ISSN No:2250-3676 ----- Crossref DOI Prefix: 10.64771 ----- Impact Factor: 9.625
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    Adaptive ANN-Based Control Framework For High-Performance Hybrid Electric Vehicle Charging

    Dr. K. Srinivas, M. Karunya

    Author

    ID: 3676

    DOI:

    Abstract :

    It May Take More Time Than Needed To Charge An Electric Vehicle (EV) Using The Onboard Type-1 And Type-2 AC Chargers Since Their Capabilities Are Often Lower, Ranging From 3.3 KW To 19 KW. The Construction And Maintenance Of Off-board High-power DC Fastcharging Stations Are Costly, But They Allow For Quick Charging. This Research Recommends A Hybrid AC-DC Charging Method To Get Over These Limitations And Charge EV Batteries Faster. This Vehicle Is Very Easy To Charge Because To Its Type-2 AC Charger And Built-in DC Charger. Making Ensuring Charging Happens Successfully Is As Simple As Following The Setup Instructions. One Way To Add A DC Input Port To An Electric Vehicle Is To Connect The Motor Windings Neutral Point To The Drivetrain Inverters Negative Rail. This Connection Makes It Possible To Directly Link To Various Renewable Energy Sources, Such As DC Microgrids, Rooftop Solar Panels, And Electric Vehicle Batteries. To Improve Power Conversion, The Electric Vehicles Drivetrain Inverter May Mimic An Integrated Interleaved DC-DC Converter By Using The Motor Windings As Filter Inductors. It Replaces The Conventional PI Controller With An ANN-based One To Increase Control Efficiency. In Various Operating Conditions, This Controller Regulates The DC-link Voltage And The Power Flow Between The AC And DC Charging Channels. The Whole System Is Tested And Assessed Using MATLAB/Simulink Under Different Charging Circumstances.

    Published:

    30-7-2026

    Issue:

    Vol. 26 No. 7 (2026)


    Page Nos:

    1282-1296


    Section:

    Articles

    License:

    This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

    How to Cite

    Dr. K. Srinivas, M. Karunya, Adaptive ANN-Based Control Framework for High-Performance Hybrid Electric Vehicle Charging , 2026, International Journal of Engineering Sciences and Advanced Technology, 26(7), Page 1282-1296, ISSN No: 2250-3676.

    DOI: