基于BA-BP模型的新能源汽车保险杠注塑模具设计及翘曲量优化

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中图分类号：TG76 文献标志码：A

Abstract：Against the backdrop of the continuous increase in global car ownership，energy scarcity，and increasingly severe environmental pollution， new energy vehicles have become the main direction for future transportation development. In the actual injection molding process，defects such as surface dents， shape deformations，and weld marks often occur， which affect product quality. To meet the comprehensive requirements of quality，cost，and durability in the manufacturing of bumper molds， this article proposes an optimization model （BA-BP） that combines neural network（NN）—genetic algorithm （GA） and bat algorithm （BA）.Optimize the initial weights and thresholds of BPNN through BA and embed them into GA to solve for the optimal process parameters. The results indicate that the BA-BP model canimprove prediction accuracy， accurately reflect the trend of warpage changes， and provide reliable fitness evaluation basis for GA， significantly improving the quality stability and efficiency of injection molding.

Key words： new energy vehicles；bumper；injection mould；genetic algorithm

0 引言

汽车注塑零件在成型过程中常常出现翘曲变形问题，其成因复杂，主要受材料特性、零件结构、模具设计及注塑工艺等多种因素影响，是产品开发阶段普遍面临的技术难题1。（剩余6347字）