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Lei, FeiranInjection Locked Synchronous Oscillators (SOs) and Reference Injected Phase-Locke Loops (PLL-RIs)
Doctor of Philosophy, The Ohio State University, 2017, Electrical and Computer Engineering
Synchronization plays an important and fundamental role as the timing basis in digital, analog, and RF integrated circuits (ICs), where Phase-Locked Loops (PLLs) find their versatile applications. The noise sources in a traditional PLL are mainly divided into two groups: noise before the low-pass loop filter such as the noise in the reference signal, Frequency Divider (FD), Phase Frequency Detector/Charge Pump (PFD/CP); and noise after the filter such as the Voltage Controlled Oscillator (VCO) noise and the loop filter noise. The output phase noise of the PLL is the combined contribution from these two equally important in-band and out-band noise sources. This research studies the effect of the synchronization in the PLL on the decoupling of the 3dB bandwidths for different noise sources to achieve an optimum phase noise and improved locking behavior with an attenuated reference signal injection (RI) into a ring-type delay-line Voltage Controlled Synchronous Oscillator (VCSO). This dissertation begins with the development of a generalized phase model for both LC-type and ring-type VCSOs. Next, the relationship between the device baseband noise (flicker and thermal noise) and a ring-type oscillator's phase noise is derived. In addition, noise shaping functions are introduced to describe signal injection into the VCSO to achieve suppression of the oscillator in-band phase noise. Then, the transient and steady-state behavior of a Charge-Pump PLL-RI are explained with nonlinear differential equations and the phase-plane method. The nonlinear phase equation is linearized for the small-signal condition and the s-domain noise transfer functions as well as noise bandwidths are derived for different noise sources in the major components of the PLL-RI. The effect of the loop parameters and the injection strength on the output phase noise, loop settling time, and lock in range is analyzed. The analysis is verified by the SPICE simulation and experimental results from a Charge-Pump PLL-RI using a 1GHz VCSO in GlobalFoundries 130nm standard CMOS technology. The designed VCSO occupies a core area of 0.005 mm$^2$, and operates from 0.5GHz to 1.7GHz. The PLL-RI, for first-harmonic locking applications, has a core area of 0.02 mm$^2$ and consumes 2.6mW power. When a 30dB attenuation is applied, phase noise at 1MHz and 10MHz offset are reduced from -118.8dBc/Hz (PLL) to -121.9dBc/Hz (PLL-RI), and -102.3dBc/Hz (PLL) to -128.3dBc/Hz (PLL-RI), respectively, with an integrated RMS jitter from 10KHz to 30MHz of 1.55ps. Finally, another application of the PLL-RI as an integer-N frequency synthesizer is studied and tested. The PLL-RI based frequency synthesizer with the ring-type VCSO achieves comparable noise performance with LC type PLLs, but uses a much smaller chip area and features lower power consumption. To summarize, this dissertation has throughly evaluated an oscillator and a PLL under small signal injection. Compared with the traditional PLL, the all-CMOS PLL-RI offers faster settling time, wider lock in range, and ability to decouple 3dB bandwidths for different noise sources to achieve an optimum noise performance. The applications of PLL-RIs can be extended to analog, digital, and RF systems for different timing schemes.

Committee:

Marvin White (Advisor); Waleed Khalil (Committee Member); Steven Bibyk (Committee Member)

Subjects:

Electrical Engineering

Keywords:

CMOS ICs; PLLs, Frequency Synthesizers, reference injection locking; phase noise suppression; jitter; low-frequency 1-f noise; thermal noise; RF measurements; device modeling parameter extraction; low power; adaptive tracking range; design and fabrication

Jamalzadeh, RezaMicrogrid Optimal Power Flow Based On Generalized Benders Decomposition
Doctor of Philosophy, Case Western Reserve University, 2018, EECS - System and Control Engineering
The future distribution system is envisioned to be a network of distributed energy resources (DER), being able to operate in both the grid connected and islanded modes. In essence, the future electrical distribution systems will operate as medium-voltage (MV) microgrids. This dissertation presents a study of the optimal power flow (OPF) based on generalized benders decomposition (GBD) for optimally scheduling DERs and managing voltage regulation device operations to enable the economic and secure operations of the future MV distribution systems. Key model considerations include multi-phase unbalanced distribution system network, conservation voltage reduction (CVR), and multi-interval energy scheduling. Further, the optimal operating decisions are studied when the MV microgrid is in different operational modes, such as the 1) grid-connected mode, 2) islanded mode, and 3) grid-connected to islanded mode transition. Excellent algorithm performance has been achieved on the IEEE test feeder models. The use of an external engine for solving the unbalanced power flow and obtaining the sensitivities for the decomposed sub-problems allows the OPF to handle scaled-up models with the increased number of decision variables, constraints, and network buses. To support solution of large-scale problems, parallel computational strategies are recommended in order to achieve solution performance required by operations. Among the output of the GBD-based OPF, the primal solution provides optimal operation set point decisions while the dual solution provides system marginal-cost based energy prices such as the locational marginal prices (LMP) for single-phase nodes. These important OPF outcomes can facilitate the economic electricity market design in the distribution system involving both DERs and end-use demands. In this dissertation, a new method based on the GBD-based OPF has also been proposed using the unbalanced power system model linearized around the near-optimal operational state to calculate LMPs for single-phase buses and support the economic market design of the distribution system. Also in this dissertation, the approximation of nodal voltage sensitivities is studied based on observations made about the radial distribution system. As a result, voltage sensitivities can be efficiently computed for all network nodes simply based on the power flow solution and topology searches. The results are validated on the IEEE test feeder models using the perturbation analysis. The proposed method can be applied to large unbalanced radial distribution systems for supporting distribution system planning and operation.

Committee:

Mingguo Hong, PhD (Advisor); Kenneth Loparo, PhD (Committee Member); Vira Chankong, PhD (Committee Member); Evren Gurkan-Cavusoglu, PhD (Committee Member)

Subjects:

Electrical Engineering; Energy

Keywords:

Active distribution system operation; conservation voltage reduction; distributed energy resources; generalized benders decomposition; locational marginal price; microgrid; optimal power flow; unbalanced distribution system; voltage sensitivity

Trombley, MichaelDesign of a Programmable Four-Preset Guitar Pedal
Master of Science in Electrical Engineering (MSEE), Wright State University, 2017, Electrical Engineering
Many companies in the music industry offer programmable preset guitar pedals. Presets allow musicians to save time and focus on their act by recalling predetermined settings during a performance. A majority of the companies in the music industry offer up to hundreds of presets, but realistically the substantial amount of presets may have a negative effect on the musician’s performance due to time constraints. The main contribution of this thesis is to address the musician by reducing the amount of presets offered in a guitar pedal design. Combining two systems, a digital control and audio processing circuit, will produce a programmable four-preset guitar pedal. Cost and size are design constraints that will also be taken into consideration. The techniques observed in this thesis will benefit the music industry because they can be adapted into other guitar pedal designs. This thesis closes with an evaluation of the final design, feedback from musicians in the community, and suggestions for future improvements.

