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- Genre: Masters Thesis
- Creators: Tamizhmani, Govindasamy
- Creators: Papandreou-Suppappola, Antonia
Description
Due to the growing concerns on the depletion of petroleum based energy resources and climate change; fuel cell technologies have received much attention in recent years. Proton exchange membrane fuel cell (PEMFCs) features high energy conversion efficiency and nearly zero greenhouse gas emissions, because of its combination of the hydrogen oxidation reaction (HOR) at anode side and oxygen reduction reaction (ORR) at cathode side. Synthesis of Pt nanoparticles supported on multi walled carbon nanotubes (MWCNTs) possess a highly durable electrochemical surface area (ESA) and show good power output on proton exchange membrane (PEM) fuel cell performance. Platinum on multi-walled carbon nanotubes (MWCNTs) support were synthesized by two different processes to transfer PtCl62- from aqueous to organic phase. While the first method of Pt/MWCNTs synthesis involved dodecane thiol (DDT) and octadecane thiol (ODT) as anchoring agent, the second method used ammonium lauryl sulfate (ALS) as the dispersion/anchoring agent. The particle size and distribution of platinum were examined by high-resolution transmission electron microscope (HRTEM). The TEM images showed homogenous distribution and uniform particle size of platinum deposited on the surface of MWCNTs. The single cell fuel cell performance of the Pt/MWCNTs synthesized thiols and ALS based electrode containing 0.2 (anode) and 0.4 mg (cathode) Pt.cm-2 were evaluated using Nafion-212 electrolyte with H2 and O2 gases at 80 oC and ambient pressure. The catalyst synthesis with ALS is relatively simple compared to that with thiols and also showed higher performance (power density reaches about 1070 mW.cm-2). The Electrodes with Pt/MWCNTs nanocatalysts synthesized using ALS were characterized by cyclic voltammetry (CV) for durability evaluation using humidified H2 and N2 gases at room temperature (21 oC) along with commercial Pt/C for comparison. The ESA measured by cyclic voltammetry between 0.15 and 1.2 V showed significant less degradation after 1000 cycles for ALS based Pt/MWCNTs.
ContributorsLiu, Xuan (Author) / Madakannan, Arunachalanadar (Thesis advisor) / Munukutla, Lakshmi (Committee member) / Tamizhmani, Govindasamy (Committee member) / Arizona State University (Publisher)
Created2011
Description
Infant mortality rate of field deployed photovoltaic (PV) modules may be expected to be higher than that estimated by standard qualification tests. The reason for increased failure rates may be attributed to the high system voltages. High voltages (HV) in grid connected modules induce additional stress factors that cause new degradation mechanisms. These new degradation mechanisms are not recognized by qualification stress tests. To study and model the effect of high system voltages, recently, potential induced degradation (PID) test method has been introduced. Using PID studies, it has been reported that high voltage failure rates are essentially due to increased leakage currents from active semiconducting layer to the grounded module frame, through encapsulant and/or glass. This project involved designing and commissioning of a new PID test bed at Photovoltaic Reliability Laboratory (PRL) of Arizona State University (ASU) to study the mechanisms of HV induced degradation. In this study, PID stress tests have been performed on accelerated stress modules, in addition to fresh modules of crystalline silicon technology. Accelerated stressing includes thermal cycling (TC200 cycles) and damp heat (1000 hours) tests as per IEC 61215. Failure rates in field deployed modules that are exposed to long term weather conditions are better simulated by conducting HV tests on prior accelerated stress tested modules. The PID testing was performed in 3 phases on a set of 5 mono crystalline silicon modules. In Phase-I of PID test, a positive bias of +600 V was applied, between shorted leads and frame of each module, on 3 modules with conducting carbon coating on glass superstrate. The 3 module set was comprised of: 1 fresh control, TC200 and DH1000. The PID test was conducted in an environmental chamber by stressing the modules at 85°C, for 35 hours with an intermittent evaluation for Arrhenius effects. In the Phase-II, a negative bias of -600 V was applied on a set of 3 modules in the chamber as defined above. The 3 module set in phase-II was comprised of: control module from phase-I, TC200 and DH1000. In the Phase-III, the same set of 3 modules which were used in the phase-II again subjected to +600 V bias to observe the recovery of lost power during the Phase-II. Electrical performance, infrared (IR) and electroluminescence (EL) were done prior and post PID testing. It was observed that high voltage positive bias in the first phase resulted in little
o power loss, high voltage negative bias in the second phase caused significant power loss and the high voltage positive bias in the third phase resulted in major recovery of lost power.
o power loss, high voltage negative bias in the second phase caused significant power loss and the high voltage positive bias in the third phase resulted in major recovery of lost power.
