BATTERY MANAGEMENT IN ELECTRICAL VEHICLES USING MACHINE LEARNING TECHNIQUES

Abstract

Electric vehicle (EV) manufacturers are increasing production in order to keep up with the fast growing demand from customers. To meet the ever-increasing demand for electric vehicles (EVs), both well enough and up-and-coming manufacturers of automobiles will need to immediately boost their production of EVs while simultaneously lowering their prices in order to compete. However, the production of electric vehicles comes with its own set of challenges for automotive manufacturers who are looking to survive in the years to come. By generating digital twins of both their products and their production processes, businesses have the ability to virtually develop and test complete assembly processes as well as entire facilities. This speeds up the process of transitioning to high-volume production without compromising the product's quality. Battery management is one of the most challenging components of driving electric vehicles (EV). Batteries and the amounts of energy that they can store were the focus of this research. Researchers make use of a technique that is referred to as "machine learning" in order to monitor and improve the management of electric car batteries.One of the most challenging factors in Electrical Vehicles (EV) is battery management. This research paper discussed the effective use of battery management and it's capacity. Researchers uses a Machine learning technique to monitor and improve the level of managing techniques in EV's batteries.