Structural Optimization and Thermal Modeling of Flux Switching Machine

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Journal Title
Journal ISSN
Volume Title
Sähkötekniikan korkeakoulu | Master's thesis
Date
2015-02-09
Department
Major/Subject
Electrical Machines, Drives and Power Electronics
Mcode
S3016
Degree programme
EST - Master’s Programme in Electrical Engineering
Language
en
Pages
64+9
Series
Abstract
The point of this study was to model a lumped parameter thermal network for flux switching machine. The model could be utilized to outline new cooling systems and as a developer for this sort of machines. The model developed is a thermal framework having segments essentially focused around existing literature. The losses in various machine sections were thought to have already found from the electromagnetic model. The elemental model can then be utilized to carry out simulations regarding cyclic loading as well as transient activities. The thermal model examined here is partitioned into different sectors, thereby empowering analysis of this machine. The model under investigation has been acknowledged by utilizing a COMSOL Multi-physics simulator and Matlab ® programming software. The heat exchange coefficients are characterized from information gathered from the comparative kind of machines. The developed framework also considers sensitivity analysis in terms of parametric effects on the behavior of the machine thermally. The developed model needs no substantial computing and can simply be run on a personal computer. The model can later be modified and connected to diverse machine developments. Structural topology optimization approach is adopted to find the optimal geometry. As a basic study, two optimization techniques i.e., genetic and simulated annealing algorithms have been adopted with the former based on the process of natural selection and the latter on the process of annealing (heating and cooling of metals). The design goal is to minimize the total dissipated losses to improve the overall efficiency and hence to achieve optimal design results.
Description
Supervisor
Arkkio, Antero
Thesis advisor
Alarcon, Vicente Climente
Shah, Sahas Bikram
Keywords
flux switching machine, FEM, thermal resistance network, optimization
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