SEARCH · Search NASA

Results for “distributed temperature sensor”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 685 records · Page 38

All sources NASA NTRS DOE OSTI

NASA NTRS2024

San Joaquin Valley Health & Air Quality II: Assessing Urban Heat Island Distribution and its Intersections with Air Quality to Understand Converging Vulnerabilities

The city of Stockton, California, located within the San Joaquin Valley (SJV), is a major hub for agricultural production and has endured the continuous threat to community health from nitrogen dioxide (NO 2 ) and increasing temperatures. The convergence of these issues occurs within historically segregated communities that are disproportionately facing health risks related to heat and air quality. Little Manila Rising (LMR), a social and environmental justice (EJ) advocacy non-profit, partnered with NASA DEVELOP for a second term project to evaluate county wide urban heat islands, sociodemographic vulnerability, landcover classification, and the convergence of these variables. We utilized Landsat 8 Thermal Infrared Sensor (TIRS) and Operational Land Imager (OLI) data to produce a land surface temperature (LST) and Normalized Difference Vegetation Index map. They added Centers for Disease Control (CDC) socioeconomic data from 2020 to identify which communities in Stockton were more susceptible to these environmental factors. Additionally, we used NAIP imagery to create a landcover map differentiating developed infrastructure from tree canopy cover. We discovered that south Stockton, where LMR resides, had the worst convergence of heat, air pollution, low canopy coverage and sociodemographic vulnerability compared to northern and rural parts of the city. This was further substantiated by statistical analysis showing a strong positive relationship between areas of high LST and low vegetation. The results provided LMR with compelling evidence to use in their EJ advocacy, and in their efforts to inform state officials of the discriminatory issues they face.

Urban Heat Islands↗

NASA NTRS1998

A Satellite Infrared Technique for Diurnal Rainfall Variability Studies

Reliable information on the distribution of precipitation at high temporal resolution (<l hour) is essential for understanding the characteristics of convection in a region. Cloud-top infrared (IR) brightness temperatures from geostationary platforms have a weak physical connection to precipitation, however, their high sampling frequency makes them attractive in studying the temporal evolution of cloudiness and convection. On the other hand, microwave-based (MW) observations from lower sampling-frequency polar-orbiting platforms can provide a better physical connection to precipitating hydrometeors. A recent invention in rainfall estimation from a combination of these two sensors involves adjustment of IR estimates using co-existing MW-based precipitation data on a monthly basis. These techniques use the MW data to remove systematic errors in IR rain estimates, while retaining the high sampling frequency of IR observations (approximately every 15-30 minutes). Perhaps of even greater importance to climate and hydrometeorological applications is the separation of mesoscale convective systems into a portion of rain associated with deep convection (hereafter called convective precipitation), and to precipitation falling from more widespread anvil clouds. This current work focuses on estimation of tropical convective and stratiform rainfall. We attempt to answer fundamental questions, such as : is estimation of convective and stratiform precipitation from IR feasible? If so, how accurate can this be? What is the scale dependence of the IR algorithm's performance? To address these questions, quantitative comparisons are performed between coincident IR- and MW-based instantaneous rainfall estimates at the MW 85 Ghz resolution (-12.5 km). Our data set spans a three-month period (January to March, 1996) of MW and IR observations over northern South America (15N-15S and 35W-80W), which includes the Amazon river basin.

Anagnostou, Emmanouil↗

NASA NTRS2007

Radiation Dry Bias of the Vaisala RS92 Humidity Sensor

The comparison of simultaneous humidity measurements by the Vaisala RS92 radiosonde and by the Cryogenic Frostpoint Hygrometer (CFH) launched at Alajuela, Cosla Rica, during July 2005 reveals a large solar radiation dry bias of the Vaisala RS92 humidity sensor and a minor temperature-dependent calibration error. For soundings launched at solar zenith angles between 10" and 30 , the average dry bias is on the order of 9% at the surface and increases to 50% at 15 km. A simple pressure- and temperature-dependent correction based on the comparison with the CFH can reduce this error to less than 7% at all altitudes up to 15.2 km, which is 700 m below the tropical tropopause. The correction does not depend on relative humidity, but is able to reproduce the relative humidity distribution observed by the CFH.

