FPGA-based sustainable EV charging controller with dynamic pricing for smart cities

Abstract

The growing adoption of electric vehicles (EVs) poses significant challenges to the stability and efficiency of the power grid, particularly under dynamic electricity pricing and variable grid availability in smart cities. This paper presents a novel, low-latency, hardware-driven approach to smart EV charging control using a field-programmable gate array (FPGA) Arty A7-100T. A customized finite state machine (FSM) evaluates the state of charge (SoC) and real-time pricing across multiple time slots. Based on this evaluation, it generates charge eligibility for each EV and transmits these decisions-along with the SoC and pricing data-via UART to an external Python interface. The received data is processed in Python and used to dynamically plot the SoC, pricing, and charging permission for each EV across time slots-providing a clear, intuitive visualization of decision-making based on energy economics. The distributed hardware-enabled paradigm minimizes delay as well as external dependency, thus offering improved responsiveness for the grid. The implementation is shown to represent a scalable solution for solving vital issue of demand side management for the evolving EV ecosystem for smart cities.