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Optimal energy management of hybrid battery/supercapacitor storage system for electric vehicle application

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 14 No. 6 (2024)

DOI
10.11591/ijece.v14i6.pp6076-6085
ISSN
2722-2578, 2088-8708
Published
2024-12-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-sa/4.0

Abstract

A proposed approach for efficient energy management for lithium-ion battery and supercapacitor hybrid energy storage system is outlined in this study. The primary aim is to ensure the electric vehicle receives a stable and high-quality supply of electricity. The suggested management strategy focuses on maintaining the bus voltage at a consistent level while meeting the varying load demands with high-quality power across different scenarios. To achieve this, a management controller is employed, which utilizes a metaheuristics technique to define the parameters of the integral sliding mode control. The supercapacitor units are responsible for controlling the direct current (DC) bus, while the lithium-ion battery plays a role in balancing power distribution on the common line. This study evaluates the potential benefits of integrating salp swarm algorithm techniques into the controller's performance. The findings of the study suggest combining metaheuristic optimization methods with integral sliding mode control. Can lead to improvements in power quality. The proposed management algorithm not only efficiently allocates power resources but also safeguards them, ultimately ensuring a consistent and high-quality power supply for the electric vehicle.

Collaboration network of the authors

8 authors · 11 co-authorship links · 6 across different organisations

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

  • King Fahd University of Petroleum and Minerals
  • Prince Sattam Bin Abdulaziz University
  • Minia University
  • Higher Institute of Engineering
  • University of Sharjah
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Enas Taha SayedMinia University1
Sulaiman Z. AlmutairAffiliation unknown1
Yahia Bahaa HassanHigher Institute of Engineering1
Montaser MahmoudUniversity of Sharjah1

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 27 Okt 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>Optimal energy management of hybrid battery/supercapacitor storage system for electric vehicle application</dc:title><dc:creator>Rezk, Hegazy</dc:creator><dc:creator>Al-Dhaifallah, Mujahed</dc:creator><dc:creator>Amrr, Syed Muhammad</dc:creator><dc:creator>Alharbi, Abdullah</dc:creator><dc:description>&lt;jats:p&gt;A proposed approach for efficient energy management for lithium-ion battery and supercapacitor hybrid energy storage system is outlined in this study. The primary aim is to ensure the electric vehicle receives a stable and high-quality supply of electricity. The suggested management strategy focuses on maintaining the bus voltage at a consistent level while meeting the varying load demands with high-quality power across different scenarios. To achieve this, a management controller is employed, which utilizes a metaheuristics technique to define the parameters of the integral sliding mode control. The supercapacitor units are responsible for controlling the direct current (DC) bus, while the lithium-ion battery plays a role in balancing power distribution on the common line. This study evaluates the potential benefits of integrating salp swarm algorithm techniques into the controller's performance. The findings of the study suggest combining metaheuristic optimization methods with integral sliding mode control. Can lead to improvements in power quality. The proposed management algorithm not only efficiently allocates power resources but also safeguards them, ultimately ensuring a consistent and high-quality power supply for the electric vehicle.&lt;/jats:p&gt;</dc:description><dc:publisher>Institute of Advanced Engineering and Science</dc:publisher><dc:date>2024-12-01</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.v14i6.pp6076-6085</dc:identifier><dc:identifier>10.11591/ijece.v14i6.pp6076-6085</dc:identifier><dc:source>International Journal of Electrical and Computer Engineering (IJECE); Vol 14 No 6 (2024); 6076</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/36149/17760</dc:relation><dc:rights>http://creativecommons.org/licenses/by-sa/4.0</dc:rights></oai_dc:dc>