Buck converter-based transformer-less electric vehicle charger using artificial intelligent controller

The uni-directional power exchange between a charging station and an electric vehicle is important for grid-to-vehicle charging. While accomplishing the operation, various converters and controllers play an important role in transferring smooth power between the grid-to-vehicle. The paper discusses designing the model of a buck converter-based transformer-less charger that uses artificial intelligent controllers as well as confirms the power exchange between the grid and battery of the vehicle. The performance of a transformer-less grid-to-vehicle charger is designed using various electric vehicles based on consumer choice. The results demonstrate that the proposed charger delivers smooth power flow between charging stations to various types of vehicles with minimum voltage tracking error. The simulation tool MATLAB and SIMULINK estimates the settling time, tracking error, peak overshoot, smoothness of the controller, and accurate charger state-of-charge to prevent the battery from being overcharged.

• Record URL:
  • https://doi.org/10.1504/IJPT.2024.140132
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/17424267
• Supplemental Notes:
  • Copyright © 2024 Inderscience Enterprises Ltd.
• Authors:
  • Priyadarshini, Aayushi
  • Yadav, Shekhar
  • Tiwari, Nitesh
• Publication Date: 2024

Language

• English

Media Info

• Media Type: Web
• Pagination: pp 156-177
• Serial:
  • International Journal of Powertrains
  • Volume: 13
  • Issue Number: 2
  • Publisher: Inderscience Enterprises Limited
  • ISSN: 1742-4267
  • EISSN: 1742-4275
  • Serial URL: https://www.inderscience.com/jhome.php?jcode=ijpt

Subject/Index Terms

• TRT Terms: Artificial intelligence; Electric controllers; Electric vehicle charging; Electrical grids; Energy conversion; Energy transfer
• Subject Areas: Aviation; Data and Information Technology; Energy; Vehicles and Equipment;

Filing Info

• Accession Number: 01929380
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 30 2024 4:59PM