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

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Authors

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

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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

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