ORCID Identifier(s)


Graduation Semester and Year




Document Type


Degree Name

Doctor of Philosophy in Electrical Engineering


Electrical Engineering

First Advisor

David Wetz


Lithium-ion batteries have gained widespread use in various applications, but safety challenges persist due to errors in assembly and faulty electronics management. Ensuring safety and reliable operation in large batteries containing numerous series/parallel cells demand innovative monitoring technologies. Elevated temperatures resulting from normal or abnormal operation are a major cause of battery failure, necessitating effective temperature monitoring techniques. Similarly, abnormal stress/strain signatures offer valuable diagnostic information. In the study discussed here, the application of a Optical Distributed Sensor Interrogator (ODiSI) employing high-definition fiber optic sensors (HD-FOS) for measuring surface temperature and case deformation of 18650 cells under normal and abnormal conditions, respectively, has been shown. The FOS replaces multiple discrete thermocouples or strain gauges and provides measurements with millimeter resolution along the fiber length, ensuring early detection and identification of abnormal cell operation on individual cells assembled within large batteries. The unique and repeatable results this measurement delivers for effective lithium-ion cell monitoring has been demonstrated through the development and employment of a novel data acquisition system that is interfaced with the ODiSI and a system level controller. In addition to the sensor work performed, this report documents the design and implementation of a novel battery sizing tool developed in the MATLAB programming environment. As power demands grow in civilian and defense applications, intelligent power system architectures with properly sized energy storage become critical. Sizing energy storage accurately is challenging due to impedance and capacity variations under different operating conditions. To address this, the MATLAB-based energy storage sizing tool uses comprehensive databases derived from empirical data collected from various energy storage cells. This tool aids power system engineers in optimally sizing energy storage to meet voltage and load requirements, considering each cell's characteristics within the database. Together, these studies present innovative approaches to address safety challenges, monitor individual cells, and properly size energy storage in lithium-ion batteries, offering promising solutions for safer and more reliable battery operation in diverse applications.


Batteries, Fiber optic sensors, Temperature monitoring, Strain monitoring, Abnormal operation, Energy storage, MATLAB, Database, Sizing tool


Electrical and Computer Engineering | Engineering


Degree granted by The University of Texas at Arlington