Scholarlink

This paper introduces an adaptive control strategy for a three-phase Dual Active Bridge (DAB) converter, designed to facilitate efficient bidirectional power flow in electric vehicle (EV) fast-charging stations. The proposed control method effectively manages real-time fluctuations in grid conditions and the state-of-charge (SOC) of batteries, ensuring stable operation in both Vehicle-to-Grid (V2G) and Grid-to-Vehicle (G2V) modes. Utilizing a dq-reference frame-based decoupled controller with SOC feedback, the solution is rigorously validated through MATLAB/Simulink simulations. The design encompasses LCL filter modeling, DAB phase shift modulation, and battery interfacing under diverse loading scenarios. Simulation results reveal significant improvements in performance, highlighting the system’s ability to maintain high efficiency during both charging and discharging phases. By enhancing the responsiveness and stability of power exchange between EVs and the grid, this research aims to contribute to the development of advanced fast-charging infrastructure capable of supporting increasing EV adoption while optimizing overall electric grid performance. The findings underscore the potential of adaptive control strategies in ensuring reliable and efficient energy management within smart grid environments.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Adaptive Control Strategy for Seamless Bidirectional Power Flow in Three-Phase Dual Active Bridge Converters for EV Fast Charging Applications

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • S. Manasa,
  • Rupam Bhaduri,
  • Pramod Kumar Naik,
  • T. G. Gangadhar,
  • S. Bharath Kumar

摘要

This paper introduces an adaptive control strategy for a three-phase Dual Active Bridge (DAB) converter, designed to facilitate efficient bidirectional power flow in electric vehicle (EV) fast-charging stations. The proposed control method effectively manages real-time fluctuations in grid conditions and the state-of-charge (SOC) of batteries, ensuring stable operation in both Vehicle-to-Grid (V2G) and Grid-to-Vehicle (G2V) modes. Utilizing a dq-reference frame-based decoupled controller with SOC feedback, the solution is rigorously validated through MATLAB/Simulink simulations. The design encompasses LCL filter modeling, DAB phase shift modulation, and battery interfacing under diverse loading scenarios. Simulation results reveal significant improvements in performance, highlighting the system’s ability to maintain high efficiency during both charging and discharging phases. By enhancing the responsiveness and stability of power exchange between EVs and the grid, this research aims to contribute to the development of advanced fast-charging infrastructure capable of supporting increasing EV adoption while optimizing overall electric grid performance. The findings underscore the potential of adaptive control strategies in ensuring reliable and efficient energy management within smart grid environments.