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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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The upcoming NASA's missions aimed at exploring our Planetary system require batteries that can operate at extreme operating temperatures, with high specific energy and energy densities. Conventional aerospace rechargeable battery systems are inadequate to meet the demands.
The effects of some materials variables on the irradiation performance of fuel pins for a lithium-cooled space power reactor design concept were examined. The variables studied were UN fuel density, fuel composition, and cladding alloy. All pins were irradiated at about 990 C in a thermal neutron environment to the design fuel burnup. An 85-percent dense UN fuel gave the best overall results in meeting the operational goals. The T-111 cladding on all specimens was embrittled, possibly by hydrogen in the case of the UN fuel and by uranium and oxygen in the case of the UO2 fuel. Tests with Cb-1Zr cladding indicate potential use of this cladding material. The UO2 fueled specimens met the operational goals of less than 1 percent cladding strain, but other factors make UO2 less attractive than low-density UN for the contemplated space power reactor use.
NASA is sponsoring research to develop advanced primary and secondary lithium cells. Lithium cells are conducive to aerospace use because they have high specific energy, volumetric energy density, and long storage capability. The primary cell research is centered on the Li/SOCl2 system. It is in the late development stage and all effort is being placed on resolving safety problems. The secondary cell, which is in the development stage, is the Li/TiS2 system. The objective is to produce a 100 wh/kg cell capable of operating in a geosynchronous orbit for 10 years. The development of improved conductivity polymeric films for electrochemical use is also being investigated. The lightweight batteries will have many applications in space and are already being prepared for the 1986 Galileo mission to Jupiter.
A simple one-dimensional model is used to describe the evolution of neutron density before and during nucleosynthesis in a high-entropy bubble left over from the cosmic quark-hadron phase transition. It is shown why cosmic nucleosynthesis in such a neutron-rich environment produces a surfeit of elements heavier than lithium. Analytical and numerical techniques are used to estimate the abundances of carbon, nitrogen, and heavier elements up to Ne-22. A high-density neutron-rich region produces enough primordial N-14 to be observed in stellar atmospheres. It shown that very heavy elements may be created in a cosmological r-process; the neutron exposure in the neutron-rich regions is large enough for the Ne-22 to trigger a catastrophic r-process runaway in which the quantity of heavy elements doubles in much less than an expansion time due to fission cycling. A primordial abundance of r-process elements is predicted to appear as an excess of rare earth elements in extremely metal-poor stars.
Currently, there are several models in the literature, such as kinetic models, microstructural models, and mass transport models that describe a Li-air battery's discharge behavior. Many of these models are calibrated and tested at low current densities and cannot be easily transferred to high current densities. Even at low current densities, there is no quantitative method for a researcher to choose a reaction kinetic model such as classical Butler-Volmer and its derivatives, and modified Marcus-Hush-Chidsey, a resistance model for lithium peroxide such as electron transport via tunneling or linear resistivity, a surface coverage model (lithium peroxide growth) such as partial coverage or full coverage, and mass transport model (discussed in Ref. [1]). Also, it is time-consuming to test different models at high current density (1C) due to a lack of well-tested models and well-calibrated model parameters. For this presentation, we will develop an analytical model, which acts as a surrogate model for a sophisticated finite element model to predict discharge time and discharge voltage. Next, we use an uncertainty quantifying technique called reduced-order stochastic optimization [2, 3] to determine the uncertainty in model parameters for rate kinetics, lithium peroxide resistivity, and parasitic resistance. Finally, a finite element simulation is performed to determine the error introduced by the surrogate model and its influence on the uncertainty in the model parameters.
This work proposes a fast Monte Carlo method to solve differential equations utilized in model-based prognostics. The methodology is derived from the theory of stochastic calculus, and the goal of such a method is to speed up the estimation of the probability density functions describing the independent variable evolution over time. In the prognostic scenarios presented in this paper, the stochastic differential equations describe variables directly or indirectly related to the degradation of a monitored system. The method allows the estimation of the probability density functions by solving the deterministic equation and approximating the stochastic integrals using samples of the model noise. By so doing, the prognostic problem is solved without the Monte Carlo simulation based on Euler's forward method, which is typically the most time consuming task of the prediction stage. Three different prognostic scenarios are presented as proof of concept: (i) life prediction of electrolytic capacitors, (ii) remaining time to discharge of Lithium-ion batteries, and (iii) prognostic of cracked structures under fatigue loading. The paper shows how the method produces probability density functions that are statistically indistinguishable from the distributions estimated with Euler's forward Monte Carlo simulation. However, the proposed solution is orders of magnitude faster when computing the time-to-failure distribution of the monitored system. The approach may enable complex real-time prognostics and health management solutions with limited computing power.
