Solar Water Pumping System with BLDC Motor and ANN-based MPPT Technique

This paper outlines the development and simulation of a solar water pumping setup that incorporates a brushless DC (BLDC) motor and utilizes an Artificial Neural Network (ANN) for maximum power point tracking (MPPT). The system aims to provide an efficient and reliable solution for water pumping applications using renewable solar energy. A boost converter, bidirectional converter, and 3-phase inverter are modelled along with the BLDC motor, battery, and solar photovoltaic (PV) array. An ANN-based MPPT algorithm is implemented to maximize energy harvesting from the solar panels. The system performance is analyzed under varying solar irradiation conditions. The outcomes of the simulation affirm the efficacy of the suggested method in achieving maximum power extraction, maintaining a consistent voltage supply to the BLDC motor, and ensuring continuous operation even in the face of variations in solar energy output. The system exhibits a smooth transition between solar and battery power, validating the hybrid architecture. This research provides a foundation for implementing intelligent control of solar water pumping systems to enhance efficiency and reliability.