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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 19 records

Charge Storage, Conductivity and Charge Profiles of Insulators as Related to Spacecraft Charging

Dissipation of charges built up near the surface of insulators due to space environment interaction is central to understanding spacecraft charging. Conductivity of insulating materials is key to determine how accumulated charge will distribute across the spacecraft and how rapidly charge imbalance will dissipate. To understand these processes requires knowledge of how charge is deposited within the insulator, the mechanisms for charge trapping and charge transport within the insulator, and how the profile of trapped charge affects the transport and emission of charges from insulators. One must consider generation of mobile electrons and holes, their trapping, thermal de-trapping, mobility and recombination. Conductivity is more appropriately measured for spacecraft charging applications as the "decay" of charge deposited on the surface of an insulator, rather than by flow of current across two electrodes around the sample. We have found that conductivity determined from charge storage decay methods is 102 to 104 smaller than values obtained from classical ASTM and IEC methods for a variety of thin film insulating samples. For typical spacecraft charging conditions, classical conductivity predicts decay times on the order of minutes to hours (less than typical orbit periods); however, the higher charge storage conductivities predict decay times on the order of weeks to months leading to accumulation of charge with subsequent orbits. We found experimental evidence that penetration profiles of radiation and light are exceedingly important, and that internal electric fields due to charge profiles and high-field conduction by trapped electrons must be considered for space applications. We have also studied whether the decay constants depend on incident voltage and flux or on internal charge distributions and electric fields; light-activated discharge of surface charge to distinguish among differing charge trapping centers; and radiation-induced conductivity. Our experiments also show that "Malter" electron emission occurs for hours after turning off the electron beam. This Malter emission similar to emission due to negative electron affinity in semiconductors is a result of the prior radiation or optical excitations of valence electrons and their slow drift among traps towards the surface where they are subsequently emitted. This work is supported through funding from the NASA Space Environments and Effects Program.

Dennison, J. R.

Alternate charging profiles for the onboard nickel cadmium batteries of the Explorer Platform/Extreme Ultraviolet Explorer

The Explorer Platform/Extreme Ultraviolet Explorer (EP/EUVE) spacecraft power is provided by the Modular Power Subsystems (MPS) which contains three 50 ampere-hour Nickel Cadmium (NiCd) batteries. The batteries were fabricated by McDonnell Douglas Electronics Systems Company, with the cells fabricated by Gates Aerospace Batteries (GAB), Gainesville, Florida. Shortly following launch, the battery performance characteristics showed similar signatures as the anomalous performance observed on both the Upper Atmosphere Research Satellite (UARS) and the Compton Gamma Ray Observatory (CGRO). This prompted the development and implementation of alternate charging profiles to optimize the spacecraft battery performance. The Flight Operations Team (FOT), under the direction of Goddard Space Flight Center's (GSFC) EP/EUVE Project and Space Power Applications Branch have monitored and managed battery performance through control of the battery Charge to Discharge (C/D) ratio and implementation of a Solar Array (SA) offset. This paper provides a brief overview of the EP/EUVE mission, the MPS, the FOT's battery management for achieving the alternate charging profile, and the observed spacecraft battery performance.

Rao, Gopalakrishna M.

Non-Invasive Electrode Impedance Estimation for Optimized Charge Profile Parameterization of Lithium-Ion Batteries

This work presents a non-invasive method for parameterizing a physically motivated equivalent circuit model of lithium-ion batteries using operando electrochemical impedance spectroscopy and time-domain data. The proposed model consists exclusively of linear circuit elements, enabling computationally efficient simulation and real-time implementation on battery management system chips. By integrating frequency- and time-domain measurements, the model accurately estimates internal states such as the negative electrode potential, achieving a root mean square error of 12.3 mV during fast charging validation. Parameterization requires only rate tests with sinusoidal perturbations at three different ambient temperatures, making the approach experimentally accessible. The model reveals key insights into battery behavior, including rate-dependent overpotentials primarily governed by charge transfer kinetics at the positive electrode, and temperature-dependent impedance contributions from both charge transfer and solid-state diffusion processes. Validation using reference electrodes confirms the model’s ability to detect lithium plating onset and reproduce impedance behavior across a wide range of operating conditions. The approach enables in situ optimization of fast charging profiles and lays the foundation for future extensions incorporating aging effects and plating dynamics.

