Electrical and Computer Engineering

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A High-Speed, Light Weight Hardware Architecture for H.264- Compatible Compression on an FPGA
(2023-01-01) Tayyebi, Azam; Hanna, Darrin M; Louie, Geoffrey; Alawneh, Shadi G; Cesmelioglu, Aycil
Video compression is a technique that reduces and removes spatial and temporal redundancy of video data, resulting in a reduction in transmission time and communication bandwidth across a network and efficient storage. H.264, a widely adopted video compression standard, is the result of collaborative efforts between the ISO (International Organization for Standardization) Moving Picture Experts Group (MPEG) and the ITU (International Telecommunication Union) Video Coding Experts Group (VCEG). H.264 uses an array of algorithms for coding digital video to achieve better compression efficiency compared to previous standards. However, this efficiency increase comes at the cost of higher computational complexity for H.264 encoders. This thesis design and implement an H.264-compatible intra-frame video encoder on FPGA. The encoding algorithms, like intra prediction, transform, quantization, and entropy coding, are initially implemented and tested in MATLAB. Later, these algorithms are translated into VHDL language and evaluated through timing simulations vi in Vivado. The FPGA implementation is then tested using various input pixel sizes and video resolutions across multiple FPGA devices. The encoder supports all video resolutions and frame rates.
An Optimal Asynchrophasor in PMU Using Second Order Kalman Filter
(2021-11-15) Alqahtani, Nayef Mohammed S; Zohdy, Mohamed; Ganesan, Subramaniam; Kobus, Christopher; Elsayed, Suzan
Phasor Measurement Units (PMU) are very costly according to energy regulator and utility companies. Utility operators work on alternative solutions to reduce the error rate and operation costs of PMU. In this paper, we sought to optimize the PMU to reduce the level of error using Second-Order Kalman Filter (SOKF). Consequently, this optimization is based on minimizing the number of errors when receiving the signal from access points or from the main access point. We derived a simple mathematical model to estimate the phase coming from the PMU.PMUs provide Global Positioning System (GPS) time stamped synchronized measurements of voltage and currents with the phase angle of the system at certain points along the grid system. Those synchronized data measurements were extracted in form of amplitude and phase from various locations of the power grid to monitor and control the power system conditions. A PMU device is a crucial part of the power equipment in terms of the cost and operative point of view. However, such ongoing development and improvement to PMUs' principal work is essential to the network operators to enhance the grid quality and the operating expenses. A MATLAB model was created to implement the proposed method in the presence of Gaussian and non-Gaussian noise. It is based on an Asyncrhophasor technique resulting in a phase error minimization when receiving the signal from access point or from the main access point. The results show the proposed SOKF method outperforming the existing model as tested using Mean Square Error (MSE). The SOKF method was replaced with a synchronization unit into the PMU structure to clarify the significance of the proposed new PMU. This paper's proposed method leads to lower costs and less complex techniques to optimize the performance of PMU using SOKF
A Bayesian Network Based Approach Toward An Anticipatory Safety Reasoning System Autonomous Vehicle Copilot
(2022-11-17) Frederick, Philip A.; Cheok, Ka C; Das, Manohar; Sengupta, Sankar; Lipták, László; Del Rose, Michael; Kania, Robert
Future ground vehicle transportation is expected to rely heavily on autonomous mobility. However, the technical progress required to ensure a completely safe autonomous vehicle for unlimited roadway use, and reliable ways to measure its safety, is behind expectations. It is believed that a research breakthrough is required to address this gap. This dissertation defines a novel method for addressing on-road autonomous vehicle safety, explicitly focusing on unsignalized intersections. A method is described to generate an anticipatory safety copilot to assist the autonomous system with motion decisions by combining data collected from global online sources and the local autonomous vehicle sensors. This anticipatory copilot reasons about the environment around the autonomous vehicle and projects the vehicle's real-time motion intent forward into a projected future version of the environment created via features from the combined local and global source information. Based on this processed information, the copilot anticipates the probabilistic success of the autonomous vehicle safely executing its intended action.