This work proposes a fast Monte Carlo method to solve differential equations utilized in model-based prognostics. The methodology is derived from the theory of stochastic calculus, and the goal of such a method is to speed up the estimation of the probability density functions describing the independent variable evolution over time. In the prognostic scenarios presented in this paper, the stochastic differential equations describe variables directly or indirectly related to the degradation of a monitored system. The method allows the estimation of the probability density functions by solving the deterministic equation and approximating the stochastic integrals using samples of the model noise. By so doing, the prognostic problem is solved without the Monte Carlo simulation based on Euler's forward method, which is typically the most time consuming task of the prediction stage. Three different prognostic scenarios are presented as proof of concept: (i) life prediction of electrolytic capacitors, (ii) remaining time to discharge of Lithium-ion batteries, and (iii) prognostic of cracked structures under fatigue loading. The paper shows how the method produces probability density functions that are statistically indistinguishable from the distributions estimated with Euler's forward Monte Carlo simulation. However, the proposed solution is orders of magnitude faster when computing the time-to-failure distribution of the monitored system. The approach may enable complex real-time prognostics and health management solutions with limited computing power.
An advanced commercial primary lithium cell (LiSoCl2) was evaluated in order to establish baseline data for improved lithium batteries for aerospace applications. The cell tested had nominal capacity of 6 Ah. Maximum energy density at low rates (less than C/30, where C is the cell capacity in amp-hrs and 30 corresponds to a 30 hr discharge time) was found to be near 300 Wh/kg. An equation which predicts the operating voltage of these cells as a function of current and state of charge is presented. Heat generation rates of these cells were determined as a function of current in a calorimeter. It was found that heat rates could be theoretically predicted with some degree of accuracy at currents less than 1 amp or the C/6 rate. No explosions were observed in the cells during the condition of overdischarge or reversal nor during high rate discharge. It was found, however, that the cells can vent when overdischarge currents are greater than C/30 and when discharge rates are greater than 1.5C.
The evolution of whistler mode turbulence and particle participation in a cold plasma release are studied experimentally as part of the Active Magnetospheric Particle Tracers Explorer (AMPTE) program. The investigation used a simple time dependent cold plasma density model, and an atypical ambient radiation belt was assumed. It is shown that a cold lithium injection in the AMPTE parameter range can give rise to whistler mode turbulence with significant gain to the wave amplitude in a single pass through a flux tube. Whistler mode growth results in the pitch angle diffusion of energetic electrons, which are in turn precipitated. The rate of power input into the ionosphere from these precipitating electrons is roughly estimated at 2 ergs per sq cm/s. It is found that this value of the precipitated power is large enough to continue producing a visible aurora until the injected plasma in the flux tube is lost or destroyed by magnetospheric convection or other processes.
Lithium-ion battery systems offer several advantages: intrinsically safe; long cycle life; environmentally friendly; high energy density; wide operating temperature range; good discharge rate capability; low self-discharge; and no memory effect.
NASA's Exploration Technology Development Program funded the Energy Storage Project to develop battery and fuel cell technology to meet the expected energy storage needs of the Constellation Program for human exploration. Technology needs were determined by architecture studies and risk assessments conducted by the Constellation Program, focused on a mission for a long-duration lunar outpost. Critical energy storage needs were identified as batteries for EVA suits, surface mobility systems, and a lander ascent stage; fuel cells for the lander and mobility systems; and a regenerative fuel cell for surface power. To address these needs, the Energy Storage Project developed advanced lithium-ion battery technology, targeting cell-level safety and very high specific energy and energy density. Key accomplishments include the development of silicon composite anodes, lithiated-mixed-metal-oxide cathodes, low-flammability electrolytes, and cell-incorporated safety devices that promise to substantially improve battery performance while providing a high level of safety. The project also developed "non-flow-through" proton-exchange-membrane fuel cell stacks. The primary advantage of this technology set is the reduction of ancillary parts in the balance-of-plant--fewer pumps, separators and related components should result in fewer failure modes and hence a higher probability of achieving very reliable operation, and reduced parasitic power losses enable smaller reactant tanks and therefore systems with lower mass and volume. Key accomplishments include the fabrication and testing of several robust, small-scale nonflow-through fuel cell stacks that have demonstrated proof-of-concept. This report summarizes the project s goals, objectives, technical accomplishments, and risk assessments. A bibliography spanning the life of the project is also included.
The National Aeronautics and Space Administration is developing battery and fuel cell technology to meet the expected energy storage needs of human exploration systems. Improving battery performance and safety for human missions enhances a number of exploration systems, including un-tethered extravehicular activity suits and transportation systems including landers and rovers. Similarly, improved fuel cell and electrolyzer systems can reduce mass and increase the reliability of electrical power, oxygen, and water generation for crewed vehicles, depots and outposts. To achieve this, NASA is developing non-flow-through proton-exchange-membrane fuel cell stacks, and electrolyzers coupled with low permeability membranes for high pressure operation. The primary advantage of this technology set is the reduction of ancillary parts in the balance-of-plant fewer pumps, separators and related components should result in fewer failure modes and hence a higher probability of achieving very reliable operation, and reduced parasitic power losses enable smaller reactant tanks and therefore systems with lower mass and volume. Key accomplishments over the past year include the fabrication and testing of several robust, small-scale non-flow-through fuel cell stacks that have demonstrated proof-of-concept. NASA is also developing advanced lithium-ion battery cells, targeting cell-level safety and very high specific energy and energy density. Key accomplishments include the development of silicon composite anodes, lithiatedmixed- metal-oxide cathodes, low-flammability electrolytes, and cell-incorporated safety devices that promise to substantially improve battery performance while providing a high level of safety.
