Electrical and Electronics Commons^™

High Frequency Dc-Dc Converter Design Optimization, Modeling And Control Based-Wbg Technology., Salah Ahmed Abdullah Eltief

Electronic Theses and Dissertations

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 …

Experience With The Stem For Success Internship, Ujwal S. Thirunagari

STEM Month

In this article, I discuss my experience working with the STEM for Success team. I detail some of the challenges I faced in completing the CRT and LED sections, how I addressed these challenges, and the widely applicable skills that I learned.

Television Guidebook, Ujwal S. Thirunagari

STEM Month

In this television guidebook, we work to clearly explain television technology by including detailed illustrations and introducing fundamental concepts. This guidebook first explains the Cathode Ray Tube by laying out the basics of circuits, thermionic emission, the electron beam gun, and the deflection yoke. Then, the guidebook tackles the modernly adopted LED panel technology used in most phones and computers by explaining the fundamentals of light and liquid crystal. In future iterations of the guidebook, we hope to delve into more detail on color CRTs, thin film transistors, OLED panels, and Micro-LED technology.

Abdominal Ultrasound Image Dataset For Organ Classification And Disease Detection, Sifat Zina Karim

Research Data

This is a dataset of Ultrasound (US) images of abdominal organs. US imaging is widely accessible and a very common diagnostic tool, as it is non-invasive and does not involve radiation risk. This dataset was curated solely for research in deep learning, with potential applications in supervised, semi-supervised, and unsupervised learning to support disease detection in resource-constrained settings.

The dataset comprises 5,468 unique images of different abdominal organs, namely: Abdominal Aorta (0), Gallbladder (1), Hepatic Vein (2), Kidneys (3), Liver (4), Ovaries (5), Pancreas (6), Portal Vein (7), Spleen (8), and the Urinary System (9), which includes the Urinary Bladder, …

A Light-Dependent Resistor Based Embedded Image Acquisition System For Use In Low-Resolution Application-Specific Data Processing, Connor Best

Journal of Undergraduate Research at Minnesota State University, Mankato

This paper proposes an efficient hardware-based approach to image acquisition & processing to replace complex camera systems in simple industrial & commercial applications.

Environment Mapping And Gps-Based Trailer Parking Using Low-Cost Peripheral Sensors And Post-Processing Algorithms, Connor Best

Journal of Undergraduate Research at Minnesota State University, Mankato

This paper explores the merit of software data optimization through two practical examples: environment mapping & GPS navigation.

Performance Analysis Of Power System Dynamic Stability Of The Nigerian 330kv Transmission Network, Charles Evuarherhe Ikeyin, Benjamin Olabisi Akinloye

Al-Bahir

Nigeria's power sector faces persistent challenges, including dynamic instability, poor voltage regulation, and frequent grid collapses, primarily driven by reactive power deficits and transmission distances exceeding 200 km in northern regions. To bridge critical research gaps, this study employs a rigorous, multi-method approach through comprehensive EMTP-RV (Electromagnetic Transients Program) analysis of Nigeria’s 330kV 52-bus grid, PV curve-based vulnerability indexing to identify cascade-critical buses, and a novel Cost-benefit Pareto framework for optimal capacitor placement. Methodology was validated against IEEE (Institute of Electrical and Electronics Engineers) 14-bus benchmarks. Validated against IEEE 14-bus benchmarks, simulations revealed severe voltage instability in northern …

Authenticating Electronic Devices Via Multi Tone Analysis, Carl Bohman Jr., Aaron Jennings, Christian Eakins, Mark B. Skouson, Richard Ott, Jamin Mccue

AFIT Patents

Methods and systems for authenticating electronic devices via multi tone analysis. A method for authenticating a device under test (DUT) of a type of DUT includes imparting voltage tones to the DUT. The voltage tones are proximate a frequency of interest that is associated with the type of DUT. Using a measurement response of the DUT to the voltage tones, an electronic signature of the DUT is determined. The DUT is determined to be authentic when the electronic signature of the DUT substantially matches an electronic signature of an authority DUT of the type of DUT.

