Results for “battery control” — Page 42

DOE OSTI2024

Nanoporous Carbon Coatings Direct Li Electrodeposition Morphology and Performance in Li Metal Anode Batteries

Li metal anodes could significantly improve battery energy density. However, Li generally electrodeposits in poorly controlled morphology, leading to safety and performance problems. One factor that controls Li anode performance and electrodeposition morphology is the nature of the electrolyte–current collector interface. Herein, we modify the Cu current collector interface by depositing precisely controlled nanoporous carbon (NPC) coatings using pulsed laser deposition to develop an understanding of how NPC coating density and thickness impact Li electrodeposition. We find that NPC density and thickness guide Li morphological evolution differently and dictate whether Li deposits at the NPC-Cu or NPC-electrolyte interface. NPC coatings generally lower overpotential for Li electrodeposition, though thicker NPC coatings limit kinetics when cycling at a high rate. Lower-density NPC enables the highest Coulombic efficiency (CE) during calendar aging tests, and higher-density NPC enables the highest CE during cycling tests.

25 ENERGY STORAGE↗

DOE OSTI2026

De-Risking Field Deployment of Storage Assets Using Hardware-in-the-Loop Experiments [Slides]

This presentation provides an overview of de-risking the field deployment of controller and power hardware technologies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Securing Digital Energy Infrastructure: Procurement, Contracting, and Supply Chain Risk Management Guidance

Recognizing the scale of this industry challenge, the United States (U.S.) Department of Energy (DOE) Grid Deployment Office (GDO) and Cybersecurity Energy Security & Emergency Response office have launched a multi-year BESS supply chain security initiative to identify consequence-driven approaches to addressing BESS supply chain security and provide resources to support prioritization of supply chain security efforts associated with the procurement of BESS equipment and services. This guide is one element of the supporting resources to be provided and sets forth a framework and guidance for procurement bidding, selection, risk analysis, and agreements stakeholders can implement to mitigate cybersecurity risks across the entirety of battery system component ecosystem, including the interconnected software and hardware required for control and monitoring BESSs.

25 ENERGY STORAGE↗

NASA NTRSDate not supplied

Systems Health Management and Decision Making

In order 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. 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. In order 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 predict the future state of the system, it is also required to possess knowledge of the current and future operations of the vehicle. Discuss research approach to develop a system level health monitoring safety indicator which runs estimation and prediction algorithms to estimate remaining useful life predictions at system as well as subsystem levels. 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. In addition a digital twin concept is being implemented in the framework to demonstrate verification and validation of developed algorithms. Note - This presentation is for the short workshop conducted at the same conference and contains all previously approved and published information.

Systems Health Managent↗

NASA NTRS1995

Engineering development program of a closed aluminum-oxygen semi-cell system for an unmanned underwater vehicle: An update

Most emerging unmanned undersea vehicle (UUV) missions require significantly longer range and endurance than is achievable with existing battery technology. The Aluminum-Oxygen (Al-O2) semi-cell is a candidate technology capable of providing a significant improvement in endurance compared to the silver-zinc battery technology currently used in UUVs and compares favorably to other proposed UUV power systems not only in performance, but also in safety and logistics. An Al-O2 semi-cell system is under development by Loral Defense Systems-Akron (Loral) for the ARPA/Navy 44 in. diameter UUV test vehicle. The power plant consists of a cell stack, gas management, oxygen storage, electrolyte management, coolant and controller subsystems, designed to replace the existing silver-zinc battery and meet existing weight, volume, electrical and thermal requirements, therefore minimizing modifications to the UUV. A detailed system design is complete. A component and material endurance test to evaluate compatibility and reliability of various material arid components is complete. Sub scale (Short stack) system testing is completed. A full-scale demonstration unit is now under construction in the second half of 1995. The full scale demonstration test will simulate environmental conditions of the operational system. This paper summarizes the results of the extensive short stack and endurance test programs, describes the plan for full-scale testing, and concludes with a brief discussions of future directions for this technology. This program is sponsored by ARPA Maritime Systems Technology Office under NASA contract NAS3-26715.

