Matching Items (54)
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- All Subjects: Electrical Engineering
- All Subjects: Point-of-care
- Creators: Ozev, Sule
Description
The efficiency of spacecraft’s solar cells reduces over the course of their operation. Traditionally, they are configured to extract maximum power at the end of their life and not have a system which dynamically extracts the maximum power over their entire life. This work demonstrates the benefit of dynamic re-configuration of spacecraft’s solar arrays to access the full power available from the solar panels throughout their lifetime. This dynamic re-configuration is achieved using enhancement mode GaN devices as the switches due to their low Ron and small footprint.
This work discusses hardware Implementation challenges and a prototype board is designed using components-off-the-shelf (COTS) to study the behavior of photovoltaic (PV) panels with different configurations of switches between 5 PV cells. The measurement results from the board proves the feasibility of the idea, showing the power improvements of having the switch structure. The measurement results are used to simulate a 1kW satellite system and understand practical trade-offs of this idea in actual satellite power systems.
Additionally, this work also presents the implementation of CMOS controller integrated circuit (IC) in 0.18um technology. The CMOS controller IC includes switched-capacitor converters in open loop to provide the floating voltages required to drive the GaN switches. Each CMOS controller IC can drive 10 switches in series and parallel combination. Furthermore, the designed controller IC is expected to operate under 300MRad of total dose radiation, thus enabling the controller modules to be placed on the solar cell wings of the satellites.
This work discusses hardware Implementation challenges and a prototype board is designed using components-off-the-shelf (COTS) to study the behavior of photovoltaic (PV) panels with different configurations of switches between 5 PV cells. The measurement results from the board proves the feasibility of the idea, showing the power improvements of having the switch structure. The measurement results are used to simulate a 1kW satellite system and understand practical trade-offs of this idea in actual satellite power systems.
Additionally, this work also presents the implementation of CMOS controller integrated circuit (IC) in 0.18um technology. The CMOS controller IC includes switched-capacitor converters in open loop to provide the floating voltages required to drive the GaN switches. Each CMOS controller IC can drive 10 switches in series and parallel combination. Furthermore, the designed controller IC is expected to operate under 300MRad of total dose radiation, thus enabling the controller modules to be placed on the solar cell wings of the satellites.
ContributorsHeblikar, Anand N (Author) / Kitchen, Jennifer (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Ozev, Sule (Committee member) / Arizona State University (Publisher)
Created2019
Description
The manufacturing process for electronic systems involves many players, from chip/board design and fabrication to firmware design and installation.
In today's global supply chain, any of these steps are prone to interference from rogue players, creating a security risk.
Manufactured devices need to be verified to perform only their intended operations since it is not economically feasible to control the supply chain and use only trusted facilities.
It is becoming increasingly necessary to trust but verify the received devices both at production and in the field.
Unauthorized hardware or firmware modifications, known as Trojans,
can steal information, drain the battery, or damage battery-driven embedded systems and lightweight Internet of Things (IoT) devices.
Since Trojans may be triggered in the field at an unknown instance,
it is essential to detect their presence at run-time.
However, it isn't easy to run sophisticated detection algorithms on these devices
due to limited computational power and energy, and in some cases, lack of accessibility.
Since finding a trusted sample is infeasible in general, the proposed technique is based on self-referencing to remove any effect of environmental or device-to-device variations in the frequency domain.
In particular, the self-referencing is achieved by exploiting the band-limited nature of Trojan activity using signal detection theory.
When the device enters the test mode, a predefined test application is run on the device
repetitively for a known period. The periodicity ensures that the spectral electromagnetic power of the test application concentrates at known frequencies, leaving the remaining frequencies within the operating bandwidth at the noise level. Any deviations from the noise level for these unoccupied frequency locations indicate the presence of unknown (unauthorized) activity. Hence, the malicious activity can differentiate without using a golden reference or any knowledge of the Trojan activity attributes.
The proposed technique's effectiveness is demonstrated through experiments with collecting and processing side-channel signals, such as involuntarily electromagnetic emissions and power consumption, of a wearable electronics prototype and commercial system-on-chip under a variety of practical scenarios.
In today's global supply chain, any of these steps are prone to interference from rogue players, creating a security risk.
