An Online Impedance Processing Method for Fuel Cell EIS Measurements Enabling Degradation Information Extraction

摘要

Effective diagnostic methods are highly needed to help improve durability and lifetime of fuel cell stacks. This paper proposes a new diagnostic method based on impedance processing of electrochemical impedance spectroscopy (EIS) measurements of a fuel cell stack (FCS). A three-dimensional feature extraction method is designed to replace the equivalent circuit model commonly used for modeling the EIS signature. By tracking internal resistance, polarization resistance, and maximum imaginary response features, the method detects a fault and isolates it from the normal degradation of a fuel cell. The proposed method can separate fault conditions from degradation and extract the degradation information effectively. The method successfully detected and isolated flooding and drying on the experimental data. The method is computationally efficient and easy to adopt for online implementations, making it particularly useful in motive applications such as fuel cell vehicles.