Aero-Propulsive Modeling for eVTOL Aircraft Using Wind Tunnel Testing with Multisine Inputs
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This presentation covers the Numerical Propulsion System Simulation (NPSS) Power Systems Library being developed by NASA. This library is a set of components, models, and interfaces for the NPSS language to enable building electric power system models for electrified propulsion systems. The presentation is to be given at the 3rd annual RVLT Toolchain Workshop, where attendees from across the eVTOL industry will be informed of NASA’s tools for eVTOL conceptual design from the vehicle level down through subsystems including propulsion, noise, electrical power, and others. It covers where the NPSS Power System Library fits into NASA’s RVLT toolchain and RVLT work in general, and will inform the audience of how the tool can be useful in their own work.
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The current aviation revolution towards electric propulsion aircraft (e.g., electric vertical takeoff-and-landing) brings unique control challenges. These vehicles are typically over-actuated (more effectors than desired control outcomes), may require control strategies for the three phases of flight (hover, transition and cruise), and currently have limited electric power availability. These vehicle challenges bring the need for optimal control allocation to the forefront of research. A leading control allocation algorithm, used in current flight vehicles, is the Cascading Generalized Inverse (CGI). Unfortunately, the Cascading Generalized Inverse algorithm is unable to achieve some desired outcomes, it intermittently provides non-optimal allocations, and it may fail to preserve moment direction near maximal achievable outcomes. In this research, the shortcomings of the Cascading Generalized Inverse algorithm are addressed by augmenting the algorithm with Scalar Difference Quadratic unsaturation identification and location at each iteration. Rigorous theory is shown that the Modified Cascading Generalized Inverse performs better at obtaining optimal allocations for all attainable outcomes. Numerical case studies for over-actuated vehicles demonstrate resolution to the aforementioned deficiencies.
The current aviation revolution towards electric propulsion aircraft (e.g., electric vertical takeoff-and-landing) brings unique control challenges. These vehicles are typically over-actuated (more effectors than desired control outcomes), may require control strategies for the three phases of flight (hover, transition and cruise), and currently have limited electric power availability. These vehicle challenges bring the need for optimal control allocation to the forefront of research. A leading control allocation algorithm, used in current flight vehicles, is the Cascading Generalized Inverse (CGI). Unfortunately, the Cascading Generalized Inverse algorithm is unable to achieve some desired outcomes, it intermittently provides non-optimal allocations, and it may fail to preserve moment direction near maximal achievable outcomes. In this research, the shortcomings of the Cascading Generalized Inverse algorithm are addressed by augmenting the algorithm with Scalar Difference Quadratic unsaturation identification and location at each iteration. Rigorous theory is shown that the Modified Cascading Generalized Inverse performs better at obtaining optimal allocations for all attainable outcomes. Numerical case studies for over-actuated vehicles demonstrate resolution to the aforementioned deficiencies.
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As the concept of on-demand electric air taxis gains popularity and begins to take shape, many research efforts are underway to address the challenges of integrating this new class of passenger-carrying air vehicles into the already congested U.S. National Airspace System. Through collaborations between the National Aeronautics and Space Administration (NASA), the Federal Aviation Administration, and industry, this concept, commonly referred to as Urban Air Mobility (UAM), envisions a safe, reliable, and efficient mode of transportation traversing metropolitan and urban areas. Among the many challenges being tackled, airspace procedures and information requirements are critical areas of research that need to be addressed. In a joint effort between NASA and Joby Aviation, a human-in-the-loop study was conducted at the NASA Ames Research Center to evaluate initial and midterm operations with air traffic controllers and on-board UAM pilots in the Dallas area. This area was chosen due to its complex Class Bravo Airspace that extends to the surface over a relatively large area. To achieve the goals and objectives of the study, multiple preceding efforts were conducted to develop the candidate procedures and information requirements. This paper provides an overview of the operational concept used for the study, the process that was followed, and the findings from the two tabletop meetings and a shakedown activity. The combination of these led to a set of airspace procedures, letters of agreement, and information requirements that were evaluated in the human-inthe-loop study.
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We propose a framework for adaptive guidance based on optimal control and estimation using closed-loop performance models. In the proposed approach, parameters of a reduced-order performance model are estimated in real time so that trajectories and guidance commands are replanned with more accurate knowledge of the system's response and performance capabilities. To apply this methodology to flight control systems, we introduce a simple yet expressive performance model modified from a reference linear design model. The proposed framework is applied to guidance of a simulated Advanced Air Mobility class concept aircraft experiencing control effector failures. We demonstrate that, by optimizing performance model parameters in real time, guidance commands can be intelligently adjusted to recover system stability and the performance of a full-order vehicle model, even in the event of effector failures. Furthermore, the reduced-order performance model requires a fraction of the computational cost of the full-order model, facilitating real-time use of adaptive, optimal guidance.