Vomel, H.↗

DOE OSTI2024

Boundary-Aware Adversarial Learning Domain Adaption and Active Learning for Cross-Sensor Building Extraction

The use of convolutional neural networks (CNNs) for building extraction from remote sensing images has been widely studied and many public datasets have been made available for accelerating development of these CNN models. Yet adapting pretrained models at scale in real-world scenarios remains a challenging task. The main barrier is that certain new labels are still needed to compensate for domain shifting between the labeled data and new images that potentially cover new geographic locations or that are from a different sensor. In this article, we propose to add informatively labeled samples from a new image pool under the paradigm of active learning. To select the most useful samples based on model uncertainty, we first tackle the problem of uncalibrated uncertainty estimation due to distribution shifting by adapting feature extractors with boundary-based adversarial learning. Calibrated uncertainty is used as the query criterion in the active learning process, where the most uncertain samples are selected for annotation and included for model retraining. The proposed workflow was tested with three data pairs in which each workflow represents a scenario often encountered in real-world applications, including adapting pretrained models to new images collected with different sensors or to new geographic areas where appearances and types of buildings are very different. Compared to several baselines, including random sampling, temperature scaling (a well-known uncertainty calibration technique), different query strategies, and active domain adaptation methods, the proposed workflow shows that strategically querying a smaller set of samples for labeling achieves comparable or better building extraction performance. The proposed method reduces the number of labeled samples required to achieve sufficient model accuracy, thus significantly reducing hundreds of person-hours for labeled data creation. In addition, we include a few considerations when deploying this workflow in a GPU cluster that can be easily adapted to achieve operational building extraction model retraining.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1974

Preliminary results of fisheries investigation associated with Skylab-3

The purpose of the 15-month investigation now in the analysis phase is to establish the feasibility of utilizing remotely sensed data acquired from aircraft and satellite platforms to provide information concerning the distribution and abundance of oceanic gamefish. Data from the test area, jointly acquired by private and professional fishermen and NASA and NOAA/NMFS elements, in the northeastern Gulf of Mexico has made possible the identification of significant environmental parameters for white marlin. Predictive models based on catch data and surface truth information have been developed and have demonstrated potential for reducing search significantly by identifying areas which have a high probability of being productive. Three of the parameters utilized by the model, chlorophyll-a, sea surface temperature and turbidity have been inferred from aircraft sensor data.

Savastano, K.↗

NASA NTRS2007

Multi-Sensor Data from A-Train Instruments Brought Together for Atmospheric Research

The A-Train is comprised of a series of instruments, developed independently, that measure highly related atmospheric components along the same flight path. In order to intercompare data from this multitude of sensors, researchers must access, subset, visualize, analyze and correlate distributed atmosphere measurements from the various A-Train instruments. The A-Train Data Depot (ATDD) has been operational for over a year, successfully performing the aforementioned functions on behalf of researchers, thus providing co-registered data from the Cloudsat, CALIOP, AIRS, and MODIS instruments for further intercomparisons. Of late, significant data from OM1 and POLDER are now included in the 'depot'. By specifying the desired spatial and temporal range, the researcher can subset, visualize, co-register, and access multi-sensor A-Train data related to: Cloud, aerosol, atmospheric temperature, and water vapor parameters (vertical profile visualizations); Cloud Pressure, cloud top temperature, water vapor, cloud optical thickness, and aerosol products (horizontal strips subsetted +/- 100km from the profile visualizations), and; Cloud pressure parameters (2-D line plots overlayed on the vertical profiles). All data is plotted using the GIOVANNI data exploration tool. A new feature of GIOVANNI is its ability to have collocated and subsetted data sets as well as PNG image files downloaded to the researcher's computing facility. By providing a convenient way to visualize and acquire multi-sensor data, ATDD affords users more time and effort to further their research.

