Date of Award

Fall 11-21-2025

Document Type

Dissertation

Degree Name

Ph.D. in Computer Science and Engineering

Organizational Unit

Daniel Felix Ritchie School of Engineering and Computer Science, Computer Science

First Advisor

Mohammad Matin

Second Advisor

Yun-Bo Yi

Third Advisor

David Gao

Fourth Advisor

Sangho Bok

Copyright Statement / License for Reuse

All Rights Reserved
All Rights Reserved.

Keywords

Control strategies, Electric vehicle, Half-bridge DC-DC converter, Particle swarm optimization, SiC and GaN devices, Wide bandgap semiconductors

Abstract

The performance of DC-DC power converters is a cornerstone of modern electric vehicle (EV) powertrains, directly governing overall system efficiency, size, cost, and reliability. This dissertation presents a comprehensive performance analysis and optimization of DC-DC converter topologies to determine the most suitable design for high voltage EV applications. The evaluation rigorously compares efficiency, power losses, and physical size under a range of harsh operating conditions. A primary objective is to leverage Wide Bandgap (WBG) semiconductors, specifically Silicon Carbide (SiC), to push the performance boundaries of power conversion. While SiC devices are known for their superior material properties, a clear understanding of the trade-offs between switching dynamics and converter efficiency especially for cascode configurations remains an area requiring deeper research. This work specifically investigates the effect of 650V and 1200V cascode SiC-JFET switches implemented in a half bridge DC-DC buck converter. The switching characteristics and energy losses are experimentally measured using a Double Pulse Test (DPT) across various voltage and current levels, operating temperatures, and gate resistances. The findings conclusively demonstrate that the integration of cascode SiC-JFETs leads to enhanced switching performance, substantially lower switching loss, and higher overall energy efficiency. Furthermore, to mitigate the challenges of source intermittency and nonlinear dynamics and to achieve precise output voltage regulation, a sophisticated control strategy is indispensable. This research implements and compares several advanced control techniques for the proposed converter. The Particle Swarm Optimization (PSO) algorithm is employed to optimize the key parameters of each controller, effectively reducing chattering and improving transient response. The results unequivocally show that the Fuzzy Adaptive Sliding Mode Control (FASMC) method surpasses all other tested controllers, offering superior dynamic response, negligible chattering, and peak operational efficiency. A practical half bridge DC-DC buck converter was designed for a high-step-down voltage conversion from 600V to 80V. The system model was simulated in Simulink at high switching frequencies ranging from 20kHz to 100kHz. The simulation results corroborate the theoretical and experimental findings, demonstrating a marked improvement in total system efficiency and solidifying the viability and advantages of the proposed converter for electric vehicle applications.

Copyright Date

11-2025

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Rights Holder

Salah Ahmed Abdullah Eltief

Provenance

Received from ProQuest

File Format

application/pdf

Language

English (eng)

Extent

180 pgs

File Size

14.5 MB

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