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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Analysis of redox additive-based overcharge protection for rechargeable lithium batteries

The overcharge condition in secondary lithium batteries employing redox additives for overcharge protection, has been theoretically analyzed in terms of a finite linear diffusion model. The analysis leads to expressions relating the steady-state overcharge current density and cell voltage to the concentration, diffusion coefficient, standard reduction potential of the redox couple, and interelectrode distance. The model permits the estimation of the maximum permissible overcharge rate for any chosen set of system conditions. Digital simulation of the overcharge experiment leads to numerical representation of the potential transients, and estimate of the influence of diffusion coefficient and interelectrode distance on the transient attainment of the steady state during overcharge. The model has been experimentally verified using 1,1-prime-dimethyl ferrocene as a redox additive. The analysis of the experimental results in terms of the theory allows the calculation of the diffusion coefficient and the formal potential of the redox couple. The model and the theoretical results may be exploited in the design and optimization of overcharge protection by the redox additive approach.

Narayanan, S. R.↗
NASA NTRS2009

NASA Tech Briefs, November 2009

Topics covered include: Cryogenic Chamber for Servo-Hydraulic Materials Testing; Apparatus Measures Thermal Conductance Through a Thin Sample from Cryogenic to Room Temperature; Rover Attitude and Pointing System Simulation Testbed; Desktop Application Program to Simulate Cargo-Air-Drop Tests; Multimodal Friction Ignition Tester; Small-Bolt Torque-Tension Tester; Integrated Spacesuit Audio System Enhances Speech Quality and Reduces Noise; Hardware Implementation of a Bilateral Subtraction Filter; Simple Optoelectronic Feedback in Microwave Oscillators; Small X-Band Oscillator Antennas; Free-Space Optical Interconnect Employing VCSEL Diodes; Discrete Fourier Transform Analysis in a Complex Vector Space; Miniature Scroll Pumps Fabricated by LIGA; Self-Assembling, Flexible, Pre-Ceramic Composite Preforms; Flight-speed Integral Image Analysis Toolkit; Work Coordination Engine; Multi-Mission Automated Task Invocation Subsystem; Autonomously Calibrating a Quadrupole Mass Spectrometer; Determining Spacecraft Reaction Wheel Friction Parameters; Composite Silica Aerogels Opacified with Titania; Multiplexed Colorimetric Solid-Phase Extraction; Detecting Airborne Mercury by Use of Polymer/Carbon Films; Lattice-Matched Semiconductor Layers on Single Crystalline Sapphire Substrate; Pressure-Energized Seal Rings to Better Withstand Flows; Rollerjaw Rock Crusher; Microwave Sterilization and Depyrogenation System; Quantifying Therapeutic and Diagnostic Efficacy in 2D Microvascular Images; NiF2/NaF:CaF2/Ca Solid-State High-Temperature Battery Cells; Critical Coupling Between Optical Fibers and WGM Resonators; Microwave Temperature Profiler Mounted in a Standard Airborne Research Canister; Alternative Determination of Density of the Titan Atmosphere; Solar Rejection Filter for Large Telescopes; Automated CFD for Generation of Airfoil Performance Tables; Progressive Classification Using Support Vector Machines; Active Learning with Irrelevant Examples; A Data Matrix Method for Improving the Quantification of Element Percentages of SEM/EDX Analysis; Deployable Shroud for the International X-Ray Observatory; Improved Model of a Mercury Ring Damper; Optoelectronic pH Meter: Further Details; X-38 Advanced Sublimator; and Solar Simulator Represents the Mars Surface Solar Environment.

