Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “battery control”

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.

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

At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

An Adaptable Power System with Software Control Algorithm

A low cost, flexible and modular spacecraft power system design was developed in response to a call for an architecture that could accommodate multiple missions in the small to medium load range. Three upcoming satellites will use this design, with one launch date in 1999 and two in the year 2000. The design consists of modular hardware that can be scaled up or down, without additional cost, to suit missions in the 200 to 600 Watt orbital average load range. The design will be applied to satellite orbits that are circular, polar elliptical and a libration point orbit. Mission unique adaptations are accomplished in software and firmware. In designing this advanced, adaptable power system, the major goals were reduction in weight volume and cost. This power system design represents reductions in weight of 78 percent, volume of 86 percent and cost of 65 percent from previous comparable systems. The efforts to miniaturize the electronics without sacrificing performance has created streamlined power electronics with control functions residing in the system microprocessor. The power system design can handle any battery size up to 50 Amp-hour and any battery technology. The three current implementations will use both nickel cadmium and nickel hydrogen batteries ranging in size from 21 to 50 Amp-hours. Multiple batteries can be used by adding another battery module. Any solar cell technology can be used and various array layouts can be incorporated with no change in Power System Electronics (PSE) hardware. Other features of the design are the standardized interfaces between cards and subsystems and immunity to radiation effects up to 30 krad Total Ionizing Dose (TID) and 35 Mev/cm(exp 2)-kg for Single Event Effects (SEE). The control algorithm for the power system resides in a radiation-hardened microprocessor. A table driven software design allows for flexibility in mission specific requirements. By storing critical power system constants in memory, modifying the system code for other programs is simple. These constants can be altered also by ground command, or in response to an anomolous event. All critical power system functions have backup hardware functions to prevent a software or computer glitch from propagating. A number of battery charge control schemes can be implemented by selecting the proper control terms in the code. The architecture allows the design engineer to tune the system response to various system components and anticipated load profiles without costly alterations. A design trade was made with the size, weight and power dissipation of the electronics versus the performance of the power bus to load variations. Linear, fine control is maintained with a streamlined electronics design. This paper describes the hardware design as well as the software control algorithm. The challenges of closing the system control loop digitally is discussed. Control loop margin and power system performance is presented. Lab measurements are shown and compared to the system response of a hardware model running actual flight software.

Castell, Karen↗
DOE OSTI2020

Flexibility Estimation and Control of Thermostatically Controlled Loads with Lock Time for Regulation Service

A virtual battery model is a simple and general method to quantify aggregate flexibility from thermostatically controlled loads (TCLs), enabling grid operators to effectively coordinate a large number of flexible building loads with supplyside resources in power systems. Lockout controls are designed to avoid wear and tear resulting from short-cycling of hardware. The lock on/off time could significantly affect aggregate flexibility from TCLs to provide ancillary services and may even fail control algorithms designed without considering the lock time constraints. This paper focuses on flexibility estimation and control design for TCLs with lock time constraints to provide frequency regulation service. We first investigate the potential impacts of lock time on TCLs’ aggregate flexibility and control performance. Both control-dependent and control-independent power bounds are derived, based on either previous TCL switching operations or regulation signals. While the control-dependent method provides aggregate flexibility for a given control method, the control-independent method calculates the theoretical maximum of power bounds. Two control algorithms are proposed to better distribute flexibility over time and thereby improve signal tracking performance. The proposed methods are illustrated and validated through simulations.

Wang, Peng↗
DOE OSTI2020

EFRC Accomplishments 2014-2020: NorthEast Center for Chemical Energy Storage (NECCES)

The mission of NECCES is to develop an understanding of how key electrode reactions occur in cathode materials for Li based batteries, and how they can be controlled to improve electrochemical performance, from the atomistic level to the macroscopic level through the life-time of the operating battery. This mission will allow the determination of the ultimate limits of intercalation reactions for chemical energy storage. The approach and specific research goals of NECCES are to: 1. Attain reversible multi-electron transfer in a cathode material using lithium, using the model compound ε -VOPO 4 ; 2. Close the gap between the theoretical and practical energy density for intercalation compounds, using the model compound LiNi 0.85 Co 0 .10Al 0.05 O 2 ; 3. Understand the transition from cation redox to anion redox electrochemistry; 4. Understand performance limiting transport in positive electrode structures from the local through the meso to the macroscale.

