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Low temperature fuel cells are very attractive energy conversion technology for automotive applications due to their qualities of being clean, quiet, efficient and good peak power densities. However, due to high cost and limited durability and reliability, commercialization of this technology has not been possible as yet. The high fuel

Low temperature fuel cells are very attractive energy conversion technology for automotive applications due to their qualities of being clean, quiet, efficient and good peak power densities. However, due to high cost and limited durability and reliability, commercialization of this technology has not been possible as yet. The high fuel cell cost is mostly due to the expensive noble catalyst Pt. Alkaline fuel cell (AFC) systems, have potential to make use of non-noble catalysts and thus, provides with a solution of overall lower cost. Therefore, this issue has been addressed in this thesis work. Hydrogen-oxygen fuel cells using an alkaline anion exchange membrane were prepared and evaluated. Various non-platinum catalyst materials were investigated by fabricating membrane-electrode assemblies (MEAs) using Tokuyama membrane (# A201) and compared with commercial noble metal catalysts. Co and Fe phthalocyanine catalyst materials were synthesized using multi-walled carbon nanotubes (MWCNTs) as support materials. X-ray photoelectron spectroscopic study was conducted in order to examine the surface composition. The electroreduction of oxygen has been investigated on Fe phthalocyanine/MWCNT, Co phthalocyanine/MWCNT and commercial Pt/C catalysts. The oxygen reduction reaction kinetics on these catalyst materials were evaluated using rotating disk electrodes in 0.1 M KOH solution and the current density values were consistently higher for Co phthalocyanine based electrodes compared to Fe phthalocyanine. The fuel cell performance of the MEAs with Co and Fe phthalocyanines and Tanaka Kikinzoku Kogyo Pt/C cathode catalysts were 100, 60 and 120 mW cm-2 using H22 and O2 gases. This thesis also includes work on synthesizing nitrogen doped MWCNTs using post-doping and In-Situ methods. Post-doped N-MWNCTs were prepared through heat treatment with NH4OH as nitrogen source. Characterization was done through fuel cell testing, which gave peak power density ~40mW.cm-2. For In-Situ N-MWCT, pyridine was used as nitrogen source. The sample characterization was done using Raman spectroscopy and RBS, which showed the presence ~3 at.% of nitrogen on the carbon surface.
ContributorsShah, QuratulAin Jawed (Author) / Madakannan, Arunachalanadar (Thesis advisor) / Tamizhmani, Govindasamy (Committee member) / Macia, Narciso (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Power rating photovoltaic modules at six irradiance and four temperature matrix levels of IEC 61853-1 draft standard is one of the most important requirements to accurately predict energy production of photovoltaic modules at different climatic conditions. Two studies were carried out in this investigation: a measurement repeatability study and a

Power rating photovoltaic modules at six irradiance and four temperature matrix levels of IEC 61853-1 draft standard is one of the most important requirements to accurately predict energy production of photovoltaic modules at different climatic conditions. Two studies were carried out in this investigation: a measurement repeatability study and a translation procedure validation study. The repeatability study was carried out to define a testing methodology that allows generating repeatable power rating results under outdoor conditions. The validation study was carried out to validate the accuracy of the four translation procedures: the first three procedures are from the IEC 60891 standard and the fourth procedure is reported by NREL. These translation procedures are needed to translate the measured data from the actual test conditions to the reporting rating conditions required by the IEC 61853-1 draft standard. All the measurements were carried out outdoors on clear days using a manual, 2-axis tracker, located in Mesa/Tempe, Arizona. Four module technologies were investigated: crystalline silicon, amorphous silicon, cadmium telluride, and copper indium gallium selenide. The modules were cooled and then allowed to naturally warm up to obtain current-voltage data at different temperatures. Several black mesh screens with a wide range of transmittance were used for varying irradiance levels. From the measurements repeatability study, it was determined that: (i) a certain minimum distance (2 inches) should be maintained between module surface and the screen surface; (ii) the reference cell should be kept outside the screen (calibrated screen) as opposed to inside the screen (uncalibrated screen); and (iii) the air mass should not exceed 2.5. From the translation procedure validation study, it was determined that the accuracy of the translation procedure depends on the irradiance and temperature range of translation. The difference between measured and translatet power at maximum power point (Pmax) is determined to be less than 3% for all the technologies, all the irradiance/ temperature ranges investigated and all the procedures except Procedure 2 of IEC 60891 standard. For the Procedure 2, the difference was found to fall between 3% and 17% depending on the irradiance range used for the translation. The difference of 17% is very large and unacceptable. This work recommends reinvestigating the cause for this large difference for Procedure 2. Finally, a complete power rating matrix for each of the four module technologies has been successfully generated as per IEC 61853-1 draft standard.
ContributorsPaghasian, Karen (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Madakannan, Arunachalandar (Committee member) / Macia, Narciso F. (Committee member) / Arizona State University (Publisher)
Created2010
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Description
Thermal modeling and investigation into heat extraction methods for building-applied photovoltaic (BAPV) systems have become important for the industry in order to predict energy production and lower the cost per kilowatt-hour (kWh) of generating electricity from these types of systems. High operating temperatures have a direct impact on the performance

