Method for determining interface conditions between a tire and ground

Abstract

A method for determining the interface condition between a tire and the ground of a motor vehicle is described, in particular a method for determining the occurrence of aquaplaning based on non-Boolean logic and a continuously varying indicator of the interface condition between the tire and the ground.

Description

[Technical Field]

[0001] Description text The present invention relates to a diagnostic method and system for motor vehicles. In particular, the invention has been developed with reference to diagnosing the interface conditions between the tire and the ground while the vehicle is moving.

[0002] prior art Several methods and systems are known for determining the interface conditions between the tires and the ground in a motor vehicle, most of which are used in the operation of systems that control the driving and / or stability of motor vehicles or systems for autonomous or semi-autonomous driving.

[0003] All the information obtained from the implementation of methods and systems such as these, however, is not sufficiently effective in predicting and contrasting some phenomena caused by specific interface conditions between the tire and the ground, such as aquaplaning, in other words, the known methods are unable to provide any information useful in predicting or contrasting this phenomenon.

[0004] Such drawbacks jeopardize the effectiveness of even the most sophisticated anti-aquaplaning systems (in this regard, the Applicant is the holder of various national patent applications such as, for example, 102021000011108, 102021000011111, 102021000011117 or 102014902296915), since it is not possible to control the anti-aquaplaning system in such a way as to obtain a specific - and ultimately more effective - intervention in response to the aquaplaning conditions that the vehicle is to face, nor to be prepared to have the anti-aquaplaning system intervene in cases where the conditions encountered by the vehicle indicate a high probability of the occurrence of aquaplaning.

[0005] On the other hand, diagnosis of the interface conditions between the tire and the ground for the purpose of controlling the anti-aquaplaning system using known methods and systems cannot be realized without resorting to further sensors or equipment that are not normally present on the vehicle and which can hardly be implemented due to their cost.

[0006] Finally, currently known diagnostic methods are based on deductive logics, either Boolean in nature or with a high degree of discretization. On the one hand, such logics are sufficiently robust against perturbations to the input data, but on the other hand, they are prone to significant losses of information levels that can jeopardize the final result. Summary of the Invention

[0007] The present invention aims to solve the technical problems outlined above. In particular, the invention aims, inter alia, to provide a method for determining the interface conditions between a tire and the ground, which makes it possible to manage the operation of an anti-aquaplaning system without requiring the contribution of additional sensors or equipment in addition to those normally present on the vehicle. A further object of the invention is to implement such a method robust with respect to perturbations to the input data, without loss of information level.

[0008] The object of the invention is achieved by means of a method having the features set forth in the following claims, which form an integral part of the technical disclosure provided herein on the invention. [Brief explanation of the drawings]

[0009] The present invention will now be described with reference to the accompanying figures, which are given by way of non-limiting example only, and in which: [Figure 1] 1 shows a block diagram of the method according to the invention. [Figure 2] 1 shows a block diagram of a preferred implementation of the first element of the method according to the invention. [Figure 3]1 shows a block diagram of a preferred implementation of the first element of the method according to the invention. [Figure 4] 1 shows a block diagram of a preferred implementation of the first element of the method according to the invention. [Figure 5] 1 shows a block diagram of a preferred implementation of the first element of the method according to the invention. [Figure 6] 1 shows a block diagram of a preferred implementation of the first element of the method according to the invention. [Figure 7] 1 shows a block diagram of a preferred implementation of the second element of the method according to the invention. [Figure 7A] 1 shows a "bicycle" model of the vehicle's lateral dynamics. [Figure 7B] A theoretical reference for the calculation of the longitudinal dynamics of a vehicle is presented. [Figure 8A] 1 shows a block diagram of a preferred implementation of the second element of the method according to the invention. [Figure 9] 1 shows a block diagram of a preferred implementation of the third element of the method according to the invention. [Figure 9A] 1 shows a block diagram of a preferred implementation of the third element of the method according to the invention. [Figure 9B] 1 shows a model of the longitudinal dynamic equilibrium of a wheel. [Figure 9C] 1 shows the longitudinal dynamics of the vehicle. [Figure 10] 1 shows a block diagram of a preferred implementation of the third element of the method according to the invention. [Figure 11] 1 shows a logic diagram representative of the method according to the invention. [Figure 12] 1 shows a logic diagram representative of the method according to the invention. [Figure 13] 1 shows a logic diagram representative of the method according to the invention. [Figure 14] 1 shows a logic diagram representative of the method according to the invention. [Figure 15] 1 shows a logic diagram representative of the method according to the invention. DETAILED DESCRIPTION OF THE INVENTION

[0010] Reference number 1 in FIG. 1 generally refers to a block diagram of a method for determining the interface condition between a tire and the ground in a motor vehicle, and in particular a method for determining the occurrence of aquaplaning, according to an embodiment of the invention.

[0011] In terms of a complete functional diagram - meaning that various embodiments may include one or more of the functional blocks shown in Figures 1 and 15 - the method according to the invention is based on a set of input data 2, a real-time calculation stage 4, an intermediate set of output data 6, an analysis stage 8 (real-time), and a final set of output data 10.

[0012] The functional definition within each of the above stages or sets may vary depending on the computational needs (or resources) and / or control requirements for the implementation of the method in real-time computation stages.

[0013] In an embodiment that must meet the most stringent computational and / or control requirements, the overall structure is shown in Figure 1, where the real-time calculation stage 4 comprises a first calculation module 12 configured to operate on a database of data of the vehicle's powertrain, a second calculation module 14 configured to operate based on global vehicle dynamics data, and a third calculation module 16 configured to operate based on individual wheel dynamics data of the vehicle. According to the invention, calculation modules 14 and 16 are optional, i.e. they can be provided to determine further levels of information and further output data for the method according to the invention, while module 12 is generally provided in all embodiments, since it is able to determine the proximity of the interface conditions between the tire and the ground to aquaplaning, even if it is not possible to rely on the further levels of information obtained from modules 14 and 16.

[0014] 2 shows a block diagram of the calculation module 12, which will be briefly referred to as the "powertrain module" in the following. In the inventive method, the powertrain module 12 is able to establish the proximity to an aquaplaning condition using estimates of the lift forces acting on each wheel of the vehicle and a comparison of said lift forces with threshold force values ​​that may cause the vehicle to lift off the ground, i.e., separation of contact between the tires and the ground.

[0015] The functional blocks designated by the reference numerals 18, 20, 22, 24 in FIG. 2 illustrate diagrammatically the steps of a method for carrying out the decisions described above.

