Electrical and Computer Engineering Commons^™

Electrical Machines For Harsh Environments, Ayman M. El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

There have been several megatrends over the past several years that have been driving research activities in the area of electrical machines and drives. These include transportation electrification (land vehicles, aerospace, ships, locomotives), expanded role of renewables (wind, solar, wave…etc.), and smart grid among others. One of those megatrends that continues to become more critical is electrical machines for harsh environments. In many applications, production has been moved to remote locations and harsh environments. These include subsea oil exploration, sour/acid gas compression, downhole and geothermal pumps, underground mining, and aerospace applications. This paper will provide an overview of electrical machine …

High-Torque-Density Low-Cost Magnetic Gear Utilizing Hybrid Magnets And Advanced Materials, Ali Hussain Al-Qarni, Fan Wu, Ayman M. El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

Two major challenges of existing high-performance magnetic gears are: (i) High content of rare-earth permanent magnets which results in high cost as well as price fluctuation; (ii) Conflict between mechanical and electromagnetic performances, especially in the design of highspeed rotor. A magnetic gear using a blend of magnet types, i.e NdFeB, or Dy-free NdFeB and ferrites, is proposed in this paper. The goal is to bring down the cost while retaining comparable torque-transducing performance to a baseline magnetic gear only using rare-earth NdFeB magnets. A variety of topologies based on different combinations of magnet types and geometric shapes have been …

Computationally Efficient Optimization Of A Five-Phase Flux-Switching Pm Machine Under Different Operating Conditions, Hao Chen, Xiangdong Liu, Nabeel Demerdash, Ayman M. El-Refaie, Zhen Chen, Jiangbiao He

Electrical and Computer Engineering Faculty Research and Publications

This paper investigates the comparative design optimizations of a five-phase outer-rotor flux-switching permanent magnet (FSPM) machine for in-wheel traction applications. To improve the comprehensive performance of the motor, two kinds of large-scale design optimizations under different operating conditions are performed and compared, including the traditional optimization performed at the rated operating point and the optimization targeting the whole driving cycles. Three driving cycles are taken into account, namely, the urban dynamometer driving schedule (UDDS), the highway fuel economy driving schedule (HWFET), and the combined UDDS/HWFET, representing the city, highway, and combined city/highway driving, respectively. Meanwhile, the computationally efficient finite-element analysis …

Towards Fully Additively-Manufactured Permanent Magnet Synchronous Machines: Opportunities And Challenges, Fan Wu, Ayman M. El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

With the growing interest in electrification and as hybrid and pure electric powertrains are adopted in more applications, electrical machine design is facing challenges in terms of meeting very demanding performance metrics for example high specific power, harsh environments, etc. This provides clear motivation to explore the impact of advanced materials and manufacturing on the performance of electrical machines. This paper provides an overview of additive manufacturing (AM) approaches that can be used for constructing permanent magnet (PM) machines, with a specific focus on additively-manufactured iron core, winding, insulation, PM as well as cooling systems. Since there has only been …

A Survey Of Prediction And Classification Techniques In Multicore Processor Systems, Cristinel Ababei, Milad Ghorbani Moghaddam

Electrical and Computer Engineering Faculty Research and Publications

In multicore processor systems, being able to accurately predict the future provides new optimization opportunities, which otherwise could not be exploited. For example, an oracle able to predict a certain application's behavior running on a smart phone could direct the power manager to switch to appropriate dynamic voltage and frequency scaling modes that would guarantee minimum levels of desired performance while saving energy consumption and thereby prolonging battery life. Using predictions enables systems to become proactive rather than continue to operate in a reactive manner. This prediction-based proactive approach has become increasingly popular in the design and optimization of integrated …

Survey Of Insulation Systems In Electrical Machines, Rasul Hemmati, Fan Wu, Ayman M. El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

