NREL, Sandia National Laboratories (SNL), and Ames Laboratory that leverages research expertise and facilities of these national labs to develop tools and approaches for reducing the design and development time of new electric drive technologies for medium and heavy-duty vehicles (MHDVs) and their associated costs while increasing reliability and asset utilization. The Next-Drive project aligns with the DOE's goals by introducing high-fidelity multi-physics and AI/ML-based modeling to design low-cost, highly reliable, and longer-lifetime drivetrains, aiming to achieve 25 years of progress in 5 years. The efforts of this project will focus on NEXT-DRIVE Task 4 (led by ORNL, NREL, and AMES) - developing high-fidelity modeling framework and identifying technologies enabling heavy-rare-earth-free electric motors for medium- and heavy-duty vehicles to achieve 1 million miles of operation. Contrary to conventional approaches that optimize the motor for power density, the focus will be to identify motor designs that achieve the best trade-off between motor power density and durable operation. NREL tasks include development of high-fidelity motor thermal models incorporating rotor windage losses and identification, evaluation and measurement of motor interface materials in key thermal pathways. The poster summarizes NREL's accomplishments for the first half of FY 2025 and outlines future plans.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Development of a dynamical model and energy analysis for wheel loader

The objective of this paper is to develop a fully integrated model for the wheel loader, including the subsystem dynamics of the engine, drivetrain, working circuit, steering circuit, and vehicle. It leads to a high-order strongly nonlinear system, and all state variables are coupled together to form a Multi-Input and Multi-Output (MIMO) system. A control architecture is proposed to decouple the MIMO system into several Single-Input and Single-Output (SISO) systems. Here, a tracking problem has been formulated to validate this fully integrated model with the field test data. The accuracy of the model is verified by the 2.3% difference between the measured and simulated fuel consumption. Meanwhile, an energy distribution analysis is conducted to reveal the energy consumption and energy loss of each portion of the wheel loader. Such a model can be used to plan the working pattern, guide the driving habits of human operators, or refine the underlying architecture, leading to the ultimate goal of reducing total fuel consumption and improving productivity.

42 ENGINEERING↗
DOE OSTI2019

Rolling Element Bearing Dynamics in Wind Turbines

There are unique reliability challenges related to wind turbine drivetrains. Predominant failure modes are not accounted for in design standards, not attributable to material deficiencies or quality control, and are complex and independent of the component supplier. The team conducted testing and analysis to enable improvement of inherent reliability, an increase of availability with less effort and drama, and a reduction in wind plant operation and maintenance costs. The analytic model was validated through uptower experiments, and the bearing speed was directly affected by drivetrain load and speed. Bearing sliding is widely present during regular turbine operations and significant sliding occurs during transient events, which can lead to bearing failures and shortened life.

17 WIND ENERGY↗
DOE OSTI2019

Investigation of Roller Sliding in Wind Turbine Gearbox High-Speed-Shaft Bearings

In a collaborative project, Flender Corporation, SKF, and the National Renewable Energy Laboratory (NREL) have instrumented a commercial drivetrain, installed it in a wind turbine at the National Wind Technology Center, and operated the turbine for more than a year. The gearbox was specifically instrumented to measure high-speed bearing loads, sliding, and the lubricant environment. Commercial SKF black-oxide coated cylindrical-roller bearings were modified by magnetizing one roller and inserting a metal pin in the cage next to it to measure roller and cage speed, respectively, with an inductive coil and a proximity switch. In this report, these measurements are used to validate two different modeling approaches for bearing sliding - one analytical dynamic model and one multibody model. Once validated, these models can be used to evaluate the roller slip losses or cumulative frictional energy that are considered potential driving factors for wind turbine gearbox high-speed-shaft and high intermediate speed shaft bearing failures by white etching cracks.

17 WIND ENERGY↗
NASA NTRS1989

NASA rotorcraft technology for the 21st century

Current and planned rotorcraft technology-related research at NASA's Ames, Lewis, and Langley research centers is discussed with a view to the fruits of these efforts beyond the year 2000. Examples of promising technologies are higher-harmonic and dynamic rotor controls, advanced structural composites, aerodynamics and acoustics simulation models for design predictions, automated flight controls, and high-reliability rotor drivetrains. The overall payoff from an integration of these technologies will allow safe automated flying in all weather conditions, as well as precision-hover and exceptionally low noise and vibration levels.