ContributorsGoranti, Sandhya (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Rogers, Bradley (Committee member) / Macia, Narciso (Committee member) / Arizona State University (Publisher)
Created2011
Description
Advancements in computer vision and machine learning have added a new dimension to remote sensing applications with the aid of imagery analysis techniques. Applications such as autonomous navigation and terrain classification which make use of image classification techniques are challenging problems and research is still being carried out to find better solutions. In this thesis, a novel method is proposed which uses image registration techniques to provide better image classification. This method reduces the error rate of classification by performing image registration of the images with the previously obtained images before performing classification. The motivation behind this is the fact that images that are obtained in the same region which need to be classified will not differ significantly in characteristics. Hence, registration will provide an image that matches closer to the previously obtained image, thus providing better classification. To illustrate that the proposed method works, naïve Bayes and iterative closest point (ICP) algorithms are used for the image classification and registration stages respectively. This implementation was tested extensively in simulation using synthetic images and using a real life data set called the Defense Advanced Research Project Agency (DARPA) Learning Applied to Ground Robots (LAGR) dataset. The results show that the ICP algorithm does help in better classification with Naïve Bayes by reducing the error rate by an average of about 10% in the synthetic data and by about 7% on the actual datasets used.
ContributorsMuralidhar, Ashwini (Author) / Saripalli, Srikanth (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Turaga, Pavan (Committee member) / Arizona State University (Publisher)
Created2011
Description
Building Applied Photovoltaics (BAPV) form an essential part of today's solar economy. This thesis is an effort to compare and understand the effect of fan cooling on the temperature of rooftop photovoltaic (PV) modules by comparing two side-by-side arrays (test array and control array) under identical ambient conditions of irradiance, air temperature, wind speed and wind direction. The lower operating temperature of PV modules due to fan operation mitigates array non uniformity and improves on performance. A crystalline silicon (c-Si) PV module has a light to electrical conversion efficiency of 14-20%. So on a cool sunny day with incident solar irradiance of 1000 W/m2, a PV module with 15% efficiency, will produce about only 150 watts. The rest of the energy is primarily lost in the form of heat. Heat extraction methods for BAPV systems may become increasingly higher in demand as the hot stagnant air underneath the array can be extracted to improve the array efficiency and the extracted low-temperature heat can also be used for residential space heating and water heating. Poly c-Si modules experience a negative temperature coefficient of power at about -0.5% /o C. A typical poly c-Si module would experience power loss due to elevation in temperature, which may be in the range of 25 to 30% for desert conditions such as that of Mesa, Arizona. This thesis investigates the effect of fan cooling on the previously developed thermal models at Arizona State University and on the performance of PV modules/arrays. Ambient conditions are continuously monitored and collected to calculate module temperature using the thermal model and to compare with actually measured temperature of individual modules. Including baseline analysis, the thesis has also looked into the effect of fan on the test array in three stages of 14 continuous days each. Multiple Thermal models are developed in order to identify the effect of fan cooling on performance and temperature uniformity. Although the fan did not prove to have much significant cooling effect on the system, but when combined with wind blocks it helped improve the thermal mismatch both under low and high wind speed conditions.
