Fuzzy-based pelican optimization for battery management and energy scheduling in solar aided electric vehicle

Electric vehicles (EVs) are considered an essential mode of transportation due to their advantages, non-polluting and noise-free characteristics. The batteries are considered the primary power source for electric vehicles, ensuring energy supply and thus improving the user experience. However, designing charging stations and uncontrolled charge scheduling are the barriers evaluated in charging stations. To solve these issues, a fuzzy-based pelican optimization algorithm (POA) is proposed in this work. Set of rules are generated in the fuzzy for optimal energy management inn charging station. POA schedules the EVs in the charging station based on arrival time and SOC to reduce the running cost. Demand in the charging station is based on the state of charge (SOC) of the EVs arriving at the charging station. Solar power with battery and ultracapacitor is used as an input source for charging stations. The energy management in the system is based on fuzzy to satisfy the load demand from PV and energy storage devices. This proposed method is implemented in the Simulink tool to evaluate the performance. This simulation result show the effectiveness of the proposed with optimal scheduling and energy management. By this method running cost are reduced compared to the existing algorithms.