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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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This presentation discusses use of Core Flight Systems in NASA Langley Research Center's drone flight test environment for autonomy algorithms research.
This paper addresses the problem of building trust in online predictions of the remaining available flying time for two different electric Unmanned Aerial Vehicles (eUAVs) powered by lithium-ion-polymer batteries. Flight tests for various automation research missions for the two vehicles were monitored using two on-board battery health management applications to make predictions of the remaining flying time (RFT) for each eUAV and to predict the state of the battery. Playback of the voltage, current and temperature profiles of the battery discharge were used to assess the accuracy of the estimation of the voltage and the charge states of the models as well as the estimate of the RFT. The reference ground truth values were the observed landing time and the measured battery pack resting pack voltage 20 minutes after the flight. The predicted RFT, state of charge (SoC), and state of energy (SoE) were compared with the observed results. Noise values of one standard deviation from the mean values of the internal charge states of the battery model during a reference run were used to vary the states during simulation. One application used an equivalent circuit model of the electrical dynamics of the battery pack, and the other application used a reduced-order electrochemistry model. The variation of the model state components was compared to the variation in the estimate of the RFT and the variation in the SoE to estimate a confidence factor. Variation in the estimates caused by factors affecting the off-line laboratory parameter identification experiments is considered. Variation in the estimates due to environmental factors are discussed.
Wildfire response depends on how fast an ignition can be confirmed and located, especially in remote regions where ground-based communication and monitoring may be limited. Geostationary sensors provide frequent observations but at kilometer-scale resolution, which is too coarse to resolve small fires in remote terrain. Ground camera networks require sightlines and infrastructure that back-country areas lack. To address these limitations, this work proposes a Multi-Tier Autonomous Wildfire Intelligence System that combines wide-area monitoring with targeted, high-resolution sensing. A solar-powered high-altitude long endurance (HALE) platform operating at approximately 60,000 ft provides persistent wide-area thermal and optical surveillance, running onboard edge inference to screen candidate ignitions and reduce false positives and downlink bandwidth. When a candidate ignition is detected, low-altitude uncrewed aircraft systems (UAS) can be deployed to conduct localized observations, including high-resolution imaging and atmospheric measurements such as wind and plume observation. By combining persistent detection with local sensing, the proposed architecture is designed to provide first responders with timely, high-resolution information about fire location and behavior to aid in emergency decision making.
The hardware for the three Autonomous Visibility Monitoring (AVM) observatories was redesigned. Changes in hardware design include electronics components, weather sensors, and the telescope drive system. Operation of the new hardware is discussed, as well as some of its features. The redesign will allow reliable automated operation.
NASA’s long-term goal is to deploy humans to the Moon and, from there, advance human exploration to Mars, with Artemis missions as pivotal milestones. Raman spectroscopy can uniquely identify minerals, compounds, water states, and other materials, providing distinctive fingerprints for classification. A Raman instrument has been successfully deployed and utilized on the Mars surface via the Perseverance rover, but has not yet been utilized at the lunar surface The SUCR DALI project is working towards developing a Raman spectroscopy instrument to be applied in various lunar mission concepts, including within the Artemis program. The objective of my research is to assist in the maturation of the proposed SUCR DALI lunar Raman instrument through the development of an autonomous detection and classification model capable of identifying minerals and water states on the Moon’s surface.
The goal of the Autonomous Power System (APS) program is to develop and apply intelligent problem solving and control to the Space Station Freedom Electrical Power System (SSF/EPS) testbed being developed and demonstrated at NASA Lewis Research Center. The objectives of the program are to establish artificial intelligence technology paths, to craft knowledge-based tools with advanced human-operator interfaces for power systems, and to interface and integrate knowledge-based systems with conventional controllers. The Autonomous Power EXpert (APEX) portion of the APS program will integrate a knowledge-based fault diagnostic system and a power resource planner-scheduler. Then APEX will interface on-line with the SSF/EPS testbed and its Power Management Controller (PMC). The key tasks include establishing knowledge bases for system diagnostics, fault detection and isolation analysis, on-line information accessing through PMC, enhanced data management, and multiple-level, object-oriented operator displays. The first prototype of the diagnostic expert system for fault detection and isolation has been developed. The knowledge bases and the rule-based model that were developed for the Power Distribution Control Unit subsystem of the SSF/EPS testbed are described. A corresponding troubleshooting technique is also described.
