Modeling and predicting output power losses of solar arrays in a particle filtering framework

Solar arrays are the main source of energy to on-orbit satellite. Their output power determines the use value in a great extent. Therefore, it is of great important reference value in the areas of satellite design and on-orbit satellite control to study the attenuation model of output power, to dynamically update the model based on the real-time data of output power, and to forecast the output power. This paper summarizes the influencing factors of attenuation about solar arrays output power, elaborates on the factors' trend with time and their effect on output power, and further describes the empirical model about output power varying with time. Next, it puts forward an algorithm of particle filter dynamic prediction based on the empirical model and historical data. By using the algorithm, model parameter updating and output power real-time prediction can be carried out. Finally, using six years data of solar arrays' voltage and current from a synchronous satellite in orbit, the validity of empirical model about solar arrays output power varying with time was verified based on curve fitting. Besides, the reliability and accuracy of the dynamic prediction method based on particle filter in model parameters updating and output power real-time prediction were also proved out.

[1]  Bhaskar Saha,et al.  Prognostics Methods for Battery Health Monitoring Using a Bayesian Framework , 2009, IEEE Transactions on Instrumentation and Measurement.

[2]  Kai Goebel,et al.  Modeling Li-ion Battery Capacity Depletion in a Particle Filtering Framework , 2009 .

[3]  Hongzheng Fang,et al.  Study of the long-term performance prediction methods using the spacecraft telemetry data , 2012, Proceedings of the IEEE 2012 Prognostics and System Health Management Conference (PHM-2012 Beijing).

[4]  J. D. Kozlowski.  Electrochemical cell prognostics using online impedance measurements and model-based data fusion techniques , 2003, 2003 IEEE Aerospace Conference Proceedings (Cat. No.03TH8652).

[5]  Jun Zheng,et al.  Output Power Variation Analysis on Solar Arrays of Three-axis Stabilized GEO Satellites(WSANE2006) , 2006 .

[6]  Gregory L. Plett,et al.  Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs: Part 2. Modeling and identification , 2004 .

[7]  Wu Jing.  Study on Attenuation Factor of Si Solar Array for Satellite in Sun Synchronous Orbit , 2011 .

[8]  Peter Berlin,et al.  The Geostationary Applications Satellite , 1988 .

[9]  Gregory L. Plett,et al.  Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs Part 1. Background , 2004 .

[10]  James J. Little,et al.  Autonomous vision-based robotic exploration and mapping using hybrid maps and particle filters , 2009, Image Vis. Comput..

[11]  David A. Stone,et al.  Nonlinear observers for predicting state-of-charge and state-of-health of lead-acid batteries for hybrid-electric vehicles , 2005, IEEE Transactions on Vehicular Technology.