Insulating materials and insulation systems design have been gaining more attentions as more electrical machines tend to operate in harsher environments for various applications. Harsh environments include high temperature, humidity, erosion, low air pressure, etc. This paper discusses recent advances in insulation systems for electrical machines. Insulation tests as well as test standards that have been used to evaluate insulation systems and detect insulation failures will be discussed. Insulating materials used for a wide range of industrial applications such as wind turbine generators, aerospace hybrid/electric powertrain, and hydro generators have been summarized. For the emerging high-altitude, highvoltage aerospace applications, partial …

Quantitative Detection Of Complex Mixtures Using A Single Chemical Sensor: Analysis Of Response Transients Using Multi-Stage Estimation, Karthick Sothivelr, Florian Bender, Fabien Josse, Edwin E. Yaz, Antonio J. Ricco

Electrical and Computer Engineering Faculty Research and Publications

Most chemical sensors are only partially selective to any specific target analyte(s), making identification and quantification of analyte mixtures challenging, a problem often addressed using arrays of partially selective sensors. This work presents and experimentally verifies a signal-processing technique based on estimation theory for online identification and quantification of multiple analytes using only the response data collected from a single polymer-coated sensor device. The demonstrated technique, based on multiple stages of exponentially weighted recursive least-squares estimation (EW-RLSE), first determines which of the analytes included in the sensor response model are absent from the mixture being analyzed; these are then eliminated …

Metal-Insulator Transition (Mit) Materials For Biomedical Applications, Mohiuddin Munna, Protap Mahanta, Ronald A. Coutu Jr.

Electrical and Computer Engineering Faculty Research and Publications

Transitional metal oxides get considerable interest in electronics and other engineering applications over few decades. These materials show several orders of magnitude metal-insulator transition (MIT) triggered by external stimuli. Bio-sensing using Vanadium dioxide (VO₂), a MIT material is largely unexplored. In this short article, we investigate the VO₂ based thermal sensor performance for measuring the biomolecule concentration. Active sensing layer is chromium and niobium co-doped VO₂ as it shows 11.9%/°C temperature coefficient of resistance (TCR) with practically no thermal hysteresis. Our study demonstrated that VO₂ based microsensors can be used to measure the biomolecule concentrations, …

Nematic Liquid Crystal Composite Materials For Dc And Rf Switching, Mohiuddin Munna, Farhana Anwar, Ronald A. Coutu Jr.

Electrical and Computer Engineering Faculty Research and Publications

Liquid Crystals (LCs) are widely used in display devices, electro-optic modulators, and optical switches. A field-induced electrical conductivity modulation in pure liquid crystals is very low which makes it less preferable for direct current (DC) and radio-frequency (RF) switching applications. According to the literature, a conductivity enhancement is possible by nanoparticle doping. Considering this aspect, we reviewed published works focused on an electric field-induced conductivity modulation in carbon nanotube-doped liquid crystal composites (LC-CNT composites). A two to four order of magnitude switching in electrical conductivity is observed by several groups. Both in-plane and out-of-plane device configurations are used. In plane …

Testing Photovoltaic Pavers For Roadway Applications, Ronald A. Coutu Jr., David Newman, James Crovetti, Ashish Kumar Mishra, Mohiuddin Munna, Allyssa Delbridge-Ramos, Julie Brusaw, Scott Brusaw

Electrical and Computer Engineering Faculty Research and Publications

Concrete and asphalt are the primary materials used to construct roadways for motor vehicles, bike paths for pedestrians and bicyclists, and runways for aircraft. Solar Roadways®, Inc. (SR) in Sandpoint, ID, proposed using robust, Solar Road Panels (SRPs) as an alternative roadway material due to the potential for creating a modular, multi-functional infrastructure product with cost-savings, user-safety, power-generation, and a better alternative in terms of environmental sustainability when compared to contemporary pavement materials. Typical roadway construction materials, on average, need to be replaced every 10-15 years while also requiring regular annual maintenance to maintain proper safety standards. SR’s novel roadway …

