Research of A Method of Satellite Power Component Degradation Estimation based on Clustering

DOI

10.2991/iccia-19.2019.4How to use a DOI?

Keywords

Satellite power unit; clustering; cycle recognition; estimation of degradation.

Abstract

For satellite on-orbit supply unit during the period of degradation problems, based on the factors that affect supply unit output power and accepted by the satellite ground stations to related telemetry data, this paper proposes a clustering-based satellite solar power components regression estimation method. By clustering method to find a place to supply unit power generation with the working conditions, according to the influence factors of power supply components, we conduct clustering and then directly fitting attenuation of the battery, and we make the periodic fitting analysis for periodic influence factors of solar cell array. Finally, we have established the model of periodic compensation and output power degradation estimation, and carried out the attenuation estimation is carried out according to the actual engineering data. The proposed method is used to evaluate the attenuation of the solar array of an on-orbit resource satellite. This method overcomes the shortcoming that the existing method must rely on long-term data to carry out attenuation evaluation. It can be applied to the auxiliary decision-making of the health state management of the power supply system of on-orbit satellites, and has important reference value for providing the operational benefit of satellites.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Mengda Cao
AU  - Jianjiang Hui
AU  - Tao Zhang
AU  - Yu Wang
AU  - Yajie Liu
PY  - 2019/07
DA  - 2019/07
TI  - Research of A Method of Satellite Power Component Degradation Estimation based on Clustering
BT  - Proceedings of the 3rd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2019)
PB  - Atlantis Press
SP  - 16
EP  - 24
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccia-19.2019.4
DO  - 10.2991/iccia-19.2019.4
ID  - Cao2019/07
ER  -