Multi-objective trajectory optimization for a hybrid propulsion system

被引:2
|
作者
Li, Taibo [1 ]
Wang, Zhaokui [2 ]
Zhang, Yulin [2 ]
机构
[1] Natl Univ Def Technol, Space Technol Inst, Changsha 410073, Hunan, Peoples R China
[2] Tsinghua Univ, Coll Aerosp Sci, Beijing 100084, Peoples R China
关键词
Hybrid propulsion system; Three-dimensional rendezvous problem; Solar sail; SOLAR SAIL; ELECTRIC SAIL; DESIGN; MISSIONS;
D O I
10.1016/j.asr.2018.06.010
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
It is attractive to use a hybrid propulsion systein (HPS) consisting of solar electric propulsion (SEP) and solar radiation pressure (SRP) in interplanetary and near-Earth missions. Compared with the equivalent pure sail and pure SEP trajectories, HPS can reduce fuel consumption and transfer time. A multi-objective optimization model for the three-dimensional rendezvous mission of hybrid propulsion system is established in this paper. The optimization index is defined as a weighted sum of transfer time and the fuel consumption. Solutions with the bang-bang thrust profile are obtained under the specific mission constraints of time and fuel consumption. The influence of weights on the optimization results is discussed, and a reasonable weight range is given based on the magnitude analysis. By combining the homotopy approach with time-optimal solar sail trajectory, the initial value of the covariates are well estimated. Numerical simulations are performed both on Earth-2000SG344 and Earth-Apophis rendezvous. The results indicate that the proposed method is advantageous to obtain solutions with different mission time and fuel consumption flexibility. (C) 2018 COSPAR. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:1102 / 1113
页数:12
相关论文
共 50 条
  • [1] Multi-objective design of a hybrid propulsion system for marine vessels
    Sciberras, E. A.
    Norman, R. A.
    [J]. IET ELECTRICAL SYSTEMS IN TRANSPORTATION, 2012, 2 (03) : 148 - 157
  • [2] A new hybrid memetic multi-objective optimization algorithm for multi-objective optimization
    Luo, Jianping
    Yang, Yun
    Liu, Qiqi
    Li, Xia
    Chen, Minrong
    Gao, Kaizhou
    [J]. INFORMATION SCIENCES, 2018, 448 : 164 - 186
  • [3] Sizing and Control of a Hybrid Ship Propulsion System Using Multi-Objective Double-Layer Optimization
    Wang, Xuezhou
    Shipurkar, Udai
    Haseltalab, Ali
    Polinder, Henk
    Claeys, Frans
    Negenborn, Rudy R.
    [J]. IEEE ACCESS, 2021, 9 : 72587 - 72601
  • [4] A multi-objective optimization energy management strategy for marine hybrid propulsion with waste heat recovery system
    Xu, Chao
    Fan, Liyun
    Feng, Yongming
    Zhu, Yuanqing
    Shen, Chongchong
    Jiang, Zejun
    [J]. APPLIED THERMAL ENGINEERING, 2024, 236
  • [5] Multi-objective trajectory planning for industrial robots using a hybrid optimization approach
    Chettibi, Taha
    [J]. ROBOTICA, 2024, 42 (06) : 2026 - 2045
  • [6] Hybrid Multi-Objective Genetic Algorithm for Multi-Objective Optimization Problems
    Zhang, Song
    Wang, Hongfeng
    Yang, Di
    Huang, Min
    [J]. 2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 1970 - 1974
  • [7] Multi-Objective Optimization of Hybrid Renewable Energy System Using an Enhanced Multi-Objective Evolutionary Algorithm
    Ming, Mengjun
    Wang, Rui
    Zha, Yabing
    Zhang, Tao
    [J]. ENERGIES, 2017, 10 (05)
  • [8] Hybrid Metaheuristics for Multi-objective Optimization
    Talbi, E-G.
    [J]. JOURNAL OF ALGORITHMS & COMPUTATIONAL TECHNOLOGY, 2015, 9 (01) : 41 - 63
  • [9] Multi-Objective Configuration Optimization of a Hybrid Energy Storage System
    Cheng, Shan
    Sun, Wei-Bin
    Liu, Wen-Li
    [J]. APPLIED SCIENCES-BASEL, 2017, 7 (02):
  • [10] Multi-objective terminal trajectory optimization based on hybrid genetic algorithm pseudospectral method
    Qiu, Jiaduo
    Xiao, Shaoqiu
    [J]. ELECTRONICS LETTERS, 2024, 60 (14)