Electrical and Computer Engineering Commons^™

High-Frequency Accurate Dual-Side Equivalent Circuit Model For Transformers, Reza Vahdani, Junyong Park, Manish Kizhakkeveettil Mathew, Zhekun Peng, Chiuk Song, Hyucksu Kweon, Jiang Lijun, Donghyun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

This study delves into the modeling of a transformer in the frequency range of 100 KHz to 30 MHZ. The coupling coefficient was considered as a function of leakage and self-inductance and incorporated in the optimization process of transformer modeling in the proposed method. The equivalent circuit focused on the critical aspects of leakage inductance, parasitic capacitance, and winding effects. At first, the winding effect of an air-core inductor over wide frequency range with both single-layer and double-layer windings was shown. Then an equivalent circuit was proposed to model a transformer over this frequency range. The comparison between the measured …

Analysis And Design Optimization Of Electric Machines With Field Intensifying Configuration, Ali Mohammadi

Theses and Dissertations--Electrical and Computer Engineering

The design and optimization of electric machines face increasing demands for efficiency, improved torque density, manufacturability, and effective utilization of materials. Meeting these demands is particularly vital in for example, electric vehicles (EVs) and renewable energy systems, where performance, reliability, and cost are critical. In this dissertation innovative field-intensifying electric machine configurations have been explored, emphasizing advanced topologies, computational modeling, and optimization techniques to advance the state of the art in electric machine design and analysis.

Electric machines with high torque density are essential for many low-speed direct-drive systems, such as wind turbines, in-wheel traction, and industrial automation. This dissertation …

Ohmic Contacts For Fabrication Of Sic Cmos Devices, Anthony Di Mauro

Graduate Theses and Dissertations

Today’s world of electronics is dominated by semiconductor devices which utilize silicon as their substrate material. Though, silicon is not ideal for semiconductor devices in high-voltage or high-temperature applications. Additionally, the efficiency of silicon devices becomes drastically reduced in nonideal operating conditions. Therefore, finding alternatives to silicon?based devices has been a topic for decades now. A few great candidates to replace silicon devices for said applications include Silicon Carbide (SiC), Gallium Nitride (GaN), and Aluminum Arsenide (AlAs). SiC has grown its reputation as the best candidate, when compared to other potential alternatives, due to its wide bandgap, high operating frequency, …

A Techno-Economic Perspective On Efficient Hybrid Renewable Energy Solutions In Douala, Cameroon’S Grid-Connected Systems, Reagan Jean Jacques Molu, Serge Raoul Dzonde Naoussi, Mohit Bajaj, Patrice Wira, Wulfran Fendzi Mbasso, Barun K. Das, Milkias Berhanu Tuka, Arvind R. Singh

Research outputs 2022 to 2026

Cameroon is currently grappling with a significant energy crisis, which is adversely affecting its economy due to cost, reliability, and availability constraints within the power infrastructure. While electrochemical storage presents a potential remedy, its implementation faces hurdles like high costs and technical limitations. Conversely, generator-based systems, although a viable alternative, bring their own set of issues such as noise pollution and demanding maintenance requirements. This paper meticulously assesses a novel hybrid energy system specifically engineered to meet the diverse energy needs of Douala, Cameroon. By employing advanced simulation techniques, especially the Hybrid Optimization Model for Electric Renewable (HOMER) Pro program, …

Two-Level Design Optimization Of Ac Machines With Dc Stator Excitation And Minimal Torque Ripple Using Reluctance Rotor Profile Shaping, Ali Mohammadi, Oluwaseun A. Badewa, Yaser Chulaee, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

Torque ripple mitigation in electric machines is important for a smooth and stable operation, minimize mechanical vibrations, and enhance the overall performance. In this paper, a novel two-level optimization method is proposed for the design of synchronous flux-switching and hybrid excitation machines with an innovative multi-point spline shaping method to minimize the torque ripple. This study uses models that are validated by experimental tests from a prototype with similar topology, and exemplifies the aforementioned optimization process on a 28 pole machine. The analysis results indicate that the torque ripple can be substantially reduced with improved electromagnetic torque of the electric …

Developing Decision-Making Models And Algorithms To Help Prevent Emergencies, Mizaakbar Xakkulmirzayevich Hudayberdiyev, Oybek Zokirovich Koraboshev