Committee:

Marian Kazimierczuk, Ph.D. (Advisor); Joe Tritschler, Ph.D. (Committee Member); Yan Zhuang, Ph.D. (Committee Member)

Subjects:

Electrical Engineering

Keywords:

Guitar; Music; Microcontroller; Programming; Audio; DSP; Digital Signal Processing; Audio Signal Processing;

Dalwadi, NeelNull Values and Null Vectors of Matrix Pencils and their Applications in Linear System Theory
Master of Science in Engineering (MSEgr), Wright State University, 2017, Electrical Engineering
Considerable literature exists in linear algebra to solve the generalized eigenvalue, eigenvector problem (F - λ G)v = 0 where F, G ∈ ℜ(s × s), are square matrices. However, a number of applications lend themselves to the case where F, G ∈ ℜ(s × t), and st. The existing methods cannot be used for such non-square cases. This research explores structural decomposition of a matrix pencil (F - λ G), s ≠ t to compute finite values of λ for which rank(F - λ G) < min(s,t). Moreover, from the decomposition of the matrix pencil, information about the order of λ at infinity, the Kronecker row and column indices of a matrix pencil can also be extracted. Equally important is the computation of non-zero vectors w ∈ ℜ(1 × s) and v ∈ ℜ(t × 1) corresponding to each finite value of λ, such that w(F - λ G) = 0 and (F - λ G)v = 0. Algorithms are developed for the computation of λ, w, and v using numerically efficient techniques. Proposed algorithms are applied to problems encountered in system theory and illustrated by means of numerical examples.

Committee:

Pradeep Misra, Ph.D. (Advisor); Xiaodong Zhang, Ph.D. (Committee Member); Luther Palmer III, Ph.D. (Committee Member)

Subjects:

Electrical Engineering; Mathematics

Keywords:

Null Values; Null Vectors; Eigenvalue; Eigenvector; Generalized Eigenvector; Non square; Matrix Pencil; Non square Matrix Pencil; values; vectors; Kronecker Canonical Form; Indices

Khalili, MohsenDistributed Adaptive Fault-Tolerant Control of Nonlinear Uncertain Multi-Agent Systems
Doctor of Philosophy (PhD), Wright State University, 2017, Engineering PhD
The research on distributed multi-agent systems has received increasing attention due to its broad applications in numerous areas, such as unmanned ground and aerial vehicles, smart grid, sensor networks, etc. Since such distributed multi-agent systems need to operate reliably at all time, despite the possible occurrence of faulty behaviors in some agents, the development of fault-tolerant control schemes is a crucial step in achieving reliable and safe operations. The objective of this research is to develop a distributed adaptive fault-tolerant control (FTC) scheme for nonlinear uncertain multi-agent systems under intercommunication graphs with asymmetric weights. Under suitable assumptions, the closed-loop system's stability and leader-follower cooperative tracking properties are rigorously established. First, a distributed adaptive fault-tolerant control method for nonlinear uncertain first-order multi-agent systems is developed. Second, this distributed FTC method is extended to nonlinear uncertain second-order multi-agent systems. Next, adaptive-approximation-based FTC algorithms are developed for two cases of high-order multi-agent systems, i.e., with full-state measurement and with only limited output measurement, respectively. Finally, the distributed adaptive fault-tolerant formation tracking algorithms for first-order multi-agent systems are implemented and demonstrated using Wright State's real-time indoor autonomous robots test environment. The experimental formation tracking results illustrate the effectiveness of the proposed methods.

Committee:

Xiaodong Zhang, Ph.D. (Advisor); Kuldip Rattan, Ph.D. (Committee Member); Pradeep Misra, Ph.D. (Committee Member); Yongcan Cao, Ph.D. (Committee Member); Raul Ordonez, Ph.D. (Committee Member); Mark Mears, Ph.D. (Committee Member)

Subjects:

Electrical Engineering; Engineering

Keywords:

Fault-Tolerant Control; Adaptive Control; Multi-Agent Systems; Nonlinear Uncertain Systems; Formation Control; Learning Systems; Cooperative Tracking; Leader-Follower Consensus; Asymmetric Communication Graphs; Fault Diagnosis; Mobile Robots

Imbulgoda Liyangahawatte, Gihan Janith MendisHardware Implementation and Applications of Deep Belief Networks
Master of Science in Engineering, University of Akron, 2016, Electrical Engineering
Deep learning is a subset of machine learning that contributes widely to the contemporary success of artificial intelligence. The essential idea of deep learning is to process complex data by abstracting hierarchical features via deep neural network structure. As one type of deep learning technique, deep belief network (DBN) has been widely used in various application fields. This thesis proposes an approximation based hardware realization of DBNs that requires low hardware complexity. This thesis also explores a set of novel applications of the DBN-based classifier that will benefit from a fast implementation of DBN. In my work, I have explored the application of DBN in the fields of automatic modulation classification method for cognitive radio, Doppler radar sensor for detection and classification of micro unmanned aerial systems, cyber security applications to detect false data injection (FDI) attacks and localize flooding attacks, and applications in social networking for prediction of link properties. The work in this thesis paves the way for further investigation and realization of deep learning techniques to address critical issues in various novel application fields.