Cellular 5G And V2X Antennas Design for Automotive Applications
(2022-03-14) Khalifa, Mohamed Osman Hussein; Aloi, Daniel N; Kaur, Amanpreet; Cheng, Eddie; Azadegan, Reza
The work presented in this dissertation involves investigation and development of antennas and antenna systems that can contribute to autonomous vehicles realization. The antennas targeted in this work are namely Fifth Generation (5G) cellular antennas and Vehicle to Everything (V2X) antenna. The studies conceived in this work followed a scientific approach which starts by accurately simulating the antennas using three dimensional Electromagnetics (EM) solver High Frequency Simulator System (HFSS) software on one meter rolled edges GND. Then antenna and antenna systems were measured on one-meter GND inside anechoic chamber and also measured either on the top of vehicle roof or at the vehicle’s windshield. Phase one of this work starts by presenting a multi-wideband branched monopole antenna that covers 5G cellular bands between 617MHz- 5000MHz. This antenna utilizes two arms and L-Shape slot structure to provide coverage for low, mid, and high 5G cellular bands and also to reject Global Navigation Satellite System (GNSS) frequency bands. The antenna has compact size, light weight, low cost, and excellent gain characteristics at the solid angle facing cellular base station communication towers. The design, simulated, and measured results were presented and discussed in detail. Phase two of this work uses the element developed in phase one to construct high order Multiple-Input-Multiple-Output (MIMO) structure in order to boost overall system throughput, capacity, and data rate. Three MIMO systems configurations were studied, the first two are 2x2 5G cellular MIMO systems with similar individual antenna elements and opposite antennas orientations whereas the third configuration is a 4x4 5G cellular MIMO system. The individual antennas performance, diversity radiation pattern, and correlation between antennas were reported and discussed for all three MIMO configurations. Phase three of this work presents a V2X cavity-backed slot antenna that can be mounted in the vehicle’s windshield or rear-view mirror. The antenna is GND independent, and it provides excellent below horizon performance allowing the vehicles to communicate with other objects of less height. The antenna can be used as a building block to implement a full V2X system that provides null-free omnidirectional coverage at V2X solid angle of interest while providing aesthetic look for the vehicle which makes it very attractive in the automotive industry. The antenna was simulated and measured, and its radiation pattern, gain, and efficiency were presented and discussed in detail.
Design and Control of a High-Efficiency System for Electric Air Taxis Using MPC And LQR Control, and GAN-Based Power Electronics with Optimized Lithium-Sulfur Battery Management
(2024-01-01) Khan, Ahmad Ali; Zohdy, Mohamed A; Rawashdeh, Osamah; Schmidt, Darrell; Barber, Gary
Lithium-sulfur (Li-S) batteries are a new type of battery that could revolutionize the way we store energy. They have the potential to deliver much more energy than current lithium-ion batteries, which are used in everything from electric cars to smartphones.
Design of a Compact Multi-Band (Cellular 5g/GNSS/V2x) Antenna and Rigorous Analysis of Antenna Performance on Glass Roofs for Vehicular Platforms
(2023-01-01) Ibrahim, Ahmad Abu Elhassan Salih; Aloi, Daniel N; Kaur, Amanpreet; Qu, Guangzhi; Shaska, Tony
The growing market competition between the automakers led to the implementation of more entertainment systems and extra features to satisfy the automotive customers. The entertainment systems depend on wireless services and communication which led to increasing numbers of antennas mounted on and inside the vehicles. This dissertation is focused on automotive antenna design and the effect of the vehicle environment on the antenna performance. For the first part of the dissertation, a compact multi-band monopole antenna is designed for vehicular roof top shark-fin applications. The proposed multi-band antenna covers 5G sub-6GHz, GNSS and V2X frequency bands starting at 617MHz to 5925MHz. The presented antenna is a three-dimensional monopole antenna with two branches to cover the required bands with compact size to fit inside a roof top shark-fin. The antenna is simulated, optimized and then a prototype is fabricated, and its radiation characteristics are measured when mounted on one-meter ground plane and on a vehicle's roof. For the second part of the dissertation, the analysis of a C-V2X quarter-wavelength monopole antenna performance when mounted on a vehicle's glass roof is presented. Antenna gain measurements performed on a full glass roof exhibited a performance degradation in a linear average gain of 8 dB compared to when the same antenna is mounted on a metallic ground plane. In addition, the antenna radiation pattern on the glass roof had deep nulls. The antenna was simulated using a full-wave, three-dimensional electromagnetic field solver on the full glass sample with low emissivity (low-E) coating on the edges of the full glass roof and the simulation results showed acceptable agreement with the measurements. Simulation shows that the C-V2X antenna performance on the full glass roof can be improved by moving the low-E coating from underneath the glass to top of the glass
Determining Spatial Relevancy of Objects for Improved Development of Multi-Object Tracking in Autonomous Driving Systems
(2023-01-01) Hammod, Maen; Rawashdeh, Osamah; Lipták, László; Dean, Brian; Qu, Guangzhi
The perception system for autonomous vehicles (AVs) typically outputs all the objects it can observe in a scene. This is significantly more objects than what the AV would interact with, and far more than any human driver focus on during a driving task. Validating the perception system on all the observed objects could penalize its performance based on objects that will never interact with the AV or affect its planned trajectory. This dissertation outlines a strategy for identifying a subset of objects, referred to as Spatially Relevant Objects (SRO), that the perception system must perform exceptionally well on. This is valuable for several reasons and has many applications. For example, it can be used to determine the set of objects that should be included in the verification dataset for the perception system and thereby have a more efficient development cycle. Additionally, when evaluating the perception system on the SRO subset, the computed metrics not only evaluate the performance but also consider the real-world safety of the perception system, and the results would heavily support the safety case arguments. Finally, determining spatially relevant objects using a representative dataset then plotting their footprints relative to the AV can help determine and confirm the necessary sensing requirements and field of view coverage by prioritizing areas where SROs are most likely to appear. This is done without ignoring the fact that the world contains objects of different classes with different kinematics and could behave in a non-compliant way. The preliminary finding of applying our system showed that we can measure the performance of the perception system using a subset that averages about 11 of the observed objects without compromising the safety of the AV.
Disturbance Accommodating Control of an Automotive Transmission Torque Converter Clutch System
(2024-01-01) Perkins, Todd Addison; Das, Manohar; Kobus, Chris; Olawoyin, Richard; Arefifar, S. Ali; Tomlin, Kasaundra
Modern automotive drivelines are facing increasing pressure to improve overall efficiency while maintaining vehicle comfort and performance. This thesis presents several new ways to control the torque converter clutch in an automotive automatic transmission in such a way they improve driveline system efficiency while maintaining its comfort. This efficiency improvement is accomplished by extending the clutch’s application conditions to a lower speed where the environment is harsher than is possible with the current class of controllers.
GNSS Patch Antenna Modeling Passive Gain Optimization Using FEKO, Design of Experiments and P-Transform Technique
(2021-11-16) Aghashirin, Gholam D; Abdel-Aty-Zohdy, Hoda S.; Zohdy, Mohamed; Kafafy, Maged; Timmons, Adam; Schmidt, Darrell
The objective of this work was to design a compact new microstrip patch antenna for applications in support of Global Navigation Satellite System (GNSS), and automotive. My GNSS patch antenna was created and developed in this dissertation to serve and represent the critical component from the system level perspective for the next generation of Automotive Radio Head Units, Navigation Systems, and L3 systems HD maps in autonomous domain. Conducted literature review and published papers studied, however observed a deficiency in the area of modeling, optimization of the design parameters, passive gain of rectangular patch antenna using FEKO, Design of Experiments, and P-Transform algorithm. Furthermore, there is no such antenna related to the Center Frequency of 1.555 [GHz] GNSS antenna, which has not been investigated. The proposed work involved a modeling of New GNSS rectangular patch antenna. The design focus was on the operating frequency range of 1.500 [GHz] to 1.610 [GHz] and FEKO 3D Electromagnetic simulation software package from Altair [4] was used, Design of Experiments (DoE) [5], and as well as applying the P-Transform algorithm [6] optimization method on the presented dual band GNSS (GPS and GLONASS) patch antenna passive v gain. The proposed antenna designed to operate at both bands, GPS (L1=1.57542 [GHz]) and GLONASS (L1=1.602 [GHz]) signal. Moreover, the ground plane length (X1[mm]), ground plane width (X2[mm]), and the substrate dielectric constant design (X3[mm]) parameters were varied at each FEKO simulation run, in order to obtain the simulation of GNSS patch antenna passive gain output results for the purpose of the optimization study by using P-Transform technique within the MATLAB environment. The presented GNSS patch antenna 2D far field and/or average passive gain measurement of GPS and GLONASS at center frequency of 1.555 [GHz] was plotted and analyzed. The computation and analysis of passive gain involved at taking the delta/difference between elevation angle at 30 and 90 degrees from the average passive gain 2D graph and this step was conducted for 120 FEKO simulation iteration runs. For each FEKO simulation run the far field (average passive gain=Y [dBi]) was computed separately unique for that specific design parameters (X1 [mm], X2 [mm], X3 [mm]) and recorded in a lookup matrix table (.csv). This four columns lookup table was called out for the purposed of the P- Transform algorithm utilization and execution within the MATLAB environment.
