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NOVEL NON-ISOLATED HIGH-VOLTAGE GAIN DCDC

CONVERTERS BASED ON 3SSC AND VMC

ABSTRACT

This project introduces a new family of dcdc converters based on the three-state

switching cell and voltage multiplier cells. A brief literature review is presented to demonstrate

some advantages and inherent limitations of several topologies that are typically used in voltage

step-up applications. In order to verify the operation principle of this family, the boost converter

is chosen and investigated in detail. The analyzed converter can be applied in uninterruptible

power supplies, fuel cell systems, and is also adequate to operate as a high-gain boost stage with

cascaded inverters in renewable energy systems. Furthermore, it is suitable in cases where dc

voltage step-up is demanded, such as electrical fork-lift, audio amplifiers, and many other

applications. The presented converter is implemented in MATLAB SIMULINK and the results

are presented.

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CHAPTER NO. TITLE PAGE

NO.

ABSTRACT

LIST OF FIGURES

LIST OF SYMBOLS

LIST OF ABBREVIATIONS

LIST OF TABLES

i

v

vii

xi

xii

1. CHAPTER 1 : INTRODUCTION

1.1 SCOPE OF TE PROJECT

1.2 EXISTING SYSTEM

1.3.1EXISTINGSYSTEMDISADVANTAGES

1.3.2 LITERATURE SURVEY

1.4 PROPOSED SYSTEM

1.4.1 PROPOSED SYSTEM ADVANTAGES

2. CHAPTER 2 : PROJECT DESCRIPTION

PROJECT DESCRIPTION

2.1 METHODOLOGIES

2.1.1 MODULES NAME

2.1.2 MODULES EXPLANATION

2.2 TECHNIQUE OR ALGORITHM

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3. CHAPTER 3 : SIMULATION THEORY

3.1 SOFTWARE REQUIREMENTS

3.2 Introduction to Matlab

3.2.1 What is Matlab?

3.2.2 Introduction to Simulink

4. CHAPTER 4 : SIMULATION RESULTS

4.1 OPEN LOOP CIRCUIT

4.2 CLOSED LOOP CIRCUIT

4.3 VARIOUS SNAPSHOTS

5.

CHAPTER 5 :

CONCLUSION

REFERENCES

CHAPTER 1

INTRODUCTION

1.1 GENERAL

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Depending on the application nature, several types of static power converters are

necessary for the adequate conversion and conditioning of the energy provided by primary

sources such as photovoltaic arrays, wind turbines, and fuel cells. Besides, considering that the

overall cost of renewable energy systems is high, the use of high-efficiency power electronic

converters is a must. Due to the importance of the conventional boost converter in obtaining

distinct and improved topologies for voltage step-up applications, some techniques have been

developed and modified with the aim of improving the characteristics of the original structure.

Basically, two strategies are adopted for this purpose: voltage step-up with and without using

extreme values of duty cycle.

Cascading one or more boost converters may be considered to obtain high voltage gain.

Even though more than one power processing stage exists, the operation in continuous

conduction mode (CCM) may still lead to high efficiency. The main drawbacks in this case are

increased complexity and the need for two sets that include active switches, magnetics, and

controllers. Besides, the controllers must be synchronized and stability is of great concern. Due

to high power levels and high output voltage, the latter cascaded boost stage has severe reverse

losses, with consequent low efficiency and high electromagnetic interference (EMI) levels.

A hybrid boostfly back converter is introduced in the past. The efficiency of the

conventional fly back structure is typically low due to the parasitic inductance. A possible

solution lies in connecting the output of the boost converter to that of the fly back topology, with

consequent increase of voltage gain due to the existent coupling between the arrangements. In

this case, the boost convert behaves as an active clamping circuit when the main switch of the fly

back stage is turned OFF. a topology for voltage step-up applications based on the use of

multiplier cells constituted by diodes and capacitors. The converter is able to operate in

overlapping mode (when a duty cycleD is higher than 0.5) and non over lapping mode (when a

duty cycleD is lower than 0.5), analogously to other 3SSC-based structures. However, the studycarried out in this paper only considers the operation withD > 0.5.

1.2 SCOPE OF THE PROJECT

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A new family of dcdc converters based on the three-state switching cell and voltage

multiplier cells. A brief literature review is presented to demonstrate some advantages and

inherent limitations of several topologies that are typically used in voltage step-up applications.

In order to verify the operation principle of this family, the boost converter is chosen and

investigated in detail. The behavior of the converter is analyzed through an extensive theoretical

analysis, while its performance is investigated by experimental results obtained from a 1-kW

laboratory prototype and relevant issues are discussed. The analyzed converter can be applied in

uninterruptible power supplies, fuel cell systems, and is also adequate to operate as a high-gain

boost stage with cascaded inverters in renewable energy systems.

1.3 EXISTING SYSTEM

Cascading one or more boost converters may be considered to obtain high voltage gain.