Albers, James A.↗
DOE OSTI2022

Impacts of wind field characteristics and non-steady deterministic wind events on time-varying main-bearing loads

Abstract. This work considers the characteristics and drivers of the loads experienced by wind turbine main bearings. Simplified load response models of two different hub and main-bearing configurations are presented, representative of both inverting direct-drive and four-point-mounted geared drivetrains. The influences of deterministic wind field characteristics, such as wind speed, shear, yaw offset, and veer, on the bearing load patterns are then investigated for similarity scaled 5, 7.5, and 10 MW reference wind turbine models. Main-bearing load response in cases of deterministic gusts and extreme changes in wind direction are also considered for the 5 MW model. Perhaps surprisingly, veer is identified as an important driver of main-bearing load fluctuations. Upscaling results indicate that similar behaviour holds as turbines become larger, but with mean loads and load fluctuation levels increasing at least cubically with the turbine rotor radius. Strong links between turbine control and main-bearing load response are also observed.

17 WIND ENERGY↗
DOE OSTI2024

Wind Turbine Design Optimization for Hydrogen Production

To help meet the need for inexpensive green fuels, we are working on wind turbine design optimization specifically for hydrogen production. We have thus far achieved a 1.53% decrease in LCOH as compared to a turbine optimized for LCOE using the same code, design variables, and models. We accomplished this by optimizing some components of the wind turbine tower, rotor, and drivetrain design with hydrogen production and costs in the design loop.

hydrogen↗
DOE OSTI2023

Wind Turbine Design Optimization for Hydrogen Production

To help meet the need for inexpensive green fuels, we are working on wind turbine design optimization specifically for hydrogen production. We have thus far achieved a 1.53% decrease in LCOH as compared to a turbine optimized for LCOE using the same code, design variables, and models . We accomplished this by optimizing some components of the wind turbine tower, rotor, and drivetrain design with hydrogen production and costs in the design loop.

design↗
DOE OSTI2023

Virtual sensing of wind turbine hub loads and drivetrain fatigue damage, Virtuelle Sensoren für die Messung von Hauptwellenlasten und Ermüdungsschäden im Antriebstrang von Windenergieanlagen

Abstract: This paper presents a Digital Twin for virtual sensing of wind turbine aerodynamic hub loads, as well as monitoring the accumulated fatigue damage and remaining useful life in drivetrain bearings based on measurements of the Supervisory Control and Data Acquisition (SCADA) and the drivetrain condition monitoring system (CMS). The aerodynamic load estimation is realized with data-driven regression models, while the estimation of local bearing loads and damage is conducted with physics-based, analytical models. Field measurements of the DOE 1.5 research turbine are used for model training and validation. The results show low errors of 6.4% and 1.1% in the predicted damage at the main and the generator side high-speed bearing respectively. Zusammenfassung: In diesem Aufsatz wird ein digitaler Zwilling für Windenergieanlagen vorgestellt, welcher die virtuelle Erfassung der Hauptwellenlasten und die Zustandsüberwachung von Ermüdungschäden und der verbleibende Nutzungsdauer der Antriebsstranglager ermöglicht. Der digital Zwilling nutzt Messdaten des Supervisory Control and Data Acquisition (SCADA) Systems und des Zustandsüberwachungssystems des Antriebsstranges (CMS). Die Berechnung der Hauptwellenlasten ist mit datenbasierten Regressionsmodellen umgesetzt, während die Berechnung der Lagerkräfte und der Ermüdungsschaden mit physikbasierten Modelle durchgeführt wird. Für die Modellentwicklung und -validierung werden Feldmessdaten der DOE 1.5MW Turbine eingesetzt. Die Abweichungen in den Ermüdungsschäden am Hauptwellenlager und am Generatorwellenlager betragen lediglich 6,4% beziehungsweise 1,1%.

17 WIND ENERGY↗
DOE OSTI2019

Roller Sliding in Wind Turbine Gearbox High-Speed-Shaft Bearings

Failures in gearbox bearings have been a primary source of reliability issues for wind turbine drivetrains, leading to costly downtime and unplanned maintenance. The most common failure mode is attributed to so-called white-etching cracks (WECs). This mode of failure can occur at 5%-20% of the predicted design life and has been observed in many other industries, bearing locations, bearing types, bearing parts, and steel types. The main drivers for the creation of WECs in steel specimens have been identified and verified by material testing. In a full-scale wind turbine gearbox, however, the conditions leading to WECs, the process by which this failure culminates, and the reasons for their apparent prevalence are all still highly debated. In a collaborative project, Flender Corporation, SKF and the National Renewable Energy Laboratory have instrumented a commercial drivetrain, installed it in a wind turbine, and operated the turbine for over a year. In this report, these measurements are used to validate two different modelling approaches for bearing sliding, one analytical dynamic model and one multi-body model. Once validated, these models can then be used to evaluate the roller slip losses or cumulative frictional energy that are each considered as potential driving factors for wind turbine gearbox bearing failures by WEC.

