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Title: Multi-function multi-modality sensing and communication system: a designer's perspective
Creator: Fepeussi, Tonmo Vanessa Carine
Date: 2019
Description: The combination of sensing and communication functionalities on the same electronic device is the key to autonomous sensing applications in...
Show moreThe combination of sensing and communication functionalities on the same electronic device is the key to autonomous sensing applications in the transportation industry, including driverless vehicles and structural health monitoring (SHM) of aero-vehicles. Due to the limited availability of spectral and hardware resources, there is a need for resource sharing between sensing and communication systems. This is achieved by the efficient integration of sensing and communication functions through a unified design of both systems into smart sensors. To that end, a multi-modality approach is employed in this research to design multi-functional systems at two different bands of the frequency spectrum, namely radio and acoustic frequencies.First, a radio-frequency (RF) software-defined system capable to support radar sensing and RF communication is proposed for use in modern interconnected automotive applications such as driverless vehicles. The proposed RF radar is designed on a software-defined homodyne transceiver prototype capable of radio communication. The system is implemented in the S band over a narrow frequency bandwidth of 34 MHz between 3.550 GHz and 3.584 GHz. Experimental measurements show that the designed radar sensor can measure short-range targets with a range accuracy of less than 21 cm.An acoustic sensing and communication system is developed in parallel for use in autonomous SHM monitoring of aero-vehicles. The proposed communication system uses M-ary time-reversal pulse position modulation (M-TRPPM) as the modulation scheme for dispersion compensated wireless communication across the elastic channel. The time reversal based time division multiple access (TR-TDMA) protocol is introduced to regulate channel access by multiple sensors. Simulation and experimental validation demonstrate that the designed system, using an excitation signal generated by a PZT sensor disc at 300 kHz resonant frequency, is capable of reliable data transmission with a bit error rate (BER) approximating zero at low data rates of a few kilobits per seconds.
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Title: Wireless Body Sensor Network for Tracking Human Mobility using Long Short-Term Memory Neural Network for Classification
Creator: Gupta, Saumya
Date: 2019
Description: A large number of sensors are used without justification of the number chosen or placement choice. Many papers about body sensor networks...
Show moreA large number of sensors are used without justification of the number chosen or placement choice. Many papers about body sensor networks explore how to capture a type or types of motion, but all their sensors are placed in different locations; making their algorithms very specific to that movement. In this research, we explore the enhancement of human activity classification algorithm using long short-term memory (LSTM) neural network and wearable sensor network. There are five identical nodes used in the body sensor network to collect data. Each node incorporates an ESP8266 Microcontroller with Wi-Fi which is connected to an inertial measurement unit consisting of triple axis accelerometer and gyroscope sensor board. An analysis on the accuracy that each sensor node provides separately and in different combinations has been conducted to allow future research to focus their positioning in optimal positions. A Robot Operating System (ROS) central node is used to illustrate the in-built multi-threading capability. For demonstration, the positions chosen are waist, ankles and wrists. The raw sensor data can be observed on screen while it is being labelled live to create fitting dataset for developing an artificial neural network. Expectation is that increasing the number of sensors should raise the overall accuracy of the output but that isn’t the case observed, positioning of the sensor is pertinent to improvement. These platforms can be further extended to understand different motions and different sensor positions, also expanded to include other sensors.
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Title: Integrated Design Framework For Electric Motor Drive Systems
Creator: Salameh, Mohamad
Date: 2020
Description: This thesis aims to develop a flexible and time-efficient framework for machine design optimization that considers driving cycles,...
Show moreThis thesis aims to develop a flexible and time-efficient framework for machine design optimization that considers driving cycles, multiphysics domains and current design. The proposed development of the framework is based on the enhancement of three key aspects in the machine design process. A data mining algorithm – the X-means – is employed in the driving cycle analysis, to establish a trade-off between the optimization objectives and the computational intensity. A novel vibration surrogate model is proposed to evaluate the vibroacoustic behavior of the machine in an accurate and time-efficient way. In the identification process, the time effectiveness of the model is attained with a minimized number of finite element simulations. Furthermore, the principle of simultaneous coupled optimization is considered in the framework, where current design variables are included in the optimization environment to allow identifying design candidates with improved performance.
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Title: ANALYSIS AND OPTIMIZATION OF VIBRATION AND ACOUSTIC NOISE IN SWITCHED RELUCTANCE MACHINES
Creator: Yaman, Selin
Date: 2019
Description: One of the main drawbacks of switched reluctance machines (SRM) is the vibration and high acoustic noise compared to other electrical motors....
