Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Electrical and Computer Engineering (186)
- Power and Energy (61)
- Electrical and Electronics (47)
- Signal Processing (32)
- Computer Engineering (30)
-
- Controls and Control Theory (24)
- Nanotechnology Fabrication (24)
- Electromagnetics and Photonics (20)
- Electronic Devices and Semiconductor Manufacturing (20)
- Physical Sciences and Mathematics (18)
- VLSI and Circuits, Embedded and Hardware Systems (16)
- Computer Sciences (13)
- Computer and Systems Architecture (10)
- Aerospace Engineering (7)
- Hardware Systems (7)
- Artificial Intelligence and Robotics (6)
- Biomedical (6)
- Other Electrical and Computer Engineering (6)
- Physics (6)
- Digital Communications and Networking (5)
- Optics (5)
- Robotics (5)
- Biomedical Engineering and Bioengineering (4)
- Systems and Communications (4)
- Engineering Science and Materials (3)
- Graphics and Human Computer Interfaces (3)
- Navigation, Guidance, Control and Dynamics (3)
- Operations Research, Systems Engineering and Industrial Engineering (3)
- Space Vehicles (3)
- Keyword
-
- Simulation (6)
- Adiabatic Logic (4)
- Computational Electromagnetics (4)
- Distributed power generation (4)
- Fault Location (4)
-
- Fault location (4)
- Machine Vision (4)
- Optimization (4)
- Small Satellites (4)
- Structured Light Illumination (4)
- Battery (3)
- CubeSat (3)
- Deep Learning (3)
- Electric machines (3)
- Electromagnetics (3)
- GTAW (3)
- Image Processing (3)
- Machine learning (3)
- Modeling (3)
- Power electronics (3)
- SCAPS-1D (3)
- 3D Reconstruction (2)
- 3D finite element analysis (2)
- Adiabatic logic (2)
- Audio Signal Processing (2)
- Average-value model (2)
- Axial flux permanent magnet (2)
- Background Subtraction (2)
- Beamforming (2)
- Biosensor (2)
Articles 1 - 30 of 198
Full-Text Articles in Engineering
Nonuniform Sampling-Based Breast Cancer Classification, Santiago Posso
Nonuniform Sampling-Based Breast Cancer Classification, Santiago Posso
Theses and Dissertations--Electrical and Computer Engineering
The emergence of deep learning models and their success in visual object recognition have fueled the medical imaging community's interest in integrating these algorithms to improve medical diagnosis. However, natural images, which have been the main focus of deep learning models and mammograms, exhibit fundamental differences. First, breast tissue abnormalities are often smaller than salient objects in natural images. Second, breast images have significantly higher resolutions but are generally heavily downsampled to fit these images to deep learning models. Models that handle high-resolution mammograms require many exams and complex architectures. Additionally, spatially resizing mammograms leads to losing discriminative details essential …
Mitigation Of Reflected Overvoltage In Wind-Turbine Generator-Converter Systems With A Smart Coil Concept, Lulu Wei
Theses and Dissertations--Electrical and Computer Engineering
In the recent decade, ultra-fast wide bandgap switching devices such as Silicon Carbide (SiC) Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) have been increasingly utilized in power electronic converters for renewable energy power generation systems due to their advantages of enabling high energy efficiency and high power density. However, the much higher voltage slew rate (i.e., dv/dt) with SiC power converters may induce voltage reflection and reliability concerns in machine-converter systems, especially for medium-voltage systems with long cable connections. In wind-turbine power generation systems, generators are typically located in the nacelles, and medium-voltage power converters are mostly placed at the bottom of the …
Cross-Layer Design Of Highly Scalable And Energy-Efficient Ai Accelerator Systems Using Photonic Integrated Circuits, Sairam Sri Vatsavai
Cross-Layer Design Of Highly Scalable And Energy-Efficient Ai Accelerator Systems Using Photonic Integrated Circuits, Sairam Sri Vatsavai
Theses and Dissertations--Electrical and Computer Engineering
Artificial Intelligence (AI) has experienced remarkable success in recent years, solving complex computational problems across various domains, including computer vision, natural language processing, and pattern recognition. Much of this success can be attributed to the advancements in deep learning algorithms and models, particularly Artificial Neural Networks (ANNs). In recent times, deep ANNs have achieved unprecedented levels of accuracy, surpassing human capabilities in some cases. However, these deep ANN models come at a significant computational cost, with billions to trillions of parameters. Recent trends indicate that the number of parameters per ANN model will continue to grow exponentially in the foreseeable …
