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Simulation and dSPACE Hardware Implementation of

the MPPT Techniques Using Buck Boost Converter

Abdullah M. Noman1, Khaled E. Addoweesh1, and Hussein M. Mashaly2 1 Electrical Engineering Department 2 Sustainable Energy Technologies Center

King Saud University anoman@ksu.edu.sa, khaled@ksu.edu.sa, hmashaly@ksu.edu.sa

Abstract- Maximum power point trackers are so important in

photovoltaic systems to increase their efficiency. This paper

presents a photovoltaic system with maximum power point

tracking facility. The system consists of a photovoltaic solar

module connected to a DC-DC buck boost converter and load. The

system is modeled using MATLAB/SIMULINK. Maximum power

point tracking is achieved using perturbation and observation

method and incremental conductance method. The MPPT system

is simulated and experimentally implemented. The implementation

of the MPPT hardware setup is done using dSPACE real time

control. Data acquisition and the control system is implemented

using dSPACE 1104. The simulation and the practical results show

that the proposed system tracked the maximum power accurately

and successfully under different conditions tested.

I. INTRODUCTION

The energy is important for the human life and economy.

Consequent due to increasing in the industrial revolution, the

world energy demand has also increased. In the later years,

irritation about the energy crisis has been increased. Fossil fuels

have been started to be gradually depleted. On the other hand

people are more concerned about the fossil fuel exhaustion and

other environment problems which are a result of conventional power generation. It is a global challenge to generate a secure,

available and reliable energy and at the same time reduce the

greenhouse gas emission [1]. Energy saving was suggested by

the researchers to meet the worldwide energy demand. But this

method is a cost effective solution. One of the most effective

and suitable solution is the renewable energy supplies.

Renewable energy can solve these problems simultaneously

since they are green and clean, environment friendly and they

are sustainable sources of energy [1, 2].

Renewable energy sources are considered as a technological

option for generating clean and sustainable energy. There are

many sources of renewable energy such as solar energy, wind energy, etc. photovoltaic (PV) system has taken a great attention

since it appears to be one of the most promising renewable

energy sources. The photovoltaic solar (PV) generation is

preferred over the other renewable energy sources due to

advantages such as the absence of fuel cost, clean, pollution

free, little maintenance and no noise due to absence of moving

parts. However, two important factors limit the implementation

of photovoltaic systems. These are high installation cost and

low efficiency of energy conversion [1]. In order to reduce

photovoltaic power system costs and to increases the utilization efficiency of solar energy, the maximum power point tracking

system of photovoltaic modules is one of the effective methods

[3]. Maximum power point tracking (MPPT) is a system used to

extract the maximum power of the PV module to deliver it to

the load [4]. Thus the efficiency is increased [4].

Since the power generated from the photovoltaic module

depends on the temperature and the solar radiation, these factors

must be taken into account while designing the maximum

power point tracker. The main goal of the MPPT is to move the

module operating voltage close to the voltage at which the PV

produces the maximum power under all atmospheric conditions.

MPPT is very important in PV systems. Different techniques have been developed to maximize the output power of the

photovoltaic module. They have advantages and limitations

over the others. These techniques vary in complexity, in the

number of sensors required, in their convergence speed and in

the cost. In this literature survey some of MPPT methods are

introduced such as open circuit voltage method, incremental

conductance method, perturbation and observation method, etc

[1, 4-8]. The open circuit voltage method is based on the fact

that the voltage of the PV module at maximum power point is

linearly proportional to the open circuit voltage [9]. The

proportional factor is K. The voltage at maximum power can be obtained by measuring the PV voltage and multiplying it by the

factor K. Then the operating voltage of the PV module is

adjusted to the calculated voltage in order to obtain the

maximum power. This process must be repeated periodically.

Although this method is simple to implement, it has a drawback

which is high power losses due to periodically interrupting the

system operation. Another drawback is that it is difficult to

choose an optimal value of the constant K [8].

P&O method is an alternative method to obtain the maximum

power point of the PV module. It measures the voltage, current

and power of the PV module and then perturbs the voltage to

encounter the change direction [9]. Fig. 1 shows the P-V curve

of the PV module. As shown in the left hand side MPP the

CCECE 2014 1569877561

1

978-1-4799-3010-9/14/$31.00 ©2014 IEEE CCECE 2014 Toronto, Canada

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power of the PV is increased with increasing the voltage of the

PV module until the MPP is reached. In the right hand side of

the MPP with increasing the voltage the power is decreased.

