Open AccessFault detection for PEM fuel cell using kalman filter
Author(s) -
D Ramamoorthy,
Ernie Che Mid
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1432/1/012070
Subject(s) - proton exchange membrane fuel cell , kalman filter , fault detection and isolation , extended kalman filter , flooding (psychology) , redundancy (engineering) , stack (abstract data type) , computer science , control theory (sociology) , engineering , fuel cells , reliability engineering , artificial intelligence , chemical engineering , actuator , psychology , control (management) , psychotherapist , programming language
Fault detection plays a key role in high cost and safe-critical systems to avoid the occurrence of an abnormal event. This work presents a model-based fault detection in the water management system of proton-exchange membrane (PEM) fuel cell stack using Kalman filter (KF). The KF is a model-based FD method relies on analytical redundancy to predict the related fault disturbed by some noise. Then, it corrected the faults with its mathematical model to minimize the error covariance between the normal and faulty scenarios by a repetitive process. Two faulty scenarios; flooding and drying which happen at anode and cathode side of PEM fuel cell are investigated. The proposed FD method using KF has successfully detected flooding and drying faults in PEMFC.