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- Creators: Bakkaloglu, Bertan
- Member of: ASU Electronic Theses and Dissertations
ContributorsJavidahmadabadi, Mahdi (Author) / Kitchen, Jennifer (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Aberle, James T., 1961- (Committee member) / Arizona State University (Publisher)
Created2015
Description
Biosensors aiming at detection of target analytes, such as proteins, microbes, virus, and toxins, are widely needed for various applications including detection of chemical and biological warfare (CBW) agents, biomedicine, environmental monitoring, and drug screening. Surface Plasmon Resonance (SPR), as a surface-sensitive analytical tool, can very sensitively respond to minute changes of refractive index occurring adjacent to a metal film, offering detection limits up to a few ppt (pg/mL). Through SPR, the process of protein adsorption may be monitored in real-time, and transduced into an SPR angle shift. This unique technique bypasses the time-consuming, labor-intensive labeling processes, such as radioisotope and fluorescence labeling. More importantly, the method avoids the modification of the biomarker’s characteristics and behaviors by labeling that often occurs in traditional biosensors. While many transducers, including SPR, offer high sensitivity, selectivity is determined by the bio-receptors. In traditional biosensors, the selectivity is provided by bio-receptors possessing highly specific binding affinity to capture target analytes, yet their use in biosensors are often limited by their relatively-weak binding affinity with analyte, non-specific adsorption, need for optimization conditions, low reproducibility, and difficulties integrating onto the surface of transducers. In order to circumvent the use of bio-receptors, the competitive adsorption of proteins, termed the Vroman effect, is utilized in this work. The Vroman effect was first reported by Vroman and Adams in 1969. The competitive adsorption targeted here occurs among different proteins competing to adsorb to a surface, when more than one type of protein is present. When lower-affinity proteins are adsorbed on the surface first, they can be displaced by higher-affinity proteins arriving at the surface at a later point in time. Moreover, only low-affinity proteins can be displaced by high-affinity proteins, typically possessing higher molecular weight, yet the reverse sequence does not occur. The SPR biosensor based on competitive adsorption is successfully demonstrated to detect fibrinogen and thyroglobulin (Tg) in undiluted human serum and copper ions in drinking water through the denatured albumin.
ContributorsWang, Ran (Author) / Chae, Junseok (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Tsow, Tsing (Committee member) / Goryll, Michael (Committee member) / Arizona State University (Publisher)
Created2015
Description
Modern Complex electronic system include multiple power domains and drastically varying power consumption patterns, requiring the use of multiple power conversion and regulation units. High frequency switching converters have been gaining prominence in the DC-DC converter market due to their high efficiency. Unfortunately, they are all subject to higher process variations jeopardizing stable operation of the power supply.
This research mainly focus on the technique to track changes in the dynamic loop characteristics of the DC-DC converters without disturbing the normal mode of operation using a white noise based excitation and correlation. White noise excitation is generated via pseudo random disturbance at reference and PWM input of the converter with the test signal being spread over a wide bandwidth, below the converter noise and ripple floor. Test signal analysis is achieved by correlating the pseudo-random input sequence with the output response and thereby accumulating the desired behavior over time and pulling it above the noise floor of the measurement set-up. An off-the shelf power converter, LM27402 is used as the DUT for the experimental verification. Experimental results show that the proposed technique can estimate converter's natural frequency and Q-factor within ±2.5% and ±0.7% error margin respectively, over changes in load inductance and capacitance.
This research mainly focus on the technique to track changes in the dynamic loop characteristics of the DC-DC converters without disturbing the normal mode of operation using a white noise based excitation and correlation. White noise excitation is generated via pseudo random disturbance at reference and PWM input of the converter with the test signal being spread over a wide bandwidth, below the converter noise and ripple floor. Test signal analysis is achieved by correlating the pseudo-random input sequence with the output response and thereby accumulating the desired behavior over time and pulling it above the noise floor of the measurement set-up. An off-the shelf power converter, LM27402 is used as the DUT for the experimental verification. Experimental results show that the proposed technique can estimate converter's natural frequency and Q-factor within ±2.5% and ±0.7% error margin respectively, over changes in load inductance and capacitance.
