ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.
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Description
The high uncertainty of renewables introduces more dynamics to power systems. The conventional way of monitoring and controlling power systems is no longer reliable. New strategies are needed to ensure the stability and reliability of power systems. This work aims to assess the use of machine learning methods in analyzing data from renewable integrated power systems to aid the decisionmaking of electricity market participants. Specifically, the work studies the cases of electricity price forecast, solar panel detection, and how to constrain the machine learning methods to obey domain knowledge.Chapter 2 proposes to diversify the data source to ensure a more accurate electricity price forecast. Specifically, the proposed two-stage method, namely the rerouted method, learns two types of mapping rules: the mapping between the historical wind power and the historical price and the forecasting rule for wind generation. Based on the two rules, we forecast the price via the forecasted generation and the learned mapping between power and price. The massive numerical comparison gives guidance for choosing proper machine learning methods and proves the effectiveness of the proposed method.
Chapter 3 proposes to integrate advanced data compression techniques into machine learning algorithms to either improve the predicting accuracy or accelerate the computation speed. New semi-supervised learning and one-class classification methods are proposed based on autoencoders to compress the data while refining the nonlinear data representation of human behavior and solar behavior. The numerical results show robust detection accuracy, laying down the foundation for managing distributed energy resources in distribution grids. Guidance is also provided to determine the proper machine learning methods for the solar detection problem.
Chapter 4 proposes to integrate different types of domain knowledge-based constraints into basic neural networks to guide the model selection and enhance interpretability. A hybrid model is proposed to penalize derivatives and alter the structure to improve the performance of a neural network. We verify the performance improvement of introducing prior knowledge-based constraints on both synthetic and real data sets.
ContributorsLuo, Shuman (Author) / Weng, Yang (Thesis advisor) / Lei, Qin (Committee member) / Fricks, John (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2022
Description
Distributed energy resources have experienced dramatic growth and are beginning to support a significant amount of customer loads. Power electronic converters are the primary interface between the grid and the distributed energy resources/storage and offer several advantages including fast control, flexibility and high efficiency. The efficiency and the power density by volume are important performance metrics of a power converter. Compact and high efficiency power converter is beneficial to the cost-effectiveness of the converter interfaced generations. In this thesis, a soft-switching technique is proposed to reduce the size of passive components in a grid-connected converter while maintaining a high power conversion efficiency. The dynamic impact of the grid-connected converters on the power system is causing concerns as the penetration level of the converter interfaced generation increases, necessitating a detailed dynamic analysis. The unbalanced nature of distribution systems makes the conventional transient stability simulation based on positive sequence components unsuitable for this purpose. Methods suitable for the dynamic simulation of grid-connected converters in large scale unbalanced and single-phase systems are presented in this thesis to provide an effective way to study the dynamic interactions between the grid and the converters. Dynamic-link library (DLL) of converter dynamic models are developed by which converter dynamic simulations can be easily conducted in OpenDSS. To extend the converter controls testing beyond pure simulation, real-time simulation can be utilized where partial realistic scenarios can be created by including realistic components in the simulation loop. In this work, a multi-platform, real-time simulation testbed including actual digital controller platforms, communication networks and inverters has been developed for validating the microgrid concepts and implementations. A hierarchical converted based microgrid control scheme is proposed which enables the islanded microgrid operation with 100% penetration level of converter interfaced generation. Impact of the load side dynamic modeling on the converter response is also discussed in this thesis.
ContributorsYu, Ziwei (Author) / Ayyanar, Raja (Thesis advisor) / Vittal, Vijay (Committee member) / Qin, Jiangchao (Committee member) / Weng, Yang (Committee member) / Arizona State University (Publisher)
Created2018
Description
The students of Arizona State University, under the mentorship of Dr George Karady, have been collaborating with Salt River Project (SRP), a major power utility in the state of Arizona, trying to study and optimize a battery-supported grid-tied rooftop Photovoltaic (PV) system, sold by a commercial vendor. SRP believes this system has the potential to satisfy the needs of its customers, who opt for utilizing solar power to partially satisfy their power needs.
