Methods and systems for estimating road surface condition

Abstract

A method and system for estimating the state of a road surface (40), wherein a monitoring unit (2) is connected to a tire (11) of a vehicle, the monitoring unit (2) including at least one detection element (3) suitable for measuring an amount describing the deformation of the tire (11); the tire (11) is fitted to the wheels (20) of the vehicle and the vehicle is driven so that the tire (11) rotates on a road segment having a road surface (40), wherein the tire (11) deforms in deformation zones (46, 42, 47, 44) due to fitting and driving. For each revolution of the tire (11), it is also specified that: a signal representing the quantity measured during the rotation of the tire (11) is obtained; the signal is frequency filtered in a first frequency band to obtain a first filtered signal, and the signal is frequency filtered in a second frequency band different from the first frequency band to obtain a second filtered signal; the first filtered signal is processed to obtain a value of a first parameter indicating the degree of variation of the first filtered signal in the first frequency band, the processing being performed at a portion of the first filtered signal corresponding to the rolling step of the tire (11), wherein the monitoring unit (2) is located within the deformation zone (46, 42, 47, 44) of the tire (11); the second filtered signal is processed to obtain a value of a second parameter indicating the degree of variation of the second filtered signal in the second frequency band, the processing being performed at a portion of the second filtered signal corresponding to the rolling step of the tire (11), wherein the monitoring unit (2) is located within the deformation zone (46, 42, 47, 44) of the tire (11).

Description

Technical Field

[0001] This invention relates to methods and systems for estimating the condition of road surfaces.

[0002] In particular, the present invention relates to a method and system for estimating the condition of a road surface by means of a monitoring unit associated with vehicle tires. Background Technology

[0003] The following definitions apply in the following description and claims.

[0004] Refer to tire terminology such as "axial", "axially", "radial", "longitudinal", "longitudinal", and "circumferential".

[0005] Specifically, the terms "axial" and "axially" refer to a reference / quantity that is arranged / measured or extended in a direction substantially parallel to the axis of rotation of the tire.

[0006] The terms “radial” and “radially” refer to a reference / quantity that is arranged / measured or extended in a direction perpendicular to the tire’s axis of rotation, that is, in a direction that intersects the tire’s axis of rotation and lies in a plane perpendicular to that axis of rotation.

[0007] The terms “longitudinal” and “longitudinally” refer to a reference / quantity that is arranged / measured or extended tangentially to the tire and substantially perpendicular to the axial and radial directions (i.e., in the direction of travel of the tire / vehicle).

[0008] The terms “circumferential” and “circumferentially” refer to a reference / quantity that indicates a circumferential arrangement / measurement or extension extending around the axis of rotation of the tire.

[0009] The term "contact area" in tire terminology refers to the portion of the tire that contacts the ground when it is mounted on a wheel rim and a predetermined vertical load is applied to it. This contact area typically extends at an angle between 5° and 60°. A value of 0 usually indicates that there is no vertical load on the tire.

[0010] The tire term "entry zone" or simply "entry zone" refers to the portion of the tire that is adjacent to the contact area and located in front of that contact area, relative to the tire's rolling direction. The entry zone typically extends at an angle between 5° and 60°.

[0011] The tire term "leaving area" or simply "leaving area" refers to the portion of the tire that is adjacent to the contact area and immediately follows it in the direction of tire rolling. The leaving area typically extends at an angle between 5° and 60°.

[0012] The term "deformation zone" in relation to a tire mounted on a wheel rim refers to the portion of the tire's surface that undergoes deformation due to the effects of vertical loads acting on it and because the tire is made of an elastically deformable material. The deformation zone may include, for example, or correspond to at least one of the following areas: a contact area, an entry area into the contact area, and a exit area away from the contact area. The deformation zone typically has an angular extension between 5° and 180°.

[0013] As the tire rolls on the ground, the contact area, entry area, exit area, and overall deformation area move along the tire's circumference.

[0014] The term "condition" in relation to road surfaces refers to the condition of the road surface in terms of its surface profile, such as the presence and extent of localized or more or less persistent deviations in the surface profile relative to a smooth reference surface.

[0015] The applicant observed that understanding road conditions is very useful for monitoring and controlling vehicle and tire performance, such as vehicle and tire handling, fuel consumption, rolling resistance, friction, adhesion, and wear.

[0016] This knowledge is also very valuable for monitoring the performance of the road surface itself, such as noise emissions and road damage or deterioration, in order to verify whether the road surface meets the predetermined standards and whether special road maintenance interventions are needed.

[0017] Against this backdrop, the international standard ISO 13473-1 classifies road contour textures into four main categories based on the spatial wavelength of the texture, that is, the distance between the periodically repeating parts of the road contour: Microtexture: The spatial wavelength of the texture is less than 0.5 mm. Macroscopic texture: The spatial wavelength of the texture is between 0.5mm and 50mm. Giant textures: The spatial wavelength of the texture is between 50mm and 0.5m. Unevenness: The spatial wavelength of the texture is between 0.5m and 50m (or up to 100m).

[0018] Generally speaking, micro-texture and macro-texture primarily affect tire / road friction, and consequently tire grip and wear.

[0019] Macro-texture and mega-texture primarily affect road and tire noise as well as tire rolling resistance.

[0020] Furthermore, large textures and unevenness often affect a vehicle's driving comfort, handling, fuel consumption, and wear.

[0021] It is known to use electronic monitoring devices inside tires, which include sensors and other components suitable for obtaining various quantities of information about the tire, such as, for example, temperature, pressure, acceleration, tire rotation speed, vehicle speed, load acting on the tire, etc.

[0022] Vehicle tires can also be used as a tool to obtain information about quantities outside the tires, such as quantities related to the surrounding environment and road infrastructure.

[0023] EP1678019 describes a method and system for determining the roughness of a tire rolling surface using a sensor device associated with the tire. The sensor device includes an accelerometer that provides a first acceleration signal representing the acceleration of the tire at a point during rolling on a road surface. The first acceleration signal is frequency-filtered using a bandpass filter to extract a second signal representing the motion component of the point due to deformation experienced by the tire during rolling. The second filtered signal is processed at a portion corresponding to the tire's rolling step length, in which the point is located in a region adjacent to the contact area where the tire contacts the rolling surface. This processing is performed to provide a current roughness parameter indicating the roughness of the rolling surface on which the tire rotates. The resulting roughness parameter is compared to a reference curve representing the trend of the roughness parameter as the tire's angular velocity changes for different categories of reference roughness. The current angular velocity of the tire during the measurement of the current roughness parameter is taken into account during the comparison.

[0024] Against this backdrop, the applicant recognized the need to provide a method for estimating road surface conditions in a reliable and universal manner.

[0025] The applicant understands that the above requirements can be met by monitoring the amount of deformation experienced by the tires during rotation on a road segment having the described road surface.

