UIC comfort tests - VTI

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Appendix 2Page 6 (10)Influence of low pass filter on jerkThe filtered lateral acceleration is used as input for the calculation of thederivative. Formula 2 is used for the calculation of the derivative.No filteringPeak at 258231 mheight 2.48 m/s 3Filter 2 HzPeak at 258224 mheight 1.78 m/s 3Filter 1 HzPeak at 258217 mHeight 1.34 m/sec 3Filter 0.5 HzPeak at 258194 mheight 1.31 m/sec 3(two peaks now merged to one)VTI notat 56A-2003
Appendix 2Page 7 (10)1.3.3.3 ConclusionAll filters do have an important consequence on the resultA 0.5 Hz low-pass filter does give unacceptable results?The filter used must be included in the standard rules in order to obtaincomparable results.1.4 Influence of averaging on amplitudes1.4.1 Discussion on taking averagesMother seriesBasic seriesDt:=1/512 sec0.1 s 0.1 s 0.1 s 0.1 sO.4 sec series Kind AO.4 sec O.4 sec O.4 secaverage: 0.4 secondsO.4 sec series Kind BStep: 0.4 secondsaverage: 0.4 secondsStep: 0.1 secondsFigure 14 Model for reducing and average atime histories.This mother series containsmuch more data detail thanis needed.For comfort estimation, allexcept vertical vibrations areonly of interest in the smallfrequency zone 0.5 to 2 Hz.Whether this is also the casefor the parametersdescribing the influence oftransition curves and curves,strictly speaking, isuncertain but likely takinginto account previousanalysis.We can reduce theinformation quantity in thetime series by two ways1. averaging the data series2. applying a low-passfilter.In this chapter, the first method is discussed.From the mother series we construct a basic series with different time basis.Average for 0.1 second , 0.4 second and 1 second.This can be done in two different ways (kind A and kind B).It can be demonstrated that a step = 0.1 second is the only feasible method.All other steps give non useful results (this is in agreement with the P CT rules).1.4.2 Influence of averaging on lateral accelerationApplication of averaging in some examplesVTI notat 56A-2003
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VTI notat 56A • 2003VTI notat 56A
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ContentsPageAbbrivations and Notati
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10.5.1 Transitions 5311 Evaluation
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Abbrivations and NotationsAEAT AEA
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chosen test track with a minimum of
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1.8.2 ModelsThree different models
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3 What does comfort mean in the con
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Representation of passengers’ opi
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4 How comfort evolves with speed4.1
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Each element may provoke a potentia
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5.2.2 Theoretical behaviour of thos
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Nominal acceleration in the horizon
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6 Actual evaluation rulesAll the fo
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Important variancesS 0 = var(y)Sr =
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7 Choice of the test zone7.1 Choice
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9.008.007.006.00roll velocity5.004.
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8 Description of the test8.1 The tr
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8.3.3 Synchronisation between votes
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8.5 Registration of data, calculati
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DRIVER CAB8.6.2 Occupied places2224
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9.3 Study of the car body angle9.3.
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9.4.2 Influence of length of the co
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9.4.4 Additional discomfort due to
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10.1.1 ConclusionsThe actual distri
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10.3 Seat positionThe influence of
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Average votes for the different tra
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Figures 10-5 to 10-10 show the infl
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Influence by roll velocity on voteA
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5.0Influence by Pct on voteAll cate
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11 Evaluation of local comfort11.1
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11.1.4 Scaling of votesThe N’ VA
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Note that very high values of later
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554433N'vaN'va221100 1 2 3 4Lateral
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Multiple regressions have therefore
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With the 1.0-second window, the jer
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The regression has been repeated wi
Page 74 and 75: (Table 11-12)Object: Simple and adj
Page 76 and 77: simple transitions, and with the re
Page 78 and 79: Table 11-18 Regression for track en
Page 80 and 81: Some characteristic data points of
Page 82 and 83: The probability that all coefficien
Page 84 and 85: Second conclusionThis also proves t
Page 86 and 87: number of real votes3025201510500,2
Page 88 and 89: 11.2.2 ParametersFour parameters we
Page 90 and 91: There are some observations from th
Page 92 and 93: Table 11-30 Two-parameter regressio
Page 94 and 95: Three-parameter regression - N'VA,
Page 96 and 97: The three-parameter regression was
Page 98 and 99: 12 Evaluation of average comfort12.
Page 100 and 101: Table 12-2 shows that the correlati
Page 102 and 103: 3.53.5332.52.5NVA21.5NVA21.5110.50.
Page 104 and 105: Table 12-5 Multiple regression for
Page 106 and 107: This is the preferred result to be
Page 108 and 109: 12.2.5 Density of importance of eac
Page 110 and 111: 13.3 Conclusions in relationship wi
Page 112 and 113: An identical observation can be mad
Page 114 and 115: 13.7.3 Evaluation of local comfort
Page 116 and 117: Appendix 1Page 1 (3)1 Preparing the
Page 118 and 119: Appendix 1Page 3 (3)2.5 Publish res
Page 120 and 121: Appendix 2Page 2 (10)For this progr
Page 122 and 123: Appendix 2Page 4 (10)Vertical accel
Page 126 and 127: Appendix 2Page 8 (10)Red line : 0.1
Page 128 and 129: Appendix 2Page 10 (10)Study of aver
Page 130: Appendix 3Page 2 (2)Evaluation of h
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UIC comfort tests - VTI

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