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Modelling the energy harvesting from ceramic-based microbial fuel cells by using a fuzzy logic approach

Modelling the energy harvesting from ceramic-based microbial fuel cells by using a fuzzy logic approach
Modelling the energy harvesting from ceramic-based microbial fuel cells by using a fuzzy logic approach
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 revealed that the prediction of the absolute power output by ceramic-based MFCs of the fuzzy-based systems is more reliable than the nonlinear multivariable regression approach. The analysis of the response surface obtained by the fuzzy inference system determines that the maximum absolute power output by the air-breathing set-up studied is 450 W when the anode area ranged from 160 to 200 cm2, the external loading is approximately 900 and a membrane thickness of 1.6 mm, taking into account that the results also confirm that the latter parameter does not show a significant effect on the power output in the range of values studied.
Microbial fuel cells, Ceramic membranes, Fuzzy inference system, Bioenergy, Modelling
0306-2619
de Ramon-Fernandez, Alberto
7b8eb9a4-728b-419b-b3ed-7a2ef4b43620
Salar-Garcia, M. J.
1a342bfd-1231-4c7e-90f3-3f50788e2d17
Ruiz-Fernandez, Daniel
286d7da2-ac21-4b44-bb3d-9e5b8ff6b6f6
Greenman, J.
eb3d9b82-7cac-4442-9301-f34884ae4a16
Ieropoulos, I.
6c580270-3e08-430a-9f49-7fbe869daf13
de Ramon-Fernandez, Alberto
7b8eb9a4-728b-419b-b3ed-7a2ef4b43620
Salar-Garcia, M. J.
1a342bfd-1231-4c7e-90f3-3f50788e2d17
Ruiz-Fernandez, Daniel
286d7da2-ac21-4b44-bb3d-9e5b8ff6b6f6
Greenman, J.
eb3d9b82-7cac-4442-9301-f34884ae4a16
Ieropoulos, I.
6c580270-3e08-430a-9f49-7fbe869daf13

de Ramon-Fernandez, Alberto, Salar-Garcia, M. J., Ruiz-Fernandez, Daniel, Greenman, J. and Ieropoulos, I. (2019) Modelling the energy harvesting from ceramic-based microbial fuel cells by using a fuzzy logic approach. Applied Energy, 251, [113321]. (doi:10.1016/j.apenergy.2019.113321).

Record type: Article

Abstract

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 revealed that the prediction of the absolute power output by ceramic-based MFCs of the fuzzy-based systems is more reliable than the nonlinear multivariable regression approach. The analysis of the response surface obtained by the fuzzy inference system determines that the maximum absolute power output by the air-breathing set-up studied is 450 W when the anode area ranged from 160 to 200 cm2, the external loading is approximately 900 and a membrane thickness of 1.6 mm, taking into account that the results also confirm that the latter parameter does not show a significant effect on the power output in the range of values studied.

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Published date: 1 October 2019
Keywords: Microbial fuel cells, Ceramic membranes, Fuzzy inference system, Bioenergy, Modelling

Identifiers

Local EPrints ID: 456248
URI: http://eprints.soton.ac.uk/id/eprint/456248
ISSN: 0306-2619
PURE UUID: 0b9284de-555a-4bd0-a83e-967e4c3b198a
ORCID for I. Ieropoulos: ORCID iD orcid.org/0000-0002-9641-5504

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Date deposited: 26 Apr 2022 22:02
Last modified: 17 Mar 2024 04:10

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Contributors

Author: Alberto de Ramon-Fernandez
Author: M. J. Salar-Garcia
Author: Daniel Ruiz-Fernandez
Author: J. Greenman
Author: I. Ieropoulos ORCID iD

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