A Novel Type-2 Fuzzy Logic for Improved Risk Analysis of Proton Exchange Membrane Fuel Cells in Marine Power Systems Application

Sajjad Bahrebar, Frede Blaabjerg, Huai Wang, Navid Vafamand, Mohammad-Hassan Khooban, Sima Rastayesh and Dao Zhou
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Sajjad Bahrebar: Department of Energy Technology, Aalborg University, Pontoppidanstræde 101, 9220 Aalborg Ø, Denmark
Frede Blaabjerg: Department of Energy Technology, Aalborg University, Pontoppidanstræde 101, 9220 Aalborg Ø, Denmark
Huai Wang: Department of Energy Technology, Aalborg University, Pontoppidanstræde 101, 9220 Aalborg Ø, Denmark
Navid Vafamand: Department of Energy Technology, Aalborg University, Pontoppidanstræde 101, 9220 Aalborg Ø, Denmark
Mohammad-Hassan Khooban: Department of Energy Technology, Aalborg University, Pontoppidanstræde 101, 9220 Aalborg Ø, Denmark
Sima Rastayesh: Department of Civil Engineering, Aalborg University, Thomas Manns Vej 23, 9220 Aalborg Ø, Denmark
Dao Zhou: Department of Energy Technology, Aalborg University, Pontoppidanstræde 101, 9220 Aalborg Ø, Denmark

Energies, 2018, vol. 11, issue 4, 1-16

Abstract: A marine energy system, which is fundamentally not paired with electric grids, should work for an extended period with high reliability. To put it in another way, by employing electrical utilities on a ship, the electrical power demand has been increasing in recent years. Besides, fuel cells in marine power generation may reduce the loss of energy and weight in long cables and provide a platform such that each piece of marine equipment is supplied with its own isolated wire connection. Hence, fuel cells can be promising power generation equipment in the marine industry. Besides, failure modes and effects analysis (FMEA) is widely accepted throughout the industry as a valuable tool for identifying, ranking, and mitigating risks. The FMEA process can help to design safe hydrogen fueling stations. In this paper, a robust FMEA has been developed to identify the potentially hazardous conditions of the marine propulsion system by considering a general type-2 fuzzy logic set. The general type-2 fuzzy system is decomposed of several interval type-2 fuzzy logic systems to reduce the inherent highly computational burden of the general type-2 fuzzy systems. Linguistic rules are directly incorporated into the fuzzy system. Finally, the results demonstrate the success and effectiveness of the proposed approach in computing the risk priority number as compared to state-of-the-art methods.

Keywords: Proton Exchange Membrane Fuel Cell (PEMFC); failure mode and effect analysis (FMEA); risk priority number (RPN); general type II fuzzy logic (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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