Thermal modeling and investigation into heat extraction methods for building-applied photovoltaic (BAPV) systems have become important for the industry in order to predict energy production and lower the cost per kilowatt-hour (kWh) of generating electricity from these types of systems. High operating temperatures have a direct impact on the performance of BAPV systems and can reduce power output by as much as 10 to 20%. The traditional method of minimizing the operating temperature of BAPV modules has been to include a suitable air gap for ventilation between the rooftop and the modules. There has been research done at Arizona State University (ASU) which investigates the optimum air gap spacing on sufficiently spaced (2-6 inch vertical; 2-inch lateral) modules of four columns. However, the thermal modeling of a large continuous array (with multiple modules of the same type and size and at the same air gap) had yet to be done at ASU prior to this project. In addition to the air gap effect analysis, the industry is exploring different ways of extracting the heat from PV modules including hybrid photovoltaic-thermal systems (PV/T). The goal of this project was to develop a thermal model for a small residential BAPV array consisting of 12 identical polycrystalline silicon modules at an air gap of 2.5 inches from the rooftop. The thermal model coefficients are empirically derived from a simulated field test setup at ASU and are presented in this thesis. Additionally, this project investigates the effects of cooling the array with a 40-Watt exhaust fan. The fan had negligible effect on power output or efficiency for this 2.5-inch air gap array, but provided slightly lower temperatures and better temperature uniformity across the array.
ContributorsHrica, Jonathan Kyler (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Rogers, Bradley (Committee member) / Macia, Narciso (Committee member) / Arizona State University (Publisher)
Created2010
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Description
Building applied photovoltaics (BAPV) is a major application sector for photovoltaics (PV). Due to the negative temperature coefficient of power output, the performance of a PV module decreases as the temperature of the module increases. In hot climatic conditions, such as the summer in Arizona, the operating temperature of a

Building applied photovoltaics (BAPV) is a major application sector for photovoltaics (PV). Due to the negative temperature coefficient of power output, the performance of a PV module decreases as the temperature of the module increases. In hot climatic conditions, such as the summer in Arizona, the operating temperature of a BAPV module can reach as high as 90°C. Considering a typical 0.5%/°C power drop for crystalline silicon (c-Si) modules, a performance decrease of approximately 30% would be expected during peak summer temperatures due to the difference between rated temperature (25°C) and operating temperature (~90°C) of the modules. Also, in a worst-case scenario, such as partial shading of the PV cells of air gap-free BAPV modules, some of the components could attain temperatures that would be high enough to compromise the safety and functionality requirements of the module and its components. Based on the temperature and weather data collected over a year in Arizona, a mathematical thermal model has been developed and presented in this paper to predict module temperature for five different air gaps (0", 1", 2", 3", and 4"). For comparison, modules with a thermally-insulated (R30) back were evaluated to determine the worst-case scenario. This thesis also provides key technical details related to the specially-built, simulated rooftop structure; the mounting configuration of the PV modules on the rooftop structure; the LabVIEW program that was developed for data acquisition and the MATLAB program for developing the thermal models. In order to address the safety issue, temperature test results (obtained in accordance with IEC 61730-2 and UL 1703 safety standards) are presented and analyzed for nine different components of a PV module, i.e., the front glass, substrate/backsheet (polymer), PV cell, j-box ambient, j-box surface, positive terminal, backsheet inside j-box, field wiring, and diode. The temperature test results obtained for about 140 crystalline silicon modules from a large number of manufacturers who tested modules between 2006 and 2009 at ASU/TÜV-PTL were analyzed and presented in this paper under three test conditions, i.e., short-circuit, open-circuit, and short-circuit and shaded. Also, the nominal operating cell temperatures (NOCTs) of the BAPV modules and insulated-back PV modules are presented in this paper for use by BAPV module designers and installers.
ContributorsOh, Jaewon (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Rogers, Bradley R (Committee member) / Macia, Narciso F. (Committee member) / Arizona State University (Publisher)
Created2010
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Description
Given the growing market in solar energy, specifically by the thin-film technologies, it is imperative that adequate and accurate standards be developed for these newer photovoltaic devices. Cadmium Telluride, CdTe, one of the major players in the thin-film PV industry is currently rated and certified using standards that have been

