Development of simulation platform for physicochemical regenerative environment control and life support system in space station

Lv, Mingbo; Li, Yunhua; Liu, Wei; Guo, Rui; Yang, Liman; Pang, Liping; Wang, Jun

doi:10.1109/iciea.2016.7603756

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…In 2004, due to the blockage of the pipeline, the main oxygen system failed again, the two astronauts inside had to rely on the oxygen in the docking cargo tank to maintain their lives, meanwhile waiting for the Russia cargo to transfer more oxygen [14]. Seen from the abovementioned events, it is necessary to monitor the working state and to diagnose the fault of the electrolysis oxygen system of the space station [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

UKF-Based State Estimation for Electrolytic Oxygen Generation System of Space Station

et al. 2021

Applied Sciences

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Electrolytic oxygen generation system (EOGS) is the only system that can provide oxygen for astronauts in a physicochemical regenerative way in a long-term manned spacecraft. In order to ensure that the astronauts in the cabin can obtain a continuous and enough oxygen supply, it is necessary to carry out real-time condition monitoring and fault diagnosis of the EOGS. This paper deals with condition monitoring and fault diagnosis of the EOGS. Firstly, the dynamic model of the system is established based on the principle electrolysis for actual oxygen production system and the state observer of the system has been designed by using unscented Kalman filter (UKF). The total pressure in the cabin and the partial pressure of oxygen in the electrolytic cell can be observed. Then, considered the actual conditions of the manned space mission with one more astronaut, i.e., 3 astronauts, the simulation experiment is carried out. The simulation results show that the method can effectively estimate the system state, and it is of great significance to ensure the normal operation of the electrolytic EOGS system in the space station.

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Section: Introductionmentioning

confidence: 99%

UKF-Based State Estimation for Electrolytic Oxygen Generation System of Space Station

et al. 2021

Applied Sciences

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A combined architecture of biologically inspired approaches to self-healing in embedded systems

Martinović

Novak

2017

2017 International Conference on Smart Systems and Technologies (SST)

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Development of simulation platform for physicochemical regenerative environment control and life support system in space station

Cited by 2 publications

References 12 publications

UKF-Based State Estimation for Electrolytic Oxygen Generation System of Space Station

UKF-Based State Estimation for Electrolytic Oxygen Generation System of Space Station

A combined architecture of biologically inspired approaches to self-healing in embedded systems

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