TY - JOUR
T1 - Fuel Cell Power Management Using Genetic Expression Programming in All-Electric Ships
AU - Tashakori Abkenar, Alireza
AU - Nazari, Ali
AU - Jayasinghe, Shantha D.Gamini
AU - Kapoor, Ajay
AU - Negnevitsky, Michael
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/6
Y1 - 2017/6
N2 - All-electric ships (AES) are considered as an effective solution for reducing greenhouse gas emissions as they provide a better platform to use alternative clean energy sources such as fuel cells (FC) in place of fossil fuel. Even though FCs are promising alternative, their response is not fast enough to meet load transients that can occur in ships at sea. Therefore, high-density rechargeable battery storage systems are required to achieve stable operation under such transients. Generally, in such hybrid systems, dc/dc converters are used to interface the FC and battery into the dc link. This paper presents an intelligent FC power management strategy to improve FC performance at various operating points without employing dc/dc interfacing converters. A hybrid AES driveline model using genetic programming is utilized using Simulink and GeneXProTools4 to formulate operating FC voltage based on the load current, FC air, and fuel flow rates. Genetic algorithm is used to adjust air and fuel flow rates to keep the FC within the safe operating range at different power demands. The proposed method maintains FC performance as well as reduces fuel consumption, and, thereby, ensures the optimal power sharing between the FC and the lithium-ion battery in AES application.
AB - All-electric ships (AES) are considered as an effective solution for reducing greenhouse gas emissions as they provide a better platform to use alternative clean energy sources such as fuel cells (FC) in place of fossil fuel. Even though FCs are promising alternative, their response is not fast enough to meet load transients that can occur in ships at sea. Therefore, high-density rechargeable battery storage systems are required to achieve stable operation under such transients. Generally, in such hybrid systems, dc/dc converters are used to interface the FC and battery into the dc link. This paper presents an intelligent FC power management strategy to improve FC performance at various operating points without employing dc/dc interfacing converters. A hybrid AES driveline model using genetic programming is utilized using Simulink and GeneXProTools4 to formulate operating FC voltage based on the load current, FC air, and fuel flow rates. Genetic algorithm is used to adjust air and fuel flow rates to keep the FC within the safe operating range at different power demands. The proposed method maintains FC performance as well as reduces fuel consumption, and, thereby, ensures the optimal power sharing between the FC and the lithium-ion battery in AES application.
KW - All-electric ships
KW - FC control strategy
KW - FC power Management
KW - fuel cells
KW - genetic algorithms
UR - http://www.scopus.com/inward/record.url?scp=85028358351&partnerID=8YFLogxK
U2 - 10.1109/TEC.2017.2693275
DO - 10.1109/TEC.2017.2693275
M3 - Article
SN - 0885-8969
VL - 32
SP - 779
EP - 787
JO - IEEE Transactions on Energy Conversion
JF - IEEE Transactions on Energy Conversion
IS - 2
M1 - 7898826
ER -