Power Quality Enhancement and System Stability Improvement in Grid-Connected PV-Based EV Charging System Using Adaptive Controlled 9-Level MLI

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Chinese explanation / 中文解读

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Original abstract

This paper presents a grid-connected photovoltaic (PV)-based electric vehicle (EV) charging system employing a Nine-Level Multilevel Inverter (9L-MLI) and an Adaptive Fuzzy Logic Controller (AFLC) to enhance power quality and system stability. The proposed system integrates a solar PV source with an EV battery through DC–DC boost and bidirectional buck–boost converters, enabling efficient energy management for Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) operations. The generated solar power is utilized for EV charging, local load support, and grid power injection depending on the operating conditions. A 9L-MLI is employed to produce a near-sinusoidal output voltage with reduced switching stress, lower total harmonic distortion (THD), and improved voltage quality compared with conventional multilevel inverter topologies. To achieve robust dynamic performance, an Adaptive Fuzzy Logic Controller is implemented for inverter switching control, DC-link voltage regulation, and grid current control under varying solar irradiance, load disturbances, and EV charging conditions. The adaptive fuzzy controller provides rapid disturbance rejection, accurate reference tracking, enhanced transient response, and improved steady-state performance compared with conventional PI-based control methods. The complete system is modeled and validated in MATLAB/Simulink. Simulation results demonstrate significant THD reduction, improved source current quality, stable DC-link voltage, enhanced power factor, efficient bidirectional power flow, and reliable operation under dynamic conditions. The proposed AFLC-based 9L-MLI topology provides an intelligent and efficient solution for renewable energy-integrated EV charging systems with superior power quality and enhanced grid stability.

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