CHARGING SLOT PREDICTION AND AUTOMATION SYSTEM FOR ELECTRIC VEHICLE CHARGING STATION

CHARGING SLOT PREDICTION AND AUTOMATION SYSTEM FOR ELECTRIC VEHICLE CHARGING STATION

KARTHIK.B, SHANMUGASUNDARAM.S, VIJAYASARATHY.R, A. BASKAR

Department of Computer Science and Engineering
E.G.S Pillay Engineering College

Nagapattinam, India

Abstract— Electric vehicle charging stations (EVCS) play a vital role in providing charging support to EV users. The rapid adoption of electric vehicles (EVs) stimulates the proliferation of charging stations (CSs), motivating the cooperative management of growing CSs. However, cooperative CS management still remains an open problem, due to the uncertain user behaviors and heterogeneous service capabilities. To capture the CS dynamics caused by uncertain user behaviors, we propose a deep reinforcement learning (DRL)-based cooperative method for multiple CSs, towards maximizing the total profit. Developed the Framework and Architecture of the Next-Generation Communication System based on Web Dashboard based EVCS Slot Prediction and Online EVs Charging Slot Booking at Charging Station. We built the stochastic queuing model for EVs in the charging station. We formulated the objective function of EV’s charging at charging points in charging stations to determine the optimal charging time, minimal charging cost, least distance, minimal queuing delay and optimal duration for particular charging slots. The proposed model of the slot prediction and booking system is designed to create a cost effective and efficient system. Our Cloud based Charging Station Management platform is developed to network and manage multiple charging stations. The proposed IoT and server-based real-time forecast charging infrastructure avoids waiting times and its scheduling management efficiently prevents the EV from halting on the road due to battery drain out.

Keywords: Electric vehicles (EVs), Electric vehicle charging stations (EVCS), Deep reinforcement learning (DRL), Cloud based charging station management platform.