Date of Award
5-2026
Degree Type
Thesis
Degree Name
M.S.E.
Degree Program
Electrical Engineering
Department
Electrical Engineering
Major Professor
Huimin Chen, Ph.D.
Second Advisor
Nikolaos I. Xiros, DEng.
Third Advisor
Kim Jovanovich, M.S., P.E.
Abstract
This thesis presents an optimization-based framework for power management in hybrid towing vessels operating under dynamic mission conditions. A physically consistent modeling approach is developed, incorporating battery state-of-charge dynamics (SOC), unified power flow, and operational constraints. The framework evaluates rule-based control using fixed heuristic thresholds, Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and multi-objective Non-Dominated Sorting Genetic Algorithm II (NSGA-II) under a representative harbor-assist mission profile. Results show that optimization-based methods significantly outperform rule-based control. PSO achieves the lowest fuel consumption and near-perfect tracking with minimal battery use, while GA provides balanced performance with moderate battery utilization. NSGA-II reveals a broader set of solutions, enabling battery-driven energy shifting at the cost of increased tracking error. The results demonstrate that objective formulation directly governs system behavior and highlight the need for mission-aware optimization strategies for hybrid marine propulsion systems.
Recommended Citation
Burchill, Rachel K., "Optimization-Based Power Management for Hybrid Towing Vessels: A Comparative Framework Toward Mission-Aware Control" (2026). University of New Orleans Theses and Dissertations. 3365.
https://scholarworks.uno.edu/td/3365
Rights
The University of New Orleans and its agents retain the non-exclusive license to archive and make accessible this dissertation or thesis in whole or in part in all forms of media, now or hereafter known. The author retains all other ownership rights to the copyright of the thesis or dissertation.