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Research Papers

A Computationally Efficient Multichannel Active Road Noise Control System

[+] 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, ML 0018,
Cincinnati, OH 45221

Teik C. Lim

Vibro-Acoustics and
Sound Quality Research Laboratory,
College of Engineering and Applied Science,
University of Cincinnati,
801 Engineering Research Center, ML 0018,
Cincinnati, OH 45221
e-mail: teik.lim@uc.edu

Ming-Ran Lee, Ming-Te Cheng, Wayne Vanhaaften, Takeshi Abe

Transmission, Driveline NVH and Advanced
Technology Development Department,
Ford Motor Company,
2400 Village Road,
Mail Drop 26,
Dearborn, MI 48124

1Corresponding author.

Contributed by the Dynamic Systems Division of ASME for publication in the JOURNAL OF DYNAMIC SYSTEMS, MEASUREMENT, AND CONTROL. Manuscript received February 5, 2013; final manuscript received August 3, 2014; published online August 28, 2014. Assoc. Editor: Qingze Zou.

J. Dyn. Sys., Meas., Control 137(1), 011003 (Aug 28, 2014) (7 pages) Paper No: DS-13-1060; doi: 10.1115/1.4028183 History: Received February 05, 2013; Revised August 03, 2014

A multichannel active noise control (ANC) system has been developed for a vehicle application, which employs loudspeakers to reduce the low-frequency road noise. Six accelerometers were attached to the vehicle structure to provide the reference signal for the feedforward control strategy, and two loudspeakers and two microphones were applied to attenuate acoustic noise near the headrest of the driver's seat. To avoid large computational burden caused by the conventional time-domain filtered-x least mean square (FXLMS) algorithm, a time-frequency domain FXLMS (TF-FXLMS) algorithm is proposed. The proposed algorithm calculates the gradient estimate and filtered reference signal in the frequency domain to reduce the computational requirement, while also updates the control signals in the time domain to avoid delay. A comprehensive computational complexity analysis is conducted to demonstrate that the proposed algorithm requires significantly lower computational cost as compared to the conventional FXLMS algorithm.

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References

Figures

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Fig. 1

Block diagram of the multiple-reference, multiple-channel active road noise control system with the conventional FXLMS algorithm

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Fig. 2

Block diagram of the proposed multiple-reference, multiple-channel active road noise control system with the TF-FXLMS algorithm

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Fig. 3

Normalized computational complexities with M = [1 : 8], K=[1:8],J=6,L=256,I=256. (a) Real multiplications and (b) real additions.

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Fig. 4

Normalized computational complexities with M = 2, K=2,J=[1:10],L=256,I=256. (Keys: solid curve with up-triangle marker , real multiplications and dashed curve with circle marker , real additions.)

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Fig. 5

Normalized computational complexities with M = 2, K=2,J=6,L=[32,64,128,256,512,1024,2048],I=256. (Keys: solid curve with up-triangle marker , real multiplications and dashed curve with circle marker , real additions.)

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Fig. 6

Normalized computational complexities with M = 2, K=2,J=6,L=256,I=[32,64,128,256,512,1024,2048]. (Keys: solid curve with up-triangle marker , real multiplications and dashed curve with circle marker , real additions.)

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Fig. 7

Magnitude and phase response of the secondary path transfer functions. (a) S∧11 (——) and S∧21 (- - -) and (b) S∧22 (——) and S∧12 (- - -).

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Fig. 8

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

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Fig. 9

Multiple coherence function between a set of reference signals and the targeted road noise. (a) Error 1 and (b) error 2.

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Fig. 10

Comparison of ANC results between using the conventional FXLMS algorithm and the proposed TF-FXLMS algorithm with six reference accelerometers. (a) Error 1 and (b) error 2. (Keys: solid line ——, baseline road noise response; dashed line - - - , conventional FXLMS algorithm; and dotted line · · · · · · · , proposed TF-FXLMS.)

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