That means if there is increase in the power the subsequent

perturbation should be kept in the same direction until MPP is

reached. If there is a decrease in the power the perturbation should be reversed [4, 5, 8, 10, 11].

The maximum power point is reached when dP

dV= 0. The flow

chart of P&O method is shown in Fig. 2 (a). In order to

implement the P&O MPPT method the PV voltage and current

must be initially measured. The change in the voltage (∆V) and

the change in the power (∆P) must then be calculated. The PV voltage must then be perturbed by a constant value. If the

perturbation in the voltage causes the power to increase the next

perturbation must be kept in the same direction otherwise the

next perturbation must be reversed.

The incremental conductance (IC) method is one of the

methods used to obtain the MPP of the PV modules. IC is based

on the fact that the slope of the PV array power curve of Fig. 1

is zero at the MPP, positive on the left of the MPP, and negative

on the right. At the MPP, the dP

dV can be expressed as:

−𝐼

𝑉=

𝑑𝐼

𝑑𝑉

(1)

The left hand side of (1) represents the opposite of the

incremental conductance while the right side represents the

incremental variation dI

dV . The variation in the current dV and

the variation in the voltage dI can be approximated to

∆VPV and ∆IPV respectively. Analyzing the derivative one can

test whether the PV generator is operating at its MPP or far

from it [12]. The flow chart of the IC algorithm is shown in Fig.

2 (b).

In this paper, the P&O MPPT method and the IC MPPT

method are simulated using MATLAB/SIMULINK and then

they are experimentally implemented. The implementation of the MPPT hardware setup is done using dSPACE real time

control. Data acquisition and the control system is implemented

by using dSPACE 1104 software and digital signal processor

card on PC.

II. CHARACTERISTICS OF SOLAR MODULE

In order In order to model the PV module, a PV cell model

must be initially established. An equivalent electrical circuit

makes it possible to model the characteristic of a PV cell. In a

practical PV cell, there are two resistances: series resistance and

parallel resistance. Series resistance accounts for the losses in

the current path due to the metal grid, contacts, and current

collecting bus. Parallel resistance due to the loss associated with

a small leakage of current through a resistive path in parallel

with the intrinsic device. Parallel resistance is large and its effect is negligible. The equivalent circuit of the PV cell is

shown in Fig. 3.

The output current delivered to the load can be expressed as

[4][13, 14]:

Where: I is the output current of the solar module (A), V is the output voltage of the solar cell (V), which can be obtained by

dividing the output voltage of the PV module by the number of

cells in series, IPV is the current source of the solar module by

solar irradiance (A), Io is the reverse saturation current of a

diode (A), NS is the series connection number of the solar

module, n is the ideality factor of the diode (n = 1~2), q is the

electric charge of an electron (1.6 × e−19c), k is the

Boltzmann’s constant (1.38 × 10−23j/K ), T is the absolute temperature of the solar cell (oK).

To model the PV module using MATLAB, the current

generated by the incident light which is also called short circuit

current (Isc) at a given temperature (Ta) must be calculated [13-15]:

Where: Iscn is the short circuit current at normal conditions

(25oC, 1000W/m2), Ta is the given temperature (oK) IPVis the

short circuit current at a given cell temperature (Ta), a is the

temperature coefficient of Isc and Gn is the nominal value of

irradiance, which is normally 1000W/m2.

TABLEI PV MODULE PARAMETERS

𝐼 = 𝐼𝑃𝑉 − 𝐼𝑜 (𝑒𝑞(𝑉+𝐼𝑅𝑠)

𝑛𝑘𝑇𝑎 − 1) (2)

𝐼𝑃𝑉 = 𝐼𝑠𝑐𝑛(1 + 𝑎(𝑇𝑎 − 𝑇𝑛))𝐺

𝐺𝑛 (3)

Maximum Power (Pmax) 115W

Voltage at Pmax (Vmp) 17.1V

Current at Pmax (Imp) 6.7A

Open Circuit Voltage (Voc) 21.8V

Short Circuit Current (Isc) 7.5A

Temperature coefficient of Isc 0.065 ± 0.015 %/ oC

0 5 10 15 20 250

20

40

60

80

100

120

Vpv [V]

Ppv [

W]

dI/dv=-I/v

dI/dv<-I/v

dI/dv>-I/v

Fig. 1: Variation of dI/dV in the P-V characteristic of the PV

module.

