Key points are not available for this paper at this time.
The aim of this article is to provide a comprehensive overview of electric vehicles (EVs), covering various related aspects, and addressing the emerging challenges and future prospects associated with them. Within this framework, an examination is conducted of the fundamental categories of electric vehicles (EVs) and the related charging methodologies. Given that EVs are anticipated to play a pivotal role in upcoming smart electrical grids (SEG), deliberations also extend to the intricacies of grid integration, along with explorations into advanced charging methodologies such as wireless power transfer and communication between station and center with wireless (WIFI, WIMAX, 5G). This article also examines the current state of EV battery (EVB) chargers in terms of converter configurations, operational modes, and power regulation strategies for electric vehicles. EVB chargers are categorized according to their power capacities and the direction of power flow. Based on power ratings, these chargers are classified into Level 1, Level 2, and Level 3. Certain emerging charging technologies that have the potential to significantly influence the future of energy storage in the realm of transportation electrification have been discussed. Regarding the future of EV station chargers focused on DC fast charging stations, this paper conducts an examination of the design and assessment of various AC/DC converter topologies in the current context, as well as future strategies for integrating them into DC fast-charging infrastructures. With this aim, the fundamental characteristics and prerequisites for vehicle-to-grid (V2G) communications, and prospects for future advancements and electrification scenarios are also introduced and examined. Compensation reactive power is presented also as V4G (vehicle-for-grid) and some technologies are used to compensate the grid. Ultimately, the Model Predictive Control (MPC) algorithm has been elaborated upon using various approaches to provide a deeper understanding of its application in fast chargers through the utilization of artificial intelligence techniques.
Hakam et al. (Mon,) studied this question.