Research Article
Article:Efficiency Optimization of Induction Motor Drive Using Soft Computing Techniques
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 3 - Issue 1 |
| Published: June 2010 |
| Authors: K.Ranjith Kumar, D.Sakthibala, Dr.S.Palaniswami |
10.5120/703-986
|
K.Ranjith Kumar, D.Sakthibala, Dr.S.Palaniswami . Article:Efficiency Optimization of Induction Motor Drive Using Soft Computing Techniques. International Journal of Computer Applications. 3, 1 (June 2010), 6-12. DOI=10.5120/703-986
@article{ 10.5120/703-986,
author = { K.Ranjith Kumar,D.Sakthibala,Dr.S.Palaniswami },
title = { Article:Efficiency Optimization of Induction Motor Drive Using Soft Computing Techniques },
journal = { International Journal of Computer Applications },
year = { 2010 },
volume = { 3 },
number = { 1 },
pages = { 6-12 },
doi = { 10.5120/703-986 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2010
%A K.Ranjith Kumar
%A D.Sakthibala
%A Dr.S.Palaniswami
%T Article:Efficiency Optimization of Induction Motor Drive Using Soft Computing Techniques%T
%J International Journal of Computer Applications
%V 3
%N 1
%P 6-12
%R 10.5120/703-986
%I Foundation of Computer Science (FCS), NY, USA
Abstract
This paper presents a new approach that minimizes copper & iron losses and optimizes the efficiency of a variable speed Induction motor drive. This method is based on a simple induction motor field oriented control model includes iron losses uses only conventional IM parameters. In literature, Fuzzy logic and Genetic Algorithms have been used for efficiency optimization of induction motor drives. This paper proposes integration of Fuzzy model identification and PSO algorithm for loss minimization. An improvement of efficiency is obtained by adjusting the magnetizing current component with respect to the torque current component to give the minimum total copper and iron losses. The whole circuit is simulated using MATLAB 7.6. The proposed method is compared with other soft computing techniques. The results obtained by Fuzzy PSO shows better results compared with other approaches.
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