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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Voltage Injection-Based Current Harmonics Suppression Strategy for Six-Phase PMSM With Nonsinusoidal Back EMF

This article presents a voltage injection-based current harmonic minimization method for wide bandgap device-based six-phase permanent magnet synchronous machine (PMSM) drives. The presence of low-order harmonics is common in the back EMF of PMSMs with low slot and high pole numbers. The back EMF harmonics generate low-order harmonic currents that increase torque ripples. Furthermore, zero-sequence current (ZSC) is also observed if all six phases are connected to a common neutral point. ZSC does not affect the torque ripple but reduces the system efficiency. A special technique is required to reduce ZSC for variable speed drives as direct ac component to synchronous reference frame (SRF) dc transformation is not possible for ZSC. In this article, a voltage injection-based current harmonics reduction method is proposed. The injected harmonic voltage coefficients are calculated from the harmonic estimations of back EMF and updated using closed-loop harmonic compensators to improve steady-state performance. For ZSC reduction, third harmonics power controller, and for 6n ± 1 (n = 1, 2,...) order harmonic current reduction, SRF current controllers are presented in this article. Furthermore, the current harmonics minimization method is experimentally verified using a GaN-based three-level active neutral point clamped inverter-driven six-phase PMSM.

42 ENGINEERING↗
DOE OSTI2025

A Digital Three Level Space Vector Modulator for High Frequency Vector Sequence Generation

This letter proposes a digital high-speed three-level space vector pulse width modulator (3L-SVPWM). A conventional 3L-SVPWM is typically computation-based, involving a sequential execution of sub-tasks on a digital signal processor (DSP) based controller. The resulting high computation time of 5.4 μs limits the implementation of additional control blocks for switching frequencies greater than 100 kHz. This is overcome by transforming sub-tasks into digital blocks with 1-0 decisions and simpler arithmetic operations. The sub-task blocks are executed concurrently on a programmable logic device (PLD). Hence, a fast 3L-SVPWM execution in 140 ns is achieved. The proposed digital 3L-SVPWM enables high switching frequency operation of wide bandgap (WBG) device-based 3 L inverters to generate high fundamental frequency waveforms. A finite state machine is an integral part of the proposed implementation with the ability to generate any vector sequence, maximizing the usage of redundant vector states in 3L-SVPWM. Here, the proposed digital 3L-SVPWM operation is demonstrated with a GaN-based 3 L active neutral point clamped (3L-ANPC) inverter. Experimental results are presented at 250 kHz switching frequency to generate vector sequences for center-aligned SVPWM (CA-SVPWM) and common mode voltage reduced SVPWM (CMVR-SVPWM). The results also showcase a high fundamental frequency generation capability of 10 kHz.

active neutral point clamped inverter↗
DOE OSTI2020

High-Speed Nonpolar InGaN/GaN Superluminescent Diode With 2.5 GHz Modulation Bandwidth

We demonstrate a superluminescent diode fabricated on a nonpolar m-plane GaN substrate by employing a linearly tapered waveguide design. A high electrical -3dB modulation bandwidth ( f\n 3dB \n) of 2.5 GHz at a current density of 30 kA/cm\n 2 \n is achieved. The high modulation bandwidth is attributed to the shorter carrier recombination lifetime, the linear gain curve in the nonpolar m-plane quantum wells, and the ability to operate at high current densities while effectively suppressing lasing. We derive a general expression for the -3dB bandwidth as a function of current density for SLDs using a similar approach to that for laser diodes. The -3dB bandwidth of a nonpolar superluminescent diode increases exponentially with current density. The experimental results are consistent with the derived expression for f\n 3dB \n vs. current density.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Power Conversion Systems Enabled by SiC BiDFET Device

The BiDirectional Field-Effect Transistor (BiDFET) can enable circuit topologies requiring four quadrant switches, that were earlier designed using discrete combinations of MOSFETs, IGBTs, GaN HEMTs and PiN diodes. The monolithic nature of the BiDFET allows lower device count, smaller switch volume, lower inductance, and simpler packaging, and hence more reliable and commercially viable implementation in power electronics converters. Furthermore, the matrix converter topologies, now feasible using BiDFETs, can eliminate the bulky and unreliable dc link capacitors or inductors required for conventional voltage-source or current-source converters in ac-ac and ac dc applications. The 1.2 kV BiDFET has the potential to disrupt all the applications utilizing 1.2 kV switches, including electric vehicle (EV) drivetrain, bidirectional EV chargers, industrial motor drives, solid-state transformers, datacenter power supplies, elevator drives, dc microgrids, energy storage grid integration, solid-state breakers, etc.

