ANFIS Based Single-Stage Zeta-Sepic-Based Multifunctional Integrated Converter for Plug in Electric Vehicles
In this paper, implementation of adaptive neuro fuzzy inference system (ANFIS) based controller for ZETA SEPIC converter is analyzed. The converter achieves all modes of vehicle operation, i.e. plug-in charging, propulsion and regenerative braking modes with wide voltage conversion ratio (M) in each mode. And it has least components compared to those existing converters which have stepping up and stepping down capability in every mode. In the case of plug in electric vehicles, the charging/discharging between vehicle and grid is not coordinated; also uncoordinated charging/discharging will increase the losses in the network. Therefore ANFIS based controller is designed and better control is achieved for the different conditions of electric vehicle’s battery and the distribution network. It is proved that the proposed ANFIS based controller improves the grid stability by flattening the load profile and reduces power losses. It is also found that the transient response of the ANFIS based controller is better than fuzzy and PI controller. fuzzy logic controller is useful for the improvement of driving performance, it also makes the hybrid vehicles achieve good fuel economy and low emissions performance.