We propose a framework for adaptive guidance based on optimal control and estimation using closed-loop performance models. In the proposed approach, parameters of a reduced-order performance model are estimated in real time so that trajectories and guidance commands are replanned with more accurate knowledge of the system's response and performance capabilities. To apply this methodology to flight control systems, we introduce a simple yet expressive performance model modified from a reference linear design model. The proposed framework is applied to guidance of a simulated Advanced Air Mobility class concept aircraft experiencing control effector failures. We demonstrate that, by optimizing performance model parameters in real time, guidance commands can be intelligently adjusted to recover system stability and the performance of a full-order vehicle model, even in the event of effector failures. Furthermore, the reduced-order performance model requires a fraction of the computational cost of the full-order model, facilitating real-time use of adaptive, optimal guidance.
Aircraft were designed and sized to meet Navy mission requirements. Five missions were established for evaluation: anti-submarine warfare (ASW), surface attack (SA), combat search and rescue (CSAR), surveillance (SURV), and vertical on-board delivery (VOD). All missions were performed with a short takeoff and a vertical landing. The aircraft were defined using existing J97-GE gas generators or reasonable growth derivatives in conjunction with turbotip fans reflecting LF460 type technology. The multipurpose aircraft configuration established for U.S. Navy missions utilizes the turbotip driven lift/cruise fan concept for V/STOL aircraft.
Using a calibrated Rolls-Royce Pegasus engine and existing aircraft instrumentation and pressure taps, total and individual nozzle reaction control system (RCS) bleed flow rates have been measured on a YAV-8B Harrier during typical short takeoff, transition, hover, and vertical landing maneuvers. RCS thrust forces were calculated from RCS nozzle total pressure measurements, and control power was determined from the moments produced by these thrusts and the aircraft's moments of inertia. These data document the characteristics of the YAV-8B RCS with its basic stability augmentation system (SAS) engaged. Advanced control system designs for the YAV-8B can be compared to the original SAS based on the total bleed use and the percentage of available bleed used. In addition, the peak and mean values of the bleed and control power data can be used for sizing the reaction controls for a future short takeoff and vertical landing (STOVL) aircraft.
Modern distributed hybrid and electric propulsion aircraft, including vertical, short, and conventional takeoff and landing configurations, exhibit significant aero-propulsive complexity and a large number of interacting test factors. This paper presents the development and evaluation of experiment designs for aero-propulsive characterization of distributed propulsion aircraft. Five different foundational response surface designs are evaluated to inform the development of two sequential design approaches tailored to complex aircraft aerodynamic characterization experiments. The first approach, which builds on sequential face-centered central composite designs, has been used previously to develop aero-propulsive models for complex aircraft using wind tunnel testing. The second approach is a new design strategy leveraging a regular I-optimal and nested I-optimal design that was developed for this study. The two sequential design strategies are compared for experiments with a large number of test factors using pre-experiment design evaluation metrics, as well as modeling results obtained from simulated wind tunnel data for the NASA LA-8 aircraft. The design evaluation metrics show that the sequential I-optimal base design has higher statistical power, lower correlation among candidate regressors, lower prediction variance, and more precise parameter estimates. The simulated wind tunnel experiments conducted using each design reveal that the sequential I-optimal base design has better predictive capability with fewer test points. The experiment design and evaluation procedures are described in detail to inform future aerodynamic characterization experiments for complex aircraft.
This publication presents material that constituted the lectures presented by the author as part of Course AA 234, Dynamics, Control, and Flying Qualities of Vertical/Short Takeoff and Landing (V/STOL) Aircraft that was taught in the Department of Aeronautics and Astronautics at Stanford University. It covers representative operations of vertical and short takeoff and landing (V/STOL) aircraft, a discussion of the pilot's strategy in controlling these aircraft, the equations of motion pertinent to V/STOL tasks, and their application in the analysis of longitudinal and lateral-directional control in hover and forward flight. Following that development, which applies to the characteristics of the basic airframe and propulsion system, the text concludes with a discussion of the contributions of control augmentation in specific flight tasks and of the integration of modern electronic displays with these controls.