基于DEM-CFD的气压式高速玉米播种机工作参数优化与试验

Optimization and Experiment of Operating Parameters for Pneumatic High-speed Maize Seeder Based on DEM-CFD

摘要:

高密度种植、高精度作业与高速度生产已成为现代玉米生产的新范式,对播种装备提出了严苛要求。针对气压式玉米播种机在实际播种中,工作参数与工况匹配不当导致播种合格率下降,难以充分发挥设备性能的问题,本文采用DEM-CFD气固双向耦合方法,从微观尺度阐明种子在排种器中的运移规律和力学特性,确定了气压、进种量和清种间隙为影响播种质量的关键因素。以单粒率为评价指标,以黄淮海地区常见的黄金粮MY73和郑单958为例,通过BoxBehnken正交试验对排种器工作参数进行优化。确定了不同品种种子在不同工作速度下排种器工作参数的最优组合,其中,黄金粮MY73在12km/h下,气压为4.0kPa、进种挡位与清种挡位为7挡时,单粒率达到最佳;郑单958在12km/h下,气压为4.5kPa、进种挡位为8挡、清种挡位为7挡时,单粒率达到最佳。在最优参数组合下进行田间试验,黄金粮MY73与郑单958的田间播种合格率分别达到95.4%与95.7%。试验结果表明,不同品种在不同的工作速度下最优工作参数存在显著差异,该研究为实际播种作业时工作参数选取提供参考,同时为实现智能播种的“一键设定”提供理论依据。

Abstract:

High-density planting, high-precision operation and high-speed production have become the new paradigm of modern corn production, putting forward strict requirements for sowing equipment. Pneumatic maize planters have attracted much attention because they can maintain a high seeding qualification rate even at high speeds. However, sowing operations confronted with three major challenges: unstructured environment, high agronomic constraints, and strong farming seasons, which led to complex and changeable working conditions. Improper matching of operational parameters to conditions reduced seeding quality and underutilized equipment performance. The DEM-CFD gas-solid two-phase coupling method was employed to elucidate seed motion dynamics and mechanical behavior within the seed metering device at the microscale. Air pressure, seed feed rate, and seed cleaning gap were identified as critical factors affecting seeding quality. Using single grain rate as the evaluation metric, the operating parameters were optimized for two representative corn varieties in the Huang-Huai-Hai region (Huangjinliang MY73 and Zhengdan 958) through Box-Behnken response surface methodology. The optimal parameter combinations were determined as follows: for MY73 at 12 km/ h, maximum singulation rate was achieved at 4 kPa air pressure, with seed feed rate and cleaning gap set to Level 7; for Zhengdan 958 at 12 km/ h, optimal performance occurred at 4. 5 kPa air pressure, Level 8 feed rate, and Level 7 cleaning gap. Orthogonal test results demonstrated that air pressure, seed feed rate, and seed cleaning gap had a very significant effect on single grain rate, with obvious interactions between factors; the established regression model fit well and can accurately predict seed discharge performance. Results demonstrated significant variation in optimal parameters across varieties and operating speeds. The research result can provide a reference for parameter selection in practical operations, which can establish a theoretical foundation for automated parameter configuration in intelligent seeding systems.