Design and implementation of hybrid energy sources with fuzzy neuro control for DC micro grid system used for electric vehicle

The management scheme of fuzzy logic control (FLC) and neural network (NN) on the DC Microgrid using hybrid renewable energy sources for electric vehicle is proposed in this paper. A solar PV array, wind source and PEM fuel cell are included in the hybrid renewable source. The fuel cell employed here is primarily used for loads when there is a power outage in power generation. For increased load, a bi-directional converter connected to the battery controls the Voltage which is sent to the load for fulfilment the load requirement. Using the bi-directional converter, charging and discharging are achieved. In contrast to traditional PI controllers, fuzzy logic governs complex mathematical modelling. In a short time interval, the fuzzy logic controller achieves less overshoot, lower oscillations and steady status. The neural network algorithm implements a simple high precision structure that achieves maximum performance efficiency, which compared to FLC, also provides better control. Control techniques for artificial intelligence (FLC and NN) include improved recognition of the optimum operating point. Simulation is done in the framework of MATLAB/Simulink.