Practically Useful Models for Kinetics of Biodiesel Production
- Generalized models are developed for the kinetics of biodiesel production that incorporate both transesterification and saponification.
- Iterative parameter estimation algorithm enhances our chances of obtaining a global optimum along with identification of the most significant rate constants.
- Validated using 60 literature experiments for eight oils, two alcohols and two catalysts.
- Ensured that the predictions of the best performing model are reliable for oils that did not feature in the experiments employed for developing the models.
- Performed an extensive analysis to identify key factors and their interactions for ester yield and biodiesel quality.
We develop four kinetic models of varying complexity for biodiesel production. The models incorporate both transesterification and saponification, thereby making them practically applicable. We then propose an iterative parameter estimation algorithm to identify a prefixed number of significant rate constants via sensitivity analysis and estimate their kinetic parameters (A and ΔE) using nonlinear regression. Using experimental data on eight different oils, two alcohols, and two catalysts, we show that our models accurately predict the dynamic concentration profiles of various species during the transesterification of oil. Furthermore, we demonstrate the applicability of the best model (based on the values of Mean Absolute Error, Root Mean Square Error, and Akaike Information Criterion) for 11 additional experiments by predicting the final biodiesel properties with significant accuracy. Finally, using N-way ANOVA, we identify the choice of oil, alcohol, and catalyst as the most significant input factors followed by the operating conditions of the reactor.
- Access the article at the publisher: DOI: 10.1021/acssuschemeng.8b05636
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