College of Engineering Electrical Engineering Dept.

College of EngineeringElectrical Engineering Dept.Power System Architecture for Cubesat

A Graduation Project presentation

Presented by:Abdulaziz Hilal AlKuwariHassan Hisham MiqdadAhmed Bassam Diab

Supervisors:Dr. Ahmed MassoudDr. Tamer Khattab

Spring 2014

2

Presentation overview• General Introduction About Cubesat.• Project Objectives.• System Divisions .• Time Schedule.• Simulation of QUbeSat Power System Architecture.• Test Results and Analysis• Modelling of the DC-DC Buck Converter.• Control of the DC-DC Buck Converter.• PV Model / Maximum-Power-Point-Tracking (MPPT).• Practical Implementation.• Project Cost • Future Work and Conclusion.

3

Literature Review

• The satellite industry was only restricted to the space agencies and institutes till the first picosatellite was created.

• Cubesat design standards have been developed by the Joint cooperation of California Polytechnic State University (Cal Poly) at 1999.

• Low Earth Orbit space missions.• Life span of about 9 months on an average.

4

Literature Review (cont’d) • General Cubesat standards and requirements

5

Why Cubesat?Universities develop Cubesat because of :

• The fact that the components needed to have complete satellite system are already available on shelf with lower cost.

• It is a standardized system which makes it simple to design the system and launch it.

6

Some Previous Cubesat Missions (cont’d)Number of successfully launched Cubesats versus the date of launching:

7

Mission of QU Satellite (QUbeSat)

Qatar university Cubesat (QUbeSat) mission is to map and observe the current waste disposal sites in Qatar and search for the illegally disposed waste in the desert.

gomspace.com

8

Project Objectives

• The aim of the project is to design power supply architecture for the (QUbeSat) that is responsible for feeding all the satellite subsystems.

• The architecture is composed of different stages including power generation, storage and finally distribution.

9

Time ScheduleThe over all project life is three years!

10

System Divisions

11

Simulation Of QUbeSat Power System Architecture• The overall power system

architecture of QUbeSat has been simulated using MATLAB/Simulink.

• The system losses (hence efficiency) are assessed including non-idealities of the system components under different scenarios.

12

Simulation Of QUbeSat Power System Architecture(cont’d)

Solar Arrays• The five side of the satellite are

connected in parallel.• Type of the PV panels is triple

junction.

MPPT Converter• Transfers the maximum power

from the solar array which maximizes the system efficiency.

gomspace.com

13


Battery Pack• Lithium-ion type.• Two connected in parallel

having a rated capacity of total 1800 mAh and nominal voltage of 7.4V.

Power Conditioning Converters• Power condition converters step

down/up the voltage of the battery to supply the satellite subsystems

gomspace.com

Simulation Of QUbeSat Power System Architecture(cont’d)• Open circuit voltage of the PV

array is 5.38V.• Nominal voltage of the battery

is 7.4V.• Aim of the MPPT-converter is to

step up the PV array voltage to the battery level.

14

15

Simulation Of QUbeSat Power System Architecture(cont’d)The schematic of buck converter (including imperfections)

The schematic of boost converter (including imperfections)

16

Simulation Of QUbeSat Power System Architecture (cont’d)• Three voltage levels to supply

the loads.

• The three converters simulated with the added imperfections.

• The three converters are connected in parallel with the battery.

17

Simulation Of QUbeSat Power System Architecture(cont’d)• The design values (for QUbeSat)

L design C design

3.3V Buck Converter 22uH 100uF

5V buck Converter 22uH 220 uF

15V boost Converter 100 uH 22 uF

18


19

Test Results and Analysis

The different cases of the PV irradiation

Case 1: PV module irradiance is not

enough to supply power to the system

Case 2: PV module irradiance is enough to supply power to

the system

Case 3: PV module irradiance is

approximately zero

20

Test Results and Analysis (cont’d)Case 1:• The power flow diagram below where the positive sign indicates

loading and negative sign indicates supplying powerThe efficiency of the MPPTC

The efficiency of 5V buck

The efficiency of 3.3V buck

The efficiency of 15V boost

21

Test Results and Analysis (cont’d)Case 2: • The power flow diagram below where the positive sign indicates





22

Test Results and Analysis (cont’d)Case 3: • The power flow diagram below where the positive sign indicates