Reinventing Integrated Photonic Devices And Circuits For High Performance Communication And Computing Applications, Venkata Sai Praneeth Karempudi
Reinventing Integrated Photonic Devices And Circuits For High Performance Communication And Computing Applications, Venkata Sai Praneeth Karempudi
Theses and Dissertations--Electrical and Computer Engineering
The long-standing technological pillars for computing systems evolution, namely Moore's law and Von Neumann architecture, are breaking down under the pressure of meeting the capacity and energy efficiency demands of computing and communication architectures that are designed to process modern data-centric applications related to Artificial Intelligence (AI), Big Data, and Internet-of-Things (IoT). In response, both industry and academia have turned to 'more-than-Moore' technologies for realizing hardware architectures for communication and computing. Fortunately, Silicon Photonics (SiPh) has emerged as one highly promising ‘more-than-Moore’ technology. Recent progress has enabled SiPh-based interconnects to outperform traditional electrical interconnects, offering advantages like high bandwidth density, …
Application Of Conventional Feedforward And Deep Neural Networks To Power Distribution System State Estimation And State Forecasting, James Paul Carmichael
Application Of Conventional Feedforward And Deep Neural Networks To Power Distribution System State Estimation And State Forecasting, James Paul Carmichael
Theses and Dissertations--Electrical and Computer Engineering
Classical neural networks such as feedforward multilayer perceptron models (MLPs) are well established as universal approximators and as such, show promise in applications such as static state estimation in power transmission systems. This research investigates the application of conventional neural networks (MLPs) and deep learning based models such as convolutional neural networks (CNNs) and long short-term memory networks (LSTMs) to mitigate challenges in power distribution system state estimation and forecasting based upon conventional analytic methods. The ability of MLPs to perform regression to perform power system state estimation will be investigated. MLPs are considered based upon their promise to learn …
A Flexible Photonic Reduction Network Architecture For Spatial Gemm Accelerators For Deep Learning, Bobby Bose
A Flexible Photonic Reduction Network Architecture For Spatial Gemm Accelerators For Deep Learning, Bobby Bose
Theses and Dissertations--Electrical and Computer Engineering
As deep neural network (DNN) models increase significantly in complexity and size, it has become important to increase the computing capability of specialized hardware architectures typically used for DNN processing. The major linear operations of DNNs, which comprise the fully connected and convolution layers, are commonly converted into general matrix-matrix multiplication (GEMM) operations for acceleration. Specialized GEMM accelerators are typically employed to implement these GEMM operations, where a GEMM operation is decomposed into multiple vector-dot-product operations that run in parallel. A common challenge that arises in modern DNNs is the mismatch between the matrices used for GEMM operations and the …
A Phase Change Memory And Dram Based Framework For Energy-Efficient And High-Speed In-Memory Stochastic Computing, Supreeth Mysore
A Phase Change Memory And Dram Based Framework For Energy-Efficient And High-Speed In-Memory Stochastic Computing, Supreeth Mysore
Theses and Dissertations--Electrical and Computer Engineering
Convolutional Neural Networks (CNNs) have proven to be highly effective in various fields related to Artificial Intelligence (AI) and Machine Learning (ML). However, the significant computational and memory requirements of CNNs make their processing highly compute and memory-intensive. In particular, the multiply-accumulate (MAC) operation, which is a fundamental building block of CNNs, requires enormous arithmetic operations. As the input dataset size increases, the traditional processor-centric von-Neumann computing architecture becomes ill-suited for CNN-based applications. This results in exponentially higher latency and energy costs, making the processing of CNNs highly challenging.