[0026] More specifically, the applicant understands that from the signal representing the quantity, the state of the road surface can be estimated based on two values ​​of two different parameters, the two values ​​of the two different parameters representing the degree of change of the quantity under two different frequency band conditions, the degree of change referring to the deformation experienced by the tire in a predetermined deformation zone related to two predetermined spatial wavelength ranges relative to the road surface. Summary of the Invention

[0027] According to a first aspect of the invention, the present invention relates to a method for estimating road surface conditions.

[0028] Preferably, the monitoring unit is configured to be connected to the vehicle's tires.

[0029] Preferably, the monitoring unit includes at least one detection element adapted to measure a quantity describing tire deformation.

[0030] Preferably, the tires are fitted onto the wheels of the vehicle.

[0031] Preferably, the vehicle is configured to operate such that the tires rotate on a road segment having the road surface.

[0032] Preferably, due to the assembly and operation, the tire deforms within the deformation zone.

[0033] Preferably, for each revolution of the tire, a signal representing the quantity measured during the tire's rotation is obtained.

[0034] Preferably, for each revolution of the tire, the signal is frequency filtered within a first frequency band to obtain a first filtered signal.

[0035] Preferably, for each revolution of the tire, the signal is frequency filtered in a second frequency band different from the first frequency band to obtain a second filtered signal.

[0036] Preferably, for each revolution of the tire, the first filtered signal is processed to obtain a value of a first parameter indicating the degree of variation of the first filtered signal within the first frequency band.

[0037] Preferably, the processing is performed at a portion of the first filtered signal corresponding to the tire rolling step, wherein the monitoring unit is located in the deformation zone of the tire.

[0038] Preferably, for each revolution of the tire, the second filtered signal is processed to obtain a value of a second parameter indicating the degree of variation of the second filtered signal within the second frequency band.

[0039] Preferably, the processing is performed at a portion of the second filtered signal corresponding to the tire rolling step, wherein the monitoring unit is located within the deformation zone of the tire.

[0040] Preferably, for each revolution of the tire, the position of a point with the values ​​of a first parameter and a second parameter as coordinates is identified in a two-dimensional space of parameters.

[0041] Preferably, for each revolution of the tire, the road surface condition is determined based on the position of the point within the space.

[0042] According to a second aspect of the invention, the present invention relates to a system for estimating road surface conditions.

[0043] Preferably, the system includes a monitoring unit configured to be connected to the vehicle's tires.

[0044] Preferably, the monitoring unit includes at least one detection element configured to measure an amount describing the deformation of the tire.

[0045] Preferably, when the tire is fitted onto the wheels of the vehicle and the vehicle is running so that the tire rotates on a road segment having the road surface, the tire deforms in the deformation zone due to the fitting and running.

[0046] Preferably, the system includes at least one processing unit, which includes a software module.

[0047] Preferably, for each revolution of the tire, the software module is configured to obtain a signal representing the quantity measured during the tire rotation.

[0048] Preferably, for each revolution of the tire, the software module is configured to perform frequency filtering on the signal within a first frequency band to obtain a first filtered signal.

[0049] Preferably, for each revolution of the tire, the software module is configured to perform frequency filtering on the signal in a second frequency band different from the first frequency band in order to obtain a second filtered signal.

[0050] Preferably, for each revolution of the tire, the software module is configured to process the first filtered signal to obtain the value of a first parameter indicating the degree of variation of the first filtered signal within the first frequency band.

[0051] Preferably, the processing is performed at a portion of the first filtered signal corresponding to the tire rolling step, wherein the monitoring unit is located in the deformation zone of the tire.

[0052] Preferably, for each revolution of the tire, the software module is configured to process the second filtered signal in order to obtain the value of a second parameter indicating the degree of variation of the second filtered signal within the second frequency band.

[0053] Preferably, the processing is performed at a portion of the second filtered signal corresponding to the tire rolling step, wherein the monitoring unit is located within the deformation zone of the tire.

[0054] Preferably, for each revolution of the tire, the software module is configured to identify the position of a point in a two-dimensional space of parameters, using the values ​​of the first parameter and the second parameter as coordinates.

[0055] Preferably, for each revolution of the tire, the software module is configured to determine the road surface condition based on the position of the point in the space.

[0056] The applicant discovered that, starting from the values ​​of the first and second parameters mentioned above, the road surface condition can be reliably estimated and this estimation can be performed independently of the tire's operating conditions (such as, for example, the tire's radius and angular velocity).

[0057] By appropriately selecting the first and second frequency bands based on a first and a second spatial wavelength range relative to the road surface, it is also possible to monitor and control various performance characteristics related to the vehicle, tires, and road surface. For example, if there is interest in monitoring and controlling aerodynamic / road friction and thus tire grip and wear, the first and second frequency bands can be selected based on a first and a second spatial wavelength range corresponding to micro-texture and macro-texture. On the other hand, if there is interest in monitoring and controlling noise from both the road and the tire and / or tire rolling resistance, the first and second frequency bands can be selected based on a first and a second spatial wavelength range corresponding to macro-texture and macro-texture. Furthermore, if there is interest in monitoring and controlling vehicle driving comfort, handling, fuel consumption, and wear, the first and second frequency bands can be selected based on a first and a second spatial wavelength range corresponding to macro-texture and roughness.

[0058] In summary, this achieves the aforementioned goals of reliability and versatility.

[0059] Preferably, the angle of the deformation zone of the tire extends to approximately 40°.

[0060] In a preferred embodiment, the deformation zone of the tire corresponds to the entry zone into the contact area.

[0061] Alternatively, the deformation zone of the tire may correspond to the contact area between the tire and the road surface, or to the departure zone that moves away from the contact area.

[0062] Alternatively, the deformation zone may include an entry zone, a contact zone, and an exit zone. In this case, the deformation zone may extend at an angle of 180°.

[0063] Preferably, the first frequency band is determined based on a first harmonic range of the signal, the first harmonic range of the signal relating to the deformation experienced by the tire, the deformation being associated with a predetermined first spatial wavelength range relative to the road surface.

[0064] Preferably, the second frequency band is determined based on a second harmonic range of the signal, the second harmonic range of the signal relating to the deformation experienced by the tire, the deformation being associated with a predetermined second spatial wavelength range relative to the road surface.

[0065] Preferably, the first spatial wavelength range and the second spatial wavelength range correspond to two different categories of road surface contour texture.

[0066] Preferably, the first spatial wavelength range and the second spatial wavelength range are different from each other and are selected from: a spatial wavelength range between 0.05 mm and 0.5 mm; a spatial wavelength range between 0.5 mm and 50 mm; a spatial wavelength range between 50 mm and 0.5 m; and a spatial wavelength range between 0.5 m and 100 m.

[0067] In a preferred embodiment, the first spatial wavelength range is between 0.5 mm and 50 mm, and the second spatial wavelength range is between 50 mm and 0.5 m.

[0068] In a preferred embodiment, the first harmonic range and the second harmonic range are determined based on the Fourier transform of the signal.

