Date of Award
Summer 8-22-2026
Document Type
Dissertation
Degree Name
Ph.D. in Electrical Engineering
Organizational Unit
Daniel Felix Ritchie School of Engineering and Computer Science, Electrical and Computer Engineering
First Advisor
Goncalo Martins
Second Advisor
Scott Trimboli
Third Advisor
Kimon Valavanis
Fourth Advisor
Rui Fan
Fifth Advisor
Alvaro Arias
Copyright Statement / License for Reuse
All Rights Reserved.
Keywords
Battery management systems, Control barrier functions, Fast charging, Model predictive control, Optimal control, State of power estimation
Abstract
Safe and efficient operation of batteries is paramount to extending their lifespan and ensuring reliability in battery management systems. This work presents a new approach for maximizing safety and performance of lithium-ion batteries in a variety of applications with a view towards efficiency in computation. The aim is to maximize a battery’s output (its power, speed of charging, and overall efficiency) while preserving its longevity and ensuring operational safety. This challenge is tackled by developing a novel control algorithm for advanced lithium-ion battery management leveraging control barrier functions (CBFs) to ensure safe and efficient operation during fast charging and discharging. Moreover, the proposed approach is extended to state of power (SOP) estimation, where the charging problem is reformulated to determine the maximum sustainable power over a predefined horizon that the battery can deliver or absorb while remaining within safe operating bounds. The aim is to help pave the way for more reliable and effective battery management systems in electric vehicles and energy storage applications.
Copyright Date
8-2026
Publication Statement
Copyright is held by the author. User is responsible for all copyright compliance.
Rights Holder
Magdalena Kossek
Provenance
Received from ProQuest
File Format
application/pdf
Language
English (eng)
Extent
142 pgs
File Size
5.2 MB
Recommended Citation
Kossek, Magdalena, "Ensuring Safety in Battery Management Systems: A Control Barrier Function Approach" (2026). Electronic Theses and Dissertations. 2783.
https://digitalcommons.du.edu/etd/2783
Included in
Other Computer Engineering Commons, Other Electrical and Computer Engineering Commons, Power and Energy Commons