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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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At least 73 records · Page 4

Combined Electromagnetic and Thermal Design Optimization Studies of in-Slot Cooling for UAM Electric Motors

Abstract- Urban Air Mobility vehicles will require high specific power and high reliability electric motors. Motor specific power is limited by the temperature limits of stator windings insulation and the motor cooling system’s ability to extract heat from the motor windings. The temperature limits of the stator winding are set by both thermal-chemical aging and thermo-mechanical stresses. In-slot cooling is known to be able to both more effectively reduce the max hotspot temperature in a winding and the thermo-mechanical stress in a winding at a given hotspot temperature relative to external cooling jackets. In this paper, a combined electromagnetic, thermal, and mechanical optimization of in-slot cooled motors for UAM applications is completed. Initial thermal and mechanical studies of in-slot cooling topologies with a reference design were used to down select an in-slot cooled topology for optimization. Optimizations were carried out for a representative UAM mission profile on both the in-slot cooled topology and a traditional externally cooled motor. Results show that the in-slot cooling topology can achieve a smaller mass than a traditional water jacket cooled design, but at the cost of lower efficiency due larger required stator thicknesses and correspondingly larger stator iron loss.

Thomas Tallerico↗

Influence of the Perception Constraint, Installation Effects, and Broadband SelfNoise on Low-Fidelity, Multi-point, UAM Vehicle Perception-Influenced-Design(PID) Optimization

UAM vehicles represent a unique challenge in acoustics because there are a limited number of full-scale datasets that can be used to calibrate and validate prediction models. In addition, acoustics is considered more often in the early design loop as a higher priority concern in UAM vehicle design, whereas with traditional vehicles, acoustics is typically addressed with post-design constraints. This paper will present an approach in design optimization of a proprotor in two flight conditions, hover, and forward flight, with several acoustic objective functions that simulate community response. An adjoint-capable vortex-lattice method (VLM), implemented in VSPAERO, will be used to compute the blade forces and inflow properties required to compute tonal and broadband noise using the second-generation Aircraft NOise Prediction Program (ANOPP2). In addition, a wing is placed near the proprotor to simulate installation effects on a vehicle’s wing. The influence of rotation rate, chord distribution, twist angle, and sweep on installation, broadband noise, and choice of perception constraint from the design optimization will be shown.

acoustics↗

Combined Bernstein Polynomial, Optimal Reciprocal Collision Avoidance, Differential Dynamic Programming for Trajectory Replanning and Collision Avoidance for UAM Vehicles

This paper presents an integration of Differential Dynamic Programming (DDP) with the Optimal Reciprocal Collision Avoidance (ORCA) algorithm as the basis for a new algorithm, titled Combined Bernstein Polynomial Optimal Reciprocal Collision Avoidance DDP (COBRA-DDP), for trajectory replanning and collision avoidance for Urban Air Mobility (UAM) vehicles. State-constrained variants of DDP provide the ability to plan trajectories while avoiding obstacles, but these methods require a large increase in computational time per iteration which hinders the overall speed of the algorithm. ORCA utilizes simplified dynamics to recognize potential collisions along a trajectory and provides an optimal velocity for the avoidance of multiple vehicles. These velocity commands, however, may not result in a dynamically feasible trajectory for DDP to plan around. As such, a Bernstein polynomial curve that considers the general dynamic constraints of the vehicle is generated to approximate a trajectory based on the velocity commands. COBRA-DDP optimizes this suggested trajectory via unconstrained DDP to provide a dynamically feasible trajectory that provides collision avoidance. This new trajectory can be applied to the vehicle or used to warm start the state constrained DDP algorithms to decrease computation time. Its benefits and effectiveness of the algorithm are demonstrated on a UAM Vertical Takeoff and Landing (VTOL) vehicle simulation with highly nonlinear dynamics.