An important part of this elaborate project is the development of a new load forecasting algorithm and a better control strategy for the optimized utilization of the storage system. The built-in algorithm of this commercial unit uses simple forecasting and battery control strategies. With the recent improvement in Machine Learning (ML) techniques, development of a more sophisticated model of the problem in hand was possible. This research is aimed at achieving the goal by utilizing the appropriate ML techniques to better model the problem, which will essentially result in a better solution. In this research, a set of six unique features are used to model the load forecasting problem and different ML algorithms are simulated on the developed model. A similar approach is taken to solve the PV prediction problem. Finally, a very effective battery control strategy is built (utilizing the results of the load and PV forecasting), with the aim of ensuring a reduction in the amount of energy consumed from the grid during the “on-peak” hours. Apart from the reduction in the energy consumption, this battery control algorithm decelerates the “cycling aging” or the aging of the battery owing to the charge/dis-charges cycles endured by selectively charging/dis-charging the battery based on need.
ii
The results of this proposed strategy are verified using a hardware implementation (the PV system was coupled with a custom-built load bank and this setup was used to simulate a house). The results pertaining to the performances of the built-in algorithm and the ML algorithm are compared and the economic analysis is performed. The findings of this research have in the process of being published in a reputed journal.
An important part of this elaborate project is the development of a new load forecasting algorithm and a better control strategy for the optimized utilization of the storage system. The built-in algorithm of this commercial unit uses simple forecasting and battery control strategies. With the recent improvement in Machine Learning (ML) techniques, development of a more sophisticated model of the problem in hand was possible. This research is aimed at achieving the goal by utilizing the appropriate ML techniques to better model the problem, which will essentially result in a better solution. In this research, a set of six unique features are used to model the load forecasting problem and different ML algorithms are simulated on the developed model. A similar approach is taken to solve the PV prediction problem. Finally, a very effective battery control strategy is built (utilizing the results of the load and PV forecasting), with the aim of ensuring a reduction in the amount of energy consumed from the grid during the “on-peak” hours. Apart from the reduction in the energy consumption, this battery control algorithm decelerates the “cycling aging” or the aging of the battery owing to the charge/dis-charges cycles endured by selectively charging/dis-charging the battery based on need.
ii
The results of this proposed strategy are verified using a hardware implementation (the PV system was coupled with a custom-built load bank and this setup was used to simulate a house). The results pertaining to the performances of the built-in algorithm and the ML algorithm are compared and the economic analysis is performed. The findings of this research have in the process of being published in a reputed journal.
ContributorsHariharan, Aashiek (Author) / Karady, George G. (Thesis advisor) / Heydt, Gerald Thomas (Committee member) / Qin, Jiangchao (Committee member) / Allee, David R. (Committee member) / Arizona State University (Publisher)
Created2018
Description
The most important metrics considered for electric vehicles are power density, efficiency, and reliability of the powertrain modules. The powertrain comprises of an Electric Machine (EM), power electronic converters, an Energy Management System (EMS), and an Energy Storage System (ESS). The power electronic converters are used to couple the motor with the battery stack. Including a DC/DC converter in the powertrain module is favored as it adds an additional degree of freedom to achieve flexibility in optimizing the battery module and inverter independently. However, it is essential that the converter is rated for high peak power and can maintain high efficiency while operating over a wide range of load conditions to not compromise on system efficiency. Additionally, the converter must strictly adhere to all automotive standards.
Currently, several hard-switching topologies have been employed such as conventional boost DC/DC, interleaved step-up DC/DC, and full-bridge DC/DC converter. These converters face respective limitations in achieving high step-up conversion ratio, size and weight issues, or high component count. In this work, a bi-directional synchronous boost DC/DC converter with easy interleaving capability is proposed with a novel ZVT mechanism. This converter steps up the EV battery voltage of 200V-300V to a wide range of variable output voltages ranging from 310V-800V. High power density and efficiency are achieved through high switching frequency of 250kHz for each phase with effective frequency doubling through interleaving. Also, use of wide bandgap high voltage SiC switches allows high efficiency operation even at high temperatures.