Even though more than one power processing stage exists, the operation in continuous

conduction mode (CCM) may still lead to high efficiency. The main drawbacks in this case are

increased complexity and the need for two sets that include active switches, magnetics, and

controllers. Besides, the controllers must be synchronized and stability is of great concern. Due

to high power levels and high output voltage, the latter cascaded boost stage has severe reverse

losses, with consequent low efficiency and high electromagnetic interference (EMI) levels.

Typical examples of such topologies are the single-switch quadratic boost converter and the two-switch three-level boost converter.

1.4 EXISTING SYSTEM ALGORITHM/TECHNIQUE

Converters with magnetically coupled inductance such as flyback or the single-ended

primary inductance converter (SEPIC) can easily achieve high voltage gain using switches with

reduced on-resistance, even though efficiency is compromised by the losses due to the leakage

inductance. An active clamping circuit is able to regenerate the leakage energy, at the cost of

increased complexity and some loss in the auxiliary circuit.

1.5 LITERATURE SURVEY

Title: An improved maximum power point tracking for photovoltaic grid-connected

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inverter based on voltage-oriented control.

Author: R. Kadri, J.-P. Gaubert, and G. Champenois,

Publish: IEEE, vol. 58, no. 1, pp. 6675, Jan. 2011.

An improved maximum power point (MPP) tracking (MPPT) with better performance

based on voltage-oriented control (VOC) is proposed to solve a fast changing irradiation

problem. In VOC, a cascaded control structure with an outer dc link voltage control loop and an

inner current control loop is used. The currents are controlled in a synchronous orthogonal d, q

frame using a decoupled feedback control.

INTRODUCTION

In order to generate the correct MPP reference voltage under rapidly changing irradiation,

a robust MPPT controller has been proposed. In this algorithm, the d-axis grid current

component reflecting the power grid side and the signal error of a proportionalintegral (PI)

outer voltage regulator is designed to reflect the change in power caused by the irradiation

variation. Hence, with this information, the proposed algorithm can greatly reduce the power

losses caused by the dynamic tracking errors under rapid weather changing conditions. The

superiority of the newly proposed method is supported by simulation and experimental results.

CONCLUSION

In order to avoid possible mistakes of the classical P&O algorithm due to the fast-

changing irradiation, this paper has proposed an improved MPPT controller without PV array

power measurement. Our control scheme uses the d-axis grid current component and the signal

error of the PI outer voltage regulator. This MPPT method permits one to differentiate the

contribution of increment perturbation and irradiation change in power variation, hence

identifying the correct direction of the MPP. In the simulation and experimental results, the

robust tracking capability under rapidly increasing and decreasing irradiance has been proved.The steady-state and dynamic responses illustrated the perfect desired reference tracking

controller. Moreover, the output power losses caused by the dynamic tracking errors are

significantly reduced, particularly under fast changing irradiation. Furthermore, one can see that

the control algorithm is simple and easy to implement in real time.

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Title: Class-D audio amplifiers in mobile applications.

Author: M. Berkhout and L. Dooper,

Publish: IEEE, vol. 57, no. 5, pp. 9921002, May 2010.

A comparative system-level overview is given of alternative class-D amplifier

architectures. The theory behind pulse width modulation and different modulation schemes is

discussed. Topological alternatives such as open-loop versus feedback and fixed-carrier versus

self-oscillating are analyzed and compared in terms of relevant characteristics, such as distortion,

power supply rejection, efficiency, and electromagnetic interference. The combination of digital-

to-analog conversion and class-D amplifiers is discussed.

INTRODUCTION

The outline of this paper is given as follows: In Section II, the basics of class-D

amplifiers are presented. In Section III, a comparative overview of different class-D amplifier

architectures is given. In Section IV, the combination of analog feedback with digital input that

revolves around the question of where to do the digital-to-analog (D/A) conversion is discussed.

Finally, in Section V, experimental results of an integrated circuit that is based on a simple

architecture that combines the benefits of digital input with an analog feedback loop are

presented.

CONCLUSION

Class-D amplifiers for mobile applications need high power supply rejection and require

digital input capability. The most attractive architecture for this combination of requirements is a

digital PWM modulator, followed by a one-bit D/A conversion and a direct PWM feedback loop

in BD-modulated BTL configuration. Measurements on a prototype IC demonstrate the

feasibility of this architecture.

Title: Highly efficient high step-up converter for fuel-cell power processing based on three-

state commutation cell.

Author: S. V. Araujo, R. P. Torrico-Bascope, and G. V. Torrico-Bascope,

Publish: IEEE, vol. 57, no. 6, pp. 19871997, Jun. 2010.

The modification of a boost converter operating with a three-state commutation cell

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that is already well suited for high current stress in the input due to the current sharing between

the active switches.

