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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Nickel-cadmium Battery Cell Reversal from Resistive Network Effects

During the individual cell short-down procedures often used for storing or reconditioning nickel-cadmium (Ni-Cd) batteries, it is possible for significant reversal of the lowest capacity cells to occur. The reversal is caused by the finite resistance of the common current-carrying leads in the resistive network that is generally used during short-down. A model is developed to evaluate the extent of such a reversal in any specific battery, and the model is verified by means of data from the short-down of a f-cell, 3.5-Ah battery. Computer simulations of short-down on a variety of battery configurations indicate the desirability of controlling capacity imbalances arising from cell configuration and battery management, limiting variability in the short-down resistors, minimizing lead resistances, and optimizing lead configurations.

Zimmerman, A. H.↗
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 NTRS1990

Analysis and design of a high power, digitally-controlled spacecraft power system

The progress to date on the analysis and design of a high power, digitally controlled spacecraft power system is described. Several battery discharger topologies were compared for use in the space platform application. Updated information has been provided on the battery voltage specification. Initially it was thought to be in the 30 to 40 V range. It is now specified to be 53 V to 84 V. This eliminated the tapped-boost and the current-fed auto-transformer converters from consideration. After consultations with NASA, it was decided to trade-off the following topologies: (1) boost converter; (2) multi-module, multi-phase boost converter; and (3) voltage-fed push-pull with auto-transformer. A non-linear design optimization software tool was employed to facilitate an objective comparison. Non-linear design optimization insures that the best design of each topology is compared. The results indicate that a four-module, boost converter with each module operating 90 degrees out of phase is the optimum converter for the space platform. Large-signal and small-signal models were generated for the shunt, charger, discharger, battery, and the mode controller. The models were first tested individually according to the space platform power system specifications supplied by NASA. The effect of battery voltage imbalance on parallel dischargers was investigated with respect to dc and small-signal responses. Similarly, the effects of paralleling dischargers and chargers were also investigated. A solar array and shunt model was included in these simulations. A model for the bus mode controller (power control unit) was also developed to interface the Orbital replacement Unit (ORU) model to the platform power system. Small signal models were used to generate the bus impedance plots in the various operating modes. The large signal models were integrated into a system model, and time domain simulations were performed to verify bus regulation during mode transitions. Some changes have subsequently been incorporated into the models. The changes include the use of a four module boost discharger, and a new model for the mode controller, which includes the effects of saturation. The new simulations for the boost discharger show the improvement in bus ripple that can be achieved by phase-shifted operation of each of the boost modules.

Lee, F. C.↗
NASA NTRS1991

Design of a battery charger for the NASA EOS space platform

A battery charger design for the NASA Earth Observing System (EOS) space platform has been developed and tested. The authors discuss the design of the battery charger power state and its current and voltage control loops. In addition to restoring energy to the batteries, this charger regulates the spacecraft bus voltage during the posteclipse transition period. The battery charger design and analysis were facilitated by use of the pulse-width-modulated (PWM) switch model and the new continuous-time model for current-mode control. Analyses of the battery charger small-signal behavior are compared to hardware measurements to verify modeling accuracy.

Sizemore, Tom↗
NASA NTRS2022

Lithium-ion Battery Strain Gauge Monitoring and Depth of Discharge Estimation

Lithium-ion battery diagnostics and prognostics rely on measurements of electrical impedance, capacity, and voltage to infer the internal state of the battery. Mechanical changes to the cell structure represent an additional measure of the battery’s state because these changes are related to the overall battery health. As lithium-ion batteries are charged and discharged, lithium ions are inserted or removed from the anode and cathode, a process called intercalation and de-intercalation. As lithium ions intercalate and de-intercalate, they can cause changes to the lattice of the electrode particles, resulting in volumetric changes. These volumetric changes cause mechanical stresses and strains on the lithium-ion battery electrodes, and subsequently, the whole cell’s thickness varies as it is charged and discharged. This paper presents a study on the use of surface-mounted strain gauges for in-situ measurement of structural changes to lithium-ion batteries, along with a characterization of the unit-to-unit differences in strain response. A neural network modeling structure is then used to predict the battery’s depth of discharge under dynamic discharge conditions.

