A Simulation-Optimization Framework for Developing Wind-Resilient AAM Networks
Fuente:
arXiv
Guardado en:
| Autores principales: | , , , , , , |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| _version_ | 1866914801816436736 |
|---|---|
| author | Onat, Emin Burak Cao, Shangqing Rizwan, Raiyan Jiang, Xuan Hansen, Mark Sengupta, Raja Chakrabarty, Anjan |
| author_facet | Onat, Emin Burak Cao, Shangqing Rizwan, Raiyan Jiang, Xuan Hansen, Mark Sengupta, Raja Chakrabarty, Anjan |
| contents | Environmental factors pose a significant challenge to the operational efficiency and safety of advanced air mobility (AAM) networks. This paper presents a simulation-optimization framework that dynamically integrates wind variability into AAM operations. We employ a nonlinear charging model within a multi-vertiport environment to optimize fleet size and scheduling. Our framework assesses the impact of wind on operational parameters, providing strategies to enhance the resilience of AAM ecosystems. The results demonstrate that wind conditions exert significant influence on fleet size even for short-distance flights, their impact on fleet size and energy requirements becomes more pronounced over longer distances. Efficient management of fleet size and charging policies, particularly for long-distance networks, is needed to accommodate the variability of wind conditions effectively. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_11118 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Simulation-Optimization Framework for Developing Wind-Resilient AAM Networks Onat, Emin Burak Cao, Shangqing Rizwan, Raiyan Jiang, Xuan Hansen, Mark Sengupta, Raja Chakrabarty, Anjan Systems and Control Environmental factors pose a significant challenge to the operational efficiency and safety of advanced air mobility (AAM) networks. This paper presents a simulation-optimization framework that dynamically integrates wind variability into AAM operations. We employ a nonlinear charging model within a multi-vertiport environment to optimize fleet size and scheduling. Our framework assesses the impact of wind on operational parameters, providing strategies to enhance the resilience of AAM ecosystems. The results demonstrate that wind conditions exert significant influence on fleet size even for short-distance flights, their impact on fleet size and energy requirements becomes more pronounced over longer distances. Efficient management of fleet size and charging policies, particularly for long-distance networks, is needed to accommodate the variability of wind conditions effectively. |
| title | A Simulation-Optimization Framework for Developing Wind-Resilient AAM Networks |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2405.11118 |