A Simulation-Based Comparative Study of Advanced Control Strategies for Residential Air Conditioning Systems

This study presents a simulation-based evaluation of advanced control strategies for residential air conditioning systems, including On–Off, PI, and Model Predictive Control (MPC) approaches. A black-box system model was identified using an ARX(2,2,0) structure, achieving over 90% prediction accuracy (FIT) for indoor temperature and power consumption. Six controllers were implemented and benchmarked in a high-fidelity Simscape environment under a realistic 48-h summer temperature profile. The proposed MPC scheme, particularly when incorporating outdoor temperature gradient logic, reduced energy consumption by up to 30% compared to conventional PI control while maintaining indoor thermal comfort within the acceptable range. This virtual design workflow shortens the development cycle by deferring climatic chamber testing to the final validation phase.