Buck converter-based transformer-less electric vehicle charger using artificial intelligent controller

被引：0
作者：
Priyadarshini, Aayushi [1 ]
Yadav, Shekhar [1 ]
Tiwari, Nitesh [1 ]
机构：
[1] Department of Electrical Engineering, Madan Mohan Malaviya University of Technology, UP, Gorakhpur
来源：
International Journal of Powertrains | 2024年 / 13卷 / 02期
关键词：
adaptive neuro-fuzzy inference system; and state-of-charge; ANFIS; ANN; artificial neural network; buck converter; FLC; fuzzy logic controller; grid-to-vehicle charger; proportional-integral controller; SOC;
D O I：
10.1504/IJPT.2024.140132
中图分类号：
学科分类号：
摘要：
The uni-directional power exchange between a charging station and an electric vehicle is important for grid-to-vehicle charging. While accomplishing the operation, various converters and controllers play an important role in transferring smooth power between the grid-to-vehicle. The paper discusses designing the model of a buck converter-based transformer-less charger that uses artificial intelligent controllers as well as confirms the power exchange between the grid and battery of the vehicle. The performance of a transformer-less grid-to-vehicle charger is designed using various electric vehicles based on consumer choice. The results demonstrate that the proposed charger delivers smooth power flow between charging stations to various types of vehicles with minimum voltage tracking error. The simulation tool MATLAB and SIMULINK estimates the settling time, tracking error, peak overshoot, smoothness of the controller, and accurate charger state-of-charge to prevent the battery from being overcharged. Copyright © 2024 Inderscience Enterprises Ltd.
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页码：156 / 177
页数：21
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