Hybrid Power System Intelligent Operation and Protection Involving Plug-in Electric Vehicles

Two key solutions to reduce the greenhouse gas emissions and increase the overall energy efficiency are to maximize the utilization of renewable energy resources (RERs) to generate energy for load consumption and to shift to low or zero emission plug-in electric vehicles (PEVs) for transportation. The present U.S. aging and overburdened power grid infrastructure is under a tremendous pressure to handle the issues involved in penetration of RERS and PEVs. The future power grid should be designed with for the effective utilization of distributed RERs and distributed generations to intelligently respond to varying customer demand including PEVs with high level of security, stability and reliability. This dissertation develops and verifies such a hybrid AC-DC power system. The system will operate in a distributed manner incorporating multiple components in both AC and DC styles and work in both grid-connected and islanding modes. The verification was performed on a laboratory-based hybrid AC-DC power system testbed as hardware/software platform. In this system, RERs emulators together with their maximum power point tracking technology and power electronics converters were designed to test different energy harvesting algorithms. The Energy storage devices including lithium-ion batteries and ultra-capacitors were used to optimize the performance of the hybrid power system. A lithium-ion battery smart energy management system with thermal and state of charge self-balancing was proposed to protect the energy storage system. A grid connected DC PEVs parking garage emulator, with five lithium-ion batteries was also designed with the smart charging functions that can emulate the future vehicle-to-grid (V2G), vehicle-to-vehicle (V2V) and vehicle-to-house (V2H) services. This includes grid voltage and frequency regulations, spinning reserves, micro grid islanding detection and energy resource support. The results show successful integration of the developed techniques for control and energy management of future hybrid AC-DC power systems with high penetration of RERs and PEVs.

Hybrid power system intelligent operation and protection involving plug-in electric vehicles

Two key solutions to reduce the greenhouse gas emissions and increase the overall energy efficiency are to maximize the utilization of renewable energy resources (RERs) to generate energy for load consumption and to shift to low or zero emission plug-in electric vehicles (PEVs) for transportation. The present U.S. aging and overburdened power grid infrastructure is under a tremendous pressure to handle the issues involved in penetration of RERS and PEVs. The future power grid should be designed with for the effective utilization of distributed RERs and distributed generations to intelligently respond to varying customer demand including PEVs with high level of security, stability and reliability. This dissertation develops and verifies such a hybrid AC-DC power system. The system will operate in a distributed manner incorporating multiple components in both AC and DC styles and work in both grid-connected and islanding modes. ^ The verification was performed on a laboratory-based hybrid AC-DC power system testbed as hardware/software platform. In this system, RERs emulators together with their maximum power point tracking technology and power electronics converters were designed to test different energy harvesting algorithms. The Energy storage devices including lithium-ion batteries and ultra-capacitors were used to optimize the performance of the hybrid power system. A lithium-ion battery smart energy management system with thermal and state of charge self-balancing was proposed to protect the energy storage system. A grid connected DC PEVs parking garage emulator, with five lithium-ion batteries was also designed with the smart charging functions that can emulate the future vehicle-to-grid (V2G), vehicle-to-vehicle (V2V) and vehicle-to-house (V2H) services. This includes grid voltage and frequency regulations, spinning reserves, micro grid islanding detection and energy resource support. ^ The results show successful integration of the developed techniques for control and energy management of future hybrid AC-DC power systems with high penetration of RERs and PEVs.^

Parameter optimization for noise and vibration reduction associated with position and speed sensorless control of permanent magnet machines at low speed