Chemical Technology, Control and Management

The article is devoted to the solution of the scientific issue of decision-making support for the prevention and elimination of the consequences of emergency situations. The relevance of this issue is related to the need to develop a theoretical basis for optimizing the risk of adverse effects on human health and the environment in connection with emergency situations, and a predictive model for the development of emergency situations and their prevention or elimination of their consequences. The optimization of the importance measure of signs for predicting the values of the factors of fire conditions has been carried out. In addition, …

Comparative Analysis Of Motors With Inner And Outer Reluctance Rotors And Pm Stators, Oluwaseun A. Badewa, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper presents a comparison of special outer and inner reluctance rotor motor topologies with permanent magnet (PM) stators having toroidal AC windings. A systematic approach is taken to study and discuss the design geometries, the respective impact on performance, and adoption of technological advancements such as stator-only cooling and hair-pin winding for high slot fill factor. Parametric FEA models are developed for both topologies, and design of experiments (DoE)-based sensitivity analysis is used to study the effect of independent variables on specific performance metrics such as torque, motor loss, torque ripple, and power factor. Inner and outer rotor topologies …

Graph-Based Modeling And Optimization Of Wpt Systems For Evs, Matthew J. Hansen, Greg Droge, Abhilash Kamineni

Electrical and Computer Engineering Student Research

A model of a system of wireless power transfer (WPT) pads is developed, where each WPT pad is modeled as a node and the coupling between pads is modeled as graph edges. This modeling approach is generalized to admit primary, secondary, and booster coils, where power can flow among the pads and a pad can fill multiple roles. An excitation in one pad induces voltage and current in all neighboring pads, causing each pad to act as both a booster coil and either a transmitter or a receiver. Power flow through the entire system can be modeled with the graph …

Techniques To Overcome Energy Storage Limitations In Electric Vehicles, Matthew J. Hansen

All Graduate Theses and Dissertations, Fall 2023 to Present

Electric vehicles are becoming increasingly popular, battery limitations (cost, size, and weight) complicate electric vehicle adoption. While important research on battery development is ongoing, this dissertation discusses two main approaches to overcome those limitations within the existing battery technology paradigm. Those thrusts are: improving battery health through an optimal charging strategy and minimizing necessary battery size through dynamic wireless power transfer. In this dissertation, relevant literature is discussed, with opportunities for further development considered. Within the two thrusts, three objectives sharpen the focus of the research presented here. First, a planning tool is defined for a battery electric bus fleet. …

Optimization Pump As Turbine Coupled To A Self-Excited Induction Generator Using Multi-Objective Genetic Algorithm, Emanuel J. Nyirenda

Tanzania Journal of Engineering and Technology (TJET)

As a way of accelerating the deployment of affordable and clean renewable energy generation technologies, applying a pump working as a turbine coupled to a self-excited induction generator is gaining popularity in various areas including energy recovery and micro hydro systems. However, it is currently challenging to predict the performance of the PAT-SEIG system and there is no agreed-upon rule on the selection of the appropriate system to be installed at a particular site. This paper has presented multi-objective optimization to select the best operating point of the PAT-SEIG system. The results show that the peak efficiencies for the PAT …

Joint Energy And Security Optimization In Underwater Wireless Communication Networks, Kazi Y. Islam, Iftekhar Ahmad, Yue Rong, Daryoush Habibi

Research outputs 2022 to 2026

Underwater wireless communication networks (UWCNs) can support a wide range of applications in the underwater domain, including mining and drilling, coastline monitoring, border surveillance, and submarine/mine detection. Some of these applications are sensitive in nature (e.g., military) and demand stringent security requirements for data communications. In order to prevent malicious attacks (e.g., jamming) in these UWCNs, robust security countermeasures must be implemented. Additionally, sensitive data communications must be protected. However, computationally expensive security protocols, such as encryption, can severely shorten UWCN lifetime, where battery-powered nodes already suffer from scarce energy supplies. In this work, we exploit content caching as a …

Optimization Of Human Interactions In The College Campus Model Via Simio Integration, Benjamin E. Chaback

Doctoral Dissertations and Master's Theses

College campuses are a significant part of life in some cities. Many students each year attend university, pursuing additional knowledge from faculty members. Both staff and faculty members rely on these students to have successful jobs and to ensure the university functions. Yet recently, more and more students are attending, leading to overcrowding, lower admission rates, and difficulty getting into good programs. Previous work exists on qualitative student affairs and quantitative retention data, yet little on using simulations to model this problem. This work aimed to (a) Determine the ability to successfully model human interactions/people flow on a college campus, …

