Induction motors are the workhorses of industries. The two viable speed control schemes for the induction motor are V/f and indirect field oriented control (IFOC) technique. The voltage source inverter is the conventional power converter employed in the drive scheme. Recently, in medium power applications the multilevel inverters (MLI) are gaining more attention due to their high performance. In this work an attempt is made to develop an MLI fed induction motor drive with V/f control as well as with IFOC technique. The closed loop drive scheme is built and simulated using Matlab / Simulink. The performance of the drive scheme with both the control techniques are exhaustively studied under various conditions and the results are presented. Simulation results of IFOC scheme are provided as it exhibits better dynamic performance compared with the V/f scheme. The performance parameters of the drive with both the control schemes are compared and tabulated. © 2013 IEEE.

Archana T

Department of Database Systems

School of Computer Science and Engineering

Vellore Campus

Chitra A

Department of Energy and Power Electronics

School of Electrical Engineering

Jayakrishnan V.K

Sarin M.V

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Performance analysis of MLI fed induction motor drive with IFOC speed control

2013 Annual IEEE India Conference (INDICON)

This paper attempts to enhance the performance of a green energy induction motor drive. The electronic power converters become indispensable part of the renewable energy systems (RES). The solar photovoltaic (PV) system is efficiently operated with artificial neural network (ANN) based maximum power point tracking (MPPT) algorithm. The inverter topologies for the green drive scheme are analyzed. To improve the drive performance a reduced switch multilevel inverter (RSMLI) is employed. As indirect field oriented control (IFOC) is used, the drive demands on-line estimation of rotor resistance. A neural learning model reference adaptive scheme (NL-MRAS) based rotor resistance estimator is found to exhibit good dynamic performance. This work also investigates the performance of the green drive with an intelligent estimator. The performance enhancement of the green energy drive obtained by ANN based MPPT for the PV system, a reduced switch MLI and an intelligent estimator is presented. © 2015 Elsevier Ltd.

Renewable Energy

Investigation and analysis of high performance green energy induction motor drive with intelligent estimator

Multilevel inverters (MLI) are suitable for renewable energy sources as they operate at lower switching frequency and voltage. The sinusoidal PWM (SPWM) techniques are popularly employed in MLIs to improve the drive performance. However as the number of switches increase it leads to more switching losses, higher price and size of the inverter. In this study, a modified reduced switch MLI (RSMLI) with five switches is proposed. Various multilevel inverter topologies with different multicarrier SPWM techniques such as phase disposition, phase opposition disposition, and alternative phase opposition disposition (APOD) are derived, analysed and presented for the proposed RSMLI. All the inverter topologies are simulated and the scheme with lowest THD is identified. The hardware setup is built for the proposed RSMLI using F28335 digital signal processor (DSP) for pulse generation and the results are validated. The vector control scheme of industrial standard requires an accurate and fast Rr estimator for stable performance. Neural based Rr estimator proposed by the authors is implemented on FPGA. The proposed RSMLI fed induction motor drive is examined with and without the neural based Rr estimator. Encouraging results obtained using the proposed RSMLI are reported. © The Institution of Engineering and Technology 2015.

IET Power Electronics

Reduced switch multilevel inverter for performance enhancement of induction motor drive with intelligent rotor resistance estimator

Inverter fed induction motor drive dynamics is greatly dependent on the input voltage pattern. Indirect field oriented control (IFOC) is of industrial standard which is highly sensitive to motor parameter variations. This paper attempts to address the above cited issues. To ensure the quality of the input voltage multilevel inverter (MLI) is employed to feed the motor. Amongst all the motor parameters rotor resistance is of paramount important as it varies with temperature, frequency and skew effects and also the exact value of rotor resistance is required for the unit vector generation and slip calculation in an IFOC scheme. Hence neural network learning based model reference adaptive system (NN-MRAS) for the on-line estimation of rotor resistance (Rr) is utilized. The Neural learning algorithm determines the estimation speed, stability, weight convergence, accuracy of estimation, speed of tracking and ease of implementation. This work proposes a new neural learning strategy for Rr estimation. The entire system is modeled and simulated in Matlab/Simulink. The MLI fed drive is compared with the conventional inverter fed drive.Also the MLI fed drive dynamics are presented with and without the proposed estimator. © Springer India 2015.

Lecture Notes in Electrical Engineering Power Electronics and Renewable Energy Systems

Investigations on the Dynamics of Seven Level Inverter Fed Induction Motor Drive with Neural Based Rotor Resistance Estimator

Variable Speed AC Drives with Inverter Output Filters

Control of Induction Motor Drives with LC Filters

Analysis of Electric Machinery and Drive Systems

2012 13th International Conference on Optimization of Electrical and Electronic Equipment (OPTIM)

Z converter control of a V/f induction motor drive

2011 INTERNATIONAL CONFERENCE ON RECENT ADVANCEMENTS IN ELECTRICAL, ELECTRONICS AND CONTROL ENGINEERING

Analog control scheme for Cascaded Multilevel Inverters based on multiple carrier PWM technique

2011 International Conference on Power Engineering, Energy and Electrical Drives

A comparative study of different control techniques for an induction motor fed by a Z-source inverter for electric vehicles

Journal	Data powered by Typeset2013 Annual IEEE India Conference (INDICON)
Publisher	Data powered by TypesetIEEE
Open Access	No