Comprehensive analysis, design details and extensive simulation results are presented. Incorporating ZVT branch with adaptive time delay results in converter efficiency close to 98%. Experimental results from a 2.5kW hardware prototype validate the performance of the proposed approach. A peak efficiency of 98.17% has been observed in hardware in the boost or motoring mode.
Currently, several hard-switching topologies have been employed such as conventional boost DC/DC, interleaved step-up DC/DC, and full-bridge DC/DC converter. These converters face respective limitations in achieving high step-up conversion ratio, size and weight issues, or high component count. In this work, a bi-directional synchronous boost DC/DC converter with easy interleaving capability is proposed with a novel ZVT mechanism. This converter steps up the EV battery voltage of 200V-300V to a wide range of variable output voltages ranging from 310V-800V. High power density and efficiency are achieved through high switching frequency of 250kHz for each phase with effective frequency doubling through interleaving. Also, use of wide bandgap high voltage SiC switches allows high efficiency operation even at high temperatures.
Comprehensive analysis, design details and extensive simulation results are presented. Incorporating ZVT branch with adaptive time delay results in converter efficiency close to 98%. Experimental results from a 2.5kW hardware prototype validate the performance of the proposed approach. A peak efficiency of 98.17% has been observed in hardware in the boost or motoring mode.
ContributorsMullangi Chenchu, Hemanth (Author) / Ayyanar, Raja (Thesis advisor) / Qin, Jiangchao (Committee member) / Lei, Qin (Committee member) / Arizona State University (Publisher)
Created2018
Description
The following report details the motivation, design, analysis, simulation and hardware implementation of a DC/DC converter in EV drivetrain architectures. The primary objective of the project was to improve overall system efficiency in an EV drivetrain. The methodology employed to this end required a variable or flexible DC-Link voltage at the input of the inverter stage. Amongst the several advantages associated with such a system are the independent optimization of the battery stack and the inverter over a wide range of motor operating conditions. The incorporation of a DC/DC converter into the drivetrain helps lower system losses but since it is an additional component, a number of considerations need to be made during its design. These include stringent requirements on power density, converter efficiency and reliability.
These targets for the converter are met through a number of different ways. The switches used are Silicon Carbide FETs. These are wide band gap (WBG) devices that can operate at high frequencies and temperatures. Since they allow for high frequency operation, a switching frequency of 250 khz is proposed and implemented. This helps with power density by reducing the size of passive components. High efficiencies are made possible by using a simple soft switching technique by augmenting the DC/DC converter with an auxiliary branch to enable zero voltage transition.
The efficacy of the approach is tested through simulation and hardware implementation of two different prototypes. The Gen-I prototype was a single soft switched synchronous boost converter rated at 2.5kw. Both the motoring mode and regenerative modes of operation (Boost and Buck) were hardware tested for over 2kw and efficiency results of over 98.15% were achieved. The Gen-II prototype and the main focus of this work is an interleaved soft switched synchronous boost converter. This converter has been implemented in hardware as well and has been tested at 6.7kw and an efficiency of over 98% has been achieved in the boost mode of operation.
These targets for the converter are met through a number of different ways. The switches used are Silicon Carbide FETs. These are wide band gap (WBG) devices that can operate at high frequencies and temperatures. Since they allow for high frequency operation, a switching frequency of 250 khz is proposed and implemented. This helps with power density by reducing the size of passive components. High efficiencies are made possible by using a simple soft switching technique by augmenting the DC/DC converter with an auxiliary branch to enable zero voltage transition.
