This thesis develops design methodologies for megawatt(MW)-scale yokeless and segmented armature (YASA) generators for wind turbine applications. The methodologies include the electromagnetic, the structural and the thermal designs of a YASA generator. The design process starts with developing an analytical method to generate preliminary machine designs for a megawatt-scale YASA generator. This analytical approach considers both electromagnetic and structural aspects of a generator, the parameters of which were obtained and visualised on a design reference map. This new concept of displaying machine parameters is useful for a designer to identify the relationship between them. An optimisation tool using pseudo-weight approach is integrated into the analytical tool to determine a optimum machine design. This is a flexible optimisation tool, allowing the user to give priorities to each objective function. The analytical calculation has reduced the design space for suitable machine candidates to be applied in further finite element analysis (FEM). In finite element analysis of an optimised YASA machine, the electromagnetic performance of a 1 MW YASA generator was produced and verified with analytical and experiment results. This is followed by structural optimisation with finite element method, where a spider wheel with a support ring geometry is applied to the rotor plate. This reduces the structural weight by more than 50% while the structure retain strong stiffness. Finally, the cooling system of the stator of the YASA generator is studied and the cooling channels design is proposed. Simulation results show that the stator of a 1 MW YASA generator can be effectively cooled with forced air.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:692893 |
| Date | January 2016 |
| Creators | Vun, Sook Teng |
| Contributors | McCulloch, Malcolm |
| Publisher | University of Oxford |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://ora.ox.ac.uk/objects/uuid:af80d024-58b6-4bb8-adca-a4aa70b69a36 |
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