Theses and Dissertations

Advisor

Rahimi, Shahram

Committee Member

Mittal, Sudip

Committee Member

Amirlatifi, Amin

Committee Member

Chaudhary, Vini

Date of Degree

8-7-2025

Original embargo terms

Immediate Worldwide Access

Document Type

Graduate Thesis - Open Access

Major

Research Computer Science

Degree Name

Master of Science (M.S.)

College

James Worth Bagley College of Engineering

Department

Department of Computer Science and Engineering

Abstract

This thesis addresses the challenge of estimating electric vehicle (EV) charging system reliability against unpredictable threats like cyberattacks and extreme weather, where traditional methods fail. We utilize the Principle of Maximum Entropy (PME), a statistical tool that provides unbiased risk estimates using limited information. Applied to the EV charging ecosystem, our case study shows how PME models stress factors to predict failures and optimize maintenance. This approach extends beyond EVs to other complex systems with scarce data, such as smart grids or healthcare devices. By linking uncertainty directly to reliability, PME offers a universal method to improve decision-making under unpredictable conditions, providing actionable insights for policymakers and industries to build safer, more resilient systems in our increasingly connected world.

Download

Share

COinS