Comparative Analysis to Predict the Temperature Rise in 3ɸ-Squirrel Cage Induction Motor using Lumped Parameter Thermal Model and Finite Element Method for Industrial Applications

Jump To References Section

Authors

  • S. Sachin
     Department of Electrical Engineering, M. S. Ramaiah University of Applied Sciences, Bengaluru 560054, Karnataka ,IN
  • Krishnan Manickavasagam
     Department of Electrical and Electronics Engineering Education National Institute of Technical Teachers Training and Research, Bhopal - 462 002, Madhya Pradesh ,IN
  • A. T. Sriram
     Department of Automotive and Aeronautical Engineering, M. S. Ramaiah University of Applied Sciences, Bengaluru 560054, Karnataka ,IN

DOI:

https://doi.org/10.18311/jmmf/2023/43609

Keywords:

Finite Element Method (FEM), Lumped Parameter Thermal Model (LPTM), Squirrel Cage Induction Motor (SCIM).

Abstract

The 3ɸ - Squirrel Cage Induction Motor (SCIM) used in industrial are prone to thermal breakdown due to its working conditions. Losses in the motor cause rise in temperature. Losses estimation of the 3ɸ - SCIM play a very important role in analyzing the electrical and thermal performances. In this paper a Lumped Parameter Thermal Model (LPTM) and Finite Element Method (FEM) is used to estimate the temperature rise in 3ɸ - SCIM. The temperature rise is obtained considering loss, with load variation between no-load to full load conditions, this enables to analyse the application of induction motor in mines. In addition to that a comparative analysis is carried out between Lumped Parameter Thermal Model (LPTM) and Finite Element Method (FEM) to determine the effective method to estimate temperature rise and determine the relative percentage error in temperature rise at various elements of 3ɸ - SCIM.

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Downloads

Published

2024-05-24

How to Cite

Sachin, S., Manickavasagam, K., & Sriram, A. T. (2024). Comparative Analysis to Predict the Temperature Rise in 3ɸ-Squirrel Cage Induction Motor using Lumped Parameter Thermal Model and Finite Element Method for Industrial Applications. Journal of Mines, Metals and Fuels, 71(12A), 383–389. https://doi.org/10.18311/jmmf/2023/43609

Issue

Volume 71, Issue 12A , 2023

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Crossref
Scopus
Google Scholar
Europe PMC

 

References

Bousbaine A. An investigation into the thermal modelling of induction motors (Doctoral dissertation, University of Sheffield).

Kylander G. Thermal modelling of small cage induction motors. Chalmers Tekniska Hogskola (Sweden); 1995.

Liang D, Zhu ZQ, Feng JH, Guo SY, Li YF, Wu JQ, Zhao AF. Influence of critical parameters in lumped-parameter thermal models for electrical machines. 22nd International Conference on Electrical Machines and Systems (ICEMS); 2019 Aug 11-14; China: Harbin; 2019. p. 1-6. https://doi. org/10.1109/ICEMS.2019.8921846 DOI: https://doi.org/10.1109/ICEMS.2019.8921846

Mellor PH, Roberts D, Turner DR. Lumped parameter thermal model for electrical machines of TEFC design. IEE Proceedings B (Electric Power Applications). 1991; 138(5):205-18. https://doi.org/10.1049/ip-b.1991.0025 DOI: https://doi.org/10.1049/ip-b.1991.0025

Popova L, Nerg J, Pyrhönen J. Combined electromagnetic and thermal design platform for totally enclosed induction machines. 8th IEEE Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives; 2011 Sep -8; Italy: Bologna; 2011. p. 153-8. https://doi. org/10.1109/DEMPED.2011.6063617 DOI: https://doi.org/10.1109/DEMPED.2011.6063617

Sachin S, Sriram AT. Review of physical and mathematical modelling aspects of thermal management of induction motors. Journal of Physics: Conference Series; 2020; 1706(1). https://doi.org/10.1088/1742-6596/1706/1/012105 DOI: https://doi.org/10.1088/1742-6596/1706/1/012105

Hooli S, Vadde A, Manickavasagam K, Kadambi GR. Measurement of torque using leakage flux for induction motors in electric vehicles by non-invasive method. Innovations in Electrical and Electronic Engineering: Proceedings of ICEEE 2020; 2021. p. 489-503. https://doi.org/10.1007/978-981-15-4692-1_38 DOI: https://doi.org/10.1007/978-981-15-4692-1_38

