Abstract: Abstract: The stable operation of the flywheel system has a great impact on the on orbit safety of spacecraft, so it is very important to assess the health status of the flywheel system. When modeling the flywheel system health sta-tus assessment, it is required that the model not only deal with various uncertainties to ensure the accuracy of the assessment results, but also have a transparent and reasonable assessment process and explicable and traceable assessment results. Therefore, based on the in-depth study of the modeling method of belief rule base (BRB), this paper constructs a new explicable belief rule base (BRB-e) flywheel system health assessment model based on expli-cable modeling. Firstly, the explicable modeling criteria are defined according to the characteristics of flywheel system; On this basis, the reasoning process of BRB-e assessment model is designed; Then, based on the whale optimization algorithm (WOA), a parameter optimization method of BRB-e model with explicable constraints is proposed; Finally, the effectiveness of the model in the flywheel system health status assessment is verified by a case study of bearing components in a flywheel system. The comparative study shows that BRB-e model has certain advantages in the ac-curacy of assessment results and the explainability of assessment process.

Key words: flywheel system, health status assessment, belief rule base, explicable modeling criteria, whale optimization algorithm