Résumé

Hydrogen is known as one of the cleanest energy carriers. To meet the challenge of applying hydrogen energy to transportation in a reliable way, continuous health monitoring and assessment of fuel cell systems are essential to the long-term daily operation and maintenance schedule. In this context, this paper presents a brief literature review of the modeling methods dedicated to the health management of proton exchange membrane fuel cells and reports a dual-scale degradation modeling method developed in a Python environment. The potential of this modeling tool for long-term degradation assessment and health index identification has been justified through several case studies