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This study presents an innovative method for charging electric vehicle batteries by integrating the digital model of a Wind Turbine (WT) driven by a Permanent Magnet Synchronous Generator (PMSG) with the digital model of a lithium (Li-ion) battery. The output power generated from WT is obtained by twinning with a PMSG, whereas the state-of-charge (SOC) and internal resistance (IR) of the battery are captured by twinning.A Dynamic Charging Current Selection Algorithm (DCCSA) is proposed to determine the required charging current for the lithium battery based on the generated output power of the WT, SOC, and IR of the battery. The DCCSA ensures that the charging current does not exceed the charging limits of the battery and power limits of the WT. This algorithm offers an adaptive and real-time solution for the efficient and using wind power for effectively charging the EV batteries. It does this by taking into account the changing characteristics of the WT and battery. MATLAB simulations showed the viability and efficacy of the suggested algorithm, yielding encouraging outcomes by using wind power for charging EV batteries.

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Dynamic Integration of Digital Twin Models for Wind Turbine and Lithium Battery in Electric Vehicle Battery Charging

  • 会议论文

  • 发表日期：

    2026年

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  • P. Sivakumar,
  • M. Arulmozhi,
  • S. Divya,
  • Javad Rahebi,
  • Kaavya Agith

摘要

This study presents an innovative method for charging electric vehicle batteries by integrating the digital model of a Wind Turbine (WT) driven by a Permanent Magnet Synchronous Generator (PMSG) with the digital model of a lithium (Li-ion) battery. The output power generated from WT is obtained by twinning with a PMSG, whereas the state-of-charge (SOC) and internal resistance (IR) of the battery are captured by twinning.A Dynamic Charging Current Selection Algorithm (DCCSA) is proposed to determine the required charging current for the lithium battery based on the generated output power of the WT, SOC, and IR of the battery. The DCCSA ensures that the charging current does not exceed the charging limits of the battery and power limits of the WT. This algorithm offers an adaptive and real-time solution for the efficient and using wind power for effectively charging the EV batteries. It does this by taking into account the changing characteristics of the WT and battery. MATLAB simulations showed the viability and efficacy of the suggested algorithm, yielding encouraging outcomes by using wind power for charging EV batteries.