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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.


Li-ion batteries are being used on a large scale varying from consumer electronics to electric vehicles. The key to efficient use of batteries is implementing a well-developed battery management system. Also, there is an opportunity for research for improving the battery performance in terms of size and capacity. For all this it is imperative to develop Li-ion cell model that replicate the performance of a physical cell unit. This report discusses a dual polarization cell model and a battery management system implemented to control the operation of the battery. The Li-ion cell is modelled, and the performance is observed in …

Contributors
Puranik, Ishaan, Qin, Jiangchao, Karady, George, et al.
Created Date
2018

With growing concern regarding environmental issues and the need for a more sustainable grid, power systems have seen a fast expansion of renewable resources in the last decade. The uncertainty and variability of renewable resources has posed new challenges on system operators. Due to its energy-shifting and fast-ramping capabilities, energy storage (ES) has been considered as an attractive solution to alleviate the increased renewable uncertainty and variability. In this dissertation, stochastic optimization is utilized to evaluate the benefit of bulk energy storage to facilitate the integration of high levels of renewable resources in transmission systems. A cost-benefit analysis is performed …

Contributors
Li, Nan, Hedman, Kory W, Tylavksy, Daniel J, et al.
Created Date
2016