ML techniques increasing the power factor of a compression ignition engine that is powered by Annona biodiesel using SATACOM

利用 SATACOM 技术,通过机器学习方法提高以番荔枝生物柴油为燃料的压燃式发动机的功率因数。

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Abstract

The global production of biodiesel in 2023 amounted to 34 billion liters because compression ignition engines need environmentally friendly fuel alternatives. The research investigates Annona biodiesel in combination with machine learning (ML) and STATCOM (Static Synchronous Compensator) technology to enhance power quality along with noise and vibration control in CI engines. Engine performance testing of diesel and B20-20% Annona biodiesel occurs under controlled conditions at rpm from 1200 to 2400 at which point STATCOM implemented both power factor improvement and current harmonic reduction for enhanced power quality. The B20 blend delivered 1.2400 kW output power while operating at 2400 RPM but generated a lower delivery than diesel engines produced at 4.8 kW. At a torque peak zone between 2100 and 2400 rpm diesel fuel exhibited enhanced performance because it had a better calorific value and reduced viscosity. Tests demonstrated B20 decreased engine vibrations to 16.8 m/s(2) in contrast to diesel's 21.1 m/s(2) level thus indicating enhanced operation smoothness. Engine speed was varied from 40 Hz/1200 rpm to 80 Hz/2400 rpm during vertical testing. The improved combustion process in B20 resulted in reduced noise emissions that followed engine speed and vibration pattern variations. The results of Multiple Linear Regression analysis displayed robust capability through its R(2) scores of 0.883 and 0.947 but Support Vector Machine produced average accuracy with R(2) scores of 0.722 for both parameters1.STATCOM and ML optimization of Annona biodiesel demonstrates evidence that this biodiesel can be used as an acceptable alternative fuel. Engine operation using power quality upgrades from these technologies produces better power quality at reduced vibration and noise levels than standard diesel fuel.

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