System of Systems Simulation driven Urban Air Mobility Vehicle Design

Abstract

Urban Air Mobility (UAM) is increasingly becoming popular for Passenger or Cargo movement in dense smart cities. Several researches so far are focused on individual vehicle architectures such as multirotor or tiltrotor etc., but not much effort in a System of Systems (SoS) point of view where a homogenous fleet of vehicle with different passenger capacity, speed, and propulsive energy concepts are assessed in a framework for a successful UAM operations in a given city. An effort is made in this paper wherein, vehicle architecture is derived from the Concept of Operations (CONOPS) of scenarios such as urban and suburban operations and as well as propulsion subsystem for sustainable UAM. This paper approaches UAM aircraft design driven by SoS approach and an agent-based simulation supports the vehicle architecture evaluation and fleet definition. The outcome of this study is: multiple aircraft design with subsystem architectures, ideal fleet size for the respective operational scenarios, autonomy and battery technology effectiveness on UAM throughput (to efficiently provide UAM on-demand service maximum passengers within 15 min wait time), and importantly, sustainability metrics such as total fleet energy required. Several System of Systems, system and subsystem level sensitivity research questions are addressed to understand the interlevel coupling.

UAM Vehicle Design with Emphasis on Electric Powertrain Architectures

“…torque and speeds for the electric motors. Furthermore, the methodology has already been integrated into a higher-level simulation model in order to show the influence of the onboard systems on the design and operation of an UAM system [20]. For further research, a full-electric architecture based on batteries as well as a hybrid powertrain architecture with fuel cells and batteries will be investigated.…”

The SoS conductor: Orchestrating resources with iterative agent‐based reinforcement learning

“…Distributed, autonomous, and semi-autonomous decision-making has shifted the paradigm of system design, leading to the popularity of SoS in various engineering design applications such as the Internet of Things, 6 autonomous vehicles, 7 urban air mobility vehicle design, 8 smart grids, [9][10][11] fractionated satellite systems where detection, processing, and communication tasks are dynamically assigned to members of the satellite cluster 12,13 ; sustainable manufacturing systems, 14,15 communication networks in which the frequency spectrum is dynamically allocated for efficient use, 16 and groups of unmanned, autonomous vehicles (such as aerial drones) that dynamically assign tasks among themselves and can utilize information gathered by other group members. 17 In most of these applications, resources such as energy, communication bandwidth, computation, and memory are constrained, necessitating an efficient and adaptable resource allocation strategy to accommodate the intricate and evolving dynamics of SoS.…”

“…For outputs (dependent variables), we track the scores of agents at each time step, calculated by the distance between each landmark and the closest corresponding agents; the total costs of resources at each time step; and the overall system performance, which is the agents' scores minus the total resource costs. We modify the experiment settings according to resource budgets (2,4,6,8,10) and the level of coordination (low-level, mid-level, and high-level).…”

Development of an urban air mobility vehicle family concept by system of systems aircraft design and assessment

“…An SoS simulation framework presented in Figure 1 is utilized for this study, developed through past research of the authors [4] and extended in the accompanying work as part of the underlying proceedings [5]. The SoS simulation framework connects aircraft design methodologies with an agentbased simulation, each of these two main components are designed to be extendible where detailed analysis can be integrated within, such as but not limited to onboard system and powertrain sizing [6] into aircraft design, or detailed vertiport and trajectory simulations into the collaborative SoS simulation as part of the ongoing work in HorizonUAM. Furthermore, in previous work life cycle assessment methodologies were integrated into the SoS simulation framework to understand the impact of subsystem, system and operational parameters at the environmental impact level, however this aspect is not included in this study.…”

“…Furthermore, in previous work life cycle assessment methodologies were integrated into the SoS simulation framework to understand the impact of subsystem, system and operational parameters at the environmental impact level, however this aspect is not included in this study. For detailed explanation of the sizing methods used in this study the reader is directed to [6,7] and for the description of the modelling and simulation of the SoS simulation, including assumptions, processes and interactions of stakeholders, the reader is directed to the accompanying work [5].…”