Smith, Peter M.↗

NASA NTRS2007

Programmable Thermostats for MPLM Shell Heater Control ULF1: Thermal Performances - 1

The Multi-Purpose Logistics Module (MPLM) is the primary carrier for "pressurized" logistics to and from the International Space Station (ISS). The MPLM is transported in the payload bay of the Space Shuttle and is docked to the ISS for unloading, and reloading, of contents within the ISS shirt sleeve environment. Foil heaters, controlled originally with bi-metallic thermostats, are distributed across the outside of the MPLM structure and are utilized to provide energy to the structure to avoid exposure to cold temperatures and prevent condensation. The existing bi-metallic, fixed temperature set point thermostats have been replaced with Programmable Thermostats Modules (PTMs) in the Passive Thermal Control Subsystem (PTCS) 28Vdc shell heater circuits. The goal of using the PTM thermostat is to improve operational efficiency of the MPLM on-orbit shell heaters by providing better shell temperature control via feedback control capability. Each heater circuit contains a programmable thermostat connected to an external temperature sensor, a Resistive Temperature Device (RTD), which is used to provide continuous temperature monitoring capability. Each thermostat has programmable temperature set points and control spans. The data acquisition system uses a standard RS-485 serial interface communications cable to provide digital control capability. The PTM system was designed by MSFC, relying upon ALTEC support for their integration within the MPLM system design, while KSC performed the installation and ground checkout testing of the thermostat and RS-485 communication cable on the MPLM FM1 flight module. The PTMs were used for the first time during the STS-121/ULF1.1 mission. This paper will describe the design, development and verification of the PTM system, as well as the PTM flight performance and comparisons with SINDA thermal model predictions.

Glasgow, Shaun↗

NASA NTRS2018

Effects of Normal Metal Features on Superconducting Transition-Edge Sensors

In transition-edge sensors (TESs), the addition of normal metal stripes on top of the superconducting bilayer, perpendicular to the current direction, is known to globally alter the sensitivity of the resistance R to changes in temperature T and current I. Here, we describe measurements of the dependence of the TES current on magnetic field B, bath temperature and voltage bias in devices with various numbers of stripes. We show that the normal metal features have a profound effect on the appearance of localized regions of very large (T/R) dR/dT. We associate this with changes in the current distribution and corresponding changes in the oscillatory pattern of I (B). 140 μm TESs with no stripes are found to have a relatively smooth resistive transition and sufficiently low noise that the measured energy resolution is 1.6 eV for X-rays of 1.5 keV. The predicted energy resolution at 6 keV is better than 2 eV, once the heat capacity is optimized for these higher energies..

Wakeham, N. A.↗

DOE OSTI2019

Embedded metallized optical fibers for high temperature applications

Embedding fiber optics in metal components could enable new capabilities such as active monitoring of spatially distributed strain. Ultrasonic additive manufacturing is a suitable technique for embedding fiber optics because it allows fibers to be embedded in metals without melting and without the use of epoxy. However, for harsh environments that could have high temperatures or high radiation doses, traditional polymer-coated fibers cannot survive for extended periods of time. This work demonstrates successful embedding of commercially available copper-, nickel-, and aluminum-coated fibers into aluminum without any observable damage to the fiber. Copper-coated fibers embedded in copper show adequate light transmission, although residual strain could not be resolved. With further processing improvements, fibers embedded in copper or other high-temperature materials could enable even higher temperature operation. Optical transmission and spatially distributed strain were measured in the fibers embedded in aluminum. Measurements were taken after embedding and during heating to temperatures greater than 500 °C. Within the embedded region, both the copper- and aluminum-coated fibers showed strain that matched the expected strain in the surrounding aluminum matrix during heating. This suggests a strong interfacial bond strength that exceeds the maximum estimated fiber strain of 1.2% (871 MPa tensile stress). Furthermore this demonstration of embedded fibers that can survive high temperatures and remain bonded to the metal matrix is the first step toward embedded fiber optic sensors for harsh environment applications.

36 MATERIALS SCIENCE↗

NASA NTRS2019

Design of Experiment for the Measurement of Aerosol Droplet Size Distribution of Temperature-Controlled Thermally Atomized Printed Electronic Inks

