Establishment and Calibration of Discrete Element Model for Buckwheat Seed Based on Static and Dynamic Verification Test

Aiming at the lack of accurate and reliable discrete element simulation parameters for the design of buckwheat metering devices and seeders based on the discrete element simulation method, an accurate buckwheat seed model was obtained by calibrating the discrete element simulation parameters. In this study, buckwheat seed particle models were established based on the manual and automatic filling methods. In order to improve the accuracy of the models, discrete element simulation parameters were calibrated, and the static cylinder-lifting test and dynamic seed-metering test were used to verify the simulation results. A 3D model of buckwheat seed was obtained using the CT scanning method, and a manual filling 7-sphere particle model and an automatic filling multi-sphere particle model were established. The physical parameters and contact parameters were measured using the uniaxial compression test, the drop test, and the friction coefficient measurement test. The Plackett–Burman test and steepest ascent path were used to obtain the optimal parameter combination based on the static cylinder-lifting test. We conducted dynamic seed-metering tests using the two particle models under the optimal parameter combination. The results show that, compared with the measured values of stacking angle, the relative errors of the simulation values of the manual filling 7-sphere and automatic filling 36-sphere particle models are 1.04% and 0.50%, respectively. When the rotation speed range of the seeding wheel is 20~60 r/min, the average relative errors between the simulated value and the measured value are 15.85% and 4.69%, respectively. When the effective working length range of the seeding wheel is 20~40 mm, the average relative errors between the simulated value and the measured value are 22.18% and 9.07%, respectively. Regardless of whether the manual filling 7-sphere or the automatic filling 36-sphere particle model of buckwheat seed was used for static motion parameter simulation or dynamic motion simulation, the automatic filling 36-sphere particle model has a higher accuracy. The buckwheat seed particle model established in this study will provide support for the design of buckwheat special seed-metering devices and improve the quality of buckwheat mechanized sowing operation.