System Identification for eVTOL Aircraft Using Simulated Flight Data

Benjamin M Simmons

NASA NTRS · 20210024304

System Identification for eVTOL Aircraft Using Simulated Flight Data

Abstract

This paper describes a system identification method for electric vertical takeoff and landing (eVTOL) aircraft. The approach merges fixed-wing and rotary-wing modeling techniques with new strategies to develop a modeling method for eVTOL vehicles using flight test data. The eVTOL aircraft system identification approach is demonstrated through application to the NASA LA-8 tandem tilt-wing, distributed electric propulsion aircraft using a high-fidelity flight dynamics simulation. Orthogonal phase-optimized multisine inputs are applied to each control surface and propulsor at numerous flight conditions throughout the flight envelope to collect informative flight data. An aero-propulsive model is identified at each flight condition using the equation-error method in the frequency domain. The local model parameters are then blended to create a global model across the nominal flight envelope. Parameter estimation results are shown to provide a good fit to modeling data and have good prediction capability. The methodology is developed with a discussion of unique eVTOL vehicle aerodynamic characteristics and practical strategies intended to inform future flight-based system identification efforts for eVTOL aircraft.

Explore related subjects

system identification aero-propulsive modeling flight test LA-8 vertical takeoff and landing distributed electric propulsion multisine inputs eVTOL aerodynamic characterization

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Benjamin M Simmons. System Identification for eVTOL Aircraft Using Simulated Flight Data. https://ntrs.nasa.gov/citations/20210024304

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

NASA NTRS2024

Comparison of Multisine Peak Factor Minimization Algorithms for Aircraft System Identification

Two phase-optimized multisine peak factor minimization algorithms are presented and evaluated. The first algorithm minimizes peak factor by iteratively clipping the peaks of generated multisine signals. The second algorithm optimizes peak factor indirectly through minimization of an approximation of the infinity norm of the multisine. Algorithm performance was evaluated as a function of different signal properties, including the number of harmonics, harmonic spacing, and number of snow harmonics (extra harmonics included for further reduction of the peak factor). The two algorithms are compared against results obtained by minimizing peak factor directly using a simplex algorithm, which has been a common approach when designing phase-optimized multisines for system identification flight tests. Sample results show that the clipping and infinity norm algorithms produced multisine signals with comparable peak factors that were lower than that of the simplex algorithm. However, the clipping algorithm runs an order of magnitude faster than the other two algorithms, which also makes it practical to repeat the algorithm multiple times to achieve even lower peak factors.

system identification↗

NASA NTRS2023

Advances in Aero-Propulsive Modeling for Fixed-Wing and eVTOL Aircraft Using Experimental Data

Small unmanned aircraft and electric vertical takeoff and landing (eVTOL) aircraft have recently emerged as vehicles able to perform new missions and stimulate future air transportation methods. This dissertation presents several system identification research advancements for these modern aircraft configurations enabling accurate mathematical model development for flight dynamics simulations based on wind-tunnel and flight-test data. The first part of the dissertation focuses on advances in flight-test system identification methods using small, fixed-wing, remotely-piloted, electric, propeller-driven aircraft. A generalized approach for flight dynamics model development for small fixed-wing aircraft from flight data is described and is followed by presentation of novel flight-test system identification applications, including: aero-propulsive model development for propeller aircraft and nonlinear dynamic model identification without mass properties. The second part of the dissertation builds on established fixed-wing and rotary-wing aircraft system identification methods to develop modeling strategies for transitioning, distributed propulsion, eVTOL aircraft. Novel wind-tunnel experiment designs and aero-propulsive modeling approaches are developed using a subscale, tandem tilt-wing, eVTOL aircraft, leveraging design of experiments and response surface methodology techniques. Additionally, a method applying orthogonal phase-optimized multisine input excitations to aircraft control effectors in wind-tunnel testing is developed to improve test efficiency and identified model utility. Finally, the culmination of this dissertation is synthesis of the techniques described throughout the document to form a flight-test system identification approach for eVTOL aircraft that is demonstrated using a high-fidelity flight dynamics simulation. The research findings highlighted throughout the dissertation constitute substantial progress in efficient empirical aircraft modeling strategies that are applicable to many current and future aeronautical vehicles enabling accurate flight simulation development, which can subsequently be used to foster advancement in many other pertinent technology areas.

system identification↗

NASA NTRS2021

System Identification for Propellers at High Incidence Angles

Propellers used for electric vertical takeoff and landing (eVTOL) aircraft propulsion systems experience a wide range of aerodynamic conditions, including large incidence angles relative to oncoming airflow. In oblique flow, propellers exhibit deviations in thrust and torque oriented along the propeller axis of rotation, as well as significant off-axis forces and moments. Although important for modeling eVTOL aircraft aerodynamics, sparse experimental data or mathematical models exist for propellers at incidence. This paper describes a propulsion system modeling methodology for the LA-8 tandem tilt-wing, eVTOL aircraft. System identification methods are applied to isolated propeller wind tunnel data gathered across the vehicle's flight envelope to develop a mathematical model of the propulsion system, including a static motor model, dynamic motor model, and propeller aerodynamic model. Modeling results validated against data withheld from the modeling process indicate good predictive capability and agree with theoretical expectations. The results are followed by a discussion of model implementation strategies into high-fidelity eVTOL aircraft simulations.

system identification↗