Modelling the energy harvesting from ceramic-based microbial fuel cells by using a fuzzy logic approach
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AuthorRamón Fernández, Alberto de; Salar García, María José; Ruiz Fernández, Daniel; Greenman, John; Ieropoulos, Ioannis
Knowledge AreaIngeniería Química
SponsorsM.J. Salar-García is supported by Fundación Séneca (Ref. 20372/PD/17). A. De Ramón-Fernández thanks the Ministry of Economy and Competitiveness the financial support for his thesis (Ref. BES-2015–073611). Parts of this work have been funded under the Bill & Melinda Gates Foundation, Grant No. OPP1149065 and the European Commission H2020 Programme, Grant No. 686585.
Bibliographic CitationRamón-Fernández, A. D., Salar-García, M. J., Ruiz-Fernández, D., Greenman, J. & Ieropoulos, I. Modelling the energy harvesting from ceramic-based microbial fuel cells by using a fuzzy logic approach. Applied Energy, 251, 113321 (2019).
KeywordsMicrobial fuel cells
Fuzzy inference system
Microbial fuel cells (MFCs) is a promising technology that is able to simultaneously produce bioenergy and treat wastewater. Their potential large-scale application is still limited by the need of optimising their power density. The aim of this study is to simulate the absolute power output by ceramic-based MFCs fed with human urine by using a fuzzy inference system in order to maximise the energy harvesting. For this purpose, membrane thickness, anode area and external resistance, were varied by running a 27-parameter combination in triplicate with a total number of 81 assays performed. Performance indices such as R2 and variance account for (VAF) were employed in order to compare the accuracy of the fuzzy inference system designed with that obtained by using nonlinear multivariable regression. R2 and VAF were calculated as 94.85% and 94.41% for the fuzzy inference system and 79.72% and 65.19% for the nonlinear multivariable regression model, respectively. As a result, these indices ...
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