Given the growing market in solar energy, specifically by the thin-film technologies, it is imperative that adequate and accurate standards be developed for these newer photovoltaic devices. Cadmium Telluride, CdTe, one of the major players in the thin-film PV industry is currently rated and certified using standards that have been developed under the context of older technologies. The behavior of CdTe has been shown to be unique enough to suggesting that standards be revised. In this research, methods built on previous industry and independent studies are used to identify these unique behaviors. As well new methods are developed to further characterize CdTe modules in the context of current standards. Clear transient and meta-stable behavior is identified across modules from four different commercial manufacturers. Conclusions drawn from this study show illumination and temperature hysteresis effects on module ratings. Furthermore, suggestions for further study are given that could be used to define parameters for any reexamination of module standards.
ContributorsPetersen, Chad (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Macia, Narciso (Committee member) / Munukutla, Lakshmi (Committee member) / Arizona State University (Publisher)
Created2010
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Description
Photovoltaic (PV) modules appear to have three classifications of failure: Infant mortality, normal-life failure, and end-of-life failure. Little is known of the end-of-life failures experienced by PV modules due to their inherent longevity. Accelerated Life Testing (ALT) has been at the crux of this lifespan prediction; however, without naturally failing

Photovoltaic (PV) modules appear to have three classifications of failure: Infant mortality, normal-life failure, and end-of-life failure. Little is known of the end-of-life failures experienced by PV modules due to their inherent longevity. Accelerated Life Testing (ALT) has been at the crux of this lifespan prediction; however, without naturally failing modules an accurate acceleration factor cannot be determined for use in ALT. By observing modules that have been aged in the field, a comparison can be made with modules undergoing accelerated testing. In this study an investigation on about 1900 aged (10-17 years) grid-tied PV modules installed in the desert climatic condition of Arizona was undertaken. The investigation was comprised of a check sheet that documented any visual defects and their severity, infrared (IR) scanning, and current-voltage (I-V) curve measurements. After data was collected on modules, an analysis was performed to classify the failure modes and to determine the annual performance degradation rates.
ContributorsSuleske, Adam Alfred (Author) / Tamizhmani, Govindasamy (Thesis advisor) / Rogers, Bradley (Committee member) / Macia, Narciso (Committee member) / Arizona State University (Publisher)
Created2010
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Description
Suction stabilized floats have been implemented into a variety of applications such as supporting wind turbines in off-shore wind farms and for stabilizing cargo ships. This thesis proposes an alternative use for the technology in creating a system of suction stabilized floats equipped with real time location modules to hel

Suction stabilized floats have been implemented into a variety of applications such as supporting wind turbines in off-shore wind farms and for stabilizing cargo ships. This thesis proposes an alternative use for the technology in creating a system of suction stabilized floats equipped with real time location modules to help first responders establish a localized coordinate system to assist in rescues. The floats create a stabilized platform for each anchor module due to the inverse slack tank effect established by the inner water chamber. The design of the float has also been proven to be stable in most cases of amplitudes and frequencies ranging from 0 to 100 except for when the frequency ranges from 23 to 60 Hz for almost all values of the amplitude. The modules in the system form a coordinate grid based off the anchors that can track the location of a tag module within the range of the system using ultra-wideband communications. This method of location identification allows responders to use the system in GPS denied environments. The system can be accessed through an Android app with Bluetooth communications in close ranges or through internet of things (IoT) using a module as a listener, a Raspberry Pi and an internet source. The system has proven to identify the location of the tag in moderate ranges with an approximate accuracy of the tag location being 15 cm.
ContributorsDye, Michaela (Author) / Redkar, Sangram (Thesis advisor) / Sugar, Thomas (Committee member) / Rogers, Bradley (Committee member) / Arizona State University (Publisher)
Created2020
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Description
Trajectory forecasting is used in many fields such as vehicle future trajectory prediction, stock market price prediction, human motion prediction and so on. Also, robots having the capability to reason about human behavior is an important aspect in human robot interaction. In trajectory prediction with regards to human motion prediction,

