Search NASA⌕ Search

SEARCH · Search NASA

Results for “BATTERY PROGRAM”

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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Time-Dependent Material Data Essential for the Durability Analysis of Composite Flywheels Provided by Compressive Experiments

Successful spaceflight operations require onboard power management systems that reliably achieve mission objectives for a minimal launch weight. Because of their high specific energies and potential for reduced maintenance and logistics, composite flywheels are an attractive alternative to electrochemical batteries. The Rotor Durability Team, which comprises members from the Ohio Aerospace Institute (OAI) and the NASA Glenn Research Center, completed a program of elevated temperature testing at Glenn' s Life Prediction Branch's Fatigue Laboratory. The experiments provided unique design data essential to the safety and durability of flywheel energy storage systems for the International Space Station and other manned spaceflight applications. Analysis of the experimental data (ref. 1) demonstrated that the compressive stress relaxation of composite flywheel rotor material is significantly greater than the commonly available tensile stress relaxation data. Durability analysis of compression preloaded flywheel rotors is required for accurate safe-life predictions for use in the International Space Station.

Thesken, John C.↗
NASA NTRS2003

Continuous Improvement in Battery Testing at the NASA/JSC Energy System Test Area

The Energy Systems Test Area (ESTA) at the Lyndon B. Johnson Space Center in Houston, Texas conducts development and qualification tests to fulfill Energy System Division responsibilities relevant to ASA programs and projects. EST A has historically called upon a variety of fluid, mechanical, electrical, environmental, and data system capabilities spread amongst five full-service facilities to test human and human supported spacecraft in the areas of propulsion systems, fluid systems, pyrotechnics, power generation, and power distribution and control systems. Improvements at ESTA are being made in full earnest of offering NASA project offices an option to choose a thorough test regime that is balanced with cost and schedule constraints. In order to continue testing of enabling power-related technologies utilized by the Energy System Division, an especially proactive effort has been made to increase the cost effectiveness and schedule responsiveness for battery testing. This paper describes the continuous improvement in battery testing at the Energy Systems Test Area being made through consolidation, streamlining, and standardization.

Boyd, William↗
DOE OSTI2017

An Overview of the Automated Dispatch Controller Algorithms in the System Advisor Model (SAM)

Three automatic dispatch modes have been added to the battery model within the System Adviser Model. These controllers have been developed to perform peak shaving in an automated fashion, providing users with a way to see the benefit of reduced demand charges without manually programming a complicated dispatch control. A flexible input option allows more advanced interaction with the automated controller. This document will describe the algorithms in detail and present brief results on its use and limitations.

25 ENERGY STORAGE↗
NASA NTRS1998

Lightweight Nickel Electrode Development Program

Because of its relatively high specific energy and excellent cycling capability, the nickel-hydrogen (Ni-H2) cell is used extensively to store energy in aerospace systems. For the past several years, the NASA Lewis Research Center has been developing the Ni-H2 cell to improve its components, design, and operating characteristics. The battery size and weight are crucial parameters in aerospace and spacecraft power systems for applications such as the International Space Station, space satellites, and space telescopes. The nickel electrode has been identified as the heaviest and most critical component of the Ni-H2 cell. Consequently, Lewis began and is leading a program to reduce the electrode's weight by using lightweight plaques.

Britton, Doris L.↗
DOE OSTI2025

Optimization of a Mixed Fleet of Aerial Drones for Medical Supplies: A Case Study of Blood Delivery Logistics

Aerial drones have emerged as an innovative solution for faster transportation of time-sensitive items (e.g., emergency medical supplies), potentially reducing the transmission of contagious diseases and enhancing healthcare availability through contactless autonomous delivery. We study fleet sizing and efficient scheduling of a mixed fleet of drones for delivering time-sensitive medical items having distinct release and due times to minimize the required fleet size and fleet composition, the required number of additional batteries, and the total energy consumption. We continuously track the remaining battery energy of drones to determine the optimal timing for battery replacement, rather than replacing the battery at each node. Using actual drone flight test data, we employed a machine learning (ML) method to estimate the energy consumption of different drone types during flight segments for different operating parameters. We present a novel mixed-integer programming model to efficiently formulate the problem that integrates the estimated energy consumption functions from ML. We propose a new greedy heuristic (GH) algorithm and a customized genetic algorithm (GA) for solving large-scale instances of this problem faster. Results demonstrate that the GH algorithm is substantially faster than the accelerated CPLEX and the GA, while sacrificing the solution quality by a small amount. Results based on an actual blood sample delivery case study from Pendleton, Oregon, United States, show that using a mixed fleet of drones reduces the total cost and total energy consumption up to 18.18% and 28.7%, respectively, compared to using a homogeneous fleet.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗
DOE OSTI2025

