Global domain fluid-thermal coupling modeling method and characteristics analysis for large capacity motor

Xu, Yongming; Xu, Ziyi; Zhao, Qianwen; Wang, Yaodong

Abstract

The global domain fluid-thermal characteristics study is challenging to perform due to the complicated ventilation arrangement and enormous volume for the large capacity electric machine. This paper uses the world's largest capacity non-superconducting low-speed induction motor, 6.5 MW, as the research object and proposes a global domain fluid-thermal characteristics calculation method. Firstly, the global domain fluid field model of the inner air path is established and solved. Then, the motor is divided into five subdomains according to the ventilation structure. The flow and pressure obtained from fluid field solutions are used as coupling parameters to couple each subdomain model, and an iterative solution is carried out based on the boundary condition continuity of the adjacent subdomains. The temperature distribution of each subdomain is obtained when the temperature difference is less than 0.1%. Finally, an experimental platform is built to verify the results. The maximum relative error between calculated and measured values is 1.67% for temperature and 4.92% for fluid velocity, which verifies the developed model's rationality and the proposed method's validity.

Citation

Xu, Y., Xu, Z., Zhao, Q., & Wang, Y. (2023). Global domain fluid-thermal coupling modeling method and characteristics analysis for large capacity motor. Case Studies in Thermal Engineering, 44, Article 102860. https://doi.org/10.1016/j.csite.2023.102860

• Journal Article Type: Article
• Acceptance Date: Feb 24, 2023
• Online Publication Date: Mar 2, 2023
• Publication Date: 2023-04
• Deposit Date: Apr 25, 2023
• Publicly Available Date: Apr 26, 2023
• Journal: Case Studies in Thermal Engineering
• Electronic ISSN: 2214-157X
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 44
• Article Number: 102860
• DOI: https://doi.org/10.1016/j.csite.2023.102860
• Public URL: https://durham-repository.worktribe.com/output/1176584