INTRODUCTION

A cross current sensorless control allows the parallelism of multiple UPSs withoutcompromising the power quality required to supply the utmost critical system. Thus, by realizing

high reliability and high efficiency at the same time, the proposed UPS is hoped to effectively

contribute to greening information technology facilities. To discuss the main features of the

proposed UPS system, this paper is organized as follows. Section II shows the advantages of the

multilevel concept for UPS systems. Section III introduces a custom insulated-gate bipolar

transistor (IGBT) module that further boosts the benefits of the multilevel topology. Section IV

devotes to the control circuit of the proposed UPS. Section V introduces the cross current

sensorless control for parallel operation. Section VI presents some test resultsto demonstrate the

performance of the proposed UPS as a single-module system as well as a multiple-module

system. Section VII concludes this paper.

CONCLUSION

This paper has proposed a UPS using a multilevel circuit topology, resulting in higher

efficiency and significant size/weight reduction. A cross current sensorless control enables

parallel operation of multiple modules and, hence, a redundant uninterruptible power system

configuration. Test results confirm the high efficiency and the high power quality of the

proposed UPS, the high performance of the digital controller, the reliability and the redundancy

to meet the requirements of the utmost critical system.

1.5.4 Title: Impedance specifications for stable dc distributed power systems.

Author: X. G. Feng, J. J. Liu, and F. C. Lee,

Publish: vol. 17, no. 2, pp. 157162, Mar. 2002.

A new forbidden region for impedance ratio on the -plane is proposed as the system

stability margin requirement. Based on this proposed forbidden region, the impedance

specifications of individual loads are established.

INTRODUCTION

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This paper will first classify the possible groups of circuits capable of providing such

voltage gain, giving an overview of their characteristics. Afterward, a circuit based on a boost

converter with a three-state commutation cell having an additional winding for operation at high

gain will be presented. Focus will be given here for a more detailed explanation about the

principle of operation and theoretical analysis. New experimental results of an optimized design

will be presented, demonstrating the effectiveness of the circuit.

CONCLUSION

This paper has proposed a topology based on a boost converter with a three-state

commutation cell that achieves high voltage gain through an additional winding on the original

autotransformer. Due to the capability of voltage gains superior to ten, the circuit is well suited

for fuel-cell applications with low input voltage that require high output levels like 400 V, which

is necessary to feed a single-phase full-bridge inverter to generate a 230-V rms voltage. Other

features seen in the experimental results are the lower blocking voltages across the controlled

switches compared to similar circuits, which allow the use of MOSFETs with lowerRDS_on

values. In addition, since the input current is divided between the switches, conduction losses can

further be reduced.

1.6 PROPOSED SYSTEM

This paper presents a topology for voltage step-up applications based on the use of

multiplier cells constituted by diodes and capacitors. The converter is able to operate in

overlapping mode (when a duty cycle D is higher than 0.5) and non-overlapping mode (when a

duty cycleD is lower than 0.5), analogously to other 3SSC-based structures. However, the study

carried out in this paper only considers the operation withD>0.5. The generic structure, which is

valid for any number of cells, is initially presented, while the analysis is focused on structures

with three cells, aiming to determine the stress regarding the elements that constitute the

aforementioned configurations.

1.7 PROPOSED SYSTEM ALGORITHM/TECHNIQUE

For good operation of the VMC, ac input voltage is required, which is an important

requirement of this cell. Due to this fact, the use of the 3SSC depicted in is considered because it

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generates such ac voltage across the terminals of the autotransformer and the drain terminals of

the controlled switches. By using the proposed cell, it is possible to generate the six novel non-

isolated dcdc converters, i.e., buck, boost, buckboost, Cuk, SEPIC, and zeta

CHAPTER 2

PROJECT DESCRIPTION

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2.1 GENERAL

A boost converter using switched capacitors is proposed in, where high voltage gain can

be obtained, but it is restricted to low-power applications. In this case, the dc output voltage can

be increased as desired by adding a given number of capacitors. Low duty cycle is used,

alleviating the problem of the boost diode reverse recovery. However, the high component count

with distinct ratings is an inherent drawback.

2.2 MODULES NAME

Module 1 OPERATING PRINCIPLE

Module 2 STATIC GAIN

Module 3 DESIGN PROCEDURE

Module 4 PRELIMINARY CALCULATION

Module 5 SIMULATION RESULTS

2.3 MODULE DESCRIPTION

For good operation of the VMC ac input voltage is required, which is an

important requirement of this cell. Due to this fact, the use of the 3SSCdepicted is considered because it generates such ac voltage across theterminals of the autotransformer and the drain terminals of the controlledswitches. In the resulting cell, the controlled switches can be represented byMOSFETs, junction field-effect transistors, insulated gate bipolar transistors,bipolar junction transistors, etc. All the generated topologies presentbidirectional characteristics. the use of the voltage multipliertechnique applied to the classical non-isolated dcdc converters inorder to obtain high step-up static gain, reduction of the maximumswitch voltage, zero current switching turn-on. The diodes reverserecovery current problem is minimized and the voltage multiplieralso operates as a regenerative clamping circuit, reducing the

problems with layout and the EMI generation. These characteristicsallows the operation with high static again and high efficiency,making possible to design a compact circuit for applications wherethe isolation is not required. The operation principle, the designprocedure and practical results obtained from the implementedprototypes are presented for the single-phase and multiphasedcdc converters.