Gregg, Dane W.↗

DOE OSTI2021

A Comprehensive Method to Mitigate Forced Oscillations in Large Interconnected Power Grids

Multiple severe forced oscillation events have recently been observed across the North American interconnections and around the world. These forced oscillations have caused power swings, limited power transfer capability, damaged equipment, and persisted indefinitely until the driving source was located and removed. This paper proposes a comprehensive method to mitigate forced oscillations. Once a forced oscillation is detected, a new source location algorithm can be used to locate the source based on the oscillation mode angle without requiring system topology information. If the source cannot be quickly located and removed, a control strategy can be activated to modulate the active power of utility-scale inverterbased battery energy storage systems (BESSs) to reduce the energy of forced oscillations to a safe level and allow sufficient time for locating the exact source. The proposed source location algorithm is validated using measurements collected during the January 11, 2019 forced oscillation event in North America and other actual grid events, while the proposed control strategy is verified using the Eastern Interconnection dynamic model under the replicated January 11, 2019 forced oscillation event. The simulation results demonstrated that the proposed source location algorithm can accurately identify the forced oscillation source, and the proposed control strategy can significantly reduce forced oscillation energy.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRSDate not supplied

Systems Health Management and Prognostics Approaches for Electric Aircrafts

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in the prediction of remaining driving flying time/distance for the flying vehicles. This information is important, particularly in the case of auto vehicles, because such vehicles can become self-aware, autonomously compute its own capabilities, and identify how to best plan and successfully complete vehicular missions safely. In case of electric aircrafts, computing the remaining flying time is also safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. A systematic prediction framework is implemented to identify all possible sources of uncertainty, quantify each of them individually, and mathematically estimate their combined effect on the system-level quantity of interest, in this case, the remaining flying time/distance of the unmanned aircraft. Note - This presentation contains all previously published information.

Systems Health Managent↗

NASA NTRSDate not supplied

Health Monitoring and Prognostics for Electric Aircrafts

As more and more electric vehicles emerge in our daily operation progressively, a very critical challenge lies in the prediction of remaining driving flying time/distance for the flying vehicles. This information is important, particularly in the case of auto vehicles, because such vehicles can become self-aware, autonomously compute its own capabilities, and identify how to best plan and successfully complete vehicular missions safely. In case of electric aircrafts, computing the remaining flying time is also safety-critical, since an aircraft that runs out of power (battery charge) while in the air will eventually lose control leading to catastrophe. To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision-making. A systematic prediction framework is implemented to identify all possible sources of uncertainty, quantify each of them individually, and mathematically estimate their combined effect on the system-level quantity of interest, in this case, the remaining flying time/distance of the unmanned aircraft. Note - This presentation contains all previously approved and published information.

Systems Health Managent↗

NASA NTRS2019

Short Course on Lithium-Ion Batteries: Fundamental Concepts, Battery Safety, and Modeling Techniques

When developing this course several years back I asked myself, "What do I think the TFAWS community needs to know about lithium-ion batteries and why should they care?" I think the answers to these questions can be boiled down to the following statements: 1. Lithium-ion (Li-ion) battery electrical performance and efficiency are heavily driven by thermal conditions. 2. Li-ion battery assemblies can experience single cell thermal runaway events which can lead to cell-to-cell propagation; these are thermally driven failure events that can be controlled with effective thermal management systems. 3. Knowledge of BOTH Li-ion battery fundamentals AND traditional thermal design principles are required to develop safe battery assemblies that are both gravimetrically and volumetrically optimized.This year the Short Course on Lithium-ion Batteries will be presented in a 2-part series. The first portion, "Fundamentals, Battery Safety, and Thermal Runaway," will focus on educating participants on the fundamental aspects of Li-ion batteries and on battery safety related topics (i.e. thermal runaway, cell-to-cell propagation, safe handling practices, et...). The second portion, "Practical Thermal Simulation Techniques," will provide participants with a real time demonstration of how to use Thermal Desktop to model of Li-ion battery assemblies. This part of the lesson will cover geometry simplification, mesh development, boundary conditions, and heat loads for both nominal operations (charge and discharge) and for thermal runaway events.

Walker, William↗

DOE OSTI2024

Generalizable, tunable control of divalent cation solvation structure via mixed anion contact ion pair formation

Multivalent batteries are a promising new technology for energy storage, but they face challenges to developing suitable electrolytes that can support reversible deposition/dissolution at the metal anode and enable compatibility with high voltage oxide cathode materials. Here, in this work, we investigate the solvation behavior of Zn 2+ , Mg 2+ , Ca 2+ and Cu 2+ in mixed anion electrolytes containing TFSI - and Cl - . Raman and nuclear magnetic resonance spectroscopies are utilized to probe the bulk solvation structure of these electrolytes and demonstrate that mixed anion contact ion pairs (CIPs) are formed in all four systems, indicating this behavior is likely general to divalent cations. Furthermore, the relative population of mixed anion CIPs can be tuned by controlling the relative ratio of TFSI : Cl, with significant CIP populations observed even at low relative fractions of Cl - . These findings imply that modifying the anion chemistry can easily adjust the solvation structure of bulk cations, which has important implications for the development of next-generation electrolytes. By understanding the factors that influence the formation of mixed anion CIPs, we can design systems that promote the formation of electrochemically-active solvation structures that can enable multivalent batteries with improved performance and lifetimes.

