Engineering Commons^™

Development Of A Versatile Switching Mode Inverter Laboratory Module, Zachariah Lee Mustar

Master's Theses

DC-AC converters, or inverters, are complex devices that play an essential role in photovoltaic, energy storage, and microgrid systems. Therefore, they constitute a class of power electronics that any power-focused electrical engineering student should be familiar with. This thesis presents the development and testing of a single device that power electronics students will use in a laboratory setting to experiment with each of the four different switching techniques employed in inverters: a simple square wave (SSWI), modified square wave (MSWI), bipolar PWM, and unipolar PWM. The module was built with a physically modifiable control stage and a power stage constituting …

Compact, Low-Power Underwater Acoustic Modem Characterization And Sensing Network Node Implementation, Lucas W. Lucia

Master's Theses

There is a growing market for compact, power-efficient underwater communication technology. Due to the limited propagation of electromagnetic waves through water, modulated acoustic waves have emerged as an effective means of wireless communication underwater. In decades past, many acoustic modems had been developed primarily for defense customers in larger systems functioning at high power. In recent years, smaller, relatively inexpensive acoustic modems have become available on the market—but data on their performance in a real-world environment is scarce. Companies such as OWL Integrations are interested in employing such acoustic modems as part of sensing networks across multiple mediums. For such …

Analog Hardware Implementation Of A Linearly Constrained Quadratic Program Real-Time Solver, Claire E. Tylutki, Claire Tylutki

Master's Theses

This thesis presents the design, implementation, and analysis of a hardware system for solving Linearly Constrained Quadratic Programs (LCQPs) in real time. The architecture follows a generalized feedback structure composed of three key elements: gradient descent on the quadratic cost function, saturation-based nonlinearity to enforce inequality constraints, and an integral controller with an anti-windup mechanism to regulate dynamic behavior and determine steady-state error. This majority analog system converges with equilibria that satisfy the Karush-Kuhn-Tucker (KKT) optimality conditions. Using a representative LCQP, this work presents simulation of the circuit in PLECS and LT Spice to confirm the feasibility of the novel …

Distributed Formation Control Of Nonholonomic Mobile Robots: Safety-Critical Leader-Follower Approach With Obstacle Avoidance And Dynamic Reconfiguration, Kelvin C. Villago

Master's Theses

Networked control systems for multi-agent robotics have emerged as a critical paradigm for executing complex coordinated tasks in diverse environments. While formation control serves as the backbone of such systems, real-world deployment introduces significant challenges including communication constraints, environmental obstacles, and the need for adaptive reconfiguration. This research addresses these challenges by developing a novel unified framework that seamlessly integrates obstacle avoidance algorithms with dynamic formation reconfiguration capabilities, specifically designed for communication-limited networked control architectures. The proposed framework represents a significant advancement over existing approaches by simultaneously handling both static and dynamic obstacles while maintaining system cohesion under communication constraints. …

Ev Microgrid Inspired Open-Source Power Inverter, Bryan A. Carrillo Martinez

Master's Theses

The development of open-source power electronics platforms plays an instrumental role in accelerating microgrid deployment, electric vehicle (EV) integration, and educational access to embedded power electronic converters. This thesis presents the design, implementation, and validation of the Atinverter V2, an open-source DC to AC inverter intended for low power EV microgrid applications and educational settings. The Atinverter V2 integrates various hardware and software subsystems centered around the ATMEGA328P microcontroller, enabling PWM-based sinusoidal power inversion, DC/AC voltage and current sensing, and embedded control features. Software development leverages a C++ object-oriented library and multiple Arduino-based modules to facilitate modular and scalable operation. …

Leveraging Machine-Learning Algorithms In Two Car Crash Detection Systems On A Custom Dataset, Addison Jacob Sandvik

Master's Theses

Traffic accidents pose a significant threat to public safety, causing millions of deaths and injuries worldwide each year. While efforts to reduce accidents have seen limited progress in recent years, improving emergency response times through automated detection systems is a promising avenue for saving lives. This thesis describes the development of machine learning-based traffic accident detection systems, exploring both video classification and image detection models. The models are trained on a new dataset deemed the Cal Poly Traffic Accident Dataset, an extension of the existing Car Accident Detection and Prediction (CADP) dataset with a precise collision annotations. Two systems were …

Nonlinear Integral Control Schemes For A Cadence-Heartrate Process: A Matlab Exploration, Alexander G. Elliott

