Power Quality Improved Grid-Interfaced PV-Assisted Onboard EV Charging Infrastructure for Smart Households Consumers

This work introduces a unique adaptive control technique, and an auto-tuned MPPT (Maximum-power-point tracking) control technique for the grid-interfaced photovoltaic (PV) assisted onboard EV (Electric Vehicle) charging infrastructure. Proposed control algorithm is “Multilayer Multi-order Generalized Discrete Integrator based Adaptive Control (MMGDI-AC). This control technique is developed, including damping reduction, noise removal, delay minimization, filtering harmonic components, and accurate fundamental component estimation feature. Furthermore, an EV safety management feature for safe EV charging is incorporated in the developed MMGDI-AC technique. Moreover, a “Single-input Adaptive Fuzzy-Logic (SIAFL)” is developed for online optimal decision taking. By using SIAFL with Perturb and Observe (P&O) algorithm, a novel SIAFL tuned P&O (SFPO) MPPT algorithm is introduced, where fixed step-change issues of classical P&O MPPT technique are solved. In this work, a double stage single phase topology is used, where optimal maximum power extraction from the solar PV array, safe EV charging, power management and power quality maintenance are the key features. The abilities of the developed techniques are tested on varying grid abnormalities, as well as the performances are also tested on varying charging dynamics. Test results are shown with the help of developed hardware.