GPU-Based Accelerated Algorithms for the Power Flow Calculation
(2023-01-01) Zeng, Lei; Alawneh, Shadi G.; Cesmelioglu, Aycil; Yang, LianXiang; He, Ping; Arefifar, Seyed Ali
Power flow (PF) calculation is critical for power systems, as the development of multiple energy supplies. Power system modeling and analysis have been challenging on power engineers and leading to great pressure for the PF calculation. For the safety, stability and real-time response in grid operation, grid planning and analysis of the power system, it is urged to require designing high-performance computing methods, accelerating PF calculation, obtaining the voltage magnitude and phase angle of buses inside the power system, and coping with the increasingly complex large-scale power system. The PF algorithm is, generally, classified into the iterative and direct methods in the perspective of numerical methods. As for iterative method, a pre-conditioner is required to be designed to reduce the condition number of sparse Jacobian matrix toimprove convergency of the power system. Although the iterative method can save much memory and solve some large-scale sparse linear equations, the PF solver severely depends on the complicated pre-conditioner of the Jacobian matrix. Usually, the PF calculation cannot get a convergent solution without validating the pre-conditioner, repeatedly. For direct method, the traditional sequential, the Newton-Raphson (NR) algorithm will consume much of the computing resource and take a long time to converge on solving large-scale sparse linear equations of the power system. To address these issues, the GPU-based parallel computing architecture, singleGPU, and multi-GPUs, was proposed to take advantage of multi-thread, task parallelism and data parallelism, accelerating the PF calculation. Also, the utilization of GPUDirect technology enhances communication efficiency and significantly reduces data transmission overhead, leading to superior performance improvements compared to the traditional sequential methods.
HEAR Device for Electrical Activity of The Heart: Computation Towards Cardiovascular Diseases Using Novel Comma-Z Classifier and GPU for Automotive
(2022-03-21) Sinnapolu, Giribabu; Alawneh, Shadi Dr; Ganesan, Dr. SubramaniamSuzan; Simon R Dixon MD; Saraydar, Dr. Cem U
The silent heart attack which is also known as silent myocardial infarction occurs in almost 45% of the heart attacks and strikes men more than women. Women have less tendency to get sudden heart attack or heart failure or arrhythmias due to the menstrual cycle hormone released by their bodies until certain age. However, studies also show that higher risk of cardiovascular events are found both in men and women. During the phase of myocardial infarction patients develop Ventricular Fibrillations or rapid Atrial Fibrillations which may lead to the risk of death in a short period of time. Covid-19 also induces arrhythmias and myocardial injury and acute coronary syndrome. The average time spent by a person behind the wheel is approximately 1 hour on an everyday basis for a 30 miles drive. The Driver and Vehicle agency promotes that a driver with heart arrhythmias require approval from medical professionals to drive and based on today’s estimation most of the drivers are likely to get into an emergency or accident or collision due to Cardiac Stress, Hypertension, Cardiomyopathy, or complications after Angioplasty. There is a tremendous increase worldwide for wearables devices ranging from 325 million in 2016 to 929 million by 2021 and now 1 in every 6 Americans are using a wearable device, automakers are trying methods that involve measuring heart data via seat sensors and steering wheel sensors. Finally, my contribution in this research comprises of inventing a circular earlobe device (HEAR) placed to the earlobe that sends enormous amount of heart related photoplethysmography (PPG) data to the in-vehicle GPU device and invented a method to observe, compute, analyze, predict, and study AF and VF arrhythmias along with NSR using novel COMMA-Z filter, Signal Differentiation and DFS filters while driving. Such a sensitive work requires thorough communication and discussion with medical professionals for correctness of final heart computed data so based on the various experiments and clinical trials conducted this research was extensively supported by well-known surgeons from Beaumont hospitals, Michigan. The HEAR device also helps in long term monitoring and study of AF and VF tachycardias and related heart conditions because it’s all about timing for heart conditions and diseases as these tachycardias may lead to occurrence of ischemic stroke and cardiac arrest and complete heart failure and other dangerous conditions.
Innovative Designs For Low Profile Antenna Systems For Mimo 5G/V2X And Gnss Communications
(2022-11-07) Yacoub, Ahmad; Aloi, Daniel N; Cesmelioglu, Aycil; Li, Jia; Qu, Guangzhi
The research in this dissertation shows the analysis and development of designing antenna elements and MIMO antenna systems that can be implemented in the automotive industry and have a significant role in an autonomous driving system. The antennas presented in this research cover 5G-sub-6GHz bands which have much more extended bandwidth compared to previous LTE network, in addition to covering Vehicle-to-Everything (V2X) frequency band. The design work presented in this research followed a scientific method that included simulating the antenna element using 3-D electromagnetic solver (HFSS) on 1-meter ground plane. The antenna was then fabricated using properlycut metal sheet, measured on 1-meter rolled-edge ground plane, and measured on a vehicle’s roof inside an anechoic chamber for practical measurements. The design guidelines and measurements are discussed in detail throughout this work. The first two sections of this research begin with presenting a novel wideband low-profile Planar Inverted F-Antenna (PIFA) that covers a wide frequency range (617MHz-6000MHz) that includes cellular 5G bands and V2X band while having reasonable rejection for Global Navigation Satellite System (GNSS) frequency bands. Then, Multiple MIMO configurations based on the novel PIFA design are studied by using spatial diversity, rotational diversity, and orthogonal diversity to increase the total throughput and data rate of the system. The performance of each element in the MIMO system is analyzed and discussed to evaluate the functionality of the system. The third section of this work introduces a 2x2 MIMO antenna system for vehicular application in the sub-6GHz 5G systems that operates in the middle and high frequency bands from 1.71GHz to 5GHz. The design consists of two novel raised printed monopoles on Flame Retardant 4 (FR4) dielectric material with Partial Ground Plane (PGP) structure to improve bandwidth impedance and achieve higher isolation across the operating frequency range. The design is an excellent candidate to be implemented in a shark-fin housing due to its low-profile characteristics and good electrical performance. Eventually, in the fourth section of this work, a fully integrated low-profile antenna systems for MIMO 5G and global navigation satellite system (GNSS) for L1/L5 frequency bands is presented. The designs can be used on the vehicle’s roof inside a low profile housing due to its physical parameters and RF performance.
Investigations Of Magnetic/Electric Field Control Of Magnetization Of Ferromagnetic And Multiferroics
(2022-11-09) Xiong, Yuzan; Qu, Hongwei; Zhang, Wei; Li, Jia; Yang, Ankun; Shillor, Meir
The shortcomings of contemporary complementary metal oxide semiconductor (CMOS) technologies include increased power consumption, scalability, volatility, and device variability. New materials and novel devices are being investigated in this regard. Spintronic devices, which are normally based on magnetic materials, store and process data based on the modes of electron spins, rather than the presence or absence of charges as in the CMOS, are one possible approach. Numerous potential advantages of spintronic devices include its quick operational speed, low power requirement, and non-volatility. Two ferromagnetic materials suitable for creating spintronic devices are investigated in his dissertation study. Material properties, techniques for regulating the magnetization of materials, with both magnetic and electrical fields, and the development of devices useful for use in frequency modulations are all respectively detailed.The first section of this dissertation studies the magnetically-induced transparence (MIT) effect in Y3Fe5O12 (YIG)/Permalloy (Py) coupled bilayers. The measurement is achieved via a heterodyne detection of the coupled magnetization dynamics using a single wavelength that probes the magneto-optical Kerr and Faraday effects of Py and YIG, respectively. Clear features of the MIT effect are evident from the deeply modulated ferromagnetic resonance of Py due to the perpendicular-standing-spin-wave of YIG. We develop a phenomenological model that nicely represents the experimental results including the induced amplitude and phase evolution caused by the magnon-magnon coupling. This work offers a new route towards studying phase-resolved spin dynamics and hybrid magnonic systems. The second part of this dissertation discusses the research on the hexaferrite material, Zn2Y, and the prospect of controlling its magnetic characteristics by applying a dc voltage, which is akin to a bias electric field. The detection and investigation of the magnetoelectric (ME) effect for in-plane currents orthogonal to the hexagonal axis in single crystal and thin films of Zn2Y grown via liquid phase epitaxy. By applying a dc voltage, tuning of ferromagnetic resonance (FMR) was achieved in the hexaferrites. In addition to the frequency shift caused by the electrical tuning, magnetic properties of the material as a function of the input tuning power was also studied.