As was mentioned before, the use of high-voltage gain converters is of

great interest, even though many approaches are based on isolated

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topologies. It is worth to notice that the use of non isolated converters

particularly dedicated to applications regarding renewable power systems

has been the scope of recent works. The efforts leading to the development

of such non isolated topologies are then well justified in the literature.

Fig.2.1. (a) Voltage multiplier cell. (b) Three-state switching cell. (c)

Resulting cell.

Module 1 OPERATING PRINCIPLE

OPERATION MODES

Mode 1 explained in Fig.2.2. Switches S1 and S2 are turned ON, while all diodes are

reverse biased. Energy is stored in inductorL and there is no energy transfer to the load. The

output capacitor provides energy to the load. This stage finishes when switch S1 is turned OFF.

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Fig.2.2. Mode 1

Second stage in Fig.2.3, switch S1 is turned OFF, while S2 is still turned ON and

diodeD5 is forward biased. There is no energy transfer to the load as well. Inductor L stores

energy, capacitors C1 and C3 are discharged, and capacitors C2, C4, and C6 are charged.

Fig.2.3. Mode 2

Third stage in Fig.2.4, switches S1 and S2 remain turned OFF and ON, respectively.

Diodes D3 and D7 are forward biased, while all the remaining ones are reverse biased. Energy is

transferred to the output stage through D7. The inductor stores energy, and capacitors C2 and C4

are still charged. Capacitors C1 is discharged, and so are C3 and C5.

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Fig.2.4. Mode 3

Fourth stage in Fig.2.5 explains the switch S2 remains turned ON, diode D3 is reverse

biased, and diode D1 is forward biased. Energy is transferred to the load through D7. The

inductor is discharged, and so are capacitors C1, C3, and C5, while C2 is charged.

Fig.2.5. Mode 4

Fifth stage [t4, t5] [see Fig. 4(e)]: This stage is identical to the first one.

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Fig.2.6. Mode 5

Sixth stage [t5, t6 ] [see Fig. 4(f)]: Switch S2 is turned OFF and switch S1 is still turned ON.

DiodeD6 is forward biased. The inductor is charged by the input source, although capacitors

C2 and C4 are discharged instead.

Seventh stage [t6, t7] [see Fig. 4(g)]: This stage is similar to the third one.

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Eighth stage [t7, t8] [see Fig. 4(h)]: Switch S1 is turned ON, while S2 remains turned OFF.

Diodes D2 and D8 are forward biased, while D4 is reverse biased as well as the remaining

diodes. Energy transfer to the load occurs through D8, and capacitor Co is still charged. The

inductor is discharged, while capacitor C1 is charged and capacitors C2, C4, and C6 are

discharged.

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B. Static Gain

The static gain for the generic structure of the boost converter can be obtained from the

inductor voltsecond balance. The voltage area multiplied by the time interval that corresponds

to the inductor charge is equal to that regarding the inductor discharged.

Modules 2: DESIGN PROCEDURE

The static gain of the proposed non-isolated boost converter can be further increased by

adding VMCs as necessary, with consequent reduction of voltage stress across the main

switches. However, this practice may lead to high component count and also compromise

robustness considering that additional diodes and multiplier capacitors are included in the

original topology.

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Even though a simpler arrangement with two VMCs could be considered instead, a

design example of the proposed 3SSC boost converter with three cells is presented as follows. It

will be also shown that the converter achieves high efficiency over a wide load range.

A. PRELIMINARY CALCULATION

The maximum input power is

The maximum duty cycle is obtained using (3) as follows

B. INDUCTOR

Besides, the normalized ripple currentas a function of the duty cycle is given by

where it can be seen that for curve mc=3 and duty cycleD=0.75 the maximum normalized

ripple current is= 0.03125. The respective inductance is calculated.

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CHAPTER 3

3.1 SOFTWARE REQUIREMENTS

MATLAB 7.14

MATLAB (MATrix LABoratory) is a fourth level programming language. Simulink is an

environment for multi domain simulation and Model-Based Design for dynamic and embedded

systems. It provides an interactive graphical environment and a customizable set of block

libraries that let you design, simulate, implement, and test a variety of time-varying systems,

including communications, controls, signal processing, video processing, and image processing.