Source record↗
NASA NTRSDate not supplied

SimUAM: A Comprehensive Microsimulation Toolchain to Evaluate the Impact of Urban Air Mobility in Metropolitan Areas

Over the past several years, Urban Air Mobility (UAM) has galvanized enthusiasm from investors and researchers, marrying expertise in aircraft design, transportation, logistics, artificial intelligence, battery chemistry, and broader policymaking. However, two significant questions remain unexplored: (1) What is the value of UAM in a region’s transportation network?, and (2) How can UAM be effectively deployed to realize and maximize this value to all stakeholders, including riders and local economies? To adequately understand the value proposition of UAM for metropolitan areas, we develop a holistic multi-modal toolchain, SimUAM, to model and simulate UAM and its impacts on travel behavior. This toolchain has several components: (1) MANTA: A fast, high-fidelity regional-scale traffic microsimulator, (2) VertiSim: A granular, discrete-event vertiport and pedestrian, (3) 3: A high-fidelity, trajectory-based aerial microsimulation. SimUAM, rooted in granular, GPU-based microsimulation, models millions of trips and their exact movements in the street network and in the air, producing interpretable and actionable performance metrics for UAM designs and deployments. The modularity, extensibility, and speed of the platform will allow for rapid scenario planning and sensitivity analysis, effectively acting as a detailed performance assessment tool. As a result, stakeholders in UAM can understand the impacts of critical infrastructure, and subsequently define policies, requirements, and investments needed to support UAM as a viable transportation mode.

Urban air mobility↗
NASA NTRSDate not supplied

Turbine Electrified Energy Management with Model Predictive Control

Affordability, sustainability, and efficiency are primary motivators driving the future of NASA aeronautics research. These factors are realized, in part, through the development and implementation of new technologies and strategies enabling efficient, affordable, and safe hybrid-electric aircraft. Research supporting electrified aircraft propulsion control systems exemplifies such new methodologies, offering varied opportunities to integrate electric machines with gas-based turbine engines. For hybrid-electric propulsion systems, current conceptual architectures seek to introduce energy storage and exploit electrical power system components to assist gas-based system components. Capitalizing on the electric machines in hybridized engines, Turbine Electrified Energy Management (TEEM) is a control approach that enhances transient operability to improve overall propulsion and vehicle efficiency by injecting or extracting power from engine shafts. Traditionally implemented with proportional-integral (PI) control, this study expands the application of TEEM by presenting model predictive control (MPC) schemes to execute the TEEM concept. Via cost function design and constraint selection, the transient operability goals for TEEM are considered in the controller designs. The proposed MPCs are simulated on a nonlinear turbofan engine model at two environmental conditions, with comparisons drawn to a baseline PI. Performance is evaluated using compressor maps and two TEEM-specific metrics: transient stack usage and transient excursion integral. Simulation results reveal the developed schemes perform comparably to the benchmark controller and can be implemented in two distinct configurations. Potential modifications for future investigations include cost function measures that optimize energy use, additional performance effectiveness measures, and battery storage capabilities.

Elyse D. Hill↗
NASA NTRSDate not supplied

SimUAM: A Comprehensive Microsimulation Toolchain to Evaluate the Impact of Urban Air Mobility in Metropolitan Areas

Over the past several years, Urban Air Mobility (UAM) has galvanized enthusiasm from investors and researchers, marrying expertise in aircraft design, transportation, logistics, artificial intelligence, battery chemistry, and broader policymaking. However, two significant questions remain unexplored: (1) What is the value of UAM in a region’s transportation network? and (2) How can UAM be effectively deployed to realize and maximize this value to all stakeholders, including riders and local economies? To adequately understand the value proposition of UAM for metropolitan areas, the authors develop a holistic multi-modal toolchain, SimUAM, to model and simulate UAM and its impacts on travel behavior. This toolchain has several components: (1) Microsimulation Analysis for Network Traffic Assignment (MANTA): A fast, high-fidelity regional-scale traffic microsimulator, (2) VertiSim: Agranular, discrete-event vertiport and pedestrian simulator, (3) Flexible Engine for Fast-time Evaluation of Flight Environments (Fe3): A high-fidelity, trajectory-based aerial microsimulation. SimUAM, rooted in granular, GPU-based microsimulation, models millions of trips and their movements in the street network and in the air, producing interpretable and actionable performance metrics for UAM designs and deployments. Once the ground-air interface is modeled, the authors find that the market for UAM decreases across all network designs relative to models with static assumptions about transfer times. However, significant improvements can be made to balance the demand and optimize the networks for transfer time, likely increasing the number of benefited trips. The modularity, extensibility, and speed of the platform will allow for rapid scenario planning and sensitivity analysis, effectively acting as a detailed performance assessment tool.

