Electrical and Electronics Commons^™

Communication-Aware Energy Optimization For Electric Vehicles With Adaptive Cruise Control, Shahriar Shahram

Graduate Studies Theses and Dissertations 2026

This dissertation develops information-driven methods to reduce traction energy in battery electric vehicles during adaptive and cooperative cruise control. Physics-grounded energetics are embedded in a predictive controller that accounts for intermittent V2V preview, sensing noise, packet loss, and powertrain limits. To ensure deployability, the nonconvex traction–power map is replaced by locally convex surrogates so each step solves a small, strictly convex QP in real time (average ≈ 70 ms/step on a desktop CPU: 8 cores/16 threads, 4.2–5.0 GHz), leaving margin at typical sampling rates (Ts =0.05–0.10 s; N=15–25).

Across standardized drive cycles from NREL DriveCAT—including FTP–75 (light duty), NREL Class …

Optically-Pumped Semiconductor Optical Amplifiers, Dhruvkumar Desai

Graduate Studies Theses and Dissertations 2026

Semiconductor optical amplifiers (SOAs) offer a low-cost, compact solution for power amplification needs in an optical communication system compared with the dominant erbium-doped fiber amplifiers (EDFAs). They can also provide a wide gain bandwidth. However, conventional electrically-pumped SOAs suffer from larger noise figures, low saturation power, and polarization dependence, in comparison with EDFAs. We propose an optically-pumped SOA (OP-SOA) that will maintain the benefits of conventional SOAs while closing the gaps in other amplifier performance metrics. The underlying reasons for optical pumping are twofold. First, optical pumping allows higher carrier injection and thus "population inversion." Second, optical pumping decouples carrier …

Federated And Explainable Spiking Neural Networks For Fair And Privacy-Preserving Nail Disease Diagnostics, Ch Pavani Reddy, Krishnanaik Vankdoth

Mansoura Engineering Journal

Automated nail disease diagnostics provide a non-invasive pathway for identifying underlying systemic health conditions; however, conventional centralized deep learning approaches often raise concerns related to privacy, fairness, and interpretability. Although the original NeuroNail-SNN framework demonstrated an energy-efficient and edge-ready diagnostic solution, its broader clinical adoption remained limited by unresolved trust, transparency, and ethical considerations. In this study, we propose the Federated and Explainable NeuroNail-SNN, which extends the original spiking neural architecture by integrating federated learning (FL), explainable artificial intelligence (XAI), fairness evaluation, and uncertainty quantification within a unified framework. Federated learning enables decentralized model training across hospitals and mobile clinics …

Automation And Habitat Development For A Space Based Marine Life Environment, Logan Trimmer, Alexander Hang

Harrisburg University Other Works

This project was a cross-collaboration between the Environmental Sciences and Advanced Manufacturing and Robotics programs for the company Monolith Space.

The goal of this project was to design an autonomous system to be able to track qualities of water in an aquaculture system designed to be sent to space.

A Solar Pv System For Industrial Application- A Case Study Of A Cement Industry In Tanzania, Santos Kihwele

Tanzania Journal of Engineering and Technology (TJET)

This study presents an implementation of the largest behind-the-meter solar photovoltaic (PV) system for a cement industry in Tanzania. The project aims to supply energy for the industry’s own use, without any energy injection into the utility grid, for the purposes of cutting energy-related expenditure and reducing reliance on the utility grid. The project also aims to contribute to the efforts towards the application of renewable and alternative energy sources as a means to reducing carbon footprints, towards achieving the net-zero CO₂ emission goal. A comprehensive site assessment was conducted, analyzing factors such as location, land availability, climate data, …

Wind Tunnel Instrumentation And Testing, Nicholas Marek, Abraham Mezera, Laura Jin, Hayden Smith, Curtis Cook

Student Scholar Symposium

The Raymond B. Jones College of Engineering was contacted by an automotive engineering firm seeking to use the college’s wind tunnel for gathering data on the aerodynamic performance of a proprietary prototype automotive door. Specifically, the client requested the quantification of the drag coefficient of the model at extreme wind speeds. The drag coefficient, a dimensionless number that quantifies the resistance of a specific geometric shape to airflow, will be a valuable datapoint for the client’s design iteration. Due to the sensitive nature of their work, the client has wished to remain anonymous. RBJCOE professors tasked a senior design team …

Development Of An Iot-Based Energy Theft Detection System For A Single-Phase Smart Meter, Ojo Julius Oladele, Funso Kehinde Ariyo, Samson Oladayo Ayanlade, Ayooluwa Peter Adeagbo, Ismail Adeniyi Adeleke

Al-Bahir

Electricity theft causes annual global losses exceeding $96 billion, severely impacting distribution networks. This paper presents a novel IoT-based system integrating current differential sensing, physical tamper detection, and edge-cloud analytics to detect energy theft in single-phase smart meters. The design employs three ACS712 current sensors to monitor Kirchhoff-compliant current flow at the grid pole, meter input, and load output, coupled with a PIR sensor for cabinet intrusion. A SIM800L GSM module enables real-time theft alerts and remote disconnection, while closed-loop control autonomously restores power after tamper resolution — a feature absent in prior GSM-only systems. An Android application provides geotagged …

