Network-Optimized Design of a Notional Hybrid Electric Airplane for Thin-Haul Operations

Abstract

Electric propulsion for aviation applications has gained significant momentum in the past few years owing to a convergence of technologies enabling the design of competitive aircraft. This excitement also highlights the expectations for how electrification enables novel airplane architectures and powertrains leading to significant reductions in energy usage, emissions, and ultimately operating costs. Thin-haul operations is a natural application for electric propulsion owing to the relatively short flights mitigating the need for large batteries. Hybridization of electric airplanes further mitigates the need for large batteries and enables an earlier entry into service. Aircraft designs often have capabilities that significantly exceed the needs of many missions making up their day-to-day operations. This study considers the optimization of a hybrid-electric aircraft for thin-haul operations and investigates how the airplane design can be modularized to enable a multi-design-point optimization. This allows the vehicle to operate as close as possible to its many design points. The objective is to maximize the aircraft direct operating profit by optimizing the hybridization ratio while accounting for the ability to trade payload for additional range. The analysis is then applied over a wide range of routes representative of the network of a thin-haul operator. This yields a network-optimized vehicle that maximizes direct operating profits. This aircraft is then compared to a baseline turboprop aircraft. Depending on the number of routes operated and profit margins being sought, the resulting design exhibits optimal hybridization ratios ranging nominally from 52% to 96%. The study also investigates the opportunity to trade payload for additional range by swapping some payload for additional batteries. The impact of various levels of battery specific energy densities on operating economics are also studied.