ANN-Based Interleaved Synchronous Rectifier for Electric Vehicle Charging

Kavitha Kumari, K. S. and Chitra, L. and Boopathy, K. and Poornima, P. and Suresh Kumar, K. (2024) ANN-Based Interleaved Synchronous Rectifier for Electric Vehicle Charging. Springer, 1007. pp. 287-295. ISSN 2367-3370

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Abstract

Vehicles that run on electricity have the advantage of being non-polluting, which makes them an excellent alternative to fuel-powered vehicles. Numerous individuals are using EVs due to high demand and price of fuels. Normally, to charge these EV vehicles, electricity is essential. For employing in EVs and load systems, this work proposes an entirely novel, highly effective interleaved synchronous rectifier with isolation transformer. To enhance the charging performance, the suggested system includes synchronous rectification technique. The high-frequency (HF) full-bridge inverter and HF isolation transformer are the essential components of this EV charger. Isolated transformers are typically required by EV battery chargers to safely isolate the power grid from the battery system. The use of a pulse-width modulation (PWM) control circuit in design of a single-phase high-frequency inverter minimizes demand for expensive circuitry to produce sinusoidal pulses for transistor switches. Artificial neural networks (ANN) are utilized to control the output of proposed interleaved synchronous rectifier, achieving maximum output to the battery for EVs by reducing HF rectification losses with faster transition response and input noise rejection. The controller accomplishes nonlinear switching converter control and increases converter's durability. The MATLAB/Simulink environment is employed to analyze the performance of this approach.

Item Type: Article
Subjects:
Divisions: Engineering and Technology > Aarupadai Veedu Institute of Technology, Chennai > Electrical & Electronics Engineering
Depositing User: Unnamed user with email techsupport@mosys.org
Last Modified: 27 Nov 2025 06:45
URI: https://vmuir.mosys.org/id/eprint/1762

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