Understanding Challenges of Optimization‐Based Distribution of Relaxation Times of Electrochemical Impedance Spectroscopy for Commercial Fuel Cell Stack

ABSTRACT The Distribution of Relaxation Times (DRT) technique has been widely used in fuel cell diagnostics due to its higher resolution of electrode processes compared to the Nyquist plot derived from impedance spectroscopy. However, DRT is often treated as a plug‐and‐play tool in many studies, leading to inappropriate or even erroneous interpretations due to insufficient investigation of optimization algorithms. This study focuses on the inversion‐based DRT and examines a common linear optimization algorithm based on Gaussian functions, spotlighting the trade‐off between accuracy and resolution as influenced by three parameters: the number of basis functions, their width, and the regularization factor. It is found that the first one affects the accuracy. The integrated peak area provides a more reliable measure than the peak height, evidenced by a standard deviation of 0.11 versus 0.16 for the latter. Meanwhile, the last two parameters significantly influence the resolution; improper selection of them leads to the emergence of spurious peaks. Using appropriately chosen parameters, the state of a 120‐cell stack is detected. Results reveal the clear evolution of oxygen transport and oxygen reduction reaction at different positions under varying stoichiometric ratios. This study underscores the importance of computational efforts in selecting key parameters to enable reliable DRT‐based diagnostics.