[0016] Specifically, according to the invention, the powertrain module comprises: - reference longitudinal acceleration of the vehicle a XPTMDL (FIGS. 3 and 4) - Block 18 - actual longitudinal acceleration of the vehicle a XCAN To measure - reference longitudinal acceleration a XPTMDL and the actual longitudinal acceleration a XCAN Calculating the difference between blocks 20 and 22 determining an additional drag value (which in aquaplaning is a fluid dynamic property) at the interface between the tire and the ground based on said difference, and determining a lift force at the interface between the tire and the ground based on said additional drag force; - determining the threshold force at which lift-off of the tire from the ground occurs; - comparing said lift force with said threshold force to determine the proximity of the interface conditions between the tire and the ground to an aquaplaning condition - Block 24 and processing a set of input data 2 (including data and parameters that are typically available on a CAN network without requiring auxiliary sensors or equipment in addition to those typically installed on the vehicle), specifically a subset relating to the powertrain, in such a way as to:

[0017] Each of the above steps will now be described in detail with reference to FIGS.

[0018] 3 shows a schematic representation of a wheel W of a motor vehicle facing a film of water WF on the ground G, which serves as a theoretical reference for the method according to the invention. At a point P1 on the surface of the tread of the wheel W, the component of the hydrodynamic drag F D and the hydrodynamic drag component F D The component of lift F depends on the value of L The resultant force of fluid dynamic forces including

[0019] Assuming that all fluid dynamic drag components act on only one axle (e.g., the front axle of a vehicle), the total drag component acting on the front axle is F D,Faxle =m(a XPTMDL -a XCAN ), i.e., this may be expressed as the reference longitudinal acceleration a XPTMDL and the actual longitudinal acceleration a XCAN is a function of the difference between

[0020] Referring to FIG. 4, the overall equation for vehicle longitudinal dynamic balance may be expressed in the following form:

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[0021] Fslope is the resultant drag or pull force due to the slope (uphill or downhill) of the ground. In the sign convention used, Fslope is positive if it is a drag force and negative if it is a pull force.

[0022] With this premise, the unknown component HydroRes may be determined by difference from a reference case where there is no water at the interface between the tire and the ground, essentially by subtracting the following two equations: ma XPTMDL =ΣF x_i,j -AeroRes-Fslope (reference case) ma XCAN =ΣF x_i,j -AeroRes-HydroRes-Fslope (actual situation when water film WF exists) From here, m(a XPTMDL -a XCAN )=HydroRes=F D,Faxle Therefore, referring to Figure 5, the CAN network in a vehicle is - engaged gear - Engine speed [rpm] - Torque delivered by the engine [Nm] - Braking torque [Nm] - Steering angle

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[0023] It will be appreciated that such data does not necessarily have to be obtained from the CAN network, but may be obtained from any data network in the vehicle. For this reason, whenever the present description refers to the use of data present on a CAN network, it means that the data may be retrieved from the CAN network or from any data network in the vehicle.

[0024] Therefore, by using such data, the reference longitudinal acceleration of the vehicle a XPTMDL in real time (block 18) and combine it with a further item of data available on the CAN network (or any other data network of the vehicle), the acceleration a XCAN (block 20), thereby obtaining the value of the hydrodynamic drag force F due to the water film WF. D,Faxle (HydroRes) is determined (block 22).

[0025] Next (Figure 6), the value F D,Faxle By using L It is possible to determine the value of the threshold force (lift) required to lift the tire off the ground, which depends heavily on static values ​​for the vehicle, such as the weight distribution (distance from the center of gravity) between the axles and over the front and rear wheelbase. D,Faxle and F L The relationship between is determined during calibration of the method and the associated computational model.

[0026] Notes on some operations:

[0027] In calculating the reference longitudinal acceleration, it is preferable to make some simplifying assumptions because various parameters taken into account in the dynamic balance equation, which can be obtained from the diagram in FIG. 4, may vary during movement. For example, the mass of the vehicle and the rolling resistance of individual tires may vary during vehicle forward movement. Generally, parameters affecting the vehicle may be calibrated during movement. Furthermore, sensor fusion logic can be implemented to minimize the influence of physical variations in factors such as these.

[0028] For example, the vehicle's mass may be updated in real time and / or after each start-up based on calculations of acceleration during low-speed driving maneuvers. For example, the initial driving maneuver during engine start-up—which is almost certainly performed at low speeds (e.g., exiting a garage or parking lot)—can be used to detect vehicle acceleration and estimate the mass upon vehicle restart, since the mass may differ from the last known value due to, for example, an increase in the number of passengers and / or an increase in fuel or cargo on board.

[0029] The computational load for calculating the threshold force value at which tire lift-off from the ground occurs can generally be low, since the variability of vehicle mass over a wide range of conditions may not significantly affect the computation of the critical strength value, and therefore the weight distribution between the axles can be considered reasonably constant (or, in any case, sufficiently constant for the computational requirements), as can the front and rear wheelbase values ​​(which are all values ​​that ultimately depend on the location of the center of mass). Naturally, a more accurate and more dynamic mapping of the location of the vehicle's center of mass and the progression of the vehicle mass itself will lead to more accurate estimates that can be restored depending on the needs and, in particular, the situation.

[0030] In summary, the following list summarizes the input and output data that characterize a preferred embodiment of powertrain module 12:

[0031] Direct Input Data - Wheel speed (front left, front right, rear left, and rear right wheel speed) [rpm] or [rad / s] - forward speed of the vehicle [m / s] -Engaged gear [-] - Engine speed [rpm] or [rad / s] - Driving torque [Nm] -Steering angle [°] - Braking torque [Nm]

[0032] Indirect Input Data - the transverse resultant interfacial force F between the tire and the ground y [N] - deduced from module 14 if present, or from data on the CAN network if not; Required parameters - tire rolling radius [m] - for each wheel; the transmission ratio T_ratio between the engine and the wheels (for front-wheel drive or rear-wheel drive vehicles) or the transmission ratio between the engine and the wheels obtained from the torque distribution between the front and rear axles (in the case of four-wheel drive vehicles); - Engine mass moment of inertia [kg m 2 ] - Mass moment of inertia of the wheel [kg m 2 ]-About each wheel - vehicle mass [kg] - longitudinal aerodynamic drag coefficient C x [-] - Area of ​​the front of the vehicle [m 2 ]

[0033] Output Data - Proximity to aquaplaning conditions [-] (Block 24) - An indicator for the type of terrain (block 26).

[0034] 7, 8, 9, and 10, the block diagrams and operational logic of the computational modules 14 and 15, corresponding to the vehicle dynamics module (14) and the wheel longitudinal dynamics module (16), respectively, are now described. These computational modules, in parallel with module 12, perform a reliable mapping of vehicle operating conditions across all conditions. In other words, each computational module 12, 14, and 16 has a reliability range that covers a subset of the entire domain of vehicle operating conditions, but not the entire domain. The reliability ranges of the domains 12, 14, and 16 have overlapping areas that can be used as a means for consistency control of the decisions made by each module, and non-overlapping areas where the module providing the most reliable results can be considered as the reference for vehicle control. The reliability ranges are influenced by the quality of the sensors present on the vehicle. The more accurate the sensors (e.g., for autonomous driving), the wider the reliability range. In this regard, in embodiments including only module 12 or not integrating module 12 with modules 14, 16 in the manner described above, the control of the vehicle and the on-board anti-aquaplaning system may be more conservative with intervention logic, if necessary, thereby reducing the impact on the boundaries of the reliability range based solely on the calculation results of module 12.

