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Articles 1 - 7 of 7
Full-Text Articles in VLSI and Circuits, Embedded and Hardware Systems
Analytical And Semi-Analytical Modeling Of Solar Cells Using The Lambert W Function: A Comprehensive Review Of Equivalent Circuits, Adel El-Shahat, Martin Ćalasan, Snežana Vujoševic, Shady H. E. Abdel Aleem
Analytical And Semi-Analytical Modeling Of Solar Cells Using The Lambert W Function: A Comprehensive Review Of Equivalent Circuits, Adel El-Shahat, Martin Ćalasan, Snežana Vujoševic, Shady H. E. Abdel Aleem
Engineering Technology Faculty Publications
The modeling of photovoltaic (PV) cells through equivalent circuits forms a central element in the analysis, simulation, and optimization of solar energy systems. Traditional approaches often depend on iterative numerical methods to solve the implicit current–voltage (I–V) equations. In contrast, the Lambert W function has emerged as an effective mathematical tool that enables closed-form or semi-analytical expressions for a wide range of PV models. This paper presents a Lambert W-centered review of analytical and semi-analytical formulations for PV equivalent-circuit models, covering classical single-diode and multi-diode structures and modern variants incorporating additional elements, voltage-dependent parameters, and topology rearrangements. The models are …
Analog Hardware Implementation Of A Linearly Constrained Quadratic Program Real-Time Solver, Claire E. Tylutki, Claire Tylutki
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 …
Artificial Intelligence Applications For Grid-Connected Solar Inverters, Utkirjon Ubaydullaev, Sarvinoz Mirzaeva, Hasan Mustafoev
Artificial Intelligence Applications For Grid-Connected Solar Inverters, Utkirjon Ubaydullaev, Sarvinoz Mirzaeva, Hasan Mustafoev
Chemical Technology, Control and Management
The increasing global demand for renewable energy has highlighted the importance of grid-connected solar inverters in ensuring efficient and stable power conversion. However, challenges such as fluctuations in solar energy generation, grid disturbances, and power quality issues necessitate advanced control strategies. The integration of artificial intelligence (AI) into solar inverters presents a transformative solution, enhancing performance, adaptability, and reliability in real-world applications.
This review explores the role of AI techniques, including machine learning (ML), deep learning (DL), fuzzy logic, and reinforcement learning (RL), in optimizing key inverter functionalities such as maximum power point tracking (MPPT), fault detection, power quality enhancement, …
Exploring Machine Learning Techniques For Embedded Hardware, Neel R. Vora
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 …
Switching Trajectory Control For High Voltage Silicon Carbide Power Devices With Novel Active Gate Drivers, Shuang Zhao
Switching Trajectory Control For High Voltage Silicon Carbide Power Devices With Novel Active Gate Drivers, Shuang Zhao
Graduate Theses and Dissertations
The penetration of silicon carbide (SiC) semiconductor devices is increasing in the power industry due to their lower parasitics, higher blocking voltage, and higher thermal conductivity over their silicon (Si) counterparts. Applications of high voltage SiC power devices, generally 10 kV or higher, can significantly reduce the amount of the cascaded levels of converters in the distributed system, simplify the system by reducing the number of the semiconductor devices, and increase the system reliability.
However, the gate drivers for high voltage SiC devices are not available on the market. Also, the characteristics of the third generation 10 kV SiC MOSFETs …
Design And Verification Environment For High-Performance Video-Based Embedded Systems, Michael Mefenza Nentedem
Design And Verification Environment For High-Performance Video-Based Embedded Systems, Michael Mefenza Nentedem
Graduate Theses and Dissertations
In this dissertation, a method and a tool to enable design and verification of computation demanding embedded vision-based systems is presented. Starting with an executable specification in OpenCV, we provide subsequent refinements and verification down to a system-on-chip prototype into an FPGA-Based smart camera. At each level of abstraction, properties of image processing applications are used along with structure composition to provide a generic architecture that can be automatically verified and mapped to the lower abstraction level. The result is a framework that encapsulates the computer vision library OpenCV at the highest level, integrates Accelera's System-C/TLM with UVM and QEMU-OS …
Approximation And Optimization Of An Auditory Model For Realization In Vlsi Hardware, Samuel L. Sangregory
Approximation And Optimization Of An Auditory Model For Realization In Vlsi Hardware, Samuel L. Sangregory
Theses and Dissertations
The Auditory Image Model (AIM) is a software tool set developed to functionally model the role of the ear in the human hearing process. AIM includes detailed filter equations for the major functional portions of the ear. Currently, AIM is run on a workstation and requires 10 to 100 times real-time to process audio information and produce an auditory image. An all-digital approximation of the AIM which is suitable for implementation in very large scale integrated circuits is presented. This document details the mathematical models of AIM and the approximations and optimizations used to simplify the filtering and signal processing …