In-Space Manufacturing (ISM) centers around NASA’s growing need and ability to produce space technologies on demand in space. As the future of long term presence in space and deep space exploration approach, fundamental questions of our dependence on earth resupply to Low Earth Orbit (LEO) remain unanswered. ISM is leading various effort to evaluate the feasibility of producing essential spares and redundant parts on demand to enable a sustainable space-based supply chain model for part resupply. Among the parts and systems being considered, Avionics form the neural network of modern day aircraft and space vehicles providing a wealth of information ranging from Guidance, Navigation, and Control (GN&C) systems to on board Environmental Control and Life Support (ECLS) systems. Recent advances in the use of Aerosol Jet Technology to print Avionics components ranging from electrical traces on a circuit board to complex transistors and sensors raise the possibility of using such technology to reproduce or recreate electronic parts on demand with the help of custom electronics 3D printers. The challenge herein lies within the ability of such printers to generate and deposit an aerosol of electronic material utilizing processes independent of or enhanced by gravity to ensure controllably identical or improved behavior of the aerosol in an International Space Station (ISS) laboratory and on the ground. The behavior as well as the hazards and properties associated with such aerosols in a microgravity environment must be understood well in order to merit a feasible approach to utilizing them for manufacturing in space. In this report, we outline the experimental setup of a modified conventional vaping device to be used as the ideal gravity independent thermal atomization mechanism to generate aerosol. Our objective is to identify the ideal mass, density, and volume of our aerosolized droplets of ink to conclude that there exist a threshold of aerosolized ink droplet sizes that are indeed independent of the effects of gravity and remain stable after atomization. We use a Malvern Spraytec® Spray Particle Size Analyzer to perform real-time laser diffraction measurement of our ink droplets during atomization. The droplet size between conductive ink, dielectric ink and vegetable glycerin have been measured and contrasted. Furthermore, the mechanism of thermal atomization versus traditional pneumatic and ultrasonic atomization for operation in microgravity have been explored.

Wu, Chih-Hao↗

DOE OSTI2023

AOI-2, A Novel Access Control Blockchain Paradigm for Cybersecure Sensor Infrastructure in Fossil Power Generation Systems

Fossil power generation systems are increasingly vulnerable to attack from both cybercriminals as well as internal threats. These vulnerabilities demand that emerging technologies such as blockchains be utilized to secure the data involved in the information flows within the Supervisory Control and Data Acquisition (SCADA) systems of the fossil power generation plants. The publicly accessible blockchain protocols, although secure, are visible to everyone. Even private blockchains currently are unable to support different levels of access to different participants, which is a critical requirement for the existing SCADA systems running the power plants. In light of the above, novel blockchain protocols that are specifically adapted to fossil power generation environments need to be developed in order to achieve the goal of cybersecure sensor networks. In this work, we address this question by creating a novel blockchain technology, namely smart private ledger, for cybersecure communication within the fossil power generation systems. A lab-scale sensor network consisting of strain and temperature sensors is constructed to develop the ledger. The technology has hierarchical access control which is compatible with the existing SCADA systems in fossil power plants. The sensor data is used with cryptographic digital signatures and secret sharing protocols within the nodes of the blockchain technology. The research results will lead to cybersecurity for machine-to-machine interactions, infrastructure for secure data logging for sensors, decentralized data storage, and second-layer technologies for high volume machine-to-machine interactions in the power plants. The work aims to largely address the concerns for the security of distributed sensor networks in such systems that can be compromised by insider threats and by cybercriminals. The research has led to the training of the next generation of engineers and scientists in the important areas of sensor engineering and blockchain technology.

01 COAL, LIGNITE, AND PEAT↗

NASA NTRS1998

Validation of the Version 1 NOAA/NASA Pathfinder Sea Surface Temperature Data Set

A high-resolution, global satellite-derived sea surface temperature (SST) data set called Pathfinder, from the Advanced Very High Resolution Radiometer (AVHRR) aboard the NOAA Polar Orbiters, is available from the Jet Propulsion Laboratory Physical Oceanography Distributed Active Archive Center (JPL PO.DAAC). Suitable for research as well as education, the Pathfinder SST data set is a result of a collaboration between the National Oceanographic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA) and investigators at several universities. NOAA and NASA are the sponsors of the Pathfinder Program, which takes advantage of currently archived Earth science data from satellites. Where necessary, satellite sensors have been intercalibrated, algorithms improved and processing procedures revised, in order to produce long time-series, global measurements of ocean, land and atmospheric properties necessary for climate research. Many Pathfinder data sets are available to researchers now, nearly a decade before the first launch of NASA's Earth Observing System (EOS). The lessons learned from the Pathfinder programs will facilitate the processing and management of terabytes of data from EOS. The Oceans component of Pathfinder has undertaken to reprocess all Global Area Coverage (GAC) data acquired by the 5-channel AVHRRs since 1981. The resultant data products are consistent and stably calibrated [Rao, 1993a, Rao, 1993b, Brown et al., 1993], Earth-gridded SST fields at a variety of spatial and temporal resolutions.

