Fuel cell diagnosis method based on multifractal analysis of stack voltage signal

Measuring local singularities on voltage signal transmits valuable information about the evolving dynamics of non-stationary and nonlinear processes in fuel cell systems. This paper deals with wavelet transform combined with multifractal formalism proposed for PEMFC behavior analysis. The proposed method combines the capability of wavelet transform to produce high coefficients on the singular points of signals and the ability of multifractal formalism to measure the singularity strength via the wavelet coefficients. This method is applied in order to discriminate the voltage signals acquired on a PEMFC operated in different conditions. The average multifractal spectrum estimated on voltage signals acquired at nominal operating conditions is compared to those measured for poor operating conditions considered as fault modes. rpose of this study is threefold. First, the multifractal structure of the fuel cell voltage signal is highlighted. Second, the singularities signature of severe operating conditions is revealed through the multifractal spectrum. Third, the wavelet based multifractal spectrum can be considered as a pertinent tool for the non-intrusive diagnosis of fuel cells.