Investigating The Harmonic Content Of A Pwm Inverter With Varying Modulation Index, Peter Makolo

Tanzania Journal of Engineering and Technology (TJET)

Photovoltaic energy is a clean and endless vital renewable energy. In order to generate electricity from solar energy an inverter is required to transform the direct current into alternating current. Also, with the emerging of new ultra-high voltage direct current transmission technology, the rectification and inverters play a great role. Most three-phase two-level inverters draw harmonics that cause heat dissipation, waveform distortions hence affect the electrical loads. Knowing that Total Harmonic Distortion content of voltage source inverter is important and must be within the allowable range. Several schemes are suggested to mitigate the distortion in order to produce as much …

Modeling An Energy Management System For Residential Hybrid Ac/Dc Power Networks, Theodor Buerchner, Giovanni Malone, Alex Maldonado

College of Engineering Summer Undergraduate Research Program

In pursuit of supporting the global efforts in reducing carbon footprint and reliance on fossil fuels, this project seeks to continue the development of a hybrid AC/DC house prototype at Cal Poly State University. To enhance the power flow to DC loads, a dedicated 48 V DC bus will be constructed to replace the impractical multiple DC buses in the previous system. This iteration will also add a key feature that enables users to monitor real-time AC and DC powers. Another new functionality will involve the provision of a mix of latching and non-latching relays to switch between sources, thus …

Experimental Study Of Energy Conversion Efficiency Improvement Of Photovoltaic (Pv) Module Using Hybrid Cooling System, Olufisayo O. Babalola, Olatunji W. Olademeji, Joseph B. Samson

Al-Bahir

The elevation of the photovoltaic module operating temperature resulting in diminution of its energy conversion efficiency is one of the key limitations to its application. A decrease of power delivered performance by 0.4-0.5% per 1 rise over its Standard Test Condition (STC) accounted for the overheating of the PV module. This study evaluates the energy conversion efficiency improvement of a PV module using hybrid cooling system. An hourly segmented hybrid cooling system made up of aluminum fins as passive cooling segment and helical structured copper tubules for water conduction as active cooling segment helps to improve the energy conversion efficiency …

An Event-Based Time-Incremented Snn Architecture Supporting Energy-Efficient Device Classification, David L. Weathers, Michael A. Temple, Brett J. Borghetti

Faculty Publications

Recent advances in Radio Frequency (RF)-based device classification have shown promise in enabling secure and efficient wireless communications. However, the energy efficiency and low-latency processing capabilities of neuromorphic computing have yet to be fully leveraged in this domain. This paper is a first step toward enabling an end-to-end neuromorphic system for RF device classification, specifically supporting development of a neuromorphic classifier that enforces temporal causality without requiring non-neuromorphic classifier pre-training. This Spiking Neural Network (SNN) classifier streamlines the development of an end-to-end neuromorphic device classification system, further expanding the energy efficiency gains of neuromorphic processing to the realm of RF …

Design And Performance Analysis Of A Frequency-Reconfigurable Rectangular Patch Antenna With Dual-Slot Defected Ground Structure For Gsm Band, Sara Abdelbaset, Ashraf Khalaf, Amr Hussien, Ahmed A. Kabeel

Journal of Engineering Research

In this paper, an innovative frequency-tunable rectangular patch antenna is presented, featuring interlaced circular and U-shaped narrow slots, combined with a rectangular-shaped defected ground structure (DGS). This design is specifically developed to produce radiation patterns similar to those of traditional dipole antennas. The integration of the rectangular DGS with three RF varactor diodes, along with two equivalent microstrip conductors, enables a tunable operating frequency band that ranges from 1.08 GHz to 1.7 GHz, achieving a total bandwidth of 0.62 GHz. The DC biasing network connected to the three RF varactor diodes is utilized to finely tune and adjust the resonance …

Exopg Maturation And Owl Interface, Duncan Michael Louden

Electrical Engineering

The maturation of the ExOPG buoy generator consists of an interface to facilitate remote data acquisition of an existing battery charge controller. This module telemeters battery controller data including voltage, temperature, and state of battery charge. The data is transmitted to a communication system and is able to be viewed by humans on a 24/7 basis for continuous operation and human usage. The module works seamlessly as an addition to the existing ExOPG generator, and it does not interfere with any existing and planned components of the generator. The module is highly efficient and draws minimal power from the existing …

