Sustainable and Intelligent Control Strategies for Electric Vehicle Systems
Rushikesh Anil Dhumane, Tejas Dadasaheb Nikam, Ram Hajare, Dipesh Bhaurao Pardeshi, P. William · 2023
Electric utilities have a number of difficulties when integrating electric vehicles (EVs) into distribution networks without a communication infrastructure. To overcome these obstacles, it is essential to design reliable autonomous controllers that can handle charging operations efficiently while ensuring adherence to grid standard restrictions. This research suggests an innovative method based on fuzzy logic for an autonomous charging controller for EVs in distribution systems. The fuzzy inference system is made to meet three main goals: eliminating under-voltage problems in the grid, optimizing the system loading profile, and ensuring equitable charging among numerous connected EVs. To do this, it takes into account both the system voltage profile and the EV's battery state of charge (SOC). The findings reveal that the communication-free autonomous charging controller operates better than existing ones, displaying quicker and better charging performance while successfully reducing voltage violations. The controller can dynamically adjust to shifting system conditions thanks to the incorporation of fuzzy logic, enabling efficient and dependable charging operations for EVs. This research advances EV integration in distribution systems by offering a reliable and communication-free approach to autonomous charging regulation.