Predictive-TOPSIS based MPPT for PEMFC Featuring Switching Frequency Reduction
A maximum power point tracking (MPPT) for a proton exchange membrane fuel cell (PEMFC) using a combination of conventional finite control set model predictive control (FCS-MPC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is proposed in this paper. The key idea is t...
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Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
Institute of Advanced Engineering and Science (IAES), Indonesia Section
2023
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Subjects: | |
Online Access: | http://ir.unimas.my/id/eprint/42860/1/TOPSIS.pdf http://ir.unimas.my/id/eprint/42860/ http://section.iaesonline.com/index.php/IJEEI/article/view/4350 |
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Summary: | A maximum power point tracking (MPPT) for a proton exchange membrane fuel cell (PEMFC) using a combination of conventional finite control set model predictive control (FCS-MPC) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is proposed in this paper. The key idea is to maximize the power generation from a PEMFC while minimizing the switching frequency of the power converter. The FCS-MPC technique is formulated to track the maximum power of PEMFC highly affected by ever-changing internal parameters. Meanwhile, the TOPSIS algorithm is applied to overcome the potential weaknesses of insulated-gate bipolar transistor (IGBT), which can only withstand a lower switching frequency. In this project, all simulations were run using MATLAB software to display the output power of the PEMFC system. As a result, the proposed predictive-TOPSIS-based MPPT algorithm can track the MPP for various PEMFC parameters within 0.019 s with an excellent accuracy up to 99.11%. The proposed MPPT technique has fast-tracking of the MPP locus, excellent accuracy, and robustness to environmental changes. |
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