Electrical Energy Consumption Forecasting Based On Conventional And Artificial Intelligence Methods: A Comparison, Haya H. Binsalim, Jana Kamal, Salma Badaam, Danah Milyani, Ghadah S. Alyami, Aziza I. Hussein

Effat Undergraduate Research Journal

Artificial Intelligence (AI)-based models have been widely applied for energy consumption forecasting over the past decades. The purpose of this paper is to review and compare the classical techniques and the emerging new AI-based techniques used for forecasting electrical energy consumption in buildings. The findings revealed that the Artificial Neural Network (ANN) model achieved the lowest Mean Absolute Percentage Error (MAPE) of 0.928%. AI-based techniques have many advantages over classical techniques, such as their ability to handle a large amount of data and provide accurate and fast results.

Fault Detection In Analog Vlsi Circuits Based On Artificial Intelligence

Effat Undergraduate Research Journal

In thepastdecade,artificialintelligence(AI)hasbeenonthe rise asatooltobeutilizedacrossallthefieldsavailableintheindustry. Specificallyinthemicroelectronicsfield,exploringthecurrentoptionsof VLSI faultdetectionandtheirtypesiscrucialforadvancementandis importantinidentifyingwhetherthereisroomforimprovementorthe optimumisalreadybeingdone.Therefore,thepurposeofthisresearch is tocompareandcontrastbetweenVLSIfaultdetectionindigitaland analog circuitsusingAI.Techniquestoimproveefficiencysuchastrou- bleshootinginsmallsegmentsratherthanthewholesystemandsome resolutions todrawbacksthataren’tdetectibletohumansliketimingare discussed andresolvedinthispaper.Moreover,somenon-idealitiesand risks likemarginalstabilitywereconsidered.Finally,presentelements that areusedintoday’sfaultdetectioncircuitslikeneuralcontrollers and theANNswerediscussedaswell.Currently,theANNsarethemost utilized toolforfaultdiagnosesanddetection;however,forthecontinu- ation ofthistechnology’sgrowth,developersneedtofindmoreefficient methodstomovepastit.

Assessing Cascaded Op-Amp And Pre-Current Amplifier Configurations In Transimpedance Amplifier Interfacing Circuits For Nano-Scale Current-Based Sensor Applications, Mohamed Mamdouh, Sameh O. Abdellatif

Electrical Engineering

This study provides a comprehensive analysis of two proposed configurations for current-to-voltage converters tailored for nano-scale current-based sensor applications, focusing on key performance metrics such as linearity, dynamic range, DC noise immunity, and power losses. The evaluation employed frequency-dependent analyses, including transient response, step response, input impedance, and frequency-dependent noise spectra, to compare a cascaded double output configuration with a pre-current amplifier design. The results indicate a trade-off between dynamic range and linearity, with the pre-current amplifier demonstrating a higher dynamic range but lower linearity compared to the cascaded configuration. Additionally, the current amplifier configuration exhibited advantages in power consumption …

Performance Analysis Of Pem Fuel Cells Via Puma Optimizer With The Aid Of Practical Verifications, Hossamm Ashraf, Sameh O. Abdellatif, Mahmoud M. Elkholy \, Attia A. El-Fergany

Electrical Engineering

This manuscript presents a novel application of the recently developed Puma Optimizer (PO) for identifying the unknown parameters in Mann’s model, which is widely used for characterizing the behavior of Polymer Electrolyte Membrane Fuel Cells (PEMFCs). The proposed PO-based methodology is rigorously evaluated using three test cases. One test case involves experimental I–V measurements under various operating conditions from a commercial PEMFC stack, the Horizon H-100 (100 W), which was assembled and tested in the laboratory. The other two cases are established benchmark PEMFC systems, the Ballard Mark V 5 kW and BCS 500 W units. Comprehensive statistical analyses over …

