System Identification of the PEMFCs based on Balanced Manta-Ray Foraging Optimization algorithm

• Main Authors: Biqi Sheng, Tianhong Pan, Yun Luo, Kittisak Jermsittiparsert
• Format: Article
• Language: English
• Published: Elsevier 2020-11-01
• Series: Energy Reports
• Subjects: Proton exchange membrane fuel cell; Model identification; Voltage estimation; Balanced Manta-Ray Foraging Optimization algorithm
• Online Access: http://www.sciencedirect.com/science/article/pii/S2352484720313561

The present paper proposes a new optimal method for modeling and simulating of a proton exchange membrane fuel cell (PEMFC) system. The main idea is to minimize the Sum of Squared Error (SSE) between the experimental and the estimated output voltages to achieve the maximum agreement between them. To minimize the error value, a modified metaheuristic, called Balanced Manta-Ray Foraging Optimization (BMRFO) algorithm has been designed. The designed algorithm is proposed for resolving the algorithm premature convergence and to improve the algorithm diversity. By performing 30 independent runs for the suggested BMRFO algorithm and comparing it with some other algorithms from the literature, it is observed that the proposed method gives better convergency in speed and accuracy.