23

Efficiency of the Overall System

24

Efficiency of the Overall System (cont’d)

Efficiency of the overall system

case 190.33%

case 289.2%

case 394.29%

25

Modeling of the DC-DC Buck Converters • The step response of the converters shows large overshoot• Loads are sensitive to small voltage variations• The response can be improved closed loop control technique• An accurate model is needed to design the controller

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

x 10-3

0

1

2

3

4

5

Time (sec)

Out

put V

olta

ge (

v)

Ub: R

26

Modeling of the DC-DC Buck Converters (cont’d)• The most significant imperfections that appears in the converter are:

1. The voltage drop across the diode.2. The voltage drop across the switch.3. The on-state resistance of the diode.4. The on-state resistance of the switch.5. The ESR of the Capacitor.6. The internal resistance of the inductor.

27

Modeling of the DC-DC Buck Converters (cont’d)

On-state Off-state


28

1State Space

Representation for the On

mode

2State Space

Representation for the Off

mode

3State

Averaging method

( produces non-linear

model)

4Linearization

by Taylor's series first

order approximation

5Transfer function

29

Modeling of the DC-DC Buck Converters (cont’d)• State space representation of the on-state mode of the buck converter

• State space representation of the off-state mode of the buck converter

30

Modeling of the DC-DC Buck Converters (cont’d)• State Averaging• The switch is on at the time dT and off at the time (1-d)T. Thus the on-

state and off state representations can be averaged as follow:

31

Modeling of the DC-DC Buck Converters (cont’d)• The Linearized Model of the Buck Converter

32


33

Modeling of the DC-DC Buck Converters (cont’d)• Result of the Buck DC- DC model

0.145 0.15 0.155 0.16 0.165-10

-5

0

5

10

15step response of the ideal buck converter (7.4-3.3)V

time (sec)

outp

ut v

olta

ge (V

)

0.145 0.15 0.155 0.16 0.165-10

-5

0

5

10

15step response of the modeled buck converter (7.4-3.3)V

time (sec)

outp

ut v

olta

ge (V

)

0.145 0.15 0.155 0.16 0.1651

2

3

4

5

6

7

8

9step response of the simulink buck converter (7.4-3.3)V

time (sec)

outp

ut v

olta

ge (V

)

Ideal Converter Derived Model Converter Physical Converter

34

Control of DC-DC Buck Converters• State Feedback Control

35

Control of DC-DC Buck Converters(Cont’d)• State Feedback Control with Integral Action

36

Control of DC-DC Buck Converters(Cont’d)

Desired Time Domain Specification (7.4-3.3) V Buck Converter (with integral)

Percent Overshoot

Peak Time Rise Time Settling Time

Damping factor

0.005 0.002 sec 0.6036 msec

0.8078 msec

0.9532

The gain vector was calculated based on the following time domain specifications

The parameters used to simulate the converter

37

Control of DC-DC Buck Converters(Cont’d)

0 1 2 3 4 5

x 10-3

0

0.5

1

1.5

2

2.5

3

3.5the output voltage of the compensated (7.4-3.3)V converter without distrubance

time (sec)

volta

ge (V

)

38

Control of DC-DC Converters (Cont’d)

0 0.005 0.01 0.015 0.02 0.025 0.030

1

2

3

4

5

6

7

8the input voltage of the compensated (7.4-3.3)V converter with distrubance

time (sec)vo

ltage

(V)

0 0.005 0.01 0.015 0.02 0.025 0.030

0.5

1

1.5

2

2.5

3

3.5the input voltage of the compensated (7.4-3.3)V converter with distrubance

time (sec)

volta

ge (V

)

39

PV Model• The aim of the PV model is to test the operation of the MPPT

algorithm.

• The available Practical PV Panel in the Lab is the 120W Polycrystalline BCT120-24.

• The PV model chosen for the simulation is the Single-Diode general model.

40

PV Model (Cont’d)• The P-V characteristic curve of the Simulated Polycrystalline PV Panel

for different solar insolation and temperature respectively.

41

Maximum-Power-Point-Tracking (MPPT)• MPPT can be achieved by different approaches and techniques, but

the well-known and widely used algorithm is the Perturb & Observe (P & O) method because of:

• Its simple implementation.• Reasonable convergence speed.

