A phenomenological-based dynamic model of ethanol steam reforming for hydrogen production

This article presents a detailed deduction of a nonlinear dynamic model for an ethanol steam reforming (ESR) process designed to produce pure hydrogen for fuel-cell applications and renewable energy integration. Such a model is derived by using a well-established phenomenological-based semi-physical modeling (PBSM) methodology. The process comprises two sequential stages, the reforming stage and the hydrogen separation stage, both carried out within a single integrated module known as a staged-separation membrane reactor (SSMR). The resulting system of algebraic and ordinary differential equations captures the temporal and spatial evolution of gas temperature and species concentrations along the device, effectively representing the system’s dynamics. A set of model parameters are identified using a multi-objective optimization algorithm to fit the model to experimental data obtained from a real SSMR setup. Simulation results under various operating conditions demonstrate the model accuracy and reliability. The model is implemented in Python and is openly accessible through an online repository. • Nonlinear dynamic model of an ethanol steam reformer for pure hydrogen production. • Model derived via phenomenological-based semi-physical modeling methodology. • Captures the dynamics of reforming and separation stages in a membrane reactor. • Parameters estimated using multi-objective optimization and experimental validation. • Open-source Python implementation available for simulation and control applications.