Innovations in Electric Vehicle Energy Management Systems by Integrating Machine Learning and Artificial Intelligence

Abstract

There are numerous aspects of managing electric vehicles that are being improved by machine learning and artificial intelligence. These aspects include the management of batteries, the most efficient use of charging infrastructure, the prediction of repair needs, and the conservation of energy. By determining the most effective routes for vehicles, including renewable energy sources into the charging ecosystem, and accurately measuring the amount of energy that is being consumed, machine learning and artificial intelligence in electric vehicle management systems make these systems more energy efficient. The widespread implementation of machine learning and artificial intelligence in this research in electric car management systems is still being hampered by a number of factors, including concerns around data privacy, issues with charging infrastructure and model compatibility, and the requirement for standardized protocols and standards. The application of machine learning and artificial intelligence in the management systems of electric cars has the potential to enhance the user experience, make the systems more efficient, and increase their overall performance. It is of the utmost importance that governments, corporations, and authorities continue to collaborate in order to determine the most effective ways to utilize this technology and encourage a greater number of people to purchase electric vehicles.