To overcome these challenges, researchers have explored the Processing-In Memory (PIM) …
Building Energy Modeling And Studies Of Electric Power Distribution Systems With Distributed Energy Resources, Evan S. Jones
Building Energy Modeling And Studies Of Electric Power Distribution Systems With Distributed Energy Resources, Evan S. Jones
Theses and Dissertations--Electrical and Computer Engineering
There is significant opportunity for savings in energy and investment from improved performance of electric Power Distribution Systems (PDSs) through optimal planning and operation of conventional voltage-controlling devices. Novel multi-step model conversion and optimal capacitor planning (OCP) procedures are proposed for large-scale utility PDSs and are exemplified with an existing utility circuit of approximately 4,000 buses. Simulated optimal control and operation is achieved with a cluster-based approach that utilizes load-forecasting to minimize equipment degradation by intelligently dispersing device setting adjustments over time such that they remain most applicable. Improved performance may also be achieved through smart building technologies and Virtual …
Establishing The Foundation To Robotize Complex Welding Processes Through Learning From Human Welders Based On Deep Learning Techniques, Rui Yu
Theses and Dissertations--Electrical and Computer Engineering
As the demand for customized, efficient, and high-quality production increases, traditional manufacturing processes are transforming into smart manufacturing with the aid of advancements in information technology, such as cyber-physical systems (CPS), the Internet of Things (IoT), big data, and artificial intelligence (AI). The key requirement for integration with these advanced information technologies is to digitize manufacturing processes to enable analysis, control, and interaction with other digitized components. The integration of deep learning algorithm and massive industrial data will be critical components in realizing this process, leading to enhanced manufacturing in the Future of Work at the Human-Technology Frontier (FW-HTF).
This …
Optimal Design Of Special High Torque Density Electric Machines Based On Electromagnetic Fea, Murat G. Kesgin
Optimal Design Of Special High Torque Density Electric Machines Based On Electromagnetic Fea, Murat G. Kesgin
Theses and Dissertations--Electrical and Computer Engineering
Electric machines with high torque density are essential for many low-speed direct-drive systems, such as wind turbines, electric vehicles, and industrial automation. Permanent magnet (PM) machines that incorporate a magnetic gearing effect are particularly useful for these applications due to their potential for achieving extremely high torque density. However, when the number of rotor polarities is increased, there is a corresponding need to increase the number of stator slots and coils proportionally. This can result in manufacturing challenges. A new topology of an axial-flux vernier-type machine of MAGNUS type has been presented to address the mentioned limitation. These machines can …
Modeling The Early Visual System, Nicholas Lanning
Modeling The Early Visual System, Nicholas Lanning
Theses and Dissertations--Electrical and Computer Engineering
There are two encoding schema present in simple cells in the early visual system of vertebrates: the retinal simple cells activate highly when the receptive field contains a center surround stimulus, while the primary visual cortex’s (V1) simple cells activate highly when the receptive field contains visual edges. Work has been done in the past to enforce constraints on visual machine learning such that the retinal or V1 encoding is learned, but this work is often done to emulate retinal and V1 encoding in a vacuum. Recent work using convolutional neural networks focuses on anatomical constraints along with a supervised …
Hourly Dispatching Wind-Solar Hybrid Power System With Battery-Supercapacitor Hybrid Energy Storage, Pranoy Kumar Singha Roy
Hourly Dispatching Wind-Solar Hybrid Power System With Battery-Supercapacitor Hybrid Energy Storage, Pranoy Kumar Singha Roy
Theses and Dissertations--Electrical and Computer Engineering
This dissertation demonstrates a dispatching scheme of wind-solar hybrid power system (WSHPS) for a specific dispatching horizon for an entire day utilizing a hybrid energy storage system (HESS) configured by batteries and supercapacitors. Here, wind speed and solar irradiance are predicted one hour ahead of time using a multilayer perceptron Artificial Neural Network (ANN), which exhibits satisfactory performance with good convergence mapping between input and target output data. Furthermore, multiple state of charge (SOC) controllers as a function of energy storage system (ESS) SOC are developed to accurately estimate the grid reference power (PGrid,ref) for each dispatching period. …
Developing Reactive Distributed Aerial Robotics Platforms For Real-Time Contaminant Mapping, Joshua Ashley
Developing Reactive Distributed Aerial Robotics Platforms For Real-Time Contaminant Mapping, Joshua Ashley
Theses and Dissertations--Electrical and Computer Engineering
The focus of this research is to design a sensor data aggregation system and centralized sensor-driven trajectory planning algorithm for fixed-wing aircraft to optimally assist atmospheric simulators in mapping the local environment in real-time. The proposed application of this work is to be used in the event of a hazardous contaminant leak into the atmosphere as a fleet of sensing unmanned aerial vehicles (UAVs) could provide valuable information for evacuation measures. The data aggregation system was designed using a state-of-the-art networking protocol and radio with DigiMesh and a process/data management system in the ROS2 DDS. This system was tested to …
