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Results for “Battery Modeling”

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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Mathematical modeling of a thermovoltaic cell

A new type of battery named 'Vaporvolt' cell is in the early stage of its development. A mathematical model of a CuO/Cu 'Vaporvolt' cell is presented that can be used to predict the potential and the transport behavior of the cell during discharge. A sensitivity analysis of the various transport and electrokinetic parameters indicates which parameters have the most influence on the predicted energy and power density of the 'Vaporvolt' cell. This information can be used to decide which parameters should be optimized or determined more accurately through further modeling or experimental studies. The optimal thicknesses of electrodes and separator, the concentration of the electrolyte, and the current density are determined by maximizing the power density. These parameter sensitivities and optimal design parameter values will help in the development of a better CuO/Cu 'Vaporvolt' cell.

White, Ralph E.↗
NASA NTRS2003

A Comparison of Two Panasonic Lithium-Ion Batteries and Cells for the IBM Thinkpad

The IBM Thinkpad 760XD has been used in the Orbiter and International Space Station since 2000. The Thinkpad is powered by a Panasonic Li-ion battery that has a voltage of 10.8 V and 3.0 Ah capacity. This Thinkpad is now being replaced by the IBM Thinkpad A31P which has a Panasonic Li-ion battery that has a voltage of 10.8 V and 4.0 Ah capacity. Both batteries have protective circuit boards. The Panasonic battery for the Thinkpad 760XD had 12 Panasonic 17500 cells of 0.75 Ah capacity in a 4P3S cOnfiguration. The new Panasonic battery has 6 Panasonic 18650 cells of 2.0 Ah capacity in a 2P3S configuration. The batteries and cells for both models have been evaluated for performance and safety. A comparison of the cells under similar test conditions will be presented. The performance of the cells has been evaluated under different rates of charge and discharge and different temperatures. The cells have been tested under abuse conditions and the safety features in the cells evaluated. The protective circuit board in the battery was also tested under conditions of overcharge, overdischarge, short circuit and unbalanced cell configurations. The results of the studies will be presented in this paper.

Jeevarajan, Judith A.↗
NASA NTRS1992

A test suite for magnetohydrodynamical simulations

A collection is presented of MHD problems that will provide researchers who have interests in modeling MHD phenomena with a battery of tests (a 'test suite') for calibrating their numerical algorithms. Use of these tests will provide a common reference for comparison of different numerical MHD algorithms. The test suite includes both 1D and 2D problems. Taken together, these problems test the abilities of a numerical method to propagate accurately all of the MHD wave families in moving and stationary media, to capture MHD shocks and contact discontinuities, and to model accurately Lorentz force terms in multiple dimensions. An example solution of each test problem is presented. Diagnostic convergence-testing procedures that provide a quantitative evaluation of MHD algorithms are demonstrated.

Stone, James M.↗
NASA NTRS1992

A mathematical model of a CuO/Cu Vaporvolt cell

A new type of battery named 'Vaporvolt' cell is in the early stage of its development. A mathematical model of a CuO/Cu 'Vaporvolt' cell is presented that can be used to predict the potential and the transport behavior of the cell during discharge. A sensitivity analysis of the various transport and electrokinetic parameters indicates which parameters have the most influence on the predicted energy and power density of the 'Vaporvolt' cell. This information can be used to decide which parameters should be optimized or determined more accurately through further modeling or experimental studies. The optimal thicknesses of electrodes and separator, the concentration of the electrolyte, and the current density are determined by maximizing the power density. These parameter sensitivities and optimal design parameter values will help in the development of a better CuO/Cu 'Vaporvolt' cell.

Kawanami, Makoto↗
NASA NTRS1994

Performance model of a recirculating stack nickel hydrogen cell

A theoretical model of the nickel hydrogen battery cell has been utilized to describe the chemical and physical changes during charge and overcharge in a recirculating stack nickel hydrogen cell. In particular, the movement of gas and electrolyte have been examined as a function of the amount of electrolyte put into the cell stack during cell activation, and as a function of flooding in regions of the gas screen in this cell design. Additionally, a two-dimensional variation on this model has been utilized to describe the effects of non-uniform loading in the nickel-electrode on the movement of gas and electrolyte within the recirculating stack nickel hydrogen cell. The type of nonuniform loading that has been examined here is that associated with higher than average loading near the surface of the sintered nickel electrode, a condition present to some degree in many nickel electrodes made by electrochemical impregnation methods. The effects of high surface loading were examined primarily under conditions of overcharge, since the movement of gas and electrolyte in the overcharging condition was typically where the greatest effects of non-uniform loading were found. The results indicate that significant changes in the capillary forces between cell components occur as the percentage of free volume in the stack filled by electrolyte becomes very high. These changes create large gradients in gas-filled space and oxygen concentrations near the boundary between the separator and the hydrogen electrode when the electrolyte fill is much greater than about 95 percent of the stack free volume. At lower electrolyte fill levels, these gaseous and electrolyte gradients become less extreme, and shift through the separator towards the nickel electrode. Similarly, flooding of areas in the gas screen cause higher concentrations of oxygen gas to approach the platinum/hydrogen electrode that is opposite the back side of the nickel electrode. These results illustrate the need for appropriate pore size distributions, and the maintenance of both convective electrolyte and gas flow paths through the stack, if the recirculating stack nickel hydrogen cell design is to work properly.