3.2 Introduction to Simulink

Simulink is a software package for modeling, simulating, and analyzing dynamical

systems. It supports linear and nonlinear systems, modeled in continuous time, sampled time, or

a hybrid of the two. Systems can also be multirate, i.e., have different parts that are sampled or

updated at different rates. For modeling, Simulink provides a graphical user interface (GUI) for

building models as block diagrams, using click-and-drag mouse operations. With this interface,

you can draw the models just as you would with pencil and paper (or as most textbooks depict

Them).Simulink includes a comprehensive block library of sinks, sources, linear and nonlinear

components, and connectors. You can also customize and create your own blocks Models are

hierarchical. This approach provides insight into how a model is organized and how its parts

interact. After you define a model, you can simulate it, using a choice of integration methods,

either from the Simulink menus or by entering commands in MATLAB's command window. The

menus are particularly convenient for interactive work, while the command-line approach is very

useful for running a batch of simulations (for example, if you are doing Monte Carlo simulations

or want to sweep a parameter across a range of values). Using scopes and other display blocks,

you can see the simulation results while the simulation is running. In addition, you can change

parameters and immediately see what happens, for "what if" exploration. The simulation results

can be put in the MATLAB workspace for post processing and visualization. And because

MATLAB and Simulink are integrated, you can simulate, analyze, and revise your models in

either environment at any point.

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3.3 Building a Simple Model

This example shows you how to build a model using many of the model building

commands and actions you will use to build your own models. The instructions for building this

model in this section are brief. The model integrates a sine wave and displays the result, along

with the sine wave. The block diagram of the model looks like this.

To create the model, first type simulink in the MATLAB command window. On Microsoft

Windows, the Simulink Library Browser appears.

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On UNIX, the Simulink library window appears.

To create a new model, select Model from the New submenu of the Simulink library window's

File menu. To create a new model on Windows, select the New Model button on the Library

Browser's toolbar.

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Simulink opens a new model window

To create this model, you will need to copy blocks into the model from the following

Simulink block libraries:

Sources library (the Sine Wave block)

Sinks library (the Scope block)

Continuous library (the Integrator block)

Signals & Systems library (the Mux block)

To copy the Sine Wave block from the Library Browser, first expand the Library

Browser tree to display the blocks in the Sources library. Do this by clicking on the Sources node

to display the Sources library blocks. Finally, click on the Sine Wave node to select the Sine

Wave block. Here is how the Library Browser should look after you have done this.

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Now drag the Sine Wave block from the browser and drop it in the model window.

Simulink creates a copy of the Sine Wave block at the point where you dropped the node icon.

To copy the Sine Wave block from the Sources library window, open the Sources

window by double-clicking on the Sources icon in the Simulink library window. (On Windows,

you can open the Simulink library window by right-clicking the Simulink node in the Library

Browser and then clicking the resulting Open Library button.)

Simulink displays the Sources library window.

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Now drag the Sine Wave block from the Sources window to your model window.

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Copy the rest of the blocks in a similar manner from their respective libraries into the

model window. You can move a block from one place in the model window to another by

dragging the block. You can move a block a short distance by selecting the block, then pressing

the arrow keys.

With all the blocks copied into the model window, the model should look something like this.

If you examine the block icons, you see an angle bracket on the right of the Sine

Waveblock and two on the left of the Mux block. The > symbol pointing out of a block is an

output port; if the symbol points to a block, it is an input port. A signal travels out of an output

port and into an input port of another block through a connecting line. When the blocks are

connected, the port symbols disappear.

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Now it's time to connect the blocks. Connect the Sine Wave block to the top input port of

the Mux block. Position the pointer over the output port on the right side of the Sine Wave block.

Notice that the cursor shape changes to cross hairs.

Hold down the mouse button and move the cursor to the top input port of the Mux block.

Notice that the line is dashed while the mouse button is down and that the cursor shape changes

to double-lined cross hairs as it approaches the Mux block.

Now release the mouse button. The blocks are connected. You can also connect the line

to the block by releasing the mouse button while the pointer is inside the icon. If you do, the line

is connected to the input port closest to the cursor's position.

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If you look again at the model at the beginning of this section, you'll notice that most of the

lines connect output ports of blocks to input ports of other blocks. However, one line connects a

line to the input port of another block. This line, called a branch line, connects the Sine Wave

output to the Integrator block, and carries the same signal that passes from the Sine Wave block

to the Mux block. Drawing a branch line is slightly different from drawing the line you just

drew. To weld a connection to an existing line, follow these steps:

1. First, position the pointer on the line between the Sine Wave and the Mux block.

Press and hold down the Ctrl key (or click the right mouse button). Press the mouse button, then

drag the pointer to the Integrator blocks input port or over the Integrator blocks itself.

Release the mouse button. Simulink draws a line between the starting point and the Integrator

block's input port.

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Finish making block connections. When you're done, your model should look something

like this.

