基于LSTM的油泥模型侧窗区域风噪主动噪声控制

Active Noise Control for Clay Model Side Window Wind Noise Based on LSTM

黄丽那 ¹王登峰 ²曹晓琳 ²贺杨 ²黄禀通 ²张小朋²

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作者信息

1. 吉林大学,汽车底盘集成与仿生全国重点实验室,长春 130022;长春大学机械与车辆工程学院,长春 130022
2. 吉林大学,汽车底盘集成与仿生全国重点实验室,长春 130022
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摘要

汽车在高速公路上行驶时,有必要降低侧窗区域的风噪声.汽车风噪的低频噪声控制可通过主动噪声控制(active noise control,ANC)实现,因此本文提出一种汽车风噪的主动噪声控制方法(active wind noise cancella-tion,AWNC),并针对侧窗区域的输入信号选取合适的参考信号:侧窗振动信号作为参考信号在100～500 Hz频段内与目标噪声的相干性较好.以风洞试验中整车全尺寸油泥模型为研究对象,通过长短期记忆方法(long short-term memory,LSTM)优化选取风噪声的参考信号,再利用FxLMS算法对优选后的参考信号进行AWNC仿真并完成硬件在环试验验证.结果表明:经过优选的参考信号不仅数量减少节约成本,且优选后的参考信号将风噪峰值频段降低了5～15 dB.

Abstract

When driving on highways,it's necessary to reduce wind noise in the side window areas of a ve-hicle.Low-frequency noise control of automobile wind noise can be achieved through Active Noise Control(ANC).Therefore,an Active Wind Noise Cancellation(AWNC)method for automobile wind noise is proposed in this paper.The suitable input signal of the side window area is selected as the reference signal,which shows good coherence with the target noise in the 100-500 Hz frequency range.Taking a full-scale clay model of the vehicle in a wind tun-nel as the research object,the reference signals for wind noise are optimized through the Long Short-Term Memory(LSTM)method.The optimized reference signals are then processed using the FxLMS algorithm for AWNC simula-tion and validated through hardware dSPACE testing.The results show that the optimized reference signals not only reduce the number of sensors needed,thus saving cost,but also decrease the peak frequency band of wind noise by 5-15 dB.

关键词

参考信号优选/LSTM/AWNC/油泥模型/风洞试验

Key words

reference signal optimization/LSTM/active wind noise control/clay model/wind tunnel experiments

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出版年

2025

汽车工程

中国汽车工程学会

汽车工程

CSTPCDCSCD北大核心

影响因子：0.751

ISSN：1000-680X

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