Accelerating Gnn Inference On Multi-Core Systems, Binglin Ji

McKelvey School of Engineering Graduate Student Theses & Dissertations

Graph Neural Networks (GNNs) are becoming increasingly popular, with their applications expanding across diverse domains. As the scale of graph data continues to grow, including larger numbers of nodes, edges, and higher embedding dimensions, standardized libraries such as DGL and PyG have been developed to facilitate GNN computation. However, with the rapid increase in the number of processor cores and the evolution of multi-core architectures, these libraries often show poor scalability and fail to execute GNN inference efficiently on the latest multi-core systems, particularly those with upwards of a hundred cores. To address this limitation, we present FGI, a Fast …

Resilient Control Framework For Ev Motor Drive System Subject To Cyber-Physical Security, Ali Arsalan

All Dissertations

The electric drive system (EDS) in electric vehicles (EVs) is one of the key safety-critical components. As IoT-enabled communication infrastructure for modern cyber-physical automotive systems continues to evolve, the importance of securing EDS against cyber threats along with physical faults, has become increasingly prominent. Among physical faults, power switches are particularly vulnerable and exhibit the highest susceptibility to open-circuit faults (OCFs). A compromised EDS, whether due to cyber threats or physical issues, can lead to excessive mechanical vibrations, increased thermal stress, fluctuations in electromagnetic torque, and elevated total harmonic distortion. These factors can substantially undermine traction control stability and jeopardize …

Owl Solar-Powered Link: Duck Radio Mesh For Autonomous Monitoring, Jaden Tran, Shane Williams

Electrical Engineering

The Solar Duck Sensor Node transforms a standard DuckLink into a fully self-sustaining environmental monitor. A compact solar panel / power bank module plugs into the power ports of both the DuckLink and the Raspberry Pi Zero 2 W, keeping them charged through day-night cycles. The Pi Zero 2 W will perform local processing of sensor data. Sensor output will come from the Raspberry Pi AI Camera and its object detection capabilities. This output will be distilled into metadata and advertised over BLE. The DuckLink captures these packets, encapsulates them into LoRa payloads, and forwards them across the ClusterDuck mesh …

Design And Validation Of A High-Frequency Multi-Output Dc-Dc Converter For Radar Power Applications, Tory Sutton

Graduate Theses and Dissertations

Modern radar systems and advanced electronics demand compact, efficient, and reliable power solutions capable of delivering multiple tightly regulated voltage rails under strict size, weight, power, and reliability (SWaP-R) constraints. This thesis presents the design, implementation, and validation of a high-frequency (460 kHz – 1 MHz), multi-output DC-DC converter for a mission?critical radar platform, addressing both integration and performance requirements. The first implementation, an isolated modular converter (IMC), utilizes isolated silicon?based DC-DC modules to deliver twelve isolated voltage outputs from a single input. This approach provided robust electrical isolation, simplified system integration, and minimized design risk, making it well-suited for …

Low Energy Ion Irradiation Effects In Electronic Devices And Materials, David C. Mccall

All Dissertations

The physics and engineering of ion-solid interactions are governed by the ion beam characteristics (flux, charge, energy) and target(s) in question. Here I present work on two projects related to the extraction of a high flux of low charge state Argon ions from a commercial plasma source and the irradiation of an engineered target, a transistor, with high charge state Argon ions.

An end-Hall ion source that produces a a high current plasma of ions and electrons in a rough vacuum environment is characterized. Using a Langmuir probe and multiple pressure measurements, the ion and electron content of the source …

Pseudo-Soft-Switching Switched-Capacitor Drive Circuits For Small-Scale Dielectric Actuators, Yanqiao Li

Dartmouth College Ph.D Dissertations

Applications including micro-robotics and haptics have motivated extensive exploration of dielectric actuators due to their high bandwidth and high efficiency at cm and mm scales. To maximize their benefits, dielectric actuators, including piezoelectric and electrostatic actuators, typically require high driving voltages, ranging from 100V to several kV. Generating such high driving voltages presents a challenge for drive circuits, particularly when powered by a small battery. Dielectric actuators are predominantly capacitive in most circumstances, necessitating the drive circuits to deliver and recover reactive energy for efficient operation. In some applications, such as micro-robotics, the drive circuits may need to have a …