• P & O technique can be well visualized in the figure shown in the next slide.

42

Maximum-Power-Point-Tracking (cont’d)• The (P&O) MPPT illustration is on Buck converter.

43

Maximum-Power-Point-Tracking (cont’d)• P&O method can be classified into:

• Fixed perturb.• Adaptive perturb.

• P&O with fixed perturb suffers some demerits and drawbacks:• Steady-state oscillations around the MPP due to fixed periodic tuning.• Possibility of tracking failure for rapid change of the atmospheric conditions

especially the solar isolation.

• The problem of steady-state oscillations can be minimized by applying small perturbation step-size, but results in slow down of the system.

44

Maximum-Power-Point-Tracking (cont’d)• Many researches went through improving the P&O method and make

it adaptive-based by utilizing an automatic variable perturb tuning in order to satisfy:

• Fast tracking response toward the maximum power point.• Low steady-state oscillations.

• Can be achieved by applying a large perturb value at starting to reach the MPP fast, then minimize the perturb value to result in lower steady-state oscillations.

45

Maximum-Power-Point-Tracking (cont’d)• The simulation of the (P&O) algorithm has been performed on the

available practical BCT120-24 PV panel to validate the functionality of the MPPT.

• The converter used is Buck converter where its design parameters were chosen same as the practical design achieved in the lab.

Switching Semiconductor

Switching Frequency Load

150 µH 470.0 µF 330.0 µF IGBT 4 KHz12V Battery in parallel with

R= 1.2 Ω

46

Maximum-Power-Point-Tracking (cont’d)• PV module power for sudden change of solar insolation and fixed

temperature (fixed-perturb of = 0.0001).

47

Maximum-Power-Point-Tracking (cont’d)• PV module power for sudden change of solar insolation and fixed

temperature (adaptive-perturb of + (0.005 ×|dP/dV|)).

48

Practical Implementation• Converter Design Parameters.

ConverterSwitching

Semiconductor

Switching Frequency

MPPT Buck

150 µH 470.0 µF 330.0 µF IGBT 4 KHzBattery +

PCC

3.3 V Buck 125 µH 1000 µF 1000 µF IGBT 10 KHZ 6.9 Ω

5.0 V Buck 131 µH 1000 µF 1000 µF IGBT 10 KHz 5.7 Ω

15 V Boost

125 µH 1000 µF 1000 µF IGBT 10 KHz 34.3 Ω

49

Practical Implementation (cont’d)

50

Practical Implementation (cont’d)• State feedback Control on the 5V Buck converter• Open Loop Response

51

Practical Implementation (cont’d)• Closed Loop Response

52

Practical Implementation (cont’d)• Practical Results of the (P&O) MPPT. (Taken at 2:00 PM on 30th of April 2014)

Fixed Perturb of = 0.005 (Transient and Steady-State)

53

Practical Implementation (cont’d)• Practical Results of the (P&O) MPPT. (Taken at 2:00 PM on 30th of April 2014)

Adaptive Perturb of = + (0.005 ×) (Transient and Steady-State)

54

Practical Implementation (cont’d)• In addition to the (P&O), MPPT has been also practically achieved

using the Artificial Intelligence (Neural Network).• A sample of 39 PV-curves were taken on the 2nd of June 2014 from

9:40 AM till 4:00 PM every 10 minutes.• Those samples were used to train the Neural Network of MATLAB

Neural Network wizard which uses Levenberg Marquardt (LM) training algorithm where the performance indices are the mean-squared-error (MSE) and the Regression index (R).

55


Taken at 1:40 PM on 4th of June 2014

56


Taken at 3:00 PM on 4th of June 2014

57

Project Cost

5 panels 1 U QUbeSat 2000.00 EUR

One piece Power modules + battery 3300.00 EUR

58

Conclusion

• A study was conducted about previous lunched cube-satellites• MPPT converter was designed, simulated and implemented.• PC converters were designed, simulated and implemented.• DC-DC Buck converter was modeled, simulated and practically

controlled.

59

Future Work

• Implementation the real standard QUbeSat•Power management•Modeling of triple junction PV panel•Over-current protection

60

Thank You For Your Attention

College of Engineering Electrical Engineering Dept.

Documents

Transcript of College of Engineering Electrical Engineering Dept.