Metamodel-Based Multidisciplinary Design Optimization of Geostationary Debris Removal Satellites

To improve the geostationary Earth orbit (GEO) debris removal efficiency and mission efficacy, a metamodel-based multidisciplinary design optimization (MDO) scheme for GEO debris removal satellites is proposed. In this work, the intercouplings between system design and mission planning are fully considered to formulate the GEO debris removal satellite MDO problem involving mixed discrete and continuous design variables. The satellite system design is investigated by considering power, thermal control, and structure disciplines to obtain the subsystem performance parameters according to the removal mission requirements. In terms of the performance of the satellite system, the floating number-based task allocation model and hybrid propulsion-based orbital transfer strategy are developed for efficient removal mission planning of multiple satellites. Then, a parallel adaptive Kriging method with constraint aggregation for mixed discrete-continuous optimization problem (PAKM-CA-DC) is proposed to efficiently minimize the total mass of multiple satellites subject to a number of practical engineering constraints, including power usage, depth of discharge, thermal equilibrium temperature, and structural frequencies. Finally, the GEO debris removal satellite MDO engineering applications are implemented to validate the effectiveness and practicability of the proposed MDO scheme.