Design and Analysis of Smart Solar EV Charging System

Notice

This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2026 | Volume : 16 | 01 | Page :
    By

    Avijit Mistry,

  • Tanay chaudhary,,

  • Suman Kumar Gupta,

  • Prasenjit jana,

  • Saumen Dhara,

  • Shantanu Naskar,

  1. UG Student, Department of Electrical Engineering, Greater Kolkata College of Engineering & Management, Baruipur, Kolkata, West Bengal, India
  2. UG Student, Department of Electrical Engineering, Greater Kolkata College of Engineering & Management, Baruipur, Kolkata, West Bengal, India
  3. UG Student, Department of Electrical Engineering, Greater Kolkata College of Engineering & Management, Baruipur, Kolkata, West Bengal, India
  4. UG Student, Department of Electrical Engineering, Greater Kolkata College of Engineering & Management, Baruipur, Kolkata, West Bengal, India
  5. Assistant Professor, Department of Electrical Engineering, Greater Kolkata College of Engineering & Management, Baruipur, Kolkata, West Bengal, India
  6. Assistant Professor, Department of Electrical Engineering, Greater Kolkata College of Engineering & Management, Baruipur, Kolkata, West Bengal, India

Abstract

The rising demand for electric vehicles (EVs) has generated an urgent requirement for sustainable and advanced charging systems. This study delineates the design and analysis of an intelligent solar EV charging system intended to reduce dependence on the grid and optimize the utilization of renewable energy. The system incorporates a solar photovoltaic (PV) array, battery energy storage, and an IoT-enabled smart controller to optimize power delivery. A Maximum Power Point Tracking (MPPT) technique is employed to optimize the energy harvesting efficiency of the photovoltaic system under fluctuating irradiance conditions. The photovoltaic system uses a Maximum Power Point Tracking (MPPT) technology to improve energy harvesting efficiency in a variety of environmental circumstances. This method guarantees the best possible solar energy extraction even in the face of temperature and irradiance fluctuations. In order to effectively and economically control charging operations, the smart controller continuously checks system data, such as battery health, state of charge, and real-time solar availability. This clever control method increases battery life, reduces energy loss, and enhances system reliability. The smart controller ensures optimal performance and energy economy by controlling charging operations based on battery health and real-time sun availability. The efficacy of the suggested method in providing steady and continuous charging is confirmed by modeling and validation using MATLAB/Simulink software. The system is a feasible and sustainable alternative for future EV infrastructure, as evidenced by simulation results showing enhanced energy utilization and decreased grid demand.

Keywords: Solar EV charging system, battery energy storage, Renewable Energy, MPPT, IoT, PV array.

How to cite this article:
Avijit Mistry, Tanay chaudhary,, Suman Kumar Gupta, Prasenjit jana, Saumen Dhara, Shantanu Naskar. Design and Analysis of Smart Solar EV Charging System. Journal of Power Electronics and Power Systems. 2026; 16(01):-.
How to cite this URL:
Avijit Mistry, Tanay chaudhary,, Suman Kumar Gupta, Prasenjit jana, Saumen Dhara, Shantanu Naskar. Design and Analysis of Smart Solar EV Charging System. Journal of Power Electronics and Power Systems. 2026; 16(01):-. Available from: https://journals.stmjournals.com/jopeps/article=2026/view=238880


References

[1] Ruan G, Dahleh MA. Temperature-controlled smart charging for electric vehicles in cold climates. IEEE Transactions on Smart Grid. 2025 Jan 3;16(3):2197-207.

[2] Arooj A, Ahmed QZ, Farooq S, Umer T, Aslam N, Alade T. Unraveling the smart charging technologies, energy sources, and regulatory standards for EVs. IEEE Access. 2025 Jun 13.

[3] Stenstadvolden A, Hansen L, Zhao L, Kapourchali MH, Lee WJ. Demand and sustainability analysis for a level-3 charging station on the US highway based on actual smart meter data. IEEE Transactions on Industry Applications. 2023 Jul 6;60(1):1310-21.

[4] Singh S, Chauhan P, Singh NJ. Feasibility of grid-connected solar-wind hybrid system with electric vehicle charging station. Journal of Modern Power Systems and Clean Energy. 2020 Jul 22;9(2):295-306.

[5] Kumar N, Saxena V, Singh B, Panigrahi BK. Power quality improved grid-interfaced PV-assisted onboard EV charging infrastructure for smart households consumers. IEEE Transactions on Consumer Electronics. 2023 Jul 18;69(4):1091-100.

[6] Calero I, Canizares CA, Farrokhabadi M, Bhattacharya K. Machine learning-based control of electric vehicle charging for practical distribution systems with solar generation. IEEE Transactions on Smart Grid. 2023 Nov 16;15(3):3098-113.

[7] Yang Y, Yeh HG, Nguyen R. A robust model predictive control-based scheduling approach for electric vehicle charging with photovoltaic systems. IEEE Systems Journal. 2022 Jul 6;17(1):111-21.

[8] Francisco AM, Monteiro J, Cardoso PJ. A digital twin of charging stations for fleets of electric vehicles. IEEE Access. 2023 Nov 7;11:125664-83.

[9] Naik M, Singh AP, Pradhan NR, Almuhaideb AM, Kumar N. A Framework for Blockchain-Enabled Internet of Electric Vehicle Charging Station Sustainability Performance Evaluation. IEEE Internet of Things Journal. 2024 Nov 22.

[10] Sangswang A, Konghirun M. Optimal strategies in home energy management system integrating solar power, energy storage, and vehicle-to-grid for grid support and energy efficiency. IEEE Transactions on Industry Applications. 2020 Apr 30;56(5):5716-28.

[11] .Lee Z, Johansson D, Low SH. ACN-Sim: An open-source simulator for data-driven electric vehicle charging research. InProceedings of the Tenth ACM International Conference on Future Energy Systems 2019 Jun 15 (pp. 411-412).

[12] El-Taweel NA, Farag H, Shaaban MF, AlSharidah ME. Optimization model for EV charging stations with PV farm transactive energy. IEEE Transactions on Industrial Informatics. 2021 Sep 21;18(7):4608-21.

[13] Singh S, Pamshetti VB, Singh SP. Time horizon-based model predictive Volt/VAR optimization for smart grid enabled CVR in the presence of electric vehicle charging loads. IEEE Transactions on Industry Applications. 2019 Jul 15;55(6):5502-13.

[14] Balogun E, Buechler E, Bhela S, Onori S, Rajagopal R. EV-EcoSim: A grid-aware co- simulation platform for the design and optimization of electric vehicle charging infrastructure. IEEE Transactions on Smart Grid. 2023 Dec 5;15(3):3114-25.

[15] Wang B, Zhao D, Dehghanian P, Tian Y, Hong T. Aggregated electric vehicle load modeling in large-scale electric power systems. IEEE Transactions on Industry Applications. 2020 Apr 16;56(5):5796-810.


Ahead of Print Subscription Review Article
Volume 16
01
Received 06/01/2026
Accepted 27/01/2026
Published 19/03/2026
Publication Time 72 Days


Login


My IP

PlumX Metrics