Now, open the Scope block to view the simulation output. Keeping the Scope window open, set

up Simulink to run the simulation for 10 seconds. First, set the simulation parameters by

choosing Simulation Parameters from the Simulation menu.On the dialog box that appears,

notice that the Stop time is set to 10.0 (its default value).

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Close the Simulation Parameters dialog box by clicking on the OK button. Simulink applies the

parameters and closes the dialog box. Choose Start from the Simulation menu and watch the

Traces of the Scope block's input.

The simulation stops when it reaches the stop time specified in the Simulation Parameters dialog

box or when you choose Stop from the Simulation menu. To save this model, choose Save from

the File menu and enter a filename and location. That file contains the description of the model.

Running a Simulation

After building your model in Simulink, you can simulate its dynamic behavior and view the

results live. Simulink software provides several features and tools to ensure the speed and accuracy of

your simulation, including fixed-step and variable-step solvers, a graphical debugger, and a model

profiler.

Using Solvers

Solvers are numerical integration algorithms that compute the system dynamics over time usinginformation contained in the model. Simulink provides solvers to support the simulation of a broad range

of systems, including continuous-time (analog), discrete-time (digital), hybrid (mixed-signal), and

multirate systems of any size.

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These solvers can simulate stiff systems and systems with state events, such as discontinuities,

including instantaneous changes in system dynamics. You can specify simulation options, including the

type and properties of the solver, simulation start and stop times, and whether to load or save simulation

data. You can also set optimization and diagnostic information for your simulation. Different

combinations of options can be saved with the model.

Debugging a Simulation

The Simulink debugger is an interactive tool for examining simulation results and locating and

diagnosing unexpected behavior in a Simulink model. It lets you quickly pinpoint problems in your model

by stepping through a simulation one method at a time and examining the results of executing that

method. (Methods are functions that Simulink uses to solve a model at each time step during the

simulation. Blocks are made up of multiple methods.)

The Simulink debugger lets you set breakpoints, control the simulation execution, and display

model information. It can be run from a graphical user interface (GUI) or from the MATLAB command

line. The GUI provides a clear, color-coded view of the model's execution status. As the model simulates,

you can display information on block states, block inputs and outputs, and other information, as well as

animate block method execution directly on the model.

Simulink debugger GUI used with a multirate control system. You can step through the

simulation one method at a time or run to breakpoints.

http://www.mathworks.in/cmsimages/40503_wl_sl_fig7_wl_15369.gif

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Executing a Simulation

Once you have set the simulation options for your model, you can run your simulation

interactively, by using the Simulink GUI, or systematically, by running it in batch mode from the

MATLAB command line. The following simulation modes can be used:

Normal (the default), which interpretively simulates your model Accelerator, which speeds model

execution by creating compiled target code while still letting you to change model parameters Rapid

Accelerator, which can simulate models faster than Accelerator mode but with less interactivity by

creating an executable separate from Simulink that can run on a second processing core You can also use

MATLAB commands to load and process model data and parameters and visualize results.

Profiling a Simulation

Model profiling can help you identify performance bottlenecks in your simulations. You can

collect performance data while simulating your model and then generate a simulation profile report based

on the collected data that shows how much time Simulink takes to execute each simulation method

3.4 Introduction to Matlab

3.5 What is Matlab?

Matlab is a high-performance language for technical computing. It integrates computation,programming and visualization in a user-friendly environment where problems and solutions are

expressed in an easy-to-understand mathematical notation.

Matlab is an interactive system whose basic data element is an array that does not require

dimensioning. This allows the user to solve many technical computing problems, especially

those with matrix and vector operations, in less time than it would take to write a program in a

scalar non-interactive language such as C or FORTRAN.

Matlab features a family of application-specific solutions which are called toolboxes. It is very

important to most users of Matlab that toolboxes allow to learn and apply specialized

technology. These toolboxes are comprehensive collections of Matlab functions, so-called M-

files that extend the Matlab environment to solve particular classes of problems.

Matlab is a matrix-based programming tool. Although matrices often need not to be dimensioned

explicitly, the user has always to look carefully for matrix dimensions. If it is not defined

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otherwise, the standard matrix exhibits two dimensions n m. Column vectors and row vectors

are represented consistently by n 1 and 1 n matrices, respectively.

Matlab operations can be classified into the following types of operations:

arithmetic and logical operations,

mathematical functions,

graphical functions, and

input/output operations.

In the following sections, individual elements of Matlab operations are explained in detail.

3.6 Expressions

Like most other programming languages, Matlab provides mathematical expressions, but unlike

most programming languages, these expressions involve entire matrices. The building blocks of

expressions are

Variables

Numbers

Operators

Functions

3.7 Variables

Matlab does not require any type declarations or dimension statements. When a new

variable name is introduced, it automatically creates the variable and allocates the appropriate

amount of memory. If the variable already exists, Matlab changes its contents and, if necessary,

allocates new storage. For example

>> books = 10

creates a 1-by-1 matrix named books and stores the value 10 in its single element. In theexpression above, >> constitutes the Matlab prompt, where the commands can be entered.