urban air mobility↗
NASA NTRS2011

US Clean Energy Sector and the Opportunity for Modeling and Simulation

The following paper sets forth the current understanding of the US clean energy demand and opportunity. As clean energy systems come online and technology is developed, modeling and simulation of these complex energy programs provides an untapped business opportunity. The US Department of Defense provides a great venue for developing new technology in the energy sector because it is demanding lower fuel costs, more energy efficiencies in its buildings and bases, and overall improvements in its carbon footprint. These issues coupled with the security issues faced by foreign dependence on oil will soon bring more clean energy innovations to the forefront (lighter batteries for soldiers, alternative fuel for jets, energy storage systems for ships, etc).

Inge, Carole Cameron↗
NASA NTRS1998

N(N)-nicotinic blockade as an acute human model of autonomic failure

Pure autonomic failure has been conceptualized as deficient sympathetic and parasympathetic innervation. Several recent observations in chronic autonomic failure, however, cannot be explained simply by loss of autonomic innervation, at least according to our current understanding. To simulate acute autonomic failure, we blocked N(N)-nicotinic receptors with intravenous trimethaphan (6+/-0.4 mg/min) in 7 healthy subjects (4 men, 3 women, aged 32+/-3 years, 68+/-4 kg, 171+/-5 cm). N(N)-Nicotinic receptor blockade resulted in near-complete interruption of sympathetic and parasympathetic efferents as indicated by a battery of autonomic function tests. With trimethaphan, small postural changes from the horizontal were associated with significant blood pressure changes without compensatory changes in heart rate. Gastrointestinal motility, pupillary function, saliva production, and tearing were profoundly suppressed with trimethaphan. Plasma norepinephrine level decreased from 1.1+/-0.12 nmol/L (180+/-20 pg/mL) at baseline to 0.23+/-0.05 nmol/L (39+/-8 pg/mL) with trimethaphan (P<.001). There was a more than 16-fold increase in plasma vasopressin (P<.01) and no change in plasma renin activity. We conclude that blockade of N(N)-cholinergic receptors is useful to simulate the hemodynamic alterations of acute autonomic failure in humans. The loss of function with acute N(N)-cholinergic blockade is more complete than in most cases of chronic autonomic failure. This difference may be exploited to elucidate the contributions of acute denervation and chronic adaptation to the pathophysiology of autonomic failure. N(N)-Cholinergic blockade may also be applied to study human cardiovascular physiology and pharmacology in the absence of confounding baroreflexes.

Non-NASA Center↗
NASA NTRS2023

Modeling and Simulation of a Parallel Hybrid Electric Regional Aircraft for the Electrified Powertrain Flight Demonstration (EPFD) Program

This paper presents a parametric modeling and integrated aircraft sizing and synthesis approach for a charge depleting parallel hybrid electric architecture. The developed models are integrated within the baseline thin-haul and regional aircraft. In addition to the physical architecture, different modes of operation enabled by propulsion system electrification are also modeled parametrically. The modes of operation presented in this paper are the peak power shaving, climb power electric boost, in-flight battery recharging, and electric taxi. The sizing of the powertrain and the aircraft are performed within the multidisciplinary analysis and optimization environment, E-PASS. The consideration of the physical system and its operation together provides a holistic approach where the propulsion system and the airframe are designed under an optimized power and energy management strategy. The parametric nature of the work enables the design space exploration for electrification and lays the groundwork for future technology projection and uncertainty quantification studies. The developed capability is generic and can be applied on other aircraft classes. The work is done as part of the Electrified Powertrain Flight Demonstration program.

electrified powertrain flight demonstration↗
NASA NTRS1987

Computer simulation of thermal modeling of primary lithium cells

The objective was to gain a better understanding of the safety problem of primary Li-SOCl2 and Li-SO2 cells by carrying out detailed thermal modeling work. In particular, the transient heat generation rates during moderate and extermely high discharge rate tests of Li-SOCl2 cells were predicted and compared with those from the electrochemical heating. The difference between the two may be attributed to the lithium corrosion and other chemical reactions. The present program was also tested for charging of Li-SO2. In addition, the present methodology should be applicable to other primary cylindrical cells as well as rechargeable battery analyses with minor modifications.