Statistical Algorithm For Nonuniformity Correction In Focal-Plane Arrays, Majeed M. Hayat, Sergio N. Torres, Ernest Armstrong, Stephen C. Cain, Brian Yasuda

Electrical and Computer Engineering Faculty Research and Publications

A statistical algorithm has been developed to compensate for the fixed-pattern noise associated with spatial nonuniformity and temporal drift in the response of focal-plane array infrared imaging systems. The algorithm uses initial scene data to generate initial estimates of the gain, the offset, and the variance of the additive electronic noise of each detector element. The algorithm then updates these parameters by use of subsequent frames and uses the updated parameters to restore the true image by use of a least-mean-square error finite-impulse-response filter. The algorithm is applied to infrared data, and the restored images compare favorably with those restored …

Computationally Efficient Strand Eddy Current Loss Calculation In Electric Machines, Alireza Fatemi, Dan M. Ionel, Nabeel Demerdash, Dave A. Staton, Rafal Wrobel, Yew Chuan Chong

Electrical and Computer Engineering Faculty Research and Publications

A fast finite element (FE) based method for the calculation of eddy current losses in the stator windings of randomly wound electric machines is presented in this paper. The method is particularly suitable for implementation in large-scale design optimization algorithms where a qualitative characterization of such losses at higher speeds is most beneficial for identification of the design solutions that exhibit the lowest overall losses including the ac losses in the stator windings. Unlike the common practice of assuming a constant slot fill factor s _f for all the design variations, the maximum s _f in the developed method is …

Hybrid Field Oriented And Direct Torque Control For Sensorless Bldc Motors Used In Aerial Drones, Kellen Carey, Nathan M. Zimmerman, Cristinel Ababei

Electrical and Computer Engineering Faculty Research and Publications

In this study, a sensorless hybrid control scheme for brushless direct current (BLDC) motors for use in multirotor aerial vehicles is introduced. In such applications, the control scheme must satisfy high-performance demands for a wide range of rotor speeds and must be robust to motor parameter uncertainties and measurement noise. The proposed controller combines field-oriented control (FOC) and direct torque control (DTC) techniques to take benefit of the advantages offered by each of these techniques individually. Simulation results demonstrate the effectiveness of the proposed control scheme over a wide range of rotor speeds as well as good robustness against parameter …

Freelabel: A Publicly Available Annotation Tool Based On Freehand Traces, Philipe A. Dias, Zhou Shen, Amy Tabb, Henry P. Medeiros

Electrical and Computer Engineering Faculty Research and Publications

Large-scale annotation of image segmentation datasets is often prohibitively expensive, as it usually requires a huge number of worker hours to obtain high-quality results. Abundant and reliable data has been, however, crucial for the advances on image understanding tasks recently achieved by deep learning models. In this paper, we introduce FreeLabel, an intuitive open-source web interface that allows users to obtain high-quality segmentation masks with just a few freehand scribbles, in a matter of seconds. The efficacy of FreeLabel is quantitatively demonstrated by experimental results on the PASCAL dataset as well as on a dataset from the agricultural domain. Designed …

Investigation Of Fault-Tolerant Capabilities In An Advanced Three-Level Active T-Type Converter, Ramin Katebi, Jiangbiao He, Nathan Weise

Electrical and Computer Engineering Faculty Research and Publications

A novel fault-tolerant three-level power converter topology, named advanced three-level active T-Type (A₃L-ATT) converter, is introduced to increase the reliability of multilevel power converters used in safety-critical applications. This new fault-tolerant multilevel power converter is derived from the conventional T-Type converter topology. The topology has significantly improved the fault-tolerant capability under any open circuit or certain short-circuit faults in the semiconductor devices. In addition, under healthy condition, the redundant phase leg can be utilized to share overload current with other main legs, which enhances the overload capability of the converter. The conduction losses in the original outer devices …

High Specific Power Electrical Machines: A System Perspective, Ayman M. El-Refaie, Mohamed Osama