This document details the timeline of the LiDAR-Powered Autonomous Charging Service Capability for Surface Rovers and Systems project, initiated by the Fall 2025 semester class and completed by the Spring 2026 semester class. This project focuses on developing a fully autonomous system composed of a mobile surface rover and an induction charging station with a robotic arm, both controlled by their own NVIDIA Jetson Orin Nano. Structural improvements to the rover suspension system and body eliminated excessive camber, reduced stress and strain on the plexiglass body, and improved maneuverability and durability of the rover. The charging station robotic arm was fully redesigned to increase reach while minimizing weight and increasing misalignment tolerance during docking on uneven terrain. Electrical system improvements addressed previous torque and power limitations of both the rover and charging station arm. High-torque servo motors were selected based on updated calculations which incorporated terrain slope and Factor of Safety, enabling zero-point turning for the rover and increased payload capacity of the charging station arm. Significant progress was made in autonomy and perception. The rover now employs 3D LiDAR and SLAM mapping for localization, mapping, and path planning. The Battery Monitoring System (BMS) was created to coordinate battery management between the rover and charging station. The BMS provides continuous monitoring of battery state of charge, temperature, current, and will enable the autonomous initiation, execution, and termination of the charging cycle via Bluetooth communication. Testing of the WIBOTIC induction charging system demonstrated reliable power transfer under both aligned and misaligned conditions. This project demonstrated the ability of an autonomously navigating surface rover to independently plan a path to the charging station, dock, and the charging station to autonomously deploy a robotic charging arm and initiate charging of the rover. This work details the progress made to demonstrate the feasibility of autonomous surface rover navigation and recharging systems.
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Conference on reduction and suppression of aircraft engine noise
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This report provides a regulatory gap assessment of the Federal Aviation Administration (FAA) and the European Union Aviation Safety Agency (EASA) Special Conditions (SC) for electric engines. This information is presented to support ongoing international harmonization efforts for electric engine certification, to establish a level of safety consistent across regulatory bodies and equivalent to that of existing combustion engines. HS Advanced Concepts LLC assembled a team of subject-matter experts to develop a comprehensive comparison of the regulatory text of EASA SC E-19 and the FAA special conditions for the certification of electric engines. The team included Mr. Chris Baczynski of BAC Aerospace Inc. and Mr. Zach Kaufman, formerly with magniX.
This presentation summarizes in-house testing performed at NASA’s Glenn Research Center on silicon anode cells for a new electric aircraft battery design funded by the Transformational Tools & Technologies (TTT) task of the Transformative Aeronautics Concept Program.
Battery pack gravimetric energy density is one of the most important, yet often miss-estimated design parameters for sizing all-electric aircraft. Proper accounting for thermal, structural, and operational safety margins are frequently lost when extrapolating performance from the cell level to the aircraft level. This paper summarizes the relevant engineering and certification details needed to better account for the penalties associated when assembling battery packs. The relationship between the cell and pack energy density is not linear, as is often assumed. Furthermore, the relationship varies depending on pack requirements, cell chemistry, and architecture. Parametric, high-fidelity models are used to determine optimal battery pack sizes over a range of conditions to better quantify technology scaling effects.
Battery pack gravimetric energy density is one of the most important, yet often miss- estimated design parameters for sizing all-electric aircraft. Proper accounting for thermal, structural, and operational safety margins are frequently lost when extrapolating performance from the cell level to the aircraft level. This paper summarizes the relevant engineering and certification details needed to better account for the penalties associated when assembling battery packs. The relationship between the cell and pack energy density is not linear, as is often assumed. Furthermore, the relationship varies depending on pack requirements, cell chemistry, and architecture. Parametric, high-fidelity models are used to determine optimal battery pack sizes over a range of conditions to better quantify technology scaling effects.
This paper briefly describes the NASA F-8 Digital Fly-By-Wire (DFBW) program and Langley Research Center's role in investigating and promoting advanced control laws for possible flight experimentation. The primary purpose of the paper is to provide background material for papers describing some of the F-8 DFBW adaptive control law studies. The paper provides a brief description of the Phase II DFBW F-8 aircraft and its control system, discusses some of the advanced control law study objectives and guidelines, and provides some mathematical models which are useful in the control analysis problem.
This paper briefly describes the NASA F-8 Digital Fly-By-Wire (DFBW) and Langley Research Center's role in investigating and promoting advanced control laws for possible flight experimentation. The primary purpose of the paper is to provide background material for the papers that follow which describe some of the F-8 DFBW adaptive control law studies. The paper provides a brief description of the Phase II DFBW F-8 aircraft and its control system, discusses some of the advanced control law study objectives and guidelines, and provides some mathematical models which are useful in the control analysis problem.