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25th AIAA International Communications Satellite Systems Conference (organized by APSCC)
AIAA 2007-3149
Thermal Propellant Gauging System for BSS 601
T. Narita.1
JSAT Corp, 229-1 Miho-Cho, Midori-ku, Yokohama 226-0015, Japan
B. Yendler.2.
LMMS/COMSAT, Sunnyvale, CA, 94089, USA.
Of the more popular methods of propellant estimation, namely, book-keeping,
PVT (Pressure, Volume, Temperature) and the Thermal Propellant Gauging
System (PGS) methods, the latter is most accurate at End-of-Life (EOL). The
thermal method uses tank temperature responses to tank heating in order to infer
the propellant load in the tank. Typically, the PGS method uses heat load from
heaters which are attached to the propellant tanks. The current paper discusses a
method of Thermal PGS when tanks do not have installed heaters. Specifically, this
paper describes how the Thermal PGS method could be applied to an on-orbit
Boeing 601 geosynchronous communications satellite. It is shown that propellant
gauging is possible even when the propellant tanks do not have heaters. This paper
examines an implementation of the Thermal PGS method on a Boeing 601
geosynchronous communications satellite which has been operated by JSAT
Corporation of Japan. Prior to the development of a thermal model, a feasibility
test was conducted in order to determine the tank temperature response to tank
heating. Due to the lack of heaters on the propellant tanks, gyro (Inertial Reference
Unit, or IRU) heaters were used for tank heating. During the 48-hour feasibility
test, the tank temperature rose several degrees C which is sufficient for propellant
estimation by the Thermal PGS method. No stationkeeping maneuvers were
conducted during the period of data collection, in fact, the first maneuver was
performed after a cool-down period for the tanks. High-fidelity tank and satellite
thermal models were developed based on the results of the feasibility test, and those
thermal models were used for propellant estimation. This paper discusses the
results of the propellant estimation operations and the accuracies achieved.
Nomenclature
Cp
= specific heat
mi
T
= mass of “i” component
= tank temperature
Tenv
= environment temperature
Qload
U
f
*
i
p
g
t
=
=
=
=
=
=
=
=
1
2
heater power
uncertainty of calculated or measured value
generic function\
effective emissivity through Multi Layer Insulation (MLI)
component index
propellant index
gas index
tank index
Deputy GM, JSAT Corp, 229-1 Miho-Cho, Midori-ku, Yokohama 226-0015, Japan.
Sr. Thermal Systems Analyst, Comsat Technical Services, 1309 Moffett park Dr. , Sunnyvale, CA 94089
.
1
Copyright © 2007 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.
I.
Introduction
The Propellant Gauging System (PGS) method of propellant estimation is based on a concept of
measuring the thermal capacitance of a tank containing liquid fuel and pressurant gas by measuring the
thermal response of the propellant tank to heating and comparing the observed temperature rise to
simulation results obtained from a tank thermal model1,2. Described in Ref. 1, 2 the PGS method employs a
very sophisticated thermal model of the propellant tank which takes into account temperature gradients in
the tank.
Non-uniform heater power distribution and uneven propellant distribution inside of the tank cause a
non-uniform temperature distribution on the tank surface. Non-uniformity of heater power distribution
stems from the fact that heater strips typically cover only a fraction of the tank surface. If propellant
position in the tank is controlled by a vane-type Propellant Management Device (PMD) in microgravity,
then at EOL the propellant is located in the sump and in the corners formed by PMD vanes and the tank
wall. A significant portion of the internal tank wall is not in contact with propellant and therefore dry. All
these factors lead to the formation of significant temperature gradients on the tank wall. Therefore, the
temperature, which is measured by the temperature sensors on the external side of the tank wall, depends
on the sensor locations. The temperature distribution on the tank surface must be determined to
successfully compare the test flight data with calculated temperatures.
