Intelligent Control for SEPIC-Fed BLDC Solar PV Water Pumping Systems with Enhanced Energy Efficiency

Authors

  • Rahul W. Patil Prof. Ram Meghe College of Engineering and Management, Badnera, Amravati – 444701, Maharashtra, India.
  • Swapnil B. Mohod Department of Electrical Engineering, Prof. Ram Meghe College of Engineering and Management, Badnera, Amravati, Maharashtra, India.

DOI:

https://doi.org/10.70917/ijcisim-2026-4205

Keywords:

Solar PV Water Pumping, BLDC Motor, SEPIC Converter, MPPT, Sensorless Control, Fuzzy Logic/ANFIS, Bio-inspired Optimization

Abstract

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.

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Published

2026-08-04

How to Cite

Rahul W. Patil, & Swapnil B. Mohod. (2026). Intelligent Control for SEPIC-Fed BLDC Solar PV Water Pumping Systems with Enhanced Energy Efficiency. International Journal of Computer Information Systems and Industrial Management Applications, 18(14s), 184–195. https://doi.org/10.70917/ijcisim-2026-4205

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Section

Original Articles