Intelligent Control of DC Microgrid Involving Multiple Renewables for Fast Charging Control of Electric Vehicles

Abstract

Electric vehicles (EVs) are now considered to be a cutting-edge form of transportation. However, the electrical grid infrastructure is not sufficiently developed to meet the rising charging demand for electric vehicles. Therefore, it is impossible to rely entirely on grid-generated electricity. This article discusses a control approach for extremely rapid charging of EV batteries driven by a hybrid DC microgrid, consisting of isolated, Photovoltaic (PV), Wind Turbine, Fuel Cell and Energy Storage Systems. An adaptive sliding mode controller is designed to provide the appropriate power for charging and discharging EVs and energy storage units (ESUs) under a variety of power generation and demand scenarios. The proposed adaptive sliding mode controller operates in a decentralized manner to maintain power distribution amongst the microgrid DC-link EVs and the ESUs. In order to validate the effectiveness of the sliding mode controller in battery charging applications, a comprehensive comparison between fuzzy logic and adaptive sliding mode control is conducted. The proposed controller operates exceptionally well in the presence of unpredictable operating point variations such as rapid changes in EV charging load, fluctuations in solar irradiation, unexpected wind conditions, and so on. Finally, the proposed controller is verified by both simulation and experimental studies.