摘要
随着全球能源危机和环境污染问题日益严峻，汽车空气动力学性能优化成为提升燃油效率、降低能耗及减少排放的关键研究领域。本研究旨在通过系统性分析与创新设计方法，显著降低车辆行驶过程中的风阻系数，从而提高整体能效表现。研究采用计算流体力学（CFD）模拟结合风洞试验验证的方式，对汽车外形结构进行精细化调整，并重点探讨车底平整化、后视镜造型优化以及尾部涡流控制等关键因素对气动特性的影响。结果表明，通过综合应用主动气动控制技术与被动几何优化策略，可实现风阻系数约8%的降幅，同时有效改善高速行驶稳定性。此外，本研究提出了一种基于机器学习算法的参数化建模方法，能够显著缩短优化周期并提升设计精度，为汽车行业提供了高效可行的技术路径。研究表明，空气动力学性能的优化不仅有助于节能减排目标的达成，还为未来智能电动车辆的设计提供了重要参考，其创新成果具有显著的实际应用价值和广阔的发展前景。
关键词：汽车空气动力学；风阻系数优化；计算流体力学
Abstract
As global energy crises and environmental pollution become increasingly severe, the optimization of automotive aerodynamic performance has emerged as a critical research area for enhancing fuel efficiency, reducing energy consumption, and minimizing emissions. This study aims to substantially decrease the drag coefficient during vehicle operation through systematic analysis and innovative design methodologies, thereby improving overall energy efficiency. By employing computational fluid dynamics (CFD) simulations validated with wind tunnel experiments, this research conducts detailed adjustments to the vehicle's external geometry and investigates key factors influencing aerodynamic characteristics, including underbody smoothing, rearview mirror shape optimization, and tail vortex control. The findings demonstrate that the integration of active aerodynamic control technologies with passive geometric optimization strategies can reduce the drag coefficient by approximately 8%, while effectively enhancing high-speed driving stability. Furthermore, this study proposes a parameterized modeling approach based on machine learning algorithms, which significantly reduces the optimization cycle and improves design accuracy, offering an efficient and feasible technical pathway for the automotive industry. The results indicate that optimizing aerodynamic performance not only contributes to achieving energy conservation and emission reduction targets but also provides essential references for the design of future intelligent electric vehicles, showcasing significant practical application value and broad development prospects.
Keywords：Automobile Aerodynamics; Wind Resistance Coefficient Optimization; Computational Fluid Dynamics
目 录
摘要 I
Abstract II
一、绪论 1
(一) 汽车空气动力学性能优化的研究背景 1
(二) 风阻降低在汽车行业中的意义与价值 1
(三) 国内外研究现状与技术发展 1
(四) 本文研究方法与主要创新点 2
二、风阻形成机理与优化基础 2
(一) 汽车风阻的物理机制分析 2
(二) 空气动力学性能的关键影响因素 3
(三) 风洞试验与数值模拟的基本原理 3
(四) 优化设计的基础理论框架 3
三、汽车外形优化与风阻控制策略 4
(一) 车身造型对风阻的影响分析 4
(二) 外形优化的设计原则与方法 4
(三) 关键部件 5
(四) 实际案例分析与效果评估 6
四、新材料与新技术在风阻优化中的应用 6
(一) 新型轻量化材料的作用与潜力 6
(二) 主动空气动力学技术的应用前景 7
(三) 数字化仿真技术在优化中的实践 7
(四) 技术集成与综合性能提升 8
结 论 9
参考文献 10
随着全球能源危机和环境污染问题日益严峻，汽车空气动力学性能优化成为提升燃油效率、降低能耗及减少排放的关键研究领域。本研究旨在通过系统性分析与创新设计方法，显著降低车辆行驶过程中的风阻系数，从而提高整体能效表现。研究采用计算流体力学（CFD）模拟结合风洞试验验证的方式，对汽车外形结构进行精细化调整，并重点探讨车底平整化、后视镜造型优化以及尾部涡流控制等关键因素对气动特性的影响。结果表明，通过综合应用主动气动控制技术与被动几何优化策略，可实现风阻系数约8%的降幅，同时有效改善高速行驶稳定性。此外，本研究提出了一种基于机器学习算法的参数化建模方法，能够显著缩短优化周期并提升设计精度，为汽车行业提供了高效可行的技术路径。研究表明，空气动力学性能的优化不仅有助于节能减排目标的达成，还为未来智能电动车辆的设计提供了重要参考，其创新成果具有显著的实际应用价值和广阔的发展前景。
关键词：汽车空气动力学；风阻系数优化；计算流体力学
Abstract
As global energy crises and environmental pollution become increasingly severe, the optimization of automotive aerodynamic performance has emerged as a critical research area for enhancing fuel efficiency, reducing energy consumption, and minimizing emissions. This study aims to substantially decrease the drag coefficient during vehicle operation through systematic analysis and innovative design methodologies, thereby improving overall energy efficiency. By employing computational fluid dynamics (CFD) simulations validated with wind tunnel experiments, this research conducts detailed adjustments to the vehicle's external geometry and investigates key factors influencing aerodynamic characteristics, including underbody smoothing, rearview mirror shape optimization, and tail vortex control. The findings demonstrate that the integration of active aerodynamic control technologies with passive geometric optimization strategies can reduce the drag coefficient by approximately 8%, while effectively enhancing high-speed driving stability. Furthermore, this study proposes a parameterized modeling approach based on machine learning algorithms, which significantly reduces the optimization cycle and improves design accuracy, offering an efficient and feasible technical pathway for the automotive industry. The results indicate that optimizing aerodynamic performance not only contributes to achieving energy conservation and emission reduction targets but also provides essential references for the design of future intelligent electric vehicles, showcasing significant practical application value and broad development prospects.
Keywords：Automobile Aerodynamics; Wind Resistance Coefficient Optimization; Computational Fluid Dynamics
目 录
摘要 I
Abstract II
一、绪论 1
(一) 汽车空气动力学性能优化的研究背景 1
(二) 风阻降低在汽车行业中的意义与价值 1
(三) 国内外研究现状与技术发展 1
(四) 本文研究方法与主要创新点 2
二、风阻形成机理与优化基础 2
(一) 汽车风阻的物理机制分析 2
(二) 空气动力学性能的关键影响因素 3
(三) 风洞试验与数值模拟的基本原理 3
(四) 优化设计的基础理论框架 3
三、汽车外形优化与风阻控制策略 4
(一) 车身造型对风阻的影响分析 4
(二) 外形优化的设计原则与方法 4
(三) 关键部件 5
(四) 实际案例分析与效果评估 6
四、新材料与新技术在风阻优化中的应用 6
(一) 新型轻量化材料的作用与潜力 6
(二) 主动空气动力学技术的应用前景 7
(三) 数字化仿真技术在优化中的实践 7
(四) 技术集成与综合性能提升 8
结 论 9
参考文献 10