The efficacy of the approach is tested through simulation and hardware implementation of two different prototypes. The Gen-I prototype was a single soft switched synchronous boost converter rated at 2.5kw. Both the motoring mode and regenerative modes of operation (Boost and Buck) were hardware tested for over 2kw and efficiency results of over 98.15% were achieved. The Gen-II prototype and the main focus of this work is an interleaved soft switched synchronous boost converter. This converter has been implemented in hardware as well and has been tested at 6.7kw and an efficiency of over 98% has been achieved in the boost mode of operation.
ContributorsRaza, Bassam (Author) / Ayyanar, Raja (Thesis advisor) / Qin, Jiangchao (Committee member) / Lei, Qin (Committee member) / Arizona State University (Publisher)
Created2019
Description
This dissertation presents innovative techniques to develop performance-based models and complete transient models of induction motor drive systems with vector controls in electro-magnetic transient (EMT) and positive sequence transient stability (PSTS) simulation programs. The performance-based model is implemented by obtaining the characteristic transfer functions of perturbed active and reactive power consumptions with respect to frequency and voltage perturbations. This level of linearized performance-based model is suitable for the investigation of the damping of small-magnitude low-frequency oscillations. The complete transient model is proposed by decomposing the motor, converter and control models into d-q axes components and developing a compatible electrical interface to the positive-sequence network in the PSTS simulators. The complete transient drive model is primarily used to examine the system response subject to transient voltage depression considering increasing penetration of converter-driven motor loads.
For developing the performance-based model, modulations are performed on the supply side of the full drive system to procure magnitude and phase responses of active and reactive powers with respect to the supply voltage and frequency for a range of discrete frequency points. The prediction error minimization (PEM) technique is utilized to generate the curve-fitted transfer functions and corresponding bode plots. For developing the complete drive model in the PSTS simulation program, a positive-sequence voltage source is defined properly as the interface of the model to the external system. The dc-link of the drive converter is implemented by employing the average model of the PWM converter, and is utilized to integrate the line-side rectifier and machine-side inverter.
Numerical simulation is then conducted on sample test systems, synthesized with suitable characteristics to examine performance of the developed models. The simulation results reveal that with growing amount of drive loads being distributed in the system, the small-signal stability of the system is improved in terms of the desirable damping effects on the low-frequency system oscillations of voltage and frequency. The transient stability of the system is also enhanced with regard to the stable active power and reactive power controls of the loads, and the appropriate VAr support capability provided by the drive loads during a contingency.
For developing the performance-based model, modulations are performed on the supply side of the full drive system to procure magnitude and phase responses of active and reactive powers with respect to the supply voltage and frequency for a range of discrete frequency points. The prediction error minimization (PEM) technique is utilized to generate the curve-fitted transfer functions and corresponding bode plots. For developing the complete drive model in the PSTS simulation program, a positive-sequence voltage source is defined properly as the interface of the model to the external system. The dc-link of the drive converter is implemented by employing the average model of the PWM converter, and is utilized to integrate the line-side rectifier and machine-side inverter.
Numerical simulation is then conducted on sample test systems, synthesized with suitable characteristics to examine performance of the developed models. The simulation results reveal that with growing amount of drive loads being distributed in the system, the small-signal stability of the system is improved in terms of the desirable damping effects on the low-frequency system oscillations of voltage and frequency. The transient stability of the system is also enhanced with regard to the stable active power and reactive power controls of the loads, and the appropriate VAr support capability provided by the drive loads during a contingency.
ContributorsLiu, Yuan (Author) / Vittal, Vijay (Thesis advisor) / Undrill, John (Committee member) / Ayyanar, Raja (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2016
Description
The past decades have seen a significant shift in the expectations and requirements re-lated to power system analysis tools. Investigations into major power grid disturbances have suggested the need for more comprehensive assessment methods. Accordingly, sig-nificant research in recent years has focused on the development of better power system models and efficient techniques for analyzing power system operability. The work done in this report focusses on two such topics
1. Analysis of load model parameter uncertainty and sensitivity based pa-rameter estimation for power system studies
2. A systematic approach to n-1-1 analysis for power system security as-sessment
To assess the effect of load model parameter uncertainty, a trajectory sensitivity based approach is proposed in this work. Trajectory sensitivity analysis provides a sys-tematic approach to study the impact of parameter uncertainty on power system re-sponse to disturbances. Furthermore, the non-smooth nature of the composite load model presents some additional challenges to sensitivity analysis in a realistic power system. Accordingly, the impact of the non-smooth nature of load models on the sensitivity analysis is addressed in this work. The study was performed using the Western Electrici-ty Coordinating Council (WECC) system model. To address the issue of load model pa-rameter estimation, a sensitivity based load model parameter estimation technique is presented in this work. A detailed discussion on utilizing sensitivities to improve the ac-curacy and efficiency of the parameter estimation process is also presented in this work.
