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A Novel Dynamic Energy Amendment Control for Solar Fed Brushless DC Motor for Water Pumping System

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Inventive Systems and Control

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 672))

Abstract

This study optimizes solar PV power for a brushless DC motor (BLDC)-driven water pumping system utilizing Dynamic Energy Amendment Control (DEAC). The improved isolated DC–DC converter with an Adaptive Perturb and Observe (APO) algorithm-based Maximum Power Point Tracking (MPPT) technology generates steady DC power alternating current, generally by a Brushless Direct Current Motor (BLDCM) motor, to enhance solar Photovoltaic (PV). BLDCM needs solar-powered water pumping. Power conversion causes varying sizes, cost, complexity, and efficiency loss. A single-stage operating solar PV system and BLDC electric pump eliminate the isolated DC–DC converter phase to create a stand-alone solution. A BLDC motor may be controlled using a Voltage Source Inverter (VSI) to drive a solar photovoltaic array at peak power. Dynamic Energy Amendment Control (DEAC) decreases BLDC motor phase current sensing. The DEAC controller automatically regulates the inverter’s PWM based on load fluctuation, therefore speed control is not needed. BLDCM speed control needs are greater because rotor position analysis requires continual self-synchronization feedback. High homeostatic functions absolute or incremental encoders are usually utilized with the BLDCM. BLDCM modelling and simulation should address motor steady-state characteristics, speed reversal, and load tolerance. The DEAC controller simulations offer accurate results under all operating situations. Test results are compared to MATLAB/Simulink results and experimentally verified under real operating circumstances.

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Correspondence to U. Arun Kumar .

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Arun Kumar, U., Chandraguptamauryan, K.S., Chandru, K., Rajan Babu, W. (2023). A Novel Dynamic Energy Amendment Control for Solar Fed Brushless DC Motor for Water Pumping System. In: Suma, V., Lorenz, P., Baig, Z. (eds) Inventive Systems and Control. Lecture Notes in Networks and Systems, vol 672. Springer, Singapore. https://doi.org/10.1007/978-981-99-1624-5_19

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