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Active Control of Vehicle Powertrain Noise using Adaptive Notch Filter with Inverse Model LMS Algorithm

Xu, Ji
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447689357

Abstract Details

2015, MS, University of Cincinnati, Engineering and Applied Science: Mechanical Engineering.
Active noise control (ANC) systems have been gaining popularity in the last couple of decades, due to the deficiencies in passive noise abatement techniques. In the future, a novel combination of passive and active noise control techniques may be applied more widely, to better control the interior sound quality of vehicles. In order to maximize the effectiveness of this combined approach, smarter algorithms will be needed for ANC systems. These algorithms will have to be computationally efficient, with high stability and convergence rates. This will be necessary in order to accurately predict and control the interior noise response of a vehicle. Most of current ANC systems are configured with the filtered-x least mean square (FXLMS) algorithm or its modified versions. However, the traditional FXLMS algorithm often exhibits a frequency dependent convergence behavior, which leads to a poor tracking ability for time-varying frequencies, and unbalanced performance at individual harmonics. To improve the ANC system performance, a novel adaptive notch filter with inverse model least means square (ANF-IMLMS) algorithm is proposed in this study, as the basis for active control of vehicle powertrain noise. The proposed algorithm possesses the following two salient features as compared to the filtered-x LMS type algorithms: (1) rapid convergence speed, and (2) good computational efficiency. To verify the analysis, the proposed algorithm is evaluated through numerical simulation, which utilizes the measured powertrain responses. The data is taken under both steady state and transient conditions. Furthermore, a comparative study, between the proposed algorithm and several other newly developed algorithms, is conducted. The controlled results show obvious enhancement in terms of the convergence speed, and noticeable noise reductions for each engine harmonic over a broader frequency range.
Teik Lim, Ph.D. (Committee Chair)
Guohua Sun, Ph.D. (Committee Member)
Jay Kim, Ph.D. (Committee Member)
David Thompson, Ph.D. (Committee Member)
66 p.
Mechanics
Active noise control; Powertrain noise; Adaptive control; Adaptive algorithm; FXLMS

Recommended Citations

Citations

  • Xu, J. (2015). Active Control of Vehicle Powertrain Noise using Adaptive Notch Filter with Inverse Model LMS Algorithm [Master's thesis, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447689357

    APA Style (7th edition)

  • Xu, Ji. Active Control of Vehicle Powertrain Noise using Adaptive Notch Filter with Inverse Model LMS Algorithm. 2015. University of Cincinnati, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447689357.

    MLA Style (8th edition)

  • Xu, Ji. "Active Control of Vehicle Powertrain Noise using Adaptive Notch Filter with Inverse Model LMS Algorithm." Master's thesis, University of Cincinnati, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1447689357

    Chicago Manual of Style (17th edition)

ucin1447689357
966
© 2015, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.