Committee:

Jin Wei (Advisor); Arjuna Madanayaka (Committee Co-Chair); Subramaniya Hariharan (Committee Member)

Subjects:

Artificial Intelligence; Computer Engineering; Electrical Engineering; Engineering; Experiments; Information Technology

Keywords:

deep belief networks; multiplierless digital architecture; Xilinx FPGA implementations; low-complexity; applications of deep belief networks; spectral correlation function; modulation classification; drone detection; doppler radar; cyber security

Pyles, David T.Effects of the Kinematic Model on Forward-Model Based Spotlight SAR ECM
Master of Science in Electrical Engineering (MSEE), Wright State University, 2017, Electrical Engineering
Spotlight synthetic aperture radar (SAR) provides a high-resolution remote image formation capability for airborne platforms. SAR image formation processes exploit the amplitude, time, and frequency shifts that occur in the transmitted waveform due to electromagnetic propagation and scattering. These shifts are predictable through the SAR forward model which is dependent on the waveform parameters and emitter flight path. The approach to develop an electronic countermeasure (ECM) system that is founded on the SAR forward model implies that the ECM system should alter the radar’s waveform in a manner that produces the same amplitude, time, and frequency shifts that a real scatterer would produce at a desired location. A collection of such scatterers would be capable of forming a larger collective energy distribution in the final image. However, since the forward model is dependent on the radar platform’s kinematic model, the jamming energy distribution created from a forward-model based ECM system will inherently have some level of sensitivity to kinematic error. This thesis discusses a forward-model based ECM modulation scheme and provides an assessment of its sensitivity through Monte Carlo simulations and an entropy-based image similarity distance.

Committee:

Michael A. Saville, Ph.D. (Committee Chair); Brian Rigling, Ph.D. (Committee Member); Steve Gorman, Ph.D. (Committee Member)

Subjects:

Electrical Engineering

Keywords:

electrical engineering; spotlight synthetic aperture radar; SAR

Rafique, SubrinaGrowth, Characterization and Device Demonstration of Ultra-Wide Bandgap ß-Ga2O3 by Low Pressure Chemical Vapor Deposition
Doctor of Philosophy, Case Western Reserve University, EECS - Electrical Engineering

High power semiconductor device technology has significant impact on the society as they can directly contribute to worldwide energy conservation. The main market segments for high-power, high-frequency semiconductor devices are industrial motors, hybrid and electric vehicles, RF and power supply, wireless infrastructure and broadcast and communication satellites. Si-based technology has been serving the power electronics market till today. However, Si based power devices are approaching their theoretical performance limits from the viewpoint of material properties. Wide bandgap (WBG) semiconductors featured with higher breakdown electric field have tremendous advantages over existing Si based technology. They can operate at higher voltages, temperatures and switching frequencies with greater efficiencies resulting in less loss. They also enable significantly reduced system level volumes due to decreased cooling requirements and smaller passive components contributing to overall lower system costs. Once widely used, wide bandgap semiconductor based power electronics technologies can save over 25% of the worldwide annual energy consumption.

Ultra-wide bandgap (UWBG) semiconductor material gallium oxide (Ga2O3) with a room temperature bandgap of ~4.9 eV, much higher than GaN (Eg~3.4 eV) and SiC (Eg~3.2 eV), is a promising candidate for next generation power devices and deep ultraviolet (DUV) photodetectors (PDs). It possesses excellent material properties and outstanding chemical and thermal stability at elevated temperatures. Most attractively, Ga2O3 substrate can be produced by low cost and scalable melting based methods. In this dissertation, a new epitaxial method based on low pressure chemical vapor deposition (LPCVD) is developed and demonstrated for the first time to grow high quality Ga2O3 based thin films and nanomaterials with fast growth rate and controllable doping. For the LPCVD growth of Ga2O3, argon (Ar) is employed as carrier gas. High purity gallium pellets (Alfa Aesar, 99.99999%) are used as the group III precursor. Oxygen (O2) and Silicon Tetrachloride (SiCl4) are the group VI precursor and n-dopant source, respectively. Proof of concept prototypes of ß-Ga2O3 thin films based PDs and Schottky barrier diode (SBD) have been demonstrated using LPCVD grown Ga2O3 thin films. The maximum room temperature electron Hall mobility achieved for LPCVD heteroepitaxial Ga2O3 thin films is 106.6 cm2/V·s with an n-type carrier concentration of 4.83x1017 cm-3. The room temperature carrier concentrations achieved so far for the (010) and (001) LPCVD homoepitaxial thin films are ~1.4x1018 cm-3 and ~6.6x1017 cm-3 with mobilities of ~72 cm2/V. s and ~42 cm2/V. s respectively. Advancement of LPCVD growth of high quality ß-Ga2O3 will open up new opportunities for high performance power electronic and optoelectronic devices.

Committee:

Hongping Zhao (Advisor)

Subjects:

Electrical Engineering

Prasad, Anurag ShivamMAKING MILLIMETER WAVE COMMUNICATION POSSIBLE FOR NON-LINE-OF-SIGHT SCENARIOS: 5G
Master of Science, Miami University, 2017, Computational Science and Engineering
This thesis, provides for an enhanced version of the 5G Channel Simulator, NYUSIM, developed by NYU Wireless Lab for Millimeter Wave outdoor communications at New York University. This research is performed in the physical layer for Non-Line-of-Sight scenarios. Our goal is to increase the received signal power and establish a viable transmission link, reducing the degrading effects of multipath and atmospheric noise. To achieve this goal, a search algorithm is implemented to find the main spatial energy lobe with maximum power concentration and separate it from other spatial lobes that mostly contain noise. This will act as a reference point in order to perform adaptive beamforming needed for increasing the total received signal power and noise reduction.

Committee:

Donald Ucci (Advisor); Dmitriy Garmatyuk (Committee Member); Qihou Zhou (Committee Member)

Subjects:

Electrical Engineering; Engineering

Keywords:

