An Application of Genetic Algorithm to Estimate the Tuning Parameters of PID Controller for a Basic Model of an Electric Vehicle Battery and the Performance Analysis of a Battery model

The current trend is E mobilitythe reason for it is to protect or save the environment. The success of $\mathbf{E}$ mobility depends on the two important components. First one is a battery and the second is motor. Among these two, battery plays a very vital role in the $\mathbf{E}$ mobility. The cost of battery is also too high. The life span of any electric vehicle depends on the life of a battery. Battery charging and discharging cycles decide the life a battery. To have a longer life for a battery it is essential to control the charging and discharging cycles of the battery. Therefore, it becomes necessary to have a controller for controlling the charging and discharging of the battery. The Proportional Integral Derivative (PID) Controllersare in use in the industries since many years. The PID controller is simple, flexible and efficient. Proper tuning of the PID controllers, results in accurate and effective controlling actions. Many researchers have developed and discussed the tuning methods of PID controllers. To cope up with the complexities of the constantly evolving industries designers developing evolutionary algorithms like Genetic Algorithms, Simulated Annealing etc. In this paper, a simulation study is carried out by using MATLAB Simulinkto analyze the effect of battery model component on the controlling action by PID controller employing Genetic algorithm. It is found that the components of a battery model have significant effect on the performance of the battery. The Genetic algorithm helps to tune the PID controller to improve the performance.