Low-thrust propulsion, such as electric propulsion, can increase the payload a mission delivers while keeping the propellant mass low. Thanks to its higher specific impulse, it uses much less propellant than a chemical spacecraft to take cargo from Earth to other celestial bodies. The price is longer transfer times, because of the low thrust, and a high power demand that translates into large propulsion elements such as solar panels. The sizing of an electric propulsion platform is also tightly linked to the transfer trajectory and to the thrust control strategy. Most available tools either optimize the trajectory for a fixed initial mass, number of thrusters and propellant, or analyze the propulsion system in depth, not both together.
We develop methods, mainly shape-based techniques and evolutionary algorithms, to generate approximate optimal trajectories for space missions such as heliocentric transfers. We derive novel shape functions that describe the evolution of the orbital elements in three-dimensional transfers, with analytical expressions chosen by analyzing real optimal transfer trajectories. We formulate the trajectory optimization problem with the constraints of each case and propose efficient methods that give reliable solutions. We validate them on three-dimensional orbit-to-orbit and rendezvous transfers. In our published comparisons, the trajectories obtained are better than those from other existing methods. See also
Evolutionary Computations and
Optimization.
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