If satellite thermal control system does not have heaters installed on the propellant tanks, the tank
temperature is controlled by internal satellite thermal control system. The BSS (former Hughes) 601
geosynchronous communication satellite is an example of such thermal control scheme3. Such a thermal
control system presents a challenge for a typical PGS method because energy input into a propellant tank is
done not by heaters installed on the propellant tanks by rather by external heat sources like payload or bus
units which heat generation is known. An example of such unit could be TWT or one of the bus units
which generate enough heat to increase tank temperature. The key is knowledge of heater power or/and
surface temperature of the unit which is used to generate energy and to increase tank temperature.
If the unit in question has a temperature sensor, heat generation by the unit can be calculated. Viceversa, knowledge of heat generation allows calculation of unit temperature which can be compared with
temperature sensor reading if the unit has temperature sensor installed. In both cases, development of a
high fidelity model of the satellite including payload and bus units is required.
Such a requirement constitutes the major difference for PGS method between satellites with and
without heaters installed on the propellant tanks. If propellant tanks have heaters installed and the tanks are
covered with thick Multi Layer Insulation (MLI) blanket, the tanks do not have much thermal interaction
with the satellite environment. Knowledge of the satellite thermal environment is not so important for
correct propellant estimation by the PGS method. On other hand, if payload or/and bus unit is a heat source
which used for propellant estimation, the heat source is part of the satellite environment. In this case, the
tank temperature rise is determined by thermal interaction between the tank and the satellite environment.
Therefore, knowledge of the satellite environment becomes very important for correct propellant
estimation.
II.
Thermal models
Regardless of the spacecraft type, the PGS method employs the same steps:
• Develop a thermal models of the propellant tanks and the satellite
• Develop a thermal models of the satellite
• Merge the thermal models of the satellite and propellant tanks
• Prepare and conduct the PGS operation
• Simulate the PGS operation for different propellant loads
• Compare flight and simulation data
• Determine tank propellant load
The first phase of the PGS method, namely, development of the tank thermal model, the development is
mostly driven by the tank design and by the fact that heaters (if installed) create a large temperature
gradient on tank walls in heaters vicinity. It means that a high fidelity tank model is required to capture
2
temperature gradients and to determine tank wall temperature at the temperature sensor location. In
absence of the heaters on the tank surface, one can expect less temperature gradient and, therefore, less
stringent requirements for capturing temperature gradients.
A. High Fidelity Tank Model
If temperature gradients can not be neglected, which is a common case, temperature distribution in the
tank should be determined numerically with corresponding boundary and initial conditions. Previously
developed a Finite Element (FE) model of the propellant tank1,2 was based on grid provided by Surface
Evolver4. The developed FEM model of the tank had several problems including difficulty of keeping the
ratio of the maximum to minimum conductances of the links between nodes in the thermal model
sufficiently small to avoid ill-conditioned matrices in the thermal modeling. Also, based on Surface
Evolver grid had extremely small or
large conductances, which are not
generally necessary. Similarly, the
minimum thermal capacitance of
elements affects step size in time and
thus overall compute time of the
modeling.
In order to avoid such problems, a
new FEM was developed.
Grid
generation
for
such
complex
geometry like tank with gas and
liquid volumes, tank wall, heaters, etc
is not simple task. The grid should
Figure 1 Cross section and shell of final tank grid
satisfy the following requirements:
have high enough density to simulate thermal gradients, particular at the temperature sensor location,
confirm to the primary geometry of model components like, tank wall, propellant, pressurant, should
confirm each other at the interfaces, confirm heater shape, etc.
GridPro5 was selected as the primary tool for creating the grid. It is a powerful tool designed to create
computational fluid dynamics (CFD) grids. Grid generation of the tank was not simple. When the
geometry is complex, it can be difficult to get a CFD style grid to converge and to model accurately the
geometry. In particular, GridPro runs into problems when the geometry becomes overly complex, like,
sharp edges, or a zero-degree angle between two surfaces. The gas/fluid interface model alone is of
sufficient complexity to cause the GridPro to have difficulty of converging. Add to this, requirements for
the grid to confirm to tank heaters shape, variations in the tank wall profile, mounting lugs, etc. and it
quickly becomes extremely time consuming to develop a grid that will converge. A suite of software tools
was developed in order to overcome these limitations.
Figure 1 shows several cross-sections of the final grid. As one can see, the grid has higher density next
to tank wall where temperature gradients are expected.
