Multidisciplinary design and metamodel assisted optimization for a telecommunication satellite with large-size payload

• Published in: Acta astronautica Vol. 228; pp. 900 - 917
• Main Authors: Shi, Renhe, Tai, Xinhui, Long, Teng, Ye, Nianhui, Dong, Fuxiang
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2025
• ISSN: 0094-5765
• DOI: 10.1016/j.actaastro.2024.12.042

With the increasing demands for high-speed data transmission and global communication, GEO telecommunication satellites with large-size antenna payload have attracted much attention nowadays. To address the challenge of effective system design, this paper proposes a metamodel assisted multidisciplinary design optimization (MDO) framework for a Large-size Payload Telecommunication Satellite (LSP-TS). In the framework, the LSP-TS MDO problem is formulated to minimize the total system mass subject to several practical engineering constraints. Considering the interconnected relationship between the large-size payload and the satellite platform, the analysis models of satellite geometry configuration, power, attitude control, structure, GEO station-keeping, orbital transfer, and mass disciplines are established. To reduce the computational cost, an adaptive Kriging method using Pareto fitness-based sampling (AKM-PFS) is proposed as the optimizer integrated with the satellite MDO framework. In this approach, the Kriging metamodels of LSP-TS system are constructed and adaptively refined for optimization via exploring the Pareto frontier of objective and constraints, which leads the search to the feasible optimized satellite system design efficiently. After optimization, the total system mass is reduced by 318.53 kg (8.87 %) compared with the initial solution where all constraints being satisfied. Moreover, the optimization solution of the proposed AKM-PFS is further discussed to illustrate the practicality and effectiveness of the proposed method. •A metamodel-assisted multidisciplinary design optimization framework is developed for the design of a large-size payload telecommunication satellite.•An innovative adaptive Kriging method utilizing Pareto fitness-based sampling is introduced to enhance the efficiency of the multidisciplinary design optimization process.•The proposed optimization algorithm demonstrates superior performance in optimality and efficiency compared with the competitive algorithms.