Adaptive Motion-Based Tracking Optimization for HVAC (Heating, Ventilating, and Air Conditioning) System Efficiency Enhancement

Abstract

The Heating, Ventilated, and Air conditioning (HVAC) system is mandatory to ensure a comfortable indoor environment in buildings, which controls high temperature ups and downs. However, high installation costs, energy consumption and noise production are considered as the boundaries of the HVAC system, which shows the impact on the efficiency of the building. Therefore, the research work employs speed-based tracking optimization HVAC System (MBTO-HVAC) to adapt to the proportional-intended (PI) controller parameters of the HVAC system. In addition, the energy consumption and thermal comfort index of the HVAC system is improved and economic cost function is estimated to reduce computational requirements. Customized controller increases economic performance and assesses thermal conditions of indoor and external temperature. The optimal set point temperature is obtained to increase the energy efficiency performance of the AC system. In particular, the developed algorithm promotes the global optimal value and ignores the local optima to increase the convergence speed, which increases the system efficiency. Eventually, the MbTO-HVAC system receives AC power, air flow rate, CO2 level, and humidity and temperature values. ​​