Master's Theses

Keeping one’s heart-rate within a specific range during a cardiovascular workout can be difficult due to many factors including variations in the exercise environment and changes in energy level. One’s heart-rate can be controlled by tuning the intensity level of the activity over time. This study focuses on the relationship between a runner’s cadence and their heart-rate and explores ways to control the heart-rate by adjusting the cadence. Previous work in this area modeled the cadence-heartrate plant as a first-order linear system, but this has been shown to be insufficient. This work improves upon previous research in this area by …

Study On The Application Of Smart Electric Meters For Secondary Voltage Protection, Jayaditya Sisodia

Master's Theses

The purpose of our research is to utilize PG&E’s Smart Meters installed across California to protect the Secondary Voltage delivered to the meter. This means detecting electrical faults between the utility’s distribution transformer and the installed Smart Meter. Our goal is to propose and implement various solutions through additional devices and protocols to detect and prevent these faults, communicate them with the meter, and forward fault information to the utility. A device will be designed to be installed on the transformer, detect faults, shut off power transmission, and communicate to the meter via fiber optic cable. Research will then be …

Open Source Asic Design Curriculum, Francisco Wilken

Master's Theses

The ever-growing importance of Application-Specific Integrated Circuits (ASICs) in a high-compute world necessitates that college graduates entering the workforce are well prepared to design them. This thesis details the design of novel ASIC curriculum, using open source tools to teach at the undergraduate level. By moving to a higher level of abstraction than classical transistor-focused coursework, chip design material can be made accessible earlier in an undergraduate degree. Additionally, open source tools provide a powerful, free, and portable platform for students to create their own designs, solving assignments focused on industry readiness. Finally, this thesis studies the results and challenges …

Remote Monitoring And Control Of Protection Relays Via Programmable Logic Controller, Rio Mcgown-Kauffman

Master's Theses

The purpose of this study is to explore the ability of a programmable logic controller (PLC) to wirelessly monitor and control power protection relays. The technologies surrounding power protection and industrial automation are ever evolving and have developed significantly in recent history. Industrial power applications call for consistent condition monitoring and status updates for various high-importance components. The high-importance components have power protection schemes that are managed by digital relays to trip circuit breakers in fault or unsafe operating conditions. The smart relays have a wide range of capabilities, including communications. Cal Poly assembled a collection of relays from Schweitzer …

Modeling Battery Energy Storage Systems To Study The Effects Of Battery Chemistry And Operation On Power Quality, Lin E. Knudsen

Master's Theses

This thesis studies the impacts of battery chemistry (specifically lithium-iron phosphate, sodium-ion, and solid-state), AC voltage, battery size, charging mode, state of charge (SOC), active power draw, and power factor on the power quality of a Battery Energy Storage System (BESS). For harmonic evaluation, the metrics provided by the IEEE Standard 519 are used as a guideline to quantify voltage and current harmonics. A comprehensive MATLAB Simulink using Simscape Electrical is used to develop and simulate the models for the battery, DC-DC converter, AC-DC converter, and the grid. A total of 57 simulation cases varying the BESS factors are performed, …

Modeling And Efficiency Analysis Of Hybrid Ac/Dc And Conventional Ac House Electrical Systems For Net-Zero Energy Homes, Tyler Bury

Master's Theses

This thesis presents the design, simulation, and comparative efficiency analysis of hybrid AC/DC residential homes versus conventional AC homes for Net Zero Energy Homes (NZEH). Motivated by the increasing prevalence of DC-native technologies such as solar photovoltaics, battery storage, and DC-powered electronics, this work evaluates whether hybrid AC/DC distribution can offer measurable efficiency benefits over traditional systems. Twelve detailed house models were developed—six employing a hybrid AC/DC architecture and six based on conventional AC systems, each supplying a combination of AC and DC residential loads. Simulations were conducted using MATLAB/Simulink to model steady-state efficiency under various loading conditions. Grid configurations …

Range-Dependent Meso-Scale Geoacoustic Seabed Quantification, Tim Sonnemann, Jan Dettmer, Charles W. Holland, Stan E. Dosso

Electrical and Computer Engineering Faculty Publications and Presentations

This study presents a probabilistic one-step two-dimensional (2D) inversion method of spherical-wave reflection coefficient data to estimate the range-dependent structure and geoacoustic parameters along a track. The approach of inverting such datasets independently as one-dimensional (1D) layered models and merging them to a 2D section is feasible but computationally expensive. This study demonstrates a more parsimonious 2D parametrization for active source data recorded on a towed hydrophone array. The comparison of data variance reduction for 1D- and 2D-based results clearly favors the 2D parametrization described here.

