thermal design and on-orbit data evaluation of the 3u

49th International Conference on Environmental Systems ICES-2019-143 7-11 July 2019, Boston, Massachusetts

Thermal Design and On-Orbit Data Evaluation of the

3U-class CubeSat TRICOM-1R, Correlation Analysis

between the Attitude and Thermal Measurement

Kikuko Miyata1, Jihoon Kim2, and Hosei Nagano3

Nagoya University, Nagoya, Aichi, 464-8603, Japan

and

Yoshihide Aoyanagi4 Takeshi Matsumoto5, and Shinichi Nakasuka6

The University of Tokyo, Bunkyo, Tokyo, 113-8656, Japan

This paper describes the thermal design and on-orbit evaluation results of 3U CubeSat-

class nanosatellite TRICOM-1R which was launched by SS-520-5 sounding rocket and

operated for a half year. The satellite has some difficulties for data evaluation and model

calibrations. First, the thermal vacuum test was skipped to shorten the development period

and only a previous satellite’s thermal mathematical model is available for analysis. Second,

the insertion orbit has high eccentricity (0.12) and very low perigee altitude (about 180 km).

The sun/eclipse duty ratio has a difference from the typical low earth orbit satellite. The

orbit and attitude profile were affected by atmospheric drag. Finally, the satellite separated

with high angular rate and it experienced variable attitude. The satellite was spin stabilized

during the initial operations but the spin axis was varied during the operation because of its

energy dissipation. The satellite mounts poor attitude sensors and there had some difficulties

to estimate exact attitude. This paper constructs the thermal-mathematical model of

TRICOM-1R and discusses the differences with the pre-launch model. We propose the pre-

launch model calibration sequence for this purpose. Usually, the attitude data is fixed for

these kinds of calibration, however, this paper also updates the attitude estimation data

together with the thermal properties calibration with the help of the thermal measurement

data. The analysis results with the established model show the acceptable differences from

on-orbit measurement data. The details of the differences are discussed and summarized to

utilize for the design and analysis of similar spacecraft development.

Nomenclature

ADC = attitude determination and control board

BAT = battery

COMM = computer for power and communication control

COTS = commercial off-the-shelf

DCDC = DC-to-DC converter

FR4 = flame retardant type 4

GNSS = global navigation satellite system

GNSSR = global navigation satellite system receiver

IGRF = international geomagnetic reference field

ISAS = Institute of space and astronautical science

1 Assistant Professor, Department of Aerospace Engineering, Furo-cho, Chikusa-ku, AIAA member. 2 Graduate Student, Department of Aerospace Engineering, Furo-cho, Chikusa-ku. 3 Professor, Department of Mechanical System Engineering, Furo-cho, Chikusa-ku, AIAA member. 4 Researcher, Department of Aeronautics and Astronautics, 7-3-1 Hongo. 5 Researcher, Department of Aeronautics and Astronautics, 7-3-1 Hongo. 6 Professor, Department of Aeronautics and Astronautics, 7-3-1 Hongo, AIAA member.

International Conference on Environmental Systems

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JAXA = Japan aerospace exploration agency

JSpOC = joint space operations center

Main CAM = main camera (name of mission equipment)

MOBC = main on-board computer

PCU = power control unit

PTFE = polytetrafluoroethylene

PID = proportional-integral-differential

RW = reaction wheel

S&F = store & forward (name of mission and mission equipment)

SAP = solar array panel

Sub CAM = sub camera

TLE = two-line element

TRICOM = triple communication (satellite name)

UHF = ultra high frequency

UHF-T/-R = UHF transmitter / UHF receiver

I. Introduction

company report forecasts growth in the number of planning

small satellite projects despite the shortage of launch

opportunities.1 The advantages of these kinds of nano-satellites are

their short development period and high cost-effectivities.

Especially, a few-kilogram class satellite represented by "CubeSat"

gain high attraction and there are worldwide researches,

developments, and launches.

Based on these situations, TRICOM-1/1R were developed. They

are 3U CubeSat-class experimental demonstration satellites for a

realization of the practical satellite with international

competitiveness. The design of the satellite bus is based on

Hodoyoshi bus technology,2 it was developed with the aim of the

system with high versatility of functions. In addition, the system

utilizes the COTS (Commercial Off-The-Shelf) devices. The first

satellite TRICOM-1 failed to enter the orbit with the launcher

failure.3 This paper describes TRICOM-1R, the substituting satellite

of TRICOM-1, and launched by SS-520-5 sounding rocket

(ISAS/JAXA), and successfully inserted into the orbit on

February 3, 2018, and operated for half a year.4 The satellite

systems of TRICOM-1 and TRICOM-1R mainly consisted of the

same hardware and configuration, except a few functional updates

of the onboard software.5 The software update does not affect the thermal operation. The updated software includes

the autonomous functions to continue the mission operation even if the satellite detects an anomaly.6

This paper discusses the thermal design and on-orbit evaluation results of TRICOM-1R, which has some

remarkable points. At first, the development period was very short. Therefore, TRICOM-1R skipped an

experimental evaluation under the thermal vacuum environment and utilizes the TRICOM-1 thermal mathematical

model as deeming compatible. Second, the insertion orbit had a high eccentricity and a very low perigee altitude.

The sun and eclipse duty ratio had a difference from the typical low earth orbit satellite. The orbit and attitude

profile were affected by atmospheric drag. Finally, the satellite separated with a high angular rate and it experienced

a variable attitude. The satellite was spin stabilized during the initial operations, but the spin axis was varied during

the operation because of its energy dissipation. The satellite was equipped with poor attitude sensors and there had

some difficulties to estimate an exact attitude.

