Optimization of Hollow Shaft Geometry for Rotor Cooling in Inductions Motors Using Response Surface Methodology

References

[1] Believe O Idogho, Ifeanyichukwu U Onyenanu, Kennedy C Owuama, Ashimedua C Ndubisi, Chukwunwendu E Ilochonwu (2025) Optimization of a Sustainable Virgin Coconut Oil Extraction Machine for Rural Communities. JournalofFood Technology&NutritionSciences. SRC/JFTNS-275. DOI: doi.org/10.47363/JFTNS/2025(7)215

[2] Deriszadeh, A., Di Battista, D., Di Giovine, G., & Cipollone, R. (2024). Model based design and optimization of a shaft cooling for automotive electric motor. Journal of Physics: Conference Series, 2893(1), 012124. https://doi.org/10.1088/1742-6596/2893/1/012124

[3] Dinh, I. (2023). Thermal Analysis Based Design of Hollow Shaft for Improved Cooling of Induction Motors. https://uwindsor.scholaris.ca/items/0d9285a0-ef1d-4ad4-8a74-22ae8f6c629a

[4] Ezechukwu, V. C., Oghenekaro, P. O., Onyenanu, I. U., Ayadinuno, G., & Agwaziam, J. O. (2025). Mathematical Modeling and Optimization of Plantain Chip Drying: A Parametric Study on Air Frying Conditions. IPS Journal of Engineering and Technology, 1(1). https://doi.org/10.54117/ijet.v1i1.13

[5] Gai, Y. (2020). A hollow-shaft rotor cooling system for automotive traction motors [PhD Thesis, Newcastle University]. http://theses.ncl.ac.uk/jspui/handle/10443/5024

[6] Gai, Y., Chong, Y. C., Adam, H., Goss, J., & Popescu, M. (2019). Power losses and thermal analysis of a hollow-shaft rotor cooling system. 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), 1–6. https://doi.org/doi:%252010.1109/ICEMS.2019.8922026.

[7] Gai, Y., Ma, C., Xu, Y., & Chong, Y. C. (2021). Numerical prediction and measurement of pressure drop and heat transfer in a water-cooled hollow-shaft rotor for a traction motor application. IET Electric Power Applications, 15(4), 476–486. https://doi.org/10.1049/elp2.12042

[8] Gundabattini, E., & Mystkowski, A. (2022). Review of air-cooling strategies, combinations and thermal analysis (experimental and analytical) of a permanent magnet synchronous motor. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 236(1), 655–668. https://doi.org/10.1177/0954406220987267

[9] Jugu, E. B., Onyenanu, I. U., & Nwobi-Okoye, C. C. (2025). Finite Element Analysis and Factorial Optimization of Heat Treatment Flaws in CNG Pressure Vessels: Implications for Structural Integrity and Safety. ScientificJournalofEngineering, andTechnology, 2(1). https://doi.org/10.69739/sjet.v2i1.487

[10] Konda, Y. R., Ponnaganti, V. K., Reddy, P. V. S., Singh, R. R., Mercorelli, P., Gundabattini, E., & Solomon, D. G. (2024). Thermal Analysis and Cooling Strategies of High-Efficiency Three-Phase Squirrel-Cage Induction Motors—A Review. Computation, 12(1), 6. https://doi.org/10.3390/computation12010006

[11] Konovalov, D., Tolstorebrov, I., Eikevik, T. M., Kobalava, H., Radchenko, M., Hafner, A., & Radchenko, A. (2023). Recent Developments in Cooling Systems and Cooling Management for Electric Motors. Energies, 16(19), 7006. https://doi.org/10.3390/en16197006

[12] Lee, M. (2025). Numerical and Experimental Analysis of Heat Transfer in a Rotating Hollow Rotor Shaft Cooling System for Electric Motor Applications. https://uwindsor.scholaris.ca/items/5f8b6803-e9b4-4ea5-96a7-cb5c447b6bc2

[13] Li, X., Zhao, X., Zhang, Z., Avelin, A., Liu, S., & Li, H. (2025). Selecting cooling methods for electric motors. Applied Thermal Engineering, 274, 126554.

[14] Madukasi, A. H., Onyenanu, I. U., Oghenekaro, P. O., Nzenwa, C. C., & Madu, K. E. (2025). Optimization of the Drying Parameters for Plantain Chips using a Locally Made Tray Dryer: A Study on Drying Efficiency and Drying Rate Modeling using RSM. JournalofFoodTechnology&NutritionSciences, 206(7), 2–10. DOI: Doi. Org/10.47363/JFTNS/2025

[15] Nwigbo, O., Nwoko, C., Emerie, S., & Onyenanu, I. (2025). Optimizing Agricultural Drying Technologies: A Systematic Review of Charcoal, Gas, and Hybrid Kilns for Sustainable Food Preservation. Journal of Sustainable Engineering & Renewable Energy (JSERE), 1(1), 37–51.

