A Simulation-Optimization Framework for Developing Wind-Resilient AAM Networks

TL;DR

This paper introduces a simulation-optimization framework that accounts for wind variability to improve the resilience and operational efficiency of advanced air mobility networks, optimizing fleet management and charging strategies.

Contribution

It presents a novel framework integrating wind variability into AAM operations, including a nonlinear charging model and multi-vertiport optimization, to enhance network resilience.

Findings

Wind significantly affects fleet size for short flights.

Long-distance flights are more impacted by wind on fleet and energy needs.

Effective fleet and charging management is crucial for resilient long-distance AAM networks.

Abstract

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.