ContributorsChatterjee, Saurabh (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Rogers, Bradley (Committee member) / Macia, Narciso (Committee member) / Arizona State University (Publisher)
Created2011
Description
Photovoltaic (PV) modules undergo performance degradation depending on climatic conditions, applications, and system configurations. The performance degradation prediction of PV modules is primarily based on Accelerated Life Testing (ALT) procedures. In order to further strengthen the ALT process, additional investigation of the power degradation of field aged PV modules in various configurations is required. A detailed investigation of 1,900 field aged (12-18 years) PV modules deployed in a power plant application was conducted for this study. Analysis was based on the current-voltage (I-V) measurement of all the 1,900 modules individually. I-V curve data of individual modules formed the basis for calculating the performance degradation of the modules. The percentage performance degradation and rates of degradation were compared to an earlier study done at the same plant. The current research was primarily focused on identifying the extent of potential induced degradation (PID) of individual modules with reference to the negative ground potential. To investigate this, the arrangement and connection of the individual modules/strings was examined in detail. The study also examined the extent of underperformance of every series string due to performance mismatch of individual modules in that string. The power loss due to individual module degradation and module mismatch at string level was then compared to the rated value.
ContributorsJaspreet Singh (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Srinivasan, Devarajan (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2011
Description
Recent changes in the energy markets structure combined with the conti-nuous load growth have caused power systems to be operated under more stressed conditions. In addition, the nature of power systems has also grown more complex and dynamic because of the increasing use of long inter-area tie-lines and the high motor loads especially those comprised mainly of residential single phase A/C motors. Therefore, delayed voltage recovery, fast voltage collapse and short term voltage stability issues in general have obtained significant importance in relia-bility studies. Shunt VAr injection has been used as a countermeasure for voltage instability. However, the dynamic and fast nature of short term voltage instability requires fast and sufficient VAr injection, and therefore dynamic VAr devices such as Static VAr Compensators (SVCs) and STATic COMpensators (STAT-COMs) are used. The location and size of such devices are optimized in order to improve their efficiency and reduce initial costs. In this work time domain dy-namic analysis was used to evaluate trajectory voltage sensitivities for each time step. Linear programming was then performed to determine the optimal amount of required VAr injection at each bus, using voltage sensitivities as weighting factors. Optimal VAr injection values from different operating conditions were weighted and averaged in order to obtain a final setting of the VAr requirement. Some buses under consideration were either assigned very small VAr injection values, or not assigned any value at all. Therefore, the approach used in this work was found to be useful in not only determining the optimal size of SVCs, but also their location.
ContributorsSalloum, Ahmed (Author) / Vittal, Vijay (Thesis advisor) / Heydt, Gerald (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2011
Description
This research work describes the design of a fault current limiter (FCL) using digital logic and a microcontroller based data acquisition system for an ultra fast pilot protection system. These systems have been designed according to the requirements of the Future Renewable Electric Energy Delivery and Management (FREEDM) system (or loop), a 1 MW green energy hub. The FREEDM loop merges advanced power electronics technology with information tech-nology to form an efficient power grid that can be integrated with the existing power system. With the addition of loads to the FREEDM system, the level of fault current rises because of increased energy flow to supply the loads, and this requires the design of a limiter which can limit this current to a level which the existing switchgear can interrupt. The FCL limits the fault current to around three times the rated current. Fast switching Insulated-gate bipolar transistor (IGBT) with its gate control logic implements a switching strategy which enables this operation. A complete simulation of the system was built on Simulink and it was verified that the FCL limits the fault current to 1000 A compared to more than 3000 A fault current in the non-existence of a FCL. This setting is made user-defined. In FREEDM system, there is a need to interrupt a fault faster or make intelligent deci-sions relating to fault events, to ensure maximum availability of power to the loads connected to the system. This necessitates fast acquisition of data which is performed by the designed data acquisition system. The microcontroller acquires the data from a current transformer (CT). Mea-surements are made at different points in the FREEDM system and merged together, to input it to the intelligent protection algorithm that has been developed by another student on the project. The algorithm will generate a tripping signal in the event of a fault. The developed hardware and the programmed software to accomplish data acquisition and transmission are presented here. The designed FCL ensures that the existing switchgear equipments need not be replaced thus aiding future power system expansion. The developed data acquisition system enables fast fault sensing in protection schemes improving its reliability.