Modeling and Control of Heat Transfer in a Single Vertical Ground Heat Exchanger for a Geothermal Heat Pump System
(2023-01-01) Salhein, Khaled Asharef Assudani; Zohdy, Mohamed A; Kobus, Christopher J; Aloi, Daniel N; Olawoyin, Richard; Schmidt, Darrell P
The Ground Heat Exchanger (GHE) is regarded as the most critical component of a Geothermal Heat Pump System (GHPS) due to its direct contact with the Earth and ability to benefit from its relatively steady temperature. A GHE can attain the maximum benefit from the Earths heat when the water temperature reaches the ground, which occurs when the water velocity is moderate, allowing the heat exchanger to balance. Optimally, controlling water velocity is crucial such that the water reaches the desired temperature. Therefore, in this dissertation, I proposed a novel mathematical model of heat transfer behavior between the water inside the underground pipe and the surrounding ground for heating and cooling modes in a GHE. The proposed dynamic model was applied to three case studies of GHPS at Oakland University, the University Politècnica de València, and Oklahoma State University in heating and cooling modes to assess its validity and further enhance the performance of the GHE by determining the optimum velocity range. The results revealed the optimal water velocity ranges for three GHPSs. Model Predictive Control (MPC) was designed to optimize the GHE’s output temperature by controlling the water velocity, which can reduce the power consumption used for the water circulation pump and therefore maximize efficiency. In this dissertation, I also introduced an Improved Grey Prediction Model (IGM (1,1)). The proposed IGM (1,1) model was based on optimizing the current predicted value by subtracting the error prediction between the previous accumulated time response of the GM (1,1) model and the previous background value throughout the prediction length. The IGM (1,1) model was applied to perform the GHPS’s output temperature prediction eight hours in advance at Oklahoma State University, the University Politècnica de València, and Oakland University, respectively. Thus, the IGM (1,1) model outperformed the traditional GM (1,1) model for all used datasets.
Multi-Objective Optimal Routing Schemes for High Mobility Vehicular Networks: A Path to Efficiency
(2024-01-01) Alolaiwy, Muhammad Musaad M; Zohdy, Mohamed A; Kaur, Amanpreet; Louis, Steven; Rugge, Erica
Technological advancements in wireless communication networks have enabled futuristic applications that support massive device access and pervasive communications. Moreover, vehicular networks in Intelligent Transportation Systems (ITS) require efficient communication and routing schemes to accommodate Electric and Flying Vehicles (EnFVs). A centralized approach is often flawed due to the high mobility and dynamic nature of device movement. Therefore, efficient and novel solutions are required to provide connectivity to EnFVs without any centrally connected unit. Our main focus in this study is to enable a faster, better, and improved communication platform for EnFVs, support a wide range of applications.