Zimmerman, Albert H.↗
NASA NTRS1940

A New Method of Studying the Flow of the Water Along the Bottom of a Model of a Flying-boat Hull

A new method of studying the flow of the water along the bottom of a model of a flying-boat hull is described. In this method, the model is fitted with a transparent bottom and is divided down the center line by a bulkhead. The flow is observed and photographed through one-half of the model by means of the diffused illumination from a battery of lamps contained in the other half of the model. Photographs of the flow, particularly of the changes that occur when the step ventilates, are shown. The results of the present investigation indicate that the method has considerable promise, chiefly in connection with motion-picture studies.

Ward, Kenneth E↗
NASA NTRS2020

Computational Design of Eutectic Molten Salt Mixtures: What Can Thermodynamic Models Do?

In the search for efficient energy storage battery technologies, designing stable electrolytes has been a long-standing challenge. Electrolytes based on molten salt eutectics are known for their stability with minimum parasitic reactions when compared to their widely used organic counterparts. However, the operating temperatures of these molten salt electrolyte-based batteries are dictated by the melting point of the eutectic mixtures. Design and high throughput screening of low melting temperature eutectic molten salt mixtures have been hindered by the lack of computational models. In this work, we develop thermodynamic models to predict the eutectic points of several molten salt mixtures. The framework of the COSMO-SAC model is used for the predictions and is compared with experimental data and other thermodynamic approaches. Rapid thermodynamics-based approaches, as shown in this study, can accelerate the discovery of new materials, complementing experimental techniques.

Ashwin Ravichandran↗
NASA NTRSDate not supplied

Enabling in-time Prognostics with Surrogate Modeling through Physics-enhanced Dynamic Mode Decomposition Method

Computational models provide essential quantitative tools for assessing and predicting the health and performance of physical systems. However, high-fidelity models are rarely used in real-time operations or large optimization loops, due to their time-intensive nature. A common approach to improving computational efficiency of prognosis is to employ surrogate models. Such models can significantly decrease computation time for some accuracy loss. In this context, use of Dynamic Mode Decomposition (DMD) is proposed to generate surrogate models for lithium-ion (Li-ion) battery discharge. DMD has been suggested and used successfully in the area of fluid dynamics for over a decade, but it has not been applied to the PHM domain, where far-ahead prediction of nonlinear behavior is crucial to propagate faults or predict Remaining Useful Life (RUL). For Li-ion battery health management, the standard application of DMD using only the observable quantities of interest was unable to capture the nonlinear discharge of batteries exhibited in lab testing. The Koopman theory, however, provides a mechanism to tradeoff low dimensional nonlinear models with high-dimensional linear ones in a DMD framework, by augmenting nonlinear state variables into the system representation. In this way, DMD allows for configurable simulation accuracy dependent on the dimensionality of the Koopman operator. For battery health management, we augmented the observable variables with the hidden states of a higher-fidelity physics model to build the DMD surrogate. In comparison to a high-fidelity model, the surrogate improved computational efficiency with only a minimal loss of accuracy, and enabled long-term prognostics horizons. A generalized method for this was implemented in the prog models python package.