Hybrid Computing For Real-Time Model Predictive Control Of A Buck Converter, Grace Paladichuk

Master's Theses

Advancements in power electronics require high switching frequencies which the digital control routines of the systems cannot keep up with. Analog computing is added to digital control systems to prevent bottlenecks and allow real-time implementation. This paper proposes a hybrid computing model predictive control system for a buck converter. The control system implements the gradient dynamics of the optimization function using digital computing, and the gradient dynamics for the penalty function and integrator using analog computing. For the full simulations of the entire system, the PLECS RT Box is used to simulate the controller in real time with a 1 …

A Parallel Fuzzy Logic Framework For Surgical Skill Evaluation Via Instance Segmentation And Deepsort Tracking, Mohsen M. Mohaidat

Dissertations

Manual evaluation of suturing skills during laparoscopic training is often subjective and labor-intensive, resulting in the lack of scalable and consistent feedback for trainees. This study proposes an automated framework that not only significantly reduces the need for in-person assessment by experts but also ensures scalability, thereby addressing the objectivity and cost-effectiveness limitations. While low-cost laparoscopic box trainers have become increasingly popular for residency training, performance assessment still depends on expert supervision. The proposed system aims to alleviate these limitations.

This study introduces a novel automated framework incorporating an optimized DeepSORT algorithm for classifying, localizing, and tracking surgical tools using …

Robust Adaptive Fractional-Order Pid Controller Design For High-Power Dc-Dc Dual Active Bridge Converter Enhanced Using Multi-Agent Deep Deterministic Policy Gradient Algorithm For Electric Vehicles, Seyyed Morteza Ghamari, Daryoush Habibi, Asma Aziz

Research outputs 2022 to 2026

The Dual Active Bridge converter (DABC), known for its bidirectional power transfer capability and high efficiency, plays a crucial role in various applications, particularly in electric vehicles (EVs), where it facilitates energy storage, battery charging, and grid integration. The Dual Active Bridge Converter (DABC), when paired with a high-performance CLLC filter, is well-regarded for its ability to transfer power bidirectionally with high efficiency, making it valuable across a range of energy applications. While these features make the DABC highly efficient, they also complicate controller design due to nonlinear behavior, fast switching, and sensitivity to component variations. We have used a …

Developing Machine Learning Models And Graphene-Based Flexible Humidity And Temperature Sensors For Machine-Learning-Assisted Sensing, Seth Hajian

Dissertations

Flexible sensor technology has recently gained tremendous momentum in both academic research and industrial applications, transitioning from conceptual frameworks to practical implementations across diverse fields. This remarkable advancement can be attributed to several converging factors, including the maturation of nanomaterial science, the advancements of machine learning algorithms, and the critical demand for intelligent sensing solutions in healthcare, environmental monitoring, and industrial automation. The growing emphasis on personalized medicine and real-time health monitoring, accelerated by global health challenges, has further highlighted the necessity for accurate, cost-effective, and adaptable sensing platforms. This dissertation presents the fulfillment of three interconnected research projects focused …

Load Balancing In Mobile Networks Using Deep Reinforcement Learning And Traffic Prediction, Shorouk Raafat Mokhtar Abouamasha

Theses and Dissertations

Wireless communication networks are advancing at a rapid pace, driven by various challenges and ambitious goals. This rapid growth is driven by a range of applications, including technologies like the Internet of Things (IoT), as well as innovations in smart cities, autonomous vehicles, and more. Different applications demand specific performance criteria such as high data throughput, low latency, robust reliability, and efficient energy usage. In this thesis, we investigate two enhancements that can be adopted in wireless networks to tackle the challenges of resource optimization and network management. The motivation behind this is the fact that future networks will face …

Hunting, Feiyang Zhuang

Masters Theses

This writing is about fragility and revelation of technological systems. It considers how brokenness, delay, and opacity are not flaws but openings—opportunities to reimagine our relationship to technology as something grounded, sensory, and continuous with the natural and material world.

Colloidal Quantum Dots: A Path Toward Making Mid-Wave Infrared Sensing A Ubiquitous Technology, Mohammad Mostafa Al Mahfuz

Dissertations

Reducing the size, weight, power consumption, and cost (SWaP-C) of infrared detectors could make infrared sensing more widely accessible. In the critical mid-wavelength infrared (MWIR) spectral range of 3-5 gm, commercially available detectors are limited by the high costs associated with epitaxial growth and hybridization, as well as the need for cryogenic cooling. These factors restrict their use to defense and space applications.

