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Frequency weighting filter design for automotive ride comfort evaluation
Authors:Feng Du
Affiliation:School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou 510640, China
Abstract:Few study gives guidance to design weighting filters according to the frequency weighting factors, and the additional evaluation method of automotive ride comfort is not made good use of in some countries. Based on the regularities of the weighting factors, a method is proposed and the vertical and horizontal weighting filters are developed. The whole frequency range is divided several times into two parts with respective regularity. For each division, a parallel filter constituted by a low- and a high-pass filter with the same cutoff frequency and the quality factor is utilized to achieve section factors. The cascading of these parallel filters obtains entire factors. These filters own a high order. But, low order filters are preferred in some applications. The bilinear transformation method and the least P-norm optimal infinite impulse response(IIR) filter design method are employed to develop low order filters to approximate the weightings in the standard. In addition, with the window method, the linear phase finite impulse response(FIR) filter is designed to keep the signal from distorting and to obtain the staircase weighting. For the same case, the traditional method produces 0.330 7 m ? s–2 weighted root mean square(r.m.s.) acceleration and the filtering method gives 0.311 9 m ? s–2 r.m.s. The fourth order filter for approximation of vertical weighting obtains 0.313 9 m ? s–2 r.m.s. Crest factors of the acceleration signal weighted by the weighting filter and the fourth order filter are 3.002 7 and 3.011 1, respectively. This paper proposes several methods to design frequency weighting filters for automotive ride comfort evaluation, and these developed weighting filters are effective.
Keywords:frequency weighting  ride comfort evaluation  least P-norm optimal method  bilinear transformation  weighting filter design
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