TY - JOUR
T1 - Metamodel-Based Multidisciplinary Design Optimization of Geostationary Debris Removal Satellites
AU - Wei, Zhao
AU - Long, Teng
AU - Tai, Kang
AU - Shi, Renhe
N1 - Publisher Copyright:
© 1965-2011 IEEE.
PY - 2024
Y1 - 2024
N2 - To improve the geostationary Earth orbit (GEO) debris removal efficiency and mission efficacy, a metamodel-based multidisciplinary design optimization (MDO) scheme for GEO debris removal satellites is proposed. In this work, the intercouplings between system design and mission planning are fully considered to formulate the GEO debris removal satellite MDO problem involving mixed discrete and continuous design variables. The satellite system design is investigated by considering power, thermal control, and structure disciplines to obtain the subsystem performance parameters according to the removal mission requirements. In terms of the performance of the satellite system, the floating number-based task allocation model and hybrid propulsion-based orbital transfer strategy are developed for efficient removal mission planning of multiple satellites. Then, a parallel adaptive Kriging method with constraint aggregation for mixed discrete-continuous optimization problem (PAKM-CA-DC) is proposed to efficiently minimize the total mass of multiple satellites subject to a number of practical engineering constraints, including power usage, depth of discharge, thermal equilibrium temperature, and structural frequencies. Finally, the GEO debris removal satellite MDO engineering applications are implemented to validate the effectiveness and practicability of the proposed MDO scheme.
AB - To improve the geostationary Earth orbit (GEO) debris removal efficiency and mission efficacy, a metamodel-based multidisciplinary design optimization (MDO) scheme for GEO debris removal satellites is proposed. In this work, the intercouplings between system design and mission planning are fully considered to formulate the GEO debris removal satellite MDO problem involving mixed discrete and continuous design variables. The satellite system design is investigated by considering power, thermal control, and structure disciplines to obtain the subsystem performance parameters according to the removal mission requirements. In terms of the performance of the satellite system, the floating number-based task allocation model and hybrid propulsion-based orbital transfer strategy are developed for efficient removal mission planning of multiple satellites. Then, a parallel adaptive Kriging method with constraint aggregation for mixed discrete-continuous optimization problem (PAKM-CA-DC) is proposed to efficiently minimize the total mass of multiple satellites subject to a number of practical engineering constraints, including power usage, depth of discharge, thermal equilibrium temperature, and structural frequencies. Finally, the GEO debris removal satellite MDO engineering applications are implemented to validate the effectiveness and practicability of the proposed MDO scheme.
KW - Geostationary earth orbit (GEO)
KW - metamodel-based design optimization
KW - mixed discrete-continuous optimization
KW - multidisciplinary design optimization (MDO)
KW - space debris removal
UR - http://www.scopus.com/inward/record.url?scp=85192730208&partnerID=8YFLogxK
U2 - 10.1109/TAES.2024.3384945
DO - 10.1109/TAES.2024.3384945
M3 - Article
AN - SCOPUS:85192730208
SN - 0018-9251
VL - 60
SP - 4621
EP - 4639
JO - IEEE Transactions on Aerospace and Electronic Systems
JF - IEEE Transactions on Aerospace and Electronic Systems
IS - 4
ER -