Maximization of Power Density of Direct Methanol Fuel Cell for Greener Energy Generation Using Beetle Antennae Search Algorithm and Fuzzy Modeling
Direct methanol fuel cells (DMFCs) are promising form of energy conversion technology that have the potential to take the role of lithium-ion batteries in portable electronics and electric cars. To increase the efficiency of DMFCs, many operating conditions ought to be optimized. Developing a reliab...
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| Format: | Article |
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MDPI AG
2023-11-01
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| Series: | Biomimetics |
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| Online Access: | https://www.mdpi.com/2313-7673/8/7/557 |
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| author | Ahmed Al Shouny Hegazy Rezk Enas Taha Sayed Mohammad Ali Abdelkareem Usama Hamed Issa Yehia Miky Abdul Ghani Olabi |
| author_facet | Ahmed Al Shouny Hegazy Rezk Enas Taha Sayed Mohammad Ali Abdelkareem Usama Hamed Issa Yehia Miky Abdul Ghani Olabi |
| author_sort | Ahmed Al Shouny |
| collection | DOAJ |
| description | Direct methanol fuel cells (DMFCs) are promising form of energy conversion technology that have the potential to take the role of lithium-ion batteries in portable electronics and electric cars. To increase the efficiency of DMFCs, many operating conditions ought to be optimized. Developing a reliable fuzzy model to simulate DMFCs is a major objective. To increase the power output of a DMFC, three process variables are considered: temperature, methanol concentration, and oxygen flow rate. First, a fuzzy model of the DMFC was developed using experimental data. The best operational circumstances to increase power density were then determined using the beetle antennae search (BAS) method. The RMSE values for the fuzzy DMFC model are 0.1982 and 1.5460 for the training and testing data. For training and testing, the coefficient of determination (R<sup>2</sup>) values were 0.9977 and 0.89, respectively. Thanks to fuzzy logic, the RMSE was reduced by 88% compared to ANOVA. It decreased from 7.29 (using ANOVA) to 0.8628 (using fuzzy). The fuzzy model’s low RMSE and high R<sup>2</sup> values show that the modeling phase was successful. In comparison with the measured data and RSM, the combination of fuzzy modeling and the BAS algorithm increased the power density of the DMFC by 8.88% and 7.5%, respectively, and 75 °C, 1.2 M, and 400 mL/min were the ideal values for temperature, methanol concentration, and oxygen flow rate, respectively. |
| first_indexed | 2024-03-09T16:59:12Z |
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| id | doaj.art-06ecf4c1b6b44e6bb55d6896831f326f |
| institution | Directory Open Access Journal |
| issn | 2313-7673 |
| language | English |
| last_indexed | 2024-03-09T16:59:12Z |
| publishDate | 2023-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Biomimetics |
| spelling | doaj.art-06ecf4c1b6b44e6bb55d6896831f326f2023-11-24T14:31:44ZengMDPI AGBiomimetics2313-76732023-11-018755710.3390/biomimetics8070557Maximization of Power Density of Direct Methanol Fuel Cell for Greener Energy Generation Using Beetle Antennae Search Algorithm and Fuzzy ModelingAhmed Al Shouny0Hegazy Rezk1Enas Taha Sayed2Mohammad Ali Abdelkareem3Usama Hamed Issa4Yehia Miky5Abdul Ghani Olabi6Department of Geomatics, Faculty of Architecture and Planning, King Abdulaziz University, Jeddah 21589, Saudi ArabiaDepartment of Electrical Engineering, College of Engineering in Wadi Alddawasir, Prince Sattam bin Abdulaziz University, Al-Kharj 11942, Saudi ArabiaDepartment of Chemical Engineering, Faculty of Engineering, Minia University, Minya 61111, EgyptDepartment of Sustainable and Renewable Energy Engineering, University of Sharjah, Sharjah P.O. Box 27272, United Arab EmiratesDepartment of Civil Engineering, Faculty of Engineering, Minia University, Minya 61519, EgyptDepartment of Geomatics, Faculty of Architecture and Planning, King Abdulaziz University, Jeddah 21589, Saudi ArabiaDepartment of Sustainable and Renewable Energy Engineering, University of Sharjah, Sharjah P.O. Box 27272, United Arab EmiratesDirect methanol fuel cells (DMFCs) are promising form of energy conversion technology that have the potential to take the role of lithium-ion batteries in portable electronics and electric cars. To increase the efficiency of DMFCs, many operating conditions ought to be optimized. Developing a reliable fuzzy model to simulate DMFCs is a major objective. To increase the power output of a DMFC, three process variables are considered: temperature, methanol concentration, and oxygen flow rate. First, a fuzzy model of the DMFC was developed using experimental data. The best operational circumstances to increase power density were then determined using the beetle antennae search (BAS) method. The RMSE values for the fuzzy DMFC model are 0.1982 and 1.5460 for the training and testing data. For training and testing, the coefficient of determination (R<sup>2</sup>) values were 0.9977 and 0.89, respectively. Thanks to fuzzy logic, the RMSE was reduced by 88% compared to ANOVA. It decreased from 7.29 (using ANOVA) to 0.8628 (using fuzzy). The fuzzy model’s low RMSE and high R<sup>2</sup> values show that the modeling phase was successful. In comparison with the measured data and RSM, the combination of fuzzy modeling and the BAS algorithm increased the power density of the DMFC by 8.88% and 7.5%, respectively, and 75 °C, 1.2 M, and 400 mL/min were the ideal values for temperature, methanol concentration, and oxygen flow rate, respectively.https://www.mdpi.com/2313-7673/8/7/557direct methanol fuel cellbeetle antennae search algorithmfuzzy modelingoptimization |
| spellingShingle | Ahmed Al Shouny Hegazy Rezk Enas Taha Sayed Mohammad Ali Abdelkareem Usama Hamed Issa Yehia Miky Abdul Ghani Olabi Maximization of Power Density of Direct Methanol Fuel Cell for Greener Energy Generation Using Beetle Antennae Search Algorithm and Fuzzy Modeling Biomimetics direct methanol fuel cell beetle antennae search algorithm fuzzy modeling optimization |
| title | Maximization of Power Density of Direct Methanol Fuel Cell for Greener Energy Generation Using Beetle Antennae Search Algorithm and Fuzzy Modeling |
| title_full | Maximization of Power Density of Direct Methanol Fuel Cell for Greener Energy Generation Using Beetle Antennae Search Algorithm and Fuzzy Modeling |
| title_fullStr | Maximization of Power Density of Direct Methanol Fuel Cell for Greener Energy Generation Using Beetle Antennae Search Algorithm and Fuzzy Modeling |
| title_full_unstemmed | Maximization of Power Density of Direct Methanol Fuel Cell for Greener Energy Generation Using Beetle Antennae Search Algorithm and Fuzzy Modeling |
| title_short | Maximization of Power Density of Direct Methanol Fuel Cell for Greener Energy Generation Using Beetle Antennae Search Algorithm and Fuzzy Modeling |
| title_sort | maximization of power density of direct methanol fuel cell for greener energy generation using beetle antennae search algorithm and fuzzy modeling |
| topic | direct methanol fuel cell beetle antennae search algorithm fuzzy modeling optimization |
| url | https://www.mdpi.com/2313-7673/8/7/557 |
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