Optimal Control for Electrically Propelled Aircraft and Urban Air Mobility Network

Abstract

This dissertation aims to address fundamental challenges in the field of Urban Air Mobility (UAM) through optimal control strategies. Three key aspects are studied to enhance the operation and performance of UAM. First, a trajectory optimization algorithm for All-Electric Aircraft (AEA) is proposed, along with the corresponding Simulink models, to minimize the operating cost of AEA. The impact of battery dynamics on optimal trajectories is explored by integrating several battery models with distinct fidelity into the corresponding optimal control problems. Second, an energy management system is designed for Hybrid-Electric Aircraft (HEA) to optimize fuel consumption. Numerical results for two HEA models indicate the limited fuel-saving achieved by using the engine to charge the battery during flight. This observation leads to the investigation of two parallel hybrid electric configurations, aiming to answer the question of whether it is worthwhile to charge the battery during flight at all. A finite-dimensional optimization problem is formulated, and numerical results indicate that increasing onboard battery capacity is more fuel-efficient than in-flight charging. Finally, two important topics related to the UAM are investigated: optimal vertiport selection problem and task assignment and vehicle routing problem. For the vertiport selection problem, a mixed-integer programming approach is developed and applied to a hybrid ground-air network to improve the traffic performance. As for the task assignment problem, a centralized approach is adopted to assign a sequence of tasks to each vehicle, maximizing the overall profit. The problem is transformed into an identification of multiple paths in a task network and is solved using a greedy algorithm.