B. High Fidelity Satellite Model
Current paper discusses development
the PGS method for BSS (former Hughes)
601 geosynchronous communication
satellite. Figure 2 shows a general view of
the satellite which design is described in
details in Ref.3.
The satellite propulsion system has
four spherical tanks (two fuel tanks and
two oxidizer tanks). Tanks are covered
with single layer MLI3. Two temperature
sensors are installed on the top and on the
bottom of a propellant tank (Fig.7 Ref.3).
The top temperature sensor approximates
pressurant temperature.
The bottom
Figure 2 BSS 601 satellite
3
So
ut
h
R
ad
i
at
or
No
r
th
Ra
di
at
or
temperature sensor senses the temperature of the propellant which is contained inside of the trap (Fig.7
Ref.3).
Such design of the propellant tanks and the satellite requires development of satellite thermal model
which should describe: a). radiation heat transfer between tanks and satellite components like panels and
payload/bus electrical and electronic units; b). heat transfer by conduction between the units and satellite
structure, between satellite structure and propellant tanks. Due to a particular position of the temperature
sensors on the propellant tank wall, heat transfer between bottom of the propellant tank and the satellite
presents the greatest interest.
Figure 3 demonstrates a developed
satellite thermal model.
The model
simulates all major elements of the BSS 601
satellite which are important for simulation
West
of the PGS operation and propellant
estimation, like internal panels, MLI
blankets, etc. All surfaces of the satellite
internal panels are assumed painted black,
which
is
common
practice
for
communication satellites in order to increase
heat rejection from the internal panels.
East
The satellite thermal model includes
solar fluxes incident on the outer surfaces of
the satellite. The radiation interaction inside
Figure 3 Satellite Thermal Model
of
the satellite and solar fluxes were
Cross shows IRU location
simulated by Thermal Synthesizer System
(TSS) software tool. Typically, North and
South panels of communication satellites house heat producing units, like Travel Guided Tube (TWT)
which usually instrumented with temperature sensors. Use of temperature sensor readings as boundary
conditions simplifies the satellite thermal model because it circumvents the need to determine temperature
of the North/South panels. Usually, East and West panels don’t have any payload or bus units; the
temperature of such panels was calculated.
III.
Propellant Estimation
This section discusses the PGS operation that was performed in 2006 on one of the BSS 601 satellites
of JSAT Corporation fleet. JSAT began to operate BSS 601 satellites in 1995. Five BSS601 satellites have
been operated so far.
All previous experience related to propellant estimation for the satellites with tanks which have heaters.
Prior to development a high fidelity models of the propellant tank and the satellite, a feasibility study was
conducted. The study included simulation and flight test. The goal of the feasibility study was to
determine whether the PGS method is suitable for propellant estimation due to the fact that propellant tanks
do not have heaters. Due to lack of the heaters on the propellant tanks, we used IRU heaters as an external
heat source. Flight experience pointed out that propellant tank temperature went up when IRU heaters were
turned ON. It shows that IRU heaters can be used for the PGS operation, but an accuracy of such estimation
was not known. As Figure 3 indicates, IRU units are located on the bus panel in vicinity of the propellant
tanks. Therefore, the IRU heaters should have the greatest influence on the tank temperature.
A. Feasibility study
1. Simulation
In order to study an effect of heat generation by IRU heater on tank temperature, we assumed IRU
temperature of 60 C when the heater is turned ON. Figure 4 shows the tank temperature trend when the
heaters are turned ON and OFF. Tank temperature rises when IRU heater is ON and falling after the IRU
heater is switched OFF. It supposed to take about 48 hr. to reach equilibrium with satellite environment
during. The cooling period also should last about 48 hr.
4
36
When IRU heater is turned ON
temperature of both tanks, NE and SE,
increase. Heat transfer to the SE tank is
conducted mostly via radiation. Heat
transfers from the unit to the NE tank via
conduction by base panel and via radiation
across the middle wall. As expected,
temperature rise of NE tank is less than
temperature rise of SE tank.
