Fuzzy modeling and parameters optimization for the enhancement of biodiesel production from waste frying oil over montmorillonite clay K-30

Abstract

Transesterification is a promising technology for the biodiesel production to provide an alternative fuel that considers the environmental concerns. From the economic and environmental protection points of view, utilization of waste frying oil for the production of biodiesel addresses very beneficial impacts. Production of higher yield of biodiesel is a challenging process in order to commercialize it with a lower cost. The current study focuses on the influence of different parameters such as reaction temperature (°C), reaction period (min), oil to methanol ratio and amount of catalyst (wt%) on the production of biodiesel. The main objective of this work is to develop a model via fuzzy logic approach in order to maximize the biodiesel produced from waste frying oil using montmorillonite Clay K-30 as a catalyst. The optimization for the operating parameters has been performed via particle swarm optimization (PSO) approach. During the optimization process, the decision variables were represented by four different operating parameters: temperature (40–140 °C), reaction period (60–300 min), oil/methanol ratio (1:6–1:18) and amount of catalyst (1–5 wt%). The model has been validated with the experimental data and compared with the optimal results reported based on other optimization techniques. Results showed the increment of biodiesel production by 15% using the proposed strategy compared to the earlier study. The obtained biodiesel production yield reached 93.70% with the optimal parameters for a temperature at 69.66 °C, a reaction period of 300 min, oil/methanol ratio of 1:9 and an amount of catalyst of 5 wt%.