Conductivity of lithium perchlorate and aluminum chloride solutions, solubility of lithium fluoride in nitromethane and butyl formate, lithium metal stability, and cell performance
Crystallization of a Li2O.2SiO2 (LS2) glass subjected to a uniform hydrostatic pressure of 4.5 GPa and 6 GPa was investigated up to a temperature of 750 C. The density of the compressed glass is about 2% greater at 4.5 GPa than at 1 atm and, depending upon the processing temperature, up to 10% greater at 6 GPa. Crystal growth rates investigated as a function of temperature and pressure show that lithium disilicate crystal growth is an order of magnitude slower at 4.5 GPa than 1 atm resulting in a shift of +45 C (plus or minus 10 C) in the growth rate curve at high pressure compared to 1 atm condition. At 6 GPa lithium disilicate crystallization is suppressed entirely, while a new high pressure lithium metasilicate crystallizes at temperatures 95 C (plus or minus 10 C) higher than those reported for lithium disilicate crystallization at 1 atm. The decrease in crystal growth rate with increasing pressure for lithium disilicate glass up to 750 C is related to an increase in viscosity with pressure associated with fundamental changes in glass structure accommodating densification.
Lithium anodes, inorganic and organic cathodes, vacuum-distilled solvents, and methods for sintering cupric fluoride on lightweight metal substrates - development of high energy battery
Li-Air batteries are a unique fit for electric aircraft due to their high theoretical energy densities and their potential to leverage on-board oxygen systems. Electrolytes are the limiting factor for advancing this technology. We will investigate novel "electrolyte engineering" concepts to enable Li-Air batteries with high practical energy densities, rechargeability and safety. New stable electrolytes will be designed and fabricated for Li-Air batteries and tested in an electric flight. An unprecedented "Dream Team" of experts from NASA, DOE, academia and industry will tackle this problem.
A rechargeable lithium molybdenum disulfide battery which has a number of superior performance characteristics which includes a high energy density, a high power density, and a long charge retention time was developed. The first cell sizes developed included a C size cell and an AA size cell. Over the last two years, a project to demonstrate the feasibility of the scale up to this technology to a BC size cell with 65 Ah capacity was undertaken. The objective was to develop, build, and test a .6 kWh storage battery consisting of 6 BC cells in series.
Commercialization of lithium-air batteries faces many challenges, such as electrolyte decomposition, short cycle life, low energy and power density, etc. However, commercialization of Li-O2 batteries for aeronautics is much more challenging due to additional safety constraints on cyclability and performance (high specific power and specific energy). For this presentation, we will discuss inter-related aspects of physics-based modeling of a pack: cell and battery model calibration. In addition, we will evaluate and present optimal battery designs for high discharge current density, high discharge time, and low battery mass using simulation-based optimization.The Finite Element Model (FEM) used to simulate a Li-O2 cell is based on the work of Bevara [1]. The different aspects of the model are based on: porous electrode theory and concentrated electrolyte theory; quantum tunneling model for the resistance of conformal layer of discharge product (Li2O2) [1]; Butler-Volmer kinetics for electrochemical reaction; Fick's diffusion for oxygen transport; and an oxygen dissolution model is applied at the air/electrolyte interface [2]. The electrolyte properties such as ion conductivity, ion diffusion, oxygen diffusion, and mass density of the electrolyte were taken from Molecular Dynamics (MD) simulations [3]; while the other model parameters, which includes mass of cell components, were calibrated to match experiments at high discharge current densities. The cell mass includes the anode, cathode, separator, electrolyte, and other components (such as current collector). This calibrated model is used to perform parametric studies on cathode thickness, porosity, tortuosity, carbon particle size, electrolyte transport and material properties, partial pressure of oxygen, discharge time, and discharge current density to study optimal designs for high specific power and energy. References:1. Bevara, V. & Andrei, P. (2014), J. Electrochem. Soc. 161 (14), A2068-A2079.2.Mehta, M. & Andrei, P. (2015), J. Power Sources. 286, 299-308.3.Liyana-Arachchi, T.; Haskins, J.; Burke, C.; Diederichsen, K.; McCloskey, B.; & Lawson, J. (2018), J. Phys. Chem. B. 122 (36), 8548 - 8559.4.Choi, W.; Kikumoto, H.; Choudhary, R. & Ooka, R. (2018), Applied Energy, 209, 306-321.