“Bridging The Gap To Midwave Infrared Event-Based Sensors: Design, Sensitivity, And Radiation-Hardness Characterization Of A Single-Pixel Iii-V Event-Based Infrared Sensor For Space Applications, Zinah M. Alsaad

Electrical and Computer Engineering ETDs

Event-based sensing presents a revolutionary paradigm shift for next-generation space surveillance systems, where power consumption is an ever-worsening constraint as temporal resolution demands increase. In addition to reduced power consumption, low latency, and wide dynamic range, the event-based sensor fundamentally only produces data when there is a change in illumination from which events are generated; no data is produced if the scene remains static. With their event-based datastream being inherently focused on the dynamic information of the scene, they are particularly well-suited to machine vision and autonomous sensing applications. While these sensors have many compelling advantages, there are presently no …

Analysing The Impact Of Bi-Directional Application Of Iliceto Shield Wire Scheme For Rural Electrification In Tanzania: A Chalinze-Hale Transmission Line Case Study, Santos Kihwele, Prisca Paul

Tanzania Journal of Engineering and Technology (TJET)

Clean energy accessibility including electricity remains a major challenge in Tanzanian villages despite the many efforts made by its government.  The primary obstacle is that these villages are located more than 100 kilometres away from high-voltage to medium-voltage (HV/MV) transformer stations. Therefore, electrifying these villages by conventional method is financially not feasible. One of the low-cost rural electrification techniques that can be used to solve the issue is the "Iliceto Shield Wire Scheme" (ISWS) technology, In Tanzania, the application of ISWS technology seems to be very promising.  However, the technology can be integrated with locally available renewable energy sources ( …

Evaluation Of Internal Field In Ppln And Studies On Qpm Shg Efficiency Factor, Prasath Rk Mr

Theses and Dissertations

Periodically Poled Lithium Niobate (PPLN) crystals have attracted interest in optoelectronics and nonlinear optics. The response to the applied electric field is determined by their larger electro-optic and nonlinear optical coefficients. An internal electric field exists in congruent PPLN crystals due to its defects. Its evaluation is important in controlling the electro-optical behavior. A simple nondestructive diffraction method is proposed to estimate the internal electric field present in the congruent lithium niobate crystal.

Due to the presence of an unrelaxed internal field, the as-poled sample acts as an index grating. When a light is incident on such a sample, it …

Isolated Dc-Dc Converter For An Ev Microgrid, Oscar Yu, William Leiker

Electrical Engineering

This product is a redesign of a DC-DC buck-boost converter which utilizes a new topology, the flyback converter, for use in an electric vehicle (EV) as a microgrid. The main driver behind the redesign is to provide electrical isolation between elements in the microgrid. The EV microgrid consists of the battery, motor, external DC and AC ports, and the power electronics (DC-DC converter and AC-DC inverter) which were designed and built in previous senior projects. Using EV’s as microgrids can help relieve stress from the main power grid caused by charging electric vehicles. Implementing EV’s as a microgrid enables the …

Platforming For Circuit Education, Grady Oliver Schneider

Computer Engineering

The purpose of this project was to provide an alternative for students being introduced to resistive circuits. As a freshman in electrical engineering (transferred to computer engineering), I saw the struggles of other freshman to grasp the conceptual basics of circuits. While there’s lots of guides to circuit education, I think many of them fall short of being both engaging and teaching the intuition behind circuits. A lot of the more advanced concepts in circuits depends on the basic intuition of KCL, KVL, and Ohm’s Law. While there’s several basic techniques (such as voltage divider, current divider, and mesh current …

Microgrid Assessment And Ml-Based Power System Faults Detection Leveraging Real-Time Co-Simulation, Diego Normando Gandara Mendez

Open Access Theses & Dissertations

The rapid growth of distributed energy resources (DERs) and the increasing reliance on data-driven decision making have reshaped the operational challenges of modern electric power systems. As microgrids become more prominent in distribution networks, utilities require methods that unify planning, control, and real-time situational awareness to ensure resilient operation under faulted or uncertain conditions. The goal of this MSEE thesis is to design and validate a latency-aware ML framework for rapid, reliable fault detection in distribution grids. To achieve the goal of the thesis, there are three specific objectives. Objective 1 evaluates optimized microgrid configurations under varying DER levels and …

Unmixing In Very High Spatial Resolution Hyperspectral Images, Ana C. Chavez Lopez

Open Access Theses & Dissertations

Hyperspectral Imaging (HSI) captures hundreds of contiguous narrow wavelength bands across the optical region of the electromagnetic spectrum collecting the spectral signature of materials in the field of view of the sensor enabling detailed analysis of each pixel's spectral signature. Satellite or airborne remote sensing systems often capture imagery with low to moderate spatial resolution (LMSR). At these resolutions, the measured spectral signature is a mixture of the signatures of the materials within a single pixel. This mixing of spectral information makes analysis and material identification difficult. Hyperspectral unmixing is an analysis technique that decomposes a pixel's spectrum into constituent …