Models And Optimal Controls For Smart Homes And Their Integration Into The Electric Power Grid, Huangjie Gong
Models And Optimal Controls For Smart Homes And Their Integration Into The Electric Power Grid, Huangjie Gong
Theses and Dissertations--Electrical and Computer Engineering
Smart homes can operate as a distributed energy resource (DER), when equipped with controllable high-efficiency appliances, solar photovoltaic (PV) generators, electric vehicles (EV) and energy storage systems (ESS). The high penetration of such buildings changes the typical electric power load profile, which without appropriate controls, may become a “duck curve” when the surplus PV generation is high, or a “dragon curve” when the EV charging load is high. A smart home may contribute to an optimal solution of such problems through the energy storage capacity, provided by its by battery energy storage system (BESS), heating, ventilation, and air conditioning (HVAC) …
Synthesizing Dysarthric Speech Using Multi-Speaker Tts For Dsyarthric Speech Recognition, Mohammad Soleymanpour
Synthesizing Dysarthric Speech Using Multi-Speaker Tts For Dsyarthric Speech Recognition, Mohammad Soleymanpour
Theses and Dissertations--Electrical and Computer Engineering
Dysarthria is a motor speech disorder often characterized by reduced speech intelligibility through slow, uncoordinated control of speech production muscles. Automatic Speech recognition (ASR) systems may help dysarthric talkers communicate more effectively. However, robust dysarthria-specific ASR requires a significant amount of training speech is required, which is not readily available for dysarthric talkers.
In this dissertation, we investigate dysarthric speech augmentation and synthesis methods. To better understand differences in prosodic and acoustic characteristics of dysarthric spontaneous speech at varying severity levels, a comparative study between typical and dysarthric speech was conducted. These characteristics are important components for dysarthric speech modeling, …
Development Of Dc Circuit Breakers For Medium-Voltage Electrified Transportation, Trevor Morgan Arvin
Development Of Dc Circuit Breakers For Medium-Voltage Electrified Transportation, Trevor Morgan Arvin
Theses and Dissertations--Electrical and Computer Engineering
Medium-voltage DC (MVDC) distribution is an enabling technology for the electrification of transportation such as aircraft and shipboard. One main obstacle for DC distribution is the lack of adequate circuit fault protection. The challenges are due to the rapidly rising fault currents and absence of zero crossings in DC systems compared to AC counterparts. Existing DC breaker solutions lack comprehensive consideration of energy efficiency, power density, fault interruption speed, reliability, and implementation cost.
In this thesis, two circuit topologies of improved DC circuit breakers are developed: the resonant current source based hybrid DC breaker (RCS-HDCB) and the high temperature superconductor …
Determining Power System Fault Location Using Neural Network Approach, Edward O. Ojini
Determining Power System Fault Location Using Neural Network Approach, Edward O. Ojini
Theses and Dissertations--Electrical and Computer Engineering
Fault location remains an extremely pivotal feature of the electric power grid as it ensures efficient operation of the grid and prevents large downtimes during fault occurrences. This will ultimately enhance and increase the reliability of the system. Since the invention of the electric grid, many approaches to fault location have been studied and documented. These approaches are still effective and are implemented in present times, and as the power grid becomes even more broadened with new forms of energy generation, transmission, and distribution technologies, continued study on these methods is necessary. This thesis will focus on adopting the artificial …
Three Dimensional Photonics Structures: Design And Applications, Mansoor Sultan
Three Dimensional Photonics Structures: Design And Applications, Mansoor Sultan
Theses and Dissertations--Electrical and Computer Engineering
Photonics is an emerging technology for light control, emission, and detection. Photonic devices control photons the same way electronic circuits control electrons in active or passive mode depending on the energy requirement of the device. This dissertation will discuss the design, fabrication, testing of photonic structures with applications including imaging and renewable energy. First, we developed a novel lithography method for fluoropolymer resist based on variable pressure electron beam lithography (VP-EBL). VP-EBL proves to be an efficient method for patterning a widely used, but challenging to process, fluoropolymer, Teflon AF. However, rather than solely mitigating charging, the ambient gas is …
Explainable Data-Driven Motor Condition Monitoring And Fault Disgnosis, Yuming Wang
Explainable Data-Driven Motor Condition Monitoring And Fault Disgnosis, Yuming Wang
Theses and Dissertations--Electrical and Computer Engineering
Industrial motors are widely used in various fields such as power generation, mining, and manufacturing. Motor faults and time-consuming maintenance process will lead to serious economic losses in this context. To monitor motor faults and detect motor conditions, different types of sensors that can test vibration and current signals are mounted on motors. However, the main challenge was how to use information gained by sensors to analyze or diagnose motor conditions.
