METHOD FOR ASCERTAINING THE DEFORMATION OF A TIRE SUBJECTED TO AN EXTERNAL STRESS WHILE ROLLING

Abstract

A method for ascertaining the deformation of a tire comprises: fastening to the tire a sensor able to generate a signal sensitive to the movement of the sensor; acquiring (201) a temporal wheel-turn signal Sig.sup.TDR (101) comprising the amplitude of the movement while rolling; determining a reference speed W.sup.reference (202) associated with a portion of the wheel-turn signal Sig.sup.TDR; normalizing (203) the portion of the wheel-turn signal Sig.sup.TDR by a variable which is a function F of W.sup.reference; angularly resampling (204) the portion of the wheel-turn signal Sig.sup.TDR; obtaining the spectral signal (205) of the portion of the normalized and angularly resampled wheel-turn Sig.sup.TDR; defining a spectral variable (206); and identifying the deformation of the tire Def % (207) as a function G of the spectral variable.

Claims

1-15. (canceled)

16. A method for ascertaining the deformation of a tire casing subjected to an external stress in a state mounted on a wheel so as to constitute a pneumatic mounted assembly in rolling state with rotation speed W, the tire casing having a crown in contact with a ground and in revolution about a natural rotational axis, comprising the following steps: fastening at least one sensor to the tire casing at the crown of the tire casing so as to generate at least one output signal sensitive to movement of the at least one sensor in the tire casing; acquiring (201) at least one first temporal signal Sig (101) comprising at least amplitude of the movement while rolling; delimiting the first signal over a number N.sup.TdR of wheel turns so as to construct a wheel-turn signal Sig.sup.TdR; determining (202) at least one reference speed W.sup.reference associated with at least one portion of the wheel-turn signal Sig.sup.TdR; normalizing (203) the at least one portion of the wheel-turn signal by a variable which is a function F of the at least one reference speed W.sup.reference; angularly resampling (204) the at least one portion of the wheel-turn signal; obtaining (205) a spectral signal spect(Sig) of the at least one portion of the normalized and angularly resampled wheel-turn signal; defining (206) at least one spectral variable on the spectral signal spect(Sig); and identifying (207) a deformation Def % of the tire casing as a function G of the at least one spectral variable.

17. The method for ascertaining the deformation of a tire casing subjected to an external stress according to claim 16, wherein the step of determining (202) the reference speed W.sup.reference consists of establishing a ratio of an angular variation to a temporal duration separating two azimuthal positions of the at least one sensor in the tire casing around the natural axis of rotation, from the wheel-turn signal Sig.sup.TDR (101) or from a signal in phase with the wheel-turn signal Sig.sup.TDR (101), according to the following formula: $\begin{array}{cc}{W}^{\mathrm{Reference}}=\frac{\left(\right)}{\left(f\right)}& \left[\mathrm{Math}1\right]\end{array}$ wherein is an angular position and t is a temporal abscissa associated with the angular position.

18. The method for ascertaining the deformation of a tire casing subjected to an external stress according to claim 17, wherein the angular positions of the tire casing are included in the group consisting of an angular position which can be detected from the wheel-turn signal Sig.sup.TDR corresponding to an entry into a contact patch, an exit from the contact patch, or a central position of the contact patch, or any defined angular position from the signal in phase with the wheel-turn signal Sig.sup.TDR.

19. The method for ascertaining the deformation of a tire casing subjected to an external stress according to claim 16, wherein an angular pitch is less than 18 degrees.

20. The method for ascertaining the deformation of a tire casing subjected to an external stress according to claim 16, wherein the at least one spectral variable is identified on a first positive frequency block of the spectral signal spect(Sig).

21. The method for ascertaining the deformation of a tire casing subjected to an external stress according to claim 20, wherein the at least one identified spectral variable is contained in the group consisting of a maximum value, a median value, a mean value, a pass-band of the first block, an area below a curve of the first block, a frequency of the median value, a frequency of the mean value, and a frequency of the maximum value.

