(518f) An Experimental Study of Feedback Control for an Electrically-Heated Steam Methane Reforming Process

Steam Methane Reforming (SMR) is the most common industrial process to produce Hydrogen (H₂) from methane and steam. The SMR reactions are overall highly endothermic, and traditionally fossil fuels are burned to provide the necessary heat. However, it was discovered that electrifying the tubular SMR reactors to replace conventional heating gives the opportunity of producing H₂ with very low emissions, lower reactor volumes and higher carbon conversion [1]. While the current studies focus on improving the catalysts or heating sources, a more efficient process control scheme can also have a significant impact to the efficient production of H₂ in terms of response speed, safety, and catalyst life. In order to explore the electrically-heated SMR process and control strategies in deeper detail, we have constructed an experimental joule-heated SMR setup at UCLA. The setup contains a tubular reactor with a wash-coated Ni-based catalyst, two thermocouples connected to the top and bottom of the reactor, a power supply for providing electrical heating, and a gas chromatograph (GC) for sensing the outlet gas concentrations. All sensors and actuators are digitalized through connecting to a LabVIEW interface. The synthesis procedure of the catalyst, data collections, and thermal considerations for catalyst degradation are experimentally demonstrated by using a proportional-integral controller to gradually increase the reactor temperature without harming the catalyst.

Advanced control strategies, such as model predictive control (MPC), require a process model that can be optimized fast in real time. In [2], we developed a lumped-parameter modeling strategy for the electrically-heated SMR reactor that would replace the time and length dependent PDEs with dynamic ODEs using mass and energy balance equations. The objective is to control H₂ production rate by manipulating the current flowing through the reactor. In order to use this model in an MPC, feedback values for all state variables should be provided by the sensors. However, the GC gives discrete measurements, and it cannot quantify the steam flowrate since it is condensed before the GC. Moreover, the volumetric flowrate, a necessary parameter for the models, cannot be measured experimentally due to high temperatures. Due to missing parameters, the process model is incorporated into an extended Luenberger observer (ELO) to account for the absence of measurements and allow for real-time estimation of critical MPC-needed state variable measurements. The ELO-based MPC results are experimentally shown to be more efficient than sensor-feedback only proportional integral control with delayed measurements (due to the GC processing time) without a model.

References:

[1] Wismann, S. T., Engbæk, J. S., Vendelbo, S. B., Bendixen, F. B., Eriksen, W. L., Aasberg-Petersen, K., ... & Mortensen, P. M. (2019). Electrified methane reforming: A compact approach to greener industrial hydrogen production. Science, 364, 756-759.

[2] Çıtmacı, B., Cui, X., Abdullah, F., Richard, D., Peters, D., Wang, Y., Hsu, E., Chheda, P., Morales-Guio, C.G., Christofides, P. D., 2024. Model predictive control of an electrically-heated steam methane reformer. Digital Chemical Engineering, 10, 100138.