Smith, Elizabeth A.↗

NASA NTRS2008

Logic Gates Made of N-Channel JFETs and Epitaxial Resistors

Prototype logic gates made of n-channel junction field-effect transistors (JFETs) and epitaxial resistors have been demonstrated, with a view toward eventual implementation of digital logic devices and systems in silicon carbide (SiC) integrated circuits (ICs). This development is intended to exploit the inherent ability of SiC electronic devices to function at temperatures from 300 to somewhat above 500 C and withstand large doses of ionizing radiation. SiC-based digital logic devices and systems could enable operation of sensors and robots in nuclear reactors, in jet engines, near hydrothermal vents, and in other environments that are so hot or radioactive as to cause conventional silicon electronic devices to fail. At present, current needs for digital processing at high temperatures exceed SiC integrated circuit production capabilities, which do not allow for highly integrated circuits. Only single to small number component production of depletion mode n-channel JFETs and epitaxial resistors on a single substrate is possible. As a consequence, the fine matching of components is impossible, resulting in rather large direct-current parameter distributions within a group of transistors typically spanning multiples of 5 to 10. Add to this the lack of p-channel devices to complement the n-channel FETs, the lack of precise dropping diodes, and the lack of enhancement mode devices at these elevated temperatures and the use of conventional direct coupled and buffered direct coupled logic gate design techniques is impossible. The presented logic gate design is tolerant of device parameter distributions and is not hampered by the lack of complementary devices or dropping diodes. In addition to n-channel JFETs, these gates include level-shifting and load resistors (see figure). Instead of relying on precise matching of parameters among individual JFETS, these designs rely on choosing the values of these resistors and of supply potentials so as to make the circuits perform the desired functions throughout the ranges over which the parameters of the JFETs are distributed. The supply rails V(sub dd) and V(sub ss) and the resistors R are chosen as functions of the distribution of direct-current operating parameters of the group of transistors used.

Krasowski, Michael J.↗

NASA NTRS2014

A Revised Calibration Function and Results for the Phoenix Mission TECP Relative Humidity Sensor

The original calibration function of the R(sub H) sensor on the Phoenix Thermal and Electrical Conductivity Sensor (TECP) has been revised in order to extend the range of the valid calibration, and to improve accuracy. The original function returned non-physical R(sub H) values at the lowest temperatures. To resolve this, and because the original calibration was performed against a pair of hygrometers that measured frost point (T(sub f)), the revised calibration equation is also cast in terms of frost point. Because of the complexity of maintaining very low temperatures and high R(sub H) in the laboratory, no calibration data exists at T is greater than 203K. However, sensor response during the mission was smooth and continuous down to 181 K. Therefore we have opted to include flight data in the calibration data set; selection was limited to data acquired during periods when the atmosphere is known to have been saturated. T(sub f) remained below 210 K throughout the mission(P is greater than 0.75 Pa). R(sub H), conversely, ranged from 1 to well under 0.01 diurnally, due to approximately 50 K temperature variations. To first order, both vapor pressure and its variance are greater during daylight hours. Variance in overnight humidity is almost entirely explained by temperature, while atmospheric turbulence contributes substantial variance to daytime humidity. Likewise, data gathered with the TECP aloft reflect higher H2O abundances than at the surface, as well as greater variance. There is evidence for saturation of the atmosphere overnight throughout much of the mission. In virtually every overnight observation, once the atmosphere cooled to T(sub f), water vapor begins to decrease, and tracks air temperature. There is no evidence for substantial decreases in water vapor prior to saturation, as expected for adsorptive exchange. Likewise, there is no evidence of local control of vapor by phases such as perchlorate hydrates hydrated minerals. The daytime average H2O pressure does not change substantially over the course of the mission, although the H2O column abundance varies by a factor of 2. Column abundances calculated from TECP data are lower than orbital measurements if one assumes that H2O is uniformly mixed through a single scale height. These results argue that the vertical distribution of H2O begins to change well in advance of surface concentrations as northern autumn approaches.

