Design and Optimization of High Ground Clearance Self-Propelled Sprayer Chassis Frame

As an important machine for agricultural application, the upland gap self-propelled sprayer is environmental friendly and operates efficiently. In this paper, the chassis frame, which is one of the important components of the sprayer, is studied and a disconnected longitudinal beam frame with an X-shaped reinforcement beam was designed. The static mechanical properties of the frame under bending, torsion, emergency braking and emergency turning conditions are analyzed by a finite element method, and the optimization idea was proposed. On this basis, the topology optimization method was applied to optimize the crossbeam and the reinforcement beam positions, resulting in a 2.2% reduction in the overall mass of the frame, a 19.4% reduction in the maximum deformation while maintaining a small change in the maximum stress in the bending condition, and a 4.1% and 15.1% reduction in the maximum deformation and maximum stress of the frame in the torsion condition, respectively. The frame section width and thickness parameters were optimized by multi-objective driven optimization. The results showed that the frame mass and maximum stress were reduced by 6.8% and 1.9%, respectively, in the bending condition at the cost of a slight increase in frame deformation.

Automated summary

This paper studies the chassis frame of the upland gap self-propelled sprayer and designs a disconnected longitudinal beam frame with an X-shaped reinforcement beam. The static mechanical properties of the frame under bending, torsion, emergency braking, and emergency turning conditions are analyzed using a finite element method, and an optimization idea is proposed. The topology optimization method is then used to optimize the crossbeam and reinforcement beam positions, resulting in reductions in mass and maximum deformation of the frame under different conditions. The section width and thickness parameters of the frame are optimized through multi-objective driven optimization.