[0069] Preferably, the first harmonic range and the second harmonic range are different from each other.

[0070] Preferably, the first harmonic range and the second harmonic range are adjacent to each other.

[0071] In a preferred embodiment, the parameter space is defined by two vertical axes representing the values ​​of the first parameter and the second parameter, respectively.

[0072] For example, the value of the first parameter can be obtained by performing root mean square, standard deviation, or arithmetic mean calculation on suitable samples of the first filtered signal, and the value of the second parameter can be obtained by performing root mean square, standard deviation, or arithmetic mean calculation on suitable samples of the second filtered signal.

[0073] Preferably, the values ​​of the first parameter and the second parameter are obtained by normalizing one or more quantities. Preferably, these quantities are selected such that the values ​​of the first parameter and the second parameter are independent of specific operating conditions (such as, for example, the angular velocity of the tire and the tire type).

[0074] Preferably, the values ​​of the first parameter and the second parameter are obtained by normalization using a factor proportional to the tire radius.

[0075] Preferably, the quantity measured during tire rotation is the acceleration component experienced by the monitoring unit during tire rolling.

[0076] In a preferred embodiment, the acceleration component is radial.

[0077] In a preferred embodiment, when the quantity measured during tire rotation is a radial acceleration component, the values ​​of the first parameter and the second parameter are obtained by normalizing with a factor proportional to the tire's reference acceleration value.

[0078] Preferably, the reference acceleration value corresponds to the value of the radial acceleration component away from the contact area, that is, at an angle position at least 50° away from the center of the contact area. In other words, the reference acceleration value corresponds to the value of the radial acceleration component outside the tire deformation zone.

[0079] Alternatively, the acceleration component can be longitudinal or axial.

[0080] Preferably, for each revolution of the tire, the road surface condition is determined by comparing the position of the points relative to one or more predetermined point clouds in the space, each point cloud representing the state of a reference road surface in the space.

[0081] Preferably, for each revolution of the tire, the road surface condition is determined by comparing the position of the point relative to one or more reference points in the space, each reference point representing the state of a reference road surface in the space.

[0082] Preferably, a first trend is defined, which involves collecting points identified during multiple tire rotations on the road segment within a first time period and determining the road surface condition on the road segment by analyzing the location of the collected points within the space.

[0083] Preferably, a second trend is defined, which involves collecting points identified during multiple tire rotations on the road segment within a second time period and determining the road surface condition on the road segment by analyzing the location of the collected points within the space.

[0084] Preferably, the second time period is after the first time period.

[0085] Preferably, a comparison is made between a first trend and a second trend in order to monitor possible changes in road surface conditions between the first time period and the second time period.

[0086] Preferably, the at least one detection element includes an accelerometer configured to measure at least one acceleration component experienced by the monitoring unit during tire rotation. Attached Figure Description

[0087] Other features and advantages of the invention will become clear from the following detailed description of some exemplary embodiments of the invention, provided only by way of non-limiting example, and will be made with reference to the accompanying drawings, wherein: - Figure 1 A system for estimating road surface conditions according to an embodiment of the present invention is illustrated schematically; - Figure 2 A radial cross-section of a tire associated with a monitoring unit according to an embodiment of the present invention is shown; - Figure 3 A monitoring unit according to an embodiment of the present invention is illustrated schematically; - Figure 4 An example of a deformed tire is shown schematically; - Figure 5 An example curve representing the radial acceleration component is shown, which can be measured by the accelerometer of the monitoring unit during tire rotation, based on the angular position θ of the accelerometer in the measurement area centered on the contact area and extending at an angle equal to 180°. - Figure 6 It shows Figure 5 The Fourier transform of the signal shown in the harmonic domain; - Figure 7 The first signal after filtering according to the method of the present invention is shown; - Figure 8 The second signal after filtering according to the method of the present invention is shown; - Figure 9 The parameter OLUR is shown. I and OLUR II The space shows point P and three point clouds N1, N2 and N3 representing three reference road surface states; - Figure 10 It shows Figure 9 The parameter space, where the position of point P varies; - Figure 11 The experimental results obtained by the applicant are shown, where the vertical axis represents the value of the proximity parameter Pr obtained for multiple tire rotations on two reference road surfaces associated with the two point clouds N3 and N2; - Figure 12 The experimental results obtained by the applicant are shown, which indicate the probability (“prob” on the vertical axis) of obtaining a specific value (represented on the horizontal axis) close to the parameter Pr in two time periods T1 and T2. - Figure 13 The experimental results obtained by the applicant are shown, where the vertical axis represents the value of the proximity parameter Pr obtained for multiple tire rotations on two reference road surfaces associated with the two point clouds N3 and N2, and the horizontal axis shows the value of the parameter MPD associated with the two road surfaces. - Figure 14 The parameter OLUR is shown. I and OLUR IIThe space contains three point clouds N1, N2, and N3, representing three different states of the reference road surface. Detailed Implementation

[0088] Figure 1 A system 30 for estimating road surface conditions according to an embodiment of the present invention is shown.

[0089] The system 30 includes four monitoring units 2 and a central processing unit 31 located outside the four monitoring units 2.

[0090] In the illustrated embodiment, system 30 is implemented in a vehicle (not shown) with four tires 11, each tire being associated with a corresponding monitoring unit 2. This vehicle could be, for example, an automobile. However, the invention is also applicable to other types of vehicles, such as two- or three-wheeled scooters, motorcycles, tractors, buses, trucks, or light trucks; that is, to vehicles having two, three, four, six, or more wheels distributed on two or more axles.

[0091] Monitoring unit 2 communicates with central processing unit 31.

[0092] The central processing unit 31 may be part of an on-board control computer (not shown) or communicate with such an on-board computer and / or other remote units (e.g., part of road infrastructure).

[0093] Typically, the communication between the monitoring unit 2 and the central processing unit 31 is wireless (e.g., Bluetooth communication).

[0094] The central processing unit 31 is located externally relative to the tire 11 on which the monitoring unit 2 is fixed. The central processing unit 31 can be positioned anywhere within the vehicle, as long as the location is within the coverage area of ​​the wireless signal (e.g., Bluetooth) emitted by the monitoring unit 2.

[0095] For example, the central processing unit 31 may be a box integrated into the vehicle. In another embodiment, the central processing unit 31 may be a personal mobile device (e.g., a smartphone or tablet) of the vehicle driver, which is equipped with suitable applications and / or software modules configured at least to communicate with the monitoring unit 2 and process data received from the monitoring unit 2.

[0096] According to one embodiment, each monitoring unit 2 is fixed on the inner surface of the corresponding tire 11.