Lithium-ion batteries, depth of discharge, strain ↗
NASA NTRSDate not supplied

Multidisciplinary Optimization of an Electric Quadrotor Urban Air Mobility Aircraft

Urban Air Mobility (UAM) vehicles have the potential to augment urban transportation systems, allowing passengers to skip the traffic below for a fee. This emerging market is opening up the design space for a new class of Urban Air Mobility (UAM) vehicles which could be powered by electric propulsion systems to be economical and environmentally friendly. However, development of these UAM concepts presents several additional challenges in the design process. First, these concept designs require including new disciplinary models for subsystems including the electric motors, cables, batteries and thermal management systems. Second, correctly designing and evaluating these various subsystems requires tight coupling between the discipline models to capture interactions. This paper presents the continued development of a multidisciplinary design optimization environment to aid in the development of these vehicle concepts. The multidisciplinary environment fully couples the various subsystem models allowing for the full vehicle to be designed and optimized simultaneously. In this research, the developed modeling approach is demonstrated in the analysis of a small, all-electric quadrotor UAM concept. Results from these studies show that numerous disciplines can be tightly coupled and producing improved overall vehicle designs.

Multidisciplinary Optimization↗
NASA NTRSDate not supplied

ICME for NASA Aerospace Applications: Batteries for Electric Aviation

NASA’s approach to computational materials modeling is detailed in the NASA Vision 2040 Roadmap for Multiscale Modeling and Simulation of Materials and Systems. This report is in the spirit of national initiatives such as the Material Genome Initiative (MGI), Integrated Computational Materials Engineering (ICME), and others. We utilize a combination of fundamental modeling, computational high-throughput screening, and data science methods, e.g., machine learning, are used to find innovative solutions to NASA or national technology challenges. Applications of interest are wide ranging from advanced alloys to batteries to coatings, among others. In this talk, we present three examples for recent work related to NASA applications. First, doping advanced sulfur battery cathodes with selenium boosts electrical conductivity important for electric aircraft applications. First principles calculations will be discussed that result in compositional design maps for these materials. Second, development of icephobic coatings is important to mitigate safety hazards associated with icing for aircraft. Molecular dynamics simulations are reported for ice-surface interfaces to understand adhesion mechanisms and help screen optimal ice-phobic coatings. Third, shape memory alloys have numerous applications as actuators, superelastic materials, etc. for aerospace. We report machine learning models that predict martensitic transition temperatures across a broad swath of compositional space.

John Lawson↗
NASA NTRS2017

Stochastic Modelling of Wireless Energy Transfer

This study investigates the efficiency of a new method of powering remote sensors by the means of wireless energy transfer. The increased use of sensors for data collection comes with the inherent cost of supplying power from sources such as power cables or batteries. Wireless energy transfer technology eliminates the need for power cables or periodic battery replacement. The time and cost of setting up or expanding a sensor network will be reduced while allowing sensors to be placed in areas where running power cables or battery replacement is not feasible. This paper models wireless channels for power and data separately. Smart scheduling for the data channel is proposed to avoid transmitting data on a noisy channel where the probability of data loss is high to improve power efficiency. Analytical models have been developed and verified using simulations.

