数值仿真生成的汽车后空调气动噪声预测及评价

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

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。

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 prediction 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 prediction model based on genetic algorithm optimization is established to predict and evaluate the aerodynamic noise performance of the rear air conditioner.The results of simulation calculation and prediction evaluation show that the simulation error of aerodynamic noise of this method is less than 10%,and the subjective prediction error is less than 0.5 points,and the proposed method can effectively guide the prospective prediction and development of aerodynamic noise performance of the air conditioner.