Framework for Technical Performance Uncertainty in Hybrid-Electric Aircraft Development

When working at the cutting edge of technology development, it is essential to understand the state of the technical performance as project testing and modeling progresses to recognize how component changes may impact the end product. This is especially true for hybrid-electric aircraft, where the implementation and operations of the electric propulsion systems have an impactful effect on the overall system performance. This paper proposes a framework for uncertainty evaluation of a hybrid-electric vehicle through the project's lifespan. The framework uses Monte Carlo analysis with the vehicle's electrical component variables to find the uncertainty in key aircraft parameters such as mission range, fuel used, and electrical energy used during cruise. The framework is applied to a parallel hybrid De Havilland Canada Dash <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{8 - 4 0 0}$</tex> aircraft. It is determined that battery specific energy and battery efficiency uncertainty has the largest influence on the key aircraft performance parameters.