Results for “voltage prediction” — Page 14

NASA NTRS2010

SONOS Nonvolatile Memory Cell Programming Characteristics

Silicon-oxide-nitride-oxide-silicon (SONOS) nonvolatile memory is gaining favor over conventional EEPROM FLASH memory technology. This paper characterizes the SONOS write operation using a nonquasi-static MOSFET model. This includes floating gate charge and voltage characteristics as well as tunneling current, voltage threshold and drain current characterization. The characterization of the SONOS memory cell predicted by the model closely agrees with experimental data obtained from actual SONOS memory cells. The tunnel current, drain current, threshold voltage and read drain current all closely agreed with empirical data.

MacLeod, Todd C.↗

DOE OSTI2024

First-principles investigation of high capacity, rechargeable CF x cathode batteries based on graphdiyne and “holey” graphene carbon allotropes

Batteries composed of CF x cathodes have high theoretical specific capacities (>860 mA h g -1 ). Attempts at realizing such batteries coupled with Li anodes have failed to deliver on this promise, however, due to a discharge voltage plateau below the theoretical maximum lowering the realized energy density and difficulties with recharging the system. Here, in this study, we use first-principles calculations to investigate novel carbon allotropes for these battery systems: graphdiyne and “holey” graphene. We first identify stable flourination structures and calculate their band gaps. We demonstrate that the holes in these carbon allotropes can induce the formation of an amorphous LiF network within the carbon and that this formation may, in fact, be kinetically favored. For structures where amorphous LiF forms within the carbon, we predict it is easier to recharge and higher discharge voltages can be achieved. If the LiF forms outside the carbon product, however, it will be crystalline in form and lead to lower discharge voltages and more difficulty in recharging the systems. Finally, we simulate XPS spectra of representative cases, demonstrating an experimental pathway for determining the reaction pathway of these systems. Our work suggests CF x allotropes with holes in them as potential targets for high capacity, rechargeable cathodes for Li batteries, provided they lead to the formation of amorphous LiF within the C structure.

25 ENERGY STORAGE↗

DOE OSTI2021

Resilient Operation of Power Distribution Systems Using MPC-Based Critical Service Restoration

Power distribution systems are more prone to disruptions and cause most power system outages. We propose a service restoration technique to recover the system service (electricity delivery) following an extreme event-triggered substation outage. The proposed technique considers the problem of controlling distributed energy resources (DERs) of a distribution system with the objective of achieving maximum load pick up while satisfying network flow and voltage constraints. The problem is formulated as a model predictive control (MPC), where a linearized optimal power flow (OPF) model is employed to describe the network. The formulation is augmented with a ramping (up) reserve product for the DERs to ensure an upward monotonic load restoration as time evolves. We perform simulations considering the IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage devices. We demonstrate the efficacy of the devised technique in restoring the system loads monotonically, without shedding previously restored loads. We also show the benefit of co-optimization of power and reserve products for DERs on service restoration. In addition, the capability of the technique in regulating nodal voltages and reducing renewable power curtailment is demonstrated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Resilient Operation of Power Distribution Systems Using MPC-Based Critical Service Restoration: Preprint

Power distribution systems are more prone to disruptions and cause most power system outages. We propose a service restoration technique to recover the system service (electricity delivery) following an extreme event-triggered substation outage. The proposed technique considers the problem of controlling distributed energy resources (DERs) of a distribution system with the objective of achieving maximum load pick up while satisfying network flow and voltage constraints. The problem is formulated as a model predictive control (MPC), where a linearized optimal power flow (OPF) model is employed to describe the network. The formulation is augmented with a ramping (up) reserve product for the DERs to ensure an upward monotonic load restoration as time evolves. We perform simulations considering the IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage devices. We demonstrate the efficacy of the devised technique in restoring the system loads monotonically, without shedding previously restored loads. We also show the benefit of co-optimization of power and reserve products for DERs on service restoration. In addition, the capability of the technique in regulating nodal voltages and reducing renewable power curtailment is demonstrated.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2021

Resilient Operation of Power Distribution Systems Using MPC-Based Critical Service Restoration

Power distribution systems are more prone to disruptions and cause most power system outages. We propose a service restoration technique to recover the system service (electricity delivery) following an extreme event-triggered substation outage. The proposed technique considers the problem of controlling distributed energy resources (DERs) of a distribution system with the objective of achieving maximum load pick up while satisfying network flow and voltage constraints. The problem is formulated as a model predictive control (MPC), where a linearized optimal power flow (OPF) model is employed to describe the network. The formulation is augmented with a ramping (up) reserve product for the DERs to ensure an upward monotonic load restoration as time evolves. We perform simulations considering the IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage devices. We demonstrate the efficacy of the devised technique in restoring the system loads monotonically, without shedding previously restored loads. We also show the benefit of co-optimization of power and reserve products for DERs on service restoration. In addition, the capability of the technique in regulating nodal voltages and reducing renewable power curtailment is demonstrated.