Cascading outages can have a catastrophic impact on power systems. As such, the NERC transmission planning (TPL) standards requires utilities to plan for n¬-1-1 out-ages. However, such analyses can be computationally burdensome for any realistic pow-er system owing to the staggering number of possible n-1-1 contingencies. To address this problem, the report proposes a systematic approach to analyze n-1-1 contingencies in a computationally tractable manner for power system security assessment. The pro-posed approach addresses both static and dynamic security assessment. The proposed methods have been tested on the WECC system.
1. Analysis of load model parameter uncertainty and sensitivity based pa-rameter estimation for power system studies
2. A systematic approach to n-1-1 analysis for power system security as-sessment
To assess the effect of load model parameter uncertainty, a trajectory sensitivity based approach is proposed in this work. Trajectory sensitivity analysis provides a sys-tematic approach to study the impact of parameter uncertainty on power system re-sponse to disturbances. Furthermore, the non-smooth nature of the composite load model presents some additional challenges to sensitivity analysis in a realistic power system. Accordingly, the impact of the non-smooth nature of load models on the sensitivity analysis is addressed in this work. The study was performed using the Western Electrici-ty Coordinating Council (WECC) system model. To address the issue of load model pa-rameter estimation, a sensitivity based load model parameter estimation technique is presented in this work. A detailed discussion on utilizing sensitivities to improve the ac-curacy and efficiency of the parameter estimation process is also presented in this work.
Cascading outages can have a catastrophic impact on power systems. As such, the NERC transmission planning (TPL) standards requires utilities to plan for n¬-1-1 out-ages. However, such analyses can be computationally burdensome for any realistic pow-er system owing to the staggering number of possible n-1-1 contingencies. To address this problem, the report proposes a systematic approach to analyze n-1-1 contingencies in a computationally tractable manner for power system security assessment. The pro-posed approach addresses both static and dynamic security assessment. The proposed methods have been tested on the WECC system.
ContributorsMitra, Parag (Author) / Vittal, Vijay (Thesis advisor) / Heydt, Gerald T (Committee member) / Ayyanar, Raja (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2016
Description
Due to the increasing trend of electricity price for the future and the price reduction of solar electronics price led by the policy stimulus and the technological improvement, the residential distribution solar photovoltaic (PV) system’s market is prosperous. Excess energy can be sold back to the grid, however peak demand of a residential customer typically occurs in late afternoon/early evening when PV systems are not a productive. The solar PV system can provide residential customers sufficient energy during the daytime, even the exceeding energy can be sold back to the grid especially during the day with good sunlight, however, the peak demand of a regular family always appears during late afternoon and early evening which are not productive time for PV system. In this case, the PV customers only need the grid energy when other customers also need it the most. Because of the lower contribution of PV systems during times of peak demand, utilities are beginning to adjust rate structures to better align the bills paid by PV customers with the cost to the utility to serve those customers. Different rate structures include higher fixed charges, higher on-peak electricity prices, on-peak demand charges, or prices based on avoided costs. The demand charge and the on-peak energy charge significantly reduced the savings brought by the PV system. This will result in a longer the customer’s payback period. Eventually PV customers are not saving a lot in their electricity bill compare to those customers who do not own a PV system.
