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http://hdl.handle.net/11375/24118
Title: | THERMAL MANAGEMENT OF A DUAL ACTIVE BRIDGE CONVERTER FOR SMART HOME APPLICATIONS: DESIGN OF AN OPTIMAL INTEGRATED FORCED AIR HEAT-PIPE EMBEDDED HEATSINK COOLING SYSTEM |
Authors: | Alizadeh, Maryam |
Advisor: | Emadi, Ali Bauman, Jennifer |
Department: | Mechanical Engineering |
Publication Date: | 2019 |
Abstract: | Due to significant progress in power density and miniaturization in the field of power electronics, point of converter packaging is becoming an important issue. Thermal management techniques should be implemented in design of a converter cooling system for ensuring robust functionality during the device operation. The thermal deign of a power converter under specific power loss is mainly determined by the maximum allowable temperature of the power switches. During operation, these switches experience rapid power transitions and therefore reliable thermal management must be used to prevent device failures. The objective of this research is to design a reliable, efficient, small cooling system for a power converter using in smart home applications. Considering the limitations in the converter’s size an integrated forced air heat pipe heat sink cooling system is proposed. A thermal model for the proposed cooling system is developed. In addition, the accuracy of the model in combination with multiple heat sources is verified with simulation and validated experimentally by building a setup for the proposed cooling system with multiple heat sources. Finally, the validated model is used in optimization algorithms for finding the optimal design of the cooling system. In this thesis the geometrical configurations of the heat sink along with the fan selection options is optimized. Two objective functions, volume and efficiency of the cooling system, have been selected as the design space. The optimization problem has been limited to six degrees of freedom represented by number of fins, fin height, fin thickness, heat sink width, base plate thickness and fan selection options. The optimization is carried out using two different algorithms, Teaching Learning Based Optimization (TLBO) and Particle Swarm Optimization (PSO). Comparisons of the results of these two algorithms presented in this study show that TLBO algorithm requires less evaluations to find the optimal design compare to PSO. It has also been found that TLBO is more robust since it does not have any algorithm-controlling parameters. The improvement from robustness of the TLBO algorithm comes at the reliable results in terms of finding the optimum design more accurately. |
URI: | http://hdl.handle.net/11375/24118 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Alizadeh_Maryam_Feb2019_degree.pdf | Design of an optimal cooling system for power electronics applications | 3.71 MB | Adobe PDF | View/Open |
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