A method for determining the interface conditions between a tire and the ground, particularly for determining the onset of aquaplaning.

Abstract

1. A method for determining an interface condition between a tire and the ground in a motorized vehicle, in particular for determining the onset of aquaplaning, comprising: determining a reference longitudinal acceleration (a XPTMDL ), determining the actual longitudinal acceleration (a XCAN ), calculating a difference between the reference longitudinal acceleration and the actual longitudinal acceleration, and calculating an additional drag force (F) at the interface between the tire and the ground based on the difference. D , PWTMDL_Drag_Level), and the further drag force (F D ) based on the lift force (F L A method is described comprising the steps of determining a threshold force at which lift-off of the tire from the ground occurs, determining a threshold force at which the tire is lifted, comparing the lift force to the threshold force and determining the proximity of an interface condition between the tire and the ground to an aquaplaning condition.

Description

Technical Field

[0001] The present invention relates to a diagnostic method and system for a motor vehicle. Specifically, the present invention has been developed by referring to the diagnosis of the interface conditions between the tire and the ground while the motor vehicle is in motion.

Background Art

[0002] A plurality of methods and systems for determining the interface conditions between the tire and the ground in a motor vehicle are known, and most of them rely on the operation of a control system for vehicle driving and / or stability, or an autonomous or semi-autonomous driving system.

[0003] However, the complexity of the information derived from the implementation of such methods and such systems is of little effectiveness in determining and comparing specific phenomena such as aquaplaning derived from specific interface conditions between the tire and the ground. In other words, in this situation, items of information that may be useful for determining or comparing such events cannot be derived through known methods.

[0004] This drawback can even impair the effectiveness of most advanced aquaplaning prevention systems (in this regard, the applicant is the patentee of a plurality of domestic patent applications such as 102021000011108, 102021000011111, 102021000011117 or 102014902296915). Because it is impossible to control the aquaplaning prevention system in such a way as to obtain a specific and ultimately more effective intervention against the aquaplaning conditions that the vehicle has to deal with, and it is also not possible to prepare the aquaplaning prevention system for intervention when the conditions faced by the vehicle indicate a high probability of suffering an aquaplaning event.

[0005] Other known methods and systems do not enable the diagnosis of the interface conditions between the tire and the ground without relying on additional sensors or devices that are not normally present on a regular vehicle and are hardly implementable due to cost, for the purpose of controlling an aquaplaning prevention system.

[0006] [Object of the Invention] The object of the present invention is to solve the technical problems mentioned above. Specifically, the object of the present invention is, inter alia, to enable the management of the operation of an aquaplaning prevention system without relying on additional sensors or devices, in addition to what is generally present on a motor vehicle, and to provide a method for determining the interface conditions between the tire and the ground.

Summary of the Invention

[0007] The object of the present invention is achieved by a method having the features described in the following claims, which form an integral part of the technical disclosure provided herein with reference to the present invention.

Brief Description of the Drawings

[0008] The present invention is described here with reference to the accompanying drawings, which are provided purely as non-limiting examples. [Figure 1] It is a block diagram of the method according to the present invention. [Figure 2] It is a block diagram relating to a preferred implementation of the first element of the method according to the present invention. [Figure 3] It is a block diagram relating to a preferred implementation of the first element of the method according to the present invention. [Figure 4] It is a block diagram relating to a preferred implementation of the first element of the method according to the present invention. [Figure 5] It is a block diagram relating to a preferred implementation of the first element of the method according to the present invention. [Figure 6] It is a block diagram relating to a preferred implementation of the first element of the method according to the present invention. [Figure 7]This is a block diagram relating to a preferred implementation of the second element of the method according to the present invention. [Figure 7A] This is a block diagram relating to a preferred implementation of the second element of the method according to the present invention. [Figure 7B] This is a block diagram relating to a preferred implementation of the second element of the method according to the present invention. [Figure 8A] This is a block diagram relating to a preferred implementation of the second element of the method according to the present invention. [Figure 8B] This is a block diagram relating to a preferred implementation of the second element of the method according to the present invention. [Figure 9] This is a block diagram relating to a preferred implementation of the third element of the method according to the present invention. [Figure 9A] This is a block diagram relating to a preferred implementation of the third element of the method according to the present invention. [Figure 9B] This is a block diagram relating to a preferred implementation of the third element of the method according to the present invention. [Figure 9C] This is a block diagram relating to a preferred implementation of the third element of the method according to the present invention. [Figure 10] This is a block diagram relating to a preferred implementation of the third element of the method according to the present invention. [Figure 11] This is a logic diagram associated with each output of the method according to the present invention. [Figure 12] This is a logic diagram associated with each output of the method according to the present invention. [Figure 13] This is a logic diagram associated with each output of the method according to the present invention. [Figure 14] This is a logic diagram associated with each output of the method according to the present invention. [Figure 15] This is a logic diagram associated with each output of the method according to the present invention. [Modes for carrying out the invention]

[0009] In Figure 1, reference numeral 1 indicates, as a whole, a block diagram of a method for determining the interface conditions between the tires and the ground in a powered vehicle, specifically, a method for determining the onset of aquaplaning, according to an embodiment of the present invention.

[0010] Referring to the overall functional diagram (different embodiments are adapted to have one or more of the functional blocks shown in Figure 1), the method according to the present invention is based on an input data complex 2, a real-time calculation stage 4, an intermediate output data complex 6, a (real-time) analysis stage 8, and a final output data complex 10.

[0011] The functional definitions within each stage or complex mentioned above may vary according to processing demands (or resources) and / or control demands requiring real-time implementation of computation methods.

