Impact of Technological Uncertainty on Design Parameter Selection of the NASA Parallel Hybrid-Electric Propulsion EPFD Vehicle

Abstract

While electrified aircraft propulsion (EAP) technologies appear as a promising solution to enable more sustainable commercial aviation in the near term, their continued development within this time frame remains subject to technological barriers. As a result, the performance of future vehicles making use of these technologies, such as the EPFD vehicle, is inherently uncertain. Previous efforts have focused on the application of sensitivity analysis and uncertainty quantification methods to develop insights and assess the potential benefits that such hybrid-electric propulsion architectures may provide over conventional aircraft. These initial efforts consisted in propagating technological uncertainty on a previously fixed vehicle design, the nominal design point. In this paper, we show that this approach suffers from two main limitations: 1) performance projections are impacted by the choice of the nominal design point, and 2) design constraints are likely to be violated by the design combinations resulting from the uncertainty propagation process. To address these limitations, we propose two alternate approaches to uncertainty propagation that better account for the EPFD vehicle design problem, including the associated constraints. The first, design optimization under uncertainty (DO-U), relies on principles from robust design and reliability-based design to find a nominal design point that is robust to technological uncertainty. The second, uncertainty propagation on design optimization (UP-DO), does not seek a nominal design point: instead, it aims at quantifying the impact of technological uncertainty on the optimal vehicle designs, i.e. designs that were optimized to maximize performance given a known set of available technologies. It was found that both proposed approaches effectively address the previously identified limitations. If a nominal design point is required, then DO-U should be preferred. However, if the goal is solely to assess the benefits of EAP technologies, then uncertainty propagation on design optimization (UP-DO) better accounts for the full potential of these technologies, as it does not impose a potentially unnecessary requirement for robustness.