25 ENERGY STORAGE

Optimal Charging of Nickel-Hydrogen Batteries for Life Extension

We are exploring the possibility of extending the cycle life of battery systems by using a charging profile that minimizes cell damage. Only nickel-hydrogen cells are discussed at this time, but applications to lithium-ion cells are being considered. The process first requires the development of a fractional calculus based nonlinear dynamic model of the specific cells being used. The parameters of this model are determined from the cell transient responses. To extend cell cycle life, an instantaneous damage rate model is developed. The model is based on cycle life data and is highly dependent on cell voltage. Once both the cell dynamic model and the instantaneous damage rate model have been determined, the charging profile for a specific cell is determined by numerical optimization. Results concerning the percentage life extension for different charging strategies are presented. The overall procedure is readily adaptable to real-time implementations where the charging profile can maintain its minimum damage nature as the specific cell ages.

Hartley, Tom T.

High spatial resolution charge sensing of quantum Hall states

Charge distribution offers a unique fingerprint of important properties of electronic systems, including dielectric response, charge ordering, and charge fractionalization. Here, we develop an architecture for charge sensing in two-dimensional electronic systems in a strong magnetic field. We probe local change of the chemical potential in a proximitized detector layer using scanning tunneling microscopy, allowing us to infer the chemical potential and the charge profile in the sample. Our technique has both high energy (<0.3 meV) and spatial (<10 nm) resolution exceeding that of previous studies by an order of magnitude. We apply our technique to study the chemical potential of quantum Hall liquids in monolayer graphene under high magnetic fields and their responses to charge impurities. The chemical potential measurement provides a local probe of the thermodynamic gap of quantum Hall ferromagnets and fractional quantum Hall states. The screening charge profile reveals spatially oscillatory response of the quantum Hall liquids to charge impurities and is consistent with the composite Fermi liquid picture close to the half-filling. Our technique also paves the way to map moiré potentials, probe Wigner crystals, and investigate fractional charges in quantum Hall and Chern insulators.

charge sensing

EVs@Scale Next-Gen Profiles - EV Profile Capture 2024

As part of the U.S. DOE EVs@Scale consortium Next-Gen Profiles (NGP) project, the profile capture and analysis of production electric vehicles undergoing high power charging (HPC) is conducted over a wide range of conditions to explore variance and performance. Charge session parameters are collected from both the electric vehicle (EV) and electric vehicle supply equipment (EVSE) at a rate of 10Hz and entered into a time-series database for analysis. These charge profiles are captured under nominal and off-nominal conditions, exploring the impact of battery state of charge (SOC), battery temperature, vehicle condition, smart charge management (SCM), and EVSE limitations. Nominal conditions are defined to be ideal conditions that should transfer the maximum allowable energy in the minimum possible amount of time. Nominal condition profiles are compared across EVs to characterize state-of-the-art EV charging performance against one another. Off-nominal condition profiles are compared against its nominal condition profile counterpart to highlight the variance across less desirable starting conditions within a single EV. This EV Profile Capture 2024 report stands as an update from the EV Profile Capture 2023 report to include the additional EV & EVSE assets tested and analyzed in 2024. The major updates within this report include the addition of three next-generation electric vehicles, added test cases, and further analysis. This expansion of analysis includes power profiles, power distribution, quantifying SOC, energy and range performance, EVSE limitation impacts, boost converter performance, etc. Additionally, NGP time-series data has been used as input towards three national laboratory-led grid modelling efforts: ANL’s IEEE-37 HIL model, INL’s Caldera model, and NREL’s EVI-X model. A summary of these platforms and how NGP has worked to improve their effectiveness has also been added to this years’ report.

