Smart Energy Management System in Advanced Electric Vehicles Using Artificial Intelligence Technologies

A significant depletion of diesel and petrol cars has hurt both the environment and individuals. Given that hybrid electric vehicles (HEVs) are more fuel-efficient and have fewer negative environmental effects, the majority of consumers will adopt electric vehicles (EVs). An EV has a built-in battery that is better monitored, intelligently managed, and can be used to power it initially. EVs can also recharge from the electrical grid and can supply energy at a certain level network in return for other services, which helps the grid work more efficiently when using energy from renewable energy sources (RESs). Additionally, EVs allow users to refill their cars at various locations, allowing them to drive longer distances. Multi-fuel vehicles, which supplement electricity with hydrogen, diesel, or biodiesel; enhanced transportation systems; fuel cells that catalyze to lower CO2 emissions, and enhanced fuel reduction performance have all been discussed. Furthermore, in our work with artificial intelligence (AI) technology, both sides of the energy transmission process are adequately protected in terms of privacy and security. As a result, the greenhouse effect may be mitigated, and the adoption of HEVs to replace conventional cars may rise in the future. An online learning approach for privacy-preserving context-based EV dispatching for energy scheduling in Microgrids is described in detail.