Control System Upgrade for Battery State-of-Charge Indications

The Advanced Test Reactor (ATR) Complex at Idaho National Laboratory (INL) relies on Battery Backed Power (BBP) systems and Uninterruptible Power Supplies (UPS) to ensure continuous power supply to critical components. This project aims to enhance the reliability and functionality of the battery monitoring and control systems by updating the State-of-Charge (SOC) system, Programmable Logic Controller (PLC), and Human-Machine Interface (HMI) for the nuclear safety-related battery banks. The current system, while functional, has areas for improvement, particularly in recharging calculations and alarm functions. The project objectives include developing flow charts, programming the new PLC and HMI, conducting bench tests, and updating design documentation. Additionally, the project ensures compliance with safety standards, develops training materials, creates comprehensive documentation, and integrates seamlessly with existing ATR infrastructure. The new SOC system is designed to be scalable for future upgrades, improve efficiency, enhance data accuracy, implement redundancy features, and achieve project goals within budget constraints while considering environmental impact. The methodology involved familiarizing with BBP and UPS systems, collecting current readings, rescaling signals, learning ladder logic, and updating the HMI. The transition from SLC 5/03 PLC using RS Logix 500 to CompactLogix 5380 using Studio 5000 was a key step. Despite challenges in transferring outdated PLC ladder logic and HMI code, starting from scratch led to a more accurate and efficient monitoring system, contributing to improved safety and operational efficiency. The project is currently awaiting approval of the Engineering Calculation and Analysis Report (ECAR) before implementation.

42 - ENGINEERING↗
DOE OSTI2016

Predictive Battery Management System for Commercial Hybrid Vehicles: Cooperative Research and Development Final Report, CRADA Number CRD-13-520

NREL and Eaton Corporation will perform work together on DOE Advanced Research Projects Agency-Energy (ARPA-E) 'Advanced Management and Protection of Energy Storage Devices' program (DE-FOA0000675). NREL will experimentally characterize aging behavior of Eaton cells and packs. Eaton and NREL will implement NREL's prognostic life model in Eaton HEV supervisory controllers and demonstrate the algorithms in accelerated life hardware-in-the loop testing conducted at NREL.

25 ENERGY STORAGE↗
NASA NTRS1983

Steady-state and dynamic evaluation of the electric propulsion system test bed vehicle on a road load simulator

The propulsion system of the Lewis Research Center's electric propulsion system test bed vehicle was tested on the road load simulator under the DOE Electric and Hybrid Vehicle Program. This propulsion system, consisting of a series-wound dc motor controlled by an infinitely variable SCR chopper and an 84-V battery pack, is typical of those used in electric vehicles made in 1976. Steady-state tests were conducted over a wide range of differential output torques and vehicle speeds. Efficiencies of all of the components were determined. Effects of temperature and voltage variations on the motor and the effect of voltage changes on the controller were examined. Energy consumption and energy efficiency for the system were determined over the B and C driving schedules of the SAE J227a test procedure.

Dustin, M. O.↗
NASA NTRS1982

A high efficiency 3 kW switchmode battery charger

This paper discusses the design approach and status of a high-efficiency switchmode battery charger designed to charge a 108 V battery from the 115 Vac line. The charger contains a transformer isolated boost chopper operating at 20 kHz. The boost inductor current is programmed to follow the ac line voltage such that high power factor operation and low line distortion are obtained.

Latos, T. S.↗
NASA NTRS1979

Near hybrid passenger vehicle development program, phase 1. Appendices C and D, Volume 2

Results of tradeoff studies are presented in summary form. Various aspects of the overall vehicle design discussed include selection of the base vehicle, the battery pack configuration, structural modifications, occupant protection, vehicle dynamics, and aerodynamics. The drivetrain design and integration, power conditioning unit, battery subsystem, control system, environmental system are described. Specifications, weight breakdown, and energy consumption measures, and advanced technology components are included.

Source record↗
NASA NTRS1979

Phase 1 of the near team hybrid passenger vehicle development program. Appendix C: Preliminary design data package. Volume 2: Appendices

The design, development, efficiency, manufacturability, production costs, life cycle cost, and safety of sodium-sulfur, nickel-zinc, and lead-acid batteries for electric hybrid vehicles are discussed. Models are given for simulating the vehicle handling quality, and for finding the value of: (1) the various magnetic quantities in the different sections in which the magnetic circuit of the DC electric machine is divided; (2) flux distribution in the air gap and the magnetization curve under load conditions; and (3) the mechanical power curves versus motor speed at different values of armature current.