[0035] 7 and 8, the vehicle dynamics module 14, like module 12, again uses the composite information present on the CAN network (or on another data network in the vehicle) as its input data set.

[0036] Five main actions are performed by Module 14, namely: - obtaining data from the CAN network (or from another data network of the vehicle); - Processing the longitudinal dynamics (block 141) and transverse dynamics (block 142) of the vehicle - analyzing the evolution of the grip force based on the dynamics of the vehicle (block 143), - global analysis of contact with the ground (block 144); - Analyzing the terrain regularity based on the vibrations along the vehicle axis z (block 145) - Defining the terrain conditions based on the grip point values ​​and their evolution over time (block 146).

[0037] Module 14 -Transverse Grip (Block 28) - Longitudinal grip (Block 28) - Terrain Regularity (Block 32) -Side slip (Block 30) The powertrain module 12 is configured to process data on the CAN network (or on another data network of the vehicle, e.g., obtained from the vehicle's inertial platform) to obtain an estimate of the force distribution between the four tires and the ground. This is useful for assessing the grip conditions of the entire vehicle and for some preliminary evaluation of the distribution of forces exchanged at their interface with the ground. Note that such an evaluation is independent of the variables considered in the powertrain module 12, and therefore, as mentioned above, the module 14 may provide a different perspective and a different mapping of the vehicle's dynamic state.

[0038] The list provided below summarizes the input and output data that characterize a preferred embodiment of the vehicle dynamics module 14.

[0039] Direct Input Data -Steering angle δ [°] - longitudinal acceleration

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[0040] Indirect Input Data - No required parameters - vehicle mass m [kg] - Mass moment of inertia of the vehicle (polar moment of inertia) I z [kg m 2 ] - Position of the center of mass of the vehicle (l f and l r -Front and rear wheel base- and h g - defined by the height of the center of mass from the ground - Coefficient of longitudinal aerodynamic drag C x [-] - Coefficient of vertical aerodynamic drag C z [-] (generally very small; it generally contributes to the calculation of vertical forces acting on the car, which can ultimately affect the vertical loads acting on the wheels) Output Data -Transverse Grip [N] - Longitudinal grip [N] - Drift angle [°] - Terrain regularity [-] The calculation of mass variations due to the use of a slipping vehicle is carried out by analyzing data on torques on the wheels and acceleration of the vehicle under normal grip. As for the polar moment about the z axis, due to its low sensitivity to variations, it is possible to refer to a value that does not need to be updated during travel. If necessary, the value of the polar moment of inertia about the z axis can be updated based on the mass of the vehicle, which is essentially the only component involved in the calculation of the moment of inertia that can vary during driving. Specifically, an increase or decrease in mass results in an increase or decrease in the polar moment of inertia, respectively. In this regard, the same considerations can be applied to the update of the vehicle's mass value: it can be updated by detecting accelerations during some reference driving maneuvers (e.g., low-speed driving maneuvers) or based on an equation for the overall dynamic balance of the vehicle, where fixed and known parameters (e.g., front wheelbase and rear wheelbase) and values ​​available on the inertial platform are taken into account.

[0041] With regard to the lateral dynamics of the vehicle, the preferred theoretical assumption corresponds to the "bicycle" model shown in Figure 7A (of course, other calculation models are possible, the bicycle model being considered as an example). The theoretical reference for the calculation of the longitudinal dynamics of the vehicle in module 14 is shown in Figure 7B.

[0042] In a preferred embodiment, module 14 operates on data retrieved from the vehicle's inertial platform and calculates the acceleration along axis x (

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[0043] By decomposing the forces on the individual wheels along x and y, and estimating the distribution of longitudinal forces between the front and rear wheel bases as a function of vertical forces during acceleration or braking (load transfer), simple balance for lateral translation and rotation can be used to determine the mass (m), wheelbase of the center of mass (l f and l r - front wheelbase and rear wheelbase), and the polar moment of inertia of the vehicle I z Knowing the forces (net of the approximations due to use, as mentioned above), it is possible to determine the following forces with reference to the "bicycle" model of FIG. 7A:

[0044] Fxf: longitudinal force on the front axle Fxr: longitudinal force on the rear axle Fyf: transverse force on the front axle Fyr: Transverse force on the rear axle.

[0045] Also, by knowing the data on load transfer due to rolling, which is also available from the inertial platform, it is possible to determine the distribution of such forces between the right and left sides (i.e., for the individual wheels).

[0046] By knowing the vertical forces Fz (due to pitch, mass, aerodynamic loads, and longitudinal load transfer - these are also known from the inertial platform, and in particular Iy, the polar moment of inertia about the axis y, and ω y , which depends on the pitch speed, see Figure 7B), it is possible to determine the vertical forces Fzf and Fzr acting on the front and rear axles, and ultimately the coefficient of friction μ for the individual wheels of the vehicle.

[0047] From an analysis of the difference in the coefficient of friction between the front and rear axles, it is possible to infer the presence or absence of aquaplaning conditions, since this phenomenon essentially affects the front wheels (in other low-grip conditions, such as driving on ice, the front and rear coefficients of friction will be similar or identical).

[0048] In particular, the determination of the forces Fxf, Fxr, Fyf, Fyr is obtained from a set of dynamic equilibrium equations, which are fully available from the literature, as follows:

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[0049] In the presence of a steering angle δ, the grip coefficient for the front axle is calculated by decomposing the forces Fyf and Fxf along the steering direction, i.e., by recalculating the longitudinal Fxf(δ) and transverse Fyf(δ) components relative to the mid-plane of the wheel being steered, whereby Fyf(δ)=Fyf·sen(δ)+Fxf·cos(δ) Fxf(δ)=Fxf·cos(δ)-Fyf·sen(δ) As already recognized with reference to module 12, some simplifying assumptions are made in the calculations because various parameters involved in the dynamic equilibrium equations that may be described with reference to the diagrams of Figures 7A and 7B may vary during operation. For example, the position of the center of mass may vary during movement, but generally, it is necessary to repeatedly update the values ​​of parameters that affect the dynamic equilibrium of the vehicle. For discretization of various types of terrain, precise knowledge of such values ​​is not necessary.

[0050] Of course, if computational load is not an issue and it is possible to continuously determine output data, updating of vehicle parameters such as these, which are available in the literature and which may vary during driving according to one or more models currently used in electronic control of vehicle dynamics, would be necessary.

[0051] It is possible to set up a dynamic equilibrium balance, thereby defining the average value of the force being exerted by each tire on the ground, averaged over the distribution of weight along the vehicle, naturally depending only on the input values ​​from the inertial platform.