Show moreOne of the main drawbacks of switched reluctance machines (SRM) is the vibration and high acoustic noise compared to other electrical motors. The root cause of the high level of acoustic noise is radial forces with high harmonic content. These harmonics may trigger resonant modes in the stator and cause the machine to create high vibration and acoustic noise. To better understand the factors influencing vibration and acoustic noise in an SRM, this dissertation first develops a multi-physics model in ANSYS Workbench environment and carries out a comprehensive analysis of multiple variations in stator and rotor geometries. Based on this understanding, this dissertation identifies distinct factors affecting noise in the machine, which are affected by electromagnetic design and power electronic control. From the electromagnetic perspective, geometrical optimizations in the stator and rotor structures are evaluated to understand the impact on NVH (noise, vibration and harshness) performance. This background is used to develop a fast geometry-sensitive analytical approach to reduce acoustic noise in the machine. While optimizing the geometry for a silent machine design, different design of experiments (DoE) methods and response surface (RS) optimization methods are also compared and presented. Furthermore, material analysis is included in structural design, where high flux material effect on vibration and acoustic noise is observed. The second topic of the NVH analysis is power electronic and switching solutions. In this study, multiple basic and advanced switching techniques have been considered and optimized to reduce acoustic noise under a preset efficiency constraint. Further, a time efficient model of SRM is introduced with vibro-acoustic noise perspective by developing a computationally cost effective SRM modeling. By using this analytical time-efficient NVH model, a current shape optimization is implemented, and results are discussed. Finally, experimental validations are provided for NVH and psychoacoustics analysis for different operating conditions and current control methods.
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Title: ARF Electrical Engineering Building, Chicago, Ill., 1953
Creator: Armour Research Foundation (U.S.)
Date: 1953
Description: Photograph of the ARF Electrical Engineering Building, located at 3201 South Michigan Avenue. The building was demolished in 1996-97. This...
Show morePhotograph of the ARF Electrical Engineering Building, located at 3201 South Michigan Avenue. The building was demolished in 1996-97. This building was initially leased by the Armour Research Foundation in 1951, and acquired by Illinois Tech in 1965. It was known as: Richard D. Irwin Inc. Building (unknown-1941), Sampson Electric Company (1930s-1950s?), Armour Research Foundation Electrical Engineering Research Building (1951-1965), Information Science Building (ca. 1965-ca. 1972), Military Science Building, and Michigan Building (1972).
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Collection: Office of Communications and Marketing photographs, 1905-1999

Title: BLOCKCHAIN FOR TRANSACTIVE ENERGY MARKET WITH NETWORKED MICROGRIDS
Creator: Yan, Mingyu
Date: 2021
Description: Transactive energy, which allows and incentivizes microgrids (MGs) to trade energy with each other, is regarded as the next-generation energy...
Show moreTransactive energy, which allows and incentivizes microgrids (MGs) to trade energy with each other, is regarded as the next-generation energy management scheme to accommodate the penetration of distributed energy resources (DERs). Blockchain provides an effective and decentralized strategy, which can address the operational challenges introduced by the transactive energy market. This thesis is aimed at providing effective transactive energy markets for incentivizing MGs to trade energy and utilizing blockchain technologies to provide a secure and efficient energy trading environment for all participants.First, this thesis offers a centralized transactive market for networked MGs to transact energy through the centralized distribution system operator (DSO) while ensuring the power network limits. All MGs cooperate in this market and the cooperative behaviors are captured using the cooperative game with externalities. A two-level problem is studied to allocate the total payoff to all participating MGs. Numerical results for a 4-MG system and the IEEE 33-bus show the validity of the centralized transactive energy model. Second, this thesis proposes a two-level network-constrained peer-to-peer (P2P) transactive energy for multi-MGs, which guarantees the distribution power network security and allows MGs to trade energy with each other flexibly. At the lower level, a P2P transactive energy is employed for multi-MGs to trade energy with each other. A multi-leader multi-follower (MLMF) Stackelberg game approach is utilized to model the energy trading process among MGs. At the upper level, the DSO reconfigures the distribution network based on the P2P transactive energy trading results by applying the AC optimal power flow considering the distribution network reconfiguration. If there are any network violations, the DSO requests energy trading adjustments at the lower level for network security. Numerical results for a 4-MG system, the modified IEEE 33-bus, and the 123-bus distribution power systems show the effectiveness of the proposed transactive energy model and its solution technique. Third, this thesis adopts the blockchain for the peer-to-peer transactive energy market among MGs. A two-level integrated blockchain-power system is provided, in which all MGs and the DSO are equipped with blockchain. At the lower level, MGs trade energy with each other through the lower-level MG blockchain, while the DSO manages the network security through the upper level DSO blockchain. We illustrate how to utilize blockchain technologies, i.e., public and private keys and smart contracts, to provide an efficient and secure energy trading environment for all MGs. Last, this thesis applies the blockchain for transacting energy and carbon right for networked MGs. MGs transact energy and carbon right through the centralized DSO while ensuring the power network limits. The introduction of blockchain achieves secure and decentralized market settlements in this centralized market. Numerical results for a 4-MG system and modified IEEE 33-bus systems show the effectiveness of the proposed transactive energy and carbon market.
