Use this URL to cite or link to this record in EThOS:
Title: Computational fluid dynamics modelling of a synchronous electric generator
Author: Connor, Peter
Awarding Body: University of Nottingham
Current Institution: University of Nottingham
Date of Award: 2013
Availability of Full Text:
Access from EThOS:
An air-cooled synchronous generator has been studied for its airflow and thermal analysis using Computational Fluid Dynamics (CFD) in conjunction with experimental validation. Due to the temperature dependent resistive losses in the machine’s windings, any improvement in cooling provides a direct reduction in losses and an increase in efficiency. In addition, detailed modelling of machine windage components provide an insight for efficiency savings associated with airflow. A full 3600 CFD generator model has been constructed including all major solid components in conjunction with the air fluid regions. Fluid flow, turbulence, rotation as well as conjugate heat transfer modelling was solved throughout the whole machine. The CFD model has been validated using experimental testing on a newly commissioned rig. Airflow parameters of mass flow rate, torque and local pressures were used to validate the fluid modelling. Thermal measurements of stator temperature, heat flux and calculated heat transfer coefficients were used to validate the conjugate heat transfer modelling of the machine. Temperature distributions throughout all machine components were analysed. These have been explained by detailed analysis of local surface heat transfer coefficients and the associated local air flow structures which determine them. This versatility and detail in the thermal analysis of electrical machines is unique to CFD modelling. The methodology presented in this thesis demonstrates advancement in the scale and complexity for CFD analyses of electrical machines. This level of cooling scrutiny will enable informed design developments for step changes in machine efficiency.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available