Modeling and simulation of electric drive systems using Matlab/Simulink environments

Dumitrescu, Ana-Maria; Fodor, D.; Jokinen, T.; Rosu, Marius; Bucurenciu, S.

doi:10.1109/iemdc.1999.769143

Cited by 17 publications

(11 citation statements)

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“…[3,4,15], but they appear to be black boxes with no internal details. Some of them [3,4,15] recommend using S-functions, which are software source codes for Simulink blocks. This technique does not fully utilize the power and ease of Simulink because S-function programming knowledge is required to access the model variables.…”

Section: Related Workmentioning

confidence: 99%

“…In this model the simulation starts with generating a three-phase stator voltages according to the equations (14,15,16), and then transforming these balanced voltages to two phase voltages referred to the synchronously rotating frame using Clarke and Park transformation as in equations (17,18). Fig.3 illustrate the internal structure of the induction machine d-q model by which the flux linkages, currents, torque and the rotor angular speed are calculated.…”

Section: Matlb/simulink Implementationmentioning

confidence: 99%

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A Generalized Matlab Simulink Model of a Three Phase Induction Motor

Phukon¹,

Baruah²

2015

IJIRSET

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Induction motors are the most widely used motor drives in industry because of its simple construction and other advantages such as reliable operation, low initial cost, easy operation and simple maintenance, high efficiency and having simple control gear for starting and speed control. This usefulness of this motor has resulted into a lot of research including the transient behaviour of the machine. This paper presents a step by step Simulink implementation of an induction machine using dq0 axis transformations of the stator and rotor variables in the arbitrary reference frame. At first the important formulas are stated and then according to these formulas a generalized model of a three phase induction motor is developed and implemented. The model is used to investigate the effects of variations in the machine size and parameter values on the dynamic performance of induction machine. The proposed system has been developed and simulated by using Matlab/Simulink.

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Section: Related Workmentioning

confidence: 99%

Section: Matlb/simulink Implementationmentioning

confidence: 99%

A Generalized Matlab Simulink Model of a Three Phase Induction Motor

Phukon¹,

Baruah²

2015

IJIRSET

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“…Simulink induction machine models are available in the literature [9][10][11], but they appear to be block-boxes with no internal details. Some of them [9][10][11] recommend using S-functions, which are software source codes for Simulink blocks.…”

Section: Andmentioning

confidence: 99%

“…Some of them [9][10][11] recommend using S-functions, which are software source codes for Simulink blocks. This technique does not fully utilize the power and ease of Simulink because S-function programming knowledge is required to access the model variables.…”

Section: Andmentioning

confidence: 99%

Simulation of Induction Machine Drive by Composite Model Flux Observer

Fazly¹,

Moussavi²

2010

IJCEE

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“…In the field of industrial sector induction motor drives are major contributors, the simulation of these drives can be done in several methods, one of such kind is Simulink model [1]- [2].Mathematical modeling of induction motor drives are involved in conventional methods where the system diverts from required performance due to system variable variation [3].The conventional methods like kalman filter,PI Controller are used by many researchers to develop dq0 & abc models [4]. The Kalman filter controller uses numerical analysis based on predictor-corrector approximation [5] and PI controller based on linearity concept for unique operating points which resulted in attaining high performance was discussed [6] by several authors.…”

Section: Introductionmentioning

confidence: 99%

Different Control Schemes for Sensor Less Vector Control of Induction Motor

Gangishetti¹,

Sandipamu²

2017

IJPEDS

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This paper deals with the design of different control schemes for sensorless vector control of induction motor.Induction motor is most widely used A.C. Motor but the major draw back is flux and torque cannot be controlled individually.This can be obtained by implementing sensorless vector control methods.The control strategy of induction motor is by different controllers like conventional control methods and artificial intelligence control methods.The conventional control methods are sensitive to parameter changes and will not be accurate. This paper proposes to design a controller to over come the above draw backs by using intelligent control techniques like fuzzy logic, artificial neutral networks (ANN) and genetic algorithm (GA). The above conventional control methods are compared with intelligent control techniques. The simulation studies are carried out using Matlab/Simulink and the wave forms for speed, torque and voltage components for various controlles are plotted. Numerical analysis for speed and torque components considering parameters like peakover shoot and peak time are presented. Keyword: Conventional controllers Fuzzy logic Genetic algorithms Induction motor (IM) Neural networks Sensor less vector control Copyright © 2017 Institute of Advanced Engineering and Science.All rights reserved. Corresponding Author:Srinivas Gangishetti, JNTUHCE, Hyderabad, India.Email: gangishetti07@gmail.com INTRODUCTIONIn the field of industrial sector induction motor drives are major contributors, the simulation of these drives can be done in several methods, one of such kind is Simulink model [1]- [2].Mathematical modeling of induction motor drives are involved in conventional methods where the system diverts from required performance due to system variable variation [3].The conventional methods like kalman filter,PI Controller are used by many researchers to develop dq0 & abc models [4]. The Kalman filter controller uses numerical analysis based on predictor-corrector approximation [5] and PI controller based on linearity concept for unique operating points which resulted in attaining high performance was discussed [6] by several authors. These methods are sensitive to rotor time and correct flux estimationis required.Sensor less Vector control gains its significance where induction motor can modelled similar to D.C Motor using Field orientation control where torque and flux are independently controlled.With the rapid development of power electronics and digital computation the errors in the above methods are nullified with adaptation of artificial intelligence methods,like Fuzzy controller,Artifical neural networks and Genetic Algorithms .Many authors created a control signal employing fuzzy systems [7], these controllers relay on firing rules which are framed by past experiences. Thus, the outcome of the controller is also random and optimal results are based on selecting the right rule depending on the situation.Artifical Neural networks was used to developed an adaptive speed control of drives and to predict th...

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Modeling and simulation of electric drive systems using Matlab/Simulink environments

Cited by 17 publications

References 1 publication

A Generalized Matlab Simulink Model of a Three Phase Induction Motor

A Generalized Matlab Simulink Model of a Three Phase Induction Motor

Simulation of Induction Machine Drive by Composite Model Flux Observer

Different Control Schemes for Sensor Less Vector Control of Induction Motor

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