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Title: MACHINE VISION NAVIGATION SYSTEM FOR VISUALLY IMPAIRED PEOPLE
Creator: Yang, Guojun
Date: 2021
Description: Visually impaired people are often challenged in the efficient navigation of complex environments. Moreover, helping them navigate intuitively...
Show moreVisually impaired people are often challenged in the efficient navigation of complex environments. Moreover, helping them navigate intuitively is not a trivial task. Cognitive maps derived from visual cues play a pivotal role in navigation. In this dissertation, we present a sight-to-sound human–machine interface (STS-HMI), a novel machine vision guidance system that enables visually impaired people to navigate with instantaneous and intuitive responses. This proposed system extracts visual context from scenes and converts them into binaural acoustic cues for users to establish cognitive maps. The development of the proposed STS-HMI system encompasses four major components: (i) a machine vision–based indoor localization system that uses augmented reality (AR) markers to locate the user in GPS-denied environments (e.g., indoor); (ii) a feature-based object detection and localization system called the simultaneous localization and mapping (SLAM) algorithm, which tracks the mobility of users when AR markers are not visible; (iii) a path-planning system that creates a course towards a destination while avoiding obstacles; and (iv) an acoustic human–machine interface to navigate users in complex navigation courses. Throughout the research and development of this dissertation, each component is analyzed for optimal performance. The navigation algorithms are used to evaluate the performance of the STS-HMI system in a complicated environment with difficult navigation paths. The experimental results confirm that the STS-HMI system advances the mobility of visually impaired people with minimal effort and high accuracy.
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Title: EVENT-BASED NONINTRUSIVE LOAD MONITORING
Creator: Yan, Lei
Date: 2021
Description: Non-Intrusive Load Monitoring (NILM) is an important application to monitor household appliance activities and provide related information to...
Show moreNon-Intrusive Load Monitoring (NILM) is an important application to monitor household appliance activities and provide related information to house owner or/and utility company via a single sensor installed at the electrical entry of the house. With this information, utilities can perform many tasks such as energy conservation, planning gen-eration more wisely, and demand response (DR) study. For house owners, they can un-derstand their bill more clearly and make better budget plan. For researchers, NILM sys-tem is a good foundation for energy management in buildings and can provide valuable power information for smart homes design. This dissertation aims to develop and demon-strate a complete and accurate event-based NILM system, which includes (1) an edge-cloud framework for event-based NILM, (2) an adaptive event detection method, (3) a two-stage event-based load disaggregation method; and (4) a high-resolution (50Hz) NILM dataset. Event detection is the first step in event-based NILM and it can provide deter-ministic transient information to identify appliances. However, existing methods with fixed parameters suffer from unpredictable and complicated changes in smart meter data such as long transition, high fluctuation and near-simultaneous events in both power and time domains. This dissertation presents an adaptive method to detect events based on home appliance load data with high sampling rate (>1Hz) by flexibly tuning the parame-ters according to the data being processed. The proposed method runs fast over the data stream and captures the transient process by multi-timescales searching as well. The mi-cro-timescale and macro-timescale window could deal with near-simultaneous events and long-transition events, respectively. Transient load signatures are extracted from detected events and stored in a sequential tree struct that can be used for NILM and load recon-struction, etc. Case studies on a 20Hz dataset, the LIFTED dataset of 50Hz, and the BLUED dataset of 60Hz demonstrate that the proposed method is able to work on data of different sampling rates and outperforms other methods in event detection. The ex-tracted load signatures could also improve the efficiency of NILM and help develop oth-er applications. This dissertation presents an online transient-based electrical appliance state track-ing method for NILM. The proposed Factorial Particle based Hidden Markov Model (FPHMM) method takes advantage of transient features in high-resolution data to infer states in the transient process and conducts steady state verification to rectify falsely identified appliances. The FPHMM method can overcome the common feature similarity problem in NILM by combining particle filter method and Markov Chain Monte Carlo sampling method, and by mining the intra-relationship of states inside a single appliance and the inter-relationship of states among multiple appliances. The FPHMM method is tested on the LIFTED dataset with appliance-level details and high sampling rates. Test-ing results demonstrate that the FPHMM method is effective in resolving the feature similarity issue. A modified mean shift algorithm with different levels of bandwidth is proposed as well to cluster the extracted features from event detection. Based on the clustered fea-tures, another solution is proposed to decode the states of appliance in two stages. The first stage uses Bayesian Inference Factorial HMM (BI-FHMM) solver to accelerate com-putational speed and improve accuracy by integrating the load signatures and statistical inference. The second stage then verifies and rectifies the results obtained from the first stage. Test results demonstrate that the proposed approach achieves good performance and can be applied to existing smart meters.
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Title: Assistant to Dr. Daniel Graupe demonstrating a computerized arm prothesis, Illinois Institute of Technology, Chicago, Illinois, 1980s
Date: 1980-1989
Description: Photograph of an unknown assistant to Dr. Daniel Graupe demonstrating a computerized prosthetic arm. Photographer unknown. Date of photograph...