Machine learning is a popular technology in recent years, and it's very suitable for crunching and analyzing data. As an important subset of machine learning, deep learning is suitable …
Energy-Efficient And Secure Hardware Using Adiabatic Logic And Non-Volatile Mtj Devices, Zachary Kahleifeh
Energy-Efficient And Secure Hardware Using Adiabatic Logic And Non-Volatile Mtj Devices, Zachary Kahleifeh
Theses and Dissertations--Electrical and Computer Engineering
Internet of Things (IoT) is a collection of devices that exchange data through a network to implement complex applications. IoT devices increase the quality of life of their user base which has a wide variety such as the medical field, consumer electronics, and the manufacturing sector. However, IoT devices have several challenges that need to be overcome namely, security and energy consumption. The threat vector that IoT devices face is growing and includes the following threats, the leakage of information through a side-channel attack known as the Correlation Power Analysis (CPA), authentication, piracy, etc. A side-channel attack is an attack …
Parametric Average-Value Modeling, Simulation, And Characterization Of Machine-Rectifier Systems, Isuje Ojo
Parametric Average-Value Modeling, Simulation, And Characterization Of Machine-Rectifier Systems, Isuje Ojo
Theses and Dissertations--Electrical and Computer Engineering
There are many techniques for modeling and simulation of synchronous machine-rectifier systems. The more common approaches are the detailed and average-value modeling techniques. The detailed simulation technique takes into account the details of the diode switching and is both very accurate and very expensive in terms of computational resources. To alleviate this disadvantage, the average-value modeling technique is often utilized. In this approach, the details of diode switching are neglected or averaged. In that light, the work presented herein proposes a unique saliency-sensitive parametric average-value model (SSPAVM) of the synchronous machine-rectifier system. This model extends existing parametric average-value models to …
Accelerometer-Based Vigilance State Classification In Dairy Cows, Evan King
Accelerometer-Based Vigilance State Classification In Dairy Cows, Evan King
Theses and Dissertations--Electrical and Computer Engineering
Globally, dairy farming is a $700 billion industry, with more than 9 million dairy cows in the United States alone. Depriving cows of required activities such as sleep has been shown to negatively impact reproductive efficiency, decrease the volume of milk produced, and increase the risk of culling. Overcrowded herds can decrease individual animal health, demanding the need for automatic behavior detection that would provide insight into their state of health.
Using electroencephalography (EEG), electrooculography (EOG), and electromyography (EMG) to characterize the phases of sleep is a technique which has been used for decades. While these techniques are considered the …
Toward Intelligent Welding By Building Its Digital Twin, Qiyue Wang
Toward Intelligent Welding By Building Its Digital Twin, Qiyue Wang
Theses and Dissertations--Electrical and Computer Engineering
To meet the increasing requirements for production on individualization, efficiency and quality, traditional manufacturing processes are evolving to smart manufacturing with the support from the information technology advancements including cyber-physical systems (CPS), Internet of Things (IoT), big industrial data, and artificial intelligence (AI). The pre-requirement for integrating with these advanced information technologies is to digitalize manufacturing processes such that they can be analyzed, controlled, and interacted with other digitalized components. Digital twin is developed as a general framework to do that by building the digital replicas for the physical entities. This work takes welding manufacturing as the case study to …
Development Of A Hybrid-Electric Aircraft Propulsion System Based On Silicon Carbide Triple Active Bridge Multiport Power Converter, Cole M. Ivey
Theses and Dissertations--Electrical and Computer Engineering
Constrained by the low energy density of Lithium-ion batteries with all-electric aircraft propulsion, hybrid-electric aircraft propulsion drive becomes one of the most promising technologies in aviation electrification, especially for wide-body airplanes. In this thesis, a three-port triple active bridge (TAB) DC-DC converter is developed to manage the power flow between the turbo generator, battery, and the propulsion motor. The TAB converter is modeled based on the emerging Silicon Carbide (SiC) Metal-Oxide-Semiconductor Field Effect Transistor (MOSFET) modules operating at high switching frequency, so the size of the magnetic transformer can be significantly reduced. Different operation modes of this hybrid-electric propulsion drive …
Combining Approximate Computing And Adiabatic Logic For Low-Power And Energy-Efficient Iot Edge Computing, Wu Yang
Theses and Dissertations--Electrical and Computer Engineering