ContributorsBakliwal, Priyanka (Author) / Ozev, Sule (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Kitchen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2015
Description
A single solar cell provides close to 0.5 V output at its maximum power point, which is very
low for any electronic circuit to operate. To get rid of this problem, traditionally multiple
solar cells are connected in series to get higher voltage. The disadvantage of this approach
is the efficiency loss for partial shading or mismatch. Even as low as 6-7% of shading can
result in more than 90% power loss. Therefore, Maximum Power Point Tracking (MPPT)
at single solar cell level is the most efficient way to extract power from solar cell.
Power Management IC (MPIC) used to extract power from single solar cell, needs to
start at 0.3 V input. MPPT circuitry should be implemented with minimal power and area
overhead. To start the PMIC at 0.3 V, a switch capacitor charge pump is utilized as an
auxiliary start up circuit for generating a regulated 1.8 V auxiliary supply from 0.3 V input.
The auxiliary supply powers up a MPPT converter followed by a regulated converter. At
the start up both the converters operate at 100 kHz clock with 80% duty cycle and system
output voltage starts rising. When the system output crosses 2.7 V, the auxiliary start up
circuit is turned off and the supply voltage for both the converters is derived from the system
output itself. In steady-state condition the system output is regulated to 3.0 V.
A fully integrated analog MPPT technique is proposed to extract maximum power from
the solar cell. This technique does not require Analog to Digital Converter (ADC) and
Digital Signal Processor (DSP), thus reduces area and power overhead. The proposed
MPPT techniques includes a switch capacitor based power sensor which senses current of
boost converter without using any sense resistor. A complete system is designed which
starts from 0.3 V solar cell voltage and provides regulated 3.0 V system output.
low for any electronic circuit to operate. To get rid of this problem, traditionally multiple
solar cells are connected in series to get higher voltage. The disadvantage of this approach
is the efficiency loss for partial shading or mismatch. Even as low as 6-7% of shading can
result in more than 90% power loss. Therefore, Maximum Power Point Tracking (MPPT)
at single solar cell level is the most efficient way to extract power from solar cell.
Power Management IC (MPIC) used to extract power from single solar cell, needs to
start at 0.3 V input. MPPT circuitry should be implemented with minimal power and area
overhead. To start the PMIC at 0.3 V, a switch capacitor charge pump is utilized as an
auxiliary start up circuit for generating a regulated 1.8 V auxiliary supply from 0.3 V input.
The auxiliary supply powers up a MPPT converter followed by a regulated converter. At
the start up both the converters operate at 100 kHz clock with 80% duty cycle and system
output voltage starts rising. When the system output crosses 2.7 V, the auxiliary start up
circuit is turned off and the supply voltage for both the converters is derived from the system
output itself. In steady-state condition the system output is regulated to 3.0 V.
A fully integrated analog MPPT technique is proposed to extract maximum power from
the solar cell. This technique does not require Analog to Digital Converter (ADC) and
Digital Signal Processor (DSP), thus reduces area and power overhead. The proposed
MPPT techniques includes a switch capacitor based power sensor which senses current of
boost converter without using any sense resistor. A complete system is designed which
starts from 0.3 V solar cell voltage and provides regulated 3.0 V system output.
ContributorsSingh, Shrikant (Author) / Kiaei, Sayfe (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Kitchen, Jennifer (Committee member) / Arizona State University (Publisher)
Created2015
Description
In this thesis, a digital input class D audio amplifier system which has the ability
to reject the power supply noise and nonlinearly of the output stage is presented. The main digital class D feed-forward path is using the fully-digital sigma-delta PWM open loop topology. Feedback loop is used to suppress the power supply noise and harmonic distortions. The design is using global foundry 0.18um technology.
Based on simulation, the power supply rejection at 200Hz is about -49dB with
81dB dynamic range and -70dB THD+N. The full scale output power can reach as high as 27mW and still keep minimum -68dB THD+N. The system efficiency at full scale is about 82%.
to reject the power supply noise and nonlinearly of the output stage is presented. The main digital class D feed-forward path is using the fully-digital sigma-delta PWM open loop topology. Feedback loop is used to suppress the power supply noise and harmonic distortions. The design is using global foundry 0.18um technology.
