Prediction of Biomass Pyrolysis Mechanisms and Kinetics: Application of the Kalman Filter

In order to predict the pyrolysis mechanisms of four different biomasses (Asbos (Psilocaulon utile), Kraalbos (Galenia africane), Scholtzbos (Pteronia pallens), and palm shell), a novel method called Kalman filter was investigated and the results were compared by regression analysis. Both analyses were applied to five different generalized biomass pyrolysis models consisting of parallel and serial irreversible-reversible reaction steps. The models consisting of reversible reactions in addition to parallel pyrolysis steps demonstrated a better fit with the experimental results. The pyrolysis step from biomass to bio-oil has the highest reaction rates compared with the other pyrolysis steps defined in the models. The Kalman filter is thus defined as a promising filtering and prediction method for the estimation of detailed pyrolysis mechanisms and model parameters, using minimum experimental data.

Automated summary

A novel method called Kalman filter was investigated to predict the pyrolysis mechanisms of four different biomasses and compared with regression analysis. The models with reversible reactions in addition to parallel pyrolysis steps showed a better fit with the experimental results. The pyrolysis step from biomass to bio-oil exhibited the highest reaction rates compared to other defined pyrolysis steps in the models. Kalman filter is considered a promising method for estimating detailed pyrolysis mechanisms and model parameters with minimum experimental data.