Thermal state estimation based on Assisted Ensemble Kalman Filter

Abstract

Thermal analysis of spacecraft is one of the most important processes to ensure the safety of spacecraft systems. However, the thermal mathematical model has uncertainty such as thermal contact conductance or thermal optical properties. These uncertain parameters in the model are non-negligible for long-term missions because these parameters can change during operation on orbit. Despite the uncertainties, the spacecraft system has only a few onboard temperature sensors compared to large and complex systems. In this study, an advanced thermal analysis method based on data assimilation is proposed to estimate the thermal state of a complex system with limited temperature data. Firstly, this paper describes a new state estimation algorithm called Assisted Ensemble Kalman Filter, which is an advanced state estimation algorithm based on Ensemble Kalman Filter (EnKF). Here, an external estimation algorithm by calculating the heat balance equation was applied to the conventional method to improve the estimation performance of the EnKF. Secondly, we propose a new parameter that indicates observability based on heat flux and temperature sensitivity, and the influence of temperature sensor location on estimation performance was discussed. These proposed approaches were applied to a simple thermal mathematical model, and numerical experiments have confirmed their availability.

Keywords

• data assimilation
• thermal analysis
• sensor location
• spacecraft