Show morePhotograph of an unknown assistant to Dr. Daniel Graupe demonstrating a computerized prosthetic arm. Photographer unknown. Date of photograph unknown. Date range listed is approximate.
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Collection: Office of Communications and Marketing photographs, 1905-1999

Title: Dr. Daniel Graupe and an assistant using a computerized arm prothesis, Illinois Institute of Technology, Chicago, Illinois, 1980s
Date: 1980-1989
Description: Photograph of Electrical Engineering professor Dr. Daniel Graupe and an assistant demonstrating a computerized prosthetic arm. Photographer...
Show morePhotograph of Electrical Engineering professor Dr. Daniel Graupe and an assistant demonstrating a computerized prosthetic arm. Photographer unknown. Date of photograph unknown. Date range listed is approximate.
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Collection: Office of Communications and Marketing photographs, 1905-1999

Title: Electrical Engineering handheld scanning device, Illinois Institute of Technology, Chicago, Illinois, 1980s
Date: 1980-1989
Description: Photograph of a handheld scanning device used (and possibly created) by the Illinois Institute of Technology's Department of Electrical...
Show morePhotograph of a handheld scanning device used (and possibly created) by the Illinois Institute of Technology's Department of Electrical Engineering. Photographer unknown.
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Collection: Office of Communications and Marketing photographs, 1905-1999

Title: TASK-BASED LOAD FORECASTING AND ROBUST RESOURCE SCHEDULING IN SMART GRID
Creator: Han, Jiayu
Date: 2021
Description: In microgrids, the uncertainty of load and renewables and lack of generation capacity will lead to a wide variety of operation problems in...
Show moreIn microgrids, the uncertainty of load and renewables and lack of generation capacity will lead to a wide variety of operation problems in both grid-connected mode and islanded mode. This motivates the design of the state-of-art microgrid master controller for microgrid energy management, load forecasting, and demand response. Uncertainty in renewables and load is a great challenge for microgrid operation, especially in islanded mode as the microgrid may be small in size and has limited flexible resources. A multi-timescale, two-stage robust dispatch model is proposed to optimize the microgrid operation. The proposed one uses only one model to combine the hourly and sub-hourly dispatch together, which means the day-ahead hourly dispatch results must also satisfy the sub-hourly conditions. At the same time, the feasibility of the day-ahead dispatch result is verified in the worst-case condition considering the high-level uncertainty in renewable energy output and load consumptions. In addition, battery energy storage system (BESS) and solar PV units are integrated as a combined solar-storage system in the proposed model and the output power of the combined solar-storage system remains unchanged on an hourly basis. Furthermore, both BESS and thermal units provide regulating reserve to manage solar and load uncertainty. The model has been tested in a controller hardware in loop (CHIL) environment for the Bronzeville Community Microgrid system in Chicago. The simulation results show that the proposed model works effectively in managing the uncertainty in solar PV and load and can provide a flexible dispatch in both grid-connected and islanded modes.When the generation capacity of an islanded microgrid is less than the load demand, load curtailment is inevitable. This dissertation proposes a multi-objective optimization model to minimize the load curtailments. Specifically, the proposed model minimizes the generation cost and total load curtailments and also minimizes the maximum load curtailment. Furthermore, the impact of the penalty coefficients of total load curtailment and maximum load curtailment is analyzed, which provides a strategy to choose the value of the two penalty coefficients according to different practical purposes. The proposed model can be used in both microgrid generation scheduling and microgrid planning problems. It was tested in the Bronzeville Community Microgrid system and the results showed that the proposed model can reduce the total load curtailment and maximum load curtailment.Load forecasting is one of the most important and studied topics in modern power systems. However, traditional load forecasting is an open-loop process as it does not consider the end use of the forecasted load. This dissertation proposes a closed-loop task-based day-ahead load forecasting model labeled as LfEdNet that combines two individual layers in one model, including a load forecasting layer based on deep neural network (Lf layer) and a day-ahead stochastic economic dispatch (SED) layer (Ed layer). The training of LfEdNet aims to minimize the cost of the day-ahead SED in the Ed layer by updating the parameters of the Lf layer. Sequential quadratic programming (SQP) is used to solve the day-ahead SED in the Ed layer. The test results demonstrate that the forecasted results produced by LfEdNet can lead to lower cost of day-ahead SED at the expense of slight reduction in forecasting accuracy.
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Title: TOPOLOGY OPTIMIZATION OF SYNCHRONOUS ELECTRIC MACHINES
Creator: Guo, Feng
Date: 2021
Description: Topology optimization of electric machine is attractive because of the increased design degree of freedom compared to conventional electric...
