Fuel Cell Power Management Using Genetic Expression Programming in All-Electric Ships

被引:58
作者
Abkenar, Alireza Tashakori [1 ]
Nazari, Ali [2 ]
Jayasinghe, Shantha D. Gamini [3 ]
Kapoor, Ajay [2 ]
Negnevitsky, Michael [4 ]
机构
[1] Avass Elect Vehicle Mfg Grp, Lara, Vic 3212, Australia
[2] Swinburne Univ Technol, Fac Sci Engn & Technol, Melbourne, Vic 3101, Australia
[3] Univ Tasmania, Australian Maritime Coll, Natl Ctr Ports & Shipping, Launceston, Tas 7248, Australia
[4] Univ Tasmania, Power Engn & Computat Intelligence, Hobart, Tas 7005, Australia
关键词
All-electric ships; FC control strategy; FC power Management; fuel cells; genetic algorithms; ENERGY MANAGEMENT; PREDICTIVE CONTROL; HYBRID; SIMULATION; LOAD; PERFORMANCE; VOLTAGE; MODELS; SYSTEM; DRIVE;
D O I
10.1109/TEC.2017.2693275
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
080707 [能源环境工程]; 082001 [油气井工程];
摘要
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.
引用
收藏
页码:779 / 787
页数:9
相关论文
共 48 条
[1]
Al Savvaris, 2016, MED C CONTR AUTOMAT, P1242, DOI 10.1109/MED.2016.7536038
[2]
[Anonymous], 2012, WORLD ACAD SCI ENG T
[3]
[Anonymous], 2015, P INT C EL SYST AIRC
[4]
[Anonymous], 1992, GENETIC PROGRAMMING
[5]
Propulsion Drive Models for Full Electric Marine Propulsion Systems [J].
Apsley, Judith M. ;
Gonzalez-Villasenor, Aurelio ;
Barnes, Mike ;
Smith, Alexander C. ;
Williamson, Steve ;
Schuddebeurs, Jeroen D. ;
Norman, Patrick J. ;
Booth, Campbell D. ;
Burt, Graeme M. ;
McDonald, J. R. .
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, 2009, 45 (02) :676-684
[6]
Simulation-Based Modeling and Power Management of All-Electric Ships Based on Renewable Energy Generation Using Model Predictive Control Strategy [J].
Banaei, Mohamad Reza ;
Alizadeh, Rana .
IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE, 2016, 8 (02) :90-103
[7]
Genetic programming model of solid oxide fuel cell stack: First results [J].
Chakraborty, Uday K. .
International Journal of Information and Communication Technology, 2008, 1 (3-4) :453-461
[8]
An Evolutionary Computation Approach to Predicting Output Voltage from Fuel Utilization in SOFC Stacks [J].
Chakraborty, Uday K. .
2009 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-5, 2009, :2165-2171
[9]
Static and dynamic modeling of solid oxide fuel cell using genetic programming [J].
Chakraborty, Uday Kumar .
ENERGY, 2009, 34 (06) :740-751
[10]
Electric, Hybrid, and Fuel-Cell Vehicles: Architectures and Modeling [J].
Chan, C. C. ;
Bouscayrol, Alain ;
Chen, Keyu .
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2010, 59 (02) :589-598