A degenerated equivalent circuit model and hybrid prediction for state-of-health (SOH) of PEM fuel cell

Abstract

The 2014 IEEE PHM data challenge problem deals with the state-of-health (SOH) of proton exchange membrane fuel cell (PEMFC) given two degradation data sets: (i) a reference data set (FC1) operated under constant current is fully given until 991 h and (ii) a test data set (FC2) operated under rippled current is partially given until 550h. The proposed research aims at predicting the SOH (or EIS spectra) of PEM fuel cell after 550h for FC2. First, a full scale equivalent circuit model (ECM) with 10 parameters is developed to describe the electrochemical physics of PEMFC more realistically. The model reduction is suggested because of limited data. Since some parameters remain nearly unchanged due to irrelevance to degradation, it is reasonable to use the degenerated 4-parameter ECM while fixing the other parameters at their means. Despite the model reduction, the degradation pattern is clearly observed through the degenerated 4-parameter ECM. Then the coefficients of the four parameters are estimated by building linear regression models between the parameters and voltage. Since the voltage change after 550h is not provided for FC2, the voltage degradation model is developed by modeling both reversible and irreversible degradation processes. This research also proposes a hybrid prognostic approach to the SOH (or EIS spectra) prediction. The voltage degradation model and the degenerated 4-parameter ECM are first developed based on the observation of the physical phenomenon. They are then trained for the purpose of the SOH prediction with the training EIS data sets (FC1 and FC2). It is demonstrated that this hybrid SOH prediction offers highly accurate prediction of the SOH (or EIS spectra) at t = 666, 830, and 1016h. Moreover, possible error sources are also discussed to further improve the prediction accuracy in future.