22. The method for ascertaining the deformation of a tire casing subjected to an external stress according to claim 16, further comprising a step of aggregating data from the at least one portion of the angularly resampled normalized wheel-turn signal Sig.sup.TDR over at least one sub-portion of the at least one portion of the angularly resampled normalized wheel-turn signal Sig.sup.TDR, the at least one sub-portion of the at least one portion of the angularly resampled normalized wheel-turn signal Sig.sup.TDR becoming the at least one portion of the angularly resampled normalized wheel-turn signal Sig.sup.TDR.

23. The method for ascertaining the deformation of a tire casing subjected to an external stress according to claim 22, wherein the at least one sub-portion of the at least one portion of the wheel-turn signal Sig.sup.TDR is an integral multiple of the wheel turn.

24. The method for ascertaining the deformation of a tire casing subjected to an external stress according to claim 22, wherein the data aggregation step (205) comprises a method selected from the group consisting of a mean over a decile interval, a median, a selection or interval of deciles, methods of interpolation, a weighted or non-weighted mean, and optimization of a parametric model of tire deformation.

25. The method for ascertaining the deformation of a tire casing subjected to an external stress according to claim 16, wherein the at least one sensor is selected from the group consisting of an accelerometer, a piezoelectric sensor, a magnetic sensor, an inductive sensor, and a capacitative sensor.

26. The method for ascertaining the deformation of a tire casing subjected to an external stress according to claim 16, wherein the movement of the at least one sensor is described by acceleration.

27. The method for ascertaining the deformation of a tire casing subjected to an external stress according to claim 26, wherein having phased the wheel-turn signal Sig.sup.TdR (101) with respect to an angular position of the tire casing, a correction Corr is made to the wheel-turn signal Sig.sup.TdR to take account of an effect of terrestrial gravity before the normalization step.

28. The method for ascertaining the deformation of a tire casing subjected to an external stress according to claim 16, wherein the first signal Sig comprises an amplitude of movement in a direction normal to the crown of the tire casing.

29. The method for ascertaining the deformation of a tire casing subjected to an external stress according to claim 16, wherein the function F is proportional to a square of the reference speed W.sup.reference.

30. The method for ascertaining the deformation of a tire casing subjected to an external stress according to claim 16, wherein the function G is a linear function of the at least one spectral variable.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The invention will be better understood upon reading the following description, which is provided solely by way of a non-limiting example and with reference to the accompanying figures, in which the same reference numbers in all cases designate identical parts and in which:

[0063] FIG. 1 shows an overview of the method according to the invention.

[0064] FIG. 2 shows an illustration of a first signal from a sensor.

[0065] FIG. 3 shows the angular resampling of the wheel-turn signal.

[0066] FIG. 4 shows an illustration of the resampled normalized wheel-turn signal.

[0067] FIG. 5 shows an illustration of the final signal after data aggregation over a sub-portion of the wheel-turn signal.

[0068] FIG. 6 is an illustration of the spectral signal spect(Sig) of the wheel turn.

DETAILED DESCRIPTION OF EMBODIMENTS

[0069] FIG. 1 shows an overview of the method according to the invention. From a first signal Sig obtained by temporal acquisition 201 of the amplitude output of a movement sensor during rolling of the tyre casing on which the sensor is mounted, a number of steps are performed following various possible pathways for obtaining a scalar representative of the final deformation of the tyre casing.

[0070] The first pathway comprises, from the temporal signal at the output of step 201, determining a reference speed W.sup.reference 202 of the tyre casing in its mounted assembly configuration, i.e. tyre casing mounted on rim and inflated. Here, the first signal Sig 101 is already delimited over a certain number of wheel turns, 12 to be precise. Consequently, the first signal Sig 101 coincides with the wheel-turn signal Sig.sup.TDR. This reference speed may be an angular speed linked to the natural rotation of the tyre casing around its rotational axis, but it may also be the translation speed per unit length of the tyre casing in the direction of travel thereof. This value may be determined from the wheel-turn signal Sig.sup.TDR but also determined from another signal temporally in phase with the first signal and hence the wheel-turn signal Sig.sup.TDR.

[0071] Then the wheel-turn signal Sig.sup.TDR is normalized 203 from the first signal resulting from step 201 by a function F of the variable W.sup.reference acquired in step 2. After this step 203, a normalized signal is obtained for the movement of the tyre casing in a temporal description.