Veilleux, Shaun↗
NASA NTRS2004

Battery Resistance Analysis of ISS Power System

The computer package, SPACE (Systems Power Analysis for Capability Evaluation) was created by the members of LT-9D to perform power analysis and modeling of the electrical power system on the International Space Station (ISS). Written in FORTRAN, SPACE comprises thousands of lines of code and has been used profficiently in analyzing missions to the ISS. LT-9D has also used its expertise recently to investigate the batteries onboard the Hubble telescope. During the summer of 2004, I worked with the members of LT-9D, under the care of Dave McKissock. Solar energy will power the ISS through eight solar arrays when the ISS is completed, although only two arrays are currently connected. During the majority of the periods of sunlight, the solar arrays provide enough energy for the ISS. However, rechargeable Nickel-Hydrogen batteries are used during eclipse periods or at other times when the solar arrays cannot be used (at docking for example, when the arrays are turned so that they will not be damaged by the Shuttle). Thirty-eight battery cells are connected in series, which make up an ORU (Orbital Replacement Unit). An ISS "battery" is composed of two ORUs. a great deal of time into finding the best way to represent them in SPACE. During my internship, I investigated the resistance of the ISS batteries. SPACE constructs plots of battery charge and discharge voltages vs. time using a constant current. To accommodate for a time-varying current, the voltages are adjusted using the formula, DeltaV = DeltaI * Cell Resistance. To enhance our model of the battery resistance, my research concentrated on several topics: investigating the resistance of a qualification unit battery (using data gathered by LORAL), comparing the resistance of the qualification unit to SPACE, looking at the internal resistance and wiring resistance, and examining the impact of possible recommended changes to SPACE. The ISS batteries have been found to be very difficult to model, and LT-9D has dedicated

Newstadt, Gregory E.↗
NASA NTRSDate not supplied

SIBatt-3D: In-Space/On-Surface 3D Printing of Sodium Ion Batteries from ISRU Materials

Constructed more than 20 years ago, the International Space Station’s primary power system originally used nickel-hydrogen batteries with a lifetime of 6.5 years, until NASA began the process of replacing them in 2016 with lithium-ion batteries with a lifetime of 10 years. The demanding and costly process was accomplished after four flights of the Japanese H-II Transfer Vehicle cargo spacecraft (with a cost of about $10,000 per pound of payload), and 13 different astronauts conducting 14 spacewalks. Besides utilization in the ISS, rechargeable batteries are present in many space applications: they are installed in exploration robots, life support systems and in portable communication devices, to mention some. In this context, this project is focused on the in-space manufacturing of shape-conformable batteries using in-situ resources, and aims to address the NASA’s gaps related to the development of next generation of energy storage devices (TX03), as well as in-space manufacturing and in-situ resource utilization (TX07). The proposed work also tackles the HEOMD’s objectives targeting the in-space additive manufacturing (AM) from Lunar/Martian materials (regolith as AM feedstock) to reinvigorate America’s Human Space Exploration Program (SPD-1). This project is in direct alignment with the STMD’s objectives to demonstrate in-space autonomous manufacturing and assembly of complete systems by 2030, and to enable humans to live and explore in space and on planetary surfaces by 2040 thanks to in-space habitation, infrastructure development and in-situ resource utilization (ST1 and ST5). Manufacturing of shape conformable batteries directly in-space and using in-situ resources would also contribute to reducing the payload weight and volume (TX12) for future missions, thus reducing risk for long term Mars missions where rapid resupply is logistically infeasible. Nowadays, commercial batteries consist of stacked two-dimensional (2D) sheets, which are only manufactured in restricted geometries (cylindrical and coin cell). Evolving from conventional 2D, complex 3D battery architectures have been proven to increase the electrochemical active surface area and ion diffusion path, leading to improved areal energy density and power performance. This tendency was illustrated in our recent in-depth modeling studies by simulating a classical Ragone plot exhibiting the energy-power relationship. Our team demonstrated through modeling that a complex gyroidal 3D printed battery architecture exhibits significantly improved power performances (>150% at the current density of 6C; full discharge in 10 minutes) in comparison to a traditional 3D printed planar geometry. Motivated by these results and as the fabrication of intricate 3D battery design is only possible experimentally thanks to the geometric freedom offered by additive manufacturing (AM), our team has already initiated leveraging thermoplastic material extrusion at the laboratory scale. While 3D printing of batteries is relatively recent (2013), it has witnessed a growing interest during the last recent years, as next-generation shape-conformable 3D batteries can be co-designed with the system. Consequently, dead-volume and mass brought from Earth are minimized, in addition to improved battery performance, in alignment with the aforementioned NASA’s objectives. Further, while this project is specifically dedicated to batteries, it lends itself towards the maturation of in-space manufacturing via 3D printing using in-situ resources, stated in HEOMD and STMD goals.

