Pv Supplied Sl-Sc based High Voltage Gain Artificial Neural Networks Controlled Boost Converter for Hv Ev Charging System

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Dr. Amira Nisar , Dr. Khwaja M Rafi, Shayam Mohan Parashar

Abstract

The fast-expanding electric vehicle market requires efficient high-voltage charging methods. The documentation introduces a new PV-based switched inductor-switched capacitor (SL-SC) high voltage gain boost converter that addresses high-voltage EV charging requirements. The proposed converter design offers high voltage gain performance together with increased efficiency and diminished stress on its components. Recursive circuit analysis includes modeling of the circuit design alongside operational principle research and performance assessment. The simulation together with experimental studies prove that the proposed circuit design outperforms traditional boost converters concerning operational effectiveness. Efficient power converters that provide maximum voltage gain and intelligent control designs must be established because high-voltage electric vehicle (EV) charging systems need more effective solutions. This research explores the implementation of a high voltage gain boost converter with PV-supplied SL-SC topology which utilizes ANN control for high-voltage EV charging systems. SL-SC networks integrated through the proposed topology produce both high voltage conversion ratios and minimal semiconductor component stress that improves system performance and efficiency. The controller based on ANN optimizes the converter operation across different solar irradiation and load ranges by providing rapid system responses alongside improved voltage regulation. The proposed system proves better than conventional boost and coupled inductor-based converters through comparative analysis of voltage gain along with efficiency and transient response performance. Testing results together with simulation data support that this proposed structure represents an effective solution for future high-voltage systems which enable EV charging sustainability.

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