[0097] Referring to this embodiment, Figure 2A cross-section of a vehicle wheel 20 is shown, the surface of which includes a tire 11 and a supporting rim 12. The tire 11 is of the so-called "tubeless" type, i.e., without an inner tube. The tire 11 can be inflated via an inflation valve 13, which is positioned, for example, in a groove on the supporting rim 12. The tire 11 includes a carcass structure 16 (not shown in detail), which is shaped according to a generally annular configuration and terminates at two bead structures 14, 14', each formed along the inner edge of the carcass 16 for securing the tire 11 to the supporting rim 12. Beads 14 and 14' include corresponding annular reinforcing elements 15 and 15', referred to as bead cores.

[0098] A belt structure 17, comprising one or more belt strips, is applied to the carcass structure 16 at a radially outer position.

[0099] The tread belt 18 is stacked on the belt structure 17 at a radially outer position. The tread belt is typically formed with longitudinal and / or transverse recesses, which are arranged to define a desired tread pattern.

[0100] Tire 11 also includes two sidewalls 19, 19', which are applied to the tire carcass structure 16 at axially opposite positions.

[0101] The inner surface of the tire 11 is typically covered with a sealing layer 111 (so-called "lining"), which comprises one or more layers of airtight elastomeric material suitable for ensuring the airtightness of the tire 11 itself.

[0102] Preferably, such as Figure 2 As shown, the monitoring unit 2 is arranged on the inner wall of the tire 11 (particularly on the liner 111), which is opposite to the tread strip 18. More preferably, the monitoring unit 2 is arranged approximately at the equatorial plane of the tire 11.

[0103] The monitoring unit 2 is secured to the inner wall of the tire 11 by a suitable fixing element 332. According to an alternative embodiment, the monitoring unit 2 may be integrated into a structure of the tire 11 located in the area of ​​the tread 18 and, for example, integrated into the tread belt 18 itself or integrated between the belt 17 and the tread belt 18.

[0104] like Figure 2 As shown, the following directions can be defined for a tire: radial direction Z, longitudinal direction (or travel direction) X, and axial direction (or lateral direction) Y.

[0105] exist Figure 3 In the illustrated embodiment, each monitoring unit 2 includes a detection section 10, a battery 8, a local processing unit (or CPU) 6 associated with a memory (not shown), a transceiver 7, and an antenna 9.

[0106] The monitoring unit 2 can be of a type currently available on the market, which typically includes temperature and / or pressure sensors and accelerometers or other inertial sensors.

[0107] In the illustrated embodiment, the detection portion 10 of the monitoring unit 2 includes an accelerometer 3, particularly a radial accelerometer, oriented inside the monitoring unit 2 such that its axis is substantially orthogonal to the inner surface of the tire 11. The accelerometer 3 is configured to output acceleration measurements describing the radial deformation experienced by the tire 11 during rolling. Other detection elements suitable for measuring physical quantities describing the deformation of the tire 11 may also be used, such as longitudinal accelerometers, axial accelerometers, strain gauges, etc.

[0108] In the illustrated embodiment, the detection portion 10 of the monitoring unit 2 further includes: a pressure sensor 4 configured to provide a measurement of the internal pressure of the tire 11; and a temperature sensor 5 configured to provide a measurement of the temperature of the tire 11.

[0109] The measurement values ​​provided by the accelerometer 3 are provided to the local processing unit 6.

[0110] The local processing unit 6 is configured to receive and process the measurement values ​​obtained from the detection section 10 by the radial accelerometer 3, the temperature sensor 4, and the pressure sensor 5 via appropriate software and / or firmware modules.

[0111] Specifically, the local processing unit 6 is configured to process the quantities measured by the accelerometer 3 by means of suitable software and / or firmware modules in order to fully implement the method for estimating road surface conditions according to the invention.

[0112] Alternatively, the local processing unit 6 may be configured to implement only a portion of the estimation method according to the invention using suitable software and / or firmware modules, and then transmit the partial results of the processed data to the central processing unit 31 via transceiver 7 and antenna 9, whereby the implementation of the method will be completed.

[0113] Ultimately, the choice of allocating processing between the detection unit 2 and the central processing unit 31 to implement the estimation method of the present invention is a trade-off between several constraints, such as hardware complexity, battery consumption, cost, and the processing power available to the local processing unit 6 of the monitoring unit 2.

[0114] The transceiver 7 is configured to conduct bidirectional communication with a central processing unit 31 via an antenna 9, the central processing unit being specifically configured to communicate with a monitoring unit 2 included within the tire 11. In a preferred embodiment, the transceiver 7 includes a Bluetooth Low Energy (BLE) module.

[0115] The battery 8 supplies electrical energy directly or indirectly to the various components of the monitoring unit 2. In a preferred embodiment, the battery 8 may be a rechargeable battery that obtains electrical energy by absorbing the mechanical energy caused by the rotation of the tire 11.

[0116] According to the estimation method of the present invention, by operating the vehicle, the tires 11 of the corresponding wheels 20 of the vehicle rotate on a road segment having a road surface 40.

[0117] like Figure 4 As illustrated, the tire 11 deforms in the deformation zone 44 due to the assembly and operation.

[0118] In particular, due to the load acting on tire 11 (in Figure 4 (Indicated by the arrow Fz perpendicular to the road surface 40) and the fact that the tire 11 is formed of an elastically deformable material, the tire 11 undergoes deformation.

[0119] This deformation affects the circumferential region 44 of the tire 11 (defined between two circumferential ends 44a, 44b), in which the shape of the tire 11 deviates from a generally circular shape (in... Figure 4 (Indicated by shading).

[0120] A circumferential region 44 is located in the lower portion of the tire 11 facing the road surface 40. The circumferential region 44 includes: a contact region 42 defined between two circumferential ends 42a and 42b; an entry region 46 entering the contact region 42 defined between the two circumferential ends 44a and 42a; and an exit region 47 leaving the contact region 42 defined between the two circumferential ends 42b and 44b.

[0121] Two regions 46 and 47 are adjacent to and located outside the contact region 42. Specifically, the entry region 46 is adjacent to the contact region 42 and is located in front of the contact region with reference to the rolling direction of the tire 11, such that... Figure 4 As indicated by arrow d in the diagram. Conversely, the departure area 47 is adjacent to the contact area 42 and follows the contact area immediately with reference to the rolling direction d of the tire 11.

[0122] The deformable region 44, contact region 42, entry region 46 and exit region 47 as a whole have angular extensions, which can vary according to the size of the tire 11, the inflation pressure and the load acting on the tire 11.

[0123] Typically, the angular extension δ of the deformation region 44 is less than or equal to 180°; the angular extension α of the contact region 42 is between 5° and 60°; the angular extension β of the entry region 46 is between 5° and 60°; and the angular extension γ of the exit region 47 is between 5° and 60°.

[0124] According to the method of the present invention, for each monitoring unit 2, once the vehicle is in operation, a measurement of a quantity describing the deformation of the tire 11 is initiated, in the embodiment of which the quantity is a radial acceleration component measured by an accelerometer 3, which in turn corresponds to the radial acceleration component experienced by the monitoring unit 2 during the rolling of the tire 11.