25 ENERGY STORAGE↗

NASA NTRS1989

Hubble Space Telescope six-battery nickel-cadmium mission simulation test

A simulation test of the six-battery nickel-cadmium mission to determine battery life and electrical power system (EPS) performance characteristics for the Hubble Space Telescope (HST) program, is described. The basic HST power system requirements are to provide power generation, energy storage, and EPS control and distribution for 2.5 years with the nickel-cadmium (NiCd) batteries at an end of life solar array of 2 years. Mission simulation life testing begain in April of 1986, and the batteries have completed their 2.5 year mission requirement. Conditions as close as practical to the actual predicted mission profiles were used. These included solar array degradation, load variations, beta angle changes, temperature changes (with excursions to 10 C), battery reconditioning, safemode simulations, and off-normal roll activities. Discounting system cycling interruptions caused by hardware, software, human error, and periodic updates and revisions, the HST EPS breadboard hardware operated continuously for 30 months and demonstrated the power system's ability to meet the HST requirement.

Jackson, Lorna G.↗

NASA NTRS1989

Motor and cognitive testing of bone marrow transplant patients after chemoradiotherapy

Assessment of cognitive and motor performance of bone marrow transplant patients prior to, during, and following intensive toxic chemoradiotherapy may provide an important adjunct to measures of physiological and medical status. The present study is an attempt to assess whether, as side-effects, these aggressive treatments result in cognitive performance deficits, and if so, whether such changes recover posttreatment. Measurement of cognitive ability in this situation presents special problems not encountered with one-time tests intended for healthy adults. Such tests must be sensitive to changes within a single individual, which emphasizes the crucial importance of high reliability, stability across repeated-measures, and resistance to confounding factors such as motivation and fatigue. The present research makes use of a microbased portable test battery developed to have reliable and sensitive tests which were adapted to study the special requirements of transplant patients who may suffer cognitive deficits as a result of treatment. The results showed slight but significant changes in neuropsychological capacity when compared to baseline levels and controls, particularly near the beginning of treatment. The sensitivity of the battery in detecting such subtle temporary changes is discussed in terms of past research showing effects of other stressors, such as stimulated high altitude and ingestion of alcohol, on these measures.

Non-NASA Center↗

NASA NTRS1989

New secondary batteries utilizing electronically conductive polymer cathodes

The objectives of this project are to optimize the transport rates in electronically conductive polypyrrole films by controlling the morphology of the film and to assess the utility of these films as cathodes in a lithium/polypyrrole secondary battery. During this research period, progress has been made in improving the charge transport rate of the supermolecular-engineered polypyrrole electrode by eliminating the polypyrrole baselayer that hampered earlier work. Also, the fibril density of the polypyrrole electrode was increased, providing more electroactive sites per unit area.

Martin, Charles R.↗

DOE OSTI2026

Potential of Data Center Controls in Grid Services

The rapid proliferation of large data centers brings both challenges and opportunities for grid reliability. The data center resources and their potential flexibility have the potential to contribute resources to grid operations. Through capabilities like energy shifting and resource coordination, data centers can help reduce their net demand on the transmission network, as well as provide additional grid services to support reliable operation on the grid. While transient and long-term grid planning and operations are the scenarios that draw most attention, the quasi-steady state timeseries (QSTS) operation of data centers and grid bring interesting scenarios that can help evaluate the data center controls to aid grid services. This work is focused on modeling data centers for QSTS applications – incorporating the AI data center load profiles and building on the PNNL digital twin model for the thermal management loads to enable simulation studies to reveal the impact of data center controls on grid performance. This includes the integration of a QSTS battery and natural gas generator model to incorporate local resource impacts to the system. The simulation study is performed with a modified IEEE 24-Bus transmission system. Scenarios are focused on evaluating the data center load impacts on the transmission system and leveraging both data center and local generation controls to mitigate those impacts and provide additional grid services. The data center controls revealed the ability to contribute to two main kinds of grid services: preventing congestion on a weak grid by coordinating the data center resources with the collocated BESS and onsite generation; and the ability to help the grid operations during stressed times of operation like during a contingency. Leveraging these and other capabilities has the potential to help data centers become grid responsive assets, aiding in both their integration into the power system and grid reliability.

power grid simulation↗

DOE OSTI2023

Design, Optimization, and Validation of GaN-Based DAB Converter for Active Cell Balancing in BTMS Applications: Preprint

