Data-driven modelling of bioethanol fuel production from rambutan fruit waste

Abstract

Owing to lack of confidence on potential yield and subsequent net benefit, wide-scale implementations of bioethanol from food/fruit waste are not gaining momentum. With the aim of enhancing stakeholders’ confidence, this paper presents a simple mathematical model formulation, which can estimate potential bioethanol generation capacity from rambutan waste under different input conditions. The mathematical formulation was derived based on three contributing factors: pH, temperature and fermentation period. The factors were derived based on an earlier experimental study on production of bioethanol from rambutan waste. The results from the derived mathematical model were compared with the experimental measurements from earlier studies. It is found that the proposed model is capable of accurately estimating potential bioethanol production from rambutan waste. The model calculated results have a coefficient of correlation of 0.98 with the measured data. Standard errors of the model's estimations are also quite low, having root mean-squared error = 0.17, mean absolute error = 0.14 and relative absolute error = 0.02. For a wider industrial generation, a mathematical framework is proposed to calculate the cost–benefit ratio of production costs against yield value considering the time value of the money. Such a mathematical framework will assist decision makers on deciding optimum input parameters through optimised energy consumption.