Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm

In this paper, a new method is designed to effectively determine the parameters of proton exchange membrane fuel cells (PEMFCs), i.e., ?1, ?2, ?3, ?4, RC, ?, and b. The fuel�cells�(FCs) involve multiple variable quantities with complex non-linear behaviours, demanding accurate modelling to ensure op...

Full description

Bibliographic Details

Main Authors:	Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.
Other Authors:	57191413142
Format:	Article
Published:	Nature Research 2025
Subjects:	proton adaptive behavior algorithm article controlled study diagnosis foraging fuel goose learning mathematical model root mean squared error simulation
Tags:	Add Tag No Tags, Be the first to tag this record!