A Reinforcement Learning-based Assignment Scheme for EVs to Charging Stations

Mohammad Aljaidi, Nauman Aslam, Xiaomin Chen, Omprakash Kaiwartya, Yousef Ali Al-Gumaei, Muhammad Khalid

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    7 Citations (Scopus)


    Due to recent developments in electric mobility, public charging infrastructure will be essential for modern transportation systems. As the number of electric vehicles (EVs) increases, the public charging infrastructure needs to adopt efficient charging practices. A key challenge is the assignment of EVs to charging stations (CSs) in an energy efficient manner. In this paper, a Reinforcement Learning (RL)-based EV Assignment Scheme (RL-EVAS) is proposed to solve the problem of assigning EV to the optimal CS in urban environments, aiming at minimizing the total cost of charging EVs and reducing the overload on Electrical Grids (EGs). Travelling cost that is resulted from the movement of EV to CS, and the charging cost at CS are considered. Moreover, the EV's Battery State of Charge (SoC) is taken into account in the proposed scheme. The proposed RL-EVAS approach will approximate the solution by finding an optimal policy function in the sense of maximizing the expected value of the total reward over all successive steps using Q-learning algorithm, based on the Temporal Difference (TD) learning and Bellman expectation equation. Finally, the numerous simulation results illustrate that the proposed scheme can significantly reduce the total energy cost of EVs compared to various case studies and greedy algorithm, and also demonstrate its behavioural adaptation to any environmental conditions.

    Original languageEnglish
    Title of host publication2022 IEEE 95th Vehicular Technology Conference - VTC 2022-Spring - Proceedings
    ISBN (Electronic)9781665482431
    Publication statusPublished - 25 Aug 2022
    Event95th IEEE Vehicular Technology Conference - Spring 2022 - Helsinki, Finland
    Duration: 19 Jun 202222 Jun 2022


    Conference95th IEEE Vehicular Technology Conference - Spring 2022
    Abbreviated titleVTC 2022-Spring


    • Bellman expectation equation
    • charging station
    • Electric vehicle assignment
    • electrical grids.
    • energy consumption
    • energy cost
    • Q-learning
    • temporal difference

    ASJC Scopus subject areas

    • Computer Science Applications
    • Electrical and Electronic Engineering
    • Applied Mathematics


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