Optimal Reciprocal Collision Avoidance↗

Acoustics Technical Working Group and UAM Noise Working Group Proceedings

The NASA Acoustics Technical Working Group Meeting originally started as a program planning meeting in 1992 and has grown through the years. The purpose of these biannual meetings is to foster communication and collaboration among NASA researchers and their university, industry, and government colleagues on activities and work of current and future mutual interest. The NASA-led Urban Air Mobility (UAM) Noise Working Group (UNWG) Meeting began in 2018 as a one-day meeting immediately following the Acoustics Technical Working Group Meeting. The UNWG utilizes four subgroups that conduct regular meetings throughout the year to focus on challenges facing UAM vehicles for community noise and acceptance. The four subgroups coordinate research for development of noise prediction tools/noise reduction technologies, ground and flight test methods, human response and metrics, and regulations and policy (led by the FAA). This work is a compilation of the presentations given at ATWG/UNWG Fall 2022 held in person and via Teams at NASA Glenn Research Center. All NASA content was previously submitted through STRIVES for public presentation. This is merely a compilation. Non-NASA content has permission to distribute. Slide 208 video is included in the Available Downloads as Medial.MOV.

Advanced Air Mobility↗

Adaptive Optimization for System Performance and Combined Bernstein Polynomial, Optimal Reciprocal Collision Avoidance, Differential Dynamic Programming for Trajectory Replanning and Collision Avoidance for UAM Vehicles

The emerging urban air mobility (UAM) sector in aerospace is driving development of unconventional multi-modal vehicle configurations and autonomous flight. The combination of multi-modal vehicle dynamics, complex environment, requirements to deal with flight contingencies in an efficient and safe manner, as well as necessity for precise trajectory following and performance, are the driving influence behind adaptive optimization for system performance. We are interested in trajectory optimization algorithm that would system parameter estimation and identifying the optimal switching time between modes of hybrid dynamical systems. This presentation discusses a parameterized optimal control trajectory optimization algorithm that is an extended and generalized version of Differential Dynamic Programming (DDP), titled Parameterized Differential Dynamic Programming (PDDP). DDP is an efficient trajectory optimization algorithm relying on second order approximations of a system’s dynamics and cost function and has recently been applied to optimize systems with time invariant parameters. Experiments are presented applying PDDP to solve model predictive control (MPC) and moving horizon estimation (MHE) tasks simultaneously. In particular, PDDP is used to determine the optimal transition point between flight regimes of a complex urban air mobility (UAM) class vehicle exhibiting multiple phases of flight and to identify and compensate for actuation faults.

optimization↗

Psychoacoustic Measures for UAM noise in the Context of Ambient Sound

The noise component of future aircraft and operations from Urban Air Mobility (UAM) vehicles is widely recognized as a challenge to community acceptance. NASA’s RVLT (Revolutionary Vertical Lift Technology) program is currently supporting research in the area of human response and psychoacoustics in an effort to augment current metrics for traditional aircraft. This talk will review current work at NASA Ames’ Human Systems Integration Division to evaluate detection, annoyance, and acceptability of UAM sound, in the context of expected ambient sound conditions.

aircraft noise disturbance↗

UAM Source Noise Hemisphere Flight Test Measurement Protocol

The overall goal of the NASA Urban Air Mobility Noise Working Group (UNWG) Ground and Flight Test Subgroup (SG2) is to develop a research measurement protocol, or set of guidelines, which can be used to adequately quantify the Urban Air Mobility (UAM) community noise impact via the creation of acoustic profiles that describe the vehicle source emission characteristics. This document lays out a measurement protocol for acquiring data suitable for the development of compact noise hemispheres that characterize the source acoustic emissions from full-scale UAM or Advanced Air Mobility (AAM) vehicles in outdoor flight. It also provides a narrative describing the numerous aspects of outdoor flight test design and execution that will hopefully prove useful to flight test engineers and practitioners.

