Advances in electrical machinery with high efficiencies could significantly reduce the cost of industrial and residential energy systems, thereby reducing fossil fuel needs and emissions. Electrical machine design is a comprehensive process based on several factors, including economic factors, material limitations, specifications and special application-dependent factors. At the same time, machine design is a multi-physics task comprising of electric design, magnetic design, insulation design, thermal design and mechanical design. However, the out-of-date conventional machine design can neither reflect the advances in the past 30 years, nor exploit the trade-offs between design factors from the multi-physics nature of the electrical machine.
This work focus on the development a fast and efficient method for the design and optimization of Surface Mount Permanent Magnet (SMPM) machines and induction machines, as influenced by the energy source, mechanical loads, thermal effects, and the up-to-date developments in materials and manufacturing capabilities.
A new analytical design method is developed for the electromagnetic design of SMPM machines. Both distributed and concentrated winding types of SMPM machines are considered and compared. Based on the proposed electromagnetic analytical design method and a generic thermo-mechanical machine design model [1], an innovative and computationally efficient electromagnetic-thermo-mechanical integrated design method is developed for SMPM machines. Particle Swarm Optimization (PSO) is applied in a novel way based on this integrated design method for the multi-objective design optimization of SMPM machines. With the proposed method, the thermal and mechanical design is no longer treated separately and heuristically as in the traditional design, but has been systemically integrated with the electromagnetic design; the effect of power source, cooling capability, thermal limits, and up-to-date material capabilities are also reflected in the design and optimization. Superior designs compared to traditional designs can be achieved with PSO based multi-objective optimization. The proposed integrated design approach also has the merit of good computational efficiency and provides a significant time reduction of the design cycle compared to finite element analysis.
A novel electromagnetic analytical design method of induction machines has been developed, which needs only six prime design variables but is able to design induction machines in fine details. The advantage over the traditional and other existing design method is that this proposed method does not have the heuristic selection of the design variables and does not need manual design iterations. The computing time is almost negligible and the design cycle is significantly reduced compared to the tradition machine design.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/37280 |
| Date | 17 November 2010 |
| Creators | Duan, Yao |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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