Colloidal quantum dots present a promising material for overcoming these challenges, with wafer-scale monolithic integration and Auger suppression being the key material capabilities to minimize the sensor's SWaP-C. Infrared sensors based on colloidal quantum dots have been …

Model-Based Reinforcement Learning And Deep Learning For Power Converter Circuit Design Automation, Shaoze Fan

Dissertations

This dissertation presents a comprehensive automated framework for power converter design, leveraging reinforcement learning (RL) and graph-transformer networks (GTN) to address critical inefficiencies in traditional manual topology optimization. Motivated by the combinatorial increase of circuit design spaces and the computational cost of iterative simulations, this work develops a robust framework for generating energy-efficient topologies requiring rapid and reliable circuit design.

The framework integrates three key components: (1) an upper-confidence-bound-tree-based (UCT-based) RL model for circuit topology space exploration, (2) parallelized UCT algorithms to accelerate exploration processes, (3) a Graph-Transformer-based Network enabling fast circuit performance evaluation. Experimental validation demonstrates the whole framework …

The Interplay Of Accommodation And Oculomotor Vergence Within Young Adults With Binocularly Normal Vision And Typically-Occurring Convergence Insufficiency, Sebastian Fine

Dissertations

Concerted binocular coordination evoking oculomotor and refractive responses to visual stimuli are essential to daily function. Oculomotor dysfunctions can inhibit binocular responses to visually-near stimuli and have high comorbidities to accommodative dysfunctions. Three visual cues for inward (convergent) and outward (divergent) oculomotor movements, when presented concertedly create natural-viewing conditions: disparity- the binocular difference in light cast onto the fovea due to differing ocular perspectives, blur- the acuity of a visual target which stimulates accommodation, and proximal- the perceived distance of a visual stimuli based on size.

This study aims to quantitatively investigate oculomotor vergence and accommodation performances between individuals with …

Next-Generation Extended Reality Systems With Real-Time Edge Artificial Intelligence And Mobile Computing, Pedro H. Regalado

Dissertations

Mixed reality (MR) and augmented reality (AR) systems are reshaping digital experiences by seamlessly integrating physical and virtual environments. This dissertation presents a comprehensive framework for next-generation immersive systems, combining advances in real-time data processing, multi-user synchronization, and secure communication. The core contributions are structured around three interconnected systems: MediVerse, TeleAvatar, and MultiAvatarLink, each addressing critical challenges in mobile MR.

MediVerse is a secure and scalable framework for real-time health and performance monitoring, integrating intelligent IoT sensors, wearable technologies, and MR interfaces. It supports multi-camera fusion, adaptive compression, and real-time three-dimensional (3D) point cloud generation, enhancing data accuracy and responsiveness …

A System Of Systems (Sos) Meta-Architecture Approach To Design Digital Platform-Based Domestic Worker Distribution System, Prithbey Raj Dey, Cihan H. Dagli, David Lee Enke

Engineering Management and Systems Engineering Faculty Research & Creative Works

In this research, a System of Systems (SoS) meta-architecture is conceptualized to design a digital platform-based system framework for the distribution of domestic workers to boost the crowd-sourced economy. While an Object Process Methodology (OPM) is used to articulate the relationships between the objects and functions, a Design Structure Matrix (DSM) has been applied to address the interactions between individual components to categorize them into subsystems to create the SoS architecture. This SoS architecture incorporates several Key Performance Attributes (KPAs) and Key Performance Parameters (KPPs) to systematically evaluate the meta-architectures. The Analytical Hierarchical Process (AHP), Pugh’s Evaluation Matrix, and Technique …

Gamified Gait Rehabilitation Via Real-Time Biofeedback And Adaptive Hip-Exoskeleton Control, Mariya Huzaifa Tohfafarosh

Theses

Gait impairments arise from systemic diseases, age-related degeneration, musculoskeletal dysfunctions, or neurological conditions. While traditional rehabilitation can be effective, they often face challenges such as high costs, inaccessibility, and low patient engagement. To address these challenges, my work introduces a virtual reality-based rehabilitation (VRBR) system, integrating real-time motion and electromyographic (EMG) muscle activation feedback with a gamified virtual environment for enhanced adaptability and engagement. The system includes a custom-designed hip-exoskeleton that provides adaptive spring-like assistance or resistance, supporting both mobility-impaired users and strength training. Assistance levels can be tuned to match the user's progress. Additionally, a custom pressure insole was …