Khazi S, Vadde A, Manickavasagam K, Kadambi GR, Narayanan V, Lokesh BM, et al. Analyzation of temperature rise in induction motor for electric vehicles. Advances in Energy Technology: Select Proceedings of EMSME 2020; 2022. p. 173-83. https://doi.org/10.1007/978-981-16-1476- 7_17 DOI: https://doi.org/10.1007/978-981-16-1476-7_17

Hooli SS, Vadde A, Manickavasagam K, Kadambi GR. Fuzzy based health monitoring of electric vehicle motor using time domain analysis. 2021 International Conference on Sustainable Energy and Future Electric Transportation (SEFET); 2021 Jan 21-23; India: Hyderabad; 2021. p. 1-6. https://doi.org/10.1109/SeFet48154.2021.9375791 DOI: https://doi.org/10.1109/SeFet48154.2021.9375791

Boglietti A, Cavagnino A, Staton DA, Popescu M, Cossar C, McGilp MI. End space heat transfer coefficient determination for different induction motor enclosure types. 2008 IEEE Industry Applications Society Annual Meeting; 2008 Oct -9; Canada: Edmonton, AB; 2008. p. 1-8. https://doi. org/10.1109/08IAS.2008.49 DOI: https://doi.org/10.1109/08IAS.2008.49

Boglietti A, Cavagnino A, Stato3n D, Shanel M, Mueller M, Mejuto C. Evolution and modern approaches for thermal analysis of electrical machines. IEEE Transactions on Industrial Electronics. 2009; 56(3):871-82. https://doi. org/10.1109/TIE.2008.2011622 DOI: https://doi.org/10.1109/TIE.2008.2011622

Dutta B, Chowdhury SK. Steady state thermal model of TEFC induction machine. 2012 IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES); 2012 Dec 16-19. India: Bengaluru; 2012. p. 1-6. https://doi.org/10.1109/PEDES.2012.6484344 PMCid:PMC3417975 DOI: https://doi.org/10.1109/PEDES.2012.6484344

Gao Z. Sensorless stator winding temperature estimation for induction machines. Conference Record of the 2006 IEEE Industry Applications Conference Forty-First IAS Annual Meeting; 2006 Oct 8-12. USA: Tampa, FL; 2006. https://doi.org/10.1109/IAS.2006.256559 DOI: https://doi.org/10.1109/IAS.2006.256559

Gao Z, Habetler TG, Harley RG, Colby RS. An adaptive Kalman filtering approach to induction machine stator winding temperature estimation based on a hybrid thermal model. Fourtieth IAS Annual Meeting. Conference Record of the 2005 Industry Applications Conference; 2005.

Mynarek P, Kowol M. Thermal analysis of three-phase induction motor using circuit models. Electrodynamic and Mechatronic Systems; 2011. p. 119-122. https://doi. org/10.1109/SCE.2011.6092137 DOI: https://doi.org/10.1109/SCE.2011.6092137

Staton D, Boglietti A, Cavagnino A. Solving the more difficult aspects of electric motor thermal analysis in small and medium size industrial induction motors. IEEE Trans Energy Convers. 2005; 20(3):620-8. https://doi.org/10.1109/ TEC.2005.847979 DOI: https://doi.org/10.1109/TEC.2005.847979

Sachin S, Manickavasagam K, Sriram AT. Effect of the temperature fluctuation on torque production by assimilating variable core loss using computational approach for electric vehicles motors. Int Rev Electr Eng. 2022; 17(6). https://doi. org/10.15866/iree.v17i6.22503 DOI: https://doi.org/10.15866/iree.v17i6.22503

Sachin S, Manickavasagam K, Sriram AT. Effect of core losses on thermal analysis of 3ɸ-Squirrel Cage Induction Motor using lumped parameter thermal model. Mater Today Proc. 2023; 80:724-30. https://doi.org/10.1016/j. matpr.2022.11.076 DOI: https://doi.org/10.1016/j.matpr.2022.11.076

Sudha B, Vadde A, Manickavasagam K. Thermal behavior on Productive torque in electric vehicle motor using computational methods. 2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA); 2021. p. 367-71.

Sudha B, Vadde A, Manickavasagam K, Kadambi GR. Characterization of temperature and productive torque for 160L frame Squirrel Cage Induction Motor. J Eng Res. 2021. p. 35-46.