||Estimation of Power Behavior in PHOENIX’s Electrical Power Subsystem
||Department of Electrical Engineering
Electrical Power System
Solar Power Generation
Battery Voltage Estimation
Research in space technology and small satellite development has become more predominant in recent years. The 2U CubeSat project, PHOENIX, was developed at NCKU as a part of the QB50 mission and was launched to the International Space Station (ISS) on April 18, 2017 by Atlas V and deployed from ISS on May 17, 2017. It is currently still operational and communicates with NCKU Guiren campus ground station several times every day. PHOENIX consists of several subsystems, the most critical one of which is the Electrical Power Subsystem (EPS), which provides, stores, distributes, and controls the satellite’s electrical power.
Prior to executing any missions, it is necessary to ensure that the power margin is sufficient. Therefore, this thesis proposes a new method to estimate the power behavior of the EPS to avoid overloading and maximize mission performance. In the light of the EPS architecture, there are three parts comprising the estimation: power generation, storage and power consumption. A power generation model builds the basic assessment based on the orbit and solar cells parameters and then compensates for any errors via some correction factors. The storage device, the lithium-ion cells, is like a bridge between the solar cells and loads, which degrades the performance due to the lifetime and the environment, so a proposed algorithm combined with fuzzy logic is used estimate the variations in the battery voltage. Power consumption depends on mission planning. Thus, in this thesis, each scenario is analyzed in order to predict the behavior of each subsystem.
With a view to verifying the power generation model, this thesis employs the data from the 2U RAIKO CubeSats. Moreover, the verification environment was constructed to retrieve the parameters of the lithium-ion battery exploited in the estimation algorithm. On account of PHOENIX’s operation, this innovative method provides predictive capacity for the mission planners and appraises the battery voltage rather than its capacity via the proposed power generation model and the scenario power consumption analyses.
List of Tables VIII
List of Figures IX
List of Abbreviation XI
Chapter 1 Introduction 1
1.1 Overview 1
1.2 Literature Review 3
1.3 Thesis Contributions 5
1.4 Thesis Organization 5
Chapter 2 PHOENIX EPS 7
2.1 QB50 Mission 7
2.2 PHOENIX CubeSat 9
2.2.1 Subsystem and Payload 11
2.2.2 Operation Mode 14
2.3 Electrical Power Subsystem 17
2.3.1 Design Criteria 17
2.3.2 EPS Architecture 18
Chapter 3 Power Generation and Consumption 21
3.1 Power Generation Model 21
3.1.1 Photovoltaic Electrical Characteristics 22
3.1.2 Simulation and Environment Parameters 25
3.1.3 Albedo 28
3.1.4 Battery Charge Regulator (BCR) 30
3.2 Power Consumption 33
3.2.1 Power Condition Module (PCM) 34
3.2.2 Scenarios Analysis 35
Chapter 4 Energy Storage 37
4.1 Lithium-ion Battery Characteristic 37
4.2 Voltage Estimation Algorithm 41
4.2.1 Algorithm Overview 42
4.2.2 Application of Fuzzy Logic 44
4.2.3 Estimation in Eclipse 45
4.2.4 Estimation in Sunlight 50
Chapter 5 Testing and Verification 54
5.1 Power Generation Estimation 54
5.2 Testing Configuration 62
5.2.1 Hardware and Testing Environment 62
5.2.2 Software Architecture for Measuring Parameters 65
5.2.3 Software Architecture for Verifying the Estimation Algorithm 67
5.3 Verification of Battery Voltage Estimation Algorithm 69
5.3.1 Testing Script One 69
5.3.2 Testing Script Two 71
Chapter 6 Conclusions and Future Work 75
6.1 Conclusion 75
6.2 Future Work 76
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