[0072] The normalized signal must then be angularly resampled in order to find a signal which is angularly periodic to the wheel turn through step 204. Then after this step 204, the result is a signal normalized and angularly resampled over several wheel turns.

[0073] The second pathway comprises, from the first signal Sig which is also the wheel-turn signal Sig.sup.TDR resulting from step 201, angularly resampling the first signal Sig by phasing this first signal by means of the form of the first signal or by having another signal temporally phased with the first signal. The other signal comes from another sensor, or another track of the same sensor, such as the circumferential acceleration of a three-dimensional accelerometer. This angular resampling of the first signal leads to a signal periodic to the wheel turn at the end of step 204.

[0074] After having phased this angular signal using another temporal signal, a reference speed is determined from another temporal signal in phase with the first signal. Preferably, this is the same other signal which was used for angular resampling of the first signal in step 204. Thus a reference speed W.sup.reference is identified at the end of step 202.

[0075] Then the reference speed allows normalizing of the angularly resampled signal from step 204 using a function of the reference speed variable. This gives an angularly resampled normalized signal at the end of step 203.

[0076] Optionally, whichever pathway is taken, the data from the angularly resampled normalized signal resulting from step 204 on the first pathway or step 203 on the second pathway are aggregated. This data aggregation is carried out on a sub-portion of the input signal which is a multiple of a wheel turn, ideally the wheel turn, since the resampled normalized signal is periodic to the wheel turn by its nature. At this level, it is sometimes necessary to resample the aggregated signal resulting from step 207 with a fixed angular pitch in order to perform the above high-quality spectral analysis.

[0077] Alternatively, if the first signal 101 is polluted by known physical phenomena such as an accelerometer signal influenced by terrestrial gravity, it is sometimes usefulalthough not essentialto perform a correction of the first signal for this physical phenomenon in order to limit the parasitic noise generated by the physical phenomenon. This correction may take place at any step between step 201 and 204, but necessarily before the data aggregation step 205, which allows an improvement in the quality of the signal for tyre casing deformation. If correction takes place after the normalization step, the correction must also be normalized so as not to introduce a correction error.

[0078] Then a spectral analysis 205 is performed on the normalized resampled wheel-turn signal in step 204 or 203 depending on pathway, this being periodic to the wheel turn. If the angular pitch is not regular, measurement points should be interpolated over the theoretical points regularly spaced over the signal. In some cases, the spectral analysis step 205 is performed after a data aggregation step 207 which supplies a signal with a fixed angular pitch.

[0079] The spectral signal resulting from step 205 is analysed to extract one or more spectral variables during step 206. Said spectral variable(s) will supply a function G, which in turn will provide a vector, preferably a scalar, as an invariant of the tyre casing deformation in rolling condition subjected to external forces.

[0080] FIGS. 2 to 4 illustrate the method using the second pathway described in the overview of FIG. 1. The illustration is given for an accelerometer fixed at the crown of a tyre casing mounted on the inner liner of the tyre casing. Here, the tyre casing is a MICHELIN CrossClimate in size 265/65R17 under a static load of 800 daN when mounted on a motor vehicle. The mounted assembly was inflated to 3 bar. Measurements were performed during travel of the vehicle on asphalt circuits with varying roughness, under standard conditions of speed and load applied according to the tyre marking. The mounted assembly was situated on the front axle of the vehicle. The measurements here were performed mostly in straight-line travel.

[0081] FIG. 2 shows a temporal signal 101 acquired with a signal acquisition frequency of 3200 Hz, allowing very fine discretization of the signal. This therefore records all variations in movement of the acceleration type at the crown of the tyre casing during rolling. This was delimited over 12 wheel turns in order to constitute the wheel-turn signal Sig.sup.TDR.