prognostics and health management↗
NASA NTRS2016

An Influenced Future

Phobos is a vital precursor and catalyst before our next giant leap to Mars. The principle period of a Phobos' mission could be a series of robotic precursor missions for experimental perception, soil examination, ecological approval and landing site distinguishing proof. For my summer intern position at Johnson Space Center I chipped away at creating a GUNNS (General Use Nodal Network Solver) based power subsystem model for the miniATHLETE hopper, which is a conceptual (idea-based) robotic lander that will operate on Phobos. Keeping in mind the end goal to begin on my venture, I needed to comprehend my undertaking before whatever else, in which I concentrated on C++ to see how to implement the code that GUNNS generates to a Trick S_define file. Prior to coming to this internship at Johnson Space Center Dr. Edwin Zack Crues provided a class on modeling and simulation, which introduced me to the Trick simulation environment. The goal of my project was to develop a GUNNS based power subsystem model for the miniATHLETE hopper. The model needed to incorporate a solar array, battery, hopping legs, and onboard scientific instruments (sensitive measuring/recording devices). The secondary bonus goal after I completed the electrical aspect of my model was to develop a GUNNS based thermal subsystem model for the miniATHLETE hopper. Stringing the two aspects together, I would need to code up a signal aspect to make the system work as one. Accomplishing my goals would not be an easy thing, however I had successfully completed the electrical aspect model with twenty-four servos, six cameras, and multiple sensors. Venturing to complete my project has eluded me to many failures in my design to tune many things like the battery to the proper voltage and the load to the proper wattage. During this time I had touched up on advanced topics in calculus in which I implemented in the converter in my electrical model. I am currently working with my mentor Zu Qun Li to create a signal aspect to control the temperatures inside my electrical aspect model. During my time at JSC I had effectively figured out how to create subsystem models utilizing Trick and GUNNS. I obtain essential knowledge of power and thermal subsystem design for a robotic vehicle. I also learned how to work and communicate in a team effectively to accomplish a goal. Before coming to Johnson Space Center my future career and educational goals included uncertainty, however now I have a completely new look on my path to a prosperous future. My NASA experience has unquestionably impacted me to accomplish and surpass my own particular desires. After my time at Johnson Space Center I plan to apply for a coop position for NASA. This has been a dream come true that I adored each moment being at JSC realizing that I am far fit for doing things most individuals can just long for.

Owens, Christopher↗
NASA NTRSDate not supplied

Health Monitoring and Prognostics in Li-ion Batteries

Space applications need to overcome a very critical challenge of predicting remaining useful life of its critical systems/subsystems, with batteries being one of them. Batteries, power electronics conditioning system and motors and one of the most critical systems. Similarly in case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. Two approaches are presented with battery prognostics application. The first approach presentation covers a physics based-modeling approach implemented for battery prognostics. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. A second hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems i.e. batteries is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Batteries↗
NASA NTRSDate not supplied

Health Monitoring and Prognostics in Li-ion Batteries

Space applications need to overcome a very critical challenge of predicting remaining useful life of its critical systems/subsystems, with batteries being one of them. Batteries, power electronics conditioning system and motors and one of the most critical systems. Similarly in case of electric aircrafts, computing remaining flying time is safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To tackle and solve the prediction problem, it is essential to have awareness of the current state and health of the system, especially since it is necessary to perform condition-based predictions. To be able to accurately predict the future state of any system, it is required to possess knowledge of its current and future operations. Given models of the current and future system behavior, the general approach of model-based prognostics can be employed as a solution to the prior stated prediction problem. Two approaches are presented with battery prognostics application. The first approach presentation covers a physics based-modeling approach implemented for battery prognostics. Given models of the current and future system behavior, a general approach of model-based prognostics can be employed as a solution to the prediction problem and further for decision making. A second hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems i.e. batteries is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Battery Prognostics↗
NASA NTRS2016

Measured Noise from Small Unmanned Aerial Vehicles

Proposed uses of small unmanned aerial vehicles (UAVs), including home package delivery, have the potential to expose large portions of communities to a new noise source. This paper discusses results of flyover noise measurements of four small UAVs, including an internal combustion-powered model airplane and three battery-powered multicopters. Basic noise characteristics of these vehicles are discussed, including spectral properties and sound level metrics such as sound pressure level, effective perceived noise level, and sound exposure level. The size and aerodynamic characteristics of the multicopters in particular make their flight path susceptible to atmospheric disturbances such as wind gusts. These gusts, coupled with a flight control system that varies rotor speed to maintain vehicle stability, create an unsteady acoustic signature. The spectral variations resulting from this unsteadiness are explored, in both hover and flyover conditions for the multicopters. The time varying noise, which differs from the relatively steady noise generated by large transport aircraft, may complicate the prediction of human annoyance using conventional sound level metrics.