17 WIND ENERGY↗
DOE OSTI2026

Individual Motorist Data - Ohio EV Ownership Trends

The individual motorist dataset contains data and analysis of consumer electric vehicle (EV) ownership trends in rural Appalachian Ohio in comparison with statewide trends. The data span four years, from Q1 2020 to Q2 2023 (partial). They are sourced from the Ohio Bureau of Motor Vehicles registration records and contain detail on drivetrain type (battery-electric vehicle [BEV] or plug-in hybrid electric vehicle [PHEV]); specific vehicle make and model; and registration location at county, city, and ZIP code levels of spatial resolution. Registration data are analyzed at the county level against such indicators as median income, poverty status, urban-rural status, and density of public charging infrastructure. In addition to tabular data, a GIS shapefile with many analysis fields joined is included.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Main bearing response in a waked 15-MW floating wind turbine in below-rated conditions

Increased wind turbine size raises unknowns related to structural flexibility. Moreover, moving to deeper waters, component reliability becomes more critical. This work investigates main bearing response dependence on drivetrain flexibility and wake impingement in a two-turbine wind farm. A 15-MW floating direct-drive turbine is considered. Large eddy simulations (LES) are employed to model neutral, stable and unstable atmospheric conditions at below-rated mean wind speed, while the engineering codes OpenFAST and FAST.Farm simulate turbine and wake behavior. Results indicate significant sensitivities in fatigue estimates to lateral distance between the upstream and downstream turbine. The trends are most substantial in stable conditions, where the waked downwind main bearing sees twice the fatigue damage estimates of the upstream turbine for one position and 50% for another. Main bearing fatigue sensitivity to drivetrain flexibility is minor, while properly including generator rotor inertia loads is important for the axial forces of the locating (axially fixed) bearing, especially in stable conditions.

17 WIND ENERGY↗
DOE OSTI2019

Drivetrain Reliability from Inherent to Operational

Despite reliability improvements made to wind turbine drivetrains over the years, premature component failures are still challenging the wind industry. There are, however, opportunities to understand drivetrain reliability challenges and investigate potential mitigation solutions. This presentation discusses a few research and development (R&D) activities on drivetrain reliability carried out by the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) over the last ten years. It covers two angles of reliability, inherent and operational, and goes into detail on specific R&D activities. Some inherent reliability challenges covered include gearbox planetary stage loads investigation, high speed shaft and main bearing operational condition understanding, dynamic modeling approaches, and recommended practices. The R&D activities on operational reliability improvements covered include benchmarking, performance and condition monitoring, and predictions on the remaining useful life of components. The presentation concludes with a list of necessary drivetrain reliability improvements that could close the loop between operational and inherent reliability efforts. The team hopes that some of these lessons learned can contribute to relevant international standards or recommended practices.

17 WIND ENERGY↗
DOE OSTI2018

NREL and Clemson University Drivetrain Test Facility Collaboration: Cooperative Research and Development Final Report, CRADA Number CRD-13-509

The National Renewable Energy Laboratory (NREL) and Clemson University have a mutual interest in collaborating in the development of wind turbine drivetrain testing facilities and grid simulators. NREL and Clemson University will work together to share resources and experiences in the development of future wind energy test facilities and capabilities. The CRADA includes sharing of facility topologies and capabilities, modeling efforts, commissioning plans, test protocols, infrastructure cost data, test plans, pro forma contracting instruments, and safe operating strategies. Further, NREL and Clemson University will exchange staff for training and development purposes, including collaborative participation in commissioning and customer testing. DOE has provided NREL with over 10 years of support in developing custom facilities and capabilities to enable testing of full-scale integrated wind turbine drivetrain systems in accordance with the needs of the US wind industry. NREL currently operates a 2.5MW dynamometer and is in the processes of building a 5MW dynamometer and a grid simulator (referred to as a 'Controllable Grid Interface' or CGI). Clemson University is currently building a drivetrain testing facility with two dynamometers, 7.5 MW and 15 MW, and 15 MW Hardware in the loop grid simulator.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Offshore Wind ENergy Simulation Toolkit (OWENS)

SAND2021-2751 O The Offshore Wind ENergy Simulation Toolkit (OWENS) is a collection of aerodynamic, structural, hydrodynamic, drivetrain, controls, composite structure and mesh preprocessing, and data postprocessing. OWENS is primarily an ontology, or glue code, pulling together many open-source and Sandia-developed libraries to model the aero-servo-hydro-elastic physics of wind and marine energy turbines. The toolkit’s intended use is for arbitrary aeroelastic rotor configurations analysis including vertical-axis wind turbines, horizontal-axis wind turbines, and analogous marine energy applications for fixed-bottom and floating configurations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525

Owens, Brian↗