Trajectory forecasting is used in many fields such as vehicle future trajectory prediction, stock market price prediction, human motion prediction and so on. Also, robots having the capability to reason about human behavior is an important aspect in human robot interaction. In trajectory prediction with regards to human motion prediction, implicit learning and reproduction of human behavior is the major challenge. This work tries to compare some of the recent advances taking a phenomenological approach to trajectory prediction. \par The work is expected to mainly target on generating future events or trajectories based on the previous data observed across many time intervals. In particular, this work presents and compares machine learning models to generate various human handwriting trajectories. Although the behavior of every individual is unique, it is still possible to broadly generalize and learn the underlying human behavior from the current observations to predict future human writing trajectories. This enables the machine or the robot to generate future handwriting trajectories given an initial trajectory from the individual thus helping the person to fill up the rest of the letter or curve. This work tests and compares the performance of Conditional Variational Autoencoders and Sinusoidal Representation Network models on handwriting trajectory prediction and reconstruction.
ContributorsKota, Venkata Anil (Author) / Ben Amor, Hani (Thesis advisor) / Venkateswara, Hemanth Kumar Demakethepalli (Committee member) / Redkar, Sangram (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Reinforcement Learning(RL) algorithms have made a remarkable contribution in the eld of robotics and training human-like agents. On the other hand, Evolutionary Algorithms(EA) are not well explored and promoted to use in the robotics field. However, they have an excellent potential to perform well. In thesis work, various RL learning

Reinforcement Learning(RL) algorithms have made a remarkable contribution in the eld of robotics and training human-like agents. On the other hand, Evolutionary Algorithms(EA) are not well explored and promoted to use in the robotics field. However, they have an excellent potential to perform well. In thesis work, various RL learning algorithms like Q-learning, Deep Deterministic Policy Gradient(DDPG), and Evolutionary Algorithms(EA) like Harmony Search Algorithm(HSA) are tested for a customized Penalty Kick Robot environment. The experiments are done with both discrete and continuous action space for a penalty kick agent. The main goal is to identify which algorithm suites best in which scenario. Furthermore, a goalkeeper agent is also introduced to block the ball from reaching the goal post using the multiagent learning algorithm.
ContributorsTrivedi, Maitry Ronakbhai (Author) / Amor, Heni Ben (Thesis advisor) / Redkar, Sangram (Thesis advisor) / Sugar, Thomas (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Multiple robotic arms collaboration is to control multiple robotic arms to collaborate with each other to work on the same task. During the collaboration, theagent is required to avoid all possible collisions between each part of the robotic arms. Thus, incentivizing collaboration and preventing collisions are the two principles which are followed

Multiple robotic arms collaboration is to control multiple robotic arms to collaborate with each other to work on the same task. During the collaboration, theagent is required to avoid all possible collisions between each part of the robotic arms. Thus, incentivizing collaboration and preventing collisions are the two principles which are followed by the agent during the training process. Nowadays, more and more applications, both in industry and daily lives, require at least two arms, instead of requiring only a single arm. A dual-arm robot satisfies much more needs of different types of tasks, such as folding clothes at home, making a hamburger in a grill or picking and placing a product in a warehouse. The applications done in this paper are all about object pushing. This thesis focuses on how to train the agent to learn pushing an object away as far as possible. Reinforcement Learning (RL), which is a type of Machine Learning (ML), is then utilized in this paper to train the agent to generate optimal actions. Deep Deterministic Policy Gradient (DDPG) and Hindsight Experience Replay (HER) are the two RL methods used in this thesis.
ContributorsLin, Steve (Author) / Ben Amor, Hani (Thesis advisor) / Redkar, Sangram (Committee member) / Zhang, Yu (Committee member) / Arizona State University (Publisher)
Created2023