DocumentCode :
264460
Title :
A degenerated equivalent circuit model and hybrid prediction for state-of-health (SOH) of PEM fuel cell
Author :
Taejin Kim ; Hyunjae Kim ; Jongmoon Ha ; Keunsu Kim ; Jungtaek Youn ; Joonha Jung ; Youn, Byeng D.
Author_Institution :
Dept. of Mech. & Aerosp. Eng., Seoul Nat. Univ., Seoul, South Korea
fYear :
2014
fDate :
22-25 June 2014
Firstpage :
1
Lastpage :
7
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.
Keywords :
condition monitoring; equivalent circuits; parameter estimation; proton exchange membrane fuel cells; regression analysis; 2014 IEEE PHM data challenge problem; EIS spectra; PEM fuel cell; PEMFC; degenerated equivalent circuit model; degradation data set; degradation pattern; electrochemical physics; full scale equivalent circuit model; hybrid prediction; linear regression models; model reduction; parameter estimation; proton exchange membrane fuel cell; reference data set; rippled current; state-of-health; test data set; voltage degradation model; Degradation; Electronic countermeasures; Estimation; Fuel cells; Impedance; Integrated circuit modeling; Predictive models;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Prognostics and Health Management (PHM), 2014 IEEE Conference on
Conference_Location :
Cheney, WA
Type :
conf
DOI :
10.1109/ICPHM.2014.7036407
Filename :
7036407
Link To Document :
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