Synthesize A Neural Network Parameter Optimizer For An Adaptive Pid Controller, Nashvandova Gulruxsor Murot Qizi

Chemical Technology, Control and Management

Wide application of proportional-integral-differential (PID)-regulator in industry requires constant improvement of methods of its parameters superstructuring. In the paper, the questions of optimization of PID-regulator parameters with application of methods of neural network technology are considered. A methodology for selecting the architecture of neural network optimizer designed to determine the tuned parameters of PID regulator is proposed. The algorithm of training of the neural network, with the set on the basis of the method of inverse gradient propagation is offered. The proposed improved PID-neural regulator allowed to provide stabilization of neural network operation and its trainability in the control loop …

Strategy For Predictive Control Of The Rectification Process Based On A Model Controller With A Given Forecast, Ildar Rafkatovich Sultanov

Chemical Technology, Control and Management

A method is being developed to optimize the generated controls for the multicomponent distillation process with prediction, based on predictive data with a moving horizon. The difference between this method and the classical modeling approach, in which the percentage of the degree of opening of valves installed on the output streams of the column is used as control actions, is that control occurs on the feedback principle. The proposed method is based on the use of a dynamic process model to optimize control actions in real time in order to achieve certain production targets. The essence of the MPC approach …

Milp Modeling Of Matrix Multiplication: Cryptanalysis Of Klein And Prince, Murat Burhan İlter, Ali Aydın Selçuk

Turkish Journal of Electrical Engineering and Computer Sciences

Mixed-integer linear programming (MILP) techniques are widely used in cryptanalysis, aiding in the discovery of optimal linear and differential characteristics. This paper delves into the analysis of block ciphers KLEIN and PRINCE using MILP, specifically calculating the best linear and differential characteristics for reduced-round versions. Both ciphers employ matrix multiplication in their diffusion layers, which we model using multiple XOR operations. To this end, we propose two novel MILP models for multiple XOR operations, which use fewer variables and constraints, proving to be more efficient than standard methods for XOR modeling. For differential cryptanalysis, we identify characteristics with a probability …

Power Grid Resiliency Enhancement Against Flood-Induced Hazards, Mohadese Movahednia

LSU Doctoral Dissertations

Natural disasters, such as floods, may damage power system assets and lead to widespread and long outages. The impact of flood can be alleviated by preventive actions such as installing tiger dams around power substations before the flood. In this regard, it is imperative that critical substations are identified in terms of the connected load and imposed costs to the system. This study presents a resource allocation approach for protecting power substations against flood events a day ahead of the event. First, the required information for the model is extracted. Flood probability distribution functions are used to generate several flood …

Reinforcement Learning For Optimal Kicking Actions In Humanoid Robotics: Advancing Robotic Autonomy And Versatility, Suresh Dodda, Sathish Kumar Chintala, Sukender Reddy Mallreddy, Sharath Chandra Macha, Yashwanth Vasa, Sapan Bharadwaj Bonala, Navin Kamuni, Sujatha Alla

Engineering Management & Systems Engineering Faculty Publications

Acquiring the necessary skills to perform a work effectively and efficiently requires a significant investment of time and computing power. Previous applications of Reinforcement Learning (RL) for action optimization in humanoid robotics have shown how promising this technology is for moving robotics towards true autonomy and versatility. Therefore, this study offers the first use of RL to create an entirely optimal kicking action for the Alderbaran Nao robot. Kicking motions that were steady, precise, quick, and able to kick farther than any existing RoboCup squad were generated by optimizing for a multi-objective reward function. We demonstrate that the ideal kicking …

Exploring Machine Learning Techniques For Embedded Hardware, Neel R. Vora

Computer Science and Engineering Theses - Archive

This thesis delves into the intricate symbiosis between machine learning (ML) methodologies and embedded hardware systems, with a primary focus on augmenting efficiency and real-time processing capabilities across diverse application domains. It confronts the formidable challenge of deploying sophisticated ML algorithms on resource-constrained embedded hardware, aiming not only to optimize performance but also to minimize energy consumption. Innovative strategies are explored to tailor ML models for streamlined execution on embedded platforms, with validation conducted across various real-world application domains. Notable contributions include the development of a deep-learning framework leveraging a variational autoencoder (VAE) for compressing physiological signals from wearables while …

A Charging Strategy For Large Commercial Electric Vehicle Fleets, Bassam Al-Hanahi, Iftekhar Ahmad, Daryoush Habibi, Pravakar Pradhan, Mohammad A. S. Masoum