2

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On the other hand the reverse saturation current of diode (Io)

at the reference temperature (Tn) is given as [13, 14]:

Where: Vocn is the open circuit voltage at normal conditions.

The reverse saturation current at a given cell temperature (Ta)

can be expressed as [14]:

The BP3115 PV module is used in this paper. The PV module

parameters under the reference conditions (1000W/m2, 25oC)

are listed in table 1. The PV module is simulated using

MATLAB/SIMULINK.

Fig. 4 shows the simulated P-V curves of the PV module under

changing solar radiation from 200W/m2 to 1000W/m2 while

keeping the temperature constant at 25oC. On the other hand

Fig. 5 shows the simulation results of the P-V curves of the PV

module under changing temperature from 10oC to 50oC while

keeping the solar radiation constant at 1000W/m2.

III. DC-DC BUCK-BOOST CONVERTER

DC conversion has gained the great importance in many

applications, starting from low power applications to high

power applications. In this paper, buck boost converter is

chosen to be used in the MPPT system. Buck boost converter is

used to step down and step up the DC voltage by changing the

duty ratio of the MOSFET. If the duty ratio is less than 0.5, the

output voltage is less than the input voltage while if the duty

ratio is greater than 0.5 the output voltage is greater than the input voltage. Duty ratio is the time at which the MOSFET is

on to the total switching time. The buck-boost converter is

shown in Fig. 6.

The relation between the input and the output voltages of the

buck-boost converter is given as:

1out in

DV V

D

(6)

Where D is the duty cycle of the converter. The buck boost converter is designed and simulated using

MATLAB/SIMULINK. The converter components used in the

simulation and in the hardware setup is shown in table 2.

𝐼𝑜𝑛 =𝐼𝑠𝑐𝑛

𝑒𝑞𝑉𝑜𝑐𝑛𝑛𝑘𝑇𝑛

− 1

(4)

1 13 ( )( )

( )

g

a n

qE

nK T Ta no on

n

TI I e

T

(5)

Start

Measure V(n), I(n)

Calculate Power P(n)

P(n)-P(n-1)=0

P(n)-P(n-1)>0

V(n)-V(n-1)<0 V(n)-V(n-1)>0

D=D + D=D -

Return

D

Yes

NO Yes

YesNO YesNo

No

D D=D + D D=D - D

(a) Perturb and Observe (P&O) method.

Start

Measure ,PVV PVI

2 1

2 1

( ) ( )

( ) ( )

PV PV PV

PV PV PV

dV V t V t

dI I t I t

PV PV

PV PV

dI I

dV V 0PVdI

0PVdV

PV PV

PV PV

dI I

dV V

D D D

0PVdI

D D D D D D D D D

Yes

No

Yes

No

Yes

Yes

No

No

Yes

No

(b) Incremental Conductance (I.C) method.

Fig. (2): Conventional MPPT flowcharts.

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IV. SIMULATION RESULTS

The P&O and IC MPPT methods are very popular methods

used to track MPP of the PV modules. Both methods are

simulated under changing ambient conditions. Simulation is

done using MATLAB/SIMULINK.

The model used for simulation is shown in Fig. 7 which

includes the PV module, buck boost converter and the MPPT

algorithm. Buck boost converter components are chosen

according to the values presented table 2. In this system the PV

module is connected to the input of the DC-DC buck boost

converter. The output of the converter is the load which is

represented by the 5𝛀 resistor. The PV module is modeled to

provide the PV current and voltage which are then used to feed

the DC-DC converter and the MPPT controller.

TABLEII

Buck Boost Converter Parameters

L 1mH

C1 1000μF

C2 330μF

fs 40KHZ

Resistive Load RL 5 𝛀

Controller Type: dSPACE 1104 DSP

MOSFET Type: IRF3710

Diode Type: BYV32-200

Components Used in the Measurement Circuit

Current Transducer LTS 25-NP

Voltage Divider Two 120K𝛀 and 39K𝛀 resistors

are connected in series. The

voltage is taken across 39K𝛀

resistor.

I

+

_

V

Fig. 3: Equivalent circuit of PV cell simulation.

0 5 10 15 20 250

20

40

60

80

100

120

140

V [V]

P [

W]

10 oc

25 oc

40 oc

55 oc

Fig. 5: P-V Curves under changing the temperature.

Vin

_

+

Vout

+

L

g

DS

MOSFET

[g]

Gate Drive Circuit

+

C2

Diode

+

RL5 ohm

Fig. 6: The buck boost converter circuit.