42 ENGINEERING↗
DOE OSTI2021

A Bulk-Capacitance Reduction Method Using Self-Driven Thyristor for AC-DC Converters

Universal serial bus power delivery (USB-PD) fast chargers equipped with wide-bandgap devices are driven to higher power density and efficiency. Furthermore, the indispensable high-voltage bulk capacitors used to smooth the rectifier output could take 40% of the total system volume due to the large capacitance value required. This paper discussed a capacitor reduction method using a self-driven thyristor scheme comprised of only three components in total. No extra control circuit is needed. Circuit analysis and design equations are presented, and the design results are implemented in a 60-W GaN-based active-clamp flyback converter. The measurement results on the prototype show a 36.4% reduction of the bulk-capacitor size with similar efficiency compared to the conventional solution.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Postfault Operation of Three-Level Inverter Driven Six-Phase PMSM With Enhanced Torque–Speed Region

This article presents an open-switch postfault operational technique with enhanced torque–speed region for three-level (3L) active neutral point clamped (ANPC) inverter-driven symmetrical six-phase (SSP) permanent magnet synchronous machines (PMSMs). Maximum torque (MT), minimum loss (ML), and single three-phase (STP) operations are commonly used for the postfault operations of six-phase drives. The maximum possible torque and speed in these operations are generally limited by voltage, current ratings, and the neutral point configuration of the motor. To enhance the postfault torque and speed operating region, the torque and speed limits in different postfault operational techniques are determined based on the voltage, current constraints, and neutral point configuration of the SSP-PMSM. In this work, a unified postfault operation is proposed that increases the postfault operational limits by combining MT, ML, and STP operations and modifying the neutral point configuration of the SSP-PMSM. In addition, a technique is also presented that modifies the pulsewidth modulation technique to enable full torque operation below 0.5 p.u. speed. The proposed postfault operational technique enables full-speed (1 p.u.) operation by operating in STP mode and full torque operation (1 p.u.) below 0.5 p.u. speed. Furthermore, the postfault operational technique is experimentally validated using a Gallium Nitride (GaN) device-based3L-ANPC inverter-driven SSP-PMSM.

42 ENGINEERING↗
DOE OSTI2021

Detecting False Data Injection Attacks in Smart Grids: A Semi-Supervised Deep Learning Approach

The dependence on advanced information and communication technology increases the vulnerability in smart grids under cyber-attacks. Recent research on unobservable false data injection attacks (FDIAs) reveals the high risk of secure system operation, since these attacks can bypass current bad data detection mechanisms. To mitigate this risk, this paper proposes a data-driven learning-based algorithm for detecting unobservable FDIAs in distribution systems. We use autoencoders for efficient dimension reduction and feature extraction of measurement datasets. Further, we integrate the autoencoders into an advanced generative adversarial network (GAN) framework, which successfully detects anomalies under FDIAs by capturing the unconformity between abnormal and secure measurements. Also, considering that the datasets collected from practical power systems are partially labeled due to expensive labeling costs and missing labels, the proposed method only requires a few labeled measurement data in addition to unlabeled data for training. Numerical simulations in three-phase unbalanced IEEE 13-bus and 123-bus distribution systems validate the detection accuracy and efficiency of this method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A Six-Phase Space Vector PWM Technique for Wide Bandgap Device-Based Three-Level Inverters

This article presents a space vector pulsewidth modulation (SVPWM) technique for wide bandgap (WBG) device-based three-level (3L) six-phase inverters. Implementation of the SVPWM techniques for any six-phase inverter is complex for its high number of possible voltage vectors. Different six-phase load configurations are also possible depending on the angle between two consecutive phases and neutral point connections. The implementation techniques change depending on the load configuration. Moreover, a common neutral point for all six phases leads to circulating currents. Capacitor voltage balancing is also needed for 3L inverters. Capacitor voltage balancing and addressing the circulating current problem further increases the implementation complexity. In this article, a generalized SVPWM technique is proposed for the six-phase 3L inverters that is implementable using two three-phase 3L SVPWM blocks. The SVPWM technique also ensures dc bus capacitor voltage balancing and minimizes circulating current. Here, the SVPWM technique is experimentally verified using a GaN-based 3L six-phase active neutral point clamped (ANPC) inverter prototype, and the results are presented in this article.