Research outputs 2022 to 2026

The popularity of Commercial Electric Vehicles (CEVs) has experienced a surge in recent years, particularly in urban vocational contexts, as a means of advancing towards the goal of attaining net-zero emissions by 2050. The return-to-base charging strategy, which involves charging CEVs at depots, has become a prevalent practice for smaller CEV fleets. Nevertheless, for larger CEV fleets, the limited charging capacity at depots presents a significant challenge, leading to a reliance on both limited depot charging infrastructure and public charging infrastructure. This reliance can have a substantial impact on both the operational costs and the sustainability of logistics services. To …

Design And Optimization Of High-Efficiency Coreless Pcb Stator Axial Flux Pm Machines With Minimal Eddy And Circulating Current Losses, Yaser Chulaee, Greg Heins, Ben Robinson, Ali Mohammadi, Mark Thiele, Dean Patterson, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

This paper proposes a systematic multi-step design procedure for highly efficient printed circuit board (PCB) stator coreless axial flux permanent magnet (AFPM) machines with minimal eddy and circulating current losses. The process begins with initial sizing, providing specific coefficients based on experience with multiple design projects. It continues with the optimization of the machine envelope design using an evolutionary algorithm and computationally efficient 3D finite element analysis (FEA) models. The subsequent step focuses on the detailed design of a PCB stator, aiming to minimize eddy and circulating current losses. Several open circuit loss mitigation techniques are proposed based on analytical …

A Novel Physics-Assisted Genetic Algorithm For Decoupling Capacitor Optimization, Li Jiang, Ling Zhang, Shurun Tan, Da Li, Chulsoon Hwang, Jun Fan, Er Ping Li

Electrical and Computer Engineering Faculty Research & Creative Works

This article proposes a new physics-assisted genetic algorithm (PAGA) for decoupling capacitor (decap) optimization in power distribution networks (PDNs), which is a highly efficient approach to minimizing the number of decaps within an enormous search space. In the proposed PAGA method, the priority of the decap ports is first determined based on their physical loop inductances. Then, an initial solution is quickly obtained by placing decaps sequentially on the port with the highest priority. Subsequently, a GA with prior physical knowledge is developed to find better decap solutions progressively. A port removal scheme that eliminates the low-priority ports and a …

Design Of An Adaptive Robust Pi Controller For Dc/Dc Boost Converter Using Reinforcement-Learning Technique And Snake Optimization Algorithm, Seyyedmorteza Ghamari, Mojtaba Hajihosseini, Daryoush Habibi, Asma Aziz

Research outputs 2022 to 2026

The DC/DC Boost converter exhibits a non-minimum phase system with a right half-plane zero structure, posing significant challenges for the design of effective control approaches. This article presents the design of a robust Proportional-Integral (PI) controller for this converter with an online adaptive mechanism based on the Reinforcement-Learning (RL) strategy. Classical PI controllers are simple and easy to build, but they need to be more robust against a wide range of disturbances and more adaptable to operational parameters. To address these issues, the RL adaptive strategy is used to optimize the performance of the PI controller. Some of the main …

Design And Optimization Of High-Efficiency Coreless Pcb Stator Axial Flux Pm Machines With Minimal Eddy And Circulating Current Losses, Yaser Chulaee, Greg Heins, Ali Mohammadi, Mark Thiele, Dan M. Ionel, Ben Robinson

Electrical and Computer Engineering Graduate Research

This paper proposes a systematic multi-step design procedure for highly efficient printed circuit board (PCB) stator coreless axial flux permanent magnet (AFPM) machines with minimal eddy and circulating current losses. The process begins with initial sizing, providing specific coefficients based on experience with multiple design projects. It continues with the optimization of the machine envelope design using an evolutionary algorithm and computationally efficient 3D finite element analysis (FEA) models. The subsequent step focuses on the detailed design of a PCB stator, aiming to minimize eddy and circulating current losses. Several open circuit loss mitigation techniques are proposed based on analytical …

Enhancing Robotic Exploration Through Semantically-Guided Sampling Strategies, Christopher Alexander Arend Tatsch

Graduate Theses, Dissertations, and Problem Reports (ETD)

