arXiv:2503.23315cs.AIcs.CE2025-03被引 39

用AI代理加速汽车设计,从草图到风阻模拟只需几分钟

AI Agents in Engineering Design: A Multi-Agent Framework for Aesthetic and Aerodynamic Car Design

  • 构建多智能体框架,整合视觉语言模型与几何深度学习
  • 将传统数周工作压缩至分钟级,支持快速迭代与全面探索
  • 适合汽车设计、工程优化等需要高效创意生成的场景

本文提出面向工程设计的「设计代理」概念,聚焦汽车设计流程,强调该方法可扩展至其他工程领域。通过将AI驱动的设计代理融入传统工程工作流,实现与工程师的无缝协作,显著提升创造力与效率,大幅缩短设计周期。自动化完成概念草图、风格优化、3D形状检索、生成建模、计算流体动力学(CFD)网格划分及气动仿真等任务,部分环节从数天或数周缩短至分钟级。代理采用先进的视觉-语言模型(VLM)、大语言模型(LLM)和几何深度学习技术,支持快速迭代与全面设计探索。研究基于行业标准基准数据集,涵盖多种经典汽车设计,并使用高保真气动仿真验证结果实用性。此外,设计代理可快速准确预测仿真结果,助力工程师进行更优的设计优化与探索。该研究展示了生成式AI在复杂工程任务中的变革潜力,推动跨学科创新应用。

原文摘要 · Abstract (English)

We introduce the concept of "Design Agents" for engineering applications, particularly focusing on the automotive design process, while emphasizing that our approach can be readily extended to other engineering and design domains. Our framework integrates AI-driven design agents into the traditional engineering workflow, demonstrating how these specialized computational agents interact seamlessly with engineers and designers to augment creativity, enhance efficiency, and significantly accelerate the overall design cycle. By automating and streamlining tasks traditionally performed manually, such as conceptual sketching, styling enhancements, 3D shape retrieval and generative modeling, computational fluid dynamics (CFD) meshing, and aerodynamic simulations, our approach reduces certain aspects of the conventional workflow from weeks and days down to minutes. These agents leverage state-of-the-art vision-language models (VLMs), large language models (LLMs), and geometric deep learning techniques, providing rapid iteration and comprehensive design exploration capabilities. We ground our methodology in industry-standard benchmarks, encompassing a wide variety of conventional automotive designs, and utilize high-fidelity aerodynamic simulations to ensure practical and applicable outcomes. Furthermore, we present design agents that can swiftly and accurately predict simulation outcomes, empowering engineers and designers to engage in more informed design optimization and exploration. This research underscores the transformative potential of integrating advanced generative AI techniques into complex engineering tasks, paving the way for broader adoption and innovation across multiple engineering disciplines.

汽车设计AI代理生成式AI气动优化

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