42 ENGINEERING↗
DOE OSTI2023

Self-Resonant Coil Design for High-frequency High-Power Inductive Wireless Power Transfer

In this paper, the design methodology of a high-frequency, high-power, long-distance inductive wireless power transfer (WPT) is presented. The airgap (d) of a traditional high-power (>1 kW) WPT is limited to a few hundred millimeters, which is almost 1/4th of the coil diameter, D; d ≤ D/4. In this paper, the power transfer distance is significantly increased (d ≥ 1.5D) by adopting a high-frequency magnetic design and GaN-based power electronics. The material and design of the coil and shield are investigated using FEA and tested experimentally. A high frequency 6.78 MHz wireless charging system was built to transfer 1 kW power over 3 m airgap.

Mohammad, Mostak↗
DOE OSTI2023

Effect of varying threading dislocation densities on the optical properties of InGaN/GaN quantum wells with intentionally created V-shaped pits

The effect of varying threading dislocation densities on the internal quantum efficiencies (IQEs) of InGaN quantum wells (QWs), with and without intentionally created “V-pits,” is reported here. InGaN QW samples grown on GaN-on-sapphire templates with threading dislocation densities of <1 × 108 and <1 × 109 cm−2 are compared, with and without GaN/InGaN superlattice (SL) layers incorporated to intentionally open up the threading dislocation cores and form large-size “V-pits.” The formation of “V-pits” is confirmed by cross-sectional transmission electron microscopy to initiate from threading dislocations in the SL layers. The densities of the pits are confirmed by plan-view SEM to agree with the substrate threading dislocation densities. The experimental room temperature IQEs of the “V-pit” QW samples are enhanced to 15% ± 1% compared to 6% ± 2% for conventional QW samples. Both conventional and “V-pit” samples show insensitivity to the magnitude of the dislocation densities with respect to IQE performance, while the “V-pit” samples show shifts in the peak emission wavelengths compared to the conventional samples, attributed to strain modulation. This study provides additional understanding of the causes of the observed insensitivity of the IQEs to different threading dislocation densities.

Engineering↗
DOE OSTI2024

Self-aligned fabrication of vertical, fin-based structures

Modern power devices rely on complex, three-dimensional, vertical designs to increase their power density, ease their thermal management, and improve their reliability. However, fabrication techniques have historically relied on 2D processes for patterning lateral features. This work presents a new technology that uses multiple steps of angled depositions to fabricate self-aligned vertical, fin-based devices that avoid fundamental lithography resolution and alignment limitations. The fabrication flows of two devices, the self-aligned vertical finFET and the high-κ dielectric fin diode, are presented to demonstrate how angled depositions can readily achieve transistors with submicrometer, vertical gates in a source-first process and also create high-aspect ratio GaN fins with a record 70:1 aspect ratio.

Perozek, Joshua (ORCID:0000000251519131)↗
DOE OSTI2022

Glass Refraction Distortion Object Detection via Abstract Features

Glass reflection and refraction lead to missing and distorted object feature data, affecting the accuracy of object detection. In order to solve the above problems, this paper proposed a glass refraction distortion object detection via abstract features. The number of parameters of the algorithm is reduced by introducing skip connections and expansion modules with different expansion rates. The abstract feature information of the object is extracted by binary cross-entropy loss. Meanwhile, the abstract feature distance between the object domain and source domain is reduced by a loss function, which improves the accuracy of object detection under glass interference. To verify the effectiveness of the algorithm in this paper, the GRI dataset is produced and made public on GitHub. The algorithm of this paper is compared with the current state-of-the-art Deep Face, VGG Face, TBE-CNN, DA-GAN, PEN-3D, LMZMPM, and the average detection accuracy of our algorithm is 92.57% at the highest, and the number of parameters is only 5.13 M.