5G;mmWaves;NYUSIM;Search Algorithm;Phased Array Antenna;Adaptive Beamforming

Casto, Matthew JamesMulti-Attribute Design for Authentication and Reliability (MADAR)
Doctor of Philosophy, The Ohio State University, 2018, Electrical and Computer Engineering
Increased globalization of design, production, and independent distribution of integrated circuits (ICs) has provided adversarial and criminal opportunity for strategic, malicious, and monetary gain through counterfeiting, cloning, and tampering, producing a supply chain vulnerable to malicious or improper function and degraded reliability. Military, commercial avionics, medical, banking, and automotive systems rely on components providing high security, high reliability operation, and the impact can be large in terms of safety, readiness, mission success, and overall lifecycle cost when tampered parts find their way into the supply chain. Likewise, commodity platforms, such as the Internet of Things (IoT), rely on each networked component providing trustworthy authentication and identification, which has proven to be extremely vulnerable to cloning and spoofing when implemented through software or firmware solutions. Across these platforms, major effort has been focused on enhancing hardware assurance through intrinsic and unique physical hardware traits. Previous hardware authentication and identification techniques have targeted digital solutions that require increased logic overhead in order to obtain adequate uniqueness, have a limited number of implementation architectures, and suffer from significant environmental instabilities. In this work, the process-induced variation response of analog mixed-signal (AMS) circuits is investigated to yield foundational anti-counterfeiting, anti-cloning, design and characterization techniques. It explores unique behaviors termed Process Specific Functions (PSFs) to identify and group circuits of the same pedigree and provide traits for authentication, individual chip identification, and reliability monitoring. PSFs are demonstrated through the expansion of fundamental quantization sampling theory to produce a statistically bounded digital to analog converter model as implemented within a transmitter architecture. Simulation capabilities showed predictable circuit traits, including random process variations for authentication and unique ID. The model showed 90% Probability of Detection (PoD) with less than a 10% false alarm rate for an individual process specific cloning scenario, demonstrating foundational design capability for AMS counterfeit prevention and identification. The work makes significant progress towards quantifying design specific authentication behavior for the first time in analog ICs. A parameter space of harmonic amplitude responses is correlated to random and systematic process variations to produce challenge driven non-linear quantifiable and measurable distribution responses. These unique authenticity and reliability characteristics are related to physical process models in a low power 90nm CMOS, and are expanded for unique identification in a 130nm SiGe process technology. Collectively, this work provides an in-situ novel and foundational analog integrated circuit (IC) supply chain risk management (SCRM) and hardware security design framework.

Committee:

Waleed Khalil (Advisor)

Subjects:

Electrical Engineering

Keywords:

Authentication; Unique ID; Hardware Security; Analog Mixed-Signal; Supply chain risk management; trusted electronics; digital to analog converter; Reliability

Mao, DavinBistatic SAR Polar Format Image Formation: Distortion Correction and Scene Size Limits
Master of Science in Electrical Engineering (MSEE), Wright State University, 2017, Electrical Engineering
The polar format algorithm (PFA) for bistatic synthetic aperture radar (SAR) image formation offers the compromise between image quality and computational complexity afforded by PFA, while enabling the geometric flexibility of a bistatic collection scenario. The use of the far-field approximation (FFA), which enables the use of the two-dimensional (2D) fast Fourier transform (FFT) in PFA, introduces spatially-varying distortion and defocus effects causing geometric warping and blurring in the resulting image. In this thesis, the residual phase errors due to the FFA are analyzed by decomposing the residual phase errors in the time dimension into their constant, linear, and quadratic Taylor series components. Based on the analysis, a 2D interpolation-based distortion correction technique is developed, and accurate scene size limits are derived for the corrected image to mitigate the effects of defocus. The phase error analysis is conducted with respect to arbitrary transmitter and receiver trajectories, and examples are demonstrated for both the ideal linear and ideal circular flight geometries using a point target scene simulation.

Committee:

Brian Rigling, Ph.D. (Advisor); Michael Saville, Ph.D. (Committee Member); Joshua Ash, Ph.D. (Committee Member)

Subjects:

Electrical Engineering; Remote Sensing

Keywords:

bistatic radar, synthetic aperture radar, polar format algorithm, distortion, defocus, scene size limits

Bhattarai, SmrityDigital Architecture for real-time face detection for deep video packet inspection systems
Master of Science, University of Akron, 2017, Electrical Engineering
Face detection and optional recognition is a highly researched area in digital image processing. Face detection allows gathering of statistical data from video sequences, with applications in a variety of areas such as bio-metrics, information security, and video surveillance. The growing abundance of video sensors that are connected to the internet require high-throughput real-time processing of a multitude of digital video feeds, where each feed provides independent real-time statistics of the number of persons shown in the feed. Typical applications include pedestrian counting, public transit monitoring, crowd control, and sporting events. Video surveillance and security applications in particular can benefit from real-time algorithms that can process large amounts of data. Thousands of video sources must be monitored for extracting situational awareness information for homeland security and public safety applications, and the manual monitoring of such a vast amount of data is nearly impossible. Algorithms for both face detection [1–4] and recognition [3, 5–7] take two main approaches involving the local detection of facial features based on a geometric model of the human face [8] and a holistic based feature recognition, where the image data is treated as an entity without isolating different regions of the face. The main challenge in feature based facial detection is identification and location of human faces regardless of their pose, facial expression, orientation, imaging condition or presence of structural components [9]. Some advanced image-based pattern recognition techniques have been developed to handle difficult scenarios like multiple faces, faces of different sizes, and even detection in heavily cluttered backgrounds. [8] In this thesis, we explore how hardware computing architecture for detection of an image, as a face or non-face, is designed. The computing architecture is first designed, modeled, and tested in MATLAB simulink using Xilinx blockset. Images were later tested using a Virtex-6 FPGA ML605 Evaluation Kit. A field-programmable gate array (FPGA) is an integrated circuit designed to be configured by a user or a designer after manufacturing. The system uses the features of a face and non-face, which were previously extracted by training the set of face and non-face patterns. The system is fully feature based and does not require any assumptions for processing. In this approach, all the images are treated in the same way. They are not separated into different categories before processing them. The system is basically a combination of different modules like convolution, sub-sampling, bias add, scaling, neuron and decision combined in a specific format to classify the images as a face or non-face on the basis of the output. The algorithm is simple without any need for preprocessing of the image. The performance trade-off exists between the computational precision, chip area, clock speed, and power consumption.

Committee:

Dr. Arjuna Madanayake (Advisor); Dr. Ryan C Toonen (Committee Member); Dr. Kye-Shin Lee (Committee Member)

Subjects:

Electrical Engineering

Keywords:

