Abstract:

The multidisciplinary design optimization (MDO) method is adopted to optimize the main parameters of an all-electric propulsion satellite in order to improve the satellite’s overall performance and design efficiency. A MDO model of an all-electric propulsion satellite is built by considering the parameters of several disciplines, i.e. orbit transfer, position-keeping, space environment, power, structure, and mass, to minimize the mass of the satellite subject to the specific constraints (e.g., orbit transfer time). An augmented Lagrange multiplier based efficient global optimization (ALM-EGO) method is proposed to solve the satellite MDO problems efficiently. Several numerical benchmark problems are used to test the performance of the proposed method. The comparison results show that the ALM-EGO outperforms the competitive methods in efficiency and convergence when solving the problems with computationally expensive constraints. Finally, the ALM-EGO is used to solve the all-electric propulsion satellite MDO problem. After the optimization, the mass of the satellite is reduced by 161.09 kg and all constraints are satisfied, demonstrating the effectiveness of the ALM-EGO and models built in this paper.

Key words: All electric propulsion satellite, Multidisciplinary design optimization, Efficient global optimization, Surrogate model, Augmented Lagrange multiplier method