[0052] Once the grip coefficients for each wheel are determined, they are analyzed according to the diagrams shown in Figures 8A and 8B. In the case of Figure 8A, the calculation corresponds to an analysis of the absolute values ​​of the grip coefficients for the four wheels. In the case of Figure 8B, the calculation corresponds to a differential analysis between the grip of the front and rear axles. This also allows for a simultaneous first analysis of the ground conditions. For example, if a longitudinal grip coefficient of 1.1 is detected, it is reasonable to exclude the presence of ice on the ground. On the other hand, if the vehicle is about to experience aquaplaning, the calculation of the longitudinal grip coefficient will produce a value that could be confused with the presence of ice on the road. In this regard, the quantitative analysis shown schematically in Figure 8A is combined with a logical analysis as shown in Figure 8B. The purpose of such an analysis is to determine the difference in the longitudinal grip coefficient between the front and rear axles. The theoretical premise follows directly from the physical characteristics of aquaplaning: the latter essentially affects the front axle of the vehicle, while the rear axle is only slightly affected, since almost all of the water film is blown away by the passing front axle. Due to such considerations, it is possible to differentiate various types of terrain from one another, and also to differentiate the presence of one of these types of terrain from aquaplaning conditions.

[0053] It is also possible to analyze the variation of the friction coefficient as a function of speed. Most terrain conditions (mud, tarmac, snow, ice) do not cause a large variation in friction with driving speed. Conversely, aquaplaning causes friction similar to that of wet tarmac, up to gliding speeds (i.e., speeds at which the lift force exceeds the threshold mentioned above, causing the vehicle axle to lift), where friction suddenly drops.

[0054] The final function of the module is to calculate the terrain irregularity, which can also help distinguish between terrain conditions. In this case, reference is made to the frequencies recorded along the axis z.

[0055] Irregular terrain will exhibit a large variation in the signal around its mean value, while more regular terrain will exhibit a more constant value. The same concept can be described for either high-frequency terrain irregularities (mud, gravel) or low-frequency irregularities (potholes, bumps).

[0056] Irregularity can be measured by referring to either a direct measurement (acceleration along axis z) or an indirect measurement (components relative to z contained in the x and y measurements).

[0057] Module 16 (or "Wheel Module") has the function of repeating the evaluation of the grip coefficient of the drive wheels for the same purpose as module 14 (i.e. to distinguish between different terrains depending on the grip coefficient), but it performs calculations using other parameters available on the vehicle's data network (CAN network or other network) to increase the level of reliability in critical situations.

[0058] 9 and 9A, wheel module 16 again uses the composite information available on the CAN network (or another data network of the vehicle) as a set of input data in exactly the same way as modules 12 and 15.

[0059] Module 16 performs five main actions, specifically: - Acquiring data from the CAN network (or from another network in the vehicle) - Determining the slip of each wheel - Calculating the dynamic balance and longitudinal grip / friction coefficient of each drive wheel -Analyzing out-of-control situations -Analyzing terrain regularities - To define the terrain conditions.

[0060] Therefore, module 16 is - slip-based indicators defining conditions of grip loss potentially caused by terrain with a low grip coefficient to inform the other modules 12, 14 of the identification of the cause of loss of control; - An index of the forces acting on the dynamic equilibrium for each wheel: the grip / friction coefficient is calculated based on the powertrain - an index of topographic regularity The system is configured to process data on the CAN network (or on another network in the vehicle) in such a way that

[0061] To summarize and further explain in part, the following list summarizes the input and output data that characterize a preferred embodiment of wheel module 16:

[0062] Direct Input Data Set 1 - Wheel (front left, front right, rear left, rear right) speed [rpm] or [rad / s] - Vehicle driving speed [m / s]

[0063] Set 2 -Engaged gear [-] - Wheel (front left, front right, rear left, rear right) speed [rpm] or [rad / s] - Driving torque [Nm] - Braking torque [Nm]

[0064] Set 3 Longitudinal acceleration [m / s 2 ]

[0065] Transverse acceleration [m / s 2 ]

[0066] Indirect Input Data -none Required parameters - wheel turning radius [m] or [mm]; the transmission ratio T_ratio between the engine and the wheels (for front-wheel drive or rear-wheel drive vehicles) or the transmission ratio between the engine and the wheels obtained from the torque distribution ratio between the front and rear axles (in the case of four-wheel drive vehicles); - Mass moment of inertia of the wheel I zW [kgm 2 ]; Output Data -Longitudinal grip [N]; -Longitudinal slip [-]; - Index of topographic regularity [-].

[0067] The function of the wheel module 16 includes synergistic cooperation with the vehicle dynamics module 14 in calculations relating to the longitudinal dynamics of the vehicle, thereby widening the scope of effectiveness of both and integrating them with the (essentially longitudinal dynamics) module 12, and consequently widening the scope of overall effectiveness of the method according to the invention.

[0068] For example, in the case of heavy braking, it is difficult to model the behavior of the vehicle braking. Therefore, calculation of the grip / friction coefficient based on the analysis of the powertrain unit becomes inconsistent, while a calculation model based on the inertial platform of the vehicle, such as the implementation using module 14, offers greater validity.

[0069] On the other hand, there may be conditions where the wheel dynamic equilibrium model is very consistent and accurate, because the force distribution on the various wheels is calculated directly rather than estimated.

[0070] Referring to FIG. 9C, slip is calculated based on input data set 1 according to models available in the literature. Slip ij (S ij )=[(ω ij ·R ij ) / v ij -1]

[0071] Where: ω ij = rotational speed of right / left wheel (i) on front / rear axle (j) R ij = turning radius of right / left wheel (i) on front / rear axle (j) v w_ij = longitudinal velocity of the right / left wheel (i) of the front / rear axle (j), which is the radius of curvature D of the path of the right / left wheel (i) of the front / rear axle (j) at the longitudinal velocity v of the vehicle and the yaw rate r ij It is equal to the sum of the product by .

[0072] Figure 9B shows a model of the longitudinal dynamic balance of the wheels, involving the calculation process of the wheel module 16 based on the values ​​of module 12. As for Figure 9C, it strictly refers to module 16 for values ​​describing the longitudinal dynamics of the vehicle. The values ​​describing the transverse dynamics essentially take into account module 14, such as values ​​Fy_ij that can be obtained from the values ​​of transverse grip Fyf and Fyr.

[0073] More specifically, data (Set 2) on the vehicle's CAN network (or on another network) is used to determine the value of the longitudinal force transmitted by each wheel to the ground.

[0074] The dynamic equilibrium equation is very simple:

[0075] F x_ij =M eng_ij -M brk_ij -I w_ij ω ij ' where: F x_ij is the longitudinal force transmitted to the ground by the right / left wheel (i) of the front / rear axle (j), M eng_ij is the driving torque acting on the right / left wheel (i) of the front / rear axle (j), M brk_ij is the braking torque acting on the right / left wheel (i) of the front / rear axle (j), Iw_ij is the mass moment of inertia of the right / left wheel (i) on the front / rear axle (j), ω ij ' is the value of the angular acceleration of the right / left wheel (i) on the front / rear axle (j).

