Evidence map›Paper›PMID 41402405›Full record

ArticleScientific reports2025

Integration of fast charging EV infrastructure with high gain Z-source converters and hybrid optimized MPPT algorithm.

R Sathish, V Sekar

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

R SathishDepartment of Electrical and Electronics Engineering, School of Engineering and Technology, Dhanalakshmi Srinivasan University, Samayapuram, Tiruchirappalli, 621112, India. rsathishme.13@gmail.com.
V SekarDean, School of Engineering and Technology, Dhanalakshmi Srinivasan University, Samayapuram, Tiruchirappalli, 621112, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electric Vehicles (EV) are considered as crucial elements in making changes towards power and transportation sector. Subsequently, the development fast charging infrastructure to support widespread adoption and efficient operation is required. To address the limitations, this research develops an EV fast charging system with the incorporation of a novel converter topology with optimization algorithms to improve power performance and effective management of energy. The voltage of Photovoltaic (PV) system is improved with the adoption of a high gain Z-source converter with switched topology resulting in improved system efficiency with lower switching stress. To improve the tracking performance of PV, the system uses hybrid Whale Optimization Algorithm (WOA) with Gray Relational Analysis (GRA) Maximum Power Point Tracking (MPPT) algorithm offering maximum performance irrespective of variation in environmental condition. In addition, the bidirectional converter with battery is incorporated supported by Proportional Integral (PI) controller for optimal charging and discharging. Moreover, to accomplish uninterrupted supply, grid is integrated via three phase Voltage Source Inverter (VSI). MATLAB simulation outcomes demonstrates that, the proposed converter together with hybrid MPPT provide effective charging, with increased efficiency of 96.85%, and tracking efficiency of 99.27% effectively, making the proposed system optimal for fast charging application.

Indexed as

Electric vehiclesGray relational analysisMATLABMPPT algorithmPV systemsWhale optimization algorithm

Identifiers

PMID41402405
PMCPMC12819433

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.