Modeling of Must Fermentation Processes for Enabling CO 2 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 CO 2 rate. An acoustic emission digital processing approach for estimating the CO 2 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 CO 2 rate sensor, having as input the audio signal collected by a microphone and as output the estimated CO 2 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 CO 2 rate monitoring during the fermentation of grape must. The estimated CO 2 rate data were fitted with the CO 2 rate profiles generated by simulating the models under similar conditions. Simulations for controlling fermentation kinetics through a CO 2 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 CO 2 rate and temperature control.