Show moreTopology optimization of electric machine is attractive because of the increased design degree of freedom compared to conventional electric machine design techniques. Also, a topology optimization approach does not necessarily require the use of a geometric template where dimensions are controlled by parameters. In this dissertation, a density-based magneto-structural topology optimization approach for the design of synchronous reluctance machine (SynRel), interior permanent magnet synchronous machine (IPMSM), and wound field synchronous machine (WFSM) rotors is developed. Depending on the electric machine type, the optimization problems are divided into single material and multi-material topology optimizations. A mass thresholding function is introduced to overcome the intermediate density issue which is caused by combining the magnetic and structural topology optimization problems. SynRel and IPMSM optimization examples are presented in the single material topology optimization section. For the multi-material topology optimization, in order to properly define the boundary conditions between multiple materials, a virtual region calculation approach is proposed. In the WFSM topology optimization, the copper field winding is represented by a virtual region. The contact and frictionless boundary conditions between the copper field winding and the electrical steel is defined and the centripetal load of the copper winding are equivalently calculated and applied on the elements on the electrical steel next to the boundary between the copper field winding and the steel of the WFSM pole tip. In additional to the total free-form magneto-structural topology optimization, a density-based combined dimensional and topology optimization is developed for the design of IPMSM and WFSM rotors. Both the dimensional and topological control variables are integrated to simplify the optimization problem. For IPMSM rotor design, the permanent magnet (PM) block shape is preferred to be retained where dimensional optimization could be used. The proposed dimensional topology optimization approach can fit in this design situation, where the PM is designed using dimensional control variables where the rest of the design domain is optimized using topology optimization. To allow the block or rectangular magnet to move and change size, the surrounding design domain mesh must deform or distort. The Laplace's smoothing mesh deformation technique is used in this approach and helper lines are connected to allow greater mesh deformation range and to avoid over mesh distortion. In addition to IPMSMs, a WFSM example is presented optimizing the winding region using dimensional optimization and the rotor core using topology optimization. An alternative combined dimensional and topology optimization approach has also been developed primarily for the design of the IPMSM rotors. In this approach, the mesh deformation is not required but there is no explicit geometric boundary between the rectangular permanent magnet and the surrounding electrical steel and air. In this approach, the PM density is expressed as a Heaviside rectangular function of dimensional variables. The function is projected onto the rotor mesh. Modified material penalizations are used. Topology optimization then controls the deposition of electrical steel and air. Three different IPMSM examples are presented with different dimensional control variables, including the PM position, size and angle.
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Title: A Novel CNFET SRAM-Based Computing-In-Memory Design and Low Power Techniques for AI Accelerator
Creator: Kim, Young Bae
Date: 2023
Description: Power consumption and data processing speed of integrated circuits (ICs) is an increasing concern in many emerging Artificial Intelligence (AI...
Show morePower consumption and data processing speed of integrated circuits (ICs) is an increasing concern in many emerging Artificial Intelligence (AI) applications, such as autonomous vehicles and Internet of Things (IoT). In addition, according to the 2020 International Technology Road map for Semiconductors (ITRS), the high power consumption trend of AI chips far exceeds the power requirements. As a result, power optimization techniques are highly regarded in nowadays AI chip designs. There are various low-power methodologies from the system level to the layout level, and we are focusing on transistor level and register transfer level (RTL) through this thesis. In this thesis, we propose a novel ultra-low power voltage-based computing-in- memory (CIM) design with a new SRAM bit cell structure for AI Accelerator. The basic working principle of CIM (Computing-in-memory) is to use the existing internal embedded memory array (e.g. SRAM) instead of external memory, and it reduces unnecessary access to external memory by calculating with internal embedded mem- ory. Since the proposed our SRAM bit cell uses a single bitline for CIM calculation with decoupled read and write operations, it supports much higher energy eciency. In addition, to separate read and write operations, the stack structure of the read unit minimizes leakage power consumption. Moreover, the proposed bit cell structure provides better read and write stability due to the isolated read path, write path and greater pull-up ratio. Compared to the state-of-the-art SRAM-CIM, our proposed SRAM-CIM does not require extra transistors for CIM vector-matrix multiplication. We implemented a 16k (128⇥128) bit cell array for the computation of 128x neurons, and used 64x binary inputs (0 or 1) and 64⇥128 binary weights (-1 or +1) values for the binary neural networks (BNNs). Each row of the bit cell array corresponding to a single neuron consists of a total of 128 cells, 64x cells for dot-product and 64x replicas cells for ADC reference. And 64x replicas cells consist of 32x cells for ADC reference and 32x cells for o↵set calibration. We used a row-by-row ADC for the quantized outputs of each neuron, which supports 1-7 bits of output for each neuron. The ADC uses the sweeping method using 32x duplicate bit cells, and the sweep cycle is set to 2N1 +1, where N is the number of output bits. The simulation is performed at room temperature (27C) using 32nm CNFET and 20nm FinFET technology via Synopsys Hspice, and all transistors in bitcells use the minimum size considering the area, power, and speed. The proposed SRAM-CIM has reduced power consumption for vector-matrix multiplication by 99.96% compared to the existing state-of-the-art SRAM-CIM. Moreover, because of the separated reading unit from an internal node of latch, there is no feedback from the read access circuit, which makes it read static noise margin (SNM) free. Furthermore, for the low power AI accelerator design, we propose a new AI accelerator design method that applies low power techniques such as bus specific clock gating (BSCG) and local explicit clock gating (LECG) at the register-transfer- level (RT-level). And evaluates them on the Xilinx ZCU-102 FPGA SoC hardware platform and 45nm technology for ASIC, respectively. It measures dynamic power using a commercial EDA tool, and chooses only a subset of FFs to be gated selectively based on their switching activities. We achieve up to a 53.21% power reduction in the ASIC implementation and saved 32.72% of the dynamic power dissipation in the FPGA implementation. This shows that our RTL low power schemes have a powerful possibility of dynamic power reduction when applied to the FPGA design flow and ASIC design flow for the implementation of the AI system.