[0082] The recording in FIG. 2 was performed in an acceleration phase of the vehicle, which is reflected by an increase in the amplitude of the accelerometric signal. The sensor here is a single-axis accelerometer mounted radially relative to the crown of the tyre casing, before creation of the mounted assembly by conventional fixing techniques known in the prior art. The data were transmitted by wireless communication between an electronic device galvanically connected to the accelerometer and a second radiofrequency device placed in the vehicle. In this particular case, the post-processing of the measurements was performed in the vehicle. However, it is quite possible to perform these in the first electronic device equipped with a microcontroller or microprocessor and coupled to sufficient memory space to perform the elementary mathematical operations required by the method.

[0083] Here, the first step consists of determining the reference speed, taking as reference speed the angular rotation speed. For this, the first temporal signal 101 must be phased with a reference azimuthal position of the wheel turn. To this end, the first signal 101 shows regular quite strong falls in amplitude 111, 112 which reflect the passage through the contact patch of the angular sector carrying the accelerometer. Naturally, these downward and upward slopes of the falls 111, 112 represent respectively the entry and exit of the contact patch. The centre of the contact patch is the middle of the interval separating the entry and exit of the contact patch. This centre is assigned the azimuthal position of 0 degrees which will be our azimuthal reference. By taking a second angular reference on the next signal fall 112 for example, the signal 101 is determined for a wheel turn of 360 degrees and a temporal interval associated with this wheel turn. The reference speed W.sup.reference is defined as the ratio of angular variation between the two centres of the contact patch to the temporal interval separating these two azimuthal positions. This reference speed W.sup.reference is assigned to the portion of the signal situated between these two centres of the contact area. Naturally, two non-contiguous falls 111, 115 of the temporal signal 101 could be considered for determining a second reference speed W.sup.reference and assigning the second speed to the portion of the signal 101 situated between the two falls 111, 115.

[0084] FIG. 3 shows the result of the step of angular resampling of the temporal signal 101. Thus, using the determination of the centres of the contact patch for each fall in temporal signal performed in the preceding step, it is easy to phase the temporal signal with the wheel turn over 360 degrees. Then the discretized measurement points are linearly distributed over the wheel turn. Even if an angular positioning error is made at this step, a linear interpolation performed for example during the data aggregation step will smooth out the results and minimize the angular positioning error. In a more sophisticated fashion, a reference speed is evaluated on each wheel turn. It is possible to assign evolving angular speeds to the wheel turn by taking into account reference speeds of contiguous turns. For example, having determined the reference speeds over three consecutive turns, it is possible to assign to the central wheel turn a first reference speed for the first quarter wheel turn, being the barycentric speed of the reference speed of the preceding weighted turn 2 and the reference speed of the current weighted turn 1. The following quarter will have a reference speed being the barycentric speed of the reference speed of the current weighted turn 2 and the reference speed of the preceding weighted turn 1. The third quarter wheel turn will have a reference speed being the barycentric speed of the reference speed of the current weighted turn 2 and the reference speed of the next weighted turn 1. Finally, the last quarter wheel turn will have a reference speed being the barycentric speed of the reference speed of the current weighted turn 1 and the reference speed of the next weighted turn 2. All discretized measurement points are distributed over each quarter wheel turn in proportion to the ratio of reference speeds of each quarter turn to the reference speed of the current turn. Other methods for smoothing the points may also be applied. Here, the spatial discretization of points is not regular because of the variable rolling speed. It is quite possible to make this discretization of points of signal 102 regular by applying a method of interpolating measurement points over a given angular distribution for the wheel turn. This then provides an angularly resampled signal 102 with a regular angular pitch. FIG. 3 shows the angularly resampled signal 102 which is periodic to the wheel turn with arbitrary discretization of measurement points.

