Computationally-Efficient Thermal Modeling Techniques for Electric Machines
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Electric machines are widely used in industry, ranging from as large as 700Mw generators used in Three Gorges in Yichang, China, to as small as brushless DC motors used in your computer hard drives. For some areas, such as automotive powertrain design, accurate and computationally-efficient models for electric machines are in great demand since they can play important roles as either real-time observers or in vehicle simulations. In this dissertation, computationally-efficient thermal and electromagnetic models for electric machines are developed. In particular, a thermal convection model to capture air region heat convection considering air density variation and slotting effects on stator surface is developed and analyzed; and an electromagnetic model to calculate AC winding resistance of different winding configurations is proposed and integrated. With the developed techniques, thermal and electromagnetic performance can be accurately and efficiently estimated. Furthermore, this dissertation has also conducted a comparative study, which shows the advantages of using thermal models for online loss estimation for electric machines over the conventionally-used electrical model. The conclusions and results of this study provide useful tools for online loss estimators with model uncertainty.
Co-chairs: Prof. Heath Hofmann, Prof. Jing Sun