Prognostics of PEM fuel cell in a particle filtering framework

Abstract

Proton Exchange Membrane Fuel Cells (PEMFC) suffer from a limited lifespan, which impedes their uses at a large scale. From this point of view, prognostics appears to be a promising activity since the estimation of the Remaining Useful Life (RUL) before a failure occurs allows deciding from mitigation actions at the right time when needed. Prognostics is however not a trivial task: 1) underlying degradation mechanisms cannot be easily measured and modeled, 2) health prediction must be performed with a long enough time horizon to allow reaction. The aim of this paper is to face these problems by proposing a prognostics framework that enables avoiding assumptions on the PEMFC behavior, while ensuring good accuracy on RUL estimates. Developments are based on a particle filtering approach that enables including non-observable states (degradation through time) into physical models. RUL estimates are obtained by considering successive probability distributions of degrading states. The method is applied on 2 data sets, where 3 models of the voltage drop are tested to compare predictions. Results are obtained with an accuracy of 90 hours around the real RUL value (for a 1000 hours lifespan), clearly showing the significance of the proposed approach.

Application of the Sensor Selection Approach in Polymer Electrolyte Membrane Fuel Cell Prognostics and Health Management

“…Data-driven approaches are more widely used for fuel cell diagnostics, that is, extracting the features by applying signal processing techniques to the sensor data, and discriminating fuel cell faults with extracted features [9][10][11][12][13]. Compared to fuel cell diagnostics, fewer studies have been devoted to fuel cell prognostics, and among these studies, training data from a fuel cell system is required to generate the input-output relationship of the fuel cell model for the prediction of future performance [14][15][16][17][18].…”

Intelligent Prognostic Framework for Degradation Assessment and Remaining Useful Life Estimation of Photovoltaic Module

“…In this case, hybrid approaches can be used that operate with two kinds of information (the degradation model and measurement data). According to bibliographic studies, particle filter is a hybrid method that meets our requirements and has shown its capability in multiple applications [56,57]. The degradation model that we aim to use in future work is that of output power, as mentioned in [58].…”

Proton exchange membrane fuel cell behavioral model suitable for prognostics

“…The black box modeling has already been investigated [21,31]. The physical based approach is developed with this first step of modeling.…”