Face detection, Convolutional Neural Network, Image processing

Abdelfattah, MoatazSwitched-Capacitor DC-DC Converters for Near-Threshold Design
Doctor of Philosophy, The Ohio State University, 2017, Electrical and Computer Engineering
With the increasing power and thermal limits in the computing industry, energy-efficient computing has become an urging necessity. Therefore, a surge of interest has been recently given to the concept of Near-Threshold Computing (NTC) as a potential candidate to realize energy-efficiency in computations. By operating at supply voltages near the transistor’s threshold voltage, NTC promises significant energy savings with moderate performance loss, which can be compensated for through parallelism. However, NTC faces a few challenges that hinder its wide adoption. On top of these challenges are the harsh specifications required for the power management and delivery units. Specifically, a power converter in an NTC system is required to achieve high efficiency at high current densities and low output voltages while seamlessly integrated on-chip, which are all contradicting specifications. To tackle the problem of energy-efficient computing, this research work addresses the challenges of NTC, with focus on power delivery. To do so, first, the target application of NTC is investigated to acquire the basic understanding of its challenges, opening doors for innovations and solutions for these challenges. Based on this understanding, which reveals the importance of power delivery for NTC and defines the requirements on power converters, most of the work in this thesis will focus on Switched-Capacitor (SC) power converters, which are found to be the most suitable type of converters for NTC. Therefore, a detailed study and literature review of SC converters is carried out. This study provides an in-depth understanding of SC converters operation, mechanisms, and challenges. Specifically, it is demonstrated that the most advantageous characteristic of SC converters is their compatibility with CMOS integration, while the most challenging aspect is their limited current density. Consequently, this thesis sets forth to address this challenge and proposes two solutions to boost the current density of SC converters, and thus, offering feasible power converter architectures for NTC. The first solution proposed in this thesis focuses on the control loop of SC converters. Unlike regular control loops, which often utilize frequency, capacitance, or conductance modulation, the proposed technique combines all three control knobs. The combination of these parameters allows for ripple reduction without sacrificing current density, and thus, effectively increases the converter’s density. Furthermore, this combination of parameters maintains the efficiency near its peak across a wide range of load currents, which is another relevant feature for NTC. The second solution introduces the concept of resonant gate drivers to SC converters, increasing the converter efficiency with no impact on current density. This solution is implemented in 45 nm SOI technology and fabricated for validation. The measurement results demonstrate a 70% efficiency at 1 A/mm2 current density and 0.4 V output voltage, which is a new efficiency/current-density record in the near-threshold range. In summary, as a potential solution to the problem of energy-efficiency in computations, NTC and its challenges are investigated. To address its most critical challenge of power delivery, SC converters are studied and circuit techniques are proposed to boost their current density and offer a feasible power delivery for NTC applications.

Committee:

Waleed Khalil (Advisor)

Subjects:

Electrical Engineering

Keywords:

DC-DC Converter, Switched-Capacitor, Power Management, Fully-integrated, Near-Threshold Design, Near-Threshold Computing, Integrated Voltage Regulator

Rohit , Akanksha Optimization and Characterization of a Capillary Contact Micro-Plotter for Printed Electronic Devices
Master of Science (MS), Ohio University, 2017, Electrical Engineering & Computer Science (Engineering and Technology)
Printed electronics is emerging as an integral part of the electronic industry due to its low cost fabrication and flexibility of devices against the rigid and expensive technology using silicon. Various methods for printing have existed for a long time with inkjet printing being the most common method used for electronic devices. This thesis explores a new and innovative printed technology using a capillary based microplotting approach implemented via Sonoplot Microplotter II. Unlike the inkjet printing technique which prints in overlapping spots with resolution between 30µm-100µm, the Microplotting approach helps to prints continuous features with a higher resolution as low as 5 ¿¿. Capillary action is used to fill picoliter amount of ink into a micropipette which is used for printing. Thus, the focus of this thesis is the optimization of this new printing technology under various conductions using different conductive inks and on a broad range of substrates and different tip diameters. In addition, passive resistive, capacitive and inductive components were printed to characterize the printing process and operation of electrical devices under different conditions. The applications of this Microplotter was further demonstrated by printing a flexible resistive strain sensor. The procedures involved for the fabrication of micropipettes using a glass puller for different diameter tips attached to the dispenser head is also explained in this thesis.

Committee:

Savas Kaya (Advisor); Chris Bartone (Committee Member); Jeffrey Dill (Committee Member); Eric Stinaff (Committee Member)

Subjects:

Electrical Engineering; Nanotechnology

Keywords:

Printed Electronics; Microplotter; Capacitive; Indictive; Resistive; Micropipettes

Khalili, FatemehDesign and Simulation of Coded-Modulation Using Turbo Trellis Coding and Multi- Layer Modulations
Doctor of Philosophy (PhD), Ohio University, 2017, Electrical Engineering & Computer Science (Engineering and Technology)
For modern wireless communication systems bandwidth efficiency and energy efficiency are the vital requirements for reasonable performance. Bandwidth determined by the rate at which information can be sent via the channel and the maximum rate at which error free information can be communicated is introduced as channel capacity by Shannon. Bandwidth efficiency or spectral efficiency is often satisfied by exploiting appropriate modulation scheme. Energy efficiency or power efficiency depends on the amount of power that a system uses which is a critical issue for wireless and cellular communications. It also shows the system tolerance against the environment noise. Energy efficiency can be improved by applying error correcting codes that produces lower error probability at the receiver for a fixed signal to noise ratio. In order to achieve both requirements, the idea of coded modulation technique which combines QPSK and OFDM modulation with a low rate, short block systematic turbo code, is proposed. We aim to achieve exceptional energy efficiency in extremely noisy environments, where moderate data rates and short messages are required. For this proposed model, the performance improvement is produced by a unique mapping of trellis structure error correcting code and spectral efficiency is achieved by exploiting OFDM modulation. The designed OFDM distributes systematic and parity symbols along all sub-channels symmetrically and adjusts their power distinctively to achieve superior bit error performance. Further, we utilize four-dimensional M-ary Quadrature Amplitude Modulation (4D-MQAM) for parity symbols which effectively increases the overall rate of the system while maintaining the same level of energy efficiency. Moreover, we apply puncturing for parity symbols to increase overall rate of the system and improve bandwidth efficiency. Also, we applied non-systematic coding structure to increase coding rate with less puncturing rate while maintaining the error rate as low as possible. The resulting performance of our designed system compared with the theoretical sphere packing lower bound indicates a very small gap (less than 0.5 dB) which means a substantially close approach to the Shannon limit.