[0076] This is the ratio F x_ij / F z_ij The friction / grip coefficient μ for each wheel, defined as x_ij This leads to obtaining the value of F z_ij is the vertical load acting on the right / left wheel (i) of the front / rear axle (j) and is known from the values ​​of Set 3, which allows the estimation of the values ​​of longitudinal load transfer and transverse load transfer.

[0077] Wheel dynamics equilibrium equation (F x_ij ,μ x_ij ) and wheel slip (S ij ) is used as input data for the following analysis, as shown in FIG.

[0078] In this case, the issue is again to characterize the terrain regularity using a procedure similar to that of module 14. In this case, the reference measurement on which the dispersion calculation is based is not the acceleration along axis z, but the wheel speed, which is compared with the vehicle speed. More specifically, for each wheel, the instantaneous angular velocity is detected and the latter is compared with a theoretical / expected value in the absence of slip, which is obtained from the instantaneous forward speed of the vehicle. In the absence of slip, the detected angular velocity and the theoretical / expected angular velocity coincide or approximately coincide (e.g., due to signal noise or small momentary fluctuations). In the case of slip, it is possible to observe a dispersion of the instantaneous angular velocity relative to the theoretical / expected angular velocity. A high dispersion indicates an irregular terrain, since loose or irregular terrain causes wheel slip, especially due to a very high variability in the interface conditions between the tire and the ground. Moreover, a very irregular terrain causes a slip phenomenon, which causes suspension movement, resulting in a slight forward and / or backward movement of the wheel relative to the theoretical conditions, and thus increases the aforementioned dispersion.

[0079] It is therefore possible to characterize the type of terrain the vehicle is moving over: the specific capabilities of the on-board sensors allow it to distinguish between wet terrain, snow, and ice depending on its high, medium, or low grip / friction, and to detect irregular terrain (e.g., mud, gravel, potholes, bumps, sewers) due to the variable frequency of slippage.

[0080] For the dynamic balance of the vehicle, it is possible to extract a set of output data similar to that obtained in module 14 for the longitudinal dynamics of the vehicle. As explained above, having similar output data sets from different computational modules may improve the reliability of the system and extend its range of validity.

[0081] Additionally, wheel module 16 operates based on the longitudinal component of the wheel, while module 14 is configured to handle forces transmitted both laterally and longitudinally to the ground.

[0082] Overall, the implementation of the operation using modules 12, 14, and 16 together results in three sets of output data being available (see again set 10 in Figure 1). i) Terrain type ii) Grip conditions iii) Information on proximity to aquaplaning conditions Among the data sets i)-iii), sets i) and iii) are discrete sets, while set ii) may be continuous (with real-time updates of such vehicle parameters that may vary during driving) or discrete. To be able to combine the results of the three calculation modules 12, 14, 16, a logical simplification is preferably employed that converts each of sets i)-iii) into a discrete set.

[0083] With reference to FIG. 11, the following simplifications are made.

[0084] Module 12 output data set PWTMDL_Drag_ (block 24): It is the additional drag force F determined using the method according to the invention. D corresponds to the value of

[0085] PWTMDL_Drag_Type (block 26): the additional drag force F determined using the method according to the invention D The value of is also used for a first estimate of the type of terrain the vehicle will be driving over. This classification involves two levels: - Level 0: The additional drag value is constant with vehicle speed. This indicates loose terrain (mud, gravel) or dry tarmac. - Level 1: Additional drag value increases with vehicle speed. It is a possible indicator of aquaplaning.

[0086] Set of output data for modules 14 and 16 VEHMDL_GripLevel (Block 144, Block 28 - Module 14, Transverse Grip), WHEMDL_LongitudinalGrip (Block 144, Block 28 - Module 14, Longitudinal Grip; Block 162, Block 32 - Module 16, Longitudinal Grip): The values ​​of the grip forces Fxf, Fxr, Fyf, Fyr and - indicated for the individual wheels - the longitudinal and transverse grip force values ​​calculated by modules 14 and 16 corresponding to the values ​​Fx,ij shown in Figures 9B and 9C, for i=1 (front), 2 (rear), j=1 (left), 2 (right) are combined into a continuous resultant force, which defines an indicator of the grip exerted on the ground.

[0087] It has also been clearly shown in the above description that the vehicle dynamics module 14 is configured to calculate both longitudinal and transverse grip values, and therefore also the level of longitudinal grip. Thus, the transverse grip calculation is performed by module 14, while the longitudinal grip calculation is performed by both modules 14 and 16. Depending on the reliability of the signals respectively output by each module (which depends on different driving conditions), it is possible to choose how much to rely on the former or latter reading. Only after reliability analysis are the values ​​combined.

[0088] In this case too, the grip value determined using the method according to the invention is also used for a first estimate of the type of terrain the vehicle is moving over.

[0089] Classification involves two levels. (VEHMDL_GripType): - Level 0: Grip value is constant with respect to vehicle speed - Level 1: Grip value varies with vehicle speed

[0090] In other words, if the grip value is detected to be low even below the aquaplaning speed (e.g. 55 km / h on slick tires), it is possible to proceed to a first determination of low grip on snow and ice rather than a determination of an aquaplaning condition.

[0091] VEHMDL_SideSlip (Block 145, Block 30 - Module 14, Side Slip), WHEMDL_Longitudinal Slip (Block 164, Block 34 - Module 16, Longitudinal Slip): These indicate the measurements of side slip (tire side slip / vehicle drift angle) and tire longitudinal slip calculated by modules 14 and 16.

[0092] On the other hand, VEHMDL_RoadRegularityLevel and WHEMDL_RoadRegularityLevel (blocks 32, 36) indicate the terrain regularity. These signals can also be used to identify tarmac conditions.

[0093] The output signals from the estimators (FIG. 11) are then combined, so that we obtain the outputs of the following indicators of the interaction between the tire and the ground (it is recognized that the contribution of models 12, 14, 16 to the definition of the following output information is indicated by the corresponding notation shown in brackets in the relevant diagrams of FIGS. 1 to 10): - indicator of resistance to advancement offered by the terrain, RES; value F explained for module 12 D,Faxle (or generally F D ) is a suitable example of the indicator RES, - indicator of the type of resistance to advancement offered by the ground REST, - indicator GRP of the grip developed on the ground; the combined longitudinal grip forces Fxf, Fxr and transverse grip forces Fyf, Fyr are suitable examples of indicator GRP, - GRPT, an indicator of the dependence of the grip on the speed of advancement; - indicator of the distribution of grip between the front and rear axles GRPD, - Indicator of terrain regularity IRR; calculation of the acceleration difference along the vertical axis z of the vehicle is a suitable example of an indicator of terrain regularity IRR, Loss of control indicator CTR; information calculated by modules 14 and 16, including measurements of side slip (tire side slip / vehicle drift angle) and tire longitudinal slip, are suitable examples of data on which the definition of the indicator CTR is based.