Piccolo, R.↗
NASA NTRSDate not supplied

Application of System-Theoretic Process Analysis (STPA) to a NASA Concept Electric Aircraft Battery System

System-Theoretic Process Analysis (STPA) is a systems-based hazard analysis method that identifies unsafe interactions and control deficiencies in complex systems but has been rarely used for NASA programs in favor of more well-established hazard analyses. To evaluate its applicability, a NASA Safety and Mission Assurance (SMA) team applied the STPA method to an early-stage hybrid electrified aircraft concept, focusing on the energy storage system and electric powertrain. Objectives include assessing STPA’s value relative to traditional methods and its suitability for early design phases. Activities include team training, system review, detailed STPA execution, and comparison with traditional analyses. Findings show STPA provides a structured, comprehensive hazard evaluation and can identify additional risks by expanding analysis boundaries. However, traditional methods can yield similar results when applied rigorously, though they typically require more mature designs. Overall, STPA is a valuable addition, particularly for early development, informing safety requirements and supporting preliminary hazard analyses. Further pilot applications are recommended.

Electric Aviation↗
DOE OSTI2022

Revenue prediction for integrated renewable energy and energy storage system using machine learning techniques

Revenue estimation for integrated renewable energy and energy storage systems is important to support plant owners or operators’ decisions in battery sizing selection that leads to maximized financial performances. A common approach to optimizing revenues of a hybrid hydro and energy storage system is using mixed-integer linear programming (MILP). Although MILP models can provide accurate production cost estimations, they are typically very computationally expensive. To provide a fast yet accurate first-step information to hydropower plant owners or operators who consider integrating energy storage systems, we propose an innovative approach to predicting optimal revenues of an integrated energy generation and storage system. In this study, we examined the performance of two prediction techniques: Generalized Additive Models (GAMs) and machine learning (ML) models developed based on artificial neural networks (ANN). Predictive equations and models are generated based on optimized solutions from a market participation optimization model, the Conventional Hydropower Energy and Environmental Resource System (CHEERS) model. The two predicting techniques reduce the computational time to evaluate annual revenue for one set of battery configurations from 3 h to 1 to 4 min per run while also being implementable with significantly less data. The model validation prediction errors of developed GAMs and ML models are generally below 5%; for model testing predictions, the ML models consistently outperform the regression equations in terms of root mean square errors. This new approach allows plant owners, operators, or potential investors to quickly access multiple battery configurations under different energy generation and market scenarios. This new revenue prediction method will therefore help reduce the barriers, and thereby promoting the deployment of battery hybridization with existing renewable energy sources.

13 HYDRO ENERGY↗
DOE OSTI2016

Overview of the DOE hydrogen safety, codes and standards program, part 3: Advances in research and development to enhance the scientific basis for hydrogen regulations, codes and standards

Hydrogen fuels are being deployed around the world as an alternative to traditional petrol and battery technologies. As with all fuels, regulations, codes and standards are a necessary component of the safe deployment of hydrogen technologies. There has been a focused effort in the international hydrogen community to develop codes and standards based on strong scientific principles to accommodate the relatively rapid deployment of hydrogen-energy systems. The need for science-based codes and standards has revealed the need to advance our scientific understanding of hydrogen in engineering environments. Here, this brief review describes research and development activities with emphasis on scientific advances that have aided the advancement of hydrogen regulations, codes and standards for hydrogen technologies in four key areas: (1) the physics of high-pressure hydrogen releases (called hydrogen behavior); (2) quantitative risk assessment; (3) hydrogen compatibility of materials; and (4) hydrogen fuel quality.

08 HYDROGEN↗
DOE OSTI2023

Reinforcement learning-based design of shape-changing metamaterials

During the last decade, artificially architected materials have been designed to obtain properties unreachable by naturally occurring materials, whose properties are determined by their atomic structure and chemical composition. In this work, we implement a new reinforcement learning (RL) method able to rationally design unique metamaterial structures at the nano-, micro-, and macroscale, which change shape during operational conditions. As an example, we apply this method to design nanostructured silicon anodes for Li-ion batteries (LIBs). The RL model is designed to apply different actions and predict change during operational conditions. The multi-component reward function comprises an increase in the total storage capacity of the resulting battery electrode and structural parameters, such as the minimum distance between the individual components of the nanostructure. Upon experimental validation using a polymer-based 3D printing technique, we expect that the newly discovered structures improve the current Si-based LIB anodes state-of-the-art by almost three times and almost ten times the current commercial LIB based on a graphitic anode. Furthermore, this RL-based optimization method opens up vast design space for other responsive metamaterials with tailored properties and pre-programmed structural transformation.

25 ENERGY STORAGE↗