Stator resistance estimation of induction motor using genetic algorithm

Nowadays, induction motors are mainly used in all industrial especially in plant industrial. In general, this motor is widely used because it is cheaper, easy to maintenance, no friction by brushes and their speed are easy to control compared to the direct current (DC) motor. But, the stator resista...

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Main Author: Nurul Syamila, Mohd Rosli
Format: Undergraduates Project Papers
Language:English
Published: 2012
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/4450/
http://umpir.ump.edu.my/id/eprint/4450/1/cd6756_56.pdf
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author Nurul Syamila, Mohd Rosli
author_facet Nurul Syamila, Mohd Rosli
author_sort Nurul Syamila, Mohd Rosli
building UMP Institutional Repository
collection Online Access
description Nowadays, induction motors are mainly used in all industrial especially in plant industrial. In general, this motor is widely used because it is cheaper, easy to maintenance, no friction by brushes and their speed are easy to control compared to the direct current (DC) motor. But, the stator resistance changes continuously with the temperature of the machine. The changes can cause an error between the actual and estimated motor torques which leads to motor break down in worst cases. In order to solve this issue, a genetic algorithm method is designed to estimate the variation of stator resistance. This project is about to design genetic algorithm estimator using MATLAB software, and builds an actual induction motor using Newcastle University Drives Simulation Library. Finally these parts of Simulink diagram will be combined to estimate the variation of stator resistance.
first_indexed 2025-11-15T01:20:59Z
format Undergraduates Project Papers
id ump-4450
institution Universiti Malaysia Pahang
institution_category Local University
language English
last_indexed 2025-11-15T01:20:59Z
publishDate 2012
recordtype eprints
repository_type Digital Repository
spelling ump-44502021-06-03T04:41:29Z http://umpir.ump.edu.my/id/eprint/4450/ Stator resistance estimation of induction motor using genetic algorithm Nurul Syamila, Mohd Rosli TK Electrical engineering. Electronics Nuclear engineering Nowadays, induction motors are mainly used in all industrial especially in plant industrial. In general, this motor is widely used because it is cheaper, easy to maintenance, no friction by brushes and their speed are easy to control compared to the direct current (DC) motor. But, the stator resistance changes continuously with the temperature of the machine. The changes can cause an error between the actual and estimated motor torques which leads to motor break down in worst cases. In order to solve this issue, a genetic algorithm method is designed to estimate the variation of stator resistance. This project is about to design genetic algorithm estimator using MATLAB software, and builds an actual induction motor using Newcastle University Drives Simulation Library. Finally these parts of Simulink diagram will be combined to estimate the variation of stator resistance. 2012-06 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/4450/1/cd6756_56.pdf Nurul Syamila, Mohd Rosli (2012) Stator resistance estimation of induction motor using genetic algorithm. Faculty of Mechanical Engineering, Universiti Malaysia Pahang.
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Nurul Syamila, Mohd Rosli
Stator resistance estimation of induction motor using genetic algorithm
title Stator resistance estimation of induction motor using genetic algorithm
title_full Stator resistance estimation of induction motor using genetic algorithm
title_fullStr Stator resistance estimation of induction motor using genetic algorithm
title_full_unstemmed Stator resistance estimation of induction motor using genetic algorithm
title_short Stator resistance estimation of induction motor using genetic algorithm
title_sort stator resistance estimation of induction motor using genetic algorithm
topic TK Electrical engineering. Electronics Nuclear engineering
url http://umpir.ump.edu.my/id/eprint/4450/
http://umpir.ump.edu.my/id/eprint/4450/1/cd6756_56.pdf