Date of Completion

12-22-2014

Embargo Period

12-22-2014

Keywords

Battery Management Systems, Condition-based Maintenance, State of Charge, State of Health, Remaining Useful Life, Fault Diagnosis and Isolation, Prognosis, Model Predictive Control, Machine Learning, Pattern Recognition, Neural Networks, Optimization, Markov Decision Processes, Hidden Markov Model, Support Vector Machine, Least Squares, Parameter Estimation, System Identification

Major Advisor

Prof. Krishna R. Pattipati

Associate Advisor

Prof. Yaakov Bar-Shalom

Associate Advisor

Prof. Shengli Zhou

Associate Advisor

Asst. Research Prof. Balakumar Balasingam

Field of Study

Electrical Engineering

Degree

Doctor of Philosophy

Open Access

Open Access

Abstract

This thesis aims to solve several important problems in engineering. Four fundamental areas of research have been examined: (i) Battery Management Systems; (ii) Battery Fuel Gauging; (iii) Condition-based Maintenance; and (iv) Prognosis in Coupled Systems. The prognostication algorithms developed have been validated on data collected from either real-world or hardware-in-the-loop experiments or both. The approaches proposed are modular and have the potential to be applicable to a wide variety of complex systems, ranging from portable applications to automotive and aerospace systems.

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