Abstract

Aerobraking represents a valuable option for interplanetary missions thanks to its capability of reducing the orbital semi-major axis through multiple atmospheric passages, thus with limited fuel consumption. However, due to structural and thermal loads the spacecraft undergoes, mission risks and ground operations costs increase. This study aims to tackle this aerobraking drawback by enhancing its autonomy. The main activities required for aerobraking execution, including atmospheric prediction, orbital state estimation, and orbit control, are tailored for onboard execution. Regarding orbit control, two different methodologies, differentiated by working principle and prediction horizon breadth, are investigated. The first plans orbit control manoeuvres based on the prediction of the atmospheric conditions for a single upcoming pericentre, while the second schedules and optimizes the manoeuvres considering the recent atmospheric conditions experienced by the spacecraft and the altitude trend of multiple upcoming pericentres. The whole operational concept is tested within a simulated environment, with the primary objective of accurately reproducing the intense atmospheric variations of the Martian atmosphere, which represents the most challenging aspect during aerobraking execution. The numerical testing, involving the simulation of different aerobraking regimes under varied conditions, shows that the natural dynamics of the orbital motion can be exploited to minimize both fuel consumption for orbit control manoeuvres and spacecraft load variations, thus enabling more efficient aerobraking and more stable flight conditions, even with the limited predictive capabilities that characterize onboard resources. Both control logics permit the aerobraking execution without exceeding the maximum allowed thermal limits, hence showing their effectiveness. Furthermore, a Monte Carlo analysis conducted on a complete aerobraking simulation reveals a 25.5% reduction in propellant consumption and a 9.4% reduction in heat rate variability when the orbit control decision process uses information relative to multiple future pericentres.

Full Text
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