Urban Air Mobility Network Asset Acquisition Optimization

Urban air mobility (UAM) has the potential to revolutionize the transportation industry, offering fast, convenient, and sustainable travel options for passengers and cargo. The development and operation of UAM networks, however, face significant challenges, including the need for infrastructure investments and the management of grid electricity usage. In this thesis, we present a comprehensive model of UAM network operations based on system-of-systems engineering principles and employ a data-driven simulation framework to analyze the expected performance of a UAM operation. Our approach optimizes the composition of the UAM network, including the number of vehicles, chargers, and sizing of solar microgrids, to minimize total acquisition costs while adhering to operational constraints such as maximum average passenger delay and grid usage for each vertiport. Through the application of our methodology to diverse case studies, we provide valuable insights into the optimal design and integration of on-site microgrids for UAM vertiport networks, highlighting their impact on carbon emissions, operating costs, and grid electricity usage. This research contributes to the development of sustainable and efficient UAM systems, supporting informed decision-making among stakeholders involved in the planning, deployment, and operation of urban air mobility networks.