25 ENERGY STORAGE↗
NASA NTRS1987

Hubble Space Telescope electrical power system simulation breadboard

The components and operation of the Hubble Space Telescope (HST) electrical power system (EPS) breadboard are described. The HST EPS breadboard consists of: (1) the power distribution breadboard, (2) the batteries, (3) the solar array simulators, (4) the load banks, (5) the charge current control hardware, and (6) a control computer; the functions of each of these elements are discussed. The HST EPS has been used to simulate changes in charge level, charge control schemes, and beta angle, failed cells, batteries, solar panel assemblies (SPAs), beginning of life SPAs, and end of life SPAs, and temperature differences. The test data reveal that the HST EPS is capable of operating over a wide range of conditions.

Bush, John R., Jr.↗
DOE OSTI2020

Electron Transfer in Microemulsion-Based Electrolytes

The use of flowing electrochemical reactors, for example, in redox flow batteries and in various electrosynthesis processes, is increasing. This technology has the potential to be of central significance in the increased deployment of renewable electricity for carbon-neutral processes. A key element of optimizing efficiency of electrochemical reactors is the combination of high solution conductivity and reagent solubility. In this work, we show a substantial rate of charge transfer for an electrochemical reaction occurring in a microemulsion containing electroactive material is loaded inside the nonpolar (toluene) subphase of the microemulsion. The measured rate constant translates to an exchange current density comparable to that in redox flow batteries. The rate could be controlled by the surfactant, which maintains partitioning of reactants and products by forming an interfacial region with ions in the aqueous phase in close proximity. The hypothesized echanism is evocative of membrane-bound enzymatic reactions. Achieving sufficient rates of electrochemical reaction is the product of an effort designed to establish a reaction condition that meets the requirements of electrochemical reactors using microemulsions to realize a separation of conducting and reactive elements of the solution, opening a door to the broad use of microemulsions to effect controlled electrochemical reactions as steps in more complex processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A Data-Driven Algorithm for Enabling Delay Tolerance in Resilient Microgrid Controls Using Dynamic Mode Decomposition

The increased implementation of smart grid technologies in the power distribution grid presents unique opportunities that enable resiliency, but also brings challenges motivating needs for novel solutions and mitigation techniques. The bi-directional power and data flow allow for the grid to operate with increased resiliency, which is the ability to avoid discontinuity of service to end-use loads during extreme events. However, in applications where control of the distribution grid or microgrid relies on communication networks, the degradation of communication systems in the form of loss or high latency can cause maloperation and result in loss of end-use loads. Here this paper presents a novel framework to enable delay tolerance of centralized microgrid control schemes to mitigate communication system latency impacts and guarantee successful control action. We demonstrate the delay tolerance on a control scheme that operates a battery energy storage system (BESS) to offset the sudden loss of generation and maintain system frequency. During periods of severely degraded communication system performance, the proposed delay-tolerant algorithm compensates for the latency by utilizing a data-driven model generated at the device level using dynamic mode decomposition (DMD) to determine the performance of the communications. The DMD technique predicts the system’s frequency using device-level terminal measurements and provides updated control signals. The HELICS cosimulation platform evaluates the cyber-physical interaction of the power system model in GridLAB-D, the centralized control agent in Python, and the discrete network model in NS-3. The framework is tested and validated on the IEEE-123 node system modified to represent a networked remote microgrid model, and the results show an improvement in the dynamic performance

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Supercritical CO2 sterilization of N95 Masks

