某中型皮卡发动机冷却风扇布局优化

秦东晨; 刘司司; 单王珍; 李彬; 张泽斌

doi:10.7638/kqdlxxb-2023.0219

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某中型皮卡发动机冷却风扇布局优化

研究专栏——汽车空气动力学 | 更新时间：2026-07-27

- 某中型皮卡发动机冷却风扇布局优化
- Engine cooling fan layout study of a medium size pickup truck
- 空气动力学学报 2024年42卷第7期页码：77-85
- 作者机构：
  
  1. 郑州大学机械与动力工程学院,郑州,450001
  2. 郑州日产汽车有限公司技术中心车型开发部整车技术科,郑州,450000
- 作者简介：
  
  秦东晨（1965—），河南温县人，教授，研究方向：机械结构与多学科优化. Email： dcqin@zzu.edu.cn
  张泽斌*，副教授，博导，研究方向：气动外形优化设计. E-mail： zebin.zhang@zzu.edu.cn
- 基金信息：
- DOI：10.7638/kqdlxxb-2023.0219
  中图分类号： U462.1
- 纸质出版：2024
- 稿件说明：
移动端阅览
秦东晨, 刘司司, 单王珍, 等. 某中型皮卡发动机冷却风扇布局优化[J]. 空气动力学学报, 2024, 42(7): 77−85.

QIN Dongchen, LIU Sisi, SHAN Wangzhen, et al. Engine cooling fan layout study of a medium size pickup truck[J]. 2024, 42(7): 77-85.
秦东晨, 刘司司, 单王珍, 等. 某中型皮卡发动机冷却风扇布局优化[J]. 空气动力学学报, 2024, 42(7): 77−85. DOI： 10.7638/kqdlxxb-2023.0219

QIN Dongchen, LIU Sisi, SHAN Wangzhen, et al. Engine cooling fan layout study of a medium size pickup truck[J]. 2024, 42(7): 77-85. DOI： 10.7638/kqdlxxb-2023.0219.

摘要

冷却风扇作为汽车发动机冷却模块的关键部件，其空间位置直接影响机舱内的流场结构，决定了通过散热器的空气流量，进而影响发动机的散热性能。为了确定既定冷却风扇在某新车型机舱内的最佳布局，以散热器流量及流量波动为目标，以风扇的空间坐标位置为变量，面向流场结构进行了布局优化。首先，通过试验设计方法生成初始设计样本点并进行几何参数化建模；然后，针对实际工况需求，选择关键车速条件，进行发动机舱内流场的CFD仿真，基于仿真结果建立Kriging代理模型；最后，以散热器进口流量和流速标准差为目标进行多目标优化，通过遗传算法获取Pareto最优解集，基于高维参变量可视化技术进行了结果分析，为机舱内零部件的布局决策提供了有价值的参考。研究结果显示了冷却风扇沿车行进方向的位置改变与散热器流量的显著相关性，为新车型冷却风扇的布置方案提供全局最优性的理论支撑。

Abstract

The cooling fan

a critical component of the automotive engine cooling module

holds utmost significance in influencing the engine's cooling efficiency

particularly in high-power diesel engines. Its precise positioning has a direct impact on the flow field structures in the engine compartment

the airflow through the radiator and consequently

the engine's heat dissipation performance. In this study

an optimization method is developed to determine the optimal placement of a cooling fan in a new engine compartment. This method aims to refine the layout and flow field structures by closely examining the radiator flow and flow fluctuations

with the fan's position as the variable. The optimization process begins by generating initial design sample points using experimental design methods

followed by geometric parametric modeling. Next

typical vehicle speeds are selected to simulate flow fields in the engine compartment under actual working conditions. A Kriging surrogate model is then established based on the simulation results. A multi-objective optimization is subsequently carried out

aiming to achieve the desired radiator inlet flow and standard deviation of flow rate. The Pareto optimal solution set is obtained through a genetic algorithm

and the results are analyzed using multi-dimensional parameter variable visualization method

which provides a valuable reference for the layout decision of parts in the cabin. The results demonstrate a significant correlation between the positional change of the cooling fan along the vehicle's travel direction and the radiator flow. This correlation provides theoretical support for the global optimality of the layout scheme of the new model's heat dissipation module.

关键词

Keywords

references

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