Self-Poled P(Vdf-Trfe) Based Composites For Energy Harvesting And Wearable Sensor Applications, Lavanya Muthusamy

All Dissertations

The growing demand for flexible, low-power, and self-powered wearable electronic systems has accelerated research interest in polymer-based sensors and energy harvesting technologies. Among piezoelectric polymer materials, Poly(vinylidene fluoride-trifluoro ethylene) [P(VDF-TrFE)], over the years, has garnered significant attention due to its unique piezoelectric properties, high dielectric constant, mechanical flexibility, thermal stability, chemical resistance, biocompatibility and compatibility with scalable fabrication processes. Despite its advantages, conventional P(VDF-TrFE)-based devices often require external poling and face limitations in integration with low-cost, flexible substrates. To overcome these limitations, this research study explores the nanofiller approach, along with facile fabrication processes, and structural design strategies aimed at …

Line Outage Impact Factors: A New Approach To Line Outage Detection With Machine Learning, Daniel Flores

Open Access Theses & Dissertations

Electric power systems have become one of our most critical infrastructures as we've grown dependent on electricity for everyday tasks. Ensuring power systems provide reliable service is a priority that can be affected by disturbance events. A common event is transmission line outages, where a line in the system becomes disconnected due to varying forms of physical damage. If an outage isn't detected in time, other lines in the system may overload, causing cascading failures that leave many customers without power. Therefore, having a power system that can automatically detect outages is crucial for reliability, as it promotes real-time response …

Low-Level Memory Attacks On Edge Assisted Robotic Applications, William Arnold

Master of Engineering Theses

This thesis investigates how low-level memory faults can undermine edge-assisted robotic systems that rely on memory optimization. As robots are utilized in real world applications, the ability to operate safely and successfully in mission critical deployment becomes important. To help achieve these goals, developers are increasingly starting to place computation nodes at network edges to meet latency and reliability requirements. Edge nodes, however, are resource-constrained and resources conservation techniques such as Kernel Same-page Merging (KSM) are enabled to deduplicate identical pages across processes or virtual machines. This thesis shows that this optimization technique quietly widens the attack surface and can …

Optimal Distributed Energy Resource Control And Scheduling In A Microgrid Framework, Timothy M. Dodge

All Graduate Theses and Dissertations, Fall 2023 to Present

As we use more renewable energy, such as solar power, and add new devices, such as electric vehicle chargers and battery storage, to our buildings, the management of electricity becomes more complex. These local energy sources and devices can form small "microgrids" that need careful coordination to work efficiently with the main power grid. The system figures out the best times to use, store or charge different devices (such as batteries and EVs) to avoid costly, high electricity demand spikes and help stabilize the main power grid, especially when asked by the utility company. A major part of this work …

Algorithmic Optimization Of Filter Bank: Harnessing Rapid Convergence And Its Applications, Keerthana B Ms

Theses and Dissertations

A novel optimization framework is proposed for the design of both uniform and non-uniform filter banks, aimed at improving the accuracy and computational efficiency of biomedical signal classification tasks, with a particular emphasis on the detection of sleep disorders and Alzheimer’s disease.The proposed algorithm is grounded in multirate signal processing theory and aims to achieve Near Perfect Reconstruction (NPR) with minimal computational overhead. The process begins with the optimization of a uniform cosine-modulated filter bank (CMFB), achieved through iterative frequency-domain analysis and parameter tuning. This is followed by the derivation of a non-uniform filter bank via selective merging of bandpass …

Algorithmic Optimization Of Filter Bank: Harnessing Rapid Convergence And Its Applications, Keerthana B

Theses and Dissertations

A novel optimization framework is proposed for the design of both uniform and non-uniform filter banks, aimed at improving the accuracy and computational efficiency of biomedical signal classification tasks, with a particular emphasis on the detection of sleep disorders and Alzheimer’s disease. The proposed algorithm is grounded in multirate signal processing theory and aims to achieve Near Perfect Reconstruction (NPR) with minimal computational overhead. The process begins with the optimization of a uniform cosine-modulated filter bank (CMFB), achieved through iterative frequency-domain analysis and parameter tuning.

This is followed by the derivation of a non-uniform filter bank via selective merging of …