An optimization approach for enhancing energy efficiency, reducing CO2 emission, and improving lubrication reliability in roller bearings using ABC algorithm

Friction and energy waste pose significant challenges in various industrial processes. Lubrication plays a crucial role in reducing friction and optimizing energy consumption. This study focuses on analyzing, simulating and calculation the oil film thickness, friction levels, energy losses, and CO₂ emissions. The objective is to optimize lubrication conditions to enhance performance, improve energy consumption, and maximize lubrication efficiency for rolling bearings in a centrifugal fan. The simulation utilizes ANSYS CFX software, MATLAB programming. The optimal oil viscosity grade is determined based on two objectives by using artificial bee colony algorithm (ABC): minimizing energy consumption (thus reducing CO₂ emission) and achieving the optimal oil film thickness and viscosity ratio. The findings reveal that, under the current lubrication conditions and normal fan operation, energy losses due to oil friction amount to 36.3 MWh per year, with CO₂ emissions resulting from power losses reaching 18,750 kg per year. By transitioning to the optimized oil grade, energy savings of 1.08 MWh per year and a corresponding reduction of 557 kg in CO₂ emissions per year can be achieved.