Intelligent and Energy-Efficient Thermal Regulation using Adaptive Quadratic Fuzzy Logic-Controlled Electrohydrodynamic Environmental Schemes for Microelectronic Cooling Applications

Research from this study suggests that Quantum Fuzzy Logic Controllers (QFLCs) could improve energy efficiency and heat transfer capabilities of ventilation systems when integrated with Electrohydrodynamic (EHD) thermoconvection systems. A two-dimensional open cavity with a square barrier and changing Rayleigh and electric Rayleigh statistics is to be numerically simulated in order to study the interplay of flow, temperature, and electric fields. Optimal thermal gradients with minimal disorder are achieved by the QFLC by real-time adjustment of the electrode voltages. Bypassing grid operation and passing code validation, our numerical model is resilient. A reduction of 25.42% in energy consumption per heat cycle and a reduction of 35.6% in entropy production were the most significant findings. Compared to standard ETHD (64.5%), QFLC increased thermal efficiency to 78.2%, and the Sustainable Energy Index (SEI) increased by over 2.5 times. There has been consistent evidence from studies of different Ra, Rae, Pr, Re, and dielectric permittivity that the average Nusselt number (Nu_avg) increases. The QFLC’s effectiveness and adaptability are demonstrated via error evolution curves, energy efficiency charts, and control input adjustments. It is evident that the model can faithfully depict charge density, streamlines, and isotherms after comparing it to benchmark literature for Ra=10^4 and Rae=550. When it comes to carbon dioxide emissions, EIAs say that HVAC systems are the way to go. More efficient and greener energy use is possible with the help of QFLC in ETHD systems since it speeds up heat transmission and enables smart thermal control.