Simulation, Modeling, And Economical Optimization Of Small Modular Reactors For Flexible Power System Operations, Javier Bejarano

Open Access Theses & Dissertations

The transition toward a low-carbon and increasingly renewable electric grid has heightened the need for generation technologies that can deliver both stability and operational flexibility. Small Modular Reactors (SMRs), with their modularity, reduced geographical footprint, and capacity for flexible operation, have emerged as promising resources for supporting modern power systems. However, a comprehensive evaluation of their technical performance across steady-state conditions, fault-induced disturbances, and economically optimized dispatch is necessary to understand their role in future grid architectures. This thesis provides an assessment of SMR capabilities using benchmark test systems, data-driven forecasting, dynamic simulation, and unit commitment modeling to evaluate how …

Optimal & Robust Control Of A Bidirectional Dc-Dc Converter In Ev Systems, Yasser Ayeva

Electrical Engineering and Computer Science Faculty Publications and Presentations

This paper analyzes the performance of PI, LQR, and H∞ controllers for the regulation of a bidirectional buck boost converter in electric vehicle systems. To get the system state space equations, a continuous conduction average model is linearized. For analysis a PI controller will be used as baseline, the LQR controller will be used to improve transient response, and the H∞ controller will be used for the system robustness and disturbance rejection. The simulation results show that the advanced controllers surpass the PI controller in terms of overshoot, settling time, and voltage ripple, with the H∞ controller offering the best …

Computational Methods For Complex Electromagnetic Geometries And Media, Edgar Bustamante

Open Access Theses & Dissertations

Additive manufacturing has enabled electromagnetic devices with increasingly complex geometries, but existing numerical tools remain limited in their ability to model and design such structures. This dissertation presents two major advancements that address these restrictions in the finite-difference frequency-domain method (FDFD) and the spatially-variant lattice algorithm (SVLA). These two numerical methods provide a foundation for future exploration in the simulation, optimization, and realization of next-generation electromagnetic devices. First, a general bianisotropic FDFD formulation based on the vector wave equation is presented that enables practical modeling of metamaterials using effective medium homogenized parameters rather than explicitly resolving subwavelength metamaterial features. The …

Further Insights Into The Network Link Outlier Factor's (Nlof) Light-Load Penalty, Sunday Oluwaleke Ogundele

Open Access Theses & Dissertations

This research investigates the performance of the Network Link Outlier Factor with Most Likely Links (NLOF:MLL), under varying network load conditions. Earlier studies reported that the NLOF:MLL algorithm experienced a noticeable drop in fault-localization accuracy when operating in lightly loaded networks. To further examine this limitation, 240 experiments were carried out to observe how the algorithm responds as overall network load increases. The evaluation focused on the classification performance metrics: precision, recall, and F1-score. The results show that NLOF:MLL’s effectiveness improves as network load increases but that the rate of improvement slows progressively, eventually stabilizing in a pattern consistent with …

Development And Optimization Of A Deep Level Transient Spectroscopy System, Samuel Ruiz

Open Access Theses & Dissertations

Deep-level transient spectroscopy (DLTS) remains one of the most widely used techniques for identifying electrically active defects that affect leakage current, carrier lifetime, and overall reliability in semiconductor devices. Legacy boxcar or capacitance meter implementations, however, often struggle with limited signal-to-noise ratio, labor-intensive data collection, and poor adaptability across diverse material systems. This thesis presents the design and optimization of a semi-automated, lock-in-amplifier-based DLTS platform. By pairing a Zurich HF2LI with PID-controlled cryogenic sweeps, precision signal generation, and MATLAB driven acquisition and processing scripts, the system will (i) enhance SNR through phase-sensitive detection, programmable low pass filtering, and parasitics calibration; …

Image And Signal Processing Methods For Clinical Decision Support: Reference-Based Lung Segmentation On Chest X-Rays And Ecg-Based Study Of Acute Hyperkalemia Using Machine Learning, Basavarajaiah Shanmukhayya Totada

Open Access Theses & Dissertations

ABSTRACT

Study-I: An Image Processing Pipeline for Reference Guided Lung Region Detection in Chest Radiographs with Shape Similarity Matching Accurate and reliable segmentation of the lung region in chest X-ray (CXR) images is essential for computer-aided diagnosis (CAD) systems, particularly in the early detection and monitoring of lung disorders. Traditional segmentation techniques often rely on manual annotations, limiting scalability and adaptability. The proposed reference-guided approach selects the most similar healthy CXRs dynamically, ensuring flexibility while benefiting from dataset-specific reference images. Building upon prior approaches that utilize shape similarity-based selection and SIFT-flow, this study introduces a fully automated segmentation pipeline that …