Nonlinear Discrete-Time Control of Modern Power Converters with Robust Adaptive Observer
(2023-01-01) Hernandez, Mauricio E.; Zohdy, Mohamed A.; Kruk, Serge; Ganesan, Subra; Edwards, William
Control systems are an integral part of modern society, crucial to the performance of these systems is the accurate mathematical model representation of the physical systems. However, every physical system is subject to external factors that over time can change its characteristics. Therefore, to adapt the mathematical model representation of the plant over time a State Observer or State Estimator is often used, which would be the main topic of my research. A ZETA Power converter is a type of switch mode power supply that offers high efficiency in addition to various advantages, among some is its low output ripple which is desired for powering modern VLSI electronics. However, due to its composition (non-linear and fourth order), controlling the dynamics could be complex. With the advances in microprocessing and their economical affordability now, implementing the control scheme of a Zeta converter in the discrete time domain makes it an ideal solution for control implementation, given the lack of research regarding discrete-time control for Zeta Power Converters, state space observers, and adaptive state estimation, this dissertation research aims to identify a novel way of controlling Zeta Converters using adaptive state observers and state feedback in the discrete-time domain that yields robustness in the presence of plant uncertainties that meets certain criteria. The results documented in this dissertation confirm but also outline the limitations of such nonlinear discrete-time domain controller state-feedback from a robust and adaptive full-state observer/estimator
NOVEL AUTOMOTIVE ANTENNA DESIGNS UTILIZING CHARACTERISTIC MODE ANALYSIS
(2023-01-01) Abdul-Rahman, Ehab Mahmoud; Aloi, Daniel N; Li, Jia; Nassar, Sayed; Schmidt, Darrell
The Theory of Characteristic Modes (TCM) provides a valuable method for antenna analysis. It helps decompose the total radiation into a set of orthogonal radiation modes. Each mode exhibits a unique reaction in terms of its current distribution and radiation pattern. TCM has proven helpful in numerous antenna design applications, such as enhancing radiation patterns, decoupling antennas, increasing bandwidth, and achieving input impedance match.This study aims to apply characteristic mode analysis (CMA) to address automotive antenna design challenges. The work involves synthesizing and controlling the desired radiation characteristic mode (CM) at the intended frequency range to achieve an excellent radiation pattern for automotive applications. The study focuses on practical antenna design for the newly defined 5G-sub 6GHz cellular bands in the 0.617-5 GHz range and its cooperation with other coexisting wireless antennas for other wireless functions.
Novel Piezoelectric Biosensor Based on SARS-CoV-2 (COVID-19) Spike Antibody for Coronavirus (Covid-19) Detection
(2022-01-01) Alromithy, Fares Sulaimin; Zohdy, Mohamed; Auner, Gregory; Kamel-ElSayed, Suzan; Das, Manohar; Kaur, Amanpreet
At the end of December 2019, the novel coronavirus SARS‐CoV‐2 appeared in Wuhan, China. The World Health Organization released a global health emergency declaration based on growing case notification rates in several locations worldwide. Therefore, sensitive, specific, rapid, and deliverable diagnostic monitoring is vital for making proper decisions on treating and isolating infected patients, which will help prevent the spread of infectious diseases. The surface Acoustic Wave (SAW) biosensor provides a unique, highly sensitive electrical approach to biomolecule detection and cell growth. For this study, a novel SAW sensor is developed, and the mass sensitivities are tested to detect the SARS‐CoV‐2 by attaching the SARS-CoV-2 spike antibody immobilized on the sensor surface. First, a two-dimensional (2D) and a three-dimensional (3D) finite element model were developed based on a realistic device to obtain a complete characterization of the senor. Then, the AlN/Al2O3 fabricated sensor was tested and ultrasonically rinsed in preparation for silanization. After depositions of (APTMS) on the sensor by the Chemical Vapor Deposition method, the antibodies were immobilized on surfaces with the aid of a crosslinker (EDC) and (Sulfo-NHS). Finally, the SARS-CoV-2 was introduced to the sensor, and the attachment of the immobilized antibody was tested and evaluated. The sensor was tested and characterized by Raman spectroscopy and the vector Network Analyzer. Finally, our device was able to detect the virus in real-time time (within two to three minutes), confirming its high sensitivity and selectivity with regard to the SARS-CoV-2 virus.
