WIRELESS CHARGING OF ELECTRIC VEHICLE WITH PROPER SELECTED COIL PARAMETERS AND CONTROLLED CONVERTERS USING ARTIFICIAL NEURAL NETWORK FOR THE IMPROVISED PERFORMANCE PARAMETERS

Abstract

In the developing countries like India, the foremost challenge in the adoption of Electrical Vehicles (EVs) is availability of charging infrastructure. To overcome these limitations wireless charging system has been developed. Further, dynamic wireless charging systems enables EVs to charge while being in motion. This reduces the delay time for consequent users in queue to power their EVs. A generic model of wireless charging system comprises an inverter, a compensation network, coils, and a rectifier. In this research work an attempt has been made to improve the power transfer efficiency of the Inductor-Capacitor-Capacitor (LCC) compensation technique. Here in this research work, Artificial Neural Network (ANN) are combined with the conventional LCC and the integrated model is named as ANN method. ANN is integrated into the inverter and rectifier to further optimize the coil parameters and thus improves the rate of power transfer. The ANN dynamic wireless charging method developed in this research work has significantly proved to be a better alternative to generic wireless charging methods as it increases power transfer efficiency by maintaining an optimal coil distance during charging.