With the advantages and popularity of Permanent Magnet (PM) motors due to their high power density, there is an increasing incentive to use them in variety of applications including electric actuation. These applications have strict noise emission standards. The generation of audible noise and associated vibration modes are characteristics of all electric motors, it is especially problematic in low speed sensorless control rotary actuation applications using high frequency voltage injection technique. This dissertation is aimed at solving the problem of optimizing the sensorless control algorithm for low noise and vibration while achieving at least 12 bit absolute accuracy for speed and position control. The low speed sensorless algorithm is simulated using an improved Phase Variable Model, developed and implemented in a hardware-in-the-loop prototyping environment. Two experimental testbeds were developed and built to test and verify the algorithm in real time.^ A neural network based modeling approach was used to predict the audible noise due to the high frequency injected carrier signal. This model was created based on noise measurements in an especially built chamber. The developed noise model is then integrated into the high frequency based sensorless control scheme so that appropriate tradeoffs and mitigation techniques can be devised. This will improve the position estimation and control performance while keeping the noise below a certain level. Genetic algorithms were used for including the noise optimization parameters into the developed control algorithm.^ A novel wavelet based filtering approach was proposed in this dissertation for the sensorless control algorithm at low speed. This novel filter was capable of extracting the position information at low values of injection voltage where conventional filters fail. This filtering approach can be used in practice to reduce the injected voltage in sensorless control algorithm resulting in significant reduction of noise and vibration.^ Online optimization of sensorless position estimation algorithm was performed to reduce vibration and to improve the position estimation performance. The results obtained are important and represent original contributions that can be helpful in choosing optimal parameters for sensorless control algorithm in many practical applications.^

Structural Health Monitoring using Index Based Reasoning for Unmanned Aerial Vehicles

Unmanned Aerial Vehicles (UAVs) may develop cracks, erosion, delamination or other damages due to aging, fatigue or extreme loads. Identifying these damages is critical for the safe and reliable operation of the systems. ^ Structural Health Monitoring (SHM) is capable of determining the conditions of systems automatically and continually through processing and interpreting the data collected from a network of sensors embedded into the systems. With the desired awareness of the systems’ health conditions, SHM can greatly reduce operational cost and speed up maintenance processes. ^ The purpose of this study is to develop an effective, low-cost, flexible and fault tolerant structural health monitoring system. The proposed Index Based Reasoning (IBR) system started as a simple look-up-table based diagnostic system. Later, Fast Fourier Transformation analysis and neural network diagnosis with self-learning capabilities were added. The current version is capable of classifying different health conditions with the learned characteristic patterns, after training with the sensory data acquired from the operating system under different status. ^ The proposed IBR systems are hierarchy and distributed networks deployed into systems to monitor their health conditions. Each IBR node processes the sensory data to extract the features of the signal. Classifying tools are then used to evaluate the local conditions with health index (HI) values. The HI values will be carried to other IBR nodes in the next level of the structured network. The overall health condition of the system can be obtained by evaluating all the local health conditions. ^ The performance of IBR systems has been evaluated by both simulation and experimental studies. The IBR system has been proven successful on simulated cases of a turbojet engine, a high displacement actuator, and a quad rotor helicopter. For its application on experimental data of a four rotor helicopter, IBR also performed acceptably accurate. The proposed IBR system is a perfect fit for the low-cost UAVs to be the onboard structural health management system. It can also be a backup system for aircraft and advanced Space Utility Vehicles. ^

Positron emission tomography (PET) tumor segmentation and quantification: Development of new algorithms

Tumor functional volume (FV) and its mean activity concentration (mAC) are the quantities derived from positron emission tomography (PET). These quantities are used for estimating radiation dose for a therapy, evaluating the progression of a disease and also use it as a prognostic indicator for predicting outcome. PET images have low resolution, high noise and affected by partial volume effect (PVE). Manually segmenting each tumor is very cumbersome and very hard to reproduce. To solve the above problem I developed an algorithm, called iterative deconvolution thresholding segmentation (IDTS) algorithm; the algorithm segment the tumor, measures the FV, correct for the PVE and calculates mAC. The algorithm corrects for the PVE without the need to estimate camera's point spread function (PSF); also does not require optimizing for a specific camera. My algorithm was tested in physical phantom studies, where hollow spheres (0.5-16 ml) were used to represent tumors with a homogeneous activity distribution. It was also tested on irregular shaped tumors with a heterogeneous activity profile which were acquired using physical and simulated phantom. The physical phantom studies were performed with different signal to background ratios (SBR) and with different acquisition times (1-5 min). The algorithm was applied on ten clinical data where the results were compared with manual segmentation and fixed percentage thresholding method called T50 and T60 in which 50% and 60% of the maximum intensity respectively is used as threshold. The average error in FV and mAC calculation was 30% and -35% for 0.5 ml tumor. The average error FV and mAC calculation were ~5% for 16 ml tumor. The overall FV error was ∼10% for heterogeneous tumors in physical and simulated phantom data. The FV and mAC error for clinical image compared to manual segmentation was around -17% and 15% respectively. In summary my algorithm has potential to be applied on data acquired from different cameras as its not dependent on knowing the camera's PSF. The algorithm can also improve dose estimation and treatment planning.^

