Genetic Algorithm Optimization of Lift-Plus-Cruise VTOL Aircraft with Electrified Propulsion

Abstract

Conventional aircraft sizing methods face challenges 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 necessitate 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. The framework is used to pursue multi-objective optimization of a lift-plus-cruise urban air mobility with all-electric, hybrid-electric, and turbo-electric propulsion system architectures using Non-dominated Sorting Algorithm II. The optimization cases considered in this work included multiple objective functions such as gross weight, mission time, energy mass fraction, and energy used per unit distance per unit payload. Optimization was performed for single-trip distances of 80, 120, and 150 kilometers and battery specific energy levels of 350 Wh/kg and 400 Wh/kg. It revealed scenarios where a single architecture was present in the final generation and others where all three architectures were present. The results obtained afford valuable insights into the relative performance of the three architectures with regard to the multiple objectives and the trends of individual design variables within the optimized populations.