The Amalgamation Performance Analysis of the LCI and VSI Fed Induction Motor Drive
Mei 2017
Shashank Kumar Singh, Imran Khan

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In this paper combination of a load-commutated inverter (LCI) and a voltage-source inverter (VSI) are employed for performance analysis of induction motor drive. Induction motors are the starting point to design an electrical drive system which is widely used in many industrial applications. In modern control theory, different mathematical models describe induction motor according to the employed control methods. Vector control strategy can be applied to this electrical motor type in symmetrical three phase version or in unsymmetrical two phase version. The operation of the induction motor can be analyzed similar to a DC motor through this control method. In this control scheme the electromagnetic torque and stator flux magnitude are estimated with only stator voltages and currents and this estimation does not depend on motor parameters except for the stator resistance. There is an increasing trend of using SVPWM, because of their easier digital realization and better DC bus utilization. The study of SVPWM technique reveals that this technique utilizes DC bus voltage more efficiently and generates less harmonic distortion when compared with sinusoidal PWM techniques. The SVPWM technique has become one of the important PWM techniques for Three Phase Voltage Source Inverter for the control of AC induction motor, Brushless DC motor, Switched Reluctance motor and Permanent Magnet Synchronous motor. In this paper having collection of different schemes in SVPWM. Specifically various schemes are Center aligned two level SVPWM, Level shifted multi-carrier concepts based SVPWM.
This paper having simulation results of all the three schemes of SVPWM by using MATLAB/SIMULINK software. The performance of Three Phase Voltage Source Inverter fed induction motor drive based on various SVPWM schemes are analyzed by various reference parameters like DC bus utilization. The simulation results are provided to validate the proposed model approaches.

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