Acoustics↗

A Systems Approach to AI Model Integration and Performance Evaluation for the Generic UAM Simulation Framework

This paper introduces py-guam, an open-source experimentation framework developed for the NASA Generic Urban Air Mobility simulation (GUAM) environment, facilitating the integration and evaluation of advanced artificial intelligence (AI) algorithms. We present a systems approach which enables the seamless incorporation of data-driven models, including off-nominal and failure state detection, into the GUAM’s Cognitive Architecture (CA). The framework supports customizable experimentation parameters, derives Safety Performance Indicators (SPIs) from UL 4600 safety case analyses, and employs rapid UAM simulations to assess AI impacts on flight performance across diverse scenarios. Through comprehensive testing and validation experiments, we demonstrate GUAM’s capability to enhance safety and efficiency in urban air mobility operations. Additionally, the open-source nature of py-guam fosters community collaboration, ensuring continuous improvement and adaptability to evolving technological advancements. This work establishes a robust tool for developing and testing AI-driven urban air mobility (UAM) systems, advancing the safety and reliability of autonomous urban air vehicles.

Artificial Intelligence↗

Analysis of Strategic Conflict Management Approaches as Applied to Simulated UAM Operations

This report presents the results of a comparison analysis of candidate Strategic Conflict Management (SCM) strategies as applied to Urban Air Mobility (UAM) operations. The SCM strategies investigated included: no SCM, resource scheduling (RS), resource flow rates (FR), area-based flow rates (AR), and conflict detection and resolution (CR). The study evaluated each strategy against the same 3 levels of flight demand in a representative airspace construct for the Dallas/Fort Worth region. The study also accounted for different levels of uncertainty in operational planning and equivalent levels of trajectory following error. In the analysis, we compared the SCM strategies’ effectiveness in reducing the need for the tactical conflict management layer to act and looked at the metrics of unmitigated losses-of-separation (LOS), flight delays imposed by strategic planning, and throughput of the overall airspace. The study results indicated that the CR strategy was the most effective at reducing LOS and percentage of flights with LOS, even in the presence of trajectory error when uncertainty is accounted for in planning. Thus, if the objective is to reduce the number of actions that the tactical conflict management layer will have to take, in terms of conflicts that may need to be resolved, CR is the strategy to use. The FR strategy was found to be the worst at reducing LOS and percentage of flights with LOS. Thus, it is not very effective at reducing the actions required by a tactical conflict management layer. In the airspace tested, the demand was high enough to produce unacceptable levels of flight delay and reductions of throughput when the SCM strategies were implemented. This was especially evident at the higher levels of trajectory uncertainty and error. The need to account for expected levels of uncertainty becomes more and more important as the demand level increases and as the level of trajectory error increases. This is because the likelihood of flights with LOS increases as the density of operations increases and as the level of trajectory error increases. Accounting for uncertainty in the SCM strategies improves the strategy effectiveness with respect to LOS but increases delays and reduces throughput. Thus, there is a tradeoff between scalability and allowable levels of uncertainty. That is, we can implement an air traffic management construct that allows high levels of uncertainty, but we can expect that same system to have limits on scalability that may be evident even at small demand levels, such as those used in this study. Therefore, the results in this study indicate that an air traffic system should attempt to implement mechanisms appropriate for reducing uncertainty where possible in order to increase the chances for scalability. And this increased level of predictability of operations needs to be balanced with mechanisms for ensuring flexibility when operational conditions and plans need to change, even though those types of changes should be the exception rather than the rule under normal conditions. The study also introduced a trade space that could serve as a mechanism for selecting the appropriate SCM strategy in a trade-off between uncertainty and error, mean flight delay, and the LOS metrics (which this study equates to the potential for tactical conflict management actions). The optimal solution for a given airspace, demand level, and other factors, could likely be a combination of SCM strategies, although this study only compared the use of a single SCM strategy at a time. The CR strategy appeared to have the best opportunity for scalability by limiting the number of potential tactical actions to nearly zero.