[0094] With reference to Figure 15, for indicators such as these, the following holds true: the indicator of resistance to advancement has a continuously varying value (i.e. a continuous value), preferably including values ​​between 0 (minimum) and 1 (maximum), corresponding to the normalized value; the indicator REST of the type of resistance to advancement has discrete values ​​(i.e. values ​​that vary discretely) indicating a constant resistance (0) or a resistance that depends on the speed of advancement (1); the indicator GRP of the grip exerted on the ground has a continuously variable value, preferably comprised between the values ​​0 (minimum) and 1 (maximum), corresponding to a normalized value; the indicator GRPT of the dependence of the grip on the speed of advancement has discrete values ​​(i.e., values ​​that vary discretely) that indicate either a constant grip (0) or a grip that depends on the speed of advancement (1); the indicator GRPD of the grip distribution between the front and rear axles has continuously variable values, in particular (normalized) values ​​between a minimum value (0) associated with identical grip conditions on the front and rear axles, and a maximum value (1) associated with higher grip conditions on the front axle relative to the rear axle; the indicator of regularity IRR has a continuously varying value between the values ​​0 (minimum) and 1 (maximum) corresponding to the normalized value; The out-of-control indicator CTR has a continuously varying value, corresponding to the normalized value, including values ​​between 0 (minimum) and 1 (maximum).

[0095] Regarding the regularity indicator IRR, it can be implemented either as a direct indicator of regularity, i.e. an indicator that has a minimum value (0) for high irregularity and a maximum value (1) for high regularity, or conversely as an indicator of irregularity, i.e. an indicator that has a minimum value (0) for high regularity and a maximum value (1) for high irregularity.

[0096] Therefore, in the inventive method, the use of the above-mentioned output data is considered as input data for a calculation logic that allows the recognition of the type of terrain. In this regard, it must be taken into account that the inventive method has so far aimed to use conventional vehicle dynamics equations to obtain all of the information that characterizes the contact between the ground and the tires.

[0097] At this stage of the method, the information is used to "fill" corresponding "data containers" that indicate the range of interface conditions that occur in the tire's interaction with different types of terrain, including terrain or road surfaces with conditions that may lead to the occurrence of an aquaplaning event.

[0098] Thus, an indication of the type of terrain is obtained based on a probability calculation.

[0099] An example of this part of the method according to the invention is shown in Figures 13 and 14. Starting from an output item of data RES calculated (by module 12) on the basis of items of data PTMDL_Drag and normalized to a value comprised between 0 and 1, let us assume that the indicator RES has a value of 0.97.

[0100] We then consider two "data containers" whose correspondences we aim to identify for two different terrains (in this example, aquaplaning terrain and dry tarmac terrain).

[0101] From the physical reality of the behavior of vehicle wheels on dry tarmac and on a water film that causes aquaplaning, it is known that if the RES has a high value (for example, 0.97, taking into account the normalization between 0 and 1), the probability of the vehicle moving on dry tarmac is very low.

[0102] For this reason, as can be seen in Figure 13, the probability PDa(RES) of a vehicle moving on dry tarmac with a normalized RES drag term of 0.97 is very low, specifically reaching PDa(RES) = 0.1. Therefore, a low probability is obtained from a normalized RES drag term with a high value. (Notation: P = probability function; Da = dry tarmac; (Res) = argument of the probability function) The probability function PDa(RES) of driving on dry tarmac for indicator RES is assumed to have a similar behavior to that shown in Figure 12, curve Da, while curve Aq shows the course of the probability function PAq(RES) of aquaplaning.

[0103] The example in Figure 12 results from the assumption that the course of the probability function is linear, but conceptually can take any behavior corresponding to a particular relationship between the tire and the ground (tarmac, aquaplaning, ice).

[0104] As a counter example, always referring to FIG. 13, when the normalized resistance value RES is low, for example equal to 0.2 as in the lower branch of the diagram in FIG. 13, the probability PDa(RES) has a relatively high value, in other words it is very likely that a low value of resistance to forward movement indicates driving on dry tarmac.

[0105] FIG. 14 shows a complementary example, namely the calculation of the probability PAq(RES) for values ​​of the normalized resistance RES between 0.97 and 0.2. (Notation: P = probability function; Aq = aquaplaning; (Res) = argument of the probability function)

[0106] In this case, the first value leads to a probability function with a very high value (a high level of resistance to forward movement is likely to indicate aquaplaning or possible driving on a film of water), while the second value leads to a probability function with a very low value (a low level of resistance to forward movement is unlikely to indicate aquaplaning or possible driving on a film of water).

[0107] After the probability of a particular value being associated with a particular terrain is obtained, such value is multiplied by a weight K1, which is a function of the indicators REST; GRP; IRR; RES, GRPT, CTR, and GRPD, taking into account the nominal weight of the value for the particular terrain (resistance to aquaplaning is the primary value, so it has a relatively high weight K1) and the reliability of the value in the particular situation (therefore, based on REST; GRP; IRR; RES; GRPT; CTR; GRPD). For example, if the indicator GRP exhibits a low value (as an indicator of grip developed on the ground, this indicator indicates the instantaneous grip used by the vehicle), the vehicle is in a stationary condition (constant speed). In such a condition, the powertrain calculation module 12 becomes very reliable. Since the indicator RES is obtained from the calculation module 12, the indicator RES should acquire greater relevance.

[0108] For this reason, assuming that K1 is defined with a value comprised between 0 and 1, the value approaches a maximum value and therefore approaches 1 (or the limit value 1).

[0109] The same can be said for K5, which "weights" the results of the probability function P(IRR). In this case, too, the variance values ​​of the accelerometers and wheel rotation speeds mounted on the vehicle at a constant speed are more reliable and are associated with a higher weight. Generally, based on the quality of the inputs and the applied calculation model, the coefficients K1 to K7 serve to increase the robustness of the estimates for the final result. Regarding reliability, it is assumed that higher weights are assigned to values ​​of the probability of aquaplaning occurring higher than a first threshold (indicating that they are plausible) and lower weights are assigned to values ​​of the probability of aquaplaning occurring lower than a second threshold (indicating that they are highly implausible).

[0110] For example, when the (normalized) continuous grip value GRP is low, the value of K1 is increased further because the normalized resistance value RES is more reliable.

[0111] As a result of such operations, the contribution of each indicator RST, REST, GRP, GPRT, GPRD, IRR, CTR in demonstrating the inference of a given type of terrain is calculated.

