A fast numerical formulation for simulating vehicle compartment acoustics

Sorosiak, Eric J.; Li, Mingfeng; Lim, Teik C.; Duan, Jie; Abe, Takeshi; Lee, Ming-Ran; Cheng, Ming-Te; Vanhaaften, Wayne

doi:10.3397/1.3140591

Cited by 3 publications

(5 citation statements)

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“…This implies thatŜ H x ð ÞŜ x ð Þ should be as flat as possible over the entire frequency range. By examining the eigenvalue equalization filtered-x least mean square (EE-FXLMS) algorithm [9][10][11][12], it is easily seen that the EE-FXLMS algorithm is a way to flatten the magnitude response ofŜ km x ð Þ for every secondary path in the system by modifying the magnitude in the frequency domain. To maintain the stability, the phase is kept unchanged.…”

Section: Convergence Analysismentioning

confidence: 99%

“…The proposed procedure is outlined as follows [9][10][11][12]: (i) obtain the estimated time-domain impulse response of the secondary path transfer functionŜ km ; (ii) perform the fast Fourier transform (FFT) process to obtainŜ km x ð Þ; (iii) divide each value in the frequency domain by its magnitude, asŜ km x ð Þ=Ŝ km x ð Þ , and then multiply the result by the mean value of the magnitude responses in the frequency range of interest, which may not necessarily be the whole frequency range available; and (iv) compute the modified secondary path impulse response function by using the inverse FFT. The process is repeated for each estimated secondary path.…”

Section: Convergence Analysismentioning

confidence: 99%

“…With increasing passengers' demands for better noise, vibration, and harshness performance, the powertrain response must be treated effectively. One of the countermeasures to tackle powertrain noise is the deployment of an active noise control system [1][2][3][4][5][6][7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, the frequency range of interest can span a broad range. The most common active noise control (ANC) system for harmonic noise is based on filtered-x least mean square (FXLMS) algorithm [1][2][3][4][5][6][7][8][9][10][11][12]. It has been found that the properties of the convergence speed of the FXLMS algorithm are affected by the eigenvalue spread of the autocorrelation matrix of the filtered reference signals [13,14].…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Virtual Secondary Path Algorithm for Multichannel Active Control of Vehicle Powertrain Noise

Duan¹,

Li²,

Lim

et al. 2013

Journal of Vibration and Acoustics

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An enhanced multiple-input multiple-output (MIMO) filtered-x least mean square (FXLMS) algorithm using improved virtual secondary path is proposed as the basis for an active noise control (ANC) system for treating vehicle powertrain noise. This new algorithm is developed to overcome the limitation caused by the frequency-dependent property of the standard FXLMS algorithm and to reduce the variation of convergence speed inherent in multiple-channel cases, in order to improve the overall performance of the control system. In this study, the convergence property of the proposed algorithm is analyzed in the frequency domain in order to yield a better understanding of the physical meaning of the virtual secondary path. In practice, because of the arrangement and sensitivities of the actuators (speakers), transducers (microphones), and physical environment, the magnitude response of the main secondary paths can be very different from each other. This difference will cause difficulty in the overall convergence of the algorithm, which will result in minimal attenuation at some of the channels. The proposed channel equalized (CE) virtual secondary path algorithm is designed to tackle this difficulty by equalizing the mean magnitude level of the main secondary paths and by adjusting other secondary paths correspondingly to keep the coupling effects among the control channels unchanged. The performance of the proposed algorithm is validated by analyzing a two-input two-output active powertrain noise control system.

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Section: Convergence Analysismentioning

confidence: 99%

Section: Convergence Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Virtual Secondary Path Algorithm for Multichannel Active Control of Vehicle Powertrain Noise

Duan¹,

Li²,

Lim

et al. 2013

Journal of Vibration and Acoustics

Self Cite

View full text Add to dashboard Cite

show abstract

“…For vehicle localization, the acoustic sensor is operated in passive manner which only receives the source sound continuously. Numerous papers describe the acoustic properties of the vehicle extensively for the automobile compartment [ 21 ], exhaust system [ 22 ], tire tread [ 23 ], tire/road interaction [ 24 ], etc. Sandberg in particular provided an insightful overview of the tire/road noise emitted by mobile vehicles under various conditions [ 25 ].…”

Section: Introductionmentioning

confidence: 99%

Lightweight Filter Architecture for Energy Efficient Mobile Vehicle Localization Based on a Distributed Acoustic Sensor Network

Kim

2013

Sensors

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The generic properties of an acoustic signal provide numerous benefits for localization by applying energy-based methods over a deployed wireless sensor network (WSN). However, the signal generated by a stationary target utilizes a significant amount of bandwidth and power in the system without providing further position information. For vehicle localization, this paper proposes a novel proximity velocity vector estimator (PVVE) node architecture in order to capture the energy from a moving vehicle and reject the signal from motionless automobiles around the WSN node. A cascade structure between analog envelope detector and digital exponential smoothing filter presents the velocity vector-sensitive output with low analog circuit and digital computation complexity. The optimal parameters in the exponential smoothing filter are obtained by analytical and mathematical methods for maximum variation over the vehicle speed. For stationary targets, the derived simulation based on the acoustic field parameters demonstrates that the system significantly reduces the communication requirements with low complexity and can be expected to extend the operation time considerably.

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Vibro-acoustic computation of irregular cavities using a combined analytical-finite element approach with application to vehicle interior acoustics

Elwali

Lim

2012

IJVNV

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A fast numerical formulation for simulating vehicle compartment acoustics

Cited by 3 publications

References 0 publications

Virtual Secondary Path Algorithm for Multichannel Active Control of Vehicle Powertrain Noise

Virtual Secondary Path Algorithm for Multichannel Active Control of Vehicle Powertrain Noise

Lightweight Filter Architecture for Energy Efficient Mobile Vehicle Localization Based on a Distributed Acoustic Sensor Network

Vibro-acoustic computation of irregular cavities using a combined analytical-finite element approach with application to vehicle interior acoustics

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