[0125] Preferably, in order to limit energy consumption, for each revolution of tire 11, the measurement is only performed when the monitoring unit 2 passes through the deformation region 44 or more generally when it passes through the measurement area centered on the contact region 22 and the angle extension is less than or equal to 180° (e.g., about 160° or 180°).

[0126] For example, Figure 5 A curve is shown representing the radial acceleration component that can be measured by the accelerometers 3 of each monitoring unit 2 during the rotation of tire 11 as a function of the angular position θ of the accelerometer 3 in the measurement area centered on contact area 22 and extending at an angle of 180°. Figure 5 In this context, θ=90° represents the angular position of the accelerometer 3 at the center of the contact area 42, θ>90° represents the angular position behind the center of the contact area 42, and θ<90° represents the angular position in front of the center of the contact area 42. Furthermore, θ=0 and θ=180° represent two angular positions of the accelerometer 3 that are diametrically opposed to the center of the contact area 42.

[0127] As can be observed, the curve has a region in which the radial acceleration value tends to be at a nearly constant value (denoted as a in the figure). p (Indicated) oscillations around; and another region where the value of radial acceleration changes drastically. Value a p The average value of the acceleration measured by accelerometer 3 when it is far from the contact area 42 (i.e., outside the deformation area 44 and at least 50° from the center of the contact area 42) corresponds to the tire being substantially undeformed. The region where the radial acceleration value changes abruptly corresponds to the accelerometer 3 approaching, entering, passing through, leaving, and moving away from the contact area 42. This region substantially corresponds to the deformation area 44 (see...). Figure 4 In the deformation zone, the tire undergoes deformation due to contact with the road surface 40 and the compression exerted by the load Fz. Therefore, Figure 5The curve in the figure represents the deformation experienced by tire 11.

[0128] According to the estimation method of the present invention, the following operation is performed for each revolution of the tire 11.

[0129] First, a signal is obtained in a common unit of measurement (e.g., a unit of electricity) representing the radial acceleration measured by the accelerometer 3 during the rotation of the tire 11.

[0130] Preferably, as described above, for each revolution of the tire 11, the measurement is performed only during the period when the monitoring unit 2 passes through the deformation region 44, or more generally, during the period when it passes through the measurement area centered on the contact region 22 and extending at an angle of, for example, 180°.

[0131] The resulting signal (whose trend will be similar to) Figure 5 The trend shown is processed to obtain the Fourier transform of the signal in the harmonic domain.

[0132] As an example, Figure 6 The curve shown represents Figure 5 The Fourier transform of the signal is a function of the number of harmonics (h) of the signal.

[0133] On this curve, a first region I and a second region II can be identified, located at a first harmonic range and a second harmonic range different from the first harmonic range, respectively. The first harmonic range is associated with the deformation experienced by the tire 11, which is associated with a predetermined first spatial wavelength range relative to the road surface 40. Conversely, the second harmonic range is associated with the deformation experienced by the tire 11, which is associated with a predetermined second spatial wavelength range relative to the road surface 40.

[0134] By appropriately selecting the first and second spatial wavelength ranges, different performance characteristics related to vehicles, tires, and road surfaces can be monitored.

[0135] For example, in a preferred embodiment of the invention, the first spatial wavelength range corresponds to the giant texture range relative to the road surface 40 (i.e., it is between 50 mm and 0.5 m), while the second spatial wavelength range corresponds to the macroscopic texture range relative to the road surface 40 (i.e., it is between 0.5 mm and 50 mm).

[0136] This advantageously allows for the monitoring and control of noise from both the road surface 40 and the tire 11, as well as the rolling resistance of the tire 11.

[0137] Once the first and second spatial wavelength ranges have been selected, the following relationship can be used: h = (π R) / λ is derived from the extreme values ​​of the first spatial wavelength range and the extreme values ​​of the second spatial wavelength range, where h represents the number of harmonics being checked, R is the tire radius, and λ is the spatial wavelength being checked relative to the road surface 40.

[0138] Once the first and second harmonic ranges of the signal are identified, the corresponding first and second frequency bands can be derived.

[0139] The extreme values ​​of the first frequency band and the second frequency band can be derived from the extreme values ​​of the first harmonic range and the second harmonic range using the following relationship:

[0140] Where f represents the frequency being checked, h is the number of harmonics being checked, R is the radius of tire 11, and a p It is the centripetal acceleration of the tire 11 when it is inspected and rotated (i.e., the radial acceleration measured by the accelerometer 3 away from the contact area 22, or in other words, the radial acceleration outside the deformation area 44).

[0141] Once the first and second frequency bands have been obtained, the signal representing the radial acceleration measured by the accelerometer 3 during the rotation period of the tire 11 (e.g., Figure 5 As shown, frequency filtering is performed in a first frequency band to obtain a first filtered signal, and frequency filtering is performed in a second frequency band different from the first frequency band to obtain a second filtered signal.

[0142] As an example, Figure 7 and Figure 8 The first filtered signal and the second filtered signal are shown respectively. The filtering is performed in the first frequency band and the second frequency band. Figure 5 The signal is filtered to obtain the first filtered signal and the second filtered signal, and the first frequency band and the second frequency band are based on the signal obtained by filtering the signal. Figure 6 The signal shown is determined by the first harmonic range and the second harmonic range identified by Fourier transform.

[0143] Subsequently, the first filtered signal is processed to obtain a first parameter OLUR indicating the degree of variation of the first filtered signal in the first frequency band. I The value of OLUR. In other words, the first parameter OLUR I Indicates the degree of change in the radial acceleration signal caused by the spatial wavelength relative to the road surface 40 (e.g., a giant texture) belonging to the first range.

[0144] like Figure 7As schematically illustrated by the boxes, the processing is performed at a selected portion of the first filtered signal, corresponding to the rolling step of tire 11, where the monitoring unit 2 is located at the entry region 46. In this example, an angular extension of 40° (where θ ranges from 30° to 70°) is considered for the entry region 46. This angular extension can be fixed (i.e., a priori selected) or it can be based on the signal shape representing the radial acceleration measured by accelerometer 3 and thus representing the operating conditions of tire 11 (e.g., the shape of the signal). Figure 5 Choose from the shapes shown.

[0145] Then, the second filtered signal is processed to obtain the second parameter OLUR. II The value of the second parameter indicates the degree of variation of the second filtered signal within the second frequency band. In other words, the second parameter OLUR... II It indicates the degree of variation in the radial acceleration signal caused by the spatial wavelength relative to the road surface 40, which belongs to the second range (e.g., macroscopic texture).

[0146] like Figure 8 As illustrated by the box diagram, the processing is performed at the portion of the second filtered signal corresponding to the rolling step length of tire 11, where the monitoring unit 2 is located at the entry region 46. In this example, an angular extension of 40° (where θ ranges from 30° to 70°) is considered for the entry region 46. This angular extension can be either fixed (i.e., a priori selected) or based on the signal shape representing the radial acceleration measured by accelerometer 3 and thus the operating conditions of tire 11 (e.g., ...). Figure 5 Use the waveform shown to select.

