Multi-Objective Design and Trajectory Optimization of Space Transport Systems with RBCC Propulsion via Evolutionary Algorithms and Pseudospectral Methods

In this study, a multi-objective design optimization coupling evolutionary algorithms and trajectory optimization via pseudo-spectral methods has been conducted for the first stage of two-stage to orbit (TSTO) system with a rocket-based combined cycle (RBCC) engine which combines rockets and ramjets by blending two kinds of vehicle configurations with different aerodynamic characteristics. The design criteria include the minimization of fuel consumption and the maximization of the final Mach number up to a separation of the TSTO system at the maximum altitude under certain ranges of acceleration and dynamic pressure. The optimization results reveal a counteractive trend between the final Mach number and fuel mass ratio and the major impact of effective specific impulse on those two objectives, which is mainly controlled by thrust throttling parameter within the trajectory optimization. In addition, the RBCC-powered vehicle tends to fly at lower altitude to attain the minimum fuel mass ratio, in contrast to the case for maximum final Mach number, which is attributed to the hybrid aerodynamic performance of the two configurations. The insight gained here can be usefully applied to the design of high-performance RBCCpowered vehicles.