Cabell, Randolph↗
NASA NTRS2018

Multidisciplinary Conceptual Design for Reduced-Emission Rotorcraft

Python-based wrappers for OpenMDAO are used to integrate disparate software for practical conceptual design of rotorcraft. The suite of tools which are connected thus far include aircraft sizing, comprehensive analysis, and parametric geometry. The tools are exercised to design aircraft with aggressive goals for emission reductions relative to fielded state-of-the-art rotorcraft. Several advanced reduced-emission rotorcraft are designed and analyzed, demonstrating the flexibility of the tools to consider a wide variety of potentially transformative vertical flight vehicles. To explore scale effects, aircraft have been sized for 5, 24, or 76 passengers in their design missions. Aircraft types evaluated include tiltrotor, single-main-rotor, coaxial, and side-by-side helicopters. Energy and drive systems modeled include Lithium-ion battery, hydrogen fuel cell, turboelectric hybrid, and turboshaft drive systems. Observations include the complex nature of the trade space for this simple problem, with many potential aircraft design and operational solutions for achieving significant emission reductions. Also interesting is that achieving greatly reduced emissions may not require exotic component technologies, but may be achieved with a dedicated design objective of reducing emissions.

Rotorcraf↗
NASA NTRSDate not supplied

Battery Cell-to-Pack Scaling Laws for Electric Aircraft

Battery pack gravimetric energy density is one of the most important, yet often miss-estimated design parameters for sizing all-electric aircraft. Proper accounting for thermal, structural, and operational safety margins are frequently lost when extrapolating performance from the cell level to the aircraft level. This paper summarizes the relevant engineering and certification details needed to better account for the penalties associated when assembling battery packs. The relationship between the cell and pack energy density is not linear, as is often assumed. Furthermore, the relationship varies depending on pack requirements, cell chemistry, and architecture. Parametric, high-fidelity models are used to determine optimal battery pack sizes over a range of conditions to better quantify technology scaling effects.

Battery Electric Aircraft↗
NASA NTRSDate not supplied

Battery Cell-to-Pack Scaling Trends for Electric Aircraft

Battery pack gravimetric energy density is one of the most important, yet often miss- estimated design parameters for sizing all-electric aircraft. Proper accounting for thermal, structural, and operational safety margins are frequently lost when extrapolating performance from the cell level to the aircraft level. This paper summarizes the relevant engineering and certification details needed to better account for the penalties associated when assembling battery packs. The relationship between the cell and pack energy density is not linear, as is often assumed. Furthermore, the relationship varies depending on pack requirements, cell chemistry, and architecture. Parametric, high-fidelity models are used to determine optimal battery pack sizes over a range of conditions to better quantify technology scaling effects.

Battery Electric Aircraft↗
NASA NTRS1996

Electrolyte Management Considerations in Modern Nickel Hydrogen and Nickel Cadmium Cell and Battery Designs

This paper reviews three general areas where the potassium ion content can impact the performance and life of nickel hydrogen and nickel cadmium cells. Sample calculations of the concentration or volume changes that can take place within operating cells are presented. With the aid of an accurate model of an operating cell or battery, the impact of changes of potassium ion content within a potential cell design can be estimated. All three of these areas are directly related to the volume tolerance and pore size engineering aspects of the components used in the cell or battery design.

Thaller, Lawrence H.↗
NASA NTRS2019

Constraint-Based Off-Nominal Behavior Modeling for Europa Clipper

The risk analysis for the Europa Clipper mission evaluates the probability of mission failure based on the failure rates of individual components and dependencies among them. The probabilities are calculated by integrating over the intervals of time within which a fault occurs, accounting for an infinite number of cases. The response of the spacecraft to different faults can result in different schedules of activities, changing the intervals of integration. Europa currently uses models of spacecraft systems and components to simulate individual flight scenarios. The goal is to develop a framework for integrating, automating, and improving this modeling process. We describe an approach to generating the schedules for the different fault cases and determining the intervals for faults. It is not enough to just simulate individual cases because we are working with continuous variables that generate an infinite number of possible futures. Instead, we determine time windows within which certain faults can occur and use these time windows as bounds for integration. We found that determining these time windows is a constraint optimization problem. In order to represent these problems, we employ a language based on ontologies of behavior and scenarios. The language enables us to specify constraints in a simple, declarative syntax. A constraint-based analysis engine uses the declarative specification to identify bounds on system parameters and fill in details of behavior. For example, we created a detailed model of power generation, power use, and the corresponding effects on the battery in order to determine when an undervoltage fault can occur. An undervoltage during a trajectory correction maneuver requires that thrusting be interrupted for just enough time to recharge the battery such that the maneuver can be completed within battery limits. This behavior is generated based on the model to minimize the interruption time. For certain scenarios the constraint optimization problems were simple enough to be solved by hand, but the framework made the process substantially faster. It also produced solutions to other problems that we could not solve by hand or with existing tools and allowed us to generate and run many scenarios at once. The scenario language and engine greatly simplified the process of identifying time bounds and separating cases.

Everline, Chester J.↗