This paper presents a comprehensive study utilizing 1D CAE simulation to accurately determine the optimal refrigerant charge quantity in both Internal Combustion Engine (ICE) and Electric Vehicle (EV) HVAC systems. By leveraging 1D simulation, we aim to enhance system efficiency, improve cabin comfort, and minimize energy consumption by optimizing the refrigerant charge quantity.
The simulation methodology involves creating detailed models of the HVAC systems encompassing compressors, condensers, evaporators, and expansion valves in 1D CAE. Experimental data, including refrigerant side (temperature, pressure), coolant side (temperature), and airside (temperature) parameters, were collected under controlled conditions. The collected data was used to calibrate and validate the 1D CAE models, ensuring their fidelity to real-world HVAC system behavior. Through iterative simulations, the refrigerant charge quantity was systematically varied, and key performance metrics, such as average vent temperature, sub-cooling, superheat, discharge pressure and suction pressure were analyzed.
By identifying the optimal refrigerant charge quantity based on the simulation results, this study provides valuable insights for optimizing HVAC system performance and reducing energy consumption in both ICE and EV vehicles. The findings can contribute to the development of more efficient and sustainable transportation solutions.