The authors propose a pre-launch thermal mathematical model calibration sequence to construct the final on-

board TRICOM-1R model, and discuss the differences with the pre-launch model. Usually, attitude data are fixed

for this type of calibration; however, this paper also updates the attitude estimation data together with the thermal

properties calibration with the help of the thermal measurement data because of the uncertainties of the attitude

sensor measurement.

A Z

XY

Figure 1. Overview and axis definition

of TRICOM-1R.


3

This paper organizes as follows: Section II explains the system overview, environmental constraints, and thermal

design specifications of the system and individual components of TRICOM-1R. Section III describes the pre-launch

thermal mathematical model construction and the experiments under the thermal vacuum environmental for

TRICOM-1. Section IV summarizes the pre-launch thermal profile estimation results under a specific orbital

scenario. Section V explains the proposed thermal-attitude correlation analysis sequence and shows the

implementation results to the on-board measurement data. In addition, the details of the differences are discussed

and summarized for use in the design and analysis of similar spacecraft development. Finally, section VI concludes

the paper.

II. Overview and Thermal Constraints for TRICOM-1R

This section explains the system overview, environmental constraints, and thermal design specifications of the

system and individual components of TRICOM-1R. The requirements from the system are also summarized and the

scope of this paper is explained.

TRICOM-1R was a 3U CubeSat-class satellite whose mass is 3.2 kg and volume is 116 mm× 116 mm× 346 mm,

except for protrusions. Figure 1 shows TRICOM-1R in overview and defines its body axis. The SS-520 insertion

orbit is distinguishing from the other launchers.4 The final orbit is an extended elliptical orbit whose perigee is

approximately 180 km, an apogee is 2,010 km, and an inclination is about 31°. The estimated lifetime is longer than

30 d. The launcher has no de-spinning device, and its payload is separated with a high spinning rate of

approximately 1.6 Hz.

The TRICOM-1R satellite had two main missions: one is the Store & Forward (S&F) demonstration7 and the

other is the image acquisition experiment by COTS imagers (Main and Sub CAMs).8 The satellite mounted the solar

cells in all side panels as the power generation source, and lithium-ion battery (BAT) as the power storage device. It

also equipped a custom-built power control unit (PCU) including a charge and discharge controllers and a power

distributor. The attitude data were measured by an attitude determination and control board (ADC) together with a

magnetometer, a gyro sensor, an acceleration sensor, and a GNSS (Global Navigation Satellite System) receiver

(GNSSR). The system also mounted actuators consist of a one-axis Reaction Wheel (RW) for despin and three-axis

magnetic torquers. The z-axis torquer could generate 0.3 Am2 and the other two torquers could generate 0.2 Am2. A

UHF band transceiver and receiver (UHF-T/-R) were equipped for communication with the ground station.8 In

addition, the system equipped two other computers: Main On-Board Computer (MOBC) and the computer for power

and communication control (COMM). Table 1 defines the operational modes and their power consumptions. Table 2

summarizes the operational temperature range for each component. The ranges for UHF-T and UHF -R were

decided from the specification of the manufacturer. The battery temperature is decided from the performance test of

the single unit. The other component ranges were decided from the experimentally verified temperature. We

performed the thermal-chamber experiment before the system integration. Figure 2 shows the configuration of the

TRICOM-1R satellite.

Table 1 Main Operational Mode Definition.

X Y Z UHF-R UHF-T

0 UVC (Under Voltage Control) 0.25 × × × ○ × × × × × × × × × ○ ×

1 Safe 1.24 × × × ○ △ ○ × × × × × × × ○ ×

2 Initial 2.35 × × × ○ △ ○ × × ○ × × × × ○ ×

3 Standby 2.35 × × × ○ △ ○ × × ○ × × × × ○ ×

4 Normal 5.27 △ △ △ ○ △ ○ ○ ○ ○ ○ × × × ○ ×

5 Mission/Downlink 10.46 △ △ △ ○ ○ ○ ○ ○ ○ ○ × × × ○ ×

6 S&F mission 5.68 △ △ △ ○ △ ○ ○ ○ ○ ○ ○ × × ○ ×

7 CAM mission 10.68 △ △ △ ○ △ ○ ○ ○ ○ ○ ○ × ○ ○ ×

RWGNSSR S&FMagnetometer SubCAM MainCAM PCUOperational ModePower

consumption W

Magnetic Torquer UHF COMM ADC MOBC

+ Power consumption is the mean value for each mode, ○: ON, ×: OFF, △: Intermittent operation.

The satellite has some limitations in functions and performance from the launcher and system specifications.

One is the difficulty of performing continuous active attitude control. The other is few possibilities for

implementation of the additional thermal management device from the mass, volume, and power consumption

constraints. These constraints make thermal design difficult.

The thermal design requirements are summarized as follows: 1) keeping the components within their operating

ranges through the whole on-orbit operational period, and 2) enduring the thermal environment during the launch.

For the latter requirement, the authors performed survivability analyses for 1) the thermal radiation from the nose


4

cone before the nose cone separation, 2) the thermal radiation from the third motor before the nose cone separation,

and 3) the aerodynamic heating from the free molecular flow caused by the nose cone separation in low altitude.