Price-Signal-Based Control Strategy For Heat Pump Water Heaters In Demand Response Applications, Othman A. Murad

Dissertations and Theses

This work presents a price-signal-based control strategy for residential Heat Pump Water Heaters (HPWHs) aimed at reducing electricity costs and shifting load away from high-price periods. By integrating the California Load Flexibility Research and Development Hub (CalFlexHub) prototype price signals, the Consumer Technology Association (CTA-2045-B) communication protocol, and the Object-oriented, Controllable, High-resolution Residential Energy (OCHRE) simulation framework, a rule-based controller was developed to align HPWH operation with dynamic electricity pricing while maintaining hot water availability.

The control strategy was evaluated through two case studies: one using a fixed water draw profile under varying levels of price signal foresight, and another …

Influencing Factors Of Angle-Of-Arrival Estimator Based On Deep Learning, Guohao Pang

Dissertations and Theses

Deep learning (DL)-based angle-of-arrival (AoA) estimation offers significant advantages over traditional signal processing methods, especially in complex and high-noise environments. However, situational complexity and differences in hardware can significantly impact the estimator's performance. It is therefore of interest to investigate the relationship between the performance of deep learning models and the variation of physical parameters such as the number of signal sources, the number of receiving antennas, and the signal-to-noise ratio (SNR). In this study, we investigate the impact of these variations on deep learning-based AoA estimation by systematically analyzing how the variations in the characteristics of the received signal …

Preparation And Modification Of Mxene Composites For Application In Electrochemical Energy Storage, Zhang-Hai You, Ding-Ze Lu, Kiran Kumar Kondamareddy, Wen-Ju Gu, Peng-Fei Cheng, Jing-Xuan Yang, Rui Zheng, Hong-Mei Wang

Journal of Electrochemistry

With the acceleration of advanced industrialization and urbanization, the environment is deteriorating rapidly, and non-renewable energy resources are depleted. The gradual advent of potential clean energy storage technologies is particularly urgent. Electrochemical energy storage technologies have been widely used in multiple fields, especially supercapacitors and rechargeable batteries, as vital elements of storing renewable energy. In recent years, two-dimensional material MXene has shown great potential in energy and multiple application fields thanks to its excellent electrical properties, large specific surface area, and tunability. Based on the layered materials of MXene, researchers have successfully achieved the dual functions of energy storage and …

Theoretical Insights Into The Atomic And Electronic Structures Of Polyperyleneimide: On The Origin Of Photocatalytic Oxygen Evolution Activity, Yi-Qing Wang, Zhi Lin, Ming-Tao Li, Shao-Hua Shen

Journal of Electrochemistry

Polymeric perylene diimide (PDI) has been evidenced as a good candidate for photocatalytic water oxidation, yet the origin of the photocatalytic oxygen evolution activity remains unclear and needs further exploration. Herein, with crystal and atomic structures of the self-assembled PDI revealed from the X-ray diffraction pattern, the electronic structure is theoretically illustrated by the first-principles density functional theory calculations, suggesting the suitable band structure and the direct electronic transition for efficient photocatalytic oxygen evolution over PDI. It is confirmed that the carbonyl O atoms on the conjugation structure serve as the active sites for oxygen evolution reaction by the crystal …

Three-Dimensional Melamine Carbon Sponge/Nai As Cathode Materials For Sodium-Ion Batteries, Qian-Ying Huang, Yue Liu, Zi-Xin Lin, Shu-Yi Zheng, Ting-Ting Mei, Yu-Ting Tang, Ying-He Zhang, Jun Liu

Journal of Electrochemistry

The sodium-iodine (Na-I) battery exhibits significant potential as an alternative energy storage device to the lithium-ion battery. However, its development is hindered by inadequate electrical and thermal stability, as well as the dissolution and shuttling of polyiodide. In this study, we report a preparation method for melamine carbon sponge (MC) via carbonizing a commercially available kitchen sponge. It was revealed that the as-prepared MC, composed of unique self-growing carbon nanotubes, could provide both physical and chemical adsorption capabilities for intermediate polyiodides to improve the electrochemical performance of NaI. Consequently, the NaI/MC electrode effectively minimized polyiodide dissolution and reduced the electrochemical …