Run‐to‐Run Optimization of Fed‐Batch Fermentation for Ethanol Production

Abstract

A two-stage design approach is introduced to determine the optimal feed rate, fed glucose concentration and fermentation time to maximize ethanol productivity by using Saccharomyces diastaticus LORRE 316. The first stage is applied to determine a kinetic model using batch time-series data. Two runs were carried out in the second stage to achieve the maximum ethanol production rate for the fedbatch fermentation process. The computational results from the kinetic model using batch and fed-batch time-series data are in better agreement with the fedbatch experiments than those from the kinetic model using batch time-series data. For cross-validation, an extra fed-batch experiment with constant feed rate was carried out for comparison with the optimal fed-batch result. According to the experimental results, this optimal approach was able to improve productivity by at least 12.56 % compared with that using the constant feed rate.

Optimization of Fed-Batch Fermentation with in Situ Ethanol Removal by CO2 Stripping

“…The literature reports studies that have used optimization tools to define the substrate feed rate profile that maximizes the final amount of ethanol during conventional fed-batch ethanol fermentation. − However, no reports were found concerning the optimization of fed-batch fermentation with ethanol removal by CO 2 stripping.…”

Optimization of Bioethanol Ethanol Production in Fed-batch Fermentation

“…Huang, et al (Huang, et al, 2010) has applied Monod type kinetic model to maximize ethanol production using Saccharomyces diastaticus LORRE 316. In order to compare their results with our, the same model from Huang and coworkers' paper was selected with ethanol and acetic acid as considered products.…”

“…Results of experiment are shown in Figure 1. Values of parameters were estimated with the same procedure in Huang's (Huang, et al, 2010). The estimated parameters are listed as Model I.…”

“…To optimize the productivity of ethanol, the modeling of fermentation process becomes an essential task. Traditionally, empirical methods based on Monod equations (Huang, Shieh, & Wang, 2010;Mekarapiruk & Luus, 2000) have been adopted for the optimization of these processes. The major problem is that the model requires significant amount of data to determine the parameters (Roeva et al, 2007).…”