An efficient battery swapping and charging mechanism for electric vehicles using bat algorithm

Vani, Batchu Veena; Kishan, Dharavath; Ahmad, Md Waseem; Reddy, B. Naresh Kumar

doi:10.1016/j.compeleceng.2024.109357

Computers and Electrical Engineering

2024

DOI: 10.1016/j.compeleceng.2024.109357

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An efficient battery swapping and charging mechanism for electric vehicles using bat algorithm

Batchu Veena Vani,

Dharavath Kishan,

Md Waseem Ahmad

et al.

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2024

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Cited by 2 publications

References 33 publications

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Accurate prediction of electric vehicles mileage for proactive battery management in varied conditions using multi-criteria approach

Jog,

Simu

2024

Computers and Electrical Engineering

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Accurate prediction of electric vehicles mileage for proactive battery management in varied conditions using multi-criteria approach

Jog,

Simu

2024

Computers and Electrical Engineering

View full text Add to dashboard Cite

Predicting and Forecasting of Vehicle Charging Station Using ECNN with DHFO Algorithm

Paul,

Selvan

2024

Energies

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The forecast of the optimal placement of a charging station (CS) according to the real-time consumption of electric vehicles is a subject of urgency in this new era. The demand of a charging station in an area based on the trend of consumption can be predicted by means of interpolation and the extrapolation of historical data using a linear function of prediction model. The prediction of the charging station system was performed with distance relevancy methods. An adaptive optimal learning model was proposed to enhance the prediction performance for charging station management and to represent the pattern of vehicles’ travelling directions. The proposed model uses Distributional Homogeneity Feature Optimization (DHFO) using artificial intelligence (AI) to categorize and forecast the charging station from the database. The prediction performance of this model is improved more than the conventional classification model by filtering the apt features from all the electric vehicular and charging station attributes in the database. The Enhanced Cladistic Neural Network (ECNN) is used to improve the pattern learning model and increase learning accuracy. By comparing statistical parameters with other state-of-the-art methodologies, the suggested model’s overall findings were verified.

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An efficient battery swapping and charging mechanism for electric vehicles using bat algorithm

Cited by 2 publications

References 33 publications

Accurate prediction of electric vehicles mileage for proactive battery management in varied conditions using multi-criteria approach

Accurate prediction of electric vehicles mileage for proactive battery management in varied conditions using multi-criteria approach

Predicting and Forecasting of Vehicle Charging Station Using ECNN with DHFO Algorithm

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