Expert diagnosis of polymer electrolyte fuel cells. (20th April 2017)

• Record Type: Journal Article
• Authors: Davies, B.; Jackson, L.; Dunnett, S.
• Is Part Of: International journal of hydrogen energy. Volume 42:Number 16(2017)
• Page Start: 11724
• Page End: 11734
• Publication Date: 2017-04-20
• Subjects: Fuel cell -- Polymer electrolyte fuel cell -- PEFC -- Diagnosis -- Fuzzy logic -- Knowledge based system; Hydrogen as fuel -- Periodicals; Hydrogène (Combustible) -- Périodiques; Hydrogen as fuel; Periodicals; 665.81
• DOI: 10.1016/j.ijhydene.2017.02.121
• Languages: English
• ISSNs: 0360-3199

Abstract

Abstract: Diagnosing faulty conditions of engineering systems is a highly desirable process within control structures, such that control systems may operate effectively and degrading operational states may be mitigated. The goal herein is to enhance lifetime performance and extend system availability. Difficulty arises in developing a mathematical model which can describe all working and failure modes of complex systems. However the expert's knowledge of correct and faulty operation is powerful for detecting degradation, and such knowledge can be represented through fuzzy logic. This paper presents a diagnostic system based on fuzzy logic and expert knowledge, attained from experts and experimental findings. The diagnosis is applied specifically to degradation modes in a polymer electrolyte fuel cell. The defined rules produced for the fuzzy logic model connect observed operational modes and symptoms to component degradation. The diagnosis is then tested against common automotive stress conditions to assess functionality. Highlights: A Fuzzy Logic diagnostic algorithm for Polymer Electrolyte Fuel Cells is proposed. The diagnosis uses expert linguistic rules to identify specific component degradation. Continuous monitoring reveals degrading operating conditions and degradation severity. Validation testing is performed for water management issues in the PEFC.