Evidence map›Paper›PMID 39511308›Full record

ArticleScientific reports2024

A fuzzy-predictive current control with real-time hardware for PEM fuel cell systems.

Badreddine Kanouni, Abd Essalam Badoud, Saad Mekhilef, Ahmed Elsanabary, Mohit Bajaj, Ievgen Zaitsev

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Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Badreddine KanouniSetif Automatic Laboratory, Electrical Engineering Department, Ferhat Abbas University, Setif 1, Setif, Algeria.
Abd Essalam BadoudSetif Automatic Laboratory, Electrical Engineering Department, Ferhat Abbas University, Setif 1, Setif, Algeria. badoudabde@univ-setif.dz.
Saad MekhilefSchool of Software and Electrical Engineering, Swinburne University of Technology, Melbourne, Australia.
Ahmed ElsanabaryInstitute of Power Engineering (IPE), Universiti Tenaga Nasional, Kajang, Selangor, Malaysia.
Mohit BajajDepartment of Electrical Engineering, Graphic Era (Deemed to Be University), Dehradun, 248002, India. mohitbajaj.ee@geu.ac.in.
Ievgen ZaitsevDepartment of Theoretical Electrical Engineering and Diagnostics of Electrical Equipment, Institute of Electrodynamics, National Academy of Sciences of Ukraine, Beresteyskiy, 56, Kyiv-57, Kyiv, 03680, Ukraine. zaitsev@i.ua.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This research study presents the application of the FC-PCC (Fuzzy Logic Predictive Current Control) algorithm in the context of maximum power point tracking (MPPT) for a proton exchange membrane fuel cell system employing a three-level boost converter (TLBC). The proposed approach involves the integration of an intelligent fuzzy controller with a predictive current control strategy in order to improve the performance of MPP tracking. Initially, the utilization of fuzzy logic involves the utilization of data values obtained from the PEMFC. The maximum point (P-I) of the PEMFC polarization curve is determined, followed by the selection of the reference current. A predictive current control technique employs the reference current to ensure the voltage balance of the output capacitor in the three-level converter. The hardware-in-the-loop system utilizes a real-time and high-speed simulator, specifically the PLECS RT Box 1, to obtain the findings. The computational cost of the overall system is rather low, making it feasible to construct using PLECS RT Box 1. The new MPPT algorithm quickly finds the maximum power point (MPP) and balances the voltage of capacitors in a number of different proton exchange membrane fuel cells. The suggested MPPT technique has been verified to demonstrate rapid tracking of the maximum power point (MPP) location, as well as precise balancing of capacitor voltage and robustness to environmental variations. This approach was tested and found to outperform conventional MPPT methods like Perturb and Observe (P&O) and Incremental Conductance (IC) in terms of tracking duration, precision, and voltage balancing, achieving a 15% reduction in tracking duration, a 5% deviation from the MPP value for voltage, and superior stability under changing temperature and pressure.

Indexed as

Fuzzy logicMPPTPEMFCPredictive current controlThree-level boost converter

Identifiers

PMID39511308
PMCPMC11544151

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.