Fault Detection and Isolation for Proton Exchange Membrane Fuel Cell Using Impedance Measurements and Multiphysics Modeling

Abstract

This study proposes a fault detection and isolation tool for proton exchange membrane fuel cell (PEMFC) operating in embedded applications. A model-based approach, taking partially into account degradation phenomena, is proposed in order to increase the robustness of the tool regarding transient operations and stack ageing. The considered faults are the abnormal operating conditions that can decrease the fuel cell lifetime. The fault detection approach is based on residual generation using both voltage and high frequency resistance measurements and thus combining the advantages of knowledge-based model and electrochemical impedance spectroscopy (EIS) diagnosis approaches. To that end, a multi-physics fuel cell model has been used. This model computes not only the stack voltage but also the high frequency resistance in dynamic conditions. Additionally, the model is modified to take into account the ageing of the fuel cell. Validation is carried out on experimental characterizations during 1,000 h ageing. The results on a new fuel cell stack show a score of 91% for fault isolation. However, without any adaptation, this score drops dramatically as the stack ages. Finally, thanks to ageing modeling and to the proposed adaptation of the detection/isolation procedure, the diagnosis performance remains reliable during fuel cell stack ageing.

Fault Detection for PEM Fuel Cells via Analytical Redundancy: A Critical Review and Prospects

“…Motivated by the fact that neither the stack output voltage nor the EIS characterization can singlehandedly provide sufficient detection of the major faults in the PEMFC, the thesis work of Julian in [26] combines estimation of the stack voltage and high-frequency impedance. The methodology employed a multiphysics model called MePHYSTO-FC, which is developed in the CEA [27].…”

Experimental investigation of stable the proton exchange membrane fuel cell control using magnetic sensor probes

“…However, these operations can cause dry-out. Therefore, for monitoring this failure, methods including cell segmentation [10], temperature measurement [11,12], cell resistance (through current interrupt) [13][14][15], and cell impedance (through the Cole-Cole plot) [10,[15][16][17], and MRI [6] are utilized. As these results affect the strategies for mitigating dry-out such as control of the operating flow rate [18] and temperature [19], it is crucial to prevent such main failures, which affect the cell performance in a PEMFC system.…”