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Title: Electric Machine Windings with Reduced Space Harmonic Content
Creator: Tang, Nanjun
Date: 2023
Description: The reduction of magnetomotive force (MMF) space harmonic content in electric machine windings can significantly improve the machine's...
Show moreThe reduction of magnetomotive force (MMF) space harmonic content in electric machine windings can significantly improve the machine's electromagnetic performance. Potential benefits include a reduction of torque ripple, a more sinusoidal back EMF, and reduced power losses. With the proposal of a uniform mathematical representation that applies to both distributed windings and fractional-slot concentrated windings (FSCWs), closed-form expressions can be derived for harmonic magnitudes, winding factors, etc. These expressions can then be used to formulate the MMF space harmonic suppression problem for windings, which looks for improved windings with certain harmonic orders reduced or even eliminated, by varying the slot distribution and coil turns. Different solution techniques are explored to gain additional insights about the solution space. The underlying mathematical relations between different harmonic orders are mathematically proved to establish the family phenomenon, which presents clear pictures of the higher order part of the harmonic spectrum and is the foundation for exact calculation of the total harmonic distortion (THD) of windings. The exact THD calculation further indicates how the minimal THD can be achieved for a winding. Windings can also be analyzed and designed from the view of subsets to incorporate distribution and excitation phase shift effects. With reduced or the minimal space harmonic content, new winding designs can help significantly improve the Pareto front when combined with motor geometry optimization. Design examples including a 12-slot 2-pole mixed-layer distributed winding, a 18-slot 2-pole mixed-layer distributed winding, and a four-layer 24-slot 22-pole FSCW with excitation phase shift are presented with finite element analysis (FEA) results to verify the performance improvements.
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Title: Polarization Induced by A Terahertz Electric Field in A Semiconductor Nanodimer in the Overlapping Regime
Creator: Wang, Zi
Date: 2023
Description: Boltzmann transport equation is a theoretical framework for the description of thermodynamics or charge reactions in a system not in...
Show moreBoltzmann transport equation is a theoretical framework for the description of thermodynamics or charge reactions in a system not in equilibrium, which can be applied to the analysis of the interactions of mobile charges with an electromagnetic wave. When the dimensions of the object are small compared to the wavelength, the induced dipole moment provides a means to characterize the collective response while providing insight to the nature of the charge-field interactions. Semiconductor nanoparticles exhibit surface plasmon resonance in the terahertz frequency range and are of current interest for the development of components and circuits in that part of the electromagnetic spectrum. By changing the plasmon frequencies of doped semiconductors through the change of carrier concentration, new opportunities arise for plasmonic manipulation in terahertz region leading to various promising applications. Despite the Drude model's long-term success and convenience in describing the electrical conductivity of metals in terms of dielectric functions, some aspects of polarization are not accounted for by bulk properties. By incorporating the transport equations of the charge carriers with Maxwell's equations, screening effects of charge carriers can be accounted for, enabling the internal field, space charge and induced dipole moment of a semiconductor nanoparticle to be studied.The computations performed for elementary dimer structures in overlapping cases revealed the internal field screening, while the complex dipole moments show dispersion and absorption effects. The numerical algorithms are implemented using the finite element method to investigate the surface plasmon resonance (SPR) induced on the semiconductor particles. Unique SPR modes evolution is observed as the thickness of the overlap region is varied. The characteristics can be interpreted by the migration of local space charge as the level of overlap is varied. This degree of freedom provided by a semiconductor nanodimer could be employed to control the local field near a simple cluster of nanoparticles, with potential for application in sensing and circuit components in the terahertz frequency range.
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Title: A New Control and Decision Support Framework To Avoid Fast-Evolving System Collapse and Cascading Failure
Creator: Guha, Bikiran
Date: 2022
Description: The modern power system is a vast and incredibly complex network with a very large number of equipment operating round the clock to reliably...
