Abstract

Conventional aircraft sizing methods face challenges in analyzing all-electric or hybrid-electric novel aircraft configurations, such as those for urban air mobility applications. The vast design space containing both continuous and discrete design variables and competing design objectives necessitates searching for not necessarily a unique optimal design but rather an array of Pareto-optimal designs. This paper uses the Parametric Energy-Based Aircraft Configuration Evaluator, an aircraft sizing framework for novel aircraft and propulsion system architectures, to pursue multi-objective optimization of a lift-plus-cruise urban air mobility aircraft with all-electric, hybrid-electric, and turbo-electric propulsion system architectures using Nondominated Sorting Genetic Algorithm II. The optimization cases considered include multiple objective functions, such as maximum takeoff mass, mission time, energy and propulsion mass fraction, and energy used per unit distance per unit payload. Optimization was performed for trip distances of 80, 120, and 150 km and battery specific energy levels of 350 and 400 Wh/kg. Except when mission time was an objective function, Pareto-optimal designs occurred near the lower bound of the velocity range. Raising that bound had an impact on the architectural composition of the final generation. All-electric architectures appeared exclusively for lower trip distances, hybrid-electric designs appeared for longer trip distances, and turbo-electric designs only appeared for combinations of longer trip distances, a higher minimum cruise speed, and a lower battery specific energy level. The sizing results were sensitive to assumptions regarding the overload capacity of lift propulsor motors in postfailure conditions.

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