Young, I. Cho↗
NASA NTRS2012

An Efficient Deterministic Approach to Model-based Prediction Uncertainty Estimation

Prognostics deals with the prediction of the end of life (EOL) of a system. EOL is a random variable, due to the presence of process noise and uncertainty in the future inputs to the system. Prognostics algorithm must account for this inherent uncertainty. In addition, these algorithms never know exactly the state of the system at the desired time of prediction, or the exact model describing the future evolution of the system, accumulating additional uncertainty into the predicted EOL. Prediction algorithms that do not account for these sources of uncertainty are misrepresenting the EOL and can lead to poor decisions based on their results. In this paper, we explore the impact of uncertainty in the prediction problem. We develop a general model-based prediction algorithm that incorporates these sources of uncertainty, and propose a novel approach to efficiently handle uncertainty in the future input trajectories of a system by using the unscented transformation. Using this approach, we are not only able to reduce the computational load but also estimate the bounds of uncertainty in a deterministic manner, which can be useful to consider during decision-making. Using a lithium-ion battery as a case study, we perform several simulation-based experiments to explore these issues, and validate the overall approach using experimental data from a battery testbed.

Daigle, Matthew J.↗
NASA NTRS1980

A new controller for battery-powered electric vehicles

This paper describes the development, under a NASA/DOE contract, of a new concept for efficient and reliable control of battery-powered vehicles. It avoids the detrimental effects of pulsed-power controllers like the SCR 'chopper' by using rotating machines to meter continuous currents to the traction motor. The concept is validated in a proof-of-principle demonstration system and a complete vehicle is simulated on an analog computer. Test results show exceptional promise for a full-scale system. Optimum control strategies to minimize controller weight are developed by means of the simulated vehicle. The design for an Engineering Model is then prepared in the form of a practical, compact two-bearing package with forced air cooling. Predicted performance is outstanding, with controller efficiency of over 90% at high speed.

Belsterling, C. A.↗
NASA NTRS1989

Optimization of the lithium/thionyl chloride battery

A 1-D math model for the lithium/thionyl chloride primary cell is used in conjunction with a parameter estimation technique in order to estimate the electro-kinetic parameters of this electrochemical system. The electro-kinetic parameters include the anodic transfer coefficient and exchange current density of the lithium oxidation, alpha sub a,1 and i sub o,i,ref, the cathodic transfer coefficient and the effective exchange current density of the thionyl chloride reduction, alpha sub c,2 and a sup o i sub o,2,ref, and a morphology parameter, Xi. The parameter estimation is performed on simulated data first in order to gain confidence in the method. Data, reported in the literature, for a high rate discharge of an experimental lithium/thionyl chloride cell is used for an analysis.

White, Ralph E.↗
NASA NTRS2018

Remaining Flying Time Prediction Implementing Battery Prognostics Framework for Electric UAV's

In this paper the problem of building trust in the online safety prediction of an fixed wing small electric unmanned aerial vehicles (e-UAV) for remaining flying time is addressed. A series of flight tests are described to verify the performance of the remaining flying time prediction algorithm. The estimate of remaining flying time is used to activate an alarm when the predicted remaining time falls below a threshold of two minutes. This updates the pilot to transition to the landing sequence of the flight profile. A second alarm is activated when the battery state of charge (SOC) falls below a specified safety limit threshold. This SOC threshold is the point at which the battery energy reserve would no longer safely support enough aborted landing attempts. During the test flights, the motor system is operated with the same predefined timed airspeed profile for each test. To test the robustness of the developed prediction algorithm, partial tests were performed with and remaining were performed without a simulated power train fault. To simulate a partial power train fault in the e-UAV the pilot engages a resistor bank at a specified time during the test flight. The flying time prediction system is agnostic of the pilot's activation of the fault and must adapt to the vehicle's state. The time at which the limit threshold on battery SOC is reached, it is then used to measure the accuracy of the remaining flying time predictions. This is demonstrated through comparing results from two battery models being developed. Accuracy requirements for the alarms are considered and the results discussed.

