Precision Landing Trajectory Optimization for eVTOL Vehicles with High-Fidelity Aerodynamic Models

Yufei Wu, Sabrullah Deniz, Yang Shi, Zhenbo Wang, Daning Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

In the concept of urban air mobility (UAM), electric vertical take-off and landing (eVTOL) vehicles are designed to exploit the third dimension of urban airspace, offering services such as package delivery, passenger transportation, and emergency medical missions. Due to limited onboard space and battery capacity, trajectory optimization for eVTOL flight missions must achieve mission objectives while adhering to all operational, safety, and dynamic constraints. However, in real-world scenarios, particularly during vehicle descent and landing phases, environmental factors can significantly impact the aircraft’s aerodynamic performance. Therefore, in this paper, we propose a novel approach for solving the optimal landing control problem for eVTOL vehicles, incorporating high-fidelity aerodynamic models. The aerodynamic models, driven by ordinary differential equations (ODEs), are integrated with nominal flight dynamics within an optimal control problem formulation. This formulation is solved using two methods for comparison: the OpenMDAO tool and the GPOPS-II solver. The results demonstrate the feasibility of the proposed approach.

Original languageEnglish (US)
Title of host publicationAIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2023
PublisherAmerican Institute of Aeronautics and Astronautics Inc, AIAA
ISBN (Print)9781624107047
DOIs
StatePublished - 2023
EventAIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2023 - San Diego, United States
Duration: Jun 12 2023Jun 16 2023

Publication series

NameAIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2023

Conference

ConferenceAIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2023
Country/TerritoryUnited States
CitySan Diego
Period6/12/236/16/23

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Nuclear Energy and Engineering
  • Aerospace Engineering

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