PEMFC internal states observation for optimizing its efficiency and useful life

Proton Exchange Membrane Fuel Cells (PEMFC) are one of the preferred technologies for decarbonizing the transport sector, due to their autonomy and ease of recharging. However, their large-scale democratization is hampered by their high cost, which is compounded by their unsatisfactory durability. 
Early degradation of PEMFCs is concentrated on their constituent parts, and in particular on the membrane that acts as the electrolyte, which is highly sensitive to variations in humidity and temperature during use. What's more, the distribution of these quantities over the surface of the membrane can be highly heterogeneous, making it difficult to measure with simple sensors. To anticipate potential degradation while improving performance, acceptable operating conditions in terms of humidity and temperature need to be maintained throughout the cell. It is in this area that this thesis focuses, firstly by estimating the stack's internal variables (humidity, temperature, quantities of materials) in real time to a satisfactory degree of accuracy, which will then be used as information for adapting the stack's control laws. This thesis will contribute to the development of accurate and fast stack models and real-time control strategies in order to remove the scientific barriers that currently prevent the sustainable use of PEMFCs. 
The PhD student will develop skills in control engineering, physical modelling, computer science and optimization, and will be likely to forge close links with high-level academic and industrial partners.

Keywords: fuel cell, hydrogen, soft sensor

• Academic supervisor    Dr Florent DI MEGLIO, CAS, ORCID : 0000-0002-0232-6130  
• Doctoral School    ED 621, Ecole des Mines Paris 
• IFPEN supervisor    Dr Gontran LANCE
• PhD location    IFPEN, Lyon, France   
• Duration and start date    3 years, starting in the fourth quarter 2024 (Novembre 4)
• Employer    IFPEN 
• Academic requirements    University Master degree in applied mathematics, automation, signal processing, electrochemistry  
• Language requirements    English level B2 (CEFR)     
• Other requirements    Good programming skills in MATLAB and/or Python, C/C++ would be welcomed 

To apply, please send your cover letter and CV to the IFPEN supervisor indicated below.