Electrical and Computer Engineering Faculty Research and Publications

There has been a growing need for high specific power electrical machines for a wide range of applications. These include hybrid/electric traction applications, aerospace applications and Oil and Gas applications. A lot of work has been done to accomplish significantly higher specific power electrical machines especially for aerospace applications. Several machine topologies as well as thermal management schemes have been proposed. Even though there has been a few publications that provided an overview of high-speed and high specific power electrical machines [1-3], the goal of this paper is to provide a more comprehensive review of high specific power electrical machines …

A Bidirectional Soft-Switched Dab-Based Single-Stage Three-Phase Ac–Dc Converter For V2g Application, Dibaker Das, Nathan Weise, Kaushik Basu, Rohit Baranwal, Ned Mohan

Electrical and Computer Engineering Faculty Research and Publications

In vehicle-to-grid applications, the battery charger of the electric vehicle (EV) needs to have a bidirectional power flow capability. Galvanic isolation is necessary for safety. An ac-dc bidirectional power converter with high-frequency isolation results in high power density, a key requirement for an on-board charger of an EV. Dual-active-bridge (DAB) converters are preferred in medium power and high voltage isolated dc-dc converters due to high power density and better efficiency. This paper presents a DAB-based three-phase ac-dc isolated converter with a novel modulation strategy that results in: 1) single-stage power conversion with no electrolytic capacitor, improving the reliability and power …

Toward A Sustainable More Electrified Future: The Role Of Electrical Machines And Drives, Ayman M. El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

This article provided an overview of the broad range of applications in which advanced electrical machines and drives play a key role. There are many applications that require steep change in the performance of electrical machines and drives. In addition to novel topologies and design optimization, a broad range of enabling technologies, including advanced materials and thermal management, will play a key role in meeting the ever-growing requirements of the aforementioned applications. Judging by the breadth of the applications and the very demanding requirements in terms of system footprint, efficiency cost, and reliability R&D efforts in the area of advanced …

Permanent Magnet Vernier Machine: A Review, Fan Wu, Ayman M. El-Refaie

Electrical and Computer Engineering Faculty Research and Publications

Permanent magnet vernier machines (PMVMs) gained a lot of interest over the past couple of decades. This is mainly due to their high torque density enabled by the magnetic gearing effect. This study will provide a thorough review of recent advances in PMVMs. This review will cover the principle of operation and nature of magnetic gearing in PMVMs, and a better understanding of novel PMVM topologies using different winding configuration as well as different modulation poles and rotor structures. Detailed discussions on the choice of gear ratio, slot-pole combinations, design optimisation and role of advanced materials in PMVMs will be …

Novel Test Fixture For Characterizing Mems Switch Microcontact Reliability And Performance, Protap Mahanta, Farhana Anwar, Ronald A. Coutu Jr.

Electrical and Computer Engineering Faculty Research and Publications

In microelectromechanical systems (MEMS) switches, the microcontact is crucial in determining reliability and performance. In the past, actual MEMS devices and atomic force microscopes (AFM)/scanning probe microscopes (SPM)/nanoindentation-based test fixtures have been used to collect relevant microcontact data. In this work, we designed a unique microcontact support structure for improved post-mortem analysis. The effects of contact closure timing on various switching conditions (e.g., cold-switching and hot-switching) was investigated with respect to the test signal. Mechanical contact closing time was found to be approximately 1 us for the contact force ranging from 10–900 μN. On the other hand, for the 1 …

Direct-To-Patient Survey For Diagnosis Of Benign Paroxysmal Positional Vertigo, Heidi Richburg, Richard J. Povinelli, David Friedland

Electrical and Computer Engineering Faculty Research and Publications

Given the high incidence of dizziness and its frequent misdiagnosis, we aim to create a clinical support system to classify the presence or absence of benign paroxysmal positional vertigo with high accuracy and specificity. This paper describes a three-phase study currently underway for classification of benign paroxysmal positional vertigo, which includes diagnosis by a specialist in a clinical setting. Patient background information is collected by a survey on an Android tablet and machine learning techniques are applied for classification. Decision trees and wrappers are employed for their ability to provide information about the question set. One goal of the study …

