Data-Fusion Prognostics of Proton Exchange Membrane Fuel Cell Degradation

• Published in: IEEE transactions on industry applications Vol. 55; no. 4; pp. 4321 - 4331
• Main Authors: Ma, Rui, Li, Zhongliang, Breaz, Elena, Liu, Chen, Bai, Hao, Briois, Pascal, Gao, Fei
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE); Institute of Electrical and Electronics Engineers
• Subjects: Acoustics; Aging; Automatic; Automobile industry; Autoregressive models; Biological system modeling; Commercialization; Degradation; Electric power; Engineering Sciences; Fluid mechanics; fuel cell; Fuel cells; Integrated circuit modeling; machine learning; Materials; Mathematical model; Mechanics; Micro and nanotechnologies; Microelectronics; modeling; Physics; Predictive models; Proton exchange membrane fuel cells; Recording; Thermics; Transportation applications

Proton exchange membrane fuel cell (PEMFC) degradation prediction is essential especially in transportation applications, since one of the major issues that hinder its worldwide commercialization is represented by its durability. However, due to the complex physical phenomena inside the fuel cell, w...