[0147] According to one embodiment, the first parameter OLUR can be obtained by performing root mean square calculation on suitable samples of the selected portion of the first filtered signal. I The value of .

[0148] For example, the first parameter OLUR I The value can be obtained using the following relation:

[0149] Where ω represents the angular velocity ω of tire 11; ω²R represents the centripetal acceleration of tire 11; R is the radius of tire 11; a i,I Represents the first filtered signal value at the i-th sample, and n represents Figure 7The box indicates the number of samples considered within region 46. The centripetal acceleration of tire 11 can correspond to the radial acceleration measured by accelerometer 3 outside deformation region 44, or it can be estimated as radius R multiplied by the square of angular velocity ω, where angular velocity ω can be determined according to techniques known in the art.

[0150] According to one embodiment, the second parameter OLUR II The value can be obtained by performing root mean square calculation on appropriate samples of the selected portion of the second filtered signal.

[0151] For example, the second parameter OLUR II The value can be obtained using the following relation:

[0152] Where ω represents the angular velocity ω of tire 11; ω²R represents the centripetal acceleration of tire 11 as described above; R is the radius of tire 11, a i,II The value of the second filtered signal at the i-th sample is represented by n, where n represents the value of the second filtered signal at the i-th sample. Figure 8 The box in the middle indicates the number of samples considered within region 46.

[0153] Preferably, in order to calculate the value OLUR I and OLUR II During each revolution of tire 11, the first and second filtered signals are sampled. The sampling frequency is adjusted according to the rolling speed of tire 11 for the revolution being inspected, so as to ensure that the same number of n samples are obtained within the entry area 46, regardless of the rolling speed of tire 11.

[0154] Advantageously, in calculating the value OLUR I and OLUR II During the process, normalization factors (specifically ω²R and R) are selected to ensure that the first parameter OLUR is optimized. I The value of the second parameter OLUR II The value of is independent of specific operating conditions (such as, for example, the tire's angular velocity ω and tire radius R).

[0155] In specific cases, after experimental testing, the applicant may consider applying OLUR. I and OLUR II Two different normalization factors (specifically ω²R and ω²R) are used. ).

[0156] Once OLUR has been calculated as described above I and OLUR IITwo values ​​are then used to obtain a pair of values, OLUR, through a series of post-processing operations (such as scaling, rotation, and translation, detailed below). I and OLUR II .

[0157] Once OLUR has been calculated I and OLUR II These two values ​​define the location of point P in the two-dimensional space of the parameters, wherein point P is identified by the first parameter OLUR. I The value of the second parameter OLUR II The value is used as the coordinate.

[0158] According to the point P in the parameter OLUR I and OLUR II The position within the space is determined, and finally the state of road surface 40 is determined.

[0159] Preferably, for each revolution of the tire 11, the state of the road surface 40 is determined by comparing the position of point P relative to one or more predetermined point clouds in the space, each of the point clouds representing the state of a reference road surface in the space.

[0160] Figure 9 The parameter space is shown, defined by two perpendicular axes, each representing the first parameter OLUR. I The value (x-axis) and the second parameter OLUR II The value of (vertical axis).

[0161] As an example, Figure 9 Three point clouds, N1, N2, and N3, are shown, representing the states of a first, second, and third reference road surface, respectively. These three reference road surfaces have different states, i.e., significantly different levels of smoothness / irregularity. Specifically, the irregularity levels of the first, second, and third reference road surfaces gradually decrease, such that the first reference road surface represents a surface with greater irregularity, while the third reference road surface represents a surface with greater smoothness.

[0162] In the example considered, the applicant experimentally obtained three point clouds N1, N2, and N3 by rolling a tire 11 on three reference surfaces with different values ​​of the parameter MPD (“mean profile depth”), which is a known indicator in the art for defining the texture level of a surface and is defined by the ISO 13473-1 standard. For example, the second reference surface corresponding to point cloud N2 has a parameter MPD of approximately 0.8 mm, while the third reference surface corresponding to point cloud N3 has a parameter MPD of approximately 2.85 mm.

[0163] During the rolling of tire 11 on the three reference surfaces, a pair of values ​​OLUR is calculated for each revolution of the tire using the above relationship. I and OLUR II Furthermore, points corresponding to each pair of values ​​are recorded in a parameter space defined by two vertical axes to obtain three point clouds N1, N2, and N3, where the two vertical axes represent the first parameter OLUR. I The value (x-axis) and the second parameter OLUR II The value (vertical axis), such as Figure 14 As shown schematically.

[0164] like Figure 14 As shown, the three point clouds N1, N2 and N3 can be well distinguished from each other.

[0165] Once this is done by OLUR I and OLUR II After obtaining the three point clouds N1, N2, and N3 within the defined parameter space, a series of post-processing operations are performed, including, for example: value scaling (e.g., a value range between -1 and 1); identifying the separating lines between point clouds N1, N2, and N3 using a specific classification algorithm (e.g., SVM or "Support Vector Machine" type); identifying the origin O where the separating lines intersect; identifying the medoids M1, M2, and M3 associated with the three point clouds; and rotating and translating the point clouds around the origin O such that the line passing through the origin O and the medoid M3 aligns with the axis OLUR. II =0 overlap.

[0166] After these post-processing operations, for each pair of calculated values ​​OLUR I and OLUR II Obtain a pair of values ​​OLUR I and OLUR II And will be determined by the value OLUR I and OLUR II Limited parameter space (e.g.) Figure 14(As shown) is converted to the value OLUR I and OLUR II Limited parameter space (e.g.) Figure 9 and Figure 10 (As shown).

[0167] In the value OLUR I and OLUR II Limited parameter space (e.g.) Figure 9 and Figure 10 As shown in the figure, after the above post-processing operations, the value OLUR I and OLUR II It is presented as a negative value.

[0168] like Figure 9 and Figure 10 As illustrated, for each point cloud N1, N2, N3, three points M1, M2, and M3 representing these point clouds are identified. In the example shown, these three points M1, M2, and M3 are obtained by determining the center points of the three point clouds N1, N2, and N3.

[0169] Therefore, in Figure 9 In the example, the state of the road surface 40 during the rotation of the inspected tire 11 can be calculated based on the position of the line passing through the origin O and point P relative to the line passing through the origin O and center points M1, M2, M3.

[0170] For example, the state of road surface 40 can be determined by determining the proximity parameter Pr, which indicates the proximity / distance of the line passing through the origin O and point P relative to the line passing through the origin O and the three center points M1, M2, M3.

[0171] exist Figure 9 In the case where point P is located at a point passing through the origin O (where OLUR) I =OLUR II =0) and below the line of center point M2, the proximity parameter Pr can be determined according to the following relationship:

[0172] The numerator represents the angle formed by the line passing through the origin O and the center point M3 and the line passing through the origin O and the point P, while the denominator represents the angle formed by the line passing through the origin O and the center point M3 and the line passing through the origin O and the center point M2.

