Page 94 - 《应用声学》2023年第2期

第 42 卷 第 2 期 Vol. 42, No. 2
2023 年 3 月 Journal of Applied Acoustics March, 2023

⋄ 研究报告 ⋄

数值仿真生成的汽车后空调气动噪声预测及评价

黄 毅 † 王伟江 秦 望 谢 然 龙书成 李 智

(广州汽车集团股份有限公司 汽车工程研究院 广州 511434)

摘要：为解决需要项目开发后期样车完成后才能进行整车空调气动噪声性能测试及评价的滞后性问题，针对
某 SUV 整车后空调高档范围工作产生的气动噪声，提出了一种基于空调整车计算流体动力学和 FW-H 声类
比方程的气动噪声仿真计算分析和神经网络的主观评价预测方法。首先采用计算流体动力学和 FW-H 声类比
相结合的方法仿真计算和验证后空调高档运行时车内产生的气动噪声特性；然后将仿真得到的时域气动噪声
样本转化成声频格式，并开发 GUI 程序界面进行噪声样本主观评价和客观参数计算；最后建立基于遗传算法
优化的主客观映射神经网络预测模型以实现车内后空调气动噪声性能的预测评价。仿真计算及预测评价结果
表明：该方法计算的气动噪声仿真误差在 10% 以内，主观预测误差在 0.5 分以内，可有效指导汽车空调气动噪
声性能的前瞻性预测开发。
关键词：汽车空调 HVAC 气动噪声；计算流体动力学建模；FW-H 声类比；神经网络预测；遗传算法
中图法分类号: U462.1 文献标识码: A 文章编号: 1000-310X(2023)02-0282-10
DOI: 10.11684/j.issn.1000-310X.2023.02.011

Prediction and evaluation of aerodynamic noise of automobile rear air conditioner
based on simulation generation

HUANG Yi WANG Weijiang QIN Wang XIE Ran LONG Shucheng LI Zhi

(Automotive Engineering Institute, Guangzhou Automotive Group Co., Ltd., Guangzhou 511434, China)

Abstract: In order to solve the lag problem that the aerodynamic noise performance test and evaluation of
automobile air conditioner can only be carried out after the sample car is completed in the later stage of the
project development, aiming at the aerodynamic noise generated by the high-grade operation of a SUV rear air
conditioner, a method of aerodynamic noise simulation analysis and neural network subjective evaluation pre-
diction based on automobile air conditioner system computational fluid dynamics (CFD) and FW-H acoustic
analogy equation is proposed. Firstly, CFD combined FW-H acoustic analogy is used to simulate and verify
the characteristics of the aerodynamic noise generated in the car when the rear air conditioner is in high-grade
operation. Then the time-domain aerodynamic noise samples obtained by simulation are transformed into
audio format, and the subjective evaluation and objective parameters calculation of noise samples are carried
out through the GUI program interface. Finally, a subjective and objective mapping neural network predic-
tion model based on genetic algorithm optimization is established to predict and evaluate the aerodynamic noise

2021-12-29 收稿; 2022-03-28 定稿
作者简介: 黄毅 (1989– ), 男, 四川巴中人, 硕士, 工程师, 研究方向: 整车 NVH 仿真与测试 (气动和电磁噪声), 电机控制算法。
† 通信作者 E-mail: henryisnow@163.com