关键词: 汽车工程；引擎盖刚度；AI 优化；参数化建模；轻量化设计

Abstract: To address the problems of traditional simulation optimization, such as heavy reliance on manual experience, long iteration cycles, and low process automation, this paper proposes an intelligent optimization toolchain method based on large artificial intelligence (AI) models. Taking the automobile hood as the research object, the full-process automation of "modeling–simulation– data processing–AI optimization–result output" is realized by constructing a parametric model for hood stiffness, designing an automated iterative algorithm, and developing a low-code AI optimization configuration interface. Relying on the data analysis and decision-making capabilities of large AI models, the dependence of traditional optimization on algorithms and engineer experience is eliminated. The iteration cycle is drastically shortened by 90%, fills the domestic gap in the integrated application of AI and automotive structural simulation optimization, and provides a reusable technical solution for the intelligent optimization of key automotive components, which can be directly applied to the actual research and development of automotive engineering.

Key words: automotive engineering; hood stiffness; AI optimization; parametric modeling; lightweight design