Strategic Conflict Management↗

Parametric Study of Federated Conflict Resolution for UAM Operations

This work presents a federated conflict resolution algorithm and its parametric study for UAM operations. A federated speed-control-based conflict resolution algorithm is introduced first, including its rules of the road, data exchange requirement, and critical parameters. Two experiments were set up for the parametric study. The first investigates five parameters: look ahead time, resolution update interval, maximum allowed speed reduction, traffic flow interval, and crossing angle. The second experiment studies the uncertainty of departure time. Metrics associated with safety, efficiency, and conflict resolution effort were measured for each scenario. A Design Of Experiment (DOE) analysis was used to perform the multi-factor analysis for the first experiment. It revealed that the crossing angle and flow interval were the most critical parameters across all three metrics, followed by maximum allowed speed reduction. Look ahead time and resolution update interval were of minor significance to safety and conflict resolution effort, but had little to no effect on efficiency. The analysis of the second experiment showed that, given a flow rate, the fluctuation in departure time was absorbed by the conflict resolution algorithm, which resulted in a relatively small fluctuation in airborne delay.

Urban air mobility↗

Parametric Study of Federated Conflict Resolution for UAM Operations using DOE Analysis

This work presents a federated conflict resolution algorithm and its parametric study for UAM operations. A federated speed-control-based conflict resolution algorithm is introduced first, including its rules of the road, data exchange requirement, and critical parameters. Two experiments were set up for the parametric study. The first investigates five parameters: look ahead time, resolution update interval, maximum allowed speed reduction, traffic flow interval, and crossing angle. The second experiment studies the uncertainty of departure time. Metrics associated with safety, efficiency, and conflict resolution effort were measured for each scenario. A Design Of Experiment (DOE) analysis was used to perform the multi-factor analysis for the first experiment. It revealed that the crossing angle and flow interval were the most critical parameters across all three metrics, followed by maximum allowed speed reduction. Look ahead time and resolution update interval were of minor significance to safety and conflict resolution effort, but had little to no effect on efficiency. The analysis of the second experiment showed that, given a flow rate, the fluctuation in departure time was absorbed by the conflict resolution algorithm, which resulted in a relatively small fluctuation in airborne delay.

Urban air mobility↗

UAM Instrument Flight Procedure Design and Evaluation in the Joby Flight Simulator

NASA’s Advanced Air Mobility (AAM) National Campaign (NC) partnered with Joby Aviation to test and evaluate different developmental candidate Urban Air Mobility (UAM) Instrument Flight Procedure (IFP) designs including new departure, enroute, approach and missed approach architectures using Joby’s high-fidelity engineering aircraft simulator. In conjunction with the simulator testing, this effort also evaluated related aspects such as charting, coding, and adherence to flight planning criteria. The test objectives were to assess the safety, efficiency, passenger comfort and noise of the different variations of the developmental IFPs. Safety-related measures include clearance from terrain and vertical obstructions, procedure flyability, and flight path conformance. Efficiency-related measures included time required, airspace volume required, and battery energy required. Passenger comfort and ride quality measures include roll/pitch angles, roll/pitch attitude change rates, and airspeeds prior to aggressive maneuvers, subjective pilot/passenger responses and acceleration forces. The noise impacts of the different IFPs will be interpolated/extrapolated using data from the simulator fed into a separate Joby acoustic software-based tool. Overall, several tradeoffs were identified and characterized between the different variations of the developmental IFP profiles. No single version of the developmental IFP structure scored highest across all measures listed above; rather, different IFP variations proved optimal for different measures, confirming that the best IFP depends on which specific measures are prioritized for a given aircraft, location and operation.

