Statistical study of the influence and significance of parameters operational effects on the performance of microbial energy cells
bioelectrochemistry; fuzzy logic; design of experiments
Microbial fuel cells (MFC) are a technology of interest in the current scenario, as they allow the simultaneous promotion of biotreatment of waste and biogeneration of electricity. In order to optimize the applications of this technology, there is an interest in investigating the variables that most significantly interfere in its performance, since these devices are complex systems. In this context, this paper aimed to employ fuzzy logic combined with design of experimets technique to statistically evaluate how MFC’s operational parameters impact their performance. As a result, it was concluded that the input variables anode area, external electrical resistance and device volume were statistically more significant for the studied outputs – power density and electrical voltage – in the searched conditions. Furthermore, statistically significant model equations were developed under the 95% confidence level that relate the input and output variables studied, helping to simplify the study of complex CEM systems.