Based on simulation, the power supply rejection at 200Hz is about -49dB with
81dB dynamic range and -70dB THD+N. The full scale output power can reach as high as 27mW and still keep minimum -68dB THD+N. The system efficiency at full scale is about 82%.
ContributorsBai, Jing (Author) / Bakkaloglu, Bertan (Thesis advisor) / Arizona State University (Publisher)
Created2015
Description
Power Management circuits are employed in almost all electronic equipment and they have energy storage elements (capacitors and inductors) as building blocks along with other active circuitry. Power management circuits employ feedback to achieve good load and line regulation. The feedback loop is designed at an operating point and component values are chosen to meet that design requirements. But the capacitors and inductors are subject to variations due to temperature, aging and load stress. Due to these variations, the feedback loop can cross its robustness margins and can lead to degraded performance and potential instability. Another issue in power management circuits is the measurement of their frequency response for stability assessment. The standard techniques used in production test environment require expensive measurement equipment (Network Analyzer) and time. These two issues of component variations and frequency response measurement can be addressed if the frequency response of the power converter is used as measure of component (capacitor and inductor) variations. So, a single solution of frequency response measurement solves both the issues. This work examines system identification (frequency response measurement) of power management circuits based on cross correlation technique and proposes the use of switched capacitor correlator for this purpose. A switched capacitor correlator has been designed and used in the system identification of Linear and Switching regulators. The obtained results are compared with the standard frequency response measurement methods of power converters.
ContributorsMalladi, Venkata Naga Koushik (Author) / Bakkaloglu, Bertan (Thesis advisor) / Kitchen, Jennifer (Committee member) / Ogras, Umit Y. (Committee member) / Arizona State University (Publisher)
Created2015
Description
The photovoltaic systems used to convert solar energy to electricity pose a multitude of design and implementation challenges, including energy conversion efficiency, partial shading effects, and power converter efficiency. Using power converters for Distributed Maximum Power Point Tracking (DMPPT) is a well-known architecture to significantly reduce power loss associated with mismatched panels. Sub-panel-level DMPPT is shown to have up to 14.5% more annual energy yield than panel-level DMPPT, and requires an efficient medium power converter.
This research aims at implementing a highly efficient power management system at sub-panel level with focus on system cost and form-factor. Smaller form-factor motivates increased converter switching frequencies to significantly reduce the size of converter passives and substantially improve transient performance. But, currently available power MOSFETs put a constraint on the highest possible switching frequency due to increased switching losses. The solution is Gallium Nitride based power devices, which deliver figure of merit (FOM) performance at least an order of magnitude higher than existing silicon MOSFETs. Low power loss, high power density, low cost and small die sizes are few of the qualities that make e-GaN superior to its Si counterpart. With careful design, e-GaN can enable a 20-30% improvement in power stage efficiency compared to converters using Si MOSFETs.
The main objective of this research is to develop a highly integrated, high efficiency, 20MHz, hybrid GaN-CMOS DC-DC MPPT converter for a 12V/5A sub-panel. Hard and soft switching boost converter topologies are investigated within this research, and an innovative CMOS gate drive technique for efficiently driving an e-GaN power stage is presented in this work. The converter controller also employs a fast converging analog MPPT control technique.
This research aims at implementing a highly efficient power management system at sub-panel level with focus on system cost and form-factor. Smaller form-factor motivates increased converter switching frequencies to significantly reduce the size of converter passives and substantially improve transient performance. But, currently available power MOSFETs put a constraint on the highest possible switching frequency due to increased switching losses. The solution is Gallium Nitride based power devices, which deliver figure of merit (FOM) performance at least an order of magnitude higher than existing silicon MOSFETs. Low power loss, high power density, low cost and small die sizes are few of the qualities that make e-GaN superior to its Si counterpart. With careful design, e-GaN can enable a 20-30% improvement in power stage efficiency compared to converters using Si MOSFETs.