Manufactured devices need to be verified to perform only their intended operations since it is not economically feasible to control the supply chain and use only trusted facilities.
It is becoming increasingly necessary to trust but verify the received devices both at production and in the field.
Unauthorized hardware or firmware modifications, known as Trojans,
can steal information, drain the battery, or damage battery-driven embedded systems and lightweight Internet of Things (IoT) devices.
Since Trojans may be triggered in the field at an unknown instance,
it is essential to detect their presence at run-time.
However, it isn't easy to run sophisticated detection algorithms on these devices
due to limited computational power and energy, and in some cases, lack of accessibility.
Since finding a trusted sample is infeasible in general, the proposed technique is based on self-referencing to remove any effect of environmental or device-to-device variations in the frequency domain.
In particular, the self-referencing is achieved by exploiting the band-limited nature of Trojan activity using signal detection theory.
When the device enters the test mode, a predefined test application is run on the device
repetitively for a known period. The periodicity ensures that the spectral electromagnetic power of the test application concentrates at known frequencies, leaving the remaining frequencies within the operating bandwidth at the noise level. Any deviations from the noise level for these unoccupied frequency locations indicate the presence of unknown (unauthorized) activity. Hence, the malicious activity can differentiate without using a golden reference or any knowledge of the Trojan activity attributes.
The proposed technique's effectiveness is demonstrated through experiments with collecting and processing side-channel signals, such as involuntarily electromagnetic emissions and power consumption, of a wearable electronics prototype and commercial system-on-chip under a variety of practical scenarios.
ContributorsKarabacak, Fatih (Author) / Ozev, Sule (Thesis advisor) / Ogras, Umit Y. (Thesis advisor) / Christen, Jennifer Blain (Committee member) / Kitchen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2020
Description
Point-of-Care diagnostics is one of the most popular fields of research in bio-medicine today because of its portability, speed of response, convenience and quality assurance. One of the most important steps in such a device is to prepare and purify the sample by extracting the nucleic acids, for which small spherical magnetic particles called magnetic beads are often used in laboratories. Even though magnetic beads have the ability to isolate DNA or RNA from bio-samples in their purified form, integrating these into a microfluidic point-of-need testing kit is still a bit of a challenge. In this thesis, the possibility of integrating paramagnetic beads instead of silica-coated dynabeads, has been evaluated with respect to a point-of-need SARS-CoV-2 virus testing kit. This project is a comparative study between five different sizes of carboxyl-coated paramagnetic beads with reference to silica-coated dynabeads, and how each of them behave in a microcapillary chip in presence of magnetic fields of different strengths. The diameters and velocities of the beads have been calculated using different types of microscopic imaging techniques. The washing and elution steps of an extraction process have been recreated using syringe pump, microcapillary channels and permanent magnets, based on which those parameters of the beads have been studied which are essential for extraction behaviour. The yield efficiency of the beads have also been analysed by using these to extract Salmon DNA. Overall, furthering this research will improve the sensitivity and specificity for any low-cost nucleic-acid based point-of-care testing device.
ContributorsBiswas, Shilpita (Author) / Christen, Jennifer B (Thesis advisor) / Ozev, Sule (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2021
Description
With the steady advancement of neural network research, new applications are continuously emerging. As a tool for test time reduction, neural networks provide a reliable method of identifying and applying correlations in datasets to speed data processing. By leveraging the power of a deep neural net, it is possible to record the motion of an accelerometer in response to an electrical stimulus and correlate the response with a trim code to reduce the total test time for such sensors. This reduction can be achieved by replacing traditional trimming methods such as physical shaking or mathematical models with a neural net that is able to process raw sensor data collected with the help of a microcontroller. With enough data, the neural net can process the raw responses in real time to predict the correct trim codes without requiring any additional information. Though not yet a complete replacement, the method shows promise given more extensive datasets and industry-level testing and has the potential to disrupt the current state of testing.
ContributorsDebeurre, Nicholas (Author) / Ozev, Sule (Thesis advisor) / Vrudhula, Sarma (Thesis advisor) / Kniffin, Margaret (Committee member) / Arizona State University (Publisher)
Created2019