A PV powered DC shunt motor: Study of dynamic analysis using maximum power Point-Based fuzzy logic controller

Abstract

• High dependency of the solar cells’ current–voltage characteristic on solar radiation and ambient temperature level. • A robust fuzzy inference system-based maximum power point tracking (MPPT) controller deployed to achieve the steady state stability. • Utilization of MPPT controller to improve the performance of PV panel connected to different types of loads. • A proposed solution built with a power electronics system and a DC-to-DC boost converter. • Improved overall dynamic system performance and stability of DC shunt motor. Solar cells absorb sun light and convert it into electricity. However, the infrastructure of solar cells, their initial cost, energy conversion and efficiency could raise some challenges and concerns. This is because of the current–voltage properties of solar cells which are strongly dependent on the solar radiation and the ambient temperature level. This further causes fluctuations in the photovoltaic (PV) output power. In this article, a novel scheme is proposed to improve the PV system efficiency. This is achieved by using tracker techniques to calculate the maximum power point tracking (MPPT) where the energy can be safely passed to the load under suitable conditions. The scheme is further enhanced by investigating a PV generator and a direct-current (DC) shunt motor using a fuzzy logic controller (FLC) method for monitoring and tracking the maximum power point. A power electronics system based on boost DC-to-DC converter is used along with the PV module to raise the performance by the shift of the converter control input duty cycle. Evaluations were made to analyze the dynamical behavior and the steady state performance of the direct current shunt motor obtained from the PV module using MATLAB SIMULINK.