High pressure and low temperature study of ammonia borane and lithium amidoborane

Hydrogen has been considered as a potentially efficient and environmentally friendly alternative energy solution. However, one of the most important scientific and technical challenges that the "hydrogen economy" faces is the development of safe and economically viable on-board hydrogen storage for fuel cell applications, especially to the transportation sector. Ammonia borane (BH3NH 3), a solid state hydrogen storage material, possesses exceptionally high hydrogen content (19.6 wt%).However, a fairly high temperature is required to release all the hydrogen atoms, along with the emission of toxic borazine. Recently research interests are focusing on the improvement of H2 discharge from ammonia borane (AB) including lowering the dehydrogenation temperature and enhancing hydrogen release rate using different techniques. Till now the detailed information about the bonding characteristics of AB is not sufficient to understand details about its phases and structures. ^ Elemental substitution of ammonia borane produces metal amidoboranes. Introduction of metal atoms to the ammonia borane structure may alter the bonding characteristics. Lithium amidoborane is synthesized by ball milling of ammonia borane and lithium hydride. High pressure study of molecular crystal provides unique insight into the intermolecular bonding forces and phase stability. During this dissertation, Raman spectroscopic study of lithium amidoborane has been carried out at high pressure in a diamond anvil cell. It has been identified that there is no dihydrogen bond in the lithium amidoborane structure, whereas dihydrogen bond is the characteristic bond of the parent compound ammonia borane. It has also been identified that the B-H bond becomes weaker, whereas B-N and N-H bonds become stronger than those in the parent compound ammonia borane. At high pressure up to 15 GPa, Raman spectroscopic study indicates two phase transformations of lithium amidoborane, whereas synchrotron X-ray diffraction data indicates only one phase transformation of this material. ^ Pressure and temperature has a significant effect on the structural stability of ammonia borane. This dissertation explored the phase transformation behavior of ammonia borane at high pressure and low temperature using in situ Raman spectroscopy. The P-T phase boundary between the tetragonal (I4mm) and orthorhombic (Pmn21) phases of ammonia borane has been determined. The transition has a positive Clapeyron slope which indicates the transition is of exothermic in nature. Influence of nanoconfinemment on the I4mm to Pmn2 1 phase transition of ammonia borane was also investigated. Mesoporus silica scaffolds SBA-15 with pore size of ~8 nm and MCM-41 with pore size of 2.1-2.7 nm, were used to nanoconfine ammonia borane. During cooling down, the I4mm to Pmn21 phase transition was not observed in MCM-41 nanoconfined ammonia borane, whereas the SBA-15 nanocondfined ammonia borane shows the phase transition at ~195 K. Four new phases of ammonia borane were also identified at high pressure up to 15 GPa and low temperature down to 90 K.^

Enhancement of field emission from multistage structure of carbon nanotube arrays

The field emission measurements for the multistage structured nanotubes (i.e., thin-multiwall and single wall carbon nanotubes grown on multiwall carbon nanotubes) were carried out and a low turn-on field of ~0.45 V/ μm, high emission current of 450 μA at a field of IV/μm and a large field enhancement factor of ~26200 were obtained. The thin multiwall carbon nanotubes (thin-MWNTs) and single wall carbon nanotubes (SWNTs) were grown on the regular arrays of vertically aligned multi wall carbon nanotubes (MWNTs) on porous silicon substrate by Chemical Vapor Deposition (CVD) method. The thin-MWNTs and SWNTs grown on MWNTs in this way have a multistage structure which gives higher enhancement of the electric field and hence the electron field emission.

