Microbial Fuel Cells Performance Evaluation through the Application of Fuzzy Logic

Abstract

Objective: This work aimed to employ fuzzy logic combined with the design of experiments technique to statistically evaluate how the microbial fuel cells operating parameters influence their performance.   Theoretical Framework: Microbial fuel cells (MFC) are a technology of interest in the current scenario as they allow simultaneously promoting the biotreatment of waste and the bio generation of electrical energy.   Methodology: Through a bibliographical search based on publications on Google Scholar platform over the last 10 years, it was noticed that anode area, external electrical resistance and reactor volume are the most reported input parameters in MFC research and current density and power density are the output parameters most frequently portrayed in these studies, which is why these variables were selected for statistical investigation.   Results and Discussion: The results showed that, for both outputs studied, reactor volume and anode area showed a positive effect, while the external electrical resistance showed a negative effect. It was also possible to develop mathematical models that indicated the relationship between the input and output variables studied, with statistical significance for power density model (R2 = 86%).   Originality: Applying computational simulations and subsequent design of experiments to obtain results in accordance with those obtained experimentally in the laboratory.