Electric vehicle charging technologies, infrastructure expansion, grid integration strategies, and their role in promoting sustainable e-mobility

Abstract: The emergence of electric vehicles (EVs) as key elements in the decarbonization of transportation demands a new class of intelligent infrastructure capable of optimizing charging behavior while maintaining power system stability. This paper proposes a novel Scalable Cloud-Based Continuous Monitoring Platform (SC-CMP) designed to support real-time optimization of microgrid operations, particularly in EV-dense and renewable-integrated environments. By fusing cloud computing, machine learning (ML), and artificial intelligence (AI) with Internet of Things (IoT) data acquisition, SC-CMP enables continuous monitoring, predictive scheduling, and adaptive energy management across distributed power networks. Unlike conventional systems, SC-CMP supports both centralized and decentralized microgrid architectures, providing scalable support for dynamic load balancing, V2G coordination, and resilient energy dispatch. Simulation and validation are performed using a real-world dataset of 3395 EV charging sessions across 105 stations, demonstrating SC-CMP's superiority over existing AI/ML baselines. Quantitatively, the platform achieves 97.34% predictive accuracy, 96.81% grid stability improvement, 94.5% resource allocation efficiency, 93% scalability, and 95.2% data privacy assurance. These outcomes position SC-CMP as a comprehensive, adaptive, and cost-effective solution for microgrid-oriented EV integration, offering substantial advances in resilient power distribution, renewable energy utilization, and sustainable electric mobility. The platform serves as a foundation for next-generation microgrid control systems that demand real-time intelligence, scalability, and reliability across evolving smart grid landscapes.

TL;DR: This study integrates S-curve modeling and social network analysis to examine electric vehicle patent trends globally and in South Korea, identifying saturation, sustainable research directions, and technological advantages, guiding stakeholders in EV technology development.

TL;DR: In this paper, the authors present five coordination schemes to enhance interaction between system operators to guarantee a safe, reliable, and cost-efficient use of flexibility-based services in the distribution grid.

TL;DR: In this paper, the authors present a cost analysis of a next-generation 80 kWnet automotive fuel cell stack for light-duty vehicles, including the baseline system characteristics and specifications and the results of Design for Manufacture and Assembly (DFMA®) analysis of system manufacturing across a range of annual production rates.

TL;DR: The characterizations of big data, smart grids as well as huge amount of data collection are discussed as a prelude to illustrating the motivation and potential advantages of implementing advanced data analytics in smart grids.

TL;DR: It is concluded that taking into account, the special characteristics of electric vehicles are so important in their mobility.