Show moreThe modern power system is a vast and incredibly complex network with a very large number of equipment operating round the clock to reliably transport electricity from generators to consumers. However, factors such as aging and faulty equipment, extreme and unpredictable weather, cyber attacks and increasing amounts of unpredictable renewable generation have made it increasingly vulnerable to cascading failure and wide-area collapse. Therefore, a lot of work has been done over the years on cascading failure vulnerability analysis and mitigation. However, to the best of our knowledge, the existing literature on this topic focus on preventive analysis and mitigation, mostly from a planning perspective. There is a lack of decision support schemes which can take real-time preventive action when the system becomes vulnerable to cascading failure, while taking into account the various dynamics and uncertainties involved in these types of failures. The only defense under these situations are pre-designed emergency control schemes. However, they are only effective against known vulnerabilities and can make matters worse if not accurately designed and calibrated.This research work has proposed a novel wide-area monitoring protection and control (N-WAMPAC-20) framework designed to make decisions in real-time to assess the vulnerabilities of the system (when a disturbance happens) and to implement mitigation actions, if necessary. The main contributions of this dissertation focus on the disturbance monitoring, real-time control and decision making aspects of this framework. The proposed framework has been divided into two major parts: an offline part and an online part. The offline part continuously runs extreme contingency analysis in the background (using combined dynamics and protection simulators) to generate elements which can assess system vulnerabilities and suggest suitable mitigation actions, if necessary. In this regard, a novel load shedding adjustment scheme is also proposed, which has been shown to be effective against a variety of fast-evolving cascading failure scenarios. The online part consists of real-time disturbance monitoring and decision-making components. The disturbance monitoring component focuses on real-time fault detection and location. If a fault has been identified and located, the real-time decision making component determines the vulnerability of the system, by consulting with the elements designed offline. If vulnerabilities are identified, targeted mitigation actions are implemented. The design and applicability of a prototype of N-WAMPAC-20 has been presented using a case of voltage collapse and a case of wide-area loss of synchronization on a synthetic model of the Texas grid.
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Title: Constellation and Detection Design for Non-orthogonal Multiple Access System
Creator: Hao, Xing
Date: 2022
Description: It is well known that the Non-Orthogonal Multiple Access (NOMA) system has the capability to achieve higher spectral efficiency and massive...
Show moreIt is well known that the Non-Orthogonal Multiple Access (NOMA) system has the capability to achieve higher spectral efficiency and massive connectivity. In this thesis, some optimized designs in both code-domain and power-domain NOMA systems are studied. Overall, the main contributions are listed as follows:Firstly, we investigate a NOMA system based on the combinatorial design with a novel constellation design for eliminating the surjective mapping from the linear adding data of multiuser and lowering the complexity of constellation design and Multiuser Detection (MUD). And for further enlarge the connectivity, we propose a Low-Density Codes structure to build a trade-off between the diversity and multiusers in resources by expurgating excessive interference on coding matrices. Therefore, our scheme can not only provide a one-to-one mapping pattern with a sparser multiple access structure but also be adjusted with more flexibility to achieve diversity and transmit a large number of users.Secondly, we proposed a constellation mapping scheme based on sub-optimized signal constellation designs by shaping the receiver’s constellation with a strategy that allows differentiated users by which resolvable points will be received allowing simpler detection and design.Thirdly, a novel NOMA system in uplink with time-delayed symbols is investigated, in which a modified Successive Interference Cancellation (SIC) scheme is used at the receiver side. In conventional SIC, when the transmission power is distributed to one user with trivial shifts to other users, the Bit Error Rate (BER) performance will be decreased significantly. Thus, we evaluated a modified SIC by adding artificial time offsets to the conventional power domain-NOMA (PD-NOMA) between users, which can provide higher degrees of freedom for power allocation of users and reduce mutual interference. And then, the added time offsets can provide additional resources to detect the superimposed signals, then the combination of users’ estimations of overall time slots will be considered to get detection improvements. Numerical results demonstrate that the BER performance of our modified SIC outperforms the PD-NOMA with other SIC-based schemes.Thirdly, we propose a new modulation scheme based on polynomial phase signals (PPS) for downlink and uplink non-orthogonal multiple-access (NOMA) transceivers in both the code and power domains. The PPS leads to outstanding spectral efficiency and bit error rate (BER) performance. We also propose a design criterion for CD-NOMA systems to enable the NOMA system to deploy a large number of users with more flexibility as well as lower design and detection complexity than traditional CD-NOMA systems, such as SCMA and PDMA.
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Title: Fault Detection and Localization in Flying Capacitor Multilevel Converters
Creator: Hekmati, Parham
Date: 2021
Description: This dissertation addresses fault detection, fault localization, and recovery in different topologies of the flying capacitor multilevel...