0 5 10 15 20 250

20

40

60

80

100

120

V [V]

P [

W]

200W/m2

400W/m2

600W/m2

800W/m2

1000W/m2

Fig. 4: P-V curves under changing the solar radiation.

4

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The MPPT controller in this case is the P&O and IC MPPT

methods. The output signal generated from the MPPT algorithm

is the switching signal which is used to drive the MOSFET. In

order to verify the tracking behavior of the P&O and IC MPPT

methods, the system is tested under changing the ambient condition shown in Fig. 8. The temperature is initially kept

constant at 25oC and the solar radiation level is starting at

300W/m2. The solar radiation is the raised up rapidly to

600W/m2 at 0.03 sec. At 0.06 sec the solar radiation is again

raised up rapidly to 1000W/m2. Then the solar radiation is kept

constant while the temperature is changed from 25oC to 50oC at

0.08 sec. The P&O MPPT method tracked the maximum power

successfully and accurately under this ambient condition as

shown in Fig. 9. The P&O MPPT tracking efficiency is 98.37%.

. As shown in this figure, with changing the solar radiation the

PV current is changed but with changing the temperature the PV

voltage is changed. The same ambient condition is applied when the IC MPPT method is used. The tracking behavior of the IC

method is shown in Fig. 10. The tracking efficiency of the IC

MPPT method is 98.38% which is very close to the efficiency

of the P&O MPPT method. The time response of the P&O

MPPT method is 6.5 msec which is a little faster than the time

response of the IC MPPT method which is 7 msec.

V. EXPERIMENTAL SETUP

The implementation of the MPPT hardware setup is done by

using dSPACE real time control. Figure 11 shows the block

diagram of the hardware setup while Fig. 12 shows the

hardware setup of the MPPT system. In the hardware setup, the DC-DC buck boost converter is built according to the values

listed in table 2. One BP 3115J PV module is connected to the

input of the DC-DC converter while the output is the load. Data

acquisition and the MPPT control system is implemented by

using dSPACE 1104 software and digital signal processor card

on PC. The PV voltage and the PV current must be initially

measured. In this system the voltage is measured by using the

voltage divider while the PV current is measured by using the

LTS 25-NP current sensor. The analog measured quantities of

the PV voltage and PV current are fed to the A/D converter of

the dSPACE in order to be used in the SIMULINK MPPT control block. The MPPT control is constructed in the

SIMULINK is shown in Fig. 13. The input signals to a dSPACE

A/D channel must be in the range of -10V to +10V. A signal of

+10V gives an internal value of 1.00 within SIMULINK. Every

signal comes from A/D converter must be multiplied by 10. The

filters are used for removing any high frequency noise or any

switching noise that appears in the signals. As shown in Fig. 13

the instantaneous measured voltage and current is then

multiplied by each other to obtain the PV instantaneous power.

The PV voltage and the PV power are then applied to the MPPT

algorithm to generate the required duty cycle. The output signal

of the MPPT algorithm is then applied to the DS1104SL_DSP_PWM block which is used to generate the

required switching signal to drive the MOSFET. The generated

PWM signals shouldn’t be connected directly to the MOSFET

since the maximum current drown from dSPACE board must

not exceed 13mA. For this reason and for the isolation purposes

a 6N137 optocoupler is used as an interconnection between the

dSPACE system and the hardware setup. The PWM generated

signal from the dSPACE is connected to the 6N137 optocoupler

and the output of the optocoupler is then connected to the

PV Module

v+-vpv1v+

-vpv

vpv

ipv

G

T

measurements

i+ -ipv

T

G

+

-

g

DS

Mosfet

[g]

Goto5

[VB]

[g]

In1

In2

Out1

MPPT Method

i+

-

Temperature

Irradiation

[T]

7

[IL]

[G]

4

[T]

[G]

[ipv]

[vpv]

[vpv]

[Pmax]

[vpv]

[ipv]

RC2LC1

Fig. 7: MPPT System used for simulation.

0

500

1000

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10

20

40

60

G [

W/m

2]

T [

oc]

Fig. 8: Changing the solar radiation with changing the temperature.

0

50

100

150

Ppv

max[

W]

0

10

20

Vpv

ma

x[V

]

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.10

5

10

Time [sec.]

Ipv

max[

A]

Fig. 10: Maximum power tracked using IC MPPT method.

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MOSFET gate on the buck boost converter and manage the on-

off time of the switch.

