Dynamic Performance of Bidirectional EVSE for IoT-Based Monitoring and Cost Estimation for Reducing Grid Stress

Electric vehicles (EV) utilise public charging stations that feature a bidirectional charger with a DC-DC converter attached to a DC bus voltage and an active front-end converter using a phase-locked loop (PLL). The minimum value of the integral time absolute error (ITAE) for the proportional integral (PI) parameter, and two optimal tuning methods, are compared with the PI controller’s error computation. The chargers are designed for vehicle-to-grid (V2G) use and support 7.2 kW and 30 kW modes that depend on the EV’s lithium-ion (Li-ion) battery’s discharge current limits. The total harmonic distortion (THD) is 2.81% of the 50 Hz fundamental frequency. 80% of the battery’s State of Charge (SOC) is used to go from constant current (CC) to constant voltage (CV) charging. SOC is increased by 0.1% from 11.99 to 16.35 seconds, depending on SOC level—the mode change from 7.56 to 10.28 kW results in a power deviation. The usage-based tariff (TOU) is computed using an Indian tariff model and other available tariff models. An Internet of Things (IoT) based control and monitoring system for EV charging stations has been developed on the ThingSpeak cloud, showcasing enhanced dynamic performance in synchronising DC link and inverter voltages. TOU calculations utilize a bidirectional electric vehicle supply equipment (EVSE) model based on Indian tariffs, and the paper validates the V2G system through simulations, estimating operational costs informed by system performance and IoT integration.