This talk presents the application of a mathematical optimization technique called signomial programming (SP) towards the assessment of electric propulsion architectures. Physics-based models for the electric components (e.g., motor) and mechanical components (e.g., turboshaft) that comprise these propulsion architectures, and which are compatible with the SP objective and constraint forms, are described. Standalone SP optimization shows a trade-off between minimizing mass and maximizing efficiency for these individual components. These component models are then used in turbofan, turboelectric, and geared turboelectric propulsion architecture optimization via a power balance and taking into account component dependencies (e.g., fan and motor shaft speed). Optimization of these architectures on the metrics of fuel consumption and propulsion system mass show that, for each architecture, there is a trade-off between optimal component masses and efficiencies.