A preliminary investigation of the use of supercritical carbon dioxide for treating of 3M 1860 N95 masks was undertaken to evaluate a potential route to low-cost, scalable, sterilization of personal protective equipment for multiple reuse in hospital settings. Upon entering the supercritical regime, the normally distinct liquid and gaseous phases of CO 2 merge into a single homogeneous phase that has density, short-range order, and solvation capacity of a liquid, but the volume-filling and permeation properties that of a gas. This enables supercritical CO2 to function as a vehicle for delivery of biocidal agents such peracetic acid into microporous structures. The potentially adverse effect of a liquid-to-gas phase transition on mask filter media is avoided by conducting cleaning operations above 31 C, the critical temperature for carbon dioxide. A sample of fifteen 3M 1860 N95 masks was subjected to ten consecutive cycles of supercritical CO 2 cleaning to determine its effect on mask performance. These 15 masks, along with 5 control samples then underwent a battery of standardized tests at the CDC NIOSH NPPTL research facility in Pittsburgh, PA. The data from these tests strongly suggest (but do not prove) that supercritical carbon dioxide do not damage 3M 1860 N95 masks. Additional tests conducted during this project confirmed the compatibility of supercritical CO 2 with ventilator tubing that, like N95 masks, has been in short supply during portions of the COVID-19 pandemic and cannot be sterilized by conventional means. Finally, a control experiment was also conducted to examine the effect of supercritical CO 2 on a BSL-2 surrogate virus, vesicular stomatitis virus (VSV), Indiana serotype strain. In the absence of biocidal additives, supercritical CO 2 exhibited no measurable lethality against VSV. This surrogate virus experiment suggests that a biocidal additive such as peracetic acid will be necessary to achieve required sterilization metrics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Closed-loop optimization of fast-charging protocols for batteries with machine learning

Simultaneously optimizing many design parameters in time-consuming experiments causes bottlenecks in a broad range of scientific and engineering disciplines. One such example is process and control optimization for lithium-ion batteries during materials selection, cell manufacturing and operation. A typical objective is to maximize battery lifetime; however, conducting even a single experiment to evaluate lifetime can take months to years. Furthermore, both large parameter spaces and high sampling variability necessitate a large number of experiments. As such, the key challenge is to reduce both the number and the duration of the experiments required. Here we develop and demonstrate a machine learning methodology to efficiently optimize a parameter space specifying the current and voltage profiles of six-step, ten-minute fast-charging protocols for maximizing battery cycle life, which can alleviate range anxiety for electric-vehicle users. We combine two key elements to reduce the optimization cost: an early-prediction model, which reduces the time per experiment by predicting the final cycle life using data from the first few cycles, and a Bayesian optimization algorithm, which reduces the number of experiments by balancing exploration and exploitation to efficiently probe the parameter space of charging protocols. Using this methodology, we rapidly identify high-cycle-life charging protocols among 224 candidates in 16 days (compared with over 500 days using exhaustive search without early prediction), and subsequently validate the accuracy and efficiency of our optimization approach. Our closed-loop methodology automatically incorporates feedback from past experiments to inform future decisions and can be generalized to other applications in battery design and, more broadly, other scientific domains that involve time-intensive experiments and multi-dimensional design spaces.

25 ENERGY STORAGE↗
DOE OSTI2021

Data-Driven Multi-agent Deep Reinforcement Learning for Distribution System Decentralized Voltage Control with High Penetration of PVs

This paper proposes a novel model-free/data-driven centralized training and decentralized execution multi-agent deep reinforcement learning (MADRL) framework for distribution system voltage control with high penetration of PVs. The proposed MADRL can coordinate both the real and reactive power control of PVs with existing static var compensators and battery storage systems. Unlike the existing DRL-based voltage control methods, our proposed method does not rely on a system model during both the training and execution stages. This is achieved by developing a new interaction scheme between the surrogate modeling of the original system and the multi-agent soft actor critic (MASAC) MADRL algorithm. In particular, the sparse pseudo-Gaussian process with a few-shots of measurements is utilized to construct the surrogate model of the original environment, i.e., power flow model. This is a data-driven process and no model parameters are needed. Furthermore, the MASAC enabled MADRL allows to achieve better scalability by dividing the original system into different voltage control regions with the aid of real and reactive power sensitivities to voltage, where each region is treated as an agent. This also serves as the foundation for the centralized training and decentralized execution, thus significantly reducing the communication requirements as only local measurements are required for control. Comparative results with other alternatives on the IEEE 123-nodes and 342-nodes systems demonstrate the superiority of the proposed method.