[0173] When point P lies on the line passing through the origin O and the center point M3, the proximity parameter Pr will be equal to 0, while when point P lies on the line passing through the origin O and the center point M2, Pr will be equal to 1.

[0174] When point P lies below the line passing through the origin O and the center point M3, the proximity parameter Pr will be negative.

[0175] On the other hand, point P lies above the line passing through the origin O and the center point M2 (e.g. Figure 10 In the case shown in the illustration, the proximity parameter Pr can be determined according to the following relationship:

[0176] In this fraction, the numerator represents the angle formed by the line passing through the center point M2 and the origin O and the line passing through the point P and the origin O, while the denominator represents the angle formed by the line passing through the center point M2 and the origin O and the line passing through the center point M1 and the origin O.

[0177] Therefore, the proximity parameter Pr will: -If point P lies between the line passing through the origin O and the center point M2 and the line passing through the origin O and the center point M1, it is between 1 and 2; -If point P lies on the line passing through the origin O and the center point M1, it equals 2; - If point P is above the line passing through the origin O and the center point M1, the value is greater than 2.

[0178] Therefore, a proximity parameter Pr value close to 0 indicates that the state of road surface 40 is similar to that of the third road surface (third point cloud N3); a proximity parameter Pr value below 0 indicates that the state of road surface 40 is smoother than that of the third road surface (third point cloud N3); a proximity parameter Pr value close to 1 indicates that the state of road surface 40 is similar to that of the second road surface (second point cloud N2); a proximity parameter Pr value close to 2 indicates that the state of road surface 40 is similar to that of the first road surface (first point cloud N1); and a proximity parameter Pr value above 2 indicates that the state of road surface 40 is less smooth than that of the first road surface (first point cloud N1).

[0179] Therefore, the value of the proximity parameter Pr calculated from this allows for the determination of the degree to which the state of pavement 40 is similar to or dissimilar to the state of one of the three reference pavements.

[0180] Then, by collecting the values ​​obtained for each revolution of the tire from each of the four monitoring units 2 associated with the vehicle, the value of the proximity parameter Pr can be better defined.

[0181] Furthermore, it can calculate the approximation parameter Pr by performing multiple tire rotations and analyze the obtained values ​​to identify road sections with varying degrees of homogeneity. For example, in the case of road sections with homogeneous road conditions, it can identify trends where all calculated values ​​tend to stabilize.

[0182] Then, by collecting values ​​from each of the four monitoring units 2 associated with the vehicle, the trend value can be better defined.

[0183] Through experimental tests conducted on two road surfaces corresponding to point clouds N2 and N3, the applicant found that for multiple rotations of the tire on the same road surface, the value of the proximity parameter Pr calculated as described above is correctly close to 0 for the surface corresponding to point cloud N3, and correctly close to 1 for the surface corresponding to point cloud N2.

[0184] The results obtained from these experimental tests Figure 11 The diagram is schematically shown, where the vertical axis represents the value of the proximity parameter Pr obtained for multiple tire rotations at the third road surface and the second reference road surface, which are respectively associated with point clouds N3 and N2.

[0185] It can be noted that the smoother surface (corresponding to point cloud N3) has a proximity parameter Pr value approaching 0 and lower dispersion of the measured values, while the more uneven surface (corresponding to point cloud N2) has a proximity parameter value approaching 1 and larger dispersion of the measured values ​​due to the greater unevenness of its texture.

[0186] The applicant will also associate the value of the proximity parameter Pr obtained for multiple revolutions of the tire at the third and second reference surfaces associated with point clouds N3 and N2 with the value of the parameter MPD of these surfaces, which is an indicator of the texture level of the surface according to the aforementioned ISO 13473-1 standard.

[0187] exist Figure 13 The results of this correlation are shown in the figure, where a good correspondence is generally observed between the obtained proximity parameter Pr value and the parameter MPD value associated with the inspected surface. In particular, it can be noted that the surface corresponding to point cloud N3 with an MPD of approximately 0.8 mm (representing a generally flat surface) has a proximity parameter Pr value tending to 0, while the surface corresponding to point cloud N2 with an MPD value of approximately 2.85 mm (representing a more uneven surface) has a proximity parameter value tending to 1.

[0188] Therefore, the values ​​of the proximity parameter Pr obtained for these two surfaces are consistent with the value MPD, and allow for a reliable indication of the road surface condition.

[0189] In a preferred embodiment, according to the estimation method of the present invention, it is further specified that points P identified during multiple rotations of the tire 11 on the same road surface 40 within a first time period T1 are collected, and that a first trend of the state of the road surface 40 is determined by analyzing the position of the collected points in the parameter space.

[0190] Subsequently, it is stipulated that points P identified during multiple rotations of the tire 11 on the same road surface 40 within the second time period T2 after the first time period T1 are collected, and the positions of the collected points are analyzed in the parameter space to determine the second trend of the road surface condition.

[0191] Then, a comparison of the first trend and the second trend is specified to monitor possible changes in the condition of the same pavement 40 between the first time period T1 and the second time period T2. This advantageously allows for monitoring of pavement condition at different times and checking for possible deterioration or improvement that may occur over time.

[0192] Through experimental testing conducted on the same road surface 40, the applicant calculated, as described above, the approximate parameter Pr for the number of revolutions of tire 11 over a first time period T1 and a subsequent second time period T2 (several months apart).

[0193] exist Figure 12 The results of these tests are shown in the figure, where the probability of obtaining a specific value (labeled on the horizontal axis) close to the parameter Pr in two time periods T1 and T2 is shown (labeled "prob" on the vertical axis). The central area marked with the reference numerals T1 and T2 represents the overlapping area between the results obtained in the two time periods T1 and T2.

[0194] As can be seen, in the first time period T1, the value of the proximity parameter Pr is close to 0.8, while in the second time period T2, the value of the proximity parameter Pr is higher (approximately 1.1) and has greater dispersion. The left-hand tail in the second time period T2 indicates the possible presence of repaired road sections (therefore associated with the lower value of the proximity parameter Pr), while the right-hand tail in the second time period T2 indicates the possible presence of deteriorated road sections (therefore associated with the higher value of the proximity parameter Pr). In this context, repaired road sections refer to sections that underwent repair work between the two time periods T1 and T2, thus these sections typically exhibit a smoother road surface condition in the second time period T2. Conversely, deteriorated road sections refer to sections that experienced increased unevenness between the two time periods T1 and T2 (e.g., due to wear, weather conditions, traffic accidents, or other reasons).

[0195] As is apparent from this description, the present invention allows for the estimation of road surface conditions in a reliable and universal manner.

[0196] Because a normalization factor is used when calculating the first and second parameters, the estimation can be made independently of the tire's operating conditions, such as its radius and angular velocity.

[0197] This invention also allows for tracking road surface conditions and checking whether they have improved or deteriorated over time.

