This research focuses on the creation of a thermal estimator to be used in an integrated electromagnetic, thermo-mechanical design tool for the rapid optimal initial sizing of switched reluctance and induction machines. The switched reluctance model includes heat generation in the rotor due to core losses, heat transfer across the air gap through convection, and a heat transfer path through the shaft to ambient. Empirical Nusselt correlations for laminar shear flow, laminar flow with vortices and turbulent flow are used to estimate the convective heat transfer coefficient in the air gap. The induction model adds ohmic heat generation within the rotor bars of the machine as an additional rotor heat source. A parametric, self-segmenting mesh generation tool was created to capture the complex rotor geometries found within switched reluctance or induction machines. Modeling the rotor slot geometries in the R-θ polar coordinate system proved to be a key challenge in the work. Segmentation algorithms were established to model standard slot geometries including radial, rectangular (parallel-sided), circular and kite-shaped features in the polar coordinate system used in the R-θ solution plane. The center-node mesh generation tool was able optimize the size and number of nodes to accurately capture the cross sectional area of the feature, in the solution plane. The algorithms pursue a tradeoff between computational accuracy and computational speed by adopting a hybrid approach to estimate three dimensional effects. A thermal circuits approach links the R-θ finite difference solution to the three dimensional boundary conditions. The thermal estimator was able to accurately capture the temperature distribution in switched reluctance and induction machines as verified with experimental results.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/53394 |
| Date | 08 June 2015 |
| Creators | Bednar, Chad Michael |
| Contributors | Mayor, J. Rhett R. |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
Page generated in 0.003 seconds