Table 2 Operational Temperature Ranges for Each Component. Maximum,℃ Minimum,℃

MainCAM 50 -10

SubCAM 50 -10

BAT 40 0

PCU 60 -10

COMM 60 -10

MOBC 60 -10

UHF-T/-R 50 -40

S&F 50 -20

Because of the sensor and communication ability constraints, we obtained only the main components

temperature during the on-orbit operational period. Therefore, this paper discusses only the components

temperatures during the on-orbit operational period.

III. Thermal Mathematical Model Construction through the Experiment for TRICOM-1

The authors constructed a thermal mathematical model based on SINDA/FLUINT by using Thermal Desktop.9

The sequence of the pre-launch thermal mathematical model construction is shown as follows: At first, the rough

accuracy model was constructed with the nominal thermal properties from the catalog specifications or data from the

previous projects. Then, the system design was verified through the numerical analysis under the assumed orbital

scenario. The real hardware verification scenario was defined by using the analysis data, and the verification

experiment was performed under the thermal vacuum environment. Finally, the thermal mathematical model was

calibrated with the experimental data and the pre-launch thermal mathematical model was constructed. This section

mainly describes details of the thermal vacuum experiment and the final calibration with the experiment data.

The thermal vacuum experiment was performed in November 2016 for TRICOM-1. The experiment consisted

only of a hot and a cold thermal equilibrant condition from the development schedule limitation. Here, the hot case

was set to the maximum temperature condition of the nominal operation mode (mode 4 in Table 1), and the cold

case was set to the minimum temperature condition of the safe mode operation (mode 1 in Table 1). The functional

tests were also performed during the thermal-equilibrant tests.

A. Experimental Environment

The experiments were performed in space environmental simulator as shown in Figure 3. The simulator consists

of a vacuum system, a cryogenic system, a controller, a control computer, and a measurement system. The vacuum

Figure 2. Configuration of TRICOM-1R.


5

system consists of a vacuum chamber, a rotary pump, and a turbo pump. The pressure inside the vacuum chamber

was kept below 10-4 Pa during the experiment. As the cryogenic system, shrouds are set inside of the vacuum

chamber. The size of the horizontal cylindrical segment is 590 mm × 650 mm, and the rectangular segment of

400 mm × 475 mm is attached to the bottom of the cylindrical segment. The inside of the shroud is painted black to

emulate the space environment. A PID (proportional-integral-differential) controller can control the surface

temperatures of the cylindrical and rectangular segments individually by controlling the heater current and

refrigerant flow rate in the cryogenic system. In the present experiments, both temperatures were set to 193.15 K to

emulate the space environment.

B. Experimental Setup

The experiments were performed on the engineering model of TRICOM-1 by using the skin heater method.10

Figure 4 shows the heater and measurement setups for this experiment and the whole experimental setup can be seen

in Figure 5. The eight flexible heaters (KH-203/10 OMEGA Engineering) were put on the four side panels instead of

the solar cells. The heater profiles were decided from the rough accuracy model analysis results. The worst hot and

cold conditions were analyzed with the model and calculated the heater input for each condition to emulate the same

situation as the steady states of this experimental setup. The heaters inputs became 1.4 W for each side to emulate

the hot condition and 0.5 W to emulate the cold condition. The temperatures were collected by 10 satellite equipped

sensor, and 30 T-type thermocouples which were added especially for this experiment. The 10 T-type thermocouples

were put inside of the satellite and the remaining 20 were put outside of the satellite. The data were recorded in 1 Hz.

There were some differences from the flight model, such as the lack of the solar cells, the existence of the cover

for the MainCAM, and lack of the antennas.

Figure 3. Overview of the experimental environment.

＋X ＋Y －X －Y22

2425

26

17

19

21

11

12

13

14

16

20 15SubCAMSubCAM GNSSR

23 18

30 mm

＋Z －Z

27 29

28 30

KH-203/10Inside of the satellite

CH1 MainCAM

CH2 MOBC1

CH3 MOBC2

CH4 COMM1

CH5 COMM2

CH6 BAT

CH7 UHF-T DCDC

CH8 UHF-T/-R

CH9 RW

CH10 Torquer

Figure 4. Heater and measurement setup. Figure 5. Experimental setup.

PTFE insulator

Thermocouples

connector

Rectangular segment


6

C. Experimental Results

The experiments were conducted based on the operational mode definition for each condition, except for

GNSSR because of the development status constraint. The heaters and components were set as the defined

operational conditions and held there until the steady state achievement. Table 3 summarizes the 30-min average

measurements for each thermocouple after the steady state achievement, except for the failed thermocouples, such as

CH 16, 18, 23, and 28. The basic functional experiments were also performed after the steady state achievement

successfully.

Table 3 30 min Average Temperature Measurement for Each Component and Condition.

