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@article{186252,
        author = {MAHENDRA NAIDU GOTTAPU and Dr. Kottala Padma},
        title = {An Intelligent Charging System for Grid-Integrated Electric Vehicles Using an ANFIS-Based Controller},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {6},
        pages = {284-301},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=186252},
        abstract = {Electric vehicles (EVs) are rapidly emerging as a key component of sustainable transportation, driving the need for advanced charging infrastructure. This work presents a multifunctional charging system integrated with the grid, EV batteries, and household utilities, offering improved efficiency and adaptability. The proposed system consists of a voltage source converter (VSC) connected to the grid and a bidirectional converter that manages battery charging and discharging while maintaining a stable DC bus voltage for EV charging. 
To enhance system performance, an Adaptive Neuro-Fuzzy Inference System (ANFIS) controller replaces the conventional PI controller, providing adaptive control, faster response, improved robustness against load variations and to estimate the active component of load current, further optimizing power management. The ANFIS-based control strategy enhances the system’s dynamic response by accelerating error convergence and improving mean square error (MSE) performance. Simulation and simulation results validate the effectiveness of the proposed intelligent charging system, demonstrating improved accuracy, efficiency, and reliability in grid-integrated EV charging applications. simulation results demonstrates that the ANFIS outperforms traditional methods by achieving superior dynamic performance and accuracy. Specifically, the ANFIS will optimize system effectively and reduces Total Harmonic Distortion (THD) of the source current to 1.06%.},
        keywords = {},
        month = {October},
        }