Phoenix Thermal and Electrical Conductivity Sensor↗

DOE OSTI2025

Monte Carlo Dropout Uncertainty Quantification of Long Short-Term Memory Autoencoder Anomaly Detection in a Liquid Sodium Cold Trap

Advanced high-temperature fluid reactors, such as sodium-cooled fast reactors (SFRs) and molten salt–cooled reactors (MSCRs), require coolant purification systems to prevent fluid contamination and local freezing that can lead to plugging. Liquid sodium purification can be achieved with a cold trap, where the sodium temperature is reduced to a near-freezing point to precipitate out impurities. Automation of monitoring of the cold trap performance with machine learning algorithms can aid in early detection of incipient anomalies. An efficient approach to loss-of-coolant–type anomaly detection in a cold trap monitored with more than two dozen thermal-hydraulic sensors consists of a long short-term memory (LSTM) autoencoder. This work develops the uncertainty quantification of the LSTM autoencoder performance for cold trap anomaly detection using the Monte Carlo (MC) dropout method. The MC dropout methodology creates a distribution of sister distributions that all slightly differ from each other because of random neurons being turned off for testing. The variances of the sister network distributions are used to make an uncertainty interval. Our analysis shows that the uncertainty in the autoencoder performance is largest near the peak of the anomaly signal. Using the MC dropout method, we investigate the uncertainty in the anomaly detection with missing sensor inputs. This capability allows the reactor operator to evaluate resilience of the anomaly detection system and to make informed decisions about continuity of operation in the event of sensor failure.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1997

Calibration of the QCM/SAW Cascade Impactor for Measurement of Ozone in the Stratosphere

The Quartz Crystal Microbalance Surface Acoustic Wave (QCM/SAW) cascade impactor collects size-fractionated distributions of aerosols on a series of 10 MHz quartz crystals and employs SAW devices coated with chemical sensors for gas detection. Presently, we are calibrating the ER-2 certified QCM/SAW cascade impactor in the laboratory for the detection of ozone. Experiments have been performed to characterize the QCM and SAW mass loading, saturation limits, mass frequency relationships, and sensitivity. We are also characterizing sampling efficiency by measuring the loss of ozone on different materials. There are parallel experiments underway to measure the variations in the sensitivity and response of the QCM/SAW crystals as a function of temperature and pressure. Results of the work to date will be shown.

Wright, Cassandra K.↗

DOE OSTI2013

ARPA-E Program: Advanced Management Protection of Energy Storage Devices (AMPED) - Fifth Quarterly Project Report - FY14 Q1

Technology has been developed that enables monitoring of individual cells in high - capacity lithium-ion battery packs, with a distributed array of wireless Bluetooth 4.0 tags and sensors, and without proliferation of extensive wiring harnesses. Given the safety challenges facing lithium-ion batteries in electric vehicle, civilian aviation and defense applications, these wireless sensors may be particularly important to these emerging markets. These wireless sensors will enhance the performance, reliability and safety of such energy storage systems. Specific accomplishments to date include, but are not limited to: (1) the development of wireless tags using Bluetooth 4.0 standard to monitor a large array of sensors in battery pack; (2) sensor suites enabling the simultaneous monitoring of cell voltage, cell current, cell temperature, and package strain, indicative of swelling and increased internal pressure, (3) small receivers compatible with USB ports on portable computers; (4) software drivers and logging software; (5) a 7S2P battery simulator, enabling the safe development of wireless BMS hardware in the laboratory; (6) demonstrated data transmission out of metal enclosures, including battery box, with small variable aperture opening; (7) test data demonstrating the accurate and reliable operation of sensors, with transmission of terminal voltage, cell temperature and package strain at distances up to 110 feet; (8) quantification of the data transmission error as a function of distance, in both indoor and outdoor operation; (9) electromagnetic interference testing during operation with live, high -capacity battery management system at Yardney Technical Products; (10) demonstrat ed operation with live high-capacity lithium-ion battery pack during charge-discharge cycling; (11) development of special polymer-gel lithium-ion batteries with embedded temperature sensors, capable of measuring the core temperature of individual of the cells during charge-discharge cycling at various temperatures, thereby enabling earlier warning of thermal runaway than possible with external sensors. Ultimately, the team plans to extend this work to include: (12) flexible wireless controllers, also using Bluetooth 4.0 standard, essential for balancing large-scale battery packs. LLNL received $925K for this project, and has $191K remaining after accomplishing these objectives.

25 ENERGY STORAGE↗

DOE OSTI2013

ARPA-E Program: Advanced Management Protection of Energy Storage Devices (AMPED) - Monthly Report - November 2013

25 ENERGY STORAGE↗