Real-Time Management System for Automotive Charging Based on Control and Optimization Algorithms (Informatica, 2025)
This research offers a novel solution to handle the mounting challenges provided by real-time management systems for vehicle charging. The solution involves developing a real-time management system that incorporates control and optimization algorithms. Recognizing the possible strain on the grid, the study starts by evaluating the effects of large-scale integration of electric vehicles into the power system during periods of peak electricity usage. A charge management system is implemented to effectively supervise the charging of electric vehicles in order to lessen this problem. This study also looks into the suitability of the electric vehicle charging management system, with an emphasis on its use in homes.The time-of-use power pricing charge management strategy is smoothly linked with multi-agent system technology in the proposed charging management system. To arrange the best times for electric vehicle charging based on time-of-use power pricing, this system introduces an agent-based method on the management platform. Finally, this study verifies the viability of the suggested approach by running simulations on a charge management platform created with Matlab, Simulink, and JADB. The simulation’s findings support the charge management system’s efficient automation of charging, which lowers charging expenses and lessens peak load demands in the process. This suggests a viable remedy for the problems associated with the real-time management of car charging systems.