Tank temperature rise due to heat input
from the IRU presents the most interest, as
far as the PGS method concern. Such a
temperature rise has the same magnitude as
tank temperature change due to daily
temperature variation. This obscures
temperature rise due to tank heating by the
IRU heater. A normalization procedure
was developed in order to extract such tank
temperature change. Figure 5 shows
behavior of the normalized temperature.
Daily temperature fluctuations are removed
and only temperature rise due to heat
injection by the IRU heaters remains.
The plot also shows an effect of tank
propellant load on the temperature rise,
which is the most interest to the PGS
method. The data clear demonstrates that
temperature rise depends on the propellant
load and can be used for propellant
estimation by the PGS method.
34
NE tank
SE tank
32
Temperature[C]
30
28
26
24
22
Heater ON
Heater OFF
20
18
0
24
48
72
96
120
144
168
192
Time[hr]
Figure 4 Tank Temperature at the bottom;
7
6
Tempearture rise [C]
5
4
0.kg
5kg
10kg
3
2
1
0
-1
0
12
24
36
48
60
72
84
96
Time[hr]
2. Flight
For the feasibility test, IRU heater was
turned ON for 24 hr. During this time tank
temperature has risen for several degrees (see Figure 6 and Table 1), which seemed to be sufficient for
propellant estimation by the PGS method.
Figure 5 Normalized Tank Temperature
39.5
39.0
38.5
38.0
Temp
37.5
.
37.0
36.5
36.0
35.5
35.0
34.5
IRU On
34.0
0
12
24
36
48
60
72
Time (hrs)
Figure 6 Fuel Tank Temperature Sensor T3 trend
IRU on for 24 hr
Table 1 Flight Test Results
5
Tank Type
Fuel
Oxidizer
Temperature Rise (°C)
2.7
5.0
B. Operational Constraints
Several considerations should be taken into account in determination of the period of the PGS operation
in order to minimize an influence of the spacecraft conditions on tank temperature:
Avoid eclipse season (change of thermal condition)
No change in payload/Bus unit configuration (change of thermal condition)
No stationkeeping maneuvers performed (change of propellant load, sloshing)
Enough time to cool-down for the tanks after turning heaters OFF
From station-keeping viewpoint, a period of cooling down of the propellant tanks after the heaters
turned OFF should be long enough in order to reduce propellant tank pressure. Increased tank pressure
might cause some variance in maneuver performance.
No stationkeeping manoeuvres were conducted during the PGS operation because temperature and
pressure of the tanks were a little bit higher than usual due to tank heating. First manoeuvre was performed
after a cool-down period which lasted for 48 hours. Temperature rise due to heating varied for different
tanks. It could be explained by difference of propellant loads or/and difference in environment conditions
for each tank. The observed temperature rise was sufficient to estimate the remaining propellant in the
tanks.
C. Flight Test –results
The PGS operation was performed after successful completion of the feasibility study. The PGS
operation consisted of two steps: PGS operation procedure preparation and a flight operation. The
developed tank and spacecraft models were used in the development of the flight operations procedure.
The goals of the simulation for the procedure development were to determine: 1) the length of time which it
takes for the tanks to reach thermal equilibrium, and 2) the length of time which it takes for the tanks to
cool down to the initial conditions. It was determined that it should take 3 -4 day for tank temperature to
reach saturation and 1-2 days to cool tanks down to the initial temperature.
The IRU heaters had been turned ON for 3 days during the PGS operation. The observed tank
temperature rises were: Fuel Tank 1 – 3.5 oC, Fuel Tank 2 – 4oC,; Oxidizer Tank 1- 5.5oC, Oxidizer Tank 2
- 5oC. The temperature trends for bottom temperature sensors (T3) of the propellant tanks are shown in
Fig.7a.
The temperature of the propellant tanks and several bus and payload units were collected during the
PGS operation. The satellite thermal model uses temperature of bus and payload units to characterize tank
a)
b)
Figure 7 Flight Operation Results – a)Tank (Sensor 3); b) Pressure Controllers temperature sensors
6
environment. In addition to tanks, IRU heaters affect temperature of bus and payload units. An example of
such influence is shown in Figure 7b. The presented data demonstrates temperature rise of pressure
controllers when IRU heaters were turned ON.