Show moreThis dissertation addresses fault detection, fault localization, and recovery in different topologies of the flying capacitor multilevel converters to guarantee the safe post-fault operation of the system and maintain load supply. There are multiple contributions of this dissertation, including techniques for device open-circuit fault (OCF) detection in stacked multicell converters (SMCs), a windows detector circuit to track the output terminal voltage levels and current directions, a fast and straightforward active power device OC fault detection and localization technique for the family of flying capacitor multilevel converters (FCMCs), a model-based open circuit fault detection and localization technique for the Buck-FCMC, a new estimator for tracking the voltage of flying capacitors, and fault detection and localization for interleaved converters. Each of these contributions is summarized below.The first contribution of this dissertation proposes a fast and straightforward technique for power device OCF detection in SMCs. The fault detection concept only needs to sense the converter's output terminal voltage and current. The sensed output terminal voltage is compared to a predicted one to detect and localize the OCF. A front-end routing circuit is then added to the SMC to maintain the operation of the converter post fault. The second contribution proposes a window detector circuit to track the output terminal voltage levels and current directions. The window detector circuit detects output terminal voltage level and current direction instead of requiring high sample rates and interrupt loops in the controller.The third contribution proposes a fast and straightforward active power device OCF detection and localization technique for the family of FCMCs, including DC to DC FCMCs, single or multi-phase H-bridge FCMCs, and cascaded H-bridge multilevel converters. This technique only needs to sense voltage and direction of current at the output terminals of the converters to detect and localize the fault. The method compares the measured and the expected terminal voltage while considering the commanded switch states and the terminal current direction. As switches transition to different states, healthy switches are excluded from the set of possible faulty switches until only one faulty switch remains. Coordination of the asynchronous operation of FPGA, DSP, and sensors is addressed for practical implementation. The fourth contribution is a model-based OCF detection and localization technique for the Buck-FCMC using model predictive control. In this technique, state-space equations of the system are developed. Comparison of the measured output inductor with the predicted one from the state-space model is used for the OCF detection and localization. This technique can potentially be used for other converters of the FCMC family. The fifth contribution is a new estimator for tracking the voltage of flying capacitors as the internal states of the FCMC. Using the proposed flying capacitor voltage estimator reduces the number of required sensors compared to the conventional model-based methods. At the same time, the overall technique's robustness to dynamic changes, including startup and load changes, is maintained. The last contribution is open and short circuit switch fault detection and localization for interleaved converters using the harmonic analysis of the output terminal parameters. With this method, monitoring electrical parameters of each leg of the interleaves converters is no longer required for fault detection and localization purposes.
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Title: INTELLIGENT SOLID STATE CIRCUIT BREAKERS USING WIDE BANDGAP SEMICONDUCTORS
Creator: Zhou, Yuanfeng
Date: 2021
Description: Electricity, in its predominant form of alternating current (AC), is at the heart of modern civilization. However, direct current (DC)...
Show moreElectricity, in its predominant form of alternating current (AC), is at the heart of modern civilization. However, direct current (DC) electricity is re-emerging, offering higher transmission efficiency, better system stability, better match with modern electrical loads, and easier integration of renewable and storage resources than AC. DC power is gaining tractions in HVDC or MVDC grids, DC data centers, photovoltaic farms, EV charging infrastructures, shipboard, and aircraft power systems. However, DC fault protection remains a major challenge. Interruption of DC currents is extremely difficult due to the lack of current zero crossings which are naturally available in AC power systems. Conventional mechanical breakers only offer a very limited DC current interruption capability even after significant power derating. Hybrid circuit breakers (HCBs) offers a relatively low conduction loss but a response time too slow to protect many low-impedance DC grids. Solid state circuit breakers (SSCBs) can quickly interrupt a DC fault current within tens of microseconds but suffer from high conduction losses. Furthermore, it is generally difficult for an SSCB to distinguish between a short circuit fault and a normal inrush current condition during the start-up of a capacitive load.The purpose of this thesis is to develop a tri-mode, intelligent solid-state circuit breaker technology using wide bandgap semiconductors (especially Gallium Nitride transistors), referred to as iBreaker. The iBreaker design methodology includes the use of mΩ-resistance GaN and SiC devices, new circuit topology and control techniques beyond the commonly used ON/OFF switch configuration, and integration of intelligent functions without increasing component count. The iBreaker adopts a distinct pulse width modulation (PWM) current limiting (PWM-CL) state in addition to the conventional ON and OFF states to facilitate soft startup, fault authentication, and fault location functions. Key design elements, such as use of wide bandgap (particularly GaN) switches, tri-mode operation, combined digital and analog control, the bidirectional buck topology, variable PWM frequency control and universal hardware/software architecture, are discussed in detail. Multiple iBreaker prototypes, rated at 380 V/20 A and 1000 V/10 A, respectively, are built and tested to validate the proposed SSCB design concept. 99.95% transmission efficiency, passive cooling, and μs-scale response time are demonstrated experimentally.
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