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Predictive-TOPSIS-based MPPT for PEMFC Featuring Switching Frequency Reduction

Indonesian Journal of Electical Engineering and Informatics (IJEEI) · Vol. 11 No. 3 (2023) · hlm. 656–672

DOI
10.52549/ijeei.v11i3.4350
ISSN
2089-3272, 2089-3272
Terbit
2023-08-19
Penerbit
IAES Indonesian Section
Bahasa
en

Abstrak

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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  • Chittagong University of Engineering & Technology
  • University of Malaya
  • University of Sciences and Technology Houari Boumediene
  • Renewable Energy Development Center
  • National Polytechnic School
  • American International University-Bangladesh
  • University Mohamed Boudiaf of M'sila
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Rekan penulisOrganisasiArtikel bersama
Noureddine BouarroudjRenewable Energy Development Center2
Boualam BenlahbibUniversity of Sciences and Technology Houari Boumediene2
Farid BouchafaaUniversity of Sciences and Technology Houari Boumediene1
Adil AtouiNational Polytechnic School1
Mostefa KermadiUniversity of Malaya1
Mohamed Seghir BoucheritNational Polytechnic School1
Khelifa BenmansourAfiliasi tidak diketahui1
Said BarkatUniversity Mohamed Boudiaf of M'sila1
Fethi AkelRenewable Energy Development Center1
Lilik Jamilatul AwalinUniversitas Airlangga1
Aditta ChowdhuryChittagong University of Engineering & Technology1
Monirul Islam MiskatChittagong University of Engineering & Technology1
Tofael AhmedChittagong University of Engineering & Technology1
Shameem AhmadAmerican International University-Bangladesh1
Md. Rifat HazariAmerican International University-Bangladesh1
Shanti Faridah SallehAfiliasi tidak diketahui1
Yonis.M.Yonis BuswigAfiliasi tidak diketahui1
Azuka AffamAfiliasi tidak diketahui1
Al-Khalid OthmanAfiliasi tidak diketahui1
Hazrul Mohamed BasriAfiliasi tidak diketahui1
Norhuzaimin JulaiAfiliasi tidak diketahui1
Thameur AbdelkrimAfiliasi tidak diketahui1
Abedeljalil DahbiAfiliasi tidak diketahui1
Bennaceur FaresAfiliasi tidak diketahui1
Abelkader LakhdariAfiliasi tidak diketahui1

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Sumber metadata: OAI-PMH (metadata jurnal) http://section.iaesonline.com/index.php/IJEEI/oai, pertama di-harvest 8 Nov 2026, terakhir terlihat 8 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en">Predictive-TOPSIS-based MPPT for PEMFC Featuring Switching Frequency Reduction</dc:title>
	<dc:creator xml:lang="en">Fam, Jye Yun</dc:creator>
	<dc:creator xml:lang="en">Wong, Shen Yuong</dc:creator>
	<dc:creator xml:lang="en">Abdullah, Mohammad Omar</dc:creator>
	<dc:creator xml:lang="en">Lias, Kasumawati</dc:creator>
	<dc:creator xml:lang="en">Mekhilef, Saad</dc:creator>
	<dc:creator xml:lang="en">Mohamed Basri, Hazrul</dc:creator>
	<dc:subject xml:lang="en">Fuel cells</dc:subject>
	<dc:subject xml:lang="en">Maximum power point tracker</dc:subject>
	<dc:subject xml:lang="en">Predictive control</dc:subject>
	<dc:subject xml:lang="en">Power electronics</dc:subject>
	<dc:subject xml:lang="en">TOPSIS</dc:subject>
	<dc:description xml:lang="en">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.</dc:description>
	<dc:publisher xml:lang="en">IAES Indonesian Section</dc:publisher>
	<dc:date>2023-08-19</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://section.iaesonline.com/index.php/IJEEI/article/view/4350</dc:identifier>
	<dc:identifier>10.52549/ijeei.v11i3.4350</dc:identifier>
	<dc:source xml:lang="en">Indonesian Journal of Electrical Engineering and Informatics (IJEEI); Vol. 11 No. 3: September 2023; 656-672</dc:source>
	<dc:source>2089-3272</dc:source>
	<dc:source>2089-3272</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://section.iaesonline.com/index.php/IJEEI/article/view/4350/852</dc:relation>
</oai_dc:dc>