Kulkarni, Chetan↗
NASA NTRSDate not supplied

Battery State-of-Health Aware Path Planning for a Mars Rover

A rover mission consists of visiting waypoints to gather scientific samples based on set requirements. However, rovers face operational uncertainties during the mission, affecting the performance of its electrical and mechanical components and overall mission success. Hence, it is critical to have a decision-making framework that is aware of the health state of the components when planning the path of the vehicle. In particular, battery degradation, and consequently the battery State of Health (SOH), can affect the optimality of decisions made by the autonomous system in the long term. This paper presents a decision-making system that incorporates information on the energy drawn from the battery (based on the vehicle’s velocity), terrain conditions, and model-based prognostic modules to assess the impact on the battery’s state of charge (SoC). The decision-making system was formulated as a Markov Decision Process (MDP) to reach the goal destination by sending commands in a determined amount of time while maintaining the battery SoC within the policy stated. The MDP problem was programmed using the open-source framework POMDPs.jl, which has a variety of online and offline solvers. To solve the MDP problem online, we used Monte Carlo Tree Search (MCTS). Results from simulations demonstrate the effect that battery degradation and charging plans have on decision-making.

Prognostics↗
NASA NTRS2025

Airports as Energy Nodes Activity Summary

Advanced aircraft concepts that use non-traditional aviation energy storage methods such as batteries or cryogenic hydrogen are in development and expected to enter regular service at airports worldwide within the next decade. The energy needs for these aircraft may quickly overwhelm the existing energy infrastructure at airports, particularly at smaller and more remote facilities. Without energy upgrades, these airports will not be able to host these advanced vehicles, but without the advanced vehicle traffic, these airports will not have the rationale or funding to build up their energy infrastructure. The Airports as Energy Nodes (ÆNodes) activity, a collaboration between the National Aeronautics and Space Administration (NASA) and the National Renewable Energy Laboratory (NREL), was executed to understand and model the energy needs that advanced aircraft concepts may levy on these smaller airports, determine cost-effective approaches to enhance the airport energy infrastructure, and demonstrate the enhanced resilience of these energy infrastructure upgrades to the airport and surrounding community via “digital twin” simulation at relevant energy and dynamic time scales. The ÆNodes team also investigated future reference aircraft designs and materials to enable cryogenic hydrogen storage for aircraft. The ÆNodes team conducted analysis at two U.S. airport partner sites — Winchester Regional Airport in Winchester, Virginia, and Tweed/New Haven Airport in New Haven, Connecticut. The goal of this partnership was to develop data and reference infrastructure designs that could accommodate advanced aircraft in the future at these airports while also enhancing the resiliency of the energy supply to the surrounding airport community, which could be used to capture funding to enable the infrastructure upgrades. Over the course of the study, a method was developed to estimate air traffic requiring advanced energy services over the course of a year using a mix of historical data and companion studies on advanced aircraft transportation networks. The study has concluded at NASA but continues at NREL, who will develop a final report discussing the energy infrastructure upgrades and digital twin results. Preliminary results indicate that unrestricted adoption of advanced battery-electric aircraft may double traffic at these airports and increase peak daily power usage by an order of magnitude, while increase electricity energy needs by a factor of two to four. The infrastructure upgrades necessary to accommodate these increased energy needs could be used to provide enhanced energy services to the airport community to offset the cost and increase the utility of the upgrades, which will be described in the NREL final report.