Design and Synthesis of 4-N-Alkanoyl and 4-N-Alkyl Gemcitabine Analogues Suitable for Positron Emission Tomography

Gemcitabine is a highly potent chemotherapeutic nucleoside agent used in the treatment of several cancers and solid tumors. However, it is therapeutically limitated because of toxicity to normal cells and its rapid intracellular deamination by cytidine deaminase into the inactive uracil derivative. Modification at the 4-(N) position of gemcitabine's exocyclic amine to an -amide functionality is a well reported prodrug strategy which has been that confers a resistance to intracellular deamination while also altering pharmacokinetics of the parent drug. Coupling of gemcitabine to carboxylic acids with varying terminal moieties afforded the 4-N-alkanoylgemcitabines whereas reaction of 4-N-tosylgemcitabine with the corresponding alkyl amines gave the 4-N-alkylgemcitabines. The 4-N-alkanoyl and 4-N-alkyl gemcitabine analogues with a terminal hydroxyl group on the 4-N-alkanoyl or 4-N-alkyl chain were efficiently fluorinated either with diethylaminosulfur trifluoride or under conditions that are compatible with the synthetic protocols for 18F labeling, such as displacement of the corresponding mesylate with KF/Kryptofix 2.2.2. The 4-N-alkanoylgemcitabine analogues displayed potent cytostatic activities against murine and human tumor cell lines with 50% inhibitory concentration (IC50) values in the range of low nM, whereas cytotoxicity of the 4-N-alkylgemcitabine derivatives were in the low to modest µM range. The cytostatic activity of the 4-N-alkanoylgemcitabines was reduced by several orders of magnitude in the 2'-deoxycytidine kinase (dCK)-deficient CEM/dCK- cell line while the 4-N-alkylgemcitabines were only lowered by 2-5 times. None of the 4-N-modified gemcitabines were found to be substrates for cytosolic dCK, however all were found to inhibit DNA synthesis. As such, the 4-N-alkanoyl gemcitabine derivatives likely need to be converted to gemcitabine prior to achieving their significant cytostatic potential, whereas the 4-N-alkylgemcitabines reach their modest activity without "measurable" conversion to gemcitabine. Thus, the 4-N-alkylgemcitabines provide valuable insight on the metabolism of 4-N-modified gemcitabine prodrugs.

Positron Emission Tomography (PET) Tumor Segmentation and Quantification: Development of New Algorithms

Tumor functional volume (FV) and its mean activity concentration (mAC) are the quantities derived from positron emission tomography (PET). These quantities are used for estimating radiation dose for a therapy, evaluating the progression of a disease and also use it as a prognostic indicator for predicting outcome. PET images have low resolution, high noise and affected by partial volume effect (PVE). Manually segmenting each tumor is very cumbersome and very hard to reproduce. To solve the above problem I developed an algorithm, called iterative deconvolution thresholding segmentation (IDTS) algorithm; the algorithm segment the tumor, measures the FV, correct for the PVE and calculates mAC. The algorithm corrects for the PVE without the need to estimate camera’s point spread function (PSF); also does not require optimizing for a specific camera. My algorithm was tested in physical phantom studies, where hollow spheres (0.5-16 ml) were used to represent tumors with a homogeneous activity distribution. It was also tested on irregular shaped tumors with a heterogeneous activity profile which were acquired using physical and simulated phantom. The physical phantom studies were performed with different signal to background ratios (SBR) and with different acquisition times (1-5 min). The algorithm was applied on ten clinical data where the results were compared with manual segmentation and fixed percentage thresholding method called T50 and T60 in which 50% and 60% of the maximum intensity respectively is used as threshold. The average error in FV and mAC calculation was 30% and -35% for 0.5 ml tumor. The average error FV and mAC calculation were ~5% for 16 ml tumor. The overall FV error was ~10% for heterogeneous tumors in physical and simulated phantom data. The FV and mAC error for clinical image compared to manual segmentation was around -17% and 15% respectively. In summary my algorithm has potential to be applied on data acquired from different cameras as its not dependent on knowing the camera’s PSF. The algorithm can also improve dose estimation and treatment planning.