[16] Offodum, C. D., Oji, A., & Onyenanu, I. U. (2025). Optimization of Inorganic Refrigerants in Cascade LNG Liquefaction Systems: A Response Surface Methodology Approach for Enhanced Energy Efficiency and Sustainability. Journal of Engineering and Applied Sciences Technology. SRC/JEAST-426. DOI: Doi. Org/10.47363/JEAST/2025 (7), 306, 2–9.

[17] Okpala, I. F., Onyenanu, I. U., Ezechukwu, V. C., & Ilochonwu, C. E. (2025). Performance Optimization of a Locally Developed Charcoal Briquette Machine Using Response Surface Methodology. Scientific Journal of Engineering, and Technology, 2(1), Article 1. https://doi.org/10.69739/sjet.v2i1.486

[18] Onyegirim, S., Onyenanu, I., Madukasi, A., & Nwigbo, O. (2025). The Role of Intake Manifold Geometry on Airflow Dynamics and Combustion Efficiency: A Computational and Experimental Review. Journal of Sustainable Engineering & Renewable Energy (JSERE), 1(1), 29–36.

[19] Onyenanu, I. U., & Nwigbo, S. C. (2021). Optimization of aluminium metal matrix composite (AMMC) for use in automobile brake disc. Int.J.Eng.Res.Technol, 10(7), 634–638.

[20] Onyenanu, I. U., Ogbogu, M. C., & Nwadiuto, C. J. (2024b). Performance optimization of an improved biomass gasifier charcoal stove using response surface method (RSM). International Journal of Engineering Research & Technology (IJERT), 13(08). DOI: 10.17577/IJERTV13IS080031

[21] Onyenanu, I. U., Ukwu, N. O., Ezechukwu, V. C., Onyenanu, I. M., & Nwadiuto, C. J. (2024a). Modelling and Optimization of Banana/Plantain Fiber Extraction Systems through Dimensional Analysis. InternationalJournalofAppliedand NaturalSciences,2(2), 40–52. https://doi.org/10.61424/ijans.v2i2.161

[22] Pereira, R. J. R., de Almeida, F. A., & Gomes, G. F. (2023). A multiobjective optimization parameters applied to additive manufacturing: DOE-based approach to 3D printing. Structures, 55, 1710–1731. https://doi.org/10.1016/j.istruc.2023.06.136

[23] Petrova, S., & Dimitrov, I. (2025). Systematic Parameter Tuning for Multi-Objective Optimization Problems Through Statistical Experimental Design. Frontiers in Emerging Artificial Intelligence and Machine Learning, 2(06), 14–26.

[24] Rachman, N. A., & Risdiyanto, A. (2015). Performance evaluation of electric motor based on review of bearing lifetime and windings temperature. International Journal of Applied Engineering Research, 10, 38070–38077.

[25] Sethupathi, P., & Senthilnathan, N. (2020). Comparative analysis of line-start permanent magnet synchronous motor and squirrel cage induction motor under customary power quality indices. Electrical Engineering, 102(3), 1339–1349. https://doi.org/10.1007/s00202-020-00955-2

[26] Shirazi, M., Khademalrasoul, A., & Safieddin Ardebili, S. M. (2020). Multi-objective optimization of soil erosion parameters using response surface method (RSM) in the Emamzadeh watershed. Acta Geophysica, 68(2), 505–517. https://doi.org/10.1007/s11600-020-00404-5

[27] Usca-Gomez, H. G., Puma-Benavides, D. S., Zambrano-Leon, V. D., Castillo-Díaz, R., Quinga-Morales, M. I., Solís-Santamaria, J. M., & Llanes-Cedeño, E. A. (2025). A Review and Case of Study of Cooling Methods: Integrating Modeling, Simulation, and Thermal Analysis for a Model Based on a Commercial Electric Permanent Magnet Synchronous Motor. World Electric Vehicle Journal, 16(8), 437. https://doi.org/10.3390/wevj16080437

[28] Wang, Q., Wu, Y., Niu, S., & Zhao, X. (2022). Advances in Thermal Management Technologies of Electrical Machines. Energies, 15(9), 3249. https://doi.org/10.3390/en15093249

[29] Wang, R., Fan, X., Li, D., Qu, R., Liu, Z., & Li, L. (2022). Comparison of heat transfer characteristics of the hollow-shaft oil cooling system for high-speed permanent magnet synchronous machines. IEEE Transactions on Industry Applications, 58(5), 6081–6092. https://doi.org/doi:%252010.1109/TIA.2022.3182312.

@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}
  }