Committee:

Jeffrey Dill, Dr (Advisor)

Subjects:

Electrical Engineering

Keywords:

Coded Modulation; Turbo Trellis Coding; Multi-Layer Modulation; Sphere Packing Bound

Li, MaoSpatial-temporal classification enhancement via 3-D iterative filtering for multi-temporal Very-High-Resolution satellite images
Master of Science, The Ohio State University, 2018, Electrical and Computer Engineering
It has been widely studied utilizing spatial-temporal remote sensing images to interpret ground objects. Due to the spectral ambiguities caused by inevitable factors like meteorological conditions, sunlight illumination, sensor radiation performance and earth objects reflectance, the interpretation accuracy of multi-class classification using a single temporal image is unsatisfactory. Under the hypothesis that earth objects have the temporal consistency, this thesis proposes a classification accuracy enhancement approach that utilizes 3-D temporal very-high-resolution images, where the digital surface model is generated through stereo dense matching. In the first place, the probability distribution of images’ coverage areas is derived from the supervised Random Forest Classifier. Then, the proposed method iteratively filters the probability maps with a 3-D bilateral filter which is built upon the domain of spectrum, spatial and height information of surface. Compared with single filtering enhancement studied before, continuously message passing from data in different dates can be achieved by iteratively filtering until the probability converge. It is conducted that each of the three experiments on 8 temporal consistent images presents convincing different types of city layout in Port-au-Prince, the capital of Haiti, including open grounds, dense residential and educational areas. After classification enhancement, the overall classification accuracy is increased by 2%~6%. The presenting results illustrate that although the study areas experienced a devastating earthquake leading to significant changes in the city landscape, the constraint on surface height effectively eliminates pre-enhancing classification errors. Furthermore, although the first filtering contributes the most on classification accuracy enhancement, this approach is manifested to consistently enhance the classification performance for similar earth objects like road and ground, permanent shelters and buildings through further iterations.

Committee:

Rongjun Qin, Dr. (Advisor); Desheng Liu, Dr. (Committee Co-Chair)

Subjects:

Computer Engineering; Computer Science; Electrical Engineering; Geographic Information Science; Geography; Remote Sensing

Keywords:

Image Enhance; Spatiotemporal probability bilateral filter; Random Forest, Classification

Sargent, Garrett CraigSingle-Image Super-Resolution via Regularized Extreme Learning Regression for Imagery from Microgrid Polarimeters
Master of Science (M.S.), University of Dayton, 2017, Electrical and Computer Engineering

Division of focal plane imaging polarimeters have the distinct advantage of being capable of obtaining temporally synchronized intensity measurements across a scene; however, they sacrifice spatial resolution in doing so due to their spatially modulated arrangement of the pixel-to-pixel polarizers and often result in aliased imagery. This shortcoming is often overcome through advanced demosaicing strategies that minimize the effects of false polarization while preserving as much high frequency content as possible. While these techniques can yield acceptable imagery, they tend to be computationally complex and the spatial resolution is often reduced below the native capabilities of the focal plane array. This thesis proposes a super-resolution method based upon a previously trained regularized extreme learning regression (RELR) that aims to recover missing high-frequency content beyond the spatial resolution of the sensor and correct low-frequency content, while maintaining good contrast between polarized and unpolarized artifacts presented in this thesis. For each of the four channels of the image, the modified RELR predicts the missing high-frequency and lowfrequency components that result from upsampling. These missing high-frequency components are then refined with a high pass filter and added back to the upsampled image. This provides a fast and computationally simple way of recovering missing high frequency components that are lost with current state-of-the-art demosaicing algorithms. The modified RELR provides better results than other visible band single-image super-resolution techniques and is much faster, thus making it applicable to real-time applications. The obtained results demonstrate the effectiveness of the modified RELR for a truth scenario (no aliasing resulting from undersampling) and a derived microgrid scenario (aliasing resulting from undersampling). The truth scenario shows that the modified RELR performs exceptionally better than other algorithms, however, the derived microgrid scenario demonstrates the problems that result from aliasing for single-image super-resolution algorithms. In general, for the degree of linear polarization (DoLP) image product, aliasing greatly distorts objects within a scene and none of the super-resolution algorithms could do anything to correct for it. The modified RELR showed superior performance against other super-resolution algorithms investigated at maintaining contrast between the polarized and unpolarized artifacts, which is of great importance. Future work is dedicated to coming up with fast ways to handle aliasing that is present in true microgrid imagery.

Committee:

Vijayan Asari, Ph.D. (Advisor); Bradley Ratliff, Ph.D. (Committee Member); Eric Balster, Ph.D. (Committee Member); Theus Aspiras, Ph.D. (Committee Member)

Subjects:

Electrical Engineering; Engineering

Keywords:

single image super resolution; microgrid polarimeter; machine learning; extreme learning machine

Chunchu, Vinay KumarLayout Implementation of A 10-Bit 1.2 GS/s Digital-to-Analog Converter In 90nm CMOS
Master of Science in Electrical Engineering (MSEE), Wright State University, 2017, Electrical Engineering
Digital-to-analog converters are the interface circuits between digital and analog domains. They are used in data communication applications and different sorts of applications where transformation amongst digital and analog signals is needed. High-speed data converters are needed to match the bandwidth demands of the present-day communication systems. This thesis presents the layout implementation of a 10-bit current steering DAC with a sampling rate of about 1.2 GS/s using CMOS 90 nm technology. Current steering DAC topology is used in high-speed applications. The DAC in this thesis is designed using a segmented architecture in which 4 LSB current cells are binary weighted and 6 MSB current cells are thermometer encoded. The issues with the mixed signal layout were discussed. The schematic design does not consider the effect of parasitic resistance and capacitance whereas the layout does. The performance of the schematic and layout designs of the sub-circuits was compared. Post layout simulations of the implemented current steering DAC were performed in Cadence with 1.2 GHz clock and 55.07 MHz input signal. The simulations show that the DAC is functional and comparisons between the layout and schematic were presented.

Committee:

Saiyu Ren, Ph.D. (Advisor); Raymond E. Siferd, Ph.D. (Committee Member); Marian K. Kazimierczuk, Ph.D. (Committee Member); Yan Zhuang, Ph.D. (Committee Member)

Subjects:

Electrical Engineering

Keywords:

electrical engineering

Barto, TaylorDesign and Control of Electronic Motor Drives for Regenerative Robotics
Master of Science in Electrical Engineering, Cleveland State University, 2017, Washkewicz College of Engineering
Two regenerative motor drives, a voltage source converter and a bidirectional buck/boost converter, are studied for energy regeneration and joint trajectory tracking. The motor drives are applied to two different robotic systems—a PUMA560 robotic arm and a hip testing robot / prosthesis system. An artificial neural network controller is implemented with the two motor drives and provides joint trajectory tracking with an RMS error of 0.03 rad. The control signals produced by the artificial neural network contain a large amount of high frequency content which prevents practical implementation. A robust passivity-based motion controller is modified to include information about the motor drives to overcome the limitations of the artificial neural network controller. The modified robust passivity-based controller outperforms the artificial neural network controller by maintaining a 3 V RMS error between the voltage generated by the converter and the desired voltage while maintaining comparable trajectory tracking. The high frequency content of the robust passivity-based controller contains less high frequency content than the artificial neural network controller. The modified robust passivity-based controller is implemented inside the semiactive virtual control energy regeneration framework to demonstrate energy regeneration with one of the motor drives. The motor drive implemented with the energy regeneration framework shows that energy can be regenerated while using the bidirectional buck/boost converter.