In-Space Manufacturing↗
NASA NTRS1986

Multikilowatt Bipolar Nickel/Hydrogen Battery

High energy densities appear feasible. Nickel/hydrogen battery utilizing bipolar construction in common pressure vessel, addressing needs for multikilowatt storage for low-Earth-orbit applications, designed and 10-cell prototype model tested. Modular-concept-design 35-kW battery projected energy densities of 20 to 24 Wh/b (160 to 190 kj/kg) and 700 to 900 Wh/ft3 (90 to 110 MJ/m3) and incorporated significant improvements over state-of-the-art storage systems.

Source record↗
NASA NTRS2000

Thermal Aspects of Lithium-Ion Cells

Objective of this investigation is to provide the necessary inputs for a thermal model of the Li-ion battery for the Mars 2001 Lander. Two alternate configurations of this battery are under development: a) prismatic parallel plate, and b) cylindrical spiral wound. Required thermal inputs for both consist of the following: a) heat generation rates, b) thermal mass, and c) thermal conductivity. Thermal mass and conductivity were computed on the basis of known properties and configuration of the cell components. The heat generation rates were taken as the product of current and difference between open circuit voltage (OCV) and operating voltages (CCV) at a given state-of charge (SOC). Herein, it was assumed that the enthalpy voltage was equal to the OCV. OCV vs SOC data were obtained experimentally and CCV vs SOC were taken from previously obtained discharge data.

Frank, H.↗
NASA NTRS2008

Power System Trade Studies for the Lunar Surface Access Module

A Lunar Lander Preparatory Study (LLPS) was undertaken for NASA's Lunar Lander Pre-Project in 2006 to explore a wide breadth of conceptual lunar lander designs. Civil servant teams from nearly every NASA center responded with dozens of innovative designs that addressed one or more specific lander technical challenges. Although none of the conceptual lander designs sought to solve every technical design issue, each added significantly to the technical database available to the Lunar Lander Project Office as it began operations in 2007. As part of the LLPS, a first order analysis was performed to identify candidate power systems for the ascent and descent stages of the Lunar Surface Access Module (LSAM). A power profile by mission phase was established based on LSAM subsystem power requirements. Using this power profile, battery and fuel cell systems were modeled to determine overall mass and volume. Fuel cell systems were chosen for both the descent and ascent stages due to their low mass. While fuel cells looked promising based on these initial results, several areas have been identified for further investigation in subsequent studies, including the identification and incorporation of peak power requirements into the analysis, refinement of the fuel cell models to improve fidelity and incorporate ongoing technology developments, and broadening the study to include solar power.

Kohout, Lisa, L.↗
NASA NTRS2013

Analytical Algorithms to Quantify the Uncertainty in Remaining Useful Life Prediction

This paper investigates the use of analytical algorithms to quantify the uncertainty in the remaining useful life (RUL) estimate of components used in aerospace applications. The prediction of RUL is affected by several sources of uncertainty and it is important to systematically quantify their combined effect by computing the uncertainty in the RUL prediction in order to aid risk assessment, risk mitigation, and decisionmaking. While sampling-based algorithms have been conventionally used for quantifying the uncertainty in RUL, analytical algorithms are computationally cheaper and sometimes, are better suited for online decision-making. While exact analytical algorithms are available only for certain special cases (for e.g., linear models with Gaussian variables), effective approximations can be made using the the first-order second moment method (FOSM), the first-order reliability method (FORM), and the inverse first-order reliability method (Inverse FORM). These methods can be used not only to calculate the entire probability distribution of RUL but also to obtain probability bounds on RUL. This paper explains these three methods in detail and illustrates them using the state-space model of a lithium-ion battery.

Sankararaman, Shankar↗