From space and deep-sea exploration to disaster response and environmental monitoring, autonomous robots are essential for advancing science, improving safety, and addressing critical challenges. This dissertation introduces a novel open-source strategy for autonomous robotic exploration: the Semantically-Guided Exploration (SGE) framework. Designed for ground vehicles, SGE integrates semantic understanding into the autonomous exploration process, improving decision-making in complex environments. Specifically, the proposed sampling-based approach uses the information from the semantic segmentation of RGB images and depth images to guide the robot's selection of exploration goals. This method enables the robot to steer away from potential dangers such as large rocks and …

Adaptation Algorithm For Self-Tuning Of Parameters Of Models Of Multi-Stage Flotation Processes, Nilufar Sharifzhanova, Maksadhan Yakubov, Francesco Gregoretti

Technical science and innovation

Modern methods for solving problems of planning the execution of batches of tasks in multi-stage systems are characterized by the presence of restrictions on their dimensionality, the impossibility of guaranteed obtaining better results in comparison with fixed packages for different values of the input parameters of the problem. In the article, the author solved the problem of optimizing the composition of job packages running in multi-stage systems using the branch and bound method. Research has been carried out on various ways to form package execution orders tasks in multi-stage systems (heuristic rules for ordering packages tasks in the sequence of …

Cost Minimizing Energy Management Control Scheme For Microgrids Considering Dynamic Electricity Prices, Levi T. Miller

All Graduate Theses and Dissertations, Fall 2023 to Present

As countries develop and technology improves, the world is using more energy than ever before. This fact along with several other political, social, and economic factors has resulted in simultaneous energy and climate crises. A partial solution to both problems is bringing clean energy sources of electricity closer to the customers who use that energy. A microgrid is a smaller version of the national electric grid where smaller electricity generators are networked with local consumers and controlled independently of the main grid. Because control of electricity sources and loads are transferred to local controllers, the flexibility with which they can …

Simulation-Based Optimization Of A Dc Microgrid: With Machine-Learning-Based Models And Hybrid Meta-Heuristic Algorithms, Tyler Van Deese

Theses and Dissertations

The field of economic dispatch (ED) focuses on optimizing power flow in a power system to minimize costs. It has the potential to significantly enhance system effectiveness, and efficiency, and reduce operating costs. Various techniques have been employed to tackle this problem, each with its own strengths and weaknesses. One promising approach is simulation-based optimization (SBO), which allows for accurate modeling of system interactions and improved representation of expected results. However, SBO requires running numerous simulations to identify an optimal solution, and there is a possibility of not achieving the global optimum. This work aims to address these challenges using …

A Study On Rapidly Exploring Random Tree Algorithms For Robot Path Planning, Sahil Sharma

Master's Theses

Robot path planning is a critical feature of autonomous systems. Rapidly-exploring Random Trees (RRT) is a path planning technique that randomly samples the robot configuration space to find a path between the start and end point. This thesis studies and compares the performance of four important RRT algorithms, namely, the original RRT, the optimal RRT (also termed RRT*), RRT*-Smart, and Informed RRT* for six different environments. The performance measures include the final path length (which is also the shortest path length found by each algorithm), time to find the first path, run time (of 1000 iterations) for each algorithm, total …

Application Of Evolutionary Algorithms For Optimization Of Operation Modes Of Regional Electric Power Systems, Isamiddin Khakimovich Siddikov, Oksana Vitalevna Porubay

Chemical Technology, Control and Management

The paper presents the possibilities of using evolutionary algorithms to solve the problem of optimizing the operation modes of electric power facilities in the presence of constraints in the form of inequalities and equalities. The limits of constraints have a variable character, depending on the generated and consumed energy. Existing methods used for the optimization of modes are based on general principles and approaches to optimization, which usually adapt to the specifics of the problem. In electric power facilities, optimization problems have some peculiarities, among which is the presence of multiple constraints applied to both independent and dependent variables. Many …

Optimizing High-Performance Computing Design: The Impacts Of Bandwidth And Topology Across Workloads For Distributed Shared Memory Systems, Jonathan A. Milton

Electrical and Computer Engineering ETDs

With the complexity of high-performance computing designs continuously increasing, the importance of evaluating with simulation also grows. One of the key design aspects is the network architecture; topology and bandwidth greatly influence the overall performance and should be optimized. This work uses simulations written to run in the Structural Simulation Toolkit software framework to evaluate a variety of architecture configurations, identify the optimal design point based on expected workload, and evaluate the changes with increased scale. The results show that advanced topologies outperform legacy architectures justifying the additional design complexity; and that after a certain point increasing the bandwidth provides …