14 SOLAR ENERGY↗
DOE OSTI2025

Design, Control, and Protection of a 13.2 kV, 1 MVA Solid State Transformer for Electric Vehicle Extreme Fast Charging Station

In this article, a medium-voltage (MV) ac-dc solid state transformer (SST) for electric vehicle (EV) extreme fast charging (XFC) station is proposed. The SST adopts a cascaded H-bridge (CHB)-based structure where the active front end (AFE) power stages are connected in input-series followed by dual active bridge (DAB) converters connected in an output-parallel configuration providing galvanic isolation through a high-frequency transformer (HFT). The SST is rated for 1 MVA and connects directly to a three-phase 13.2 kV MV ac grid through ac switchgear and outputs 750-V dc. At the dc bus, several dc/dc converters are connected, each of which can charge an EV based on its battery capacity. A novel decentralized control architecture of the SST is adopted in this work which simplifies the MV dc link voltage and module-level power balancing. In addition, the local and central protection designs of the SST are presented which identify and respond to the internal fault of the system. Finally, the experimental validations of the SST hardware prototype are presented up to the rated voltage. Furthermore, this article details the design and implementation of the MV SST addressing the challenges of an isolated MV class power converter for connecting directly to the MV ac grid with unique controller architecture, distributed protection framework, and SST constructional features.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2001

International Space Station Bus Regulation With NASA Glenn Research Center Flywheel Energy Storage System Development Unit

An experimental flywheel energy storage system is described. This system is being used to develop a flywheel based replacement for the batteries on the International Space Station (ISS). Motor control algorithms which allow the flywheel to interface with a simplified model of the ISS power bus, and function similarly to the existing ISS battery system, are described. Results of controller experimental verification on a 300 W-hr flywheel are presented.

Kascak, Peter E.↗
NASA NTRSDate not supplied

Li-ion Battery Aging with Hybrid Physics-Informed Neural Networks and Fleet-wide Data

In this work, we propose a hybrid model for Li-ion battery discharge and aging prediction that leverages fleet-wide data to predict future capacity drops.The model is built upon an hybrid approach merging physics-based and empirical equations, as well as neural network models in a recurrent neural network cell. The hybrid physics-informed neural network can predict voltage discharge cycles given the loading profile, and estimate the used capacity of the battery under random-loading conditions by tracking aging parameters connected to the residual capacity of the battery. By merging information on the battery aging parameters with existing fleet-wide aging data, the model can predict the future residual capacity of the battery that is being monitored, and therefore enable predictions of voltage discharge curves far ahead in the battery life cycle. We validated the approach using the NASA Prognostics Data Repository Battery data-set, which contains experimental data on Li-ion batteries discharged at random loading conditions in a controlled environment. The approach also allows the identification of discrepancies between the battery aging trend and the trend observed at the fleet level, so that batteries behaving differently from the rest of the fleet can be subject to closer monitoring and further testing to refine predictions.

PINN↗
NASA NTRS1988

Mechanical design engineering. NASA/university advanced design program: Lunar Bulk Material Transport Vehicle

The design of a Lunar Bulk Material Transport Vehicle (LBMTV) is discussed. Goals set in the project include a payload of 50 cubic feet of lunar soil with a lunar of approximately 800 moon-pounds, a speed of 15 mph, and the ability to handle a grade of 20 percent. Thermal control, an articulated steering mechanism, a dump mechanism, a self-righting mechanism, viable power sources, and a probable control panel are analyzed. The thermal control system involves the use of small strip heaters to heat the housing of electronic equipment in the absence of sufficient solar radiation and multi-layer insulation during periods of intense solar radiation. The entire system uses only 10 W and weighs about 60 pounds, or 10 moon-pounds. The steering mechanism is an articulated steering joint at the center of the vehicle. It utilizes two actuators and yields a turning radius of 10.3 feet. The dump mechanism rotates the bulk material container through an angle of 100 degree using one actuator. The self-righting mechanism consists of two four bar linkages, each of which is powered by the same size actuator as the other linkages. The LBMTV is powered by rechargeable batteries. A running time of at least two hours is attained under a worst case analysis. The weight of the batteries is 100 pounds. A control panel consisting of feedback and control instruments is described. The panel includes all critical information necessary to control the vehicle remotely. The LBMTV is capable of handling many types of cargo. It is able to interface with many types of removable bulk material containers. These containers are made to interface with the three-legged walker, SKITTER. The overall vehicle is about 15 feet in length and has a weight of about 1000 pounds, or 170 lunar pounds.