Age Grading An. Gambiae And An. Arabiensis Using Near Infrared Spectra And Artificial Neural Networks, Masabho Peter Milali, Maggy T. Sikulu-Lord, Samson S. Kiware, Floyd E. Dowell, George F. Corliss, Richard J. Povinelli

Electrical and Computer Engineering Faculty Research and Publications

Background

Near infrared spectroscopy (NIRS) is currently complementing techniques to age-grade mosquitoes. NIRS classifies lab-reared and semi-field raised mosquitoes into < or ≥ 7 days old with an average accuracy of 80%, achieved by training a regression model using partial least squares (PLS) and interpreted as a binary classifier.

Methods and findings

We explore whether using an artificial neural network (ANN) analysis instead of PLS regression improves the current accuracy of NIRS models for age-grading malaria transmitting mosquitoes. We also explore if directly training a binary classifier instead of training a regression model and interpreting it as a binary classifier improves the accuracy. A total of 786 and 870 NIR spectra collected from laboratory reared An. gambiae and An. arabiensis, respectively, were used and pre-processed according …

Predicting Cascading Failures In Power Grids Using Machine Learning Algorithms, Rezoan Ahmed Shuvro, Pankaz Das, Majeed M. Hayat, Mitun Talukder

Electrical and Computer Engineering Faculty Research and Publications

Although there has been notable progress in modeling cascading failures in power grids, few works included using machine learning algorithms. In this paper, cascading failures that lead to massive blackouts in power grids are predicted and classified into no, small, and large cascades using machine learning algorithms. Cascading-failure data is generated using a cascading failure simulator framework developed earlier. The data set includes the power grid operating parameters such as loading level, level of load shedding, the capacity of the failed lines, and the topological parameters such as edge betweenness centrality and the average shortest distance for numerous combinations of …

Sdn Testbed For Evaluation Of Large Exo-Atmospheric Emp Attacks, Diogo Oliveira, Nasir Ghani, Majeed M. Hayat, Jorge Crichigno, Elias Bou-Harb

Electrical and Computer Engineering Faculty Research and Publications

Large-scale nuclear electromagnetic pulse (EMP) attacks and natural disasters can cause extensive network failures across wide geographic regions. Although operational networks are designed to handle most single or dual faults, recent efforts have also focused on more capable multi-failure disaster recovery schemes. Concurrently, advances in software-defined networking (SDN) technologies have delivered highly-adaptable frameworks for implementing new and improved service provisioning and recovery paradigms in real-world settings. Hence this study leverages these new innovations to develop a robust disaster recovery (counter-EMP) framework for large backbone networks. Detailed findings from an experimental testbed study are also presented.

Microscale Direct Measurement Of Localized Photothermal Heating In Tissue-Mimetic Hydrogels, Benyamin Davaji, James E. Richie, Chung-Hoon Lee

Electrical and Computer Engineering Faculty Research and Publications

Photothermal hyperthermia is proven to be an effective diagnostic tool for cancer therapy. The efficacy of this method directly relies on understanding the localization of the photothermal effect in the targeted region. Realizing the safe and effective concentration of nano-particles and the irradiation intensity and time requires spatiotemporal temperature monitoring during and after laser irradiation. Due to uniformities of the nanoparticle distribution and the complexities of the microenvironment, a direct temperature measurement in micro-scale is crucial for achieving precise thermal dose control. In this study, a 50 nm thin film nickel resistive temperature sensor was fabricated on a 300 nm …

An Electron‐Rich Calix[4]Arene‐Based Receptor With Unprecedented Binding Affinity For Nitric Oxide, Denan Wang, Lena V. Ivanova, Maxim V. Ivanov, Saber Mirzaei, Qadir K. Timerghazin, Scott A. Reid, Rajendra Rathore