A battery system is a promising technology that can improve monthly bill savings since a battery can store the solar energy and the off-peak grid energy and release it later during the on-peak hours. Sponsored by Salt River Project (SRP), a smart home model consists 1.35 kW PV panels, a 7.76 kWh lithium-ion battery and an adjustable resistive load bank was built on the roof of Engineering Research Center (ERC) building. For analysis, data was scaled up by 6/1.35 times to simulate a real residential PV setup. The testing data had been continuously recorded for more than one year (Aug.2014 - Oct.2015) and a battery charging strategy was developed based on those data. The work of this thesis deals with the idea of this charging strategy and the economic benefits this charging strategy can bring to the PV customers. Part of this research work has been wrote into a conference paper which is accepted by IEEE PES General Meeting 2016. A new and larger system has been installed on the roof with 6 kW PV modules and 6 kW output integrated electronics. This project will go on and the method come up by this thesis will be tested.
A battery system is a promising technology that can improve monthly bill savings since a battery can store the solar energy and the off-peak grid energy and release it later during the on-peak hours. Sponsored by Salt River Project (SRP), a smart home model consists 1.35 kW PV panels, a 7.76 kWh lithium-ion battery and an adjustable resistive load bank was built on the roof of Engineering Research Center (ERC) building. For analysis, data was scaled up by 6/1.35 times to simulate a real residential PV setup. The testing data had been continuously recorded for more than one year (Aug.2014 - Oct.2015) and a battery charging strategy was developed based on those data. The work of this thesis deals with the idea of this charging strategy and the economic benefits this charging strategy can bring to the PV customers. Part of this research work has been wrote into a conference paper which is accepted by IEEE PES General Meeting 2016. A new and larger system has been installed on the roof with 6 kW PV modules and 6 kW output integrated electronics. This project will go on and the method come up by this thesis will be tested.
ContributorsWang, Xin'an (Author) / Karady, George G. (Thesis advisor) / Smedley, Grant (Committee member) / Qin, Jiangchao (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2016
Description
Alternate sources of energy such as wind, solar photovoltaic and fuel cells are coupled to the power grid with the help of solid state converters. Continued deregulation of the power sector coupled with favorable government incentives has resulted in the rapid growth of renewable energy sources connected to the distribution system at a voltage level of 34.5kV or below. Of late, many utilities are also investing in these alternate sources of energy with the point of interconnection with the power grid being at the transmission level. These converter interfaced generation along with their associated control have the ability to provide the advantage of fast control of frequency, voltage, active, and reactive power. However, their ability to provide stability in a large system is yet to be investigated in detail. This is the primary objective of this research.
In the future, along with an increase in the percentage of converter interfaced renewable energy sources connected to the transmission network, there exists a possibility of even connecting synchronous machines to the grid through converters. Thus, all sources of energy can be expected to be coupled to the grid through converters. The control and operation of such a grid will be unlike anything that has been encountered till now. In this dissertation, the operation and behavior of such a grid will be investigated. The first step in such an analysis will be to build an accurate and simple mathematical model to represent the corresponding components in commercial software. Once this bridge has been crossed, conventional machines will be replaced with their solid state interfaced counterparts in a phased manner. At each stage, attention will be devoted to the control of these sources and also on the stability performance of the large power system.
This dissertation addresses various concerns regarding the control and operation of a futuristic power grid. In addition, this dissertation also aims to address the issue of whether a requirement may arise to redefine operational reliability criteria based on the results obtained.
In the future, along with an increase in the percentage of converter interfaced renewable energy sources connected to the transmission network, there exists a possibility of even connecting synchronous machines to the grid through converters. Thus, all sources of energy can be expected to be coupled to the grid through converters. The control and operation of such a grid will be unlike anything that has been encountered till now. In this dissertation, the operation and behavior of such a grid will be investigated. The first step in such an analysis will be to build an accurate and simple mathematical model to represent the corresponding components in commercial software. Once this bridge has been crossed, conventional machines will be replaced with their solid state interfaced counterparts in a phased manner. At each stage, attention will be devoted to the control of these sources and also on the stability performance of the large power system.