Daugherty, Paul↗
DOE OSTI2022

Nanotomographic observation and statistical analysis of overcharging induced cracks in LiCoO 2 single crystalline particles

Particle fracture represents an important mode of battery electrode degradation. Extensive cracking occurs in the layered oxide cathodes of lithium-ion rechargeable batteries when they are charged beyond safe operational voltages. In this paper, we analyze the morphology and distribution of cracks in over 100 overcharged LiCoO 2 (LCO) single-crystalline particles imaged via X-ray nanotomography. Herein, we observe a strong particle size dependence in both nucleation and growth of cracks, with percentage of cracked particles, crack size, and crack surface area per unit volume all increasing significantly with particle volume. Increasing the cutoff voltage above 4.6V is found to trigger much more pronounced crack growth, which we attribute to the large misfit stress caused by the H1-3 to O1 phase transition. This study offers valuable statistical insights into the fracture behavior of layered oxide cathodes and reveals the importance of particle size control on electromechanical degradation of battery electrodes.

25 ENERGY STORAGE↗
DOE OSTI2024

Probabilistic machine learning for battery health diagnostics and prognostics—review and perspectives

Abstract Diagnosing lithium-ion battery health and predicting future degradation is essential for driving design improvements in the laboratory and ensuring safe and reliable operation over a product’s expected lifetime. However, accurate battery health diagnostics and prognostics is challenging due to the unavoidable influence of cell-to-cell manufacturing variability and time-varying operating circumstances experienced in the field. Machine learning approaches informed by simulation, experiment, and field data show enormous promise to predict the evolution of battery health with use; however, until recently, the research community has focused on deterministic modeling methods, largely ignoring the cell-to-cell performance and aging variability inherent to all batteries. To truly make informed decisions regarding battery design in the lab or control strategies for the field, it is critical to characterize the uncertainty in a model’s predictions. After providing an overview of lithium-ion battery degradation, this paper reviews the current state-of-the-art probabilistic machine learning models for health diagnostics and prognostics. Details of the various methods, their advantages, and limitations are discussed in detail with a primary focus on probabilistic machine learning and uncertainty quantification. Last, future trends and opportunities for research and development are discussed.

25 ENERGY STORAGE↗
DOE OSTI2022

Lithiating magneto-ionics in a rechargeable battery

Magneto-ionics, real-time ionic control of magnetism in solid-state materials, promise ultralow-power memory, computing, and ultralow-field sensor technologies. The real-time ion intercalation is also the key state-of-charge feature in rechargeable batteries. Here, we report that the reversible lithiation/delithiation in molecular magneto-ionic material, the cathode in a rechargeable lithium-ion battery, accurately monitors its real-time state of charge through a dynamic tunability of magnetic ordering. The electrochemical and magnetic studies confirm that the structural vacancy and hydrogen-bonding networks enable reversible lithiation and delithiation in the magnetic cathode. Coupling with microwave-excited spin wave at a low frequency (0.35 GHz) and a magnetic field of 100 Oe, we reveal a fast and reliable built-in magneto-ionic sensor monitoring state of charge in rechargeable batteries. The findings shown herein promise an integration of molecular magneto-ionic cathode and rechargeable batteries for real-time monitoring of state of charge.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Opportunities and Challenges to Capturing Distributed Battery Value via Retail Utility Rates and Programs

Distributed battery deployment is increasing with advanced metering, control, and communication technologies, leaving electric utilities with an under-utilized, flexible grid resource in aggregate. Rates can reflect locational and temporal prices while utility incentive-based programs allow DERs to provide direct grid services. However, utilities must balance accurately reflecting dynamic grid conditions versus simple and feasible design that encourages customer participation. Currently, most rates and incentive-based programs are simple, but as penetration of DER and advanced controls increase, dynamic designs could become prevalent. Utilities could encourage providing multiple services to optimize distributed battery dispatch and value streams, however, challenges persist when stacking services across distribution and bulk systems. A DER committed to multiple discrete services concurrently necessitates coordination between operators and a clear hierarchy of commitments. One way to address this is to separate commitments by time or capacity. For services that follow cyclic, predictable patterns, or those that are peak driven with predictability, an operator could ensure sufficient state of charge for participation, leaving time where a distributed battery could otherwise provide different services by segmenting participation temporally. To provide continuous or unexpected services, a battery operator may use state of charge management to reserve some percentage of the battery and segment participation by capacity. Macroeconomic trends, load patterns, generation profiles, and grid configurations drive variation in value and the subsequent implications for utility offerings and how a customer might participate. As distributed battery adoption increases, both regulators and utilities will need to ensure no adverse grid impacts and encourage provision of societal value beyond the customer domain.

24 POWER TRANSMISSION AND DISTRIBUTION↗