Biogeography Based Optimization Tuned Fuzzy Logic Controller to Adjust Speed of Electric Vehicle

There are many power electronic converters and motor drives connected together to form the electrical system of an Electric Vehicle. In this paper, we have presented a modeling tool that has the advantages of utilizing capabilities of the PMSM software in detailed simulations of converters, motor drives, and electric machines. In addition, equivalent electrical models of Electric Vehicle drive system. This paper also gives a brief idea of PMSM validity as an Electric Vehicle simulation tool. PMSM drive system is described and analyzed due to its importance in many applications especially in Electric Vehicle applications. This application is high efficiency, low inertia and high torque to volume ratio. In this paper we embody the simulation of Fuzzy Logic Controller. The controller govern the speed control of Electrical Vehicle EV using permanent magnet synchronous motor PMSM. This work characterizes to obtain the optimal parameters of FLC. Biogeography Based Optimization (BBO) is a new intelligent technique for optimization; it can be used to tune the parameters in different fields. The main contribution of this work efforts the ability of BBO to design the parameters of FLC by determining the shapes of triangle memberships of the inputs and output. The results of optimal controller (BBO-FLC) compared with the other controllers designed by Genetic Algorithm GA which it is a powerful method has been found to solve the optimization problem. The implementation of BBO algorithm has been done by M-file/Matlab, this program linked with SIMULINK to calculate the finesses function which has the complete mathematical system model has implemented using. The results show the excellent performance of BBO-FLC compared with GA-FLC and PI controller, also the proposed method was very fast and need a few number of iterations. These results also confirmed that the transient torque and current never exceed the maximum permissible value.