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Holistic Investigation of Ground-Based Infrastructures for Advanced Air Mobility: Methodology and Application
Citation Link: https://doi.org/10.15480/882.13873
Publikationstyp
Conference Paper
Date Issued
2024-09
Sprache
English
Author(s)
TORE-DOI
Article Number
630144
Citation
Eltgen, J.; Kloock-Schreiber, D.; et al. (2024): Holistic Investigation of Ground-Based Infrastructures for Advanced Air Mobility: Methodology and Application. Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V.: 630144
Contribution to Conference
Publisher DOI
Publisher
Deutsche Gesellschaft für Luft- und Raumfahrt - Lilienthal-Oberth e.V.
Advanced Air Mobility (AAM) addresses future transportation challenges by extending networks into the air, helping cities like Hamburg overcome infrastructural limitations. Ground-based infrastructures (GBIs) are crucial for integrating AAM, connecting air and ground transport through subsystems like landing areas, gates, and terminals, tailored to local demands. Our previous work identified necessary GBI subsystems and modeling methods, using scenario techniques to understand influences and constraints in mission planning, topology, maintenance, repair, and energy management. This paper details a simulation-based analysis of GBIs, emphasizing topologies, maintenance, and energy management interactions. AAM is modeled as a complex optimization problem within a simulation environment, using scenario analysis to set parameters and objectives. Network optimization aims to strategically plan local capacities for parking, charging infrastructure, and traffic flows, improving fleet operations. Infrastructure design integrates air and ground systems for VTOL vehicles, with key performance indicators and the Vertiport Design Problem optimizing topology. Maintenance, Repair, and Overhaul (MRO) Ports are designed to be demand-responsive, integrating ground-based infrastructure and mission management systems. Energy management systems consider energy requirements, charging power, range, state of charge, and electrical grid use. MATLAB Simulink models estimate drone energy demand across various scenarios. Subsystem interactions are defined in a workflow for overall system simulation, divided into sub-workflows, exploring synergy effects between parameters.
Subjects
Advanced Air Mobility
AAM
Ground-Based Infrastructure
GBI
Vertiport
DDC Class
629.1: Aviation
658: Marketing
621.3: Electrical Engineering, Electronic Engineering
Publication version
publishedVersion
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630144.pdf
Type
Main Article
Size
234.76 KB
Format
Adobe PDF