CH1 MainCAM 30.1 -30.2

CH2 MOBC1(center) 63.6 -21.4

CH3 MOBC2(side) 52.5 -24.5

CH4 COMM1(center) 57.7 -13.6

CH5 COMM2(side) 56.8 -14.3

CH6 BAT 47.9 -17.8

CH7 UHF-T DCDC 40.9 -22.4

CH8 UHF-T/-R 45.1 -21.6

CH9 RW 43.1 -29.2

CH10 Torquer Blacket 42.2 -29.0

CH11 -X[Up] 31.1 -30.0

CH12 -X[Middle] 20.7 -35.3

CH13 -X[Down] 35.0 -27.1

CH14 -Y[Up] 32.6 -29.6

CH15 -Y[Middle] 32.2 -29.3

HOT, ℃ COLD, ℃

CH16 -Y[Down] ― ―

CH17 +Y[Up] 28.1 -31.8

CH18 +Y[Middle] ― ―

CH19 +Y[Middle] 30.3 -30.9

CH20 +Y[Middle] 22.3 -34.2

CH21 +Y[Down] 32.7 -28.4

CH22 +X [Up] 31.8 -30.0

CH23 +X[Middle] ― ―

CH24 +X[Middle] 21.7 -34.4

CH25 +X[Middle] 30.0 -31.6

CH26 +X[Down] 30.5 -29.4

CH27 +Z[center] 15.4 -35.6

CH28 +Z[edge] ― ―

CH29 -Z[center] 22.7 -32.5

CH30 -Z[edge] 19.5 -33.5

HOT, ℃ COLD, ℃

D. Thermal Mathematical Model Construction

The rough accuracy thermal mathematical model was modified to fit the experimental conditions. The total node

of the original on-board model was 6,311 nodes despite the experiment model consists of 4,951 nodes. The

environmental temperature was the temperature of the chamber (193.15 K) for the experimental model and 3 K for

the on-orbit model. The experimental model lacked the solar cells and antennas but included the experimental

heaters and the insulator to set the system into the environmental chamber. The insulator was made from PTFE. It

was placed between the engineering model and the rectangular segment of the chamber. The heater inputs were

assumed to be diffused for each panel and were set to the mean values of the panel because the side plate was made

from aluminum alloy. The model calibration was performed by adjusting the thermal properties and contact thermal

resistance. The left-hand figure in Figure 6 shows an overview of the constructed model for the on-orbit application.

The right-hand figure shows the experimental model.

Table 4 shows the main materials of each component and the surface characteristics. The S&F antennas consist

of three materials: the inner conductor material was copper, the insulator material was Teflon, and the outer

conductor material is the tin-plated copper. Table 5 shows the thermal properties after calibration. The properties

Figure 6. Overview of the thermal mathematical model (left: on-orbit, right: experimental).

PTFE


7

were calibrated to reduce the error from the experimental result based on the literature value.11-15 Table 6

summarizes and compares the experimental and analytical results.

Table 4 Main Materials of Each Component and the Surface Characteristics. Inside Surface

MainCAM AL5052 Black alumite

Structure AL5052 AL5052

Internal structure supporter Titanium Titanium

GNSSR FR4 Kapton

BAT Battery Black alumite

S&F antenna Copper/Teflon/ Tin-plated copper Tin

UHF antenna SK95-CSP Kapton

Torquer Copper Copper

PCU FR4 FR4

COMM FR4 FR4

MOBC FR4 FR4

Solar cell SAP SAP

UHF-T/-R AL5052 Black alumite

Table 5 Thermal Properties of Main Materials.

Solar absorptivity Emissivity Thermal conductivity W/m2・K Density kg/m3 Heat capacity J/(kg・K)

AL5052 0.08 0.15 138 2680 960

SAP 0.651 0.85 20 5307 325

Kapton 0.366 0.8 - - -

FR4 0.8 0.8 0.3 1900 1369

Copper 0.02 0.02 386 8940 384.5

SK95-CSP - - 47.8 7830 486

Teflon 0.8 0.8 4.6 940 1890

Black alumite 0.88 0.88 - - -

Tin 0.05 0.05 - - -

Titanium 0.1 0.1 17.1 4500 520

Battery - - 44 7850 478

We performed the calibrations in the following three categories to reduce the error between the experimental and

analysis results: 1) the thermal balance with the environment, 2) thermal conductance between the components and

frames, and 3) thermal distribution in the components.

For the thermal-balance calibration, we performed the calibration of optical parameters of the aluminum tapes

and plates. The heaters were covered in aluminum tape and the optical property was different from the aluminum

plates, which were used for the structure panel. Therefore, we calibrated both optical parameter separately.

For the thermal conductance, the thermal conductance between the frames was different from those of the sides.

There was a huge difference in the thermal conductance between the side panels and between the side and upper or

bottom frame. The results show that the latter was a quarter of the former. The conductance between the components

and supporting frames also differed among the components. The components can be divided roughly into three

groups; 1) MOBC and mission equipment, 2) COMM, PCU, and Battery, and 3) UHF-R/-T. The thermal

conductance was calibrated separately for each category. The value in category 1) was a third of that for category 2).

For thermal distribution, the larger thermal distribution was seen in each component than the experiments. The

error source was the thermal property difference in the electric circuit because the components mainly consist of the

electric circuit boards. Therefore, we updated the FR4’s thermal properties referring to the literature data.

The comparison results show the relatively large errors of the centers of the side panel temperatures. The heater

input assumption caused these errors. There were no heaters around the centers of the side panels as shown in

Figure 4, but the analysis model assumes an averaged heater input for each panel. In addition to these errors, there

are relatively large errors in torquers and RW under the hot condition. These temperature errors are assumed to be

caused by the intermittent operation of the actuators. The duty cycle of the magnetic torquers are 100 %, and the

RW was not operated; however, the thermal conductance between these components was very small and the torquers

operation also affected the RW temperature. The heater input was identical for the side panels; however, the

temperature results are asymmetric for each panel. The asymmetry and errors come from the component layout. The

magnetic torquers are set around the middle of the satellite, and parallel to the -X and -Y side panels. They are

placed close to those panels. The actuators power were not small and this fact caused the large errors. The other

components experimental results are generally consistent with the analysis results.


8

Table 6 Summary of the Experimental and Analytical Results.

