Jiang, Wei and Xie, Weicheng and Sun, Shuai (2022) Parametric Optimisation Analysis of Micro/Nano-Satellite Flywheels Based on the NSGA-Ⅱ Optimisation Algorithm. Aerospace, 9 (7). p. 386. ISSN 2226-4310
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Abstract
As the key mechanism of attitude control of micro/nano-satellites, the flywheel design is mostly based on empirical formulae that do not meet the requirements of lightweight and high-performance micro/nano-satellite platforms. In this paper, the structural shape of micro/nano-satellite flywheels is analysed, and a set of flywheel optimisation methods is proposed to realise the parametric optimisation analysis of the structural shape. First, the general principle of flywheel efficiency is introduced, the optimisation evaluation factor of flywheel design is proposed, and the parametric model of a flywheel structure is established by using the finite element secondary development technology, which can be used to quickly build a finite element model of different dimensions. Second, the optimisation model of flywheels is established while introducing the approximate model algorithm, greatly improving the optimisation efficiency. Considering the phenomenon that the genetic algorithm falls below local optimisation under a large parameter range, the method of initial optimisation is proposed to reduce the upper and lower limits of the optimisation parameters. Finally, the optimal shape of the flywheel is obtained by using the parametric optimisation model of the flywheel. The finite element analysis results show that the flywheel optimisation evaluation factor proposed in this work can effectively improve the comprehensive performance of the flywheel as the optimisation target, and the corresponding optimisation method can be well applied to the engineering application and design of micro/nano-satellite platforms. This can help guide the structural optimisation design of micro/nano-satellite platforms in the future.
Item Type: | Article |
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Subjects: | Open Digi Academic > Engineering |
Depositing User: | Unnamed user with email support@opendigiacademic.com |
Date Deposited: | 07 Apr 2023 08:10 |
Last Modified: | 12 Sep 2024 04:32 |
URI: | http://publications.journalstm.com/id/eprint/506 |