Possibility-Based Sizing Method for Hybrid Electric Aircraft

At the early stage of aircraft design, the sizing process plays a critical role in determining key parameters such as mass, geometry, and propulsion system characteristics based on design requirements. However, existing sizing methods, relying on historical data, assumptions, and low-fidelity models, often fail to address uncertainties, leading to costly design modifications, particularly for electric aircraft, where technological uncertainties pose significant challenges. It is crucial to account for uncertainties at the sizing stage to ensure reliable outcomes, highlighting the need for a method that efficiently integrates uncertainty into the process. We propose a possibility-based sizing approach, which accounts for design uncertainties into sizing process, yields possible feasible design outcomes and identifies critical parameters for refinement in later stages. We verified our approach with two case studies meeting CS23 certification. The results demonstrate design feasibility through trade-offs between conservative and optimistic designs, with possibility indices from 0.75 to 1, identifying maximum and stall speeds as key limiting factors. Sensitivity analysis shows that aerodynamic design, airframe, and propulsion efficiencies significantly impact maximum takeoff mass. Propulsion system integration achieves a relative mass reduction of 0.05, outperforming hydrogen fuel cells (0.025) and battery systems (0.009). The study highlights that power density is more critical than battery energy density in high-power segments, providing valuable insights for sizing and key parameters in future hybrid electric aircraft development.