Establishment and validation of a negative pressure prediction model for rice air-suction seed-metering device

The negative pressure of the rice air-suction seed metering device has a significant impact on the accuracy, efficiency, uniformity, low damage, and protection of sowing. However, there is a lack of convincing research on predicting the negative pressure. A fast, efficient, and concise method for predicting the negative pressure needs to be urgently studied. To address this issue, a negative pressure prediction model was proposed. Firstly, the most essential equation of the negative pressure prediction model was derived by analysis of the air-suction principle. Secondly, the rice seed gravity G of the equation was fitted to be a function by calculus and weighted average. Afterwards, the air-suction force F_a of the equation was fitted to be a function by the CFD-DEM simulation experiment. To obtain a relatively simple and accurate fitting function, the linear fitting function was chosen to represent the relationship between the air-suction force and the negative pressure. Then, the impact levels of negative pressure and rotation speed are determined to be 400–800 Pa and 30–60 r·min⁻¹, respectively. The equivalent coefficient ψ of the equation was calculated to be 2.73 by orthogonal experiment and parameter target optimisation. Finally, the applicability of the pressure prediction model was verified by the verification experiment. The result shows that the prediction model can effectively predict the negative pressures corresponding to various rice seeds. This study provides a theoretical foundation, technical accumulation, and scientific guidance for the subsequent optimisation design of the rice air-suction seed-metering device.