Committee:

Dan Simon, Ph.D. (Committee Chair); Hanz Richter, Ph.D. (Committee Member); Zhiqiang Gao, Ph.D. (Committee Member)

Subjects:

Electrical Engineering

Moore, Levi M.An Enhanced Body Area Network to Wirelessly Monitor Biometric Information
Master of Science (MS), Ohio University, 2017, Electrical Engineering & Computer Science (Engineering and Technology)
Body Area Networks are beneficial in many applications including fitness tracking and remote healthcare monitoring. This thesis discusses system enhancements to the award-winning Ohio University Body Area Network system which senses heart rate, integrates an inertial measurement unit, and measures ambient temperature. An upgraded ARM-based Nordic microprocessor was implemented to collect and process biometric sensor data and utilize low-energy Bluetooth (BLE) to transmit data via a Bluetooth antenna. Data is received on an updated Android application running on a handheld Nexus 5 Smartphone. Power received measurements were performed to compare the Baseline and Enhanced systems using several Bluetooth antenna solutions including an e-textile spiral antenna, a traditional inset-fed patch antenna, and a printed monopole antenna.

Committee:

Chris Bartone (Advisor); Savas Kaya (Committee Member); Maarten Uijt De Haag (Committee Member); David Drozek (Committee Member)

Subjects:

Computer Engineering; Electrical Engineering

Keywords:

Body Area Network; Remote Healthcare Monitoring; Biometric Sensors; Bluetooth Low Energy; ARM-based Microcontroller

Abdelaziz, Amr MohamedInformation Theoretical Studies on MIMO Channel with Limited Channel State Information
Doctor of Philosophy, The Ohio State University, 2017, Electrical and Computer Engineering
Tremendous increase in throughput, reliability and security requirements in present and future wireless communication networks necessitates the migration towards the underutilized higher frequency bands. The premise of large scale multiple input multiple output (MIMO) technology deployment in these bands has the potential of fulfilling future network requirements. At the same time, large scale network deployment, or the so-called dense coverage (large number of small scale base stations), is another link level strategy that also has the potential of enhancing the overall network quality of service (QoS). Performance of MIMO communication systems is governed by the amount of channel state information (CSI) available at both transmitter and receiver especially when deployed in a dense coverage network which has the potential of high line of sight (LoS) opportunity. This thesis aims to address throughput, reliability and physical layer security aspects of MIMO communication systems deployed in a fading environment with a stable path between transmitter and receiver with limited CSI feedback. The research involves four major research directions: (1) Transmitter optimization for public messages with minimal form of CSI feedback, (2) Secrecy capacity and optimal transmission strategy for confidential messages under the same limited CSI feedback model with eavesdropper uncertainty, (3) Establishing fundamental limits of covert communication of MIMO AWGN channel and highlight the potential of having a dominant channel mode in establishing high covert rates, (4) Message source authentication over MIMO channel with dominant mode. We start by considering the MIMO channel with dominant LoS component where the only CSI available at the transmitter are the Rician factor and the physical direction of the receiver with respect to the transmitter antennas array. For this particular scenario, although the exact capacity still unknown in a closed form, we establish an upper bound using Jensen’s inequality for which we derive the maximizing transmission strategy in a closed form. Despite of being suboptimal, the upper bound maximizing strategy, when compared to all previously proposed strategies, is shown to provide a substantial gain in terms of gap to capacity over a wide range of system parameters. We extend our research with the previous setup to the scenario in which the exchanged message are subject to secrecy constraint. We establish the delay limited secrecy capacity of the channel with eavesdropper uncertainty. We introduce a novel class of eavesdropper CSI uncertainty that makes use of the location diversity of communicating nodes. Further, we obtain upper and lower bounds on the ergodic secrecy capacity when the exchanged message are not subject to delay constraint. Different from low probability of intercept constraint, low probability of detection (LPD) is a more restrictive communication scenario in which the communication is required to be undetectable by a passive adversary. We extend our research to establish the fundamental limits of covert (LPD) communication over MIMO channel. We derive the exact scaling laws of the number of covert bits that can transmitted over MIMO channel in the two asymptotic limits of MIMO channel, large block length and large array limits. A key advantage of MIMO channel with dominant mode is the geolocation awareness, i.e., transmitter and receiver have the ability to identify the physical direction of each others. In this correspondence, we study message authentication problem by leveraging the cooperation between existing cryptographic authentication schemes and physical layer based wireless authentication. In particular, we introduce the angle of arrival (AoA) based wireless authentication in which the actual AoA of a given message is checked for consistency with the information available at the receiver about the communication channel. Hardware implantation details and field experimental results are provided to offset the gap between theoretical studies of physical layer security and their application to practical communication systems.

Committee:

Hesham El Gamal, Professor (Advisor); Can Emre Koksal, Professor (Advisor); Inder Gupta, Professor (Committee Member); Sheila Morgan, Professor (Committee Member)

Subjects:

Communication; Electrical Engineering; Information Science

Keywords:

Information Theory; Secrecy Capacity; Transmitter Optimization; Limited CSI; Delay Limited Secrecy Capacity; Ergodic Secrecy Capacity; Covert MIMO Communication; Physical Layer Authentication; Jamming Attack

Ye, HaoquanControl of Quadcopter UAV by Nonlinear Feedback
Master of Sciences, Case Western Reserve University, 2018, EECS - System and Control Engineering
A quadcopter, also called a quadrotor helicopter or quadrotor, is a popular small-scale UAV that has been used for a variety of applications such as photography, monitoring, surveillance and inspection, etc. It needs reliable hardware and control systems to guarantee its performance in various missions. Therefore, developing effective control algorithms is vital for the performance and applications of quadcopters. In this thesis, a nonlinear control method is proposed and a smooth state feedback controller is designed to achieve attitude control and stabilization of the quadcopter. First, we study the dynamics of a quadcopter and establish a mathematical model in state space. Then, with the help of a transformation that puts the quadcopter model into a nonlinear system in the normal form, we design a smooth state feedback controller by taking advantage of the nonlinearity of the quadcopter, combined with the techniques of adding an integrator and feedback linearization. Finally, MATLAB simulations are conducted to validate the effectiveness of the proposed nonlinear controller. The simulations results demonstrate that the new control scheme has a satisfactory dynamic performance and certain robustness against wind disturbance.

