Function-Based Architecture Optimization: An Application to Hybrid-Electric Propulsion Systems

Decisions arising in architecting processes greatly impact the success of the final product,
however are subject to high uncertainty and large combinatorial design spaces. Selecting the best
architecture for the problem at hand can be supported by architecture optimization techniques. In this
paper, we show how architecture optimization can used for designing complex aeronautical systems,
with the design of hybrid-electric aircraft propulsion systems as an application case. The function-
based architecture optimization problem is formulated using an Architecture Design Space Graph
(ADSG) created with the ADORE tool. Automatically generated architecture alternatives are
evaluated using a multidisciplinary analysis framework coupling an overall aircraft design tool to
mission and propulsion system simulation code. The multidisciplinary analysis toolchain is rebuilt
for each architecture, automatically including and coupling selecting components. Architectures are
optimized for three objectives using a multi-objective genetic algorithm. It is demonstrated that the
large architecture design space can be effectively searched and a Pareto front can be obtained.