Current Status and Future Prospects of Simulation Technology in Cleaning Systems for Crop Harvesters

The performance of the cleaning system in crop harvesters directly impacts overall operational efficiency and harvest quality. Against the background of traditional design relying on physical experiments—which is costly and provides limited mechanistic insight—Discrete Element Method (DEM), Computational Fluid Dynamics (CFD), and their coupled simulation (CFD-DEM) have become key means for in-depth study of the cleaning process, capable of revealing the complex interactions between particles and between particles and airflow. With the increasingly widespread and deep application of computer simulation technology in agricultural machinery research and development, it is particularly necessary to systematically review its research progress in cleaning systems. Therefore, this study provides a comprehensive and systematic analysis and summary of the key technologies in cleaning system simulation, aiming to address the current gap in systematic reviews of simulation technology in this field. Compared with previous studies that mostly focus on a single method or a specific crop type, this paper systematically reviews the application of three simulation technologies in cleaning systems of various crop harvesters. First, based on the working principle and core operational challenges of cleaning systems, the necessity of applying simulation technology is clarified. Second, the basic principles, modeling processes, and suitable application scenarios and key points for the cleaning simulation of each method are analyzed. Third, typical cases are reviewed to summarize their key achievements in structural innovation, parameter optimization of cleaning devices, and revealing the mechanisms of material separation. Finally, current bottlenecks in simulation applications are pointed out, and future development directions are outlined, including high-precision multi-field coupling, integration with intelligent algorithms, and the construction of digital twin systems. This study aims to provide systematic theoretical reference and methodological support for the innovative design and performance improvement of cleaning systems.