https://orcid.org/0000-0002-3143-3939
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Abstract
Optimal air feed control of PEM fuel cell system is a very important issue to prevent stack degradation and maximize the net power output of the fuel cell stack. The control objective is to adjust the oxygen excess ratio at the required reference value to avoid the oxygen starvation at sudden current demand preventing the fuel-cell stack damage. This paper proposes a new controller which combines fuzzy feedback and fuzzy feedforward to eliminate the effect of the disturbance. The feedback part comprises a fuzzy PID controller and the feedforward part comprises a single input single output fuzzy controller. Simultaneous optimization of the controller parameters is accomplished using a new optimization algorithm called electromagnetic field optimization (EFO). EFO is a new physics-inspired evolutionary algorithm with a high level of cooperation between population members. This paper is the first use of the EFO algorithm for control applications and fuzzy controller optimization with the application to PEMFC air feed system. Simulation results show the effectiveness of the proposed controller by improving the transient response and regulating the oxygen excess ratio at the required value.
ACKNOWLEDGMENT
M. S. AbouOmar acknowledges the CSC and the Egyptian Government for the financial support. Authors acknowledge the reviewers for their valuable time and comments.
Additional information
Notes on contributors
Mahmoud S. AbouOmar
Mahmoud S AbouOmar received the BSc and MSc in industrial electronic and control engineering from Menofia University, Egypt, in 2009 and 2014, respectively. Now, he is a PhD candidate at school of Automation, Wuhan University of Technology, China. His current research interests include intelligent control, system optimization, soft computing techniques, evolutionary algorithms, control of new energy sources, mechatronics and embedded systems. Email: [email protected]
Yi-Xin Su
Yi-Xin Su received the BSc degree in process control from Wuhan University, China, in 1985, the MSc degree in control theory and application from Southeast University, China, in 1988. He received the Ph.D. degree in mechanical manufacturing & automation from Huazhong University of Science and Technology (HUST), China, in 2006. He is currently a professor at the School of Automation, Wuhan University of Technology, China. He is the deputy dean of the School of Automation, Wuhan University of Technology, China. His current research interests include intelligent controls, evolutionary computation, marine motion control, and cryptography technology for networks, etc. Email: [email protected]
Hua-Jun Zhang
Hua-Jun Zhang received the BSc degree in electrical engineering and MSc degree in control theory and application from Wuhan University of Technology, China, in 2003 and 2006, and the PhD degree in control theory and application from Huazhong University of Science and Technology (HUST), China, in 2010, respectively. He is an associate professor of electrical engineering at the School of Automation, Wuhan University of Technology, China. His current research interests include adaptive control, system optimization, and control of ocean vehicles. Corresponding author. Email: [email protected]
