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Adaptive tracking of road vehicle engine speed based on acceleration measurements

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Języki publikacji
EN
Abstrakty
EN
The paper presents adaptive approach to a method of vehicle engine speed tracking based on acceleration measurements which are taken in the vehicle body part. Engine-induced vibrations, which are acquired using a vehicle measurement system, as strongly nonlinear can be modelled using multi-notch filter. It was stated the optimal parameter of the multi-notch filter exists; however, solution space function of the optimization problem is significantly nonlinear. For such conditions adaptive LMS algorithm, which includes multi-notch filter, tends to converge to local minimum points of the solution space. Cross-correlation estimation of multi-notch filter output and its delayed version as well as power estimation of engineinduced acceleration signal were used to tune online an adaptation constant of LMS algorithm and bandwidth parameter of multi-notch filter. Results obtained for stationary and nonstationary engine-induced vibrations justified high accuracy of the tracking algorithm.
Twórcy
autor
  • Institute of Automatic Control, Faculty of Automatic Control, Electronics and Computer Science, Silesian University of Technology, Gliwice
Bibliografia
  • 1. Peng H., et al.: The adaptive filtering of engine transient rotating seed signals. W: Proc. of IEEE 10th Int. Conf. “Signal Processing”. 24-28 October 2010, s. 279-282.
  • 2. Krauze P.: Adaptive filtering of engine vibration in a vehicle measurement system. In: Proc. of 14th Int. PhD Workshop OWD2012. Wisła, 20-23 October 2012.
  • 3. Bin X., et al.: The improved active control algorithm for marine diesel two-stage vibration isolation system. W: Proc. of 14th Int. Congress “Sound and Vibration”. Cairns, Australia, 9-12 July 2012.
  • 4. Ogonowski Z.: Quality control of semi-active systems. W: Proc. of 13th IEEE/IFAC Int. Conf. “Methods and Models in Automation and Robotics”. Szczecin, 2007.
  • 5. Pereira R. R., et al.: Harmonic detection with LMS adaptive notch filter and transient detection. W: Proc. of Brazilian IEEE Int. Conf. „Power Electronics”. 11-15 September 2011, s. 142-146.
  • 6. Bertran E., Montoro G.: Adaptive suppression of narrow-band vibrations. W: Proc. of 5th Int. IEEE Workshop “Advanced Motion Control”. Coimbra, Portugal, 29 June – 1 July 1998, s. 288-292.
  • 7. Amin M. G.: A frequency-domain LMS comb filter. “IEEE Trans. Cirtuits and Systems” December 1991, nr 38(12), s. 1573-156.
  • 8. Laguna P., et al.: The adaptive linear combiner with a periodic-impulse reference input as a linear comb filter. “Signal Processing” 1996, nr 48, s. 193-203.
  • 9. Tan L., Jiang J., Wang L.: Adaptive harmonic IIR notch filters for frequency estimation and tracking. W: “Adaptive Filtering”, ISBN 978-953-307-158-9. Croatia: InTech, September 2011, chapter 13, s. 313-331.
  • 10.Krauze P.:Skyhook control of front and rear magnetorheological vehicle suspension. In: Proc. of 13th Int. PhD Workshop OWD2011. Wisła, 22-25 October 2011, s. 380-385.
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Bibliografia
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bwmeta1.element.baztech-8dfd11df-3587-442f-bca2-525aec9ca6ce
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