[0085] FIG. 4 shows the result of the step of normalizing the first angularly resampled signal 102 without interpolation of points. Thus, using the periodicity to the wheel turn of the first resampled signal, it is easy to break down the angular signal over a wheel turn or over a multiple of the wheel turn as illustrated in FIG. 4, here 12 wheel turns. The normalization step consists of dividing the amplitude of the signal by a function of the reference speed associated with each portion of a wheel turn. The reference speed was determined during the first signal processing step 101 for example. The function used here is the square of the reference speed, the reference speed being an angular speed. The result observed on curves 103 and 103bis is that the amplitude of the normalized signal is similar for each wheel turn. We no longer see the strong variations in amplitude between the various wheel turns performed at difference speeds and on different roads. Also, the signal is centred on the unit value. Then the wheel turn segments are superposed over the same angular interval of a length which is an integral multiple of 360 degrees, as shown by the grey curves which here form a curve bundle 103. This takes into account the spread of measurements between the wheel turns, which is accentuated by the fact that the signals have not been corrected for terrestrial gravity. However, if a low-pass filter is applied, we obtain black curve 103bis which is smoother since cleaned of parasitic noise. This allows us to see that signal 103bis is periodic to the wheel turn with slight variations between wheel turns. At the end of this normalization of signal 102, we obtain an angularly resampled normalized signal 103. FIG. 4 shows the angularly resampled normalized signal 103 which is centred on the unit value, as confirmed by the filter applied to curve 103bis.

[0086] FIG. 5 is the result of the step of aggregation of the data from signal 103 from the preceding step, which is an optional step. Here, the segments of each wheel turn are superposed over the same angular interval of a length of 360 degrees, as shown by the grey curves which here form a curve bundle 104. This takes into account the spread of measurements between each wheel turn, which is accentuated by the fact that the signals have not been corrected for terrestrial gravity. However, if we apply a correction for terrestrial gravity to each wheel turn before the normalization step, since the accelerometer is here sensitive to terrestrial gravity, data aggregation by a method of the mean over a decile interval determines the curve 104bis, which is much more stable for the wheel turn. This gives a signal for tyre casing deformation subjected to external forces, in particular the static load in this case. This signal 104bis is representative of the measurement of the tyre casing in rolling condition at variable speed on ground of any roughness. This curve is an invariant of the tyre casing in rolling condition under static load in a state mounted on the rim and inflated.

[0087] FIG. 6 shows the spectrum of the angularly resampled normalized wheel-turn signal with a fixed angular pitch of 0.1 degrees which was delimited over 12 wheel turns. In order to limit the high-frequency phenomena, the signal resulting from step 203 in the first pathway or step 204 in the second pathway was first filtered using a low-pass filter of one thirtieth of the wheel turn.

[0088] The filtered signal, or here the signal from the aggregation step in step 207, was then spectrally analysed using a Fourier transformation before obtaining curve 105, which represents the amplitude of the Fourier transformation over a limited frequency band. This curve shows various spectral blocks, a first of which has great amplitude. However, the following blocks are themselves not negligible.

[0089] It is possible to obtain multiple spectral variables from this spectral response 105. In this case we will focus on the first block, but analysis may also take place on the following blocks.

[0090] In order to take account of the sensitivity of the method, FIG. 6 shows a second dotted curve 106 which corresponds to the spectral response of the same sensor fixed to the same mounted assembly, for a different static load and a different inflation pressure, wherein the mounted assembly has been swapped between the front and rear axles of the vehicle. Thus necessarily, the mechanical response of the tyre casing to its two variables, inflation pressure and static load, is different. However, the spectral response shows a similarity in terms of form by a response in the form of successive blocks, the width and height of which are a function of external forces applied to the tyre casing.

[0091] From this, we find that analysis of the first block is sufficiently discriminating to determine the tyre casing deformation following these variations in external forces, although may not be sufficient for weaker variations in external forces applied to the tyre casing.

[0092] The spectral variables such as the maximum value, median value, mean value, pass band, area below the curve associated with the first block, are all potential criteria for differentiation of the tyre casing deformation. But also the frequency of the median value, the frequency of the mean value and the frequency of the maximum value are secondary criteria in the tyre casing deformation which show a much weaker although still discriminating dynamic.

[0093] We can then assign a tyre casing deformation value by means of a function of one or more spectral variables in the form of a vector or scalar, which may in some cases serve as weighting for the various components of the vector. Preferably, it is found that the maximum value 105bis and 106bis of the first block is a very good indicator of the tyre casing deformation, which allows determination of the tyre casing deformation through an affine function of the maximum value of the first block. However, determination of the tyre casing deformation may become more sophisticated if other spectral variables, also linked to secondary spectral blocks, are taken into account.