National Campaign↗

High-Intensity Radiated Field (HIRF) Map - An Avoidance Approach for UAM, AAM, and UAS Vehicles

Advanced Air Mobility (AAM), Urban Air Mobility (UAM), and Unmanned Aerial Systems (UAS) vehicles will fly in similar airspace to Transport Category Rotorcraft, thereby requiring them to meet the most severe requirements for HighIntensity Radiated Fields (HIRF) certification. The environment is severe for rotorcraft, much more so than for fixed-wing aircraft, due to lower altitude operations, potentially exposing the vehicles to close and direct view of high-power transmitters on the ground. High-level HIRF exposure potentially leads to avionic system upsets, interference, and undesirable effects. Shielding and circuit protection against HIRF will be a significant barrier to size, weight, and cost, especially for emerging electric vertical take-off and landing (eVTOL) and electric short take-off and landing (eSTOL) vehicles. This paper proposes a novel approach to HIRF protection, which reduces costs by testing and certifying vehicles to a “vehicle tolerance level” that is lower than required for Transport Category Rotorcraft. The remaining protection is achieved by maintaining a safe distance from known HIRF sources, calculated based on the vehicle's tolerance level and transmitter characteristics such as transmit power, antenna beamwidth, and direction. Tailored maps are developed, identifying transmitters and avoidance zones within an operating area or along a flight path, allowing for restricted vehicle operations. The HIRF avoidance zones could be smaller for vehicles with higher tolerance levels, enabling them to operate closer to transmitters. Transmitter data can be extracted from regulatory databases like the FCC and NOAA. A map tool is developed in Matlab to calculate and plot HIRF avoidance zones from transmitters in FCC and NOAA databases as proof of concept. Illustrations are presented for AM/FM/TV transmitters, communication satellite dishes, and weather radars. Also illustrated are HIRF zones for smaller transmitters, including land-mobile radios, pagers, microwave links, and cellular towers. An example of flight planning around the transmitters is presented. This method is a substantial deviation from the standard approach and involves slightly higher flight-planning complexity, but the potential cost savings are significant. Future AAM/UAM/UAS aeronautical charts could include these new HIRF avoidance zones.

HIRF↗

High-Intensity Radiated Field (HIRF) Map - An Avoidance Approach for UAM, AAM, and UAS Vehicles

Advanced Air Mobility (AAM), Urban Air Mobility (UAM), and Unmanned Aerial Systems (UAS) vehicles will fly in similar airspace to Transport Category Rotorcraft, thereby requiring them to meet the most severe requirements for High Intensity Radiated Fields (HIRF) certification. The environment is severe for rotorcraft, much more so than for fixed-wing aircraft, due to lower altitude operations, potentially exposing the vehicles to close and direct view of high-power transmitters on the ground. High-level HIRF exposure potentially leads to avionic system upsets, interference, and undesirable effects. Shielding and circuit protection against HIRF will be a significant barrier to size, weight, and cost, especially for emerging electric vertical take-off and landing (eVTOL) and electric short take-off and landing (eSTOL) vehicles. This paper proposes a novel approach to HIRF protection, which reduces costs by testing and certifying vehicles to a “vehicle tolerance level” that is lower than required for Transport Category Rotorcraft. The remaining protection is achieved by maintaining a safe distance from known HIRF sources, calculated based on the vehicle's tolerance level and transmitter characteristics such as transmit power, antenna beamwidth, and direction. Tailored maps are developed, identifying transmitters and avoidance zones within an operating area or along a flight path, allowing for restricted vehicle operations. The HIRF avoidance zones could be smaller for vehicles with higher tolerance levels, enabling them to operate closer to transmitters. Transmitter data can be extracted from regulatory databases like the FCC and NOAA. A map tool is developed in Matlab to calculate and plot HIRF avoidance zones from transmitters in FCC and NOAA databases as proof of concept. Illustrations are presented for AM/FM/TV transmitters, communication satellite dishes, and weather radars. Also illustrated are HIRF zones for smaller transmitters, including land-mobile radios, pagers, microwave links, and cellular towers. An example of flight planning around the transmitters is presented. This method is a substantial deviation from the standard approach and involves slightly higher flight-planning complexity, but the potential cost savings are significant. Future AAM/UAM/UAS aeronautical charts could include these new HIRF avoidance zones.

HIRF↗