Exp. Anal. D Exp. Anal. D

CH1 MainCAM 30.1 37.9 7.8 -30.2 -30.0 0.2

CH2 MOBC1(center) 63.6 65.4 1.8 -21.4 -16.4 5.0

CH3 MOBC2(side) 52.5 61.4 8.9 -24.5 -21.2 3.3

CH4 COMM1(center) 57.7 64.2 6.5 -13.6 -10.5 3.1

CH5 COMM2(side) 56.8 62.2 5.4 -14.3 -10.9 3.4

CH6 BAT 47.9 52.3 4.4 -17.8 -16.0 1.8

CH7 UHF-T DCDC 40.9 51.4 10.5 -22.4 -16.9 5.5

CH8 UHF-T/-R 45.1 51.7 6.6 -21.6 -16.3 5.3

CH9 RW 43.1 51.1 8.0 -29.2 -27.3 1.9

CH10 Torquer Blacket 42.2 40.9 -1.3 -29.0 -27.4 1.6

CH11 -X[Up] 31.1 31.6 0.5 -30.0 -32.7 -2.7

CH12 -X[Middle] 20.7 39.5 18.8 -35.3 -26.8 8.5

CH13 -X[Down] 35.0 38.3 3.3 -27.1 -27.2 -0.1

CH14 -Y[Up] 32.6 38.9 6.3 -29.6 -27.9 1.7

CH15 -Y[Middle] 32.2 40.2 8.0 -29.3 -27.2 2.1

CH16 -Y[Down]

CH17 +Y[Up] 28.1 31.5 3.4 -31.8 -32.7 -0.9

CH18 +Y[Middle]

CH19 +Y[Middle] 30.3 39.9 9.6 -30.9 -27.0 3.9

CH20 +Y[Middle] 22.3 40.0 17.7 -34.2 -27.1 7.1

CH21 +Y[Down] 32.7 38.3 5.6 -28.4 -27.1 1.3

CH22 +X [Up] 31.8 28.2 -3.6 -30.0 -27.6 2.4

CH23 +X[Middle]

CH24 +X[Middle] 21.7 29.4 7.7 -34.4 -27.2 7.2

CH25 +X[Middle] 30.0 29.6 -0.4 -31.6 -27.2 4.4

CH26 +X[Down] 30.5 29.1 -1.4 -29.4 -27.4 2.0

CH27 +Z[center] 15.4 15.0 -0.4 -35.6 -32.7 2.9

CH28 +Z[edge]

CH29 -Z[center] 22.7 23.6 0.9 -32.5 -29.7 2.8

CH30 -Z[edge] 19.5 23.6 4.1 -33.5 -29.7 3.8

HOT, ℃ COLD, ℃

IV. Pre-Launch Thermal Profile Estimation

This section performs the on-orbit temperature profile estimation for the specific orbital scenario by using the

constructed thermal-mathematical model in Section III. The orbital conditions were defined as follows: an

inclination was 31°, a right ascension of the ascending node was 68 deg, a semi-major axis was 7,211 km, and an

eccentricity was 0.09 at 23:00 UTC, on November 30, 2016. The solar flux16 was set to 1,366 W/m2 and Albedo

coefficient was set to 0.35. The Earth IR is included in the analysis and the Earth temperature is set to 250 K. The

satellite was spin stabilized around its Z-axis with a high spin rate. The +Z axis was along to the Earth-centered

direction. The power consumption conditions, which are deeply related to the internal heat conditions, were defined

as Table 7. The transmitter’s operation time was defined from the maximum access duration of the ground station.

Figures 7 and 8 show the on-orbit averaged component temperatures estimation results under Table 7 conditions.

Figure 7 shows the hot case and Figure 8 shows the cold case results. Table 8 summarizes the highest and lowest

temperature for each component and condition.

Table 7 Power Consumption Condition (on-orbit, worst case).

Hot case Cold case

MainCAM 5(600 sec around the perigee) -

SubCAM 3(600 sec around the perigee) -

PCU 0.153(const.) 0.154(const.)

COMM 0.5+0.32(const.) 0.5(const.)

MOBC 1.11(const.) -

-T: 5.68(1600 sec around the perigee) -T: 5.68(1601 sec around the perigee)

-R：0.1(const.) -R：0.2(const.)

Torquer 0.85(x), 0.85(y), 0.75(z)(const.) -

Power comsumption，W

UHT-R/-T


9

Table 8 Highest and Lowest Temperature for Each Component and Condition, ℃.

Max Min Max Min

MainCAM 11.5 -0.7 -1.7 -12.3

SubCAM 35.1 -11.1 9.3 -22.8

BAT 52.8 45.3 38.4 30.9

PCU 48.9 43.5 29.1 23.9

COMM 49.0 43.5 24.7 19.5

MOBC 50.0 42.6 11.8 5.2

UHF-R/-T 63.1 44.0 49.7 30.6

S&F 42.4 34.6 16.5 9.2

GNSSR 22.5 -11.3 10.5 -23.0

Torquer 21.7 -10.0 6.9 -22.8

ColdHot

The operational temperature ranges are highlighted in Figures 7 and 8. Here, some overshoots are found in

MainCAM in the cold case and BAT and UHF-T in the hot case. MainCAM does not plan to operate during the cold

case as shown in Table 1, and the researchers decided not to apply the additional modification for this problem. The

operational temperature ranges were determined from the verified temperatures in the thermal chamber experiments.

