TY - GEN
T1 - Dynamic Modeling and Control of Hybrid Electric Vessels with a Super-Capacitor and a Lithium Battery
AU - Huang, Chi Chang
AU - Lin, Chien Ming
AU - Lin, Yu Hsuan
AU - Lin, Chan Chiao
AU - Hung, Yi Hsuan
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This paper presents a dynamic model of a dual-motor vessel powered by an integrated energy system consisting of a supercapacitor (SC) and lithium battery. The SC manages high-power demands, reducing the load on the lithium battery to enhance its lifespan and improve overall system efficiency. MATLAB/Simulink was used to simulate this model, integrating energy sources, transmission systems, traction motors, propellers, and vessel body dynamics. A rule-based control strategy (RBCS) with specific operational modes—Supercapacitor Mode, Hybrid Mode I, Hybrid Mode II, and Hybrid Mode III—was developed to effectively manage energy distribution, improving energy flow and extending battery life, which lowers maintenance costs and enhances performance. Additionally, a fuzzy control method was implemented and compared to RBCS. Results indicate that fuzzy control improves velocity stabilization by 3.8% between 750 and 1200 seconds, and reduces energy consumption by approximately 5.7% compared to RBCS, highlighting its potential for greater efficiency and control in vessel propulsion energy management.
AB - This paper presents a dynamic model of a dual-motor vessel powered by an integrated energy system consisting of a supercapacitor (SC) and lithium battery. The SC manages high-power demands, reducing the load on the lithium battery to enhance its lifespan and improve overall system efficiency. MATLAB/Simulink was used to simulate this model, integrating energy sources, transmission systems, traction motors, propellers, and vessel body dynamics. A rule-based control strategy (RBCS) with specific operational modes—Supercapacitor Mode, Hybrid Mode I, Hybrid Mode II, and Hybrid Mode III—was developed to effectively manage energy distribution, improving energy flow and extending battery life, which lowers maintenance costs and enhances performance. Additionally, a fuzzy control method was implemented and compared to RBCS. Results indicate that fuzzy control improves velocity stabilization by 3.8% between 750 and 1200 seconds, and reduces energy consumption by approximately 5.7% compared to RBCS, highlighting its potential for greater efficiency and control in vessel propulsion energy management.
KW - energy management system
KW - super-capacitor and lithium battery
KW - vessel control
KW - vessel dynamics
UR - https://www.scopus.com/pages/publications/85215011188
UR - https://www.scopus.com/pages/publications/85215011188#tab=citedBy
U2 - 10.1109/RASSE64357.2024.10773634
DO - 10.1109/RASSE64357.2024.10773634
M3 - Conference contribution
AN - SCOPUS:85215011188
T3 - RASSE 2024 - 2024 IEEE International Conference on Recent Advances in Systems Science and Engineering, Proceedings
BT - RASSE 2024 - 2024 IEEE International Conference on Recent Advances in Systems Science and Engineering, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE International Conference on Recent Advances in Systems Science and Engineering, RASSE 2024
Y2 - 6 November 2024 through 8 November 2024
ER -
