基于LSTM的油泥模型侧窗区域风噪主动噪声控制

doi:10.19562/j.chinasae.qcgc.2025.01.017

Abstract

Abstract:

When driving on highways， it's necessary to reduce wind noise in the side window areas of a vehicle. 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 tunnel 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 simulation 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.

Key words: reference signal optimization, LSTM, active wind noise control, clay model, wind tunnel experiments

Lina Huang,Dengfeng Wang,Xiaolin Cao,Yang He,Bingtong Huang,Xiaopeng Zhang. Active Noise Control for Clay Model Side Window Wind Noise Based on LSTM[J].Automotive Engineering, 2025, 47(1): 168-177.

Figures/Tables 18

References 35

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车速/ （km·h^-1）	偏航角/ （°）	峰值频段/ Hz	AWNC 关闭/ dB	AWNC 开启/ dB
100	0	120-160	69-77	62-68
140	0	120-160	72-80	70-77
120	＋10	120-160	76-82	73-79
120	－10	120-160	79-85	74-80

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

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