MainCAM experienced ─30 ℃ in the non-operational mode during the cold case of the thermal vacuum test, and no

problem occurred after that. Therefore, the project accepted this temperature overshoot. The temperature overshoots

of BAT and UHF-T in the hot case have a deep relationship to the continuous operational duration of the transmitter.

Their temperature profiles are not related to the orbital motion and merely follow the operation of the transmitter.

When the transmitter was not in operation, the temperature decreased because only the receiver was in operation.

The researchers decided to limit the system operation duration and not to re-design the thermal system because of

the lack of additional thermal design capacities from the satellite specification constraints. If the transmitter

Figure 7. Hot case analysis results.

Figure 8. Cold case analysis results.


10

operation duration is limited to 1,000 s, UHF-T temperature becomes 33-50 ℃ in hot case, and BAT temperature

35-41 ℃. Therefore, the project decided to limit the continuous transmitter operation to 1,000 s.

V. Calibration of Thermal Mathematical Model with the On-orbit Measurement Data

This section performs the thermal-mathematical model calibration by using the on-orbit measurement data. At

first, the difference between the orbit environment and operation condition is summarized. Then, the thermal-

attitude correlation analysis sequence is proposed, and its details are explained. Finally, the implementation results

are shown with the on-board measurement data.

A. Actual Orbital and Satellite Conditions

The actual orbital and attitude conditions have differences from the pre-launch analysis conditions. The apogee

of the actual orbit is approximately 2,000 km despite the perigee is almost the same as the pre-launch information.

The launch epoch is also different. The de-spin operation was failed at the beginning of the operation, and it caused

some attitude variation. The spin axis also varied from the Z axis to the X axis during the operation because of its

energy dissipation. The antenna or other appendices affected the satellite as energy dissipators. Such a semirigid

body is stable only when spinning around its major inertia axis. The satellite initially spun about its minor inertia

axis; however, it was an unstable state. Therefore, it entered a tumbling mode and eventually reoriented itself into a

stable state, spinning around the maximum inertia axis.17 These facts caused the difference in the thermal input

profile from the pre-launch analysis. The satellite was assumed to achieve spin stabilization around its Z axis with a

high spin rate, with the spin axis was along to the Earth-centered direction. The operation mode was also

reconfigured, and the satellite did not experience long-term stable operation under the analysis conditions because of

the components’ status or some other operational reason. Therefore, the exact same operational situation data could

not be obtained from the on-orbit measurements. In addition, the satellite time-stamp data included uncertainties.

These conditions make the calibration procedure complex.

Under these situations, the authors selected some data sets for thermal mathematical model evaluation. The

operation states are the closest and stable condition to the analyzed conditions. The authors select the data with the

MainCAM operation period for the hot case analysis as shown in Figure 9. The data duration was approximately one

orbital period starting from 20:30 UTC, on February 16, 2018. Here, PCU, COMM, UHF-R, and MOBC were

turned on. MainCAM and UHF-T were operated intermittently. For the cold case, the operation period data with

PCU, COMM, and UHF-R/-T were selected as summarized in Figure 10. The data has no continuousness because of

hardware failure. The authors noticed the interruption of MOBC telemetry during the operation on February 19,

2018. MOBC, which manages the control and data handling of the camera and stored telemetry, has been failed to

perform data handling until the end of the satellite lifetime. Because of this failure, the continuous measurement

could not be stored, but the data duration is approximately 1.4 orbital periods starting from 18:45 UTC, on March 10,

2018. The realistic solar flux was defined by using the SORCE (Solar Radiation & Climate Experiment)’s total solar

irradiance measurement at Earth distance.18 It was approximately 1,393.7 W/m2 for Figure 9 condition and

1379.3 W/m2 for Figure 10 condition.

The satellite environmental situation was quite different from the design one. Fortunately, all components

temperature were within the operational ranges. The transmitter temperature increased around the ground-station

operation duration, as highlighted in Figure 9. This tendency can also be seen from the pre-launch analysis.

Figure 9. Hot case on-orbit results.


11

B. Thermal-Attitude Correlation Analysis

The proposed analysis sequence is summarized in Figure 11.

The data example for the explanation of the sequence is based

on the hot case whose temperatures are already shown in

Figure 9. At first, the satellite status data are taken as the input

of the sequence. The orbital data are generated from the TLE

(Two Line Element) released by the JSpOC (Joint Space

Operations Center) through the Space-Track website.19 The

other status data come from the satellite telemetry: including the

satellite time, angular rate, solar-cell current, magnetometer,

temperature, and components’ operation status. Before the

detailed analysis, the certainty of the time-stamp trend is

evaluated by comparing the magnetometer sensor data

magnitude with the theoretical magnitude values calculated

from the IGRF-12 model,20 as shown in Figure 12. Here, the

telemetry data were affected by the sensor noise or disturbance,

but a similar variation trend to that of the model is obtained.

Then, a rough attitude estimation is performed based on the

magnetometer, gyro sensor, and solar-cell current measurements.

Figure 13 shows the sun aspect angle estimation results for each

side panel obtained with the normalization of the measured current data by the expected maximum current. The

angle becomes zero when the sunlight inserts normal to the panel. Figure 14 shows the angular rate determined by

the gyro sensor. Figure 15 shows the angle between the magnetometer measurement and the theoretical magnetic

vector. The time-series attitude data are obtained by combining these data as summarized in Figure 16. These data

become the input for the thermal analysis model together with the orbital data.

Rough attitude estimation

Orbital estimation

Thermal analysis

Satellite data

Error caused by

thermal input

Error caused by

thermal property

Vivificated Model

No

No

Yes

Yes

Figure 11. Sequence of Thermal-Attitude

Correlation Analysis.