Thurston, Sam

EV Profile Capture 2025: Next-Gen Profiles Project Report

As part of the Next-Gen Profiles (NGP) project, the profile capture and analysis of production electric vehicles undergoing high-power charging (HPC) is conducted over a wide range of conditions to explore variance and performance. Charge session parameters are collected from both the electric vehicle (EV) and electric vehicle supply equipment (EVSE) at a rate of 10Hz and entered into a time-series database for analysis. These charge profiles are captured under nominal and off-nominal conditions, exploring the impact of starting battery state of charge (SOC), battery temperature, vehicle condition, smart charge management (SCM), EVSE limitations and charging adapter usage. Nominal conditions are defined as ideal conditions that should transfer the maximum allowable energy in the minimum possible amount of time. Nominal condition profiles are compared across EVs to characterize state-of-the-art EV charging performance against one another. Off-nominal condition profiles are compared against their nominal condition profile counterparts to highlight the variance across less desirable starting conditions within a single EV.

33 ADVANCED PROPULSION SYSTEMS

High-Fidelity Analysis of EV Integration on Real Utility Feeders in Colorado

Residential electric vehicle (EV) charging has the potential to alter long-held assumptions on load characteristics impacting distribution grid planning, operations, and design standards. This study identifies analysis and control methods to increase the affordability of residential EV charging both for Xcel Energy and their customers. The project also provides solutions for more reliable grid interconnection that can support a reliable utility business model prepared for increasing EV charging load in the coming years. For this project, we referenced Level 2 alternating current (AC) onboard charging profiles for various vehicle models and high-fidelity charging data collected at the experimental setup established at the EV Research Infrastructure Laboratory at the National Renewable Energy Laboratory (NREL). Next, we developed EV adoption models for 2030 and 2040 for the Boulder and Aurora regions in Colorado. Moreover, we evaluated different smart charging control algorithms and compared their performance. We developed time-of-use (TOU)-based and grid-aware active EV charging control methods and integrated them within the study region to understand field impacts. Diving deeper, we selected 10 feeders in Boulder and Aurora for high-fidelity grid modeling down to the house level. We executed detailed grid analysis comparing the smart charge management (SCM) algorithms we developed. Finally, we created a novel tool, Electric Vehicle Infrastructure--Distribution System Integration Tool (EVI-DiST), to integrate all the approaches in a single software environment to provide easy integration, fast simulation, and detailed evaluation capability for utility engineers and other stakeholders.

33 ADVANCED PROPULSION SYSTEMS

OCHRE

OCHRE™ uses a variety of input data sources to run time-series simulations. Building models can be taken from the ResStock™ database or generated using the Building Energy Optimization Tool (BEopt™) or other OpenStudio-HPXML workflows. EV charging profiles can be taken from datasets used in NLR's 2030 National Charging Network project. Weather data can be taken from the National Solar Radiation Database or EnergyPlus® weather files. There are no public datasets with OCHRE outputs at this time. However, a recent project dataset on water heater and EV demand flexibility can be requested. OCHRE is a Python-based energy modeling tool designed to model flexible loads in residential buildings. OCHRE includes detailed models and controls for flexible devices including HVAC equipment, water heaters, EVs, solar PV, and batteries. It is designed to run in co-simulation with custom controllers, aggregators, and grid models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI

A mathematical model for predicting cyclic voltammograms of electronically conductive polypyrrole

Polypyrrole is an attractive polymer for use as a high-energy-density secondary battery because of its potential as an inexpensive, lightweight, and noncorrosive electrode material. A mathematical model to simulate cyclic voltammograms for polypyrrole is presented. The model is for a conductive porous electrode film on a rotating disk electrode (RDE) and is used to predict the spatial and time dependence of concentration, overpotential, and stored charge profiles within a polypyrrole film. The model includes both faradic and capacitance charge components in the total current density expression.

Yeu, Taewhan

A mathematical model for predicting cyclic voltammograms of electronically conductive polypyrrole

Polypyrrole is an attractive polymer for use as a high-energy-density secondary battery because of its potential as an inexpensive, lightweight, and noncorrosive electrode material. A mathematical model to simulate cyclic voltammograms for polypyrrole is presented. The model is for a conductive porous electrode film on a rotating disk electrode (RDE) and is used to predict the spatial and time dependence of concentration, overpotential, and stored charge profiles within a polypyrrole film. The model includes both faradic and capacitance charge components in the total current density expression.