The growing data-intensive applications that run on IoT edge devices require the circuit to be low-power consumption and energy-efficient for limited resources. As conventional Complementary Metal-Oxide-Semiconductor (CMOS) scales down to the nanometer technology node, it reaches its limits, such as leakage and power consumption. Adiabatic logic and approximate computing are emerging techniques for the low-power circuit. Adiabatic logic can recycle energy which is a promising solution for building energy-efficient circuits. However, the power clock scheme and dual-rail structure of adiabatic logic increase the overall area. Power consumption is further reduced by applying approximate computing while reducing the complexity and size …
Boundary Integral Equation Method For Electrostatic Field Prediction In Piecewise-Homogeneous Electrolytes, Christopher Keith Pratt
Boundary Integral Equation Method For Electrostatic Field Prediction In Piecewise-Homogeneous Electrolytes, Christopher Keith Pratt
Theses and Dissertations--Electrical and Computer Engineering
This thesis presents a method to predict electrostatic fields, potentials, and currents in regions containing piecewise-homogeneous electrolytes. Additionally, an efficient electric field calculation is presented. A boundary integral equation is formulated for the boundary potentials and currents and is discretized using the Locally Corrected Nyström method. Solution convergence with respect to the mesh discretization and basis order is investigated. The techniques are validated through analysis of problems with either analytic solutions, with published data, or with other solution methods.
Fabrication And Simulation Of Perovskite Solar Cells, Maniell Workman
Fabrication And Simulation Of Perovskite Solar Cells, Maniell Workman
Theses and Dissertations--Electrical and Computer Engineering
Since the dawning of the industrial revolution, the world has had a need for mass energy production. In the 1950s silicon solar panels were invented. Silicon solar panels have been the main source of solar energy production. They have set the standard for power conversion efficiency for subsequent generations of photovoltaic technology. Solar panels utilize light’s ability to generate an electron hole pair. By creating a PN Junction in the photovoltaic semiconductor, the electron and hole are directed in opposing layers of the solar panel generating the electric current. Second generation solar panels utilized different thin film materials to fabricate …
Novel Machine Learning And Wearable Sensor Based Solutions For Smart Healthcare Monitoring, Rajdeep Kumar Nath
Novel Machine Learning And Wearable Sensor Based Solutions For Smart Healthcare Monitoring, Rajdeep Kumar Nath
Theses and Dissertations--Electrical and Computer Engineering
The advent of IoT has enabled the design of connected and integrated smart health monitoring systems. These health monitoring systems can be utilized for monitoring the mental and physical wellbeing of a person. Stress, anxiety, and hypertension are the major elements responsible for the plethora of physical and mental illnesses. In this context, the older population demands special attention because of the several age-related complications that exacerbate the effects of stress, anxiety, and hypertension. Monitoring stress, anxiety, and blood pressure regularly can prevent long-term damage by initiating necessary intervention or clinical treatment beforehand. This will improve the quality of life …
Traveling Wave Fault Location Method For Distribution Systems With Distributed Generation, Oluwafeyisayo Afolabi
Traveling Wave Fault Location Method For Distribution Systems With Distributed Generation, Oluwafeyisayo Afolabi
Theses and Dissertations--Electrical and Computer Engineering
Fault location is an important topic within electric power systems, as accurate fault location techniques will improve the reliability of the system and reduce downtime caused by outages. This paper explores fault location in distribution systems with distributed generation using the traveling wave fault location method. The single-ended and double-ended traveling wave methods are evaluated using a single-circuit distribution system which is modeled using MATLAB SIMULINK. The results are compared using a basis of signals and bus pairs across fault types, sampling rates and fault resistances.
Electric Power Systems And Components For Electric Aircraft, Damien Lawhorn
Electric Power Systems And Components For Electric Aircraft, Damien Lawhorn
Theses and Dissertations--Electrical and Computer Engineering
Electric aircraft have gained increasing attention in recent years due to their potential for environmental and economic benefits over conventional airplanes. In order to offer competitive flight times and payload capabilities, electric aircraft power systems (EAPS) must exhibit extremely high efficiencies and power densities. While advancements in enabling technologies have progressed the development of high performance EAPS, further research is required.
One challenge in the design of EAPS is determining the best topology to be employed. This work proposes a new graph theory based method for the optimal design of EAPS. This method takes into account data surveyed from a …