Snow removal vehicles operate under severe working conditions, and the snowplow mounting frame is a critical structural component responsible for transmitting loads generated during snow-removal operations. To improve material utilization and reduce structural weight without compromising mechanical performance, a lightweight design methodology based on topology optimization was developed. The primary design objective was to achieve at least a 16% reduction in structural mass while maintaining acceptable stress, strain, deformation, and durability performance. First, a three-dimensional model of the mounting frame assembly was established, and finite element analysis was conducted using ANSYS under representative loading conditions. Topology optimization based on compliance minimization with a mass constraint was then performed to identify structurally inefficient regions and generate an optimized material distribution. Based on the optimization results, the mounting frame was reconstructed into a practical and manufacturable CAD model and subsequently re-evaluated through finite element analysis and fatigue assessment. The mass of the mounting frame was successfully reduced from 177.52 kg to 137.77 kg, corresponding to a weight reduction of 22.39%, significantly exceeding the initial design target. Despite this substantial reduction in weight, the maximum stress, strain, and deformation remained within allowable design limits. Furthermore, fatigue analysis predicted no fatigue failure within 1 × 106 loading cycles, while the minimum fatigue safety factor remained greater than unity, confirming the durability and reliability of the redesigned structure. The results demonstrate that topology optimization provides an effective approach for improving material utilization, reducing structural weight, and enhancing the overall structural efficiency of snow-removal equipment. The successful reconstruction of the optimized topology into a manufacturable design further highlights the practical industrial applicability of the proposed methodology.
Xu et al. (Mon,) studied this question.