scholarly journals Discrete and continuous model of three-phase linear induction motors considering attraction force and end-effects

Author(s):  
Nicolás Toro-García ◽  
Yeison Alberto Garcés-Gómez ◽  
Fredy E. Hoyos

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p><span>The continuous model of the linear induction motor (LIM) has been made considering the edge effects and the attraction force. Taking the attraction force into account is im- portant when considering dynamic analysis when the motor operates under mechanical load. A laboratory prototype has been implemented from which the parameters of the equivalent LIM circuit have been obtained. The discrete model has been developed to quickly obtain computational solutions and to analyze non-linear behaviors through the application of discrete control systems. In order to obtain the discrete model of the LIM we have started from the solution of the continuous model. To develop the model, the magnetizing inductance has been considered, which reflects the edge effects. In the results, the model is compared without considering the edge effects or the attraction force with the proposed model. </span></p></div></div></div>

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 655 ◽  
Author(s):  
Nicolás Toro-García ◽  
Yeison Garcés-Gómez ◽  
Fredy Hoyos

A fifth-order dynamic continuous model of a linear induction motor (LIM), without considering “end effects” and considering attraction force, was developed. The attraction force is necessary in considering the dynamic analysis of the mechanically loaded linear induction motor. To obtain the circuit parameters of the LIM, a physical system was implemented in the laboratory with a Rapid Prototype System. The model was created by modifying the traditional three-phase model of a Y-connected rotary induction motor in a d–q stationary reference frame. The discrete-time LIM model was obtained through the continuous time model solution for its application in simulations or computational solutions in order to analyze nonlinear behaviors and for use in discrete time control systems. To obtain the solution, the continuous time model was divided into a current-fed linear induction motor third-order model, where the current inputs were considered as pseudo-inputs, and a second-order subsystem that only models the currents of the primary with voltages as inputs. For the discrete time model, the current-fed model is discretized by solving a set of differential equations, and the subsystem is discretized by a first-order Taylor series. Finally, a comparison of the continuous and discrete time model behaviors was shown graphically in order to validate the discrete time model.


2013 ◽  
Vol 416-417 ◽  
pp. 711-717
Author(s):  
Zhi Hua Zhang ◽  
Li Ming Shi ◽  
Hua Cai ◽  
Yao Hua Li

Linear drive system is widely applied in mid-low speed Maglev, subway transportation, etc. It is composed of two principal components, high power converter and linear induction motor. The converter and motor are designed separately, whole drive system usually use circuit simulation by extracting the mathematical model of linear induction motor. However, LIM has complex electromagnetic field, which needs to considerate the transverse and longitude end effects [1-. This makes LIM mathematical model inaccurate, hard to simulate the real dynamic characteristics of LIM.


2018 ◽  
Vol 7 (4) ◽  
pp. 2028 ◽  
Author(s):  
Ameer L. Saleh ◽  
Badiryah A. Obaid ◽  
Adel A. Obed

This paper contains a proposed controller based on optimal recurrent wavelet neural network (RWNN) with PID controller to control the velocity and hence the stator current as well as the developed thrust of three phase linear induction motor (LIM) which consider the end effects. A vector control represented by indirect field oriented control (IFOC) technique is appointed to attain velocity and flux control for different loading conditions. Moreover, a voltage source inverter based on space vector pulse width modulation (SVPWM) is utilized to give the required stator voltage of LIM. A well-known particle swarm optimization (PSO) algorithm is employed for online tuning of the proposed controller. The computer simulation results show that this controller is effective and gives preferable and rigorous performance compared with a results obtained from conventional wavelet neural network (WNN) and PID controllers.  


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