Estimation of biogas composition in a catalytic reactor via an extended Kalman filter

Catalytic reforming of biogas for use in a solid oxide fuel cell is a promising method of stationary fuel cell power generation. Potential challenges include the variable composition of input biogas and the resulting effects on the lifetime of the catalytic reactor. Environmental factors cause variability in the produced biogas stream which requires either expensive post processing of the biogas or operation of the reactor at a less efficient operating point. State estimation can be combined with a low-order model of the catalytic reactor to estimate the unknown composition of the biogas. The model used is a continually stirred reactor combined with surface chemistry. This model utilizes a predetermined reaction mechanism for hydrocarbons over a rhodium catalyst. The model reduces to a differential algebraic equation system with order one. An extended Kalman filter is used to estimate the unknown composition of the biogas. Results are presented based on both experimental and model based data.