Neural Network Based On Board Electric Vehicle Charger for Solar Powered Six Phase PMSM Drive
Abstract
In this article, the proposed novel neural network is designed for a board electric vehicle charger for a solar-powered six-phase permanent magnet synchronous motor (PMSM) drive. The neural network is intended to optimize the charging process of the electric vehicle by controlling the amount of power received from the solar panel, and it utilizes the unique six-phase architecture of the PMSM drive to ensure maximum efficiency. The network incorporates advanced machine learning algorithms to constantly adapt and optimize the charging process based on various environmental and operational factors. By leveraging the power of neural networks, the proposed board charger provides an innovative and efficient solution for sustainable electric vehicle charging. Both charging and simultaneous driving and charging modes and their working are shown
Keywords
Neural network based on-board charger, simultaneous driving and charging, six- phase machine, solar-powered electric vehicle (EV), vehicle-roof photovoltaic panels (PPS), Neural network (NN)