Particle Swarm Optimization Control Loop for Improving the PV System

Recently, the electric vehicles search extracting energy from any possible energy source. It looks to its aerodynamic forces, to its inertial energy, and to the solar energy for help increasing its autonomy. Concentrating on who extracting energy from the photovoltaic panels, the electric car can have a better energetic performance and can help increasing the battery autonomy inside the vehicle. Therefore, the objective of this study is to build a robust control loop which extract the maximum of energy from these solar panels. So, finding the best control tool will help having a better performance for this renewable energy system. Referring to the existing literature, many algorithms can be used for extracting the maximum of energy. Perturb and observe, Incremental or Particle swarm optimization algorithms can give an acceptable solution. Studying these algorithms and compare their results can give a clear view about the performances of each one. So, initially, it is necessary to study correctly all these algorithms and define their variables and parameters that must be fixed, then implementing all these algorithms and control their outputs. MATLAB/Simulink is the used control tool.