[0112] This logical sequence may be repeated for each of the data entries RES, REST, GRP, GRPT, IRR, CTR, GPRD and for each possible terrain type (Figure 15), and the calculated probability level determines the "winner" of the various inferences made, i.e. the most likely terrain type. In this regard, Figure 15 shows the aquaplaning probability functions PAq(RES), PAq(REST), PAq(GRP), PAq(GRPT), PAq(IRR), PAq(CTR), PAq(GPRD) associated with each item of input data RES, REST, GRP, GRPT, IRR, CTR, GPRD, their respective weights K1, K2, K3, K4, K5, K6, K7, and the weighted probability functions PAq(RES)*K1, PAq(REST)*K2, PAq(GRP)*K3, PAq(GRPT)*K4, PAq(IRR)*K5, PAq(CTR)*K6, PAq(GPRD)*K7, which define the individual contributions that are combined in the calculation of the final aquaplaning probability PAq_OUT.

[0113] Finally, with regard to the latter, a threshold can be defined that allows for obtaining the final output data that is presented to the user / driver.

[0114] If an approach based on filtering out false positives is preferred, a very high threshold can be fixed (e.g., 0.9). If an approach that tolerates some false positives but does not risk false negatives is preferred, the activation threshold value can be lowered to (e.g.) 0.6.

[0115] Thus, output data that can be obtained using the method according to the invention (related to the inference of terrain conditions) include: -Aquaplaning -Partial aquaplaning -snow -ice -Mud road - Potholes, bumps, drainage systems (generally, concentrated irregularities in the road surface) -Paved roads -Dry tarmac

[0116] Regarding the definition of probability rules for each terrain, these are based on the physical characteristics of various phenomena studied a priori based on a theoretical formulation of tire-ground interactions, and the associated probability functions can be more accurately developed using experimental data detected for various terrains. The inventive method offers clear improvements over estimation methods based solely on Boolean logic and on discrete states. The latter computational models assume discrete levels of sampling, which consequently offer the advantage of robustness against perturbations caused by variations in vehicle parameters (e.g., mass or tire pressure), but on the other hand, suffer from a loss of information levels potentially useful for the final decision. As explained above, the inventive method utilizes so-called "sensor fusion" techniques to maximize the available information level and robustness against perturbations.

[0117] Naturally, implementation details and embodiments may vary considerably from those described and illustrated above without departing from the scope of the present invention, as defined in the appended claims. (Item 1) 1. A method for determining the interface conditions between a tire and the ground of a motor vehicle, in particular for determining the occurrence of aquaplaning, comprising: - determining a number of indicators of the interface condition between the tire and the ground (RST, REST, GRP, GPRT, GPRD, IRR, CTR), - calculating the values ​​of each of a number of indicators of the interface condition between the tire and the ground (RST, REST, GRP, GPRT, GPRD, IRR, CTR) based on the dynamic equilibrium of the vehicle, - determining a value of the probability of occurrence of the aquaplaning phenomenon (PAq(RES), PAq(REST), PAq(GRP), PAq(GRPT), PAq(IRR), PAq(CTR), PAq(GPRD)) for each calculated value of a plurality of indicators of the interface condition between the tire and the ground, - determining weights (K1, K2, K3, K4, K5, K6, K7) for each value of the probability of occurrence of aquaplaning and applying each weight (K1, K2, K3, K4, K5, K6, K7) to each value of the probability of occurrence of aquaplaning (PAq(RES), PAq(REST), PAq(GRP), PAq(GRPT), PAq(IRR), PAq(CTR), PAq(GPRD)), thereby determining probability weights (PAq(RES)*K1, PAq(REST)*K2, PAq(GRP)*K3, PAq(GRPT)*K4, PAq(IRR)*K5, PAq(CTR)*K6, PAq(GPRD)*K7) for each value of the probability of occurrence of aquaplaning, - determining the final value (PAq_OUT) of the probability of occurrence of the aquaplaning phenomenon by combining the weighted values ​​of the weighted probabilities (PAq(RES)*K1, PAq(REST)*K2, PAq(GRP)*K3, PAq(GRPT)*K4, PAq(IRR)*K5, PAq(CTR)*K6, PAq(GPRD)*K7); A method for providing the above. (Item 2) 2. The method of claim 1, further comprising the step of transmitting a signal of the occurrence of aquaplaning when the final value of the probability of the occurrence of aquaplaning (PAq_OUT) is higher than a predetermined threshold. (Item 3) Item 1. The method according to item 1, wherein the step of determining the weights (K1, K2, K3, K4, K5, K6, K7) for each value of the probability of occurrence of aquaplaning comprises the step of determining the weights for each value of the probability of occurrence of aquaplaning and as a function thereof. (Item 4) 2. The method according to claim 1, wherein the step of determining the final value of the probability of occurrence of aquaplaning (PAq_OUT) by combining the weighted values ​​of the weighted probabilities (PAq(RES)*K1, PAq(REST)*K2, PAq(GRP)*K3, PAq(GRPT)*K4, PAq(IRR)*K5, PAq(CTR)*K6, PAq(GPRD)*K7) comprises the step of calculating the sum of the weighted values ​​of the probabilities. (Item 5) 2. The method according to claim 1, wherein the step of calculating the values ​​of each of the indicators of the interface condition between the tire and the ground (RST, REST, GRP, GPRT, GPRD, IRR, CTR) further comprises a step of normalizing the values ​​in a reference range of values, preferably in the range between 0 and 1. (Item 6) 6. The method according to any one of items 1 to 5, wherein determining the weights (K1, K2, K3, K4, K5, K6, K7) for each value of the probability of occurrence of aquaplaning (PAq(RES), PAq(REST), PAq(GRP), PAq(GRPT), PAq(IRR), PAq(CTR), PAq(GPRD)) comprises assigning higher weights to values ​​of the probability of occurrence of aquaplaning that are higher than a first threshold and assigning lower weights to values ​​of the probability of occurrence of aquaplaning that are lower than a second threshold. (Item 7) A plurality of indicators of the interface condition between the tire and the ground (RST, REST, GRP, GPRT, GPRD, IRR, CTR) are - an indicator of the resistance to advance offered by the ground (RES) - an indicator of the type of resistance to advancement offered by the ground (REST) - an indicator of the grip developed on the ground (GRP) - an indicator of the dependence of the grip on the speed of the advance (GRPT) - Indicator of grip distribution between the front and rear axles (GRPD) - Indicator of terrain regularity (IRR) - Loss of Control Indicator (CTR) 7. The method according to any one of items 1 to 6, comprising: (Item 8) - said indicator of resistance to advancement (RES) has a continuous value; - said indicators (REST) ​​of the type of resistance to advancement offered by the ground have discrete values ​​representing a constant resistance (0) or a resistance dependent on the speed of advancement (1), - the indicator of the grip developed on the ground (GRP) has a continuously variable value, - the indicator of the dependence of the grip on the speed of advancement (GRPT) has discrete values ​​indicating a constant grip (0) or a grip dependent on the speed of advancement (1), the indicator of grip distribution between the front and rear axles (GRPD) has a continuously variable value, in particular between a minimum value associated with identical grip conditions at the front and rear axles, and a maximum value associated with higher grip conditions at the front axle relative to the rear axle, - said indicator of terrain regularity (IRR) has a continuously varying value; - The method according to item 7, wherein the out-of-control indicator (CTR) has a continuously varying value. (Item 9) - the reference longitudinal acceleration of the vehicle (a XPTMDL ) determining - the actual longitudinal acceleration of the vehicle (a XCAN ) measuring the - calculating the difference between said reference longitudinal acceleration and said actual longitudinal acceleration, - Additional drag force (F) at the interface between the ground and the tire based on the difference D , PWTMDL_Drag_Level), and the additional drag force (F D ) at the interface between the tire and the ground, based on L), wherein the additional drag force defines the indicator of resistance to advancement (RES). - determining the threshold force at which lift-off of the tire from the ground occurs; - comparing the lift force to a threshold force to determine the proximity of the interface condition between the tire and the ground to an aquaplaning condition. (Item 10) The additional drag force (F D 10. The method according to item 9, wherein the step of determining the further resistance (REST) ​​on the speed of forward movement of the vehicle (PWTMDL_Drag_Level, PWTMDL_Drag_Level) comprises a step of defining the indicator (REST) ​​of the type of resistance to forward movement offered by the ground by determining the presence of a dependence of the further resistance on the speed of forward movement of the vehicle (PWTMDL_Drag_Type). (Item 11) - determining the longitudinal grip of the vehicle, - determining the transverse grip of the vehicle, - The method according to item 7 or 8, further comprising a step of defining the indicator of the grip developed on the ground (GRP) based on a combination of the longitudinal grip force and the transverse grip force (WHEMDL_LongGrip_Level, VEHMDL_LatGrip_Level). (Item 12) - determining the vehicle side slip indicator (VEHMDL_SideSlip_Level), - determining the longitudinal slip (WHEMDL_Slip_Level) of said vehicle tyre, - The method according to item 7 or item 8, further comprising determining the loss of control indicator (CTR) based on the vehicle side slip indicator and the longitudinal slip. (Item 13) 9. The method of claim 7 or 8, comprising determining the indicator of terrain regularity (IRR) by calculating the variability of vertical acceleration of the vehicle. (Item 14) 7. The method of claim 6, further comprising enabling intervention of an anti-aquaplaning system installed in the vehicle.

