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Modeling Anaerobic Co-Digestion of Corn Stover Hydrochar and Food Waste for Sustainable Biogas Production
| Title: | Modeling Anaerobic Co-Digestion of Corn Stover Hydrochar and Food Waste for Sustainable Biogas Production |
| Authors: | Mohammed, Ibrahim Shaba Browse this author | | Na, Risu Browse this author | | Shimizu, Naoto Browse this author →KAKEN DB |
| Keywords: | adaptive identifier | | anaerobic digestion | | hydrothermal carbonization | | state-space model | | control signal | | biorefinery system |
| Issue Date: | 3-Mar-2022 |
| Publisher: | MDPI |
| Journal Title: | Fermentation |
| Volume: | 8 |
| Issue: | 3 |
| Start Page: | 110 |
| Publisher DOI: | 10.3390/fermentation8030110 |
| Abstract: | Despite the importance of the biodegradability of lignocellulose biomass, few studies have evaluated the lignocellulose biomass digestion kinetics and modeling of the process. Anaerobic digestion (AD) is a mature energy production technique in which lignocellulose biomass is converted into biogas. However, using different organic waste fractions in AD plants is challenging. In this study, lignocellulose biomass (corn stover hydrochar) obtained from hydrothermal carbonization at a temperature, residential time, and biomass/water ratio of 215 degrees C, 45 min, and 0.115, respectively, was added to the bioreactor as a substrate inoculated with food waste and cow dung to generate biogas. A state-space AD model containing one algebraic equation and two differential equations was constructed. All the parameters used in the model were dependent on the AD process conditions. An adaptive identifier system was developed to automatically estimate parameter values from input and output data. This made it possible to operate the system under different conditions. Daily cumulative biogas production was predicted using the model, and goodness-of-fit analysis indicated that the predicted biogas production values had accuracies of >90% during both model construction and validation. Future work will focus on the application of modeling predictive control into an AD system that would comprise both models and parameters estimation. |
| Type: | article |
| URI: | http://hdl.handle.net/2115/85150 |
| Appears in Collections: | 北方生物圏フィールド科学センター (Field Science Center for Northern Biosphere) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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