Yeu, Taewhan

A Forward-Looking Dataset of EV Managed Charging Resource and Costs

This presentation summarizes a high-resolution, forward-looking dataset of EV adoption, EV charging, and managed charging resource. Vehicle-level data are grounded in current adoption and charging patterns, and ~200,000 real-world vehicle-weeks of travel data covering all on-road segments (i.e., light-duty, transit and school buses, local, regional and long-haul medium- and heavy-duty). The data, which include multiple charging profiles per vehicle to bound flexibility, are then processed and aggregated to describe baseline charging and charge management resource by county, hour, year, scenario, and vehicle type. Coupled with one of four scenarios of how EV managed charging costs might evolve over time, the dataset enables a power sector capacity expansion model to select cost-optimal quantities of EV managed charging and supply-side resources to reliably satisfy demand. Five integration strategies: Baseline, Daytime and Flat (passive), Flex (active), and Stress (anti-strategy), illustrate how baseline charging and flexibility potential changes with EVSE build-out and charging preferences.

33 ADVANCED PROPULSION SYSTEMS

Instrumentation for Studies of Electron Emission and Charging From Insulators

Making measurements of electron emission properties of insulators is difficult since insulators can charge either negatively or positively under charge particle bombardment. In addition, high incident energies or high fluences can result in modification of a material s conductivity, bulk and surface charge profile, structural makeup through bond breaking and defect creation, and emission properties. We discuss here some of the charging difficulties associated with making insulator-yield measurements and review the methods used in previous studies of electron emission from insulators. We present work undertaken by our group to make consistent and accurate measurements of the electron/ion yield properties for numerous thin-film and thick insulator materials using innovative instrumentation and techniques. We also summarize some of the necessary instrumentation developed for this purpose including fast response, low-noise, high-sensitivity ammeters; signal isolation and interface to standard computer data acquisition apparatus using opto-isolation, sample-and-hold, and boxcar integration techniques; computer control, automation and timing using Labview software; a multiple sample carousel; a pulsed, compact, low-energy, charge neutralization electron flood gun; and pulsed visible and UV light neutralization sources. This work is supported through funding from the NASA Space Environments and Effects Program and the NASA Graduate Research Fellowship Program.

Thomson, C. D.

CalderaCast User Manual Version 1.0

CalderaCast is a user-friendly web-based tool for electrical-load forecast, providing stakeholders with a fully customizable decision-support framework that estimates the likely power draw from a possible future electric-vehicle (EV) charging station at a given location on a given day along an alternative fuel corridor (AFC). These EV charging profiles are accurately modeled in CalderaCast using the Caldera software framework developed by Idaho National Laboratories (INL), reflecting the realistic charging levels observed in actual charge events. This tool was developed as part of the National Electric Vehicle Infrastructure (NEVI) program, which is quickly generating substantial interest from would-be charging station operators (CSO), large and small electric utilities, and state transportation planners, some of whom had not seriously considered EV charging previously. All these entities—with or without background in EV infrastructure—must estimate the electricity load that a proposed charging station will generate. This load forecast is critically important for a utility to properly assess the capacity of their distribution network to support the proposed station or properly size grid upgrades for potential load growth due to future EV adoption, vehicle technology improvements, or station growth. This document describes each aspect of the CalderaCast tool and provides guidance to users who are interested in utilizing the tool for their work.

24 - POWER TRANSMISSION AND DISTRIBUTION

Analyzing Power Supply and Demand on the ISS

Station Power and Energy Evaluation Determiner (SPEED) is a Java application program for analyzing the supply and demand aspects of the electrical power system of the International Space Station (ISS). SPEED can be executed on any computer that supports version 1.4 or a subsequent version of the Java Runtime Environment. SPEED includes an analysis module, denoted the Simplified Battery Solar Array Model, which is a simplified engineering model of the ISS primary power system. This simplified model makes it possible to perform analyses quickly. SPEED also includes a user-friendly graphical-interface module, an input file system, a parameter-configuration module, an analysis-configuration-management subsystem, and an output subsystem. SPEED responds to input information on trajectory, shadowing, attitude, and pointing in either a state-of-charge mode or a power-availability mode. In the state-of-charge mode, SPEED calculates battery state-of-charge profiles, given a time-varying power-load profile. In the power-availability mode, SPEED determines the time-varying total available solar array and/or battery power output, given a minimum allowable battery state of charge.