61 RADIATION PROTECTION AND DOSIMETRY↗

NASA NTRS1999

Suppression of Random Dopant-Induced Threshold Voltage Fluctuations in Sub-0.1-(micron)meter MOSFET's with Epitaxial and (delta)-Doped Channels

A detailed three-dimensional (3-D) statistical 'atomistic' simulation study of fluctuation-resistant sub-0.1-(micron)meter MOSFET architectures with epitaxial channels and delta doping is presented. The need for enhancing the fluctuation resistance of the sub-0.1-(micron)meter generation transistors is highlighted by presenting summarized results from atomistic simulations of a wide range of conventional devices with uniformly doped channel. According to our atomistic results, the doping concentration dependence of the random dopant-induced threshold voltage fluctuations in conventional devices is stronger than the analytically predicted fourth-root dependence. As a result of this, the scaling of such devices will be restricted by the "intrinsic" random dopant-induced fluctuations earlier than anticipated. Our atomistic simulations confirm that the introduction of a thin epitaxial layer in the MOSFET's channel can efficiently suppress the random dopant-induced threshold voltage fluctuations in sub-0.1-(micron)meter devices. For the first time, we observe an "anomalous" reduction in the threshold voltage fluctuations with an increase in the doping concentration behind the epitaxial channel, which we attribute to screening effects. Also, for the first time we study the effect of a delta-doping, positioned behind the epitaxial layer, on the intrinsic threshold voltage fluctuations. Above a certain thickness of epitaxial layer, we observe a pronounced anomalous decrease in the threshold voltage fluctuation with the increase of the delta doping. This phenomenon, which is also associated with screening, enhances the importance of the delta doping in the design of properly scaled fluctuation-resistant sub-0.1-(micron)meter MOSFET's. Index Terms-Doping, fluctuations, MOSFET, semiconductor device simulation, silicon devices, threshold.

Asenov, Asen↗

NASA NTRS2014

Development and Implementation of a Hardware In-the-Loop Test Bed for Unmanned Aerial Vehicle Control Algorithms

Successful prediction and management of battery life using prognostic algorithms through ground and flight tests is important for performance evaluation of electrical systems. This paper details the design of test beds suitable for replicating loading profiles that would be encountered in deployed electrical systems. The test bed data will be used to develop and validate prognostic algorithms for predicting battery discharge time and battery failure time. Online battery prognostic algorithms will enable health management strategies. The platform used for algorithm demonstration is the EDGE 540T electric unmanned aerial vehicle (UAV). The fully designed test beds developed and detailed in this paper can be used to conduct battery life tests by controlling current and recording voltage and temperature to develop a model that makes a prediction of end-of-charge and end-of-life of the system based on rapid state of health (SOH) assessment.

Battery Testbed↗

DOE OSTI2020

High-Efficiency Model Predictive Control for Star-Connected Cascaded H-Bridge STATCOM Under Unbalanced Conditions

This paper presents a high-efficiency model predictive control (HMPC), which is enabled by a sorting approach based on dc capacitor voltages to significantly reduce the exponentially-increasing switching states in cascaded Hbridge (CHB) converters. In addition, a generic discrete-time prediction model for star-connected CHB static synchronous compensator is proposed to address the issues due to either grid and/or load unbalances. Both simulation and hardware-in-loop experimental results are presented to validate the feasibility and effectiveness of the proposed HMPC strategy.

Li, Yufei↗

DOE OSTI2022

Capacitance of Carbon Nanotube/Graphene Composite Electrodes with [BMIM + ][BF$_4^–$]/Acetonitrile: Fixed Voltage Molecular Dynamics Simulations

