Research Article
Low-Orbit Satellite Solar Array Current Prediction Method Based on Unsupervised Learning
@INPROCEEDINGS{10.1007/978-3-030-69072-4_11, author={Guan Wu and Jun Chen and Wei Zhang and Xing Hu and Jing Zhao}, title={Low-Orbit Satellite Solar Array Current Prediction Method Based on Unsupervised Learning}, proceedings={Wireless and Satellite Systems. 11th EAI International Conference, WiSATS 2020, Nanjing, China, September 17-18, 2020, Proceedings, Part II}, proceedings_a={WISATS PART 2}, year={2021}, month={2}, keywords={Current Prediction Reflection Solar array}, doi={10.1007/978-3-030-69072-4_11} }- Guan Wu
Jun Chen
Wei Zhang
Xing Hu
Jing Zhao
Year: 2021
Low-Orbit Satellite Solar Array Current Prediction Method Based on Unsupervised Learning
WISATS PART 2
Springer
DOI: 10.1007/978-3-030-69072-4_11
Abstract
With the continuous development of the space industry, the role of satellite become more and more important in China’s national economic construction, disaster prevention and mitigation. Power system is one of the important sub-systems that directly impact the in-orbit safe and affection of satellites. Satellite solar array determine the current output of whole satellite. The paper shows the solar array current prediction method based on unsupervised learning which can solve the low-orbit satellite solar array current prediction problem. This method introduces the competition elements that establish the mapping relation between the historical data and the competition element, obtains the best sample through the competition between the competition elements in the prediction processes, the relation functions take the best sample data as the benchmark which can realize the prediction of solar cell array output. Through competition the information of temperature, earth reflection, conversion efficiency and attenuation factors in the sample data are introduced effectively, and the description of such factors in the prediction process is avoided. Through the actual data analysis, we realize the extrapolation of the one-year current mean error is not more than 0.4 a, and the maximum error is not more than 0.5 a. The prediction algorithm for the solar cell array of low orbit satellites without the mathematical description of temperature, earth reflection, conversion efficiency and attenuation factors can predict the reasonable introduction of the above factors.
