Analysis of thermal characteristics and operating parameters during the food cold chain delivery process

With the rapid expansion of the online food market due to COVID-19, maintaining an optimal temperature for food conditions during delivery has become increasingly crucial. In this study, a numerical model was developed using MATLAB to predict temperature variations and cooling duration in a food cold chain delivery system by considering various parameters. The model was validated through two chamber experiments in a controlled environment and two field experiments under actual delivery conditions. Increasing the number of ice packs from three to five extended the cooling duration by 67.9 %; however, this effect diminished beyond a certain threshold. Lower initial ice pack temperatures slightly increased the cooling duration, but increased the risk of chilling injury. The addition of bottled water increased the cooling duration by 11.2 % because of its higher thermal mass, whereas lower initial water temperatures led to faster warming. External air temperature strongly influenced performance, with cooling duration increasing by 88.0 % as temperature rose from 10 °C to 15 °C. The parcel box volume and wall thickness also significantly affected cooling, with the duration tripling as thickness tripled. This study provides insights into the nonlinear characteristics of refrigerated packaging systems and their parameter optimization. The developed numerical model serves as a practical tool for designing efficient cold chain packaging strategies, minimizing coolant waste, and ensuring food freshness.