High Pressure and Low Temperature Study of Ammonia Borane and Lithium Amidoborane

Hydrogen has been considered as a potentially efficient and environmentally friendly alternative energy solution. However, one of the most important scientific and technical challenges that the “hydrogen economy” faces is the development of safe and economically viable on-board hydrogen storage for fuel cell applications, especially to the transportation sector. Ammonia borane (BH3NH3), a solid state hydrogen storage material, possesses exceptionally high hydrogen content (19.6 wt%).However, a fairly high temperature is required to release all the hydrogen atoms, along with the emission of toxic borazine. Recently research interests are focusing on the improvement of H2 discharge from ammonia borane (AB) including lowering the dehydrogenation temperature and enhancing hydrogen release rate using different techniques. Till now the detailed information about the bonding characteristics of AB is not sufficient to understand details about its phases and structures. Elemental substitution of ammonia borane produces metal amidoboranes. Introduction of metal atoms to the ammonia borane structure may alter the bonding characteristics. Lithium amidoborane is synthesized by ball milling of ammonia borane and lithium hydride. High pressure study of molecular crystal provides unique insight into the intermolecular bonding forces and phase stability. During this dissertation, Raman spectroscopic study of lithium amidoborane has been carried out at high pressure in a diamond anvil cell. It has been identified that there is no dihydrogen bond in the lithium amidoborane structure, whereas dihydrogen bond is the characteristic bond of the parent compound ammonia borane. It has also been identified that the B-H bond becomes weaker, whereas B-N and N-H bonds become stronger than those in the parent compound ammonia borane. At high pressure up to 15 GPa, Raman spectroscopic study indicates two phase transformations of lithium amidoborane, whereas synchrotron X-ray diffraction data indicates only one phase transformation of this material. Pressure and temperature has a significant effect on the structural stability of ammonia borane. This dissertation explored the phase transformation behavior of ammonia borane at high pressure and low temperature using in situ Raman spectroscopy. The P-T phase boundary between the tetragonal (I4mm) and orthorhombic (Pmn21) phases of ammonia borane has been determined. The transition has a positive Clapeyron slope which indicates the transition is of exothermic in nature. Influence of nanoconfinemment on the I4mm to Pmn21 phase transition of ammonia borane was also investigated. Mesoporus silica scaffolds SBA-15 with pore size of ~8 nm and MCM-41 with pore size of 2.1-2.7 nm, were used to nanoconfine ammonia borane. During cooling down, the I4mm to Pmn21 phase transition was not observed in MCM-41 nanoconfined ammonia borane, whereas the SBA-15 nanocondfined ammonia borane shows the phase transition at ~195 K. Four new phases of ammonia borane were also identified at high pressure up to 15 GPa and low temperature down to 90 K.

Modeling, Simulation, and Characterization of Space Debris in low-Earth Orbit

Every space launch increases the overall amount of space debris. Satellites have limited awareness of nearby objects that might pose a collision hazard. Astrometric, radiometric, and thermal models for the study of space debris in low-Earth orbit have been developed. This modeled approach proposes analysis methods that provide increased Local Area Awareness for satellites in low-Earth and geostationary orbit. Local Area Awareness is defined as the ability to detect, characterize, and extract useful information regarding resident space objects as they move through the space environment surrounding a spacecraft. The study of space debris is of critical importance to all space-faring nations. Characterization efforts are proposed using long-wave infrared sensors for space-based observations of debris objects in low-Earth orbit. Long-wave infrared sensors are commercially available and do not require solar illumination to be observed, as their received signal is temperature dependent. The characterization of debris objects through means of passive imaging techniques allows for further studies into the origination, specifications, and future trajectory of debris objects. Conclusions are made regarding the aforementioned thermal analysis as a function of debris orbit, geometry, orientation with respect to time, and material properties. Development of a thermal model permits the characterization of debris objects based upon their received long-wave infrared signals. Information regarding the material type, size, and tumble-rate of the observed debris objects are extracted. This investigation proposes the utilization of long-wave infrared radiometric models of typical debris to develop techniques for the detection and characterization of debris objects via signal analysis of unresolved imagery. Knowledge regarding the orbital type and semi-major axis of the observed debris object are extracted via astrometric analysis. This knowledge may aid in the constraint of the admissible region for the initial orbit determination process. The resultant orbital information is then fused with the radiometric characterization analysis enabling further characterization efforts of the observed debris object. This fused analysis, yielding orbital, material, and thermal properties, significantly increases a satellite’s Local Area Awareness via an intimate understanding of the debris environment surrounding the spacecraft.