Temperature Rise (deg_C)
D. Propellant Estimation
Propellant remaining in all four tanks was estimated using the developed thermal models of the tanks
and of BSS 601 satellite and flight data. Several simulations were run with varying propellant loads for
each propellant tank. Propellant remaining was estimated using normalized flight data and normalized
simulations results. Figure
4
8 shows an example of the
comparison
of
the
FTank2
3.5
8kg
normalized flight data with
10kg
normalized
simulations
12kg
3
results for the Oxidizer tank
1. The diurnal temperature
2.5
variations
have
been
removed
via
data
2
normalization
procedure
1.5
which was described earlier.
The normalized flight and
1
simulation data illustrate
temperature rise due to tank
0.5
heating without obscuring it
by
daily
temperature
0
0
2
4
6
8
10
12
14
16
18
20
22
24
fluctuations. As one can see
Time (hrs)
from Fig. 8, the comparison
of flight and simulation data
Figure 8 Results of PGS estimation for Oxidizer Tank 1.
Lines – simulation results; Markers – Temperature Sensor T3 reading indicates that the propellant
load of Ox1 tank is close to
IRU heater was turned ON at t=0
10 kg with probable
variation of 2 kg.
We need to stress that simulated temperature variation with propellant load of a tank does not represent
an accuracy of the PGS method. It rather illustrates the sensitivity of temperature rise to tank load. The
accuracy of the PGS estimation is addressed in the next Section. However, we would like to mention that a
sensitivity plot, like Fig 8, can only give “eye ball” estimation of the PGS accuracy.
IV.
Accuracy of Propellant Estimation
Typically, a satellite operator is interested not only in estimation of propellant remaining but also in the
accuracy of the propellant estimation. The review of existing methods can be found elsewhere6. We will
use an uncertainty analysis7to determine an error of propellant estimation.
In general, a propellant tank mass consist of three components, namely, propellant mass, m p , mass of
pressurizing gas,
m g , and mass of the tank itself mt . Calculated propellant mass is function of many
parameters like applied heat load Qload , environment temperature Tenv , etc. Then, the uncertainty of
propellant mass estimation is defined as:
m p = f (T , Q load ,
U (m p ) =
2
mp
T
*
, m g , mt , Tenv , C P ,....)
2
U (T )
+
mp
Qload
2
U (Qload )
+
mp
*
2
U(
*
)
+ .....
(1)
7
Uncertainty of absolute temperature measurement T does not have an effect on PGS accuracy of
propellant estimation because the PGS method uses temperature difference for propellant estimation
instead of the absolute temperature.
It is convenient to express all uncertainties in terms of temperature uncertainty. For example, the second
term in (Eq.1), which shows the mass uncertainty related to the heater power uncertainty, can be expressed
as
mt
mt
U (Q ) =
U (TQ ) ; where
Q
T
U (TQ ) ) =
T
U (Q )
Q
(2)
Using manipulation (Eq.2) for other terms in (Eq.1), easy to present (Eq.1) in the form
U (m p ) =
2
mp
T
2
2
(T ) 2
Where (T) is the total temperature uncertainty, defined as
2
[
]
(T ) = U 2 (T ) + U 2 (TQload ) + U 2 (T * ) + .....
(3)
When a high fidelity model of the propellant tank is used for propellant estimation, the temperature
distribution in the tank is determined by numerical solution of (Eq.4) by SINDA/Fluint with corresponding
boundary and initial conditions.
mc p
T
= k T +Q
t
(4)
Therefore, the closed form of solution of (Eq.4) is impossible to obtain. In order to calculate the
derivatives in (Eq.1), the terms in mass uncertainty (Eq.2) are expressed in (Eq.3) form. Essentially, the
derivative of tank temperature over parameter is calculated instead of finding derivative of mass over
parameter. The derivative of the temperature over model parameters, like, IRU power (
emissivity (
T
*
T
), effective
Q
), etc is obtained by solving FE tank thermal model with varied parameters. The resulting
uncertainty is summarized in Table 2 for the fuel and oxidizer tanks.
