Melola Discovery

← Melola Discovery

Open access Jurnal SINTA 1

Vehicle side control of a wireless power transfer charger using optimized artificial neural network

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 15 No. 2 (2025)

DOI
10.11591/ijece.v15i2.pp1487-1498
ISSN
2722-2578, 2088-8708
Published
2025-04-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

This paper investigates a new approach to control a wireless power transfer (WPT) charger for electric vehicles (EVs) employing an optimized artificial neural network (ANN). Enhancing the efficiency and robustness of such systems is crucial, and integrating artificial intelligence (AI)-based solutions has introduced innovative approaches in this field. The proposed method enables precise regulation of battery charging voltage even under challenging conditions, such as coil misalignment or shared grounding assemblies for multiple EVs. To assess the stability and robustness of the proposed controller, its performance was evaluated under scenarios of coil misalignment and shared grounding assemblies for EVs with varying battery voltages. The controller effectively eliminated overshoot and significantly reduced residual output voltage ripple by 4.33% compared to a conventional proportional-integral (PI) controller, demonstrating the superior performance and reliability of the ANN-based control approach.

Collaboration network of the authors

9 authors · 20 co-authorship links · 2 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Université Ibn-Tofail
  • Mohammed V University
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Abdelaziz KabbaUniversité Ibn-Tofail2
El Ayachi ChaterMohammed V University1
Halima HousnyUniversité Ibn-Tofail1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 1 Nov 2026.
Metadata as oai_dc, converted from Crossref
<oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/"><dc:title>Vehicle side control of a wireless power transfer charger using optimized artificial neural network</dc:title><dc:creator>Ancary, Marouane El</dc:creator><dc:creator>Lassioui, Abdellah</dc:creator><dc:creator>Fadil, Hassan El</dc:creator><dc:creator>Hasni, Anwar</dc:creator><dc:creator>Asri, Yassine El</dc:creator><dc:creator>Idrissi, Zakariae El</dc:creator><dc:description>&lt;jats:p&gt;This paper investigates a new approach to control a wireless power transfer (WPT) charger for electric vehicles (EVs) employing an optimized artificial neural network (ANN). Enhancing the efficiency and robustness of such systems is crucial, and integrating artificial intelligence (AI)-based solutions has introduced innovative approaches in this field. The proposed method enables precise regulation of battery charging voltage even under challenging conditions, such as coil misalignment or shared grounding assemblies for multiple EVs. To assess the stability and robustness of the proposed controller, its performance was evaluated under scenarios of coil misalignment and shared grounding assemblies for EVs with varying battery voltages. The controller effectively eliminated overshoot and significantly reduced residual output voltage ripple by 4.33% compared to a conventional proportional-integral (PI) controller, demonstrating the superior performance and reliability of the ANN-based control approach.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2025-04-01</dc:date><dc:type>info:eu-repo/semantics/article</dc:type><dc:format>application/pdf</dc:format><dc:identifier>https://doi.org/10.11591/ijece.v15i2.pp1487-1498</dc:identifier><dc:identifier>10.11591/ijece.v15i2.pp1487-1498</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 15 No 2 (2025); 1487</dc:source><dc:source>2722-2578</dc:source><dc:source>2088-8708</dc:source><dc:relation>https://ijece.iaescore.com/index.php/IJECE/article/viewFile/37224/18072</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>