ContributorsThirumalai, Arvind (Author) / Karady, George G. (Thesis advisor) / Vittal, Vijay (Committee member) / Hedman, Kory (Committee member) / Arizona State University (Publisher)
Created2011
Description
Spotlight mode synthetic aperture radar (SAR) imaging involves a tomo- graphic reconstruction from projections, necessitating acquisition of large amounts of data in order to form a moderately sized image. Since typical SAR sensors are hosted on mobile platforms, it is common to have limitations on SAR data acquisi- tion, storage and communication that can lead to data corruption and a resulting degradation of image quality. It is convenient to consider corrupted samples as missing, creating a sparsely sampled aperture. A sparse aperture would also result from compressive sensing, which is a very attractive concept for data intensive sen- sors such as SAR. Recent developments in sparse decomposition algorithms can be applied to the problem of SAR image formation from a sparsely sampled aperture. Two modified sparse decomposition algorithms are developed, based on well known existing algorithms, modified to be practical in application on modest computa- tional resources. The two algorithms are demonstrated on real-world SAR images. Algorithm performance with respect to super-resolution, noise, coherent speckle and target/clutter decomposition is explored. These algorithms yield more accu- rate image reconstruction from sparsely sampled apertures than classical spectral estimators. At the current state of development, sparse image reconstruction using these two algorithms require about two orders of magnitude greater processing time than classical SAR image formation.
ContributorsWerth, Nicholas (Author) / Karam, Lina (Thesis advisor) / Papandreou-Suppappola, Antonia (Committee member) / Spanias, Andreas (Committee member) / Arizona State University (Publisher)
Created2011
Description
For synthetic aperture radar (SAR) image formation processing, the chirp scaling algorithm (CSA) has gained considerable attention mainly because of its excellent target focusing ability, optimized processing steps, and ease of implementation. In particular, unlike the range Doppler and range migration algorithms, the CSA is easy to implement since it does not require interpolation, and it can be used on both stripmap and spotlight SAR systems. Another transform that can be used to enhance the processing of SAR image formation is the fractional Fourier transform (FRFT). This transform has been recently introduced to the signal processing community, and it has shown many promising applications in the realm of SAR signal processing, specifically because of its close association to the Wigner distribution and ambiguity function. The objective of this work is to improve the application of the FRFT in order to enhance the implementation of the CSA for SAR processing. This will be achieved by processing real phase-history data from the RADARSAT-1 satellite, a multi-mode SAR platform operating in the C-band, providing imagery with resolution between 8 and 100 meters at incidence angles of 10 through 59 degrees. The phase-history data will be processed into imagery using the conventional chirp scaling algorithm. The results will then be compared using a new implementation of the CSA based on the use of the FRFT, combined with traditional SAR focusing techniques, to enhance the algorithm's focusing ability, thereby increasing the peak-to-sidelobe ratio of the focused targets. The FRFT can also be used to provide focusing enhancements at extended ranges.
ContributorsNorthrop, Judith (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Spanias, Andreas (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Arizona State University (Publisher)
Created2011
Description
The tracking of multiple targets becomes more challenging in complex environments due to the additional degrees of nonlinearity in the measurement model. In urban terrain, for example, there are multiple reflection path measurements that need to be exploited since line-of-sight observations are not always available. Multiple target tracking in urban terrain environments is traditionally implemented using sequential Monte Carlo filtering algorithms and data association techniques. However, data association techniques can be computationally intensive and require very strict conditions for efficient performance. This thesis investigates the probability hypothesis density (PHD) method for tracking multiple targets in urban environments. The PHD is based on the theory of random finite sets and it is implemented using the particle filter. Unlike data association methods, it can be used to estimate the number of targets as well as their corresponding tracks. A modified maximum-likelihood version of the PHD (MPHD) is proposed to automatically and adaptively estimate the measurement types available at each time step. Specifically, the MPHD allows measurement-to-nonlinearity associations such that the best matched measurement can be used at each time step, resulting in improved radar coverage and scene visibility. Numerical simulations demonstrate the effectiveness of the MPHD in improving tracking performance, both for tracking multiple targets and targets in clutter.
ContributorsZhou, Meng (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Tepedelenlioğlu, Cihan (Committee member) / Kovvali, Narayan (Committee member) / Arizona State University (Publisher)
Created2011