Variable names consist of a string, which start with a letter, followed by any number of letters,

digits, or underscores. Matlab is case sensitive; it distinguishes between uppercase and lowercase

letters. A and a are not the same variable. To view the matrix assigned to any variable, simply

enter the variable name.

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Numbers

Matlab uses the conventional decimal notation. A decimal point and a leading plus or

minus sign is optional. Scientific notation uses the letter e to specify a power-of-ten scale factor.

Imaginary numbers use either i or j as a suffix. Some examples of legal numbers are:

7 -55 0.0041 9.657838 6.10220e-10 7.03352e21 2i -2.71828j 2e3i 2.5+1.7j.

Operators

Expressions use familiar arithmetic operators and precedence rules. Some examples are:

+ Addition

- Subtraction

* Multiplication

/ Division

Complex conjugate transpose

( ) Brackets to specify the evaluation order.

Functions

Matlab provides a large number of standard elementary mathematical functions,

including sin, sqrt, exp, and abs. Taking the square root or logarithm of a negative number does

not lead to an error; the appropriate complex result is produced automatically. Matlab also

provides a lot of advanced mathematical functions, including Bessel and Gamma functions. Most

of these functions accept complex arguments. For a list of the elementary mathematical

functions, type

>> help elfun

Some of the functions, like sqrt and sin are built-in. They are a fixed part of the Matlab core so

they are very efficient. The drawback is that the computational details are not readily accessible.

Other functions, like gamma and sinh, are implemented in so called M-files. You can see thecode and even modify it if you want.

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Graphics

Matlab offers extensive facilities for displaying vectors and matrices as graphs, as well as

annotating and printing these graphs. This section describes some of the most important graphics

functions and gives some examples of some typical applications.

Creating a Plot

The plot function has different forms, depending on the input arguments. If y is a vector, plot(y)

produces a piecewise linear graph of the elements of y versus the index of the elements of y. If

two vectors are specified as arguments, plot(x,y) produces a graph of y versus x. For example to

plot the value of the sine function from zero to 2, use

>> x = 0:pi/100:2*pi;

>> y = sin(x);

>> plot(x,y)

0 1 2 3 4 5 6 7-1

-0.5

0

0.5

1

x

y

y = sin(x)

Figure.1.1 Sine Plot

The xlabel, ylabel and zlabel functions are useful to add x-, y- and z-axis labels. The zlabel

function is only necessary for three-dimensional plots. The title function adds a title to a graph at

the top of the figure and the text function inserts a text in a figure.

The following commands create the final appearance of figure 1.1.

>> xlabel(x);

>> ylabel(y);

>> title(y = sin(x))

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Multiple x-y pairs create multiple graphs with a single call to plot. Matlab automatically cycles

through a predefined (but user settable) list of colors to distinguish between different graphs.

For example, these statements plot three related functions of x1, each curve in a separate

distinguishing color:

>> x1 = 0:pi/100:2*pi;

>> y1 = sin(x1);

>> y2 = sin(x1 - 0.25);

>> y3 = sin(x2 - 0.5);

>> plot(x1,y1,x1,y2,x1,y3)

The number of points of the individual graphs may be even different. It is possible to specify the

color, the line style and the markers, such as plus signs or circles, with: plot(x,y,color style

marker)

0 1 2 3 4 5 6 7-1

-0.5

0

0.5

1

x

y

y = s in(x)

Figure.1.2 Multiple graphs with a single call to plot

A color style marker is a 1-, 2-, or 3-character string. It may consist of a color type, a line style

type, and a marker type:

Color strings are c, m, y, r, g, b, w and k. These correspond to cyan, magenta,

yellow, red, green, blue, white, and black.

Line style strings are - for solid, -- for dashed, : for dotted, -. for dash-dotted and none

for no line.

The most common marker types include +, o, * and x.

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For example, the statement plot(x1,y1,b:*) plots a blue dotted line and places asterisk sign

markers at each data point. If only a marker type is specified but not a line style, Matlab draws

only the marker.

The plot function automatically opens a figure window to plot the graphic. If there is already an

existing figure window, these windows will be used for the new plot. The command figure can

be used to keep an existing figure window and open a new one, which will be used for the next

plot. To make an existing window the current window, type figure(n) where n is the number in

the title bar of the window to be selected. The next graphic will be plotted in this selected

window.

To add further plots to an existing graph, the hold command is useful. The hold on command

keeps the content of the figure and plots can be added. So the above example could be done with

three single plot commands and the hold on command. hold off ends the hold on status of a

figure window. hold can be used to toggle between on and off.

Controlling Axes

Usually, Matlab finds the maxima and minima of the data to be plotted by it and uses them to

create an appropriate plot box and axes labeling. The axis function overwrites this default by

setting custom axis limits,

>> axis([xmin xmax ymin ymax]).The following example illustrates the use of the functions presented above.