Figure 12. Time stamp verification by the magnetometer measurement.

Figure 10. Cold case on-orbit results.


12

Figure 13. Sun insertion angle estimation.

Figure 15. Angle between the magnetometer measurement and the theoretical magnetic vector.

Figure 16. Attitude estimation.

Figure 14. Angular rate by gyro sensor.


13

The analysis results are compared with the on-board measurements from two points of the views. One is the

whole system temperature trend, and the other is the components temperatures trends. If the whole satellite system

has a difference from the measurements, the satellite attitude profile is updated because the errors can be assumed to

be caused by the thermal input variation. If some specific components data have a difference from the measurements,

the thermal properties of those components, as represented by the thermal contact resistance, are updated to be close

to the measurements.

C. Implemental Results

Figures 17 and 18 show the implementation results for the hot case. Figure 17 shows the side panels’

temperatures, and figure 18 shows the internal components temperatures. Here, the measurements are plotted as

scatter points, and the analysis results are plotted as lines. From this comparison, there is the possibility of

implementation errors, regarding the temperature sensors of MOBC and MainCAM. Their input ports are next to

each other, and the analysis results also become closer if they exchanged each other. The difference between the

whole-satellite temperatures becomes relatively large in the latter part. The satellite time-stamp uncertainty in the

telemetry might affect this difference because this effect is out of the main calibration target. The analysis results

obtained with the established model show acceptable differences of less than ± 5 ℃ from the on-orbit measurement

data.

Figures 19 and 20 show the implementation results for the cold case. Figure 19 shows the side panels’ results

and figure 20 shows the internal components temperatures the same as the hot case. Again, the measurements are

plotted as scatter points, and the analysis results are plotted as lines. The whole-satellite analysis is shifted to a

higher temperature compared with the analysis results. The analysis results with the established model show

acceptable differences of less than ± 5 ℃ from the on-orbit measurement data.

0 0.2 0.4 0.6 0.8 1.0

Orbital period, rev

-10

0

10

20

30

40

Tem

per

ature

, C

o

PZ

MZ

PY

MX

pz-anl

mz-anl

py-anl

mx-anl

Figure 17. Comparison of the side-panel temperatures.

0 0.2 0.4 0.6 0.8 1

Orbital period, rev

-10

0

10

20

30

40

Tem

per

ature

, C

o

MainCamera

COMMCPU

Battery

MainCPU

Transmitter

Transmitter DCDC

MainCamera-anl

COMMCPU-anl

Battery-anl

MainCPU-anl

Transmitter-anl

Figure 18. Comparison of the inner components temperatures.


14

0 0.2 0.4 0.6 0.8 1 1.2 1.4

Orbital period, rev

-20

-10

0

10

20

30

40

Tem

per

ature

, C

o

PZMZ

PYMX

pz-anlmz-anl

py-anlmx-anl

Figure 19. Comparison of the side-panel temperatures.

0 0.2 0.4 0.6 0.8 1 1.2 1.4

Orbital period, rev

-20

-10

0

10

20

30

40

Tem

per

ature

, C

o

MainCamera

COMMCPU

BatteryMainCPU

TransmitterTransmitter DCDC

MainCamera-anlCOMMCPU-anl

Battery-anlMainCPU-anl

Transmitter-anl

Figure 20. Comparison of the inner components temperatures.

D. Discussion

At first, the analysis results show acceptable differences of less than ± 5 ℃ from the on-orbit measurement data

under both hot and cold conditions. This fact shows the effectiveness of the proposed method. Then, the differences

between the pre-launch and on-orbit model are discussed. The uncertainties on the surface properties of the SAP

(solar array panel) in the on-ground experimental condition. They are the most significant differences caused by the

on-ground experimental condition. This difference affects the thermal input for the system. The heat capacity of the

satellite system is very small and the difference affects the transition analysis results. The difference cannot be

reduced with only a system-level experiment with the skin heater method. The additional thermal property

measurements or estimation with the experiments might help to reduce the uncertainties. In this calibration, we

added the solar aspect angle dependence on SAP’s absorptivity, based on experiments of the power generation and

literature data. For the thermal input variation, the effect from the attitude condition variance is very important

because it varies the relationship between the sun and the Earth aspect angle to the satellite; however, the attitude

control ability has differences depending on the system or project requirements. Therefore, detailed pre-launch

attitude and thermal analysis must be performed to confirm the thermal input variation and its results.

The transition analysis was also affected by the variation of the contact thermal resistance between the structural

panels and components. This can be viewed as being another significant difference. For example, PCU’s contact

thermal resistance affects the whole-satellite temperatures because it has a relatively large amount of power

continuously, and is close to the side panel. One of the candidates for this variation is causing by manufacturing.

The fact can be seen from the comparison of the pre-launch analysis and the on-orbit data. The established thermal-

mathematical model has differences in the contact thermal resistance. In case of this satellite, the inside of the

satellite system was filled with instrumentation cables, and it is very difficult to control the contact area or

conditions with the surrounding. Therefore, the component contacting analysis and control is important for the

system design phase. The instrumentation cables also affect the satellite heat capacity, and this modeling error

causes the thermal transition estimation error.

As explained before, the heat capacity is very important for system stability in terms of thermal management. A

proper heat capacity also has to be designed to obtain or increase the robustness against the thermal conditions.


