Fuel optimum low-thrust elliptic transfer using numerical averaging

Low-thrust electric propulsion is increasingly being used for spacecraft missions primarily due to its high propellant efficiency. As a result, a simple and fast method for low-thrust trajectory optimization is of great value for preliminary mission planning. However, few low-thrust trajectory tools are appropriate for preliminary mission design studies. The method presented in this paper provides quick and accurate solutions for a wide range of transfers by using numerical orbital averaging to improve solution convergence and include orbital perturbations. Thus, preliminary trajectories can be obtained for transfers which involve many revolutions about the primary body. This method considers minimum fuel transfers using first-order averaging to obtain the fuel optimum rates of change of the equinoctial orbital elements in terms of each other and the Lagrange multipliers. Constraints on thrust and power, as well as minimum periapsis, are implemented and the equations are averaged numerically using a Gausian quadrature. The use of numerical averaging allows for more complex orbital perturbations to be added in the future without great difficulty. The effects of zonal gravity harmonics, solar radiation pressure, and thrust limitations due to shadowing are included in this study. The solution to a transfer which minimizes the square of the thrust magnitude is used as a preliminary guess for the minimum fuel problem, thus allowing for faster convergence to a wider range of problems. Results from this model are shown to provide a reduction in propellant mass required over previous minimum fuel solutions.

► A quick and accurate method for obtaining minimum fuel orbit transfers is presented.
► Numerical averaging is used to improve convergence behavior.
► Shadowing, solar radiation pressure and zonal gravity effects are considered.
► A periapsis penalty function is utilized.
► Results are shown to provide a reduction propellant mass over previous solutions.