Controlling and Analysis of Battery Energy System in Electric Vehicle

The largest concern in the situation of today, when the majority of people use automobiles is whether or not the car will be safe. Due to the alarming increase in the number of car accidents and life-threatening injuries, it is now essential that vehicles have suitable safety features. It is believed that the concept of smart-hybrid vehicle is appropriate enough to achieve fuel efficiency and improved safely for the user which makes the city and transportation smart at an initial level environmental pollution is worsening as per capita energy consumption increases. With the new alternative energy source, it is essential to reduce the use of traditional fuel-powered engines. Pure electric vehicles cannot be mass-produced due to many problems such as short running time and in-sufficient charging equipment. Therefore, the development of the hybrid electric vehicle over a period of time is of particular importance. The price of battery technology, battery longevity, the quantity of charging stations, and charging time are some of the issues with electrification. Electric vehicle’s energy management and propulsion optimization are achieved in an efficient way using machine learning and deep learning algorithms. The primary factors that will determine the improvement of the propulsion system in EVs include vehicle range, cost of the vehicle, battery pack replacement cost, battery pack life, rapid and simple recharging. The majority of propulsion system development will focus on battery solutions, with the exception of vehicle cost. The charging system of electrical should be robust and reliable as the usage is increasing day by day. Significant efforts were made to address the fuel shortages and pollution issues. The lower emissions and operational costs are due to the variation in primary global consumer demand. The price of battery technology, battery longevity, the quantity of charging stations, and charging time are some of the issues with electrification. Electric vehicle’s energy management and propulsion optimization are achieved in an efficient way using machine learning and deep learning algorithms.