1. Implementation the P&O MPPT Method

In order to start real time tracking the MPP of the PV module, the SIMULINK MPPT control block must be downloaded to the

dSPACE board to generate C code of the MPPT control block.

The performance of the P&O MPPT varies according the

perturbation step size. A large step size may increase the

tracking speed but at the same time the oscillation around MPP

is increased. Therefore it is important to compromise between

the tracking speed and the oscillation. In the hardware

implementation of P&O of this paper the step size of the duty

cycle is chosen to be 0.001. This step size value gives a better

tracking performance. The P&O MPPT method is tested under

the ambient conditions shown in Fig. 14. This condition was taken from 10:04 AM to 03:04 PM. As shown the upper figure

is the changing in the solar radiation while the lower is the

temperature of the PV module. P&O MPPT method tracked the

maximum power under this condition successfully and

accurately. The maximum power tracked and the related voltage

and current is shown in Fig. 15. With changing the solar

radiation, the maximum power is changed accordingly.

1. Implementation the IC MPPT Method

IC MPPT method is also practically implemented using dSPACE 1104 system. The IC MPPT control block is

downloaded to the dSPACE board to generate C code. In the IC

algorithm, the step size of the duty cycle is chosen to be 0.001

since this step size gives a better tracking performance. The IC

MPPT method is tested under changing the ambient condition

as shown in Fig. 16. It seems that this day was a cloudy day. IC

MPPT tracked the MPP successfully and accurately as shown in

Fig. 17.

VI. CONCLUSION

Photovoltaic model using MATLAB/SIMULINK and

design of appropriate DC-DC buck boost converter with a

maximum power point tracking facility are presented in this

paper. Two algorithms are used in this paper for maximum

power point tracking. These are perturbation and observation

method and incremental conductance method. The models are

tested under disturbance in both solar radiation and photovoltaic

Vo

82 ohm

1UF550 ohm

Temperature in oK

Solar radiation W/m2

+

L

g

DS

IRF3710100V, 57A

1000

25+273

+

C2

+

C1

BYV32-200

+

39K

+120K

+

RL5 ohm120W

16A

Current Sensor

PV ModuleBP 3115J

dSPACE 1104 System

Vcc

Optocoupler6N137

ComputerMPPT Algorithm

Fig. 11: Block diagram of the hardware setup.

Voltage Sensor Calibration

3PPV

2VPVa

1IPVa

P

V

D

MPPT algorithm

Product

10

Gain3

10

Gain2

DS1104SL_DSP_PWM

ADC Channel

DS1104ADC_C6

DS1104ADC_C5

In1 Out1

Current Sensor Calibration

0

1

0

butter

AnalogFilter Design5

butter

AnalogFilter Design1

[P]

9

[vpv]

3

[vpv]

[P]

In1 Out2

ADC Channel

Fig. 13: MPPT SIMULINK model implemented in dSPACE 1104.

Buck boost Converter

dSPACE Hardware

Connection to the PV Module

Fig. 12: The hardware setup of the system.

6

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temperature. Simulation results show that both algorithms

effectively track the maximum power point under different

ambient conditions. The simulation results show that the

tracking efficiency of both methods is very close to each other.

The two MPPT algorithms are then experimentally

implemented. The practical results show how these methods track the MPP effectively and accurately. The results indicating

that the designed MPP tracker with both methods is capable of

tracking the PV module maximum power and hence improving

the efficiency of the PV system.

ACKNOLEDGMENT

This work was financially supported by the National Plan

for Science and Technology (NPST) program of the King Saud

University; Project Number: 09 ENE 741-02.

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0

200

400

600

800

G [

W/m

2]

0 2000 4000 6000 8000 10000 12000 14000 16000 180000

20

40

60

Time [sec.]

Tpv [oC

]

10:04AM

12:00PM

03:04PM

Fig. 14: Changing the ambient conditions. P&O Method.

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50

Pp

v m

ax[W

]

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1

Time [sec.]

Du

ty R

atio

10:04AM

12:00PM

03:04PM

90

Fig. 15: Experimentally Tracking behavior of the P&O MPPT.

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/m2

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Tpv [oC

]

11:10 AM

12:10 PM

04:10 PM

75

Fig. 16: Changing the ambient conditions. IC Method.

0

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Ppv

max

[W]

0

10

20

Vpv

max

[V]

0

5

Ipv

max

[A]

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0.5

1

Dut

y R

atio

90

Time [sec.]

8

11:10 AM

12:10 PM

04:10 PM

Fig. 17: Experimentally tracking behavior of the IC MPPT.

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