A sensitivity constrained FeLMS algorithm for interior road noise
ID:87 View Protection:ATTENDEE Updated Time:2021-08-19 16:17:08 Hits:443 Oral Presentation

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Abstract
For the adaptive active headrest system of road noise in a vehicle, the secondary source cannot generate sufficiently large sound in the low frequency range, which may lead to excessive amplitude of the control filter causing distortion of the secondary signal, and then affects the system performance. For the feedback system, the performance is also affected by the noise amplification caused by the waterbed effect. A sensitivity constrained filter error LMS (ScFeLMS) adaptive algorithm is proposed in this paper, which can constrain the amplitude of the sensitivity function of the feedback active noise control (ANC) system, thereby suppressing the noise amplification caused by the waterbed effect. The combination of the FeLMS algorithm also suppresses the low frequency output of the controller. Using the transfer functions and noise data measured inside an electric vehicle which is driven on rough road at 50 km/h, the noise reduction performance of the adaptive feedback system and the adaptive hybrid system based on the proposed algorithm is simulated. The results show that the control performance in the target frequency band from 70 Hz to 500 Hz of the adaptive feedback system is similar to that of the multi-channel feedforward system, but the system complexity and cost are significantly reduced, while the hybrid system can significantly improve the noise reduction in the target frequency range.
Keywords
Adaptive algorithm; Feedback system; Hybrid system; Electric vehicle; Road noise control
Speaker
Li Shi
Nanjing University

Submission Author
Li Shi Nanjing University
Chaohui Zhou Nanjing University
Haishan Zou Nanjing University
Kai Chen Nanjing University
Jiancheng Tao Nanjing University
Xu Zhong Shanghai Huawei Technologies Co., Ltd.
Sheng Wu Shanghai Huawei Technologies Co., Ltd.
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Important Date
  • Conference Date

    Nov 01

    2022

    to

    Nov 03

    2022

  • Oct 30 2022

    Draft paper submission deadline

  • Nov 09 2022

    Registration deadline

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