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CASE STUDY

TEST BED: Monopropellant Propulsion System (MPS)


A simple, pressure fed Monopropellant Propulsion System (MPS) for a small space flight vehicle has been chosen to be used as initial proof-of-concept implementation. The purpose of the system is to provide thrust for the vehicle while in orbit. For this study additional support systems such as thermal and electrical control systems were not considered.

Model of MPS

A simplified model of MPS with several failure prone components like heater, regulator, and valves. (Click to enlarge)

OPERATIONAL DESCRIPTION - The system uses hydrogen peroxide (H2O2) that passes over a catalyst and decomposes into byproducts of oxygen, water, and heat to create an expanding gas producing a thrust that changes the spacecraft velocity. The system consists of a reservoir TK1 of inert gas that is fed through an isolation valve IV1 to a pressure regulator RG1. The pressure regulator RG1 senses pressure downstream and opens or closes to control the pressure at a constant level. A redundant valve path consisting of IV4 and RG2 is available for contingency situations. The ACM system can switch the gas path to the redundant path when a severe fault in either IV1 or RG occurs. A check valve, CV1, allows passage of the inert gas to the Propellant Tank PT1. Separating the inert gas from the propellant is a bladder that collapses as propellant is depleted. Propellant is forced through a feed line to the Thruster Isolation Valve IV2 and then to the Thrust Chamber Inlet Valve IV3. For the Thruster to fire, the system must first be armed, by opening IV1 and IV2. After the system is armed, a command is sent to IV3, to open, allowing H2O2

OPERATIONAL MODES - There are three normal operational modes for this propulsion system as depicted in the figure below. Ideally, the system should switch between these modes as commanded through the thrust vector. As one might expect, there are numerous, non-trivial fault scenarios which can be potentially addressed with various contingency management schemes. In some cases, these faults are catastrophic or otherwise impractical for ACM to handle successfully. For such cases, a fail-safe mode is designed. Fail-safe configuration depends on the task of the system. In this case, since the propulsion system is meant to provide thrust to the vehicle while in orbit, a reasonable fail-safe operation would be shut down the complete system to avoid any loss.

Diagram of modes of operation

Different modes of operation for the ACM system are defined by the state of various switches and valves.

SYSTEM MODELING - A Matlab Simulink model, developed at Georgia Institute of Technology, was used for simulation purposes. It consists of three main blocks namely, System Model, Fault Injector and a Display Module. Several fault scenarios can be simulated on this model, which then can be used to evaluate ACM's response. Further, the ACM system was itself developed using Matlab's stateflow toolbox for easy interfacing with the simulink model.

Diagram of mps

The Monopropellant Propulsion System was modeled in Simulink and includes a Fault Injection Module

ACM MODELING - The ACM model has been developed using Matlab's Stateflow toolbox. The figure below shows a part of the Stateflow diagram that covers a heater fault (stuck ON) and a regulator valve fault (stuck open). Whenever the system makes a transition from the normal mode to a fault mode, the costs are computed and the action is taken at a time instant such that the total costs are the minimum.

ACM Stateflow Model for thrust mode

ACM Stateflow model for thrust mode

COST MODELING - As mentioned above, it is important to develop cost models that map various non-measurable objectives and constraints into quantifiable entities. As a proof of concept, a simple cost model was developed. This model takes two factors into account in calculating the total costs,energy consumption for the heater and extra time to accomplish the mission.

Total Cost = w1 * cost(heater_ON) + w2 * cost(extra time to complete mission)

One must note here that these costs are associated with the value of the resources in the given scenario. For instance, spending extra energy to use the heater may be more risky in the initial phase of the mission, however same spending may not be as risky towards the end of the mission where we can hopefully afford to exhaust the emergency buffers. The cost models should take into account such factors. Later, individual cost equations may be combined to form a composite cost function. The weights for such cost functions may be assessed from domain experts' knowledge. At each decision-making step, costs associated with an action are assessed for all future instances. The decision is made to take the action at an instance where these costs are minimum.

schematic showing point of lowest cost

DEMONSTRATION TEST BED - The figure below depicts the overall scheme conceptualized for a proof of concept demonstration using a Monopropellant Propulsion System (MPS). Mission-level objectives are translated into external commands, e.g. Move forward by x distance, increase speed, stop, etc., which provide inputs to various components in the system model. Once a fault is detected, the stateflow model indicates the failure to the decision maker, which in turn requests the ACM model to provide possible corrective action sequences along with associated costs. The decision maker makes a decision based on specified criteria (currently the minimum cost). The corrective action is applied to the system. Various fault injection options have also been included using a fault simulator that can simulate various faults like sensor degradation, stuck valves, malfunctioning regulator valve, malfunctioning heater, gas leakage, etc.

Diagram Optimization-based ACM & Test Bench

Optimization-based ACM & Test Bench
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