The main objective of this research is to develop a highly integrated, high efficiency, 20MHz, hybrid GaN-CMOS DC-DC MPPT converter for a 12V/5A sub-panel. Hard and soft switching boost converter topologies are investigated within this research, and an innovative CMOS gate drive technique for efficiently driving an e-GaN power stage is presented in this work. The converter controller also employs a fast converging analog MPPT control technique.
ContributorsKrishnan Achary, Kiran Kumar (Author) / Kitchen, Jennifer (Thesis advisor) / Kiaei, Sayfe (Committee member) / Bakkaloglu, Bertan (Committee member) / Arizona State University (Publisher)
Created2015
Description
This work implements three switched mode power amplifier topologies namely inverse class-D (CMCD), push-pull class-E and inverse push-pull class-E, in a GaN-on-Si process for medium power level (5-10W) femto/pico-cells base-station applications. The presented power amplifiers address practical implementation design constraints and explore the fundamental performance limitations of switched-mode power amplifiers for cellular band. The designs are analyzed and compared with respect to non-idealities like finite on-resistance, finite-Q of inductors, bond-wire effects, input signal duty cycle, and supply and component variations. These architectures are designed for non-constant envelope inputs in the form of digitally modulated signals such as RFPWM, which undergo duty cycle variation. After comparing the three topologies, this work concludes that the inverse push-pull class-E power amplifier shows lower efficiency degradation at reduced duty cycles. For GaN based discrete power amplifiers which have less drain capacitance compared to GaAs or CMOS and where the switch loss is dominated by wire-bonds, an inverse push-pull class-E gives highest output power at highest efficiency. Push-pull class-E can give efficiencies comparable to inverse push-pull class-E in presence of bondwires on tuning the Zero-Voltage Switching (ZVS) network components but at a lower output power. Current-Mode Class-D (CMCD) is affected most by the presence of bondwires and gives least output power and efficiency compared to other two topologies. For systems dominated by drain capacitance loss or which has no bondwires, the CMCD and push-pull class-E gives better output power than inverse push-pull class-E. However, CMCD is more suitable for high breakdown voltage process.
ContributorsShukla, Shishir Ramasare (Author) / Kitchen, Jennifer N (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Trichopoulos, Georgios (Committee member) / Arizona State University (Publisher)
Created2015
Description
Internet of Things (IoT) has become a popular topic in industry over the recent years, which describes an ecosystem of internet-connected devices or things that enrich the everyday life by improving our productivity and efficiency. The primary components of the IoT ecosystem are hardware, software and services. While the software and services of IoT system focus on data collection and processing to make decisions, the underlying hardware is responsible for sensing the information, preprocess and transmit it to the servers. Since the IoT ecosystem is still in infancy, there is a great need for rapid prototyping platforms that would help accelerate the hardware design process. However, depending on the target IoT application, different sensors are required to sense the signals such as heart-rate, temperature, pressure, acceleration, etc., and there is a great need for reconfigurable platforms that can prototype different sensor interfacing circuits.
This thesis primarily focuses on two important hardware aspects of an IoT system: (a) an FPAA based reconfigurable sensing front-end system and (b) an FPGA based reconfigurable processing system. To enable reconfiguration capability for any sensor type, Programmable ANalog Device Array (PANDA), a transistor-level analog reconfigurable platform is proposed. CAD tools required for implementation of front-end circuits on the platform are also developed. To demonstrate the capability of the platform on silicon, a small-scale array of 24×25 PANDA cells is fabricated in 65nm technology. Several analog circuit building blocks including amplifiers, bias circuits and filters are prototyped on the platform, which demonstrates the effectiveness of the platform for rapid prototyping IoT sensor interfaces.
IoT systems typically use machine learning algorithms that run on the servers to process the data in order to make decisions. Recently, embedded processors are being used to preprocess the data at the energy-constrained sensor node or at IoT gateway, which saves considerable energy for transmission and bandwidth. Using conventional CPU based systems for implementing the machine learning algorithms is not energy-efficient. Hence an FPGA based hardware accelerator is proposed and an optimization methodology is developed to maximize throughput of any convolutional neural network (CNN) based machine learning algorithm on a resource-constrained FPGA.
