Sun Polar Probe Trajectory Design Based on Multi-objective Genetic Algorithm

Solar polar probe is of great importance for space physics and the forecast of space weather, but to reach that goal of high solar inclination needs a huge amount of energy. Thus the trajectory of low-thrust and gravity-assist is often used for the sake of energy. In this paper, Jupiter was chosen to be the gravity-assist planet because of its powerful gravitation and the successful experience of Ulysses Probe launched by NASA. Only interplanetary low-thrust transfer stage and gravity-assist stage were considered and linked according to the patched conic approach at the initial design stage, with Earth escape stage being neglected. Low-thrust trajectory was modeled by the so called nominal trajectory concept with linearization about the Kepler orbit, further being analyzed by optimal control using state transmition matrix. In order to reach the goal of high solar inclination, the gravity-assist at Jupiter was modeled and an adjunct angle was defined to confirm the effect of gravity-assist to reach the high solar inclination. Multi-objective genetic algorithm was applied to optimize the two indices being established for energy saving of low-thrust interplanetary transfer and the high solar inclination for the Jupiter gravity-assist. Two optimal schemes were chosen from the final population, whose trajectory parameters are analyzed afterwards. Results showed that multi-objective genetic algorithm was compatible to find promising trajectory scheme of low-thrust gravity-assist trajectory to achieve the demands of solar polar probe mission.