Cai, Lei↗
DOE OSTI2021

Diverse Super-Resolution (diversity_SR) [SWR-21-60]

Deep learning tools for enhancing the spatial resolution of wind data. The software is developed in Python using the TensorFlow deep learning package. Models for diversity super-resolution is provided. Included in the package are pretrained models with example code/data to perform the super-resolution as well as tools of training models for different enhancement- or data-types. The super-resolution is an inherently ill-conditioned problem, with multiple high-resolution fields plausibly mapping to the same coarse field. Considitional GANs provide a framework for generating a distribution of high-resolution realizations from a given low-resolution input. Stochastic estimation is used to inform the network of the expected degree and location of sub-grid diversity. The package includes a pretrained network to generate distributions of 10x-enhanced fields of wind data.

Glaws, Andrew↗
DOE OSTI2023

AdversarialTensors

This library builds a framework for defending ML models against adversarial attacks. The library will be developed at various stages leading to publication and software release at each stage. We employ tensor decomposition strategies as preprocessing stages for the first stage to provide robustness against the prominent adversarial noise. In the second stage, we develop a latent noise generator capable of generating novel adversarial noise that threatens the existing state-of-the-art defense strategy. In the third stage, we develop a UNSUP-GAN model, where the generator is trained to denoise against latent noise and most adversarial noises. This generator can provide a robust adversarial attack against any unseen attack.

Bhattarai, Manish↗
DOE OSTI2025

On the Effectiveness of Neural Operators at Zero-Shot Weather Downscaling [SWR-25-20]

Code repository for the experiments performed in the paper: On the Effectiveness of Neural Operators at Zero-Shot Weather Downscaling (https://doi.org/10.1017/eds.2025.11) Overall, our work investigates the zero-shot downscaling potential of neural operators. To summarize, our contributions are: 1. We provide a comparative analysis based on two challenging weather downscaling problems, between various neural operator and non-neural-operator methods with large upsampling factors (e.g., 8x and 15x) and fine grid resolutions (e.g., 2 km × 2 km wind speed). 2. We examine whether neural operator layers provide unique advantages when testing downscaling models on upsampling factors higher than those seen during training, i.e., zero-shot downscaling. Our results instead show the surprising success of an approach that combines a powerful transformer-based model with a parameter-free interpolation step at zero-shot weather downscaling. 3. We find that this Swin-Transformer-based approach mostly outperforms all neural operator models in terms of average error metrics, whereas an enhanced super-resolution generative adversarial network (ESRGAN)-based approach is better than most models in capturing the physics of the system, and suggests their use in future work as strong baselines. However, these approaches still do not capture variations at smaller spatial scales well, including the physical characteristics of turbulence in the HR data. This suggests a potential for improvement in transformer or GAN-based methods and neural-operator-based methods for zero-shot weather downscaling.

Sinha, Saumya [National Renewable Energy Laborator↗
DOE OSTI2021

Classification of Semiconductors Using Photoluminescence Spectroscopy and Machine Learning

Photoluminescence spectroscopy is a nondestructive optical method that is widely used to characterize semiconductors. In the photoluminescence process, a substance absorbs photons and emits light with longer wavelengths via electronic transitions. This paper discusses a method for identifying substances from their photoluminescence spectra using machine learning, a technique that is efficient in making classifications. Neural networks were constructed by taking simulated photoluminescence spectra as the input and the identity of the substance as the output. Here, six different semiconductors were chosen as categories: gallium oxide (Ga 2 O 3 ), zinc oxide (ZnO), gallium nitride (GaN), cadmium sulfide (CdS), tungsten disulfide (WS 2 ), and cesium lead bromide (CsPbBr 3 ). The developed algorithm has a high accuracy (>90%) for assigning a substance to one of these six categories from its photoluminescence spectrum and correctly identified a mixed Ga 2 O 3 /ZnO sample.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

High external quantum efficiency (6.5%) InGaN V-defect LEDs at 600 nm on patterned sapphire substrates

Highly efficient long-wavelength InGaN LEDs have been a research focus in nitride LEDs for their potential applications in displays and solid-state lighting. A key breakthrough has been the use of laterally injected quantum wells via naturally occurring V-defects which promote hole injection through semipolar sidewalls and help to overcome the barriers to carrier injection that plague long wavelength nitride LEDs. In this article, we study V-defect engineered LEDs on (0001) patterned sapphire substrates (PSS) and GaN on (111) Si. V-defects were formed using a 40-period InGaN/GaN superlattice and we report a packaged external quantum efficiency (EQE) of 6.5% for standard 0.1 mm 2 . LEDs on PSS at 600 nm. We attribute the high EQE in these LEDs to lateral injection via V-defects.

Ewing, Jacob J.↗