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Modeling and Optimization Algorithm for SiC-based Three-phase Motor Drive System

Date Issued
August 1, 2020
Author(s)
Ren, Ren  
Advisor(s)
Fred Wang
Additional Advisor(s)
Leon Tolbert
Daniel Costinett
Zheyu Zhang
Permanent URI
https://trace.tennessee.edu/handle/20.500.14382/28181
Abstract

More electric aircraft (MEA) and electrified aircraft propulsion (EAP) becomes the important topics in the area of transportation electrifications, expecting remarkable environmental and economic benefits. However, they bring the urgent challenges for the power electronics design since the new power architecture in the electrified aircraft requires many benchmark designs and comparisons. Also, a large number of power electronics converter designs with different specifications and system-level configurations need to be conducted in MEA and EAP, which demands huge design efforts and costs. Moreover, the long debugging and testing process increases the time to market because of gaps between the paper design and implementation.


To address these issues, this dissertation covers the modeling and optimization algorithms for SiC-based three-phase motor drive systems in aviation applications. The improved models can help reduce the gaps between the paper design and implementation, and the implemented optimization algorithms can reduce the required execution time of the design program.

The models related to magnetic core based inductors, geometry layouts, switching behaviors, device loss, and cooling design have been explored and improved, and several modeling techniques like analytical, numerical, and curve-fitting methods are applied. With the developed models, more physics characteristics of power electronics components are incorporated, and the design accuracy can be improved.

To improve the design efficiency and to reduce the design time, optimization schemes for the filter design, device selection combined with cooling design, and system-level optimization are studied and implemented. For filter design, two optimization schemes including Ap based weight prediction and particle swarm optimization are adopted to reduce searching efforts. For device selection and related cooling design, a design iteration considering practical layouts and switching speed is proposed. For system-level optimization, the design algorithm enables the evaluation of different topologies, modulation schemes, switching frequencies, filter configurations, cooling methods, and paralleled converter structure. To reduce the execution time of system-level optimization, a switching function based simulation and waveform synthesis method are adopted.

Furthermore, combined with the concept of design automation, software integrated with the developed models, optimization algorithms, and simulations is developed to enable visualization of the design configurations, database management, and design results.

Subjects

power electronics

converter design

motor drive

optimization

modeling

Disciplines
Electrical and Electronics
Power and Energy
Degree
Doctor of Philosophy
Major
Electrical Engineering
Embargo Date
August 15, 2021
File(s)
Thumbnail Image
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Dissertation_Ren_Ren_3.0.docx

Size

28.76 MB

Format

Microsoft Word XML

Checksum (MD5)

616b606df10b9128a4c41b48ec033541

Thumbnail Image
Name

Dissertation_Ren_Ren_final_v2.pdf

Size

8.94 MB

Format

Adobe PDF

Checksum (MD5)

c5f49a4cec908f7a3bc843cc3df2910c

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