Next Article in Journal
Implementation of SOH Estimator in Automotive BMSs Using Recursive Least-Squares
Previous Article in Journal
A Review of Automatic Phenotyping Approaches using Electronic Health Records
Previous Article in Special Issue
An Effective Multiclass Twin Hypersphere Support Vector Machine and Its Practical Engineering Applications
Open AccessArticle

A Life Prediction Model of Flywheel Systems Using Stochastic Hybrid Automaton

1
College of Astronautics Engineering, Nanjing University of Aeronautics & Astronautics, Nanjing 210016, China
2
China Academy of Space Technology, Beijing 100094, China
*
Author to whom correspondence should be addressed.
Electronics 2019, 8(11), 1236; https://doi.org/10.3390/electronics8111236
Received: 19 September 2019 / Revised: 19 October 2019 / Accepted: 24 October 2019 / Published: 29 October 2019
(This article belongs to the Special Issue Fault Detection and Diagnosis of Intelligent Mechatronic Systems)
This paper proposes a practical life prediction model for Flywheel Systems (FSs) using the Stochastic Hybrid Automaton (SHA) method. The reliability of motors and the performance degradation of bearings are considered key causes of the failure of FSs. The unit flywheel SHA model is established for the failure mechanism, considering burst failure of motors and the accumulated performance degradation of bearings. This prediction model also describes the dynamic relation of lifetime with the configurations of FSs, work modes, and running environments. Monte Carlo simulation results demonstrate that the life distributions of FSs are quite different if the spacecrafts run in various orbits or with different configurations, or under changed work modes. The proposed method provides an engineering reference and guidance for the scheme design and in-orbit mission planning of FSs. View Full-Text
Keywords: life prediction; stochastic hybrid automaton; dynamic fault tree; flywheel subsystem life prediction; stochastic hybrid automaton; dynamic fault tree; flywheel subsystem
Show Figures

Figure 1

MDPI and ACS Style

Cheng, Y.; Jiang, B.; Han, X.; Wang, Z. A Life Prediction Model of Flywheel Systems Using Stochastic Hybrid Automaton. Electronics 2019, 8, 1236.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop