ABSTRACT
Generally, rotating electrical machines converts electrical energy to mechanical energy or vice versa. This is made possible by the interaction of electrical circuits and magnetic fields across an air gap; the usefulness of the motor has resulted in a lot of research. This project presents the development of a simulink model of asynchronous motor with pump load. The model is to investigate the effect of the parameter values on the dynamic performance of a 7.5kw induction motor. The simulation is obtained from non-linear differential equations. It is verified that accurate simulations of the machine under steady and transient states are possible. It concludes that, comparison on load, no load and pump load of an Asynchronous motor using simulink can be achieved.
TABLE OF CONTENTS
Title page i
Declaration ii
Certification iii
Dedication iv
Acknowledgments v
Table of contents vi
List of tables viii
List of figure ix
Abstract xi
CHAPTER 1: INTRODUCTION
1.1 Background of the Study 1
1.2 Statement of Problems 8
1.3 Aim and Objectives 9
1.4 Project Outline 9
CHAPTER 2: LITERATURE REVIEW
2.1 Introduction 10
CHAPTER 3: MATERIALS AND METHOD
3.1 Materials 14
3.2 Method 14
3.3 Machine parameters 17
3.4 Simulink Model 18
CHAPTER 4: SIMULATION AND DISCUSSION OF RESULTS
4.1 Simulation 22
4.2 Discussion of results 45
CHAPTER 5: CONCLUSION AND RECOMMENDATIONS
5.1 Conclusion 47
5.2 Recommendations 49
REFERENCES
LIST OF TABLES
3.1 Machine Parameters 17
LIST OF FIGURES
3.1 Squirrel- cage induction motor model in d-q axis 14
3.2 3-phase induction Motor MATLAB/SIMULINK Model 18
3.3 Internal structure of the 3-phase induction motor d-q model 19
3.4 Internal structure of the flux linkages 19
3.5 Internal structure of the model for flux linkage calculations 20
3.6 Internal structure of the torque and angular speed equations 20
3.7 Internal structure of the current transformations 21
4.1 A graph of electromagnetic torque against time at no load 22
4.2 A graph of Rotor speed against time at no load 23
4.3 A graph of ias against time at no load 24
4.4 A graph of ibs against time at no load 25
4.6 A graph of Torque against speed at no load 26
4.7 A graph of electronmagnetic torque against time at constant load 28
4.8 A graph of rotor speed against time at constant load 29
4.9 A graph of ias against time at constant load 30
4.10 A graph of ibs against time at constant load 31
4.11 A graph of ics against time at constant load 32
4.12 A graph of torque against speed at constant load 33
4.13 A graph of electromagnetic torque against time at pump load 34
4.14 A graph of rotor speed against time at pump load 35
4.15 A graph of ias against time at pump load 36
4.16 A graph of ibs against time at pump load 37
4.17 A graph of ics against time at pump load 38
4.18 A graph of torque against speed at pump load 39
4.19 A graph of electromagnetic torque against time when compared 40
4.20 A graph of rotor speed against time when compared 41
4.21 A graph of ias against time when compared 42
4.22 A graph of ibs against time when compared 43
4.23 A graph of ics against time when compared 44
4.24 A graph of Torque against speed when compared 45
CHAPTER 1
INTRODUCTION
1.1 BACKGROUND STUDY
An induction motor is one of the most often used electric machines in high performance drive applications. Squirrel cage induction motor is popularly known as the work-horse of the modern industry. It is due to its simplicity in design, robust construction, reliability, tremendous self-starting capability and high-efficiency.
Induction motors are highly nonlinear and electric rotor variables are not measurable. The skin effect in the rotor winding and iron core saturation lead to even bigger complications in the modeling process of the machine (Megherbi et al, 2010).
Traditionally dynamic parameters are estimated by performing no-load test and locked-rotor test. Due to the complication of dynamic behaviors of induction motors, inaccuracy of transient characteristics may obtain while using these dynamic parameters (Boonaruang et al, 2006). These tests are not convenient because they require human electrical measurements and intervention on the machine. The locked rotor test results in very high slip frequency, and increasing skin effect influence on the rotor resistance. This leads to incorrect operating conditions and inaccurate parameter estimation.
Dynamic modelling and simulation of induction motor drives is of great importance to both industry and academia due to the prevalence of these types of drives in various industrial settings as well as in the validation of design process of the motor-drive systems, eliminating inadvertent design mistakes and the resulting errors in the prototype constructions and testing
(Krause et al, 2002, Stanley, 1938). The dynamic model of the induction motor is derived by transferring the three-phase quantities into two phase direct and quadrature axes quantities. This project presents a modular, easy-to-understand Simulink induction motor model (de Aguiar, 2000, Wade et al, 1997). With the modular system (Burak and Leon, 2003), each block solves one of the model equations; therefore, unlike in black box models, all of the machine parameters are accessible for control and verification purposes. The power of the proposed tool lies in the ability to study the dynamic behaviour of the induction machine in the absence of complicated mathematics. The program was designed to illustrate clearly the effects of the Park’s transformation (McPherson et al, Sushma et al, 2010). This concept is normally very difficult to learn, but by representing the model of the induction motor in a generic reference frame rotating with an angular speed ω, and simulating some transients, with different operating conditions, one can learn quite well from this concept.
Dynamic simulations play an important role in the pre-testing of motor drive systems (Kocabas et al, 2011). Pre-testing is conducted by engineers in industry as well as by researchers in academia. Pre-testing using dynamic simulations can help researchers to determine the experimental setup that will be used for a given set of experimental tests. The transient behaviour of an electric machine is of particular importance when the drive system is to be controlled. Many different methods and control algorithms are available in the literature for controlling the three-phase induction motor (Kumar et al, 2012). A dynamic model of a machine leads to insight into the electrical transients (Dordevic et al, 2010). There are many Simulink induction motor models in the literature (Momoh, 2012). However, most of them do not give the details as to how the model equations and subsystems within the model are derived.
The use of asynchronous motors particularly squirrel-cage rotor has increased tremendously since the day of its invention. They are being used as actuators in many types of industrial processes, robotics, house appliances (generally single-phase) and other similar applications. The reason for its daily increasing popularity can be primarily attributed to its simplicity in design, robust construction and cost effectiveness, high efficiency, reliability and good self –starting capability (Shakuntla et al, 2012, Shi et al, 1999 and Krishan, 2001). The analysis of induction motor is carried out in steady state whereby the machine is modeled as a second order electromechanical system.
Dynamic model of machine describes the transient and the steady state behavior of the induction machine. This model can be used to simulate the asynchronous motor drives and evaluate their transient performances including that of using the scalar control techniques. This model is also used when developing high performance control techniques for the asynchronous motor drives such as vector control or direct control (DTC) drives. During start-up and other motoring operations, this motor draws large currents, produce oscillatory torques, voltage dips and can even generate harmonics in the power system. So it is important to be able to model the asynchronous machine in order to predict these phenomenon. Various models have been developed and d-q axis model for the study of transient behaviour has been well tested and proven to be reliable and accurate (Lee et al, 1984).
In modern electrical technologies, application of the induction motors in speed and position controlled drives have been increased drastically. The main reason behind this is that the large-scale development of the AC induction motors over traditionally used DC motors. To obtained high static and dynamic qualities of these AC drives, control engineers need more information about the control objective. Therefore, the importance of the characteristics and parameter calculation of the induction motor has gone up. Generally, an induction motor dynamics is simulated in circuit simulators like PSpice, its steady state model is used, but for electrical drive studies, the transient behavior is also useful. One of the major advantage of Simulink over circuit simulators is the in modeling the transients of electrical motors. As the equations are known, any control algorithm can be developed in Simulink. A connection to the network and starting of the induction motor is transient effect. Starting the induction motor is followed by a current and torque surges
Any programming language or simulation program can be used for induction motor simulated model. In this paper, MATLAB Simulink model is used after calculating the equivalent circuit parameters of the induction motor. The calculation is done by developing an m file. Basic concepts are used to complete the all necessary calculations. In most of the paper parameters are being calculated by performing the actual no load and blocked rotor test. For the student working on the simulink model, it is quite tough to do actual test for every motor for calculating the circuit parameters used in defining the simulink model box of induction motor. So, step by step method is being discussed in this paper for calculating the desired parameters without involving into the actual test on the motor. Though, this method gives the approximate results but it may be good for the starting the working on the simulink model.
In this paper, MATLAB/Simulink is used to simulate the dynamic performance of an induction motor model. This simulated program makes it easy for the user to follow and understand the development process since it also gives full details about the Simulink structure of each of the model equations.
The pump with induction motor (IM) is one of the most used drives. Most part of generated energy is consumed by using pumps, for example, it is merchantable in several oil industries. It is necessary that pump performance depends on unbalanced voltage value. Net power quality makes influences on induction motor efficiency. This occurrence causes torque ripples. To make pump working more efficient, manufacturers decrease electrical machine loses and researchers improve new control methods and algorithms for drive control (Girdharkini, 2010 and Wu et al, 2011).Nowadays pump drive systems are sometimes used as renewable energy sources. For example, produced energy from wind generator is supplied to pump. After that the pump transports water to reservoir that is located at high place. At the end the stored water is derived to hydro generator. In this case the cost of kilowatt per hour is lower. It means that this type of accumulated energy system will develop more in coming future (Forco, 2011). Energy obtained from solar panels was converted and supplied to pump system pumping water to users. The objective of the paper was to develop converter that supplies three-phase induction motor (Binte et al, 2012).It is necessary to take into account pump drive system vibrations. Shaft vibration is deviation from steady state mode. There are two kinds of vibrations; torsional and ·translational. The value of vibrations depends on rotor eccentricity and not less important is how singular motor and pump are centered (Qutb, 2006).
The pumps belong to the class of the variable load machines the torque of which changes as a function of speed. They develop a reduced torque when driven at speeds well below the rated level and an increased torque as the speed grows. Besides the pumps, the loading systems with viscous friction, calendaring equipment, Eddy current brakes, and separately excited direct current generators feeding fixed resistance loads also fall into this group of machines. Since fans and centrifugal blowers are similar in operation to some sorts of pumps, much of them are also applicable here. The properties of the pump as a motor load are often discussed from the viewpoint of the drive design as well as the pump start-up behavior, response to pump overload, and losses of priming fluid as well as their characteristics as the control system elements (Stewart, 1997, Divona and Dolan, 1985). Nevertheless, in multiple investigations of pumping processes, the pumping drive controllability under the changing loads has not been properly analyzed.In many variable load machines the torque is proportional to some power of the speed (Bose, 2001). In the pumps, fans, and blowers the torque changes with the square of the speed and the power varies with the speed cubed throughout the range of usable speeds. Propellers in ships or airplanes also have the same type of the speed-torque characteristic. With certain type of lathes, boring machines, milling machines, steel mill coilers, etc., the hyperbolic speed-torque characteristics are associated in which the torque is inversely proportional to the speed. Additionally, in all the machines with crankshafts, particularly in reciprocating pumps and compressors, frame saws, weaving looms, rocking pumps used in petroleum industry, etc. the torque is described as a function of the crank position, i.e. the angular displacement of the motor shaft or rotor. The load of the drives used for steering ships also belongs to this category.At closer examination, the load of the significant group of centrifugal pumps represents an enough complex composition of the above mentioned loads in varying proportions (Lonel, 1986). This is the reason, why the torque of these mechanisms can be resolved into two components, one of constant magnitude and the other, periodically changing depending on the speed or the angular position of the shaft. In this way, neglecting the small deviations in angle from the equilibrium position, a load can be transformed to one which varies in respect to time. This alternation may be periodic and repetitive.
Many pumps operate under cyclically varying loads (Snirnov, 2007, Peretti and Zigliotto, 2009). Unlike the machines with continuous constant loads, such as pumps or fans operating for a long time at the same conditions, it is convenient to classify the cyclically operated pumping equipment under the following groups:
• pulsating loads, such as reciprocating pumps and compressors (Saito et al, 2012)
• impact loads, such as apparent, regular and repetitive load peaks or pulses which occur in pumps of waste applications (bakman and Vodovozov, 2012)
• short-time intermittent loads, such as those occurring at almost all forms of abnormal operations (Benjes and Foster, 1985)
Certain pumps do not strictly fall into any of the above groups. In a great deal it concerns the centrifugal pumps capable of transporting high-viscosity fluids and solid-liquid mixtures used in various industrial settings, including cement plants, sewage treatment plants, food plants, and multiple medical fields. If these loads are characterized by frequent impacts of comparatively small peaks, it would be more appropriate to classify them under continuous variable loads rather than under impact loads. Sometimes, it is difficult to distinguish pulsating loads from impact loads since both of them are periodic in nature and, hence, may be expressed as a sum of sinusoidal waves of different amplitude, frequency, and phase. One and the same machine can be represented by a load torque which varies either with speed or with time. For example, a pump whose load torque is proportional to the square of the speed is also a continuous constant loading machine. Rocking pumps for petroleum have a load varying with angular position of the shaft, but can also be classified as pulsating mechanisms. Accuracy of the pump speed adjustment at the load variations is greatly dependent on the control strategy of the variable speed electric drive. As the fast torque response is not a crucial requirement in the pumping applications, the motor speed control in such plants is usually based on the scalar voltage-frequency method (Mohan, 2003, Vodovozov, 2012). Because of the open ended topology, the speed adjustment possibilities of the pump drive remain low enough. To improve situation, online measuring equipment is sometimes applied purposing the load assessing to estimate the temporary fluid rate of the pipelineand to make decision of its use (Hajnal et al, 2012). Nevertheless, they weakly affect the pumping management (Ebrahim et al, 2010). Resulting from the system analysis of working conditions in pumping systems, many problems are encountered due to the speed inaccuracy at the speed-load alternation, such as hydraulic hammers, dynamic stresses in the mechanical parts, overheating in the driving motors, and other issues. From this viewpoint the energy saving is a very sensitive problem (Angers, 2009). Besides, the reliability of the pump also depends on the speed-load variations since the risk of cavitation and the magnitudes of hydraulic excitation forces on the impeller are minimized. If the pump is working outside the preferred operating region, the rate of mechanical wear grows. As shown in (Ahonen, 2011), operation at 70 or 115 % of the best efficiency point tenfold decreases the characteristic life of the pump. In these conditions, the safe pump control should be considered as an effective instrument both to exclude the pump damage and to improve the pumping quality (Chenghu et al, 2011).
This project uses the SIMULINK software of MATLAB, in the dynamic modelling of the induction motor. The main advantage of SIMULINK over other programming softwares is that, instead of compilation of program code, the simulation model is built up systematically by means of basic function blocks. Through a convenient graphical user interface (GUI), the function blocks can be created, linked and edited easily using menu commands, the keyboard and an appropriate pointing device (such as the mouse). A set of machine differential equations can thus be modelled by interconnection of appropriate function blocks, each of which performing a specific mathematical operation. Programming efforts are drastically reduced and the debugging of errors is easy. Since SIMULINK is a model operation programmer, the simulation model can be easily developed by addition of new sub-models to cater for various control functions. As a sub-model the induction motor could be incorporated in a complete electric motor drive system
1.2 STATEMENT OF PROBLEMS
In the past, researchers have developed their own software packages for dynamics modelling of induction motor. It is unnecessary to develop user-written software for dynamic model of induction motor when we have proprietary software package such as Matlab/Simulink, licensed by MathWorks which makes simulation design more efficient and allows other interested parties to understand the operation of the system more easily than a programming-language implementation. The project tends to model and simulate an induction motor in SIMULINK with pump load.
1.3 AIM AND OBJECTIVES
The aim of the project is the development of Simulink models of asynchronous machine with pump load. The specific objectives include
• Develop the electrical model of the induction machine
• Develop a mechanical model of the machine
• Developing of SIMULINK blocks that solves the systems of differential equations for the transient state studies
• Comparing the motor performances on load and pump load
1.4 PROJECT OUTLINE
Chapter Two presents a comprehensive survey of previous work on the study on the design and analysis of induction machines. The proposed Electrical and Mechanical models together with the SIMULINK blocks are presented in Chapter Three. Chapter Four presents the computer simulation and discussion of the results of the proposed models. The conclusions and recommendations are summarized in Chapter five.
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