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Optimization of Hollow Shaft Geometry for Rotor Cooling in Inductions Motors Using Response Surface Methodology
Subject area: Science,Engineering and Technology · Area of research: Induction Motor Rotor Cooling Optimization
DOI: https://doi.org/10.64388/IREV9I12-1718796
Abstract
Maintaining performance and dependability in induction motors requires efficient thermal management, especially as power density requirements rise in electric vehicle applications. Although direct rotor heat extraction is possible with hollow shaft cooling, systematic geometric optimisation that takes structural, hydraulic, and thermal trade-offs into account has not yet been investigated. This study optimizes hollow shaft geometry for a 120-kW induction motor using Response Surface Methodology (RSM) coupled with Computational Fluid Dynamics (CFD). Three variables were examined in relation to four responses: heat transfer coefficient, temperature reduction, pressure drop, and structural safety factor. These variables were fin density (15–25 fins/100 mm), channel aspect ratio (1.5–2.5), and coolant flow rate (4–8 L/min). A Central Composite Design with 20 experimental runs was employed. Coolant flow rate emerged as the dominant factor influencing all responses. Maximum thermal performance (709.6 W/m²·K, 18.07°C reduction) occurred at the highest factor levels but produced the lowest safety factor (1.753) and the highest pressure drop (22.98 kPa), confirming inherent design trade-offs. Linear models adequately predicted thermal responses, while pressure drop and safety factor exhibited significant curvature, requiring quadratic modeling. The optimized configuration balances thermal enhancement against hydraulic and structural constraints, providing a validated framework for hollow shaft cooling design in traction motors.
Keywords
Induction Motor, Hollow Shaft Cooling, Response Surface Methodology, Thermal Management, Multi-Objective Optimization, Rotor Cooling
How to cite this paper
@article{1718796,
author = {Onyeji Levi Chinaka, Ibezim Joseph Maduabuchi, Dr Samuel O. Ikegbula, Unya Ndukwe},
title = {Optimization of Hollow Shaft Geometry for Rotor Cooling in Inductions Motors Using Response Surface Methodology},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {12},
pages = {1416-1434},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1718796.pdf},
abstract = {Maintaining performance and dependability in induction motors requires efficient thermal management, especially as power density requirements rise in electric vehicle applications. Although direct rotor heat extraction is possible with hollow shaft cooling, systematic geometric optimisation that takes structural, hydraulic, and thermal trade-offs into account has not yet been investigated. This study optimizes hollow shaft geometry for a 120-kW induction motor using Response Surface Methodology (RSM) coupled with Computational Fluid Dynamics (CFD). Three variables were examined in relation to four responses: heat transfer coefficient, temperature reduction, pressure drop, and structural safety factor. These variables were fin density (15–25 fins/100 mm), channel aspect ratio (1.5–2.5), and coolant flow rate (4–8 L/min). A Central Composite Design with 20 experimental runs was employed. Coolant flow rate emerged as the dominant factor influencing all responses. Maximum thermal performance (709.6 W/m²·K, 18.07°C reduction) occurred at the highest factor levels but produced the lowest safety factor (1.753) and the highest pressure drop (22.98 kPa), confirming inherent design trade-offs. Linear models adequately predicted thermal responses, while pressure drop and safety factor exhibited significant curvature, requiring quadratic modeling. The optimized configuration balances thermal enhancement against hydraulic and structural constraints, providing a validated framework for hollow shaft cooling design in traction motors.},
keywords = {Induction Motor, Hollow Shaft Cooling, Response Surface Methodology, Thermal Management, Multi-Objective Optimization, Rotor Cooling},
month = {June},
doi = {https://doi.org/10.64388/IREV9I12-1718796}
}