An Online-Applicable Model for Predicting Health Degradation of PEM Fuel Cells with Root Cause Analysis

This paper proposes a new prognostic method for the health state of proton exchange membrane (PEM) fuel cells. The method is designed to predict the state-of-health (SOH) of PEMs and provide root cause analysis of the predicted health degradation. In this method, an equivalent circuit model (ECM) is built to emulate the impedance spectrum of PEM fuel cells. Because the key degradation parameters in the ECM cannot be measured in situ, this method instead estimates the parameters indirectly using the output voltage. The estimation is based on the linear relationship between the key ECM parameters and the output voltage. Using the constructed ECM and the estimated parameters, an impedance spectrum at the current moment is produced. The historical voltage evolution is then extrapolated using linear and exponential models that represent the irreversible and reversible phenomena, respectively. The models are used to predict future ECM parameters and, eventually, the impedance spectrum at any moment in the future. Through these steps, the proposed method provides an online estimation of the current SOH and predicts the level of future degradation. The primary novel feature of the proposed method is its ability to diagnose the root causes of potential degradation using data from nondisruptive online monitoring.