The capacitance of nanoporous carbon electrode materials is dictated by the physical interactions with electrolyte ions and molecules at the accessible interior electrode surface. While significant progress has been made in designing and synthesizing carbon materials with well-defined and relatively homogeneous nanoporosity, the majority of materials remain heterogeneous, and the resulting properties reflect an average over this distribution. In this regard, computer simulations can be a valuable tool to predict or validate structure/property relationships by systematically investigating well-defined, model electrode morphologies. In this work, we utilize fixed-voltage molecular dynamics simulations to predict structure/capacitance relationships for five different model morphologies of carbon nanotube/graphene (CNT/G) composite electrodes with 1-butyl-3-methylimidazolium tetrafluoroborate/acetonitrile electrolyte. The CNT/G electrode models are inspired by experimental “layer-by-layer” syntheses and strike a balance between realism and computational tractability. Comparison between different model electrode architectures elucidates important structure/property relationships. We find that CNT/graphene contact points serve as “hot spots” with significantly enhanced charge separation relative to the rest of the electrode. Furthermore, we demonstrate a specific nanoconfinement motif that provides substantial 3–4$\times$ enhancement of local capacitance, resulting in a ~40% increase of the total electrode differential capacitance. Because the accessible surface area of the model CNT/G electrodes is precisely determined, a comparison of per-area capacitance across systems is unambiguous. Our results thus complement a prior computational demonstration of capacitance enhancement in nanoconfinement while elucidating additional interaction motifs at CNT/G electrochemical interfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Fast Diagnosis of Failure Mechanisms and Lifetime Prediction of Li Metal Batteries

Explore the source record for details and available documents.

99 GENERAL AND MISCELLANEOUS↗

NASA NTRS2019

Predicting Composition of Photo Voltaic Cells Using Neural Networks

A better understanding of IV (current voltage) curve data collected from photo voltaic cells may lead to the construction of solar cells with improved electrical properties. With this in mind, IV curve data from different types of solar cells were acquired from the Photovoltaics and Electrochemical Systems Branch, NASA Glenn Research Center. Neural networks were created to predict the chemical composition of three classes of solar cells. The success of these predictions varied with class.

Norman, Thaddeus J.↗

NASA NTRS1995

Active Piezoelectric Structures for Tip Clearance Management Assessed

Managing blade tip clearance in turbomachinery stages is critical to developing advanced subsonic propulsion systems. Active casing structures with embedded piezoelectric actuators appear to be a promising solution. They can control static and dynamic tip clearance, compensate for uneven deflections, and accomplish electromechanical coupling at the material level. In addition, they have a compact design. To assess the feasibility of this concept and assist the development of these novel structures, the NASA Lewis Research Center developed in-house computational capabilities for composite structures with piezoelectric actuators and sensors, and subsequently used them to simulate candidate active casing structures. The simulations indicated the potential of active casings to modify the blade tip clearance enough to improve stage efficiency. They also provided valuable design information, such as preliminary actuator configurations (number and location) and the corresponding voltage patterns required to compensate for uneven casing deformations. An active ovalization of a casing with four discrete piezoceramic actuators attached on the outer surface is shown. The center figure shows the predicted radial displacements along the hoop direction that are induced when electrostatic voltage is applied at the piezoceramic actuators. This work, which has demonstrated the capabilities of in-house computational models to analyze and design active casing structures, is expected to contribute toward the development of advanced subsonic engines.

Source record↗

DOE OSTI2023

Modeling salt adsorption in electrical double layer for capacitive deionization

Abstract This work presents an electrical double layer (EDL) model for capacitive deionization (CDI) by intercorrelating the salt adsorption, the electrode voltage, and the surface charge density. The counterion condensation is considered a crucial contribution to salt adsorption because of the high surface charge density in the charged micropores. The counterions condense when the surface charge density exceeds a critical value, which is predicted by the counterion condensation theory. The EDL model accurately correlates the NaCl salt adsorption and electrode voltage with various surface charge densities and well predicts the salt adsorption in a wide range of external salt concentrations. The EDL model reproduces the non‐monotonic relationship between the salt adsorption and the specific surface area observed in experiments and provides an explanation from the modeling perspective. Exhibiting superior accuracy and predictability for salt adsorption, the EDL model could serve as an enabling tool contributing to the development of CDI processes.

Lin, Yu‐Jeng↗

DOE OSTI2024

Modeling the Low-Pressure High-Voltage Branch of the Paschen Curve for Hydrogen and Deuterium

A physical and numerical model of the Townsend discharge in molecular hydrogen and deuterium has been developed to meet the needs of designing a plasma-based switching device for power grid applications. Here, the model allows to predict the low-pressure branch of the Paschen curve for applied voltage in the range of several hundred kilovolts. In the regime of interest, electrons are in a runaway state and ionization by ions and fast neutrals sustains the discharge. It was essential to correctly account for both gas-phase and surface interactions (electron emission and electron backscattering), especially in terms of their dependence on particle energy. The model yields results consistent with prior data obtained for lower voltage. The three-species (electrons, ions, and fast neutrals) model successfully captures the essential physics of the process.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1980

The performance and efficiency of four motor/controller/battery systems for the simpler electric vehicles