This dissertation addresses various concerns regarding the control and operation of a futuristic power grid. In addition, this dissertation also aims to address the issue of whether a requirement may arise to redefine operational reliability criteria based on the results obtained.
ContributorsRamasubramanian, Deepak (Author) / Vittal, Vijay (Thesis advisor) / Undrill, John (Committee member) / Ayyanar, Raja (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2017
Description
Presently, hard-switching buck/boost converters are dominantly used for automotive applications. Automotive applications have stringent system requirements for dc-dc converters, such as wide input voltage range and limited EMI noise emission. High switching frequency of the dc-dc converters is much desired in automotive applications for avoiding AM band interference and for compact size. However, hard switching buck converter is not suitable at high frequency operation because of its low efficiency. In addition, buck converter has high EMI noise due to its hard-switching. Therefore, soft-switching topologies are considered in this thesis work to improve the performance of the dc-dc converters.
Many soft-switching topologies are reviewed but none of them is well suited for the given automotive applications. Two soft-switching PWM converters are proposed in this work. For low power automotive POL applications, a new active-clamp buck converter is proposed. Comprehensive analysis of this converter is presented. A 2.2 MHz, 25 W active-clamp buck converter prototype with Si MOSFETs was designed and built. The experimental results verify the operation of the converter. For 12 V to 5 V conversion, the Si based prototype achieves a peak efficiency of 89.7%. To further improve the efficiency, GaN FETs are used and an optimized SR turn-off delay is employed. Then, a peak efficiency of 93.22% is achieved. The EMI test result shows significantly improved EMI performance of the proposed active-clamp buck converter. Last, large- and small-signal models of the proposed converter are derived and verified by simulation.
For automotive dual voltage system, a new bidirectional zero-voltage-transition (ZVT) converter with coupled-inductor is proposed in this work. With the coupled-inductor, the current to realize zero-voltage-switching (ZVS) of main switches is much reduced and the core loss is minimized. Detailed analysis and design considerations for the proposed converter are presented. A 1 MHz, 250 W prototype is designed and constructed. The experimental results verify the operation. Peak efficiencies of 93.98% and 92.99% are achieved in buck mode and boost mode, respectively. Significant efficiency improvement is achieved from the efficiency comparison between the hard-switching buck converter and the proposed ZVT converter with coupled-inductor.
Many soft-switching topologies are reviewed but none of them is well suited for the given automotive applications. Two soft-switching PWM converters are proposed in this work. For low power automotive POL applications, a new active-clamp buck converter is proposed. Comprehensive analysis of this converter is presented. A 2.2 MHz, 25 W active-clamp buck converter prototype with Si MOSFETs was designed and built. The experimental results verify the operation of the converter. For 12 V to 5 V conversion, the Si based prototype achieves a peak efficiency of 89.7%. To further improve the efficiency, GaN FETs are used and an optimized SR turn-off delay is employed. Then, a peak efficiency of 93.22% is achieved. The EMI test result shows significantly improved EMI performance of the proposed active-clamp buck converter. Last, large- and small-signal models of the proposed converter are derived and verified by simulation.
For automotive dual voltage system, a new bidirectional zero-voltage-transition (ZVT) converter with coupled-inductor is proposed in this work. With the coupled-inductor, the current to realize zero-voltage-switching (ZVS) of main switches is much reduced and the core loss is minimized. Detailed analysis and design considerations for the proposed converter are presented. A 1 MHz, 250 W prototype is designed and constructed. The experimental results verify the operation. Peak efficiencies of 93.98% and 92.99% are achieved in buck mode and boost mode, respectively. Significant efficiency improvement is achieved from the efficiency comparison between the hard-switching buck converter and the proposed ZVT converter with coupled-inductor.
ContributorsNan, Chenhao (Author) / Ayyanar, Raja (Thesis advisor) / Bakkaloglu, Bertan (Committee member) / Karady, George G. (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2016