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Efficiency Optimization of Three-Phase Induction Motor Using Response Surface Methodology

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Proceedings of Third International Conference on Intelligent Computing, Information and Control Systems

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1415))

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Abstract

Induction motors are the most common in residential, commercial, and industrial settings are also known as the workhorses of modern industry. Specially, Squirrel-cage type induction motor is distinguished by its simplicity, resilience, and low cost, all of which have always made it highly appealing, and it has thus risen to the top of the industrial sectors. These motors use a significant portion of the total electrical energy produced in the industry as a result of their widespread use. To improve the efficiency of induction motor becomes the priority during the design stage. This paper aims at optimizing the efficiency of three-phase induction motor by manipulating diameter of stator conductor and input power of a motor while keeping constant motor output of 1.1 KW while rest of the parameters are kept constant. Central composite design is adopted and, therefore, the experiments are conducted supported the planning matrix so obtained. A mathematical model additionally developed for the identical parametric optimization is finished through the response surface methodology. The response optimizer optimizes the overall efficiency of the motor through multi-objective optimization.

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Appendix

Appendix

The following table is obtained by ANSYS software for 3 phase, 1.1 KW, 440 V, 50 Hz induction motor.

Stator wire diameter (mm)

Speed (rpm)

Torque (N)

Input power

Output power

Efficiency

0.287

2896.61

3.6277

1.45855

1.1004

75.4445

0.302

2896.72

3.62586

1.45719

1.09988

75.4793

0.32

2896.79

3.62625

1.4562

1.10003

75.5407

0.34

2896.8

3.62642

1.45589

1.10008

75.5607

0.361

2896.72

3.62592

1.456719

1.099

75.4808

0.381

2896.28

3.6266

1.46268

1.09996

75.2017

0.404

2897.29

3.62535

1.44952

1.09995

75.8836

0.429

2896.71

3.62587

1.45623

1.09991

75.5313

0.455

2895.81

3.6266

1.46868

1.09978

74.8819

0.483

2896.93

3.62501

1.45443

1.09997

75.6107

0.511

2895.23

3.62781

1.47606

1.09991

74.5166

0.541

2896.37

3.62651

1.46168

1.09994

75.2522

0.574

2892.85

3.6341

1.50235

1.10009

73.2247

0.607

2894.39

3.62939

1.485

1.10007

74.0785

0.643

2895.81

3.626261

1.4687

1.09964

74.8718

0.683

2896.93

3.62497

1.45443

1.099669

75.6095

0.724

2888.64

3.63702

1.54543

1.1009

71.1897

0.767

2890.96

3.63342

1.52188

1.09998

72.2781

0.813

2892.9

3.63157

1.50191

1.10016

73.2511

0.861

2894.53

3.62882

1.48389

1.09995

74.9144

0.912

2895.86

3.6273

1.46833

1.09999

75.5979

0.965

2896.93

3.6245

1.45447

1.09955

75.5979

1.024

2896.93

3.6245

1.45447

1.09955

75.5979

2.052

2896.93

3.6245

1.45447

1.09955

75.5979

2.174

2896.93

3.6245

1.45447

1.09955

75.5979

2.304

2896.93

3.6245

1.45447

1.09955

75.5979

3.081

2896.93

3.6245

1.45447

1.09955

75.5979

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Sonje, D.M., Bangali, Y.N., Rout, S.R., Chaudhary, A.M. (2022). Efficiency Optimization of Three-Phase Induction Motor Using Response Surface Methodology. In: Pandian, A.P., Palanisamy, R., Narayanan, M., Senjyu, T. (eds) Proceedings of Third International Conference on Intelligent Computing, Information and Control Systems. Advances in Intelligent Systems and Computing, vol 1415. Springer, Singapore. https://doi.org/10.1007/978-981-16-7330-6_77

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