Table 2 Parameter uncertainty for oxidizer and fuel tanks
Effect [kg]
Model Parameter
Oxidizer
Fuel
Tank-base connection
1.47
1.72
Tank MLI e*
1.77
0.62
Black paint emissivity
0.23
0.15
External plume shield e*
1.68
0.43
Transition function
1.80
1.20
Temperature sensor (T3) resolution
2.77
2.23
Total Uncertainty [kg]
4.37
3.16
8
The uncertainty of each parameter is independent from each other. Therefore, the RSS method is used
to determine the total uncertainty of the propellant estimation. As Table 2 indicates, the error of propellant
estimation by the PGS method is relatively small.
An error of estimation of the consumed propellant obtained by the bookkeeping method typically is in
the range of ±2.5 % - 3.5 %, according to Ref. 6, 8, 9. Assuming the error of 3%, the bookkeeping method
has uncertainty around ± 14 kg per tank at EOL based on data on BSS 601 propellant tanks volume3.
An accuracy of the PVT method was subject of several studies. The reported error of propellant
estimation by the PVT method various significantly. For example, the error of propellant estimation is
reported as high as 35% 10 and as low as 0.22% 11 at EOL. Such difference greatly influenced by
uncertainty in reading of the pressure transducer. A high resolution pressure transducer is used in Ref.11. It
is not clear, however, how reliable this pressure transducer is after 10 years in flight.
V.
Discussion
Precise estimation of remaining propellant is needed to extend the satellite mission life as long as
possible. In addition, it guarantees confident de-orbiting of the satellite at the end of its mission life.
Initially, JSAT Corporation (Japan) has used both the book-keeping and the PVT methods for
estimation of remaining propellant. JSAT decided to use the PGS method for propellant estimation of one
of BSS601 satellite fleet as an alternative method to the bookkeeping and the PVT methods. It allows
comparing the results of all three methods in order to make more rational decision for prediction of End-ofLife of the satellite.
Each method can provide different estimation of remaining propellant and with different uncertainty.
Use of different methods helps to avoid a systematic error introduced by an individual method in order to
minimize a possibility of unexpected depletion. For example, the result of the comparison between the
PGS and other two methods can be used for selection of pair of the propellant tank used during stationkeeping maneuvers. It also helps to have a balanced consumption of remaining propellant to the rest of the
satellite mission.
JSAT plans to evaluate the results of the PGS estimation and determine if it would be possible to track
propellant depletion in deorbit operations in the future using the PGS method. Such an evaluation will be
helpful for improvement of an accuracy of the PGS method.
VI.
Conclusion
Proposed paper shows that the thermal PGS method for propellant estimation can be applied
successfully to a satellite which does not have heaters installed on the propellant tanks, like BSS (former
Hughes) 601 geosynchronous communication satellite. It is shown that the PGS propellant estimation can
be conducted if a payload or a bus unit is used as heat source external to the propellant tank. However, use
of the PGS method for propellant estimation requires development of a satellite thermal model of higher
fidelity compared to the case when the propellant tanks have heaters installed and tanks are insulated from
the satellite environment.
It is shown that the error of propellant estimation by the PGS method is less than error of propellant
estimation by the book keeping method at EOL for BSS 601 satellite. Use of the PGS method allows JSAT
Corporation execute an independent verification of the propellant estimation obtained by the bookkeeping
and PVT methods, to mitigate risk of unexpected depletion and increase confidence in fleet reliability.
9
VII.
Reference
1
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A. Yip, B. Yendler, T. A. Martin, S. H. Collicott, “Anik E Spacecraft Life Extension”,
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3
Purohit, G.P., et al. “ Transient Lumped Capacity Thermodynamics Model of Satellite Propellant
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K.A. Brakke, The Surface Evolver, Experimental Mathematics, 1(2):141-165, 1992
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Michael Perry. ESA SP-398. Paris: European Space Agency, 1997., pp.561-570
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Hasan, D. et al, “Application of Satellite Hydrazine Propulsion System In-Orbit Monitoring
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Dandaleix, L, et al, “Flight Validation of the Thermal Propellant Gauging Method Used at
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10