Optimization Approaches for Optimal Power Flow Problems in Renewable Energy Grids
(2021-11-15) Alzahrani, Abdullah Mohammed A; Zohdy, Mohamed; Alaweh, Shadi; Monroe, Ryan; Elsayed, Suzan
In recent years, the global energy crisis confronting humanity is attributable to a deficiency in classical energy sources whereas the energy demands are widespread growth. In overcoming this crisis, increasing the efficiency of energy and sustainability are becoming significantly crucial. Therefore, the integration of various renewable energy resources into the traditional electrical grid is quite a challenging issue due to their intermittent nature. In this dissertation, the main focus is on the operational stage optimization problem considering the optimal power flow (OPF) problem to economically meet time-varying consumer demands. This brings a new level of complexity to the OPF problem that needs to be addressed by new and more performant optimization algorithms. One promising area of research that will be followed in this work is the use of heuristic optimization algorithms. These have been used both alone or in hybrid combinations of two optimization algorithms to compensate for the weaknesses of each.Due to nonlinearity introduced by alternating current power flow equations, this research focuses on improving the non-linear of the OPF problem for an electrical power grid that includes different energy sources along with thermal plants as energy generators. This dissertation illustrates how to improve the numerical stability of the proposed optimization approach by considering different variables to avoid ill-conditioned numerical operations. The proposed optimization approach, on the other hand, is able to deal with non-convex problems with multiple local optima, and also it is able to deal with the additional complexity of the hybrid power grid. This dissertation aimed at improving the use of stand-alone and hybrid AC/DC microgrid systems by minimizing some issues, e.g., global warming emissions and the increasing cost of power systems and losses during the entire time horizon. In this work, some assumptions have been made by considering line constraints on the network to theoretically prove that the performance of the polynomial optimization problem relaxation can satisfy the original power flow equations. Finally, the performance of the proposed algorithm has been examined on different electrical power networks with various power system sizes, such as IEEE 5, 14, and 30 bus. The outcomes of the experiments proved the adaptability of the algorithm when considering large-scale electrical power networks. In addition, this proposed algorithm has been compared with some exiting optimization algorithms given in the literature for similar power systems, where it shows the effectiveness of this proposed method. This achievement will strengthen the use of this convexification approach in its applications on large-scale systems to reduce energy expenses and network system losses.
Robust Implementation of the Model Predictive Control For DCDC Power Converters and Industrial Control Applications
(2022-03-26) Albira, Mohamed E.; Zohdy, Mohamed; Ganesan, Subramaniam; Barber, Gary; Li, Li
This dissertation addresses the development of the robustness and strength of the Model Predictive Control algorithm subjected to input constraints for a plant system with and without parameters' uncertainties. In the beginning, the MPC control system was implemented for systems with no types of parameters' uncertainties. The proposed system models were stable and linear and all of its parameters were fully known. They were formulated in model state-space system format. The main objective of this control system design was to maintain a smooth and constant output signal that could easily track theassigned desired output signal. The technical process of this control design was to calculate the optimal solutions for the proposed plant system by optimizing the Quadratic programming problem (QP) subjected to linear inequality constraints. Therefore, the proposed control system successfully forced the outputs of the proposed systems to track the output reference signals in a fast response and with very small steady-state errors, even with the change in prediction horizon values. The second control system approach was for a system model which assumed its parameters’ uncertainties. In the other words, the parameters were not precisely known, but they were bounded in a minimum and maximum range. The parameters' uncertainties and the converter's switching behaviors made it act as a highly nonlinear system. Therefore, the Adaptive Model Predictive controller (AMPC) with the Linear Parameter Varying (LPV) control algorithm was implemented to address these issues and to secure a sustainable output signal with on types of noise or degradations. In this algorithm, the LPV model was created out of a set of Linear Time-Invariant (LTI) models, which are used to update the AMPC controller based on the feedback signals that come from the plant model and the change in the system parameters. Due to the changes in the plant model parameters over time, the AMPC was the perfect control approach due to its capability to update its prediction model and the operating condition over a prediction horizon interval. Since the AMPC is an online optimization-based approach, the QP variables and parameters can be tuned based on changes of the system measurements in real-time, and the LPV scheduling parameters. The proposed AMPC and LPV algorithm was compared against different control system approaches. Also, the proposed AMPC and LPV algorithm was implemented using an Arduino Mega 2560 microcontroller to show its performance in a real-time environment. In summary, from the outputs and the results, the proposed AMPC and LPV control system showed higher levels of the performance interims of the purified output, faster responses, and the computational time in both the simulation and real time results. MATLAB, SIMULINK, and ARDUINO support packages were used for the system design and implementations.

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