Intelligent Control for SEPIC-Fed BLDC Solar PV Water Pumping Systems with Enhanced Energy Efficiency
DOI:
https://doi.org/10.70917/ijcisim-2026-4205Keywords:
Solar PV Water Pumping, BLDC Motor, SEPIC Converter, MPPT, Sensorless Control, Fuzzy Logic/ANFIS, Bio-inspired OptimizationAbstract
One of the most common and commonly used decentralized uses of renewable energy is solar photovoltaic (PV) water pumping, which provides an alternative to diesel-powered irrigation and drinking-water provision in remote and off-grid areas. Of all the different combinations of motor and converter reported in the literature, the brushless direct current (BLDC) motor driven by single-ended primary inductor converter (SEPIC) has proven to be a particularly appealing design since it offers the high efficiency and low maintenance of BLDC machines with either the wide-range buck-boost capability, constant input current, and non-inverting output of the SEPIC topology. This is a review of the state of the art of intelligent control strategies implemented on SEPIC-fed BLDC solar PV water pumping systems, especially maximum power point tracking (MPPT), sensorless commutation, and adaptive speed/torque control. The traditional approaches that include Perturb and Observe and Incremental Conductance are discussed as well as intelligent approaches that include fuzzy logic control, artificial neural networks, adaptive neuro-fuzzy inference systems (ANFIS) and bio-inspired metaheuristic optimization methods which include particle swarm optimization, genetic algorithms and grey wolf optimization. The review also addresses system-level integration, converter design issues, energy efficiency improvement mechanisms and relative performance in terms of tracking performance, steady-state ripple, partial shading resistance and complexity of implementation. Potential research issues associated with computational load, sensor reliance, standardization and techno-economic feasibility are pinpointed and future research opportunities with regard to hybrid intelligent controllers, digital twins, and Internet-of-Things (IoT)-enabled predictive control are described. The review aims to be a summary of research that can be used by researchers and practitioners in the development of next-generation, high-efficiency solar water pumping systems.