Dynamic Modeling and Validation of Heat and Mass Transfer Processes in a Cabinet-Type Solar Dryer Using MATLAB/Simulink

Solar drying is a sustainable technology that utilizes renewable solar energy for preserving agricultural and medicinal products. However, the performance of cabinet-type solar dryers is strongly affected by nonlinear heat and mass transfer phenomena, fluctuating environmental conditions, and moisture migration within the drying material. Accurate dynamic modeling is therefore essential for understanding drying behavior and improving system performance. This study presents a dynamic mathematical model of a cabinet-type solar dryer developed in the MATLAB/Simulink environment. The model is formulated using coupled transient heat and mass balance equations describing moisture evaporation, airflow behavior, temperature variation, water vapor transport, and energy transfer within the drying chamber. Key process variables, including solar radiation intensity, drying air temperature, airflow rate, material moisture content, mass transfer coefficient, and vapor partial pressure, were incorporated into the simulation framework. Numerical simulations were performed under different operating conditions to evaluate the dynamic response of the drying process. The simulation results demonstrated that the proposed model successfully captured the temporal evolution of moisture content, drying rate, evaporation dynamics, and energy utilization. The predicted moisture content decreased from approximately 78% to 10%, consistent with typical drying requirements for medicinal plant materials. The analysis revealed that drying air temperature and mass transfer characteristics significantly influenced moisture removal efficiency and drying kinetics. Furthermore, the model accurately represented variations in vapor partial pressure and thermal energy distribution during the drying process. The developed MATLAB/Simulink model provides a reliable tool for analyzing heat and mass transfer processes in cabinet-type solar dryers. The proposed framework can support performance assessment, process optimization, and the future development of advanced control strategies for sustainable solar drying applications.