Electrical and Computer Engineering Faculty Research and Publications

Calixarenes have found widespread application as building blocks for the design and synthesis of functional materials in host–guest chemistry. The ongoing desire to develop a detailed understanding of the nature of NO bonding to multichromophoric π‐stacked assemblies led us to develop an electron‐rich methoxy derivative of calix[4]arene (3), which we show exists as a single conformer in solution at ambient temperature. Here, we examine the redox properties of this derivative, generate its cation radical (3^+.) using robust chemical oxidants, and determine the relative efficacy of its NO binding in comparison with model calixarenes. We find …

Impacts Of Operators’ Behavior On Reliability Of Power Grids During Cascading Failures, Zhuoyao Wang, Mahshid Rahnamay-Naeini, Joana M. Abreu, Rezoan A. Shuvro, Pankaz Das, Andrea Mammoli, Nasir Ghani, Majeed M. Hayat

Electrical and Computer Engineering Faculty Research and Publications

Human operators play a key role in the reliable operation of critical infrastructures. However, human operators may take actions that are far from optimum. This can be due to various factors affecting the operators' performance in time-sensitive and critical situations such as reacting to contingencies with significant monetary and social impacts. In this paper, an analytic framework is proposed based on Markov chains for modeling the dynamics of cascading failures in power grids. The model captures the effects of operators' behavior quantified by the probability of human error under various circumstances. In particular, the observations from historical data and information …

Field Oriented Sliding Mode Control Of Surface-Mounted Permanent Magnet Ac Motors: Theory And Applications To Electrified Vehicles, Xin Wang, Max Reitz, Edwin E. Yaz

Electrical and Computer Engineering Faculty Research and Publications

Permanent magnet ac motors have been extensively utilized for adjustable-speed traction motor drives, due to their inherent advantages including higher power density, superior efficiency and reliability, more precise and rapid torque control, larger power factor, longer bearing, and insulation life-time. Without any proportional-and-integral (PI) controllers, this paper introduces novel first- and higher-order field-oriented sliding mode control schemes. Compared with the traditional PI-based vector control techniques, it is shown that the proposed field oriented sliding mode control methods improve the dynamic torque and speed response, and enhance the robustness to parameter variations, modeling uncertainties, and external load perturbations. While both first- …

Multispecies Fruit Flower Detection Using A Refined Semantic Segmentation Network, Philipe A. Dias, Amy Tabb, Henry P. Medeiros

Electrical and Computer Engineering Faculty Research and Publications

In fruit production, critical crop management decisions are guided by bloom intensity, i.e., the number of flowers present in an orchard. Despite its importance, bloom intensity is still typically estimated by means of human visual inspection. Existing automated computer vision systems for flower identification are based on hand-engineered techniques that work only under specific conditions and with limited performance. This letter proposes an automated technique for flower identification that is robust to uncontrolled environments and applicable to different flower species. Our method relies on an end-to-end residual convolutional neural network (CNN) that represents the state-of-the-art in semantic segmentation. To enhance …

Obtaining Chemical Selectivity From A Single, Nonselective Sensing Film: Two-Stage Adaptive Estimation Scheme With Multiparameter Measurement To Quantify Mixture Components And Interferents, Karthick Sothivelr, Florian Bender, Fabien Josse, Edwin E. Yaz, Antonio J. Ricco

Electrical and Computer Engineering Faculty Research and Publications

A new approach is reported to detect and quantify the members of a group of small-aromatic-molecule target analytes: benzene, toluene, ethylbenzene, and xylenes (BTEX), dissolved in water, in the presence of interferents, using only the data collected from a single polymer-coated SH-SAW (shear horizontal surface acoustic wave) device and a two-stage adaptive estimation scheme. This technique is composed of exponentially weighted recursive least-squares estimation (EW-RLSE) and a bank of Kalman filters (BKFs) and does not require any prior knowledge of the initial concentration range of the target analytes. The proposed approach utilizes the transient sensor response to sorption and/or desorption …