Thomas, Justin

A Dynamic Pricing Method to Manage the Impact of EV Charging on the Grid Using RL

This work addresses the challenge of managing electrical vehicle (EV) charging loads on distribution feeders with the increase in deployment of fast charging stations. To mitigate the adverse impacts on feeder health, a novel dynamic grid-informed pricing approach is proposed. This approach leverages reinforcement learning (RL) to determine hourly charging prices based on real-time grid conditions. A synthetic environment was developed to train the reinforcement learning agent. A model of an IEEE 34-bus distribution feeder with EV charging stations has been developed in OpenDSS utilizing Caldera for realistic EV charging profiles. Test cases demonstrate that the dynamic pricing strategy achieves higher energy delivery to the EV end user at a lower cost compared to constant pricing methods, while lowering voltage deviations and congestion. This approach offers more granular price adjustments, responding dynamically to feeder conditions and potentially improving grid stability and efficiency. The communication architecture to implement this dynamic pricing method is described. This research contributes to the development of smart grid-informed charging solutions that can reduce the cost of charging to the end user while also helping the grid.

EV charging, dynamic pricing, grid-informed chargi

A dynamic pricing method to manage the impact of EV charging on the grid using RL

This work addresses the challenge of managing electrical vehicle (EV) charging loads on distribution feeders with the increase in deployment of fast charging stations. To mitigate the adverse impacts on feeder health, a novel dynamic grid-informed pricing approach is proposed. This approach leverages reinforcement learning (RL) to determine hourly charging prices based on real-time grid conditions. A synthetic environment was developed to train the reinforcement learning agent. A model of an IEEE 34-bus distribution feeder with EV charging stations has been developed in OpenDSS utilizing Caldera for realistic EV charging profiles. Test cases demonstrate that the dynamic pricing strategy achieves higher energy delivery to the EV end user at a lower cost compared to constant pricing methods, while lowering voltage deviations and congestion. This approach offers more granular price adjustments, responding dynamically to feeder conditions and potentially improving grid stability and efficiency. The communication architecture to implement this dynamic pricing method is described. This research contributes to the development of smart grid-informed charging solutions that can reduce the cost of charging to the end user while also helping the grid.

24 - POWER TRANSMISSION AND DISTRIBUTION

Reconditioning of Batteries on the International Space Station

Primary source of electric power for the International Space Station (ISS) is the photovoltaic module (PVM). At assembly complete stage, the ISS will be served by 4 PVMs. Each PVM contains two independent power channels such that one failure will result in loss of only one power channel. During early stages of assembly, the ISS is served by only one PVM designated as P6. Solar arrays are used to convert solar flux into electrical power. Nickel hydrogen batteries are used to store electrical power for use during periods when the solar input is not adequate to support channel loads. Batteries are operated per established procedures that ensure that they are maintained within specified temperature limits, charge current is controlled to conform to a specified charge profile, and battery voltages are maintained within specified limits. Both power channels on the PVM P6 have been operating flawlessly since December 2000 with 100 percent power availability. All components, including batteries, are monitored regularly to ensure that they are operating within specified limits and to trend their wear out and age effects. The paper briefly describes the battery trend data. Batteries have started to show some effects of aging and a battery reconditioning procedure is being evaluated at this time. Reconditioning is expected to reduce cell voltage divergence and provide data that can be used to update the state of charge (SOC) computation in the software to account for battery age. During reconditioning, each battery, one at a time, will be discharged per a specified procedure and then returned to a full state of charge. The paper describes the reconditioning procedure and the expected benefits. The reconditioning procedures have been thoroughly coordinated by all affected technical teams and approved by all required boards. The reconditioning is tentatively scheduled for September 2004.

Hajela, Gyan