A test and analysis program performed on four complete propulsion systems for an urban electric vehicle (EV) is described and results given. A dc series motor and a permanent magnet (PM) motor were tested, each powered by an EV battery pack and controlled by (1) a series/parallel voltage-switching (V-switch) system; and (2) a system using a pulse width modulation, 400 Hz transistorized chopper. Dynamometer tests were first performed, followed by eV performance predictions and data correlating road tests. During dynamometer tests using chopper control; current, voltage, and power were measured on both the battery and motor sides of the chopper, using three types of instrumentation. Conventional dc instruments provided adequate accuracy for eV power and energy measurements, when used on the battery side of the controller. When using the chopper controller, the addition of a small choke inductor improved system efficiency in the lower duty cycle range (some 8% increase at 50% duty cycle) with both types of motors. Overall system efficiency rankings during road tests were: (1) series motor with V-switch; (2) PM motor with V-switch; (3) series motor with chopper; and (4) PM motor with chopper. Chopper control of the eV was smoother and required less driver skill than V-switch control.

Shipps, P. R.↗

NASA NTRS1984

Radiation effects in silicon and gallium arsenide solar cells using isotropic and normally incident radiation

Several types of silicon and gallium arsenide solar cells were irradiated with protons with energies between 50 keV and 10 MeV at both normal and isotropic incidence. Damage coefficients for maximum power relative to 10 MeV were derived for these cells for both cases of omni-directional and normal incidence. The damage coefficients for the silicon cells were found to be somewhat lower than those quoted in the Solar Cell Radiation Handbook. These values were used to compute omni-directional damage coefficients suitable for solar cells protected by coverglasses of practical thickness, which in turn were used to compute solar cell degradation in two proton-dominated orbits. In spite of the difference in the low energy proton damage coefficients, the difference between the handbook prediction and the prediction using the newly derived values was negligible. Damage coefficients for GaAs solar cells for short circuit current, open circuit voltage, and maximum power were also computed relative to 10 MeV protons. They were used to predict cell degradation in the same two orbits and in a 5600 nmi orbit. Results show the performance of the GaAs solar cells in these orbits to be superior to that of the Si cells.

Anspaugh, B. E.↗

NASA NTRS1984

Radiation effects in silicon and gallium arsenide solar cells using isotropic and normally incident radiation

Several types of silicon and gallium arsenide solar cells were irradiated with protons with energies between 50 keV and 10 MeV at both normal and isotropic incidence. Damage coefficients for maximum power relative to 10 MeV were derived for these cells for both cases of omni-directional and normal incidence. The damage coefficients for the silicon cells were found to be somewhat lower than those quoted in the Solar Cell Radiation Handbook. These values were used to compute omni-directional damage coefficients suitable for solar cells protected by coverglasses of practical thickness, which in turn were used to compute solar cell degradation in two proton-dominated orbits. In spite of the difference in the low energy proton damage coefficients, the difference between the handbook prediction and the prediction using the newly derived values was negligible. Damage coefficients for GaAs solar cells for short circuit current, open circuit voltage, and maximum power were also computed relative to 10 MeV protons. They were used to predict cell degradation in the same two orbits and in a 5600 nmi orbit. Results show the performance of the GaAs solar cells in these orbits to be superior to that of the Si cells.

Anspaugh, B. E.↗

DOE OSTI2026

Using Explainable Artificial Intelligence to Predict Perovskite Solar Cell Electrical Metastability from Operando Photoluminescence Images in Accelerated Stress Testing

Metal halide perovskite (MHP) solar cells exhibit a metastable response to bias governed by coupled ionic–electronic processes, complicating the conventional reciprocity relation between luminescence intensity and device open-circuit voltage (V oc ). This limits the use of luminescence as a diagnostic for device screening or accelerated stress testing, motivating new approaches that can interpret photoluminescence (PL) signals under nonequilibrium conditions. From the artificial intelligence perspective, we develop an explainable deep learning framework that integrates convolutional neural networks (CNN), long short-term memory (LSTM) layers, and an attention mechanism to learn spatiotemporal features from operando photoluminescence PL image sequences. The model achieves a mean absolute error of ±0.027 V in predicting open-circuit voltage transients and reduces extreme-tail errors by up to 78% compared to physics-based reciprocity calculations. Gradient-weighted Class Activation Mapping (Grad-CAM) provides interpretability by highlighting physically meaningful regions such as electrode edges and emergent defect features. From the engineering application perspective, this framework enables accurate, contactless prediction of device V oc and identification of degradation-relevant features during accelerated aging of perovskite solar cells. This approach demonstrates how explainable AI can enhance operando diagnostics and reliability analysis in photovoltaic devices under nonequilibrium conditions.

14 SOLAR ENERGY↗