Committee:

Wei Lin (Advisor); Kenneth Loparo (Committee Member); Vira Chankong (Committee Member)

Subjects:

Electrical Engineering; Engineering; Robotics

Keywords:

Quadcopter, Nonlinear Control, Adding an Integrator, Feedback Linearization, Dynamic Model

Preston, DouglasLast Two Surface Range Detector for Direct Detection Multisurface Flash Lidar in 90nm CMOS Technology
Master of Science in Electrical Engineering (MSEE), Wright State University, 2017, Electrical Engineering
This thesis explores a novel detection architecture for use in a Direct-Detect Flash LIDAR system. The proposed architecture implements detection of the last two surfaces within single pixels of a target scene. The novel, focal plane integrated detector design allows for detection of objects behind sparse and/or partially reflective covering such as forest canopy. The proposed detector would be duplicated and manufactured on-chip behind each avalanche photodiode within a focal plane array. Analog outputs are used to minimize interference from digital components on the analog input signal. The proposed architecture is a low-footprint solution which requires low computational post-processing. Additionally, constant fraction discrimination is used to mitigate range walk. The proposed architecture is designed in 90nm CMOS technology. The footprint is 170.1 µm² with the largest transistor dimension being 22 µm. The design is easily expandable in hardware to allow additional surfaces to be detected.

Committee:

Saiyu Ren, Ph.D. (Advisor); Arnab Shaw, Ph.D. (Advisor); Ray Siferd, Ph.D. (Committee Member); Robert Muse (Other)

Subjects:

Electrical Engineering

Keywords:

Lidar; Flash Lidar; Multisurface; Time of Flight Camera; ToF Camera; Direct Detection; 90nm CMOS; CMOS; VLSI; Analog; Analogue; Constant Fraction Discriminator; CFD; Feedback Shift Register; Time to Digital Converter; TDC; Low Footprint; Footprint

Patterson, Erin LeighCompression of Medical Images Using Local Neighbor Difference
Master of Science (M.S.), University of Dayton, 2017, Electrical Engineering
Medical images are an essential part to any health professional’s career when helping patients and diagnosing health concerns. Due to the need for large storage capacity and fast transferring speed, research in image compression has grown. Image compression uses the property of redundant information in the image to reduce the amount of data in the image to solve both problems of storage and transmission. For medical images, lossless compression algorithms are of interest to make sure that the reconstructed image provides the same details as the original image. This thesis presents a proposed algorithm called the Local Neighbor Difference (LND) which is a preprocessing technique to allow the redundancy in the medical image to be reduced before being sent into a commercial-off-the-shelf compressor (COTS), XZ. LND, when used in conjunction with XZ losslessly, compresses images, on average, by 6% more than XZ alone. The LND process, along with some future work, is proposed in this paper and results in a viable option for a pre-process to a compressor.

Committee:

Eric Balster, Dr. (Advisor)

Subjects:

Electrical Engineering

Keywords:

medical images; lossless; image compression; XZ;

Kibalama, Dennis SsebinaDesign and Implementation of a Belted Alternator Starter System for the OSU EcoCAR 3 Vehicle
Master of Science, The Ohio State University, 2017, Electrical and Computer Engineering
The transportation sector is a great contributor to overall energy consumption and emissions. Stringent regulations have been put in place to curb the emissions and regulate fuel consumption due to dependency on a finite resource, fossil fuels. This has driven OEMs to re-engineer the automotive powertrain which has led to a burst in production of PHEVs, HEVs and EVs. The U.S. D.O.E, General Motors, Argonne National Laboratory (ANL) and other industry sponsors have spearheaded (Advanced Vehicle Technology Competitions) AVTCs with a goal of training the next generation of automotive engineers by challenging collegiate teams to re-engineer stock vehicles to improve fuel consumption, reduce emissions while maintaining consumer acceptability. The latest in this AVTC series is the EcoCAR 3, a 4-year competition which challenges 16 North American university teams to re-engineer a 2016 Chevrolet Camaro into a HEV while maintaining the performance aspects of the iconic American car. The OSU EcoCAR 3 vehicle boasts a Parallel-series post transmission PHEV architecture designed by the team in Year 1 of the competition. To meet the team designed (Vehicle Technical Specification) VTS targets, the architecture includes a motor coupled to the engine, a Belted Alternator Starter (BAS) which performs engine start/stop, series operation, speed matching and torque assist. Due to the versatility of the component in realizing the VTS targets, this thesis sets to outline the design and validation work done with regards to the BAS system. The BAS system consists of the electric machine, the engine, belt transmission, inverter and battery pack. The thesis outlines the design metrics considered in the design of the BAS system ranging from electrical, performance, mechanical and thermal considerations. The BAS chosen is a sponsor donated component that wasn't supplied with an inverter solution. This thesis details the two inverter choices adopted over Years 2 – 3 of the competition and the control, calibration, validation, performance and packaging carried out to realize functionality of the BAS. To accurately model the dynamics of the BAS system during engine startup, a dynamic engine model is developed to model engine, BAS and belt transmission dynamics. The underlying assumptions made to develop an accurate representation of the dynamics while minimizing calibration efforts are also outlined. This model will be used in Year 4 for development and optimization of an engine start/stop controller. The thesis also analyses the two control methods adopted for engine start; an open loop controller and a closed loop controller and evaluates the performance of the controllers in terms of rise time, engine speed overshoot, maximum jerk and root mean square acceleration. This thesis encompasses the design and validation work done to move the BAS system development work from a component/subsystem level to vehicle/system level. This sets the team in a good position heading into Year 4 of the competition to implement engine start/stop functionality in the vehicle, optimize torque assist functionality and use the BAS for speed matching for faster shift times.

Committee:

Giorgio Rizzoni (Advisor); Levent Guvenc (Committee Member); Shawn Midlam-Mohler (Committee Member)

Subjects:

Electrical Engineering

Keywords:

BAS; Belted Alternator Starter; EcoCAR

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