Intelligent EV Charging Slot Allocation Using Scheduling Algorithms: Design, Implementation and Comparative Analysis

Electric vehicles (EVs) are rapidly replacing their conventional fuel-powered modes as a cleaner alternative of transportation, but this has brought immense pressure on the charging infrastructure. Most of the charging stations utilize a simple First-Come-First-Served (FCFS) system where the vehicles are charged in the order of their arrival at the station. This approach does not consider several important factors, like how much time will be taken, how much the vehicle needs to charge and the overall utility of the charging station, leading to congested queues and under-utilized slots. This paper presents the design of an EV charging slot allocation system where the charging slot allocation problem is modeled as a scheduling problem. Three scheduling strategies are implemented and compared: FCFS as the baseline, Shortest Job First (SJF) which prioritizes vehicles with the least amount of charge required and a proposed prioritization algorithm that balances between waiting time and need for charge. The system has been implemented as a web application with a backend scheduling engine, where a vehicle owner may request a slot and get one based on the algorithm in use. The three algorithms were compared to simulated charging request data using average waiting time, slot utilization and fairness as the evaluation metrics. The results demonstrate the trade-off between simplicity and performance: while FCFS is easy to implement, it performs poorly in terms of average waiting time in high-load scenarios, SJF decreases average waiting time but can lead to long wait times for vehicles needing a full charge and the proposed algorithm offers a middle-ground prioritization approach. The overall purpose of this paper is to present a practical and extensible system that can facilitate smarter EV charging stations.