Claims

1. 1. A method for determining the interface conditions between a tire and the ground of a motor vehicle, in particular for determining the occurrence of aquaplaning, comprising: - determining a number of indicators of the interface condition between the tire and the ground, - calculating values ​​of each of a plurality of indicators of the interface condition between the tire and the ground based on the dynamic equilibrium of the vehicle, - determining, for each calculated value of a plurality of indicators of the interface condition between the tire and the ground, a value of the probability of occurrence of the aquaplaning phenomenon; - determining a weighted probability value for each value of the probability of occurrence of aquaplaning by determining a weight for each value of the probability of occurrence of aquaplaning and applying each weight to the respective value of the probability of occurrence of aquaplaning, - determining a final value of the probability of occurrence of the aquaplaning phenomenon by combining the weighted values ​​of the weighted probabilities. A method for providing

2. The method of claim 1 , further comprising the step of transmitting a signal of the occurrence of aquaplaning when the final value of the probability of the occurrence of aquaplaning is higher than a predetermined threshold.

3. 2. The method of claim 1, wherein determining the weight for each value of the probability of occurrence of aquaplaning comprises determining the weight for each value of the probability of occurrence of aquaplaning and as a function thereof.

4. 2. The method of claim 1, wherein the step of determining a final value of the probability of occurrence of the aquaplaning phenomenon by combining the weighted values ​​of the weighted probabilities includes the step of calculating a sum of the weighted values ​​of the probabilities.

5. 2. The method of claim 1, wherein the step of calculating the respective values ​​of the indicators of the interface condition between the tire and the ground further comprises a step of normalizing the values ​​in a reference range of values, preferably in the range between 0 and 1.

6. 2. The method of claim 1, wherein for each value of the probability of occurrence of aquaplaning, determining the weight comprises assigning a higher weight to a value of the probability of occurrence of aquaplaning that is higher than a first threshold and assigning a lower weight to a value of the probability of occurrence of aquaplaning that is lower than a second threshold.

7. The plurality of indicators of the interface condition between the tire and the ground include: - an indicator of the resistance to advancement offered by the ground - an indicator of the type of resistance to advancement offered by the ground - an indicator of the grip developed on said ground an indicator of the dependence of said grip on the speed of said advancement; -Indicator of grip distribution between the front and rear axles - indicator of terrain regularity - Out of control indicator 7. The method of claim 1, comprising:

8. - the indicator of resistance to advancement has a continuous value; - said indicators of the type of resistance to advancement offered by the ground have discrete values ​​that respectively indicate a constant resistance or a resistance that depends on the speed of advancement; - the indicator of the grip developed on the ground has a continuously varying value, - the indicator of the dependence of the grip on the speed of advancement has discrete values ​​that indicate a constant grip or a grip that depends on the speed of advancement, the indicator of the grip distribution between the front and rear axles has a continuously variable value, in particular between a minimum value associated with identical grip conditions at the front and rear axles, and a maximum value associated with higher grip conditions at the front axle relative to the rear axle, - said indicator of terrain regularity has a continuously varying value; The method of claim 7, wherein the indicator of loss of control has a continuously varying value.

9. - determining a reference longitudinal acceleration of the vehicle, - measuring the actual longitudinal acceleration of the vehicle, - calculating the difference between said reference longitudinal acceleration and said actual longitudinal acceleration, determining an additional drag force at the interface between the ground and the tire based on said difference and a lift force at the interface between the tire and the ground based on said additional drag force, said additional drag force defining said indicator of resistance to forward motion; - determining the threshold force at which lift-off of the tire from the ground occurs; - comparing the lift force with the threshold force to determine the proximity of the interface condition between the tire and the ground to an aquaplaning condition.

10. 10. The method of claim 9, wherein the step of determining the additional drag includes determining the existence of a dependence of the additional resistance on a speed of forward movement of the vehicle, thereby defining the indicator of the type of resistance to forward movement offered by the ground.

11. - determining the longitudinal grip of the vehicle, - determining the transverse grip of the vehicle, 8. The method of claim 7, further comprising the step of: - defining the indicator of the grip developed on the ground surface based on a combination of the longitudinal grip force and the transverse grip force.

12. - determining a vehicle side slip indicator; - determining the longitudinal slip of the vehicle tires, 8. The method of claim 7, further comprising determining the loss of control indicator based on the vehicle side slip indicator and the longitudinal slip.

13. 8. The method of claim 7, including determining the indicator of terrain regularity by calculating a variance in vertical acceleration of the vehicle.

14. 7. The method of claim 6, further comprising the step of enabling intervention of an anti-aquaplaning system installed on the vehicle.

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