This thesis primarily focuses on two important hardware aspects of an IoT system: (a) an FPAA based reconfigurable sensing front-end system and (b) an FPGA based reconfigurable processing system. To enable reconfiguration capability for any sensor type, Programmable ANalog Device Array (PANDA), a transistor-level analog reconfigurable platform is proposed. CAD tools required for implementation of front-end circuits on the platform are also developed. To demonstrate the capability of the platform on silicon, a small-scale array of 24×25 PANDA cells is fabricated in 65nm technology. Several analog circuit building blocks including amplifiers, bias circuits and filters are prototyped on the platform, which demonstrates the effectiveness of the platform for rapid prototyping IoT sensor interfaces.
IoT systems typically use machine learning algorithms that run on the servers to process the data in order to make decisions. Recently, embedded processors are being used to preprocess the data at the energy-constrained sensor node or at IoT gateway, which saves considerable energy for transmission and bandwidth. Using conventional CPU based systems for implementing the machine learning algorithms is not energy-efficient. Hence an FPGA based hardware accelerator is proposed and an optimization methodology is developed to maximize throughput of any convolutional neural network (CNN) based machine learning algorithm on a resource-constrained FPGA.
ContributorsSuda, Naveen (Author) / Cao, Yu (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Ozev, Sule (Committee member) / Yu, Shimeng (Committee member) / Seo, Jae-Sun (Committee member) / Arizona State University (Publisher)
Created2016
Description
The modern era of consumer electronics is dominated by compact, portable, affordable smartphones and wearable computing devices. Power management integrated circuits (PMICs) play a crucial role in on-chip power management, extending battery life and efficiency of integrated analog, radio-frequency (RF), and mixed-signal cores. Low-dropout (LDO) regulators are commonly used to provide clean supply for low voltage integrated circuits, where point-of-load regulation is important. In System-On-Chip (SoC) applications, digital circuits can change their mode of operation regularly at a very high speed, imposing various load transient conditions for the regulator. These quick changes of load create a glitch in LDO output voltage, which hamper performance of the digital circuits unfavorably. For an LDO designer, minimizing output voltage variation and speeding up voltage glitch settling is an important task.
The presented research introduces two fully integrated LDO voltage regulators for SoC applications. N-type Metal-Oxide-Semiconductor (NMOS) power transistor based operation achieves high bandwidth owing to the source follower configuration of the regulation loop. A low input impedance and high output impedance error amplifier ensures wide regulation loop bandwidth and high gain. Current-reused dynamic biasing technique has been employed to increase slew-rate at the gate of power transistor during full-load variations, by a factor of two. Three design variations for a 1-1.8 V, 50 mA NMOS LDO voltage regulator have been implemented in a 180 nm Mixed-mode/RF process. The whole LDO core consumes 0.130 mA of nominal quiescent ground current at 50 mA load and occupies 0.21 mm x mm. LDO has a dropout voltage of 200 mV and is able to recover in 30 ns from a 65 mV of undershoot for 0-50 pF of on-chip load capacitance.
The presented research introduces two fully integrated LDO voltage regulators for SoC applications. N-type Metal-Oxide-Semiconductor (NMOS) power transistor based operation achieves high bandwidth owing to the source follower configuration of the regulation loop. A low input impedance and high output impedance error amplifier ensures wide regulation loop bandwidth and high gain. Current-reused dynamic biasing technique has been employed to increase slew-rate at the gate of power transistor during full-load variations, by a factor of two. Three design variations for a 1-1.8 V, 50 mA NMOS LDO voltage regulator have been implemented in a 180 nm Mixed-mode/RF process. The whole LDO core consumes 0.130 mA of nominal quiescent ground current at 50 mA load and occupies 0.21 mm x mm. LDO has a dropout voltage of 200 mV and is able to recover in 30 ns from a 65 mV of undershoot for 0-50 pF of on-chip load capacitance.
ContributorsDesai, Chirag (Author) / Kiaei, Sayfe (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Seo, Jae-Sun (Committee member) / Arizona State University (Publisher)
Created2016