Modeling of Must Fermentation Processes for Enabling CO2 Rate-Based Control

Models for must fermentation kinetics are investigated and used in simulations for enabling control strategies based on temperature adjustment during the alcoholic fermentation process using the estimated CO2 rate. An acoustic emission digital processing approach for estimating the CO2 rate in the must fermentation process is proposed and investigated. The hardware architecture was designed considering easy integration with other sensor networks, remote monitoring of the fermentation-related parameters, and wireless communication between the fermentation vessel and the processing unit. It includes a virtual CO2 rate sensor, having as input the audio signal collected by a microphone and as output the estimated CO2 rate. Digital signal processing performed on an embedded board involves acquisition, filtering, analysis, and feature extraction. Time domain-based methods for analyzing the audio signal were implemented. An experimental setup with a small fermentation vessel (100 L) was used for CO2 rate monitoring during the fermentation of grape must. The estimated CO2 rate data were fitted with the CO2 rate profiles generated by simulating the models under similar conditions. Simulations for controlling fermentation kinetics through a CO2 rate-based temperature control were performed and analyzed. The simulations indicate the proposed approach as valid for a closed-loop system implementation capable of controlling kinetics behavior using estimated CO2 rate and temperature control.