Fuel cells enable the use of green hydrogen in sustainable propulsion concepts and could hence significantly contribute to achieving aviation’s climate goals. To maximise benefits, performance and cost efficiency are essential. The convergence of sensing and machine learning offers new degrees of freedom for optimisation through innovative monitoring and control strategies. For effective exploitation, it is imperative to research correlations of, for example, aviation-typical operating conditions and ageing or design and control parameters. Hence, gaining a solid database from dedicated stress and performance tests is essential to exploit potentials for optimised design, durability, and life-cycle costs.