Journal of Smart Energy Systems and Sustainable Technologies

Articles

Vol. 1 (2025)

Global Fusion of Nascent Technologies in Next -Generation Electric Vehicles models: Evolution, Developments and Regulatory Prospects

Submitted
November 7, 2025
Published
2025-11-07

Abstract

Due to its potential to have the lowest carbon footprints on the planet, electrical vehicles, or EVs, have drawn a lot of attention globally in the period of moving towards greener and zero-emission energy generation and transportation. Climate change is currently seen as one of the main negative consequences of burning fossil fuels and traditional modes of transportation. Because Renewable Energy Sources (RESs) are variable and electric vehicles (EVs) are one of the primary means of increasing them, electrifying energy consumption is one of the most important aspects of the energy transition when considering the replacement of conventional plants with RE. This study had a comprehensive review about evolution of electric vehicles with emphasis on the information about 'Model', 'Make', 'Electric range', 'Base MRSP' and 'Electric Vehicle Type'. By using EV sales data the study focussed on global trends at the continent and country level by identifying the best and worst performing countries in terms of sales. Using data-driven methods, this study investigates the EV characteristics that have a significant influence on range. Web mining was used to get a comprehensive dataset of the technical parameters of commercial EV models produced between 2013 and 2023. Regression analysis of 103 EV models showed that price is significantly impacted by top speed and efficiency. Moreover, ML algorithms were trained and tested on a data set comprising (Historical, Projection-APS, and Projection-STEPS) for a time period of 2011-2030 with a lowest mean squared error of 0.00015 and r2 of 67 percent, and MSE 4.7 and r2 of 90 percent, obtained from Adaboost and XGB indicative of the good predictive accuracy of the model. These performance parameters that were determined are useful to EV consumers to choose best EV model. 

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