Theses and Dissertations - Department of Electrical & Computer Engineering (ECE)
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Browsing Theses and Dissertations - Department of Electrical & Computer Engineering (ECE) by Author "Abu Qahouq, Jaber"
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Item Architectures and control for energy storage systems with wired and wireless power transfer(University of Alabama Libraries, 2019) Cao, Yuan; Abu Qahouq, Jaber; University of Alabama TuscaloosaIn the past two decades, the performance of battery energy storage systems (BESS) has been significantly improved with the utilization of advanced architectures and control methods and new electronic devices. However, the increasing demands imposed by BESS applications still necessitate the need for additional performance improvement and/or create new issues that need to be addressed. These can be summarized as follows: (1) The imbalance in the state-of-charge (SOC) between cells might occur, which might degrade the performance of the battery system. (2) In a BESS, with the increasingly advanced functions and control methods, the number of required components is increased. (3) In electrical vehicles (EVs) applications, the limited driving range and the needed charging time of the lithium-ion (Li-Ion) battery pack is one of the major reasons slowing down the adoption of EVs. (4) The transmission efficiency of wireless power transfer (WPT) systems is decreased as the distance and misalignment between transmitter (Tx) and receiver (Rx) increase. (5) In order to realize the wireless power transfer in BESS, additional components such as DC-AC inverter Tx coil, Rx coil and AC-DC rectifier are required, which increase the cost and size of the system. This dissertation work focuses on investigating the challenges mentioned above to further improve the overall performance of battery system, reduce the number of components and converters, increase the system efficiency and realize a robust and cost-effective battery energy storage system. Chapter 2 and Chapter 3 focus on the challengers related to SOC balancing and large number of components in battery systems. In Chapter 4, one unique aspect of the WEDES system is used in order to add flexibility and improve safety. Chapter 5 and Chapter 6 address the challenge related to decreased transmission efficiency in wireless power transfer when charging a battery. In Chapter 7, in order to deal with the challenge that additional components are required to realize wireless power transfer, a single dual-type-output power converter is discussed and analyzed. Chapter 8 provides a summary and conclusion for the work presented in this dissertation and discusses some potential future work.Item State-of-health diagnosis of lithium-ion battery systems and health-based control(University of Alabama Libraries, 2021) Xia, Zhiyong; Abu Qahouq, Jaber; University of Alabama TuscaloosaLithium-ion batteries are widely used in battery energy storage systems (BESS) because of their unique advantages, such as high energy density. State-of-health (SOH) estimation, as a critical function of a battery management system (BMS), is important to improve the safety and reliability of lithium-ion BESS. One objective of this dissertation is to develop fast and accurate SOH estimation methods to overcome shortcomings of conventional methods, such as slow estimation speed. Another main objective of this dissertation is to develop battery health-based control algorithms that utilize the output of SOH estimators. Chapter 1 presents an introduction to BESS and BMS and a literature review. It points out the challenges and importance of developing SOH estimation methods with improved performance such as speed and battery health-based SOC balancing control algorithms. Chapter 2 discusses the development of an in-house autonomous battery ageing platform. The developed platform can age a battery autonomously while obtaining and recording experimentally measured data of interest to support battery health diagnosis investigation and research. Chapter 3 analyzes the aggregated battery ageing data collected from the developed autonomous battery ageing platform. Several distinctive SOH indicators are identified to reflect the degradation level of battery to support the development of SOH estimators. Chapter 4 focuses on the development of power electronics based real-time online complex impedance spectrum measurement methods. These developed measurement methods support the development of online impedance based SOH estimators which provide fast SOH estimation for battery cells. In chapter 5, the correlations between the identified SOH indicators presented in chapter 3 and the SOH values of battery cells are utilized to develop deep neural network (DNN) based SOH estimators. It is observed that the diversity of SOH indicators used as the input of DNN can substantially improve estimation performance. Chapter 6 presents a battery health based SOC balancing control method. The presented method allows for drawing energy from battery cells intelligently based on the SOH differences among different battery cells, which helps to improve energy utilization efficiency and reliability of BESS. Chapter 7 concludes the research work presented in this dissertation and discusses potential future research.