Development and calibration of a predictive physics-based model for solar array power degradation in spacecraft

Accurate modeling and simulation of solar array power degradation in spacecraft is essential for mission planning, remaining useful life assessment, and lifetime extension. A relevant example is European Space Agency (ESA)’s Cluster spacecraft fleet, launched in 2000 and operated at the European Space Operation Centre (ESOC), whose solar arrays have suffered severe degradation due to space radiation causing challenges to routine operations. However, currently available physics-based and machine learning models have been proven ineffective in modeling the drastic reduction in power generation over the long operational life of the spacecraft. In response to these limitations, this work introduces a novel simplified physics-based model whose configurable parameters are adjusted using two different calibration methods. The first method consists of a meta-heuristic optimization algorithm that searches for an optimal set of parameter values, whereas the second is based on Bayesian inference and accounts for various sources of uncertainty. The latter provides posterior estimates for model parameters and credible intervals for model predictions by exploring the posterior distribution with a Markov chain Monte Carlo algorithm. Moreover, the extrapolation of model discrepancy using a Gaussian process is investigated. The results demonstrate the effectiveness of the proposed approach in providing an accurate estimate of Cluster solar array power evolution.