This paper focuses on the design of a bidirectional dual active bridge (DAB) DC/DC converter that utilizes Gallium Nitride (GaN) switches as active components. In the existing literature, MOSFET-based DAB for active cell balancing is available, but GaN-based DAB converter for active cell balancing is still new. The proposed modular isolated GaN-based DAB converter is designed as an individual module of active cell balancing for behind-the-meter storage (BTMS) applications, targeting high-power charging stations. Modular isolated converters are connected to each cell (low voltage bus), and each cell is connected in series to build up a battery module. According to the reference current command of supervisory control, each DAB converter can transfer power back and forth through the high voltage (HV) bus to balance the State of Charge (SoC) between the cells. Each module DAB converter is designed at a 50W power rating. Switch power and transformer losses are analyzed for different switching frequencies, showing the optimum switching frequency for minimum losses. Furthermore, the procedure to select the required gate driver and the PCB layout optimization are discussed. Finally, the DAB performance analysis of GaNbased DAB and Si-based DAB is provided for a battery module operating with a LiFeMnPO4 prismatic cell with 3.2V 20Ah rated values.

active cell balancing↗

DOE OSTI2021

Modulating the Surface Ligand Orientation for Stabilized Anionic Redox in Li‐Rich Oxide Cathodes

Abstract Anionic redox chemistry is emerging as a key concept in the development of high‐energy lithium‐ion batteries, as it enables a nearly doubled charge storage capacity, aiding the development of high‐capacity batteries. However, the anionic reactivity is frequently irreversible from charge to discharge, leading to rapid decay of the capacity and voltage of batteries over long‐term cycling. Although the possibility of controlling the anionic redox reactions by tuning the geometric and electronic structures has recently been proposed, the implementation of this strategy is still a critical challenge. Herein, a strategy is proposed to improve the anionic redox reversibility of a model anionic redox active cathode material, Li 1.2 Ni 0.13 Co 0.13 Mn 0.54 O 2 , by tuning the surface ligand geometry via the growth of a lattice‐compatible spinel LiCoO 2 coating layer on the particle surface. Detailed local structure and first principles investigations reveal that the shape and orientation of the octahedral layer in the host lattice are modified. Accordingly, a two‐band oxygen redox behavior is triggered in the ligand‐orientation‐regulated Li‐rich cathode, leading to enhanced reversibility, and thus, remarkably improved capacity and voltage retention over cycling. This study highlights the importance of controllable ligand orientation, carving a new path for the development and design of Li‐rich cathodes in the future.

Liu, Yanchen↗

DOE OSTI2024

Electrochemical Imaging of Precisely‐Defined Redox and Reactive Interfaces

Abstract Understanding the diverse electrochemical reactions occurring at electrode‐electrolyte interfaces (EEIs) is a critical challenge to developing more efficient energy conversion and storage technologies. Establishing a predictive molecular‐level understanding of solid electrolyte interphases (SEIs) is challenging due to the presence of multiple intertwined chemical and electrochemical processes occurring at battery electrodes. Similarly, chemical conversions in reactive electrochemical systems are often influenced by the heterogeneous distribution of active sites, surface defects, and catalyst particle sizes. In this mini review, we highlight an emerging field of interfacial science that isolates the impact of specific chemical species by preparing precisely‐defined EEIs and visualizing the reactivity of their individual components using single‐entity characterization techniques. We highlight the broad applicability and versatility of these methods, along with current state‐of‐the‐art instrumentation and future opportunities for these approaches to address key scientific challenges related to batteries, chemical separations, and fuel cells. We establish that controlled preparation of well‐defined electrodes combined with single entity characterization will be crucial to filling key knowledge gaps and advancing the theories used to describe and predict chemical and physical processes occurring at EEIs and accelerating new materials discovery for energy applications.

Edgecomb, Joseph↗

DOE OSTI2024

Electrochemical Imaging of Precisely‐Defined Redox and Reactive Interfaces

Abstract Understanding the diverse electrochemical reactions occurring at electrode‐electrolyte interfaces (EEIs) is a critical challenge to developing more efficient energy conversion and storage technologies. Establishing a predictive molecular‐level understanding of solid electrolyte interphases (SEIs) is challenging due to the presence of multiple intertwined chemical and electrochemical processes occurring at battery electrodes. Similarly, chemical conversions in reactive electrochemical systems are often influenced by the heterogeneous distribution of active sites, surface defects, and catalyst particle sizes. In this mini review, we highlight an emerging field of interfacial science that isolates the impact of specific chemical species by preparing precisely‐defined EEIs and visualizing the reactivity of their individual components using single‐entity characterization techniques. We highlight the broad applicability and versatility of these methods, along with current state‐of‐the‐art instrumentation and future opportunities for these approaches to address key scientific challenges related to batteries, chemical separations, and fuel cells. We establish that controlled preparation of well‐defined electrodes combined with single entity characterization will be crucial to filling key knowledge gaps and advancing the theories used to describe and predict chemical and physical processes occurring at EEIs and accelerating new materials discovery for energy applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