>> t = -pi:pi/100:pi;

>> s = cos(t);

>> plot(t,s)

>> axis([-pi pi -1 1])

>> xlabel(-\pi \leq t \leq \pi)

>> ylabel(cos(t))

>> title(The cosine function)

>> text(-2, -0.5,This is a note at position (-2, -0.5))

\leq is used to generate the less-equal sign.

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-3 -2 -1 0 1 2 3-1

-0.5

0

0.5

1

- t

cos(t)

The cosine function

This is a note at position (-2, -0.5)

Figure.1.3 Example for controlling the axes

To take a closer look at an interesting part of a plot, the zoom command can be used. Afterwards

it is possible to zoom by marking this part with the mouse. The grid command is used to turn a

grid on and off.

3.8 Working with Matlab

For simple problems, entering requests at theMatlab prompt in the command window is fast andefficient. However, as the number of commands increases, or whenever a change of value of one

or more variables with a reevaluation is desired, typing at the Matlab prompt becomes tedious.

Matlab allows to place Matlab commands in a simple text file, and by telling Matlab to open this

file, the stored commands are evaluated one-by- one as if they were just typed in. Those files are

called M-files. There are two kinds of M-files:

Scripts, which do not accept input arguments or return output arguments.

Functions, which can accept input arguments and return output arguments. Internal

variables are local to the function. The only difference in the syntax of a Script-file and a

Function-file is the first line. The first line in a Function-file starts with the keyword

function followed by the list of output arguments, an equals sign, the name of the

function and ending with the list of input variables enclosed in parentheses and separated

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by commas. If the function has multiple output arguments, the output argument list must

be enclosed in square brackets, e.g.:

function [x,y,z] = cosytrans(theta, phi, rho)

In a Script-file there is no predefined syntax for the first line.

To create or edit an M-file in the environment of Linux the command nedit can be used to start a

text editor. The command nedit must be typed at a Linux command window. The use of this

editor is very simple and the most important commands can be found in top-down-menus.

Another important aspect concerning the work with Matlab should be mentioned here. The

commands presented in this paper were introduced without a concluding semicolon. Therefore, a

response to the commands occurs at the command prompt. So entering a new variable causes a

repetition of the variable name and its values. Sometimes it is much better to avoid this repetition

especially in large M-files since a load of information would appear on the screen and the really

interesting data might get lost within this load. To suppress this response a concluding semicolon

must be entered after the command, e.g.:

>> a = 0:5

leads to the response

a = 0 1 2 3 4 5

while

>> a = 0:5;

generates the same array, but does not display it.

Whenever there is a question about Matlab, the best way to solve it, is to use the Matlab help

command which is a powerful tool searching within a huge data base. Just type help at the

command prompt. A list of the main topics will be listed. By typing help topic the help can be

specified. Additionally the cross-references help to find the interesting command with its

options.

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CHAPTER 4 : SIMULATION RESULTS

4.1 OPEN LOOP CIRCUIT

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OPEN LOOP OUTPUT

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CLOSE LOOP

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CLOSE LOOP OUTPUT

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ADVANTAGES OF PROPOSED SYSTEM

Reduced No of switches

Increased efficiency

Control Logic Reduces

Reduced losses

CONCLUSION

Six generalized non isolated high gain voltage dcdc converters. To verify the principle

operation of the generated structures, the boost converter was chosen. The topology is adequate

for several applications such as photovoltaic systems, fuel cell systems, and UPSs, where high

voltage gain between the input and output voltages are demanded.

REFERENCES

[1] R. Kadri, J.-P. Gaubert, and G. Champenois, An improved maximum power point tracking

for photovoltaic grid-connected inverter based on voltage-oriented control, IEEE Trans. Ind.

Electron., vol. 58, no. 1, pp. 6675, Jan. 2011.

[2] M. Berkhout and L. Dooper, Class-D audio amplifiers in mobile applications, IEEE Trans.

Circuits Syst. I, Reg. Papers, vol. 57, no. 5, pp. 9921002, May 2010.

[3] S. V. Araujo, R. P. Torrico-Bascope, and G. V. Torrico-Bascope, Highly efficient high step-up converter for fuel-cell power processing based on three-state commutation cell,IEEE Trans.

Ind. Electron., vol. 57, no. 6, pp. 19871997, Jun. 2010.

[4] X. G. Feng, J. J. Liu, and F. C. Lee, Impedance specifications for stable dc distributed power

systems,IEEE Trans. Power Electron., vol. 17, no. 2, pp. 157162, Mar. 2002.

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[5] Y. Jang and M. M. Jovanovic, Interleaved boost converter with intrinsic voltage-doubler

characteristic for universal-line PFC front end, IEEE Trans. Power Electron., vol. 22, no. 4, pp.

13941401, Jul. 2007.