0
Research Papers

Combined Feedforward–Feedback Active Control of Road Noise Inside a Vehicle Cabin

[+] Author and Article Information
Jie Duan, Mingfeng Li

Vibro-Acoustics and Sound
Quality Research Laboratory,
College of Engineering and Applied Science,
University of Cincinnati,
801 Engineering Research Center,
2901 Woodside Drive, P.O. Box 210018,
Cincinnati, OH 45221-0018

Teik C. Lim

Vibro-Acoustics and Sound
Quality Research Laboratory,
College of Engineering and Applied Science,
University of Cincinnati,
801 Engineering Research Center,
2901 Woodside Drive, P.O. Box 210018,
Cincinnati, OH 45221-0018
e-mail: teik.lim@uc.edu

Ming-Ran Lee, Wayne Vanhaaften, Takeshi Abe

Powertrain NVH R&D Department,
Research and Advanced Engineering Center,
Ford Motor Company,
Dearborn, MI 48124

Ming-Te Cheng

Powertrain NVH R&D Department,
Research and Advanced Engineering Center,
Ford Motor Company,
Dearborn, MI 48124

1Corresponding author.

Contributed by the Noise Control and Acoustics Division of ASME for publication in the JOURNAL OF VIBRATION AND ACOUSTICS. Manuscript received April 22, 2013; final manuscript received May 11, 2014; published online June 12, 2014. Assoc. Editor: Dr. Corina Sandu.

J. Vib. Acoust 136(4), 041020 (Jun 12, 2014) (8 pages) Paper No: VIB-13-1124; doi: 10.1115/1.4027713 History: Received April 22, 2013; Revised May 11, 2014

Conventional active control of road noise inside a vehicle cabin generally uses a pure feedforward control system with the conventional filtered-x least mean square (FXLMS) algorithm. While it can yield satisfactory noise reduction when the reference signal is well correlated with the targeted noise, in practice, it is not always possible to obtain a reference signal that is highly coherent with a broadband response typically seen in road noise. To address this problem, an active noise control (ANC) system with a combined feedforward–feedback controller is proposed to improve the performance of attenuating road noise. To take full advantage of the feedforward control, a subband (SFXLMS) algorithm, which can achieve more noise attenuation over a broad frequency range, is used to replace the conventional FXLMS algorithm. Meanwhile, a feedback controller, based on internal model control (IMC) architecture, is introduced to reduce the road noise components that have strong response but are poorly correlated with the reference signals. The proposed combined feedforward–feedback ANC system has been demonstrated by a simulation model with six reference accelerometers, two control loudspeakers and one error microphone, using actual data measured from a test vehicle. Results show that the performance of the proposed combined controller is significantly better than using either a feedforward controller only or a feedback controller only, and is able to achieve about 4 dBA of overall sound pressure level reduction.

FIGURES IN THIS ARTICLE
<>
Copyright © 2014 by ASME
Your Session has timed out. Please sign back in to continue.

References

Figures

Grahic Jump Location
Fig. 1

Relative power spectral density of the top ten largest uncorrelated principle components

Grahic Jump Location
Fig. 2

Multiple coherence function and potential maximum noise reduction in decibels of the best set of six accelerometers, along with sound pressure level of a typical road noise. (Keys: solid line —, sound pressure level of typical road noise, labeled as the left y-axis; dashed - - - -, multiple-reference function, labeled as the right y-axis; dotted · · · · , potential maximum noise reduction; and shadow area , frequency range that has high SPL of road noise but low multiple coherence value.)

Grahic Jump Location
Fig. 3

Block diagram of the proposed combined feedforward–feedback active road noise control system

Grahic Jump Location
Fig. 4

Feedforward control part of the proposed active road noise control system based on SFXLMS algorithm

Grahic Jump Location
Fig. 9

Control result of the feedback control system alone. (Keys: solid line —, baseline road noise response; and dotted line · · · · , feedback control system alone.)

Grahic Jump Location
Fig. 8

Comparison between the feedforward control result by using the SFXLMS algorithm and the potential maximum noise reduction. (Keys: black solid line —, baseline road noise response; dashed line - - - -, SFXLMS algorithm; and gray solid line , potential maximum noise reduction.)

Grahic Jump Location
Fig. 7

Comparison of the feedforward control results between the SFXLMS algorithm and the conventional FXLMS algorithm. (Keys: solid line —, baseline road noise response; dashed line - - - -, SFXLMS algorithm; and dotted line · · · · , conventional FXLMS algorithm.)

Grahic Jump Location
Fig. 6

IRF and FRF of the measured secondary path: (a) IRF and (b) FRF

Grahic Jump Location
Fig. 5

Feedback control part of the proposed active road noise control system based on IMC architecture with FXLMS algorithm

Grahic Jump Location
Fig. 10

Comparison of the control results between the proposed combined feedforward–feedback control system and the feedforward control system alone with the SFXLMS algorithm. (Keys: solid line —, baseline road noise response; dashed line - - - -, combined feedforward–feedback control system; and dotted line · · · · , feedforward control system alone with the SFXLMS algorithm.)

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In