Airports↗
NASA NTRSDate not supplied

Weight and Balance Considerations for Electrified Aircraft Propulsion Applied to the Parallel Electric-Gas Architecture with Synergistic Utilization Scheme (PEGASUS) Concept

The focus of this research was to understand the impact of batteries and electric motors on the weight and balance of the Parallel Electric-Gas Architecture with Synergistic Utilization Scheme (PEGASUS) concept. Because electrified aircraft propulsion components can comprise a large part of an aircraft’s weight, their integration has a significant impact on the center of gravity location and the related stability characteristics of the aircraft. We developed an analysis framework that enabled estimating the weight and volume of electrified aircraft components, their contribution to the center of gravity location, and the stability and performance of the aircraft. Trades were performed on battery placement, wing attachment point, and electric motor power to determine their impact on figures of merit such as maximum takeoff weight and block fuel. We identified batteries, and to a lesser extent electric motors, as having a large impact on aircraft center of gravity and the required horizontal tail size for longitudinal static stability. Placing electric component weight as far forward as possible resulted in reductions in the horizontal tail size required to maintain static stability. Configurations output from this framework were also evaluated using a six-degree-of-freedom simulation to quantify dynamic stability characteristics. Although shifting weight forward reduced horizontal tail size, it negatively impacted dynamic stability. This study confirms that mass property modeling and dynamic simulation, which are usually limited in conceptual design, are important for electrified aircraft concepts.

electrified aircraft propulsion↗
NASA NTRSDate not supplied

A Multiphysics Study to Improve Specific Energy of Primary Batteries for Low Temperature Operation for Deep Space Missions

Several lander missions on the outer planets such as Europa, Enceladus, and Titan require electrical power to operate scientific and communication equipment. The traditional power generation methods, such as a photovoltaic array, are not feasible as their efficiency drops significantly at these vast distances. The novel radioisotope power systems are not practical today based on current lander designs and the effectiveness of these systems. To perform in situ science on distant planets, a high specific energy battery (>700 Wh/kg) needs to operate for about 480 hours under cold temperatures (-40C or 0C) [1]. While a primary battery such as Li-CFx can provide high specific energy at room temperature, its specific capacity decreases significantly at low temperatures. One of the causes for this drop is low ion and electrical conductivity, and slower reaction kinetics. Slower transport and facile kinetics lead to an increase in the battery’s resistance and higher voltage drops during the cell operation, thus reducing specific capacity. Both the transport and kinetics show a strong dependence on temperature. Thus, a small temperature rise can lead to an increase in the reaction rate and ion conductivity; since the temperature, cell resistance, and specific capacity are interdependent. A conventional battery model accounts for ohmic, thermodynamic, and, electrochemical, and chemical decomposition heating. The ohmic heating can be controlled by designing a resistive microstructure and varying the ratios of the active materials [2]. The kinetics can be improved by increasing the surface area, reducing the particle size, or adding a catalyst. These parameters are often optimized to achieve high specific energy at room temperatures. A similar optimization study is not available at low temperatures and for a primary (high specific energy) battery. For this presentation, we will explore the effect of geometrical, microstructural, and material properties on optimal specific capacity at low temperatures through multiphysics simulations. The ion transport resistance depends on the porosity and the tortuosity of an electrode and the separator.

M. Mehta↗
NASA NTRS2013

Advanced Methods for Determining Prediction Uncertainty in Model-Based Prognostics with Application to Planetary Rovers

Prognostics is centered on predicting the time of and time until adverse events in components, subsystems, and systems. It typically involves both a state estimation phase, in which the current health state of a system is identified, and a prediction phase, in which the state is projected forward in time. Since prognostics is mainly a prediction problem, prognostic approaches cannot avoid uncertainty, which arises due to several sources. Prognostics algorithms must both characterize this uncertainty and incorporate it into the predictions so that informed decisions can be made about the system. In this paper, we describe three methods to solve these problems, including Monte Carlo-, unscented transform-, and first-order reliability-based methods. Using a planetary rover as a case study, we demonstrate and compare the different methods in simulation for battery end-of-discharge prediction.

prognosis↗