A Numerical Framework for Multiparametric Optimization of Distributed Electric Propulsion

We investigate the interaction of tractor propellers in a distributed propulsion configuration with a lifting surface. An optimization framework is constructed based on genetic algorithms. An aeropropulsive model for propeller–wing systems in a tractor configuration is developed based on a vortex lattice method lifting-line for the aerodynamic lifting surfaces, coupled with a blade element momentum theory model to describe the propellers. We define the optimum based on different figures of merit, namely the lift, the propulsive efficiency, and the aerodynamic efficiency. Configurations with the number of propellers ranging from 2 to 12 are explored, showing that a 10% increase in lifting capabilities is achievable with the use of distributed propulsion on a wing representative of a regional transport aircraft. By using a data-driven optimization scheme, a quick assessment of a vast number of conditions becomes possible, enabling one to tackle the problem from a multi-objective optimization point of view. This opens a discussion that is not necessarily centered on the value of the optimized metric but on the combination of parameters and physical relations that constitute an optimized case. We conclude by extending the numerical model into a panel code to assess the implications of distributed propulsion on the horizontal tail of an aircraft.