[0198] Furthermore, by appropriately selecting a first spatial wavelength range and a second spatial wavelength range relative to the road surface, it is possible to monitor and control different performance characteristics relative to the vehicle, tires, and road surface.

[0199] For example, by selecting a first spatial wavelength range and a second spatial wavelength range to correspond to macro-texture and mega-texture, it is possible to monitor the performance of the road surface in terms of noise emissions and surface damage or deterioration, so as to verify whether the road surface meets predetermined standards (e.g., noise emissions) and whether specific road maintenance interventions are required.

[0200] Therefore, tires are used as a tool to obtain information about their external quantities, such as the performance of road sections in terms of noise and integrity.

[0201] The information processed by the estimation method according to the invention can then be transmitted outside the vehicle (e.g., to a remote server) for use by a special road infrastructure management and maintenance system.

Claims

1. A method for estimating the state of a road surface (40), the method comprising: The monitoring unit (2) is associated with the tire (11) of the vehicle, and the monitoring unit (2) includes at least one detection element (3) adapted to measure the amount of deformation describing the tire (11). The tire (11) is fitted onto the wheel (20) of the vehicle and the vehicle is driven so that the tire (11) rotates on a road section having the road surface (40), wherein, due to the fitting and driving, the tire (11) deforms in the deformation zones (46, 42, 47, 44). For each rotation of the tire (11), the method includes: - Obtain a signal representing the quantity measured during the rotation of the tire (11); - The signal is frequency filtered in the first frequency band to obtain a first filtered signal; - The signal is frequency filtered in a second frequency band different from the first frequency band in order to obtain a second filtered signal; - Process the first filtered signal to obtain the value of a first parameter indicating the degree of change of the first filtered signal in the first frequency band, the processing of the first filtered signal is performed at a portion of the first filtered signal corresponding to the rolling step of the tire (11), wherein the monitoring unit (2) is located in the deformation zone (46, 42, 47, 44) of the tire (11); - Process the second filtered signal to obtain the value of a second parameter indicating the degree of change of the second filtered signal in the second frequency band, the processing of the second filtered signal is performed at a portion of the second filtered signal corresponding to the rolling step of the tire (11), wherein the monitoring unit (2) is located within the deformation zone (46, 42, 47, 44) of the tire (11); - In the two-dimensional space of the parameters, identify the position of point (P), the point using the values ​​of the first parameter and the second parameter as coordinates; - Based on the position of the point (P) in the space, determine the state of the road surface (40).

2. The method according to claim 1, wherein, The deformation zones (46, 42, 47, 44) of the tire (11) correspond to the contact area (42) between the tire (11) and the road surface, the entry area (46) into the contact area (42), or the exit area (47) away from the contact area (42).

3. The method according to claim 1 or 2, wherein: The first frequency band is determined based on the first harmonic range of the signal, which is related to the deformation experienced by the tire (11) relative to a predetermined first spatial wavelength range of the road surface (40); and The second frequency band is determined based on the second harmonic range of the signal, which is related to the deformation experienced by the tire (11) relative to a predetermined second spatial wavelength range of the road surface (40).

4. The method according to claim 3, wherein, The first spatial wavelength range and the second spatial wavelength range correspond to two different categories of road surface contour texture.

5. The method according to claim 3 or 4, wherein, The first spatial wavelength range and the second spatial wavelength range are different from each other and are selected from: a spatial wavelength range between 0.05 mm and 0.5 mm; a spatial wavelength range between 0.5 mm and 50 mm; a spatial wavelength range between 50 mm and 0.5 m; and a spatial wavelength range between 0.5 m and 100 m.

6. The method according to any one of the preceding claims, wherein, The quantity measured during the rotation of the tire (11) is the acceleration component experienced by the monitoring unit (2) during the rolling of the tire (11).

7. The method according to any one of the preceding claims, wherein, For each revolution of the tire (11), the state of the road surface (40) is determined by comparing the position of the point (P) relative to one or more predetermined point clouds (N1, N2, N3) in the space, each of the point clouds (N1, N2, N3) representing the state of a reference road surface in the space.

8. The method according to any one of the preceding claims, wherein, For each revolution of the tire (11), the state of the road surface (40) is determined by comparing the position of the point (P) relative to one or more reference points (M1, M2, M3) in the space, each of the reference points (M1, M2, M3) representing the state of a reference road surface in the space.

9. The method according to any one of the preceding claims, wherein, The document specifies the collection of points (P) identified during multiple rotations of the tire (11) on the road segment within a first time period (T1) and specifies a first trend for determining the state of the road surface (40) on the road segment by analyzing the position of the collected points (P) within the space.

10. The method according to claim 9, wherein, The second trend is defined as collecting the points (P) identified during multiple rotations of the tire (11) on the road segment in a subsequent second time period (T2) and determining the state of the road surface (40) on the road segment by analyzing the position of the collected points (P) in the space.

11. The method according to claim 10, wherein, The first trend and the second trend are compared to monitor possible changes in the condition of the road surface (40) between the first time period (T1) and the second time period (T2).

12. A system (30) for estimating the state of a road surface (40), the system comprising: A monitoring unit (2) configured to be associated with a tire (11) of a vehicle, the monitoring unit (2) including at least one detection element (3) configured to measure an amount describing the deformation of the tire (11), wherein, when the tire (11) is mounted on the wheel (20) of the vehicle and the vehicle is driven to rotate the tire (11) on a road section having the road surface (40), the tire (11) deforms in deformation zones (46, 42, 47, 44) due to the mounting and driving; At least one processing unit (6, 31), the processing unit including a software module configured for each revolution of the tire (11) to: - Obtain a signal representing the quantity measured during the rotation of the tire (11); - The signal is frequency filtered within a first frequency band to obtain a first filtered signal; - The signal is frequency filtered in a second frequency band different from the first frequency band in order to obtain a second filtered signal; - The first filtered signal is processed to obtain the value of a first parameter, the first parameter indicating the degree of variation of the first filtered signal within the first frequency band, the processing of the first filtered signal is performed at the portion of the first filtered signal corresponding to the rolling step of the tire (11), wherein the monitoring unit (2) is located within the deformation zone (46, 42, 47, 44) of the tire (11); - Process the second filtered signal to obtain the value of the second parameter, the second parameter indicating the degree of change of the second filtered signal in the second frequency band, the processing of the second filtered signal is performed at the portion of the second filtered signal corresponding to the rolling step of the tire (11), wherein the monitoring unit (2) is located in the deformation zone (46, 42, 47, 44) of the tire (11); - In the two-dimensional space of the parameters, identify the position of point (P), the point using the values ​​of the first parameter and the second parameter as coordinates; - Based on the position of the point (P) in the space, determine the state of the road surface (40).

13. The system (30) according to claim 12, wherein, The at least one detection element includes an accelerometer (3) configured to measure at least one acceleration component experienced by the monitoring unit (2) during the rotation of the tire (11).

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