15

VI. Conclusion

This paper describes the thermal design, thermal mathematical model construction, and on-orbit evaluation

results for the 3U CubeSat-class nanosatellite TRICOM-1R, mainly focusing on acceptable temperature ranges. The

discussion is mainly focused on keeping the components temperatures acceptable range during the on-orbit

operation phase. A pre-launch thermal mathematical model was constructed through a limited number of

experiments with the previous design hardware design. The authors propose a cross-calibration sequence for attitude

and thermal properties, and evaluated the method by means of the analysis with on-board measurement data. The

analysis results obtained using the established model showed acceptable differences of less than ± 5 ℃ from the on-

orbit measurement data. The details of the differences are discussed and concluded that the effect of the variation in

the contact thermal resistance is significant for a satellite of this size. In addition, the satellite attitude also affects the

results because of the small heat capacity of the satellite and the large variation in the thermal input causing by the

attitude variation. The information could be used in the design and analysis of similar spacecraft developments in

the future.

Acknowledgments

This development program was funded by the Ministry of Economy and, Trade and Industry JAPAN and

industry investments. Part of this work was subsidized by JKA through its promotion funds from KEIRIN RACE.

References 1SpaceWorks, “2019 Nano/Microsatellite Market Forecast,” https://www.spaceworks.aero/wp-content/uploads/Nano-

Microsatellite-Market-Forecast-9th-Edition-2019.pdf, 2019. [cited 30 Jan. 2019]. 2Tsuruda, Y., Aoyanagi, Y., Matsumoto, T., Nakasuka, S. and Shirasaka, S., “System Design and Operation Result of

Hodoyoshi-3 and -4: the Micro-Satellites Based on Reasonably Reliable System Engineering,” IEICE technical report, 116(115),

13-18, 2016-06-24 (in Japanese). 3Aoyanagi, Y., Matsumoto, T., and Nakasuka, S., “Development of Satellite Bus for 3U-CubeSat TRICOM-1,” Proceedings

of the 61st Space Sciences and Technology Conference, JSASS-2017-4189 (in Japanese). 4Inatani, Y., and Otsuka, H., “SS-520 Nano satellite launcher and its flight result,” 32nd Annual AIAA/USU. Conference on

Small Satellites, SSC18-IX-03, URL: https://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=4120&context=small

sat [cited 20 Feb 2019]. 5Press Releases of the University of Tokyo: Successful of the launch of Nanosatellite ”TRICOM-1R(Tasuki),” the image

acquisition experiment by COTS imager, the functional demonstration for responsive observation, and S&F, https://www.t.u-

tokyo.ac.jp/shared/press/data/setnws_201802211351495770963444_207260.pdf, [cited 1 Aug. 2018] (in Japanese). 6Obata, T., Nakasuka, S., Aoyanagi, Y., and Matsumoto, T., “The Goal-oriented Robust Operations and Their Demonstration

on Orbit,” Proceedings of 2018 SpaceOps Conference, AIAA 2018-2575. 7Matsumoto, T., Aoyanagi, Y., Obata, T. and Nakasuka, S., “The result of Store and forward mission of TRICOM-1R

microsatellite using LoRa modulation,” Proceedings of the 62nd Space Sciences and Technology Conference, JSASS-2018-4137

(in Japanese). 8Aoyanagi, Y., Matsumoto, T., Obata, T. and Nakasuka, S., “Development and On-orbit result of TRICOM-1R “TASUKI”,”

Proceedings of the 62nd Space Sciences and Technology Conference, JSASS-2018-4136 (in Japanese). 9C&R technologies, Thermal Desktop user’s manual CAD Based Thermal Analysis and Design Version 5.7 October 2014. 10JAXA, “Thermal vacuum test handbook”, JERG-2-130-HB005B URL: http://sma.jaxa.jp/TechDoc/Docs/JAXA-JERG-2-

130-HB005B.pdf [cited 20 Feb 2019]. (in Japanese). 11Wiberg, A., “Thermal Study on hardware with comparisons between physical measurements and simulations”, ABB

Automation Tech-nologies AB, Tech. Rep., 2005 12Zhanli, J. and Joshi, S. C., “Thermal Control Schemes for a Micro-Satellite with All-Active and Selectively Active Solar

String Designs,” Heat Transfer Engineering, 27:10, 80-89, (2006) DOI: 10.1080/01457630600908644 13MatWeb: Online Materials Information Resource, http://www.matweb.com/ [cited 20 Feb 2019]. 14Gilmore, D. G. (Ed.), Spacecraft thermal control handbook, 2nd ed., Vol.1, Aerospace Press, El Segundo, 2002 15Onishi, A. (Ed.), Thermal Design of Spacecraft, The University of Nagoya Press, 2014 16JAXA, “Design Standard, Spacecraft Thermal Control System,” JERG-2-310, http://sma.jaxa.jp/en/TechDoc/Docs/

E_JAXA-JERG-2-310_08_RE.pdf [cited 3 Apr 2019]. 17M.H. Kaplan, Modern Spacecraft Dynamics and Control, John Wiley & Sons, New York, 1976. 18Home Page of the SOlar Radiation and Climate Experiment (SORCE), http://lasp.colorado.edu/home/sorce/data/tsi-data/

[cited 3 Apr 2019]. 19Space-Track.org [online database], URL: https://www.space-track.org/ [cited 20 Feb 2019]. 20Thébault, E., et al., “International Geomagnetic Reference Field: the 12th generation,” Earth, Planets and Space, Vol. 67,

No. 1, 2015, pp. 79.

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