[0012] In embodiments that must satisfy the most stringent processing and / or control requirements, the overall structure is as shown in Figure 1, where the real-time calculation stage 4 includes a first calculation module 12 configured to operate based on data from the vehicle powertrain assembly, a second calculation module 14 configured to operate based on overall vehicle dynamics data, and a third calculation module 16 configured to operate based on dynamics data for each individual wheel of the vehicle. According to the present invention, calculation modules 14 and 16 are optional, i.e., they may be provided to determine further levels of information and further output data for the method according to the present invention, while module 12 is provided as a whole in all embodiments, because (even in the absence of further levels of information from modules 14 and 16) it allows for the determination of the proximity of interface conditions between the tire and the ground to the aquaplaning phenomenon.

[0013] Figure 2 shows a block diagram of the calculation module 12, which is defined below as the "powertrain module" for simplicity. In the method according to the present invention, the powertrain module 12 enables the determination of proximity to aquaplaning conditions by using an estimate of the lift force acting on each wheel of the vehicle and comparing said lift force to a threshold force value that would cause the vehicle to lift off the ground, i.e., to separate the contact between the tires and the ground.

[0014] The functional blocks shown by 18, 20, 22, and 24 in Figure 2 schematically illustrate the steps in the process of implementing the decisions mentioned above.

[0015] Specifically, according to the present invention, the powertrain module is - Reference longitudinal acceleration of the vehicle a XPTMDL To determine (Figures 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 the two, - Based on the above difference, determine the additional drag force at the interface between the tire and the ground (in aquaplaning, this is a hydrodynamic property), and determine the lift force at the interface between the tire and the ground based on this additional drag force. - Determining the threshold force at which the tire lifts off the ground, -Compare the above lift force with the above threshold force to determine the degree of proximity of the interface conditions between the tire and the ground for aquaplaning conditions. -Block 24 The system is configured to process the input data complex 2 (including data and parameters that are normally available on the CAN network without requiring additional sensors or equipment beyond those typically present in the vehicle), and specifically the subcomplex relating to the powertrain assembly.

[0016] Each of the steps mentioned above will now be described in detail with reference to Figures 3 to 6.

[0017] Figure 3 shows a view of a wheel W of a vehicle facing a water film WF on the ground G taken as a theoretical reference for the method according to the invention. At a point P1 on the tread surface of the wheel W, a resultant hydrodynamic force including a hydrodynamic drag component F D and a lift component F L is applied, which depends on the value of the hydrodynamic drag component F D .

[0018] Assuming that all hydrodynamic drag components act on a single axis (i.e., the front axle of the vehicle), the total drag component acting on the front axle is F D,Faxle =m(a XPTMDL -a XCAN ) and may be expressed as, i.e., this is a function of the difference between the reference longitudinal acceleration a XPTMDL and the actual longitudinal acceleration a XCAN .

[0019] Referring to Figure 4, the overall equation for the longitudinal dynamic balance of the vehicle is

Equation

Equation

[0020] Given these assumptions, the unknown component HydroRes can be determined as the difference from a reference case where there is no water film at the interface between the tire and the ground, by essentially subtracting the following two equations: ma XPTMDL =ΣF x_i,j -AeroRes-Fslope (see reference case) ma XCAN =ΣF x_i,j -AeroRes-HydroRes-Fslope (Actual situation when a water film WF is present) From here: m(a XPTMDL -a XCAN )=HydroRes=F D,Faxle Therefore, referring to Figure 5, several operational and dynamic parameters are known from the vehicle's CAN network, including the following: -Engaged gear - Engine rotational speed [rpm] - Torque transmitted by the engine [Nm] - Braking torque [Nm] - Steering angle [°] -Lateral acceleration [m / s2] - Pitch angle [°].

[0021] Such data is not necessarily obtained from the CAN network and may be obtained from any data network of the vehicle. For this reason, whenever this specification refers to the use of data that resides on the CAN network, it should be understood that the data may be derived either from the CAN network or from any other data network of the vehicle.

[0022] Therefore, by utilizing such data, the value of the vehicle's reference longitudinal acceleration a can be obtained in real time. XPTMDL Calculate (block 18) and use it as a further item of data available on the CAN network (or any data network of the vehicle), namely acceleration aXCAN It is possible to compare this (block 20), thereby determining the hydrodynamic drag value F caused by the water film WF. D,Faxle (HydroRes) is determined (block 22).

[0023] Subsequently (Figure 6), the value F D,Faxle By utilizing the lift component F L It is possible to determine this, and then compare it to the threshold force (lift) value, which is necessary to lift the tires off the ground and depends heavily on static vehicle values ​​such as the weight distribution between axles and the front and rear wheelbases (distance from the center of mass). Value F D,Faxle and F L The relationship between them is determined during the calibration of the method and related computational models.

[0024] Several calculation notes.

[0025] In calculating the reference longitudinal acceleration, several simplified assumptions are preferably made because various parameters involved in the dynamic balance equation, which can be described with reference to the figure in Figure 4, can vary during operation. For example, the vehicle mass and the rotational resistance of each individual tire can vary during operation. Generally, the values ​​of parameters affecting the longitudinal dynamic balance of the vehicle should be repeatedly updated, but the method according to the present invention makes it possible to solve this calculation problem by determining multiple (preferably three; see blocks 24A, 24B, and 24C) proximity levels or degrees of proximity to the aquaplaning conditions. With such divisions, for example, it is no longer necessary to know the exact position of the vehicle's center of mass or the vehicle mass over time, and thus a minimally corrected reference value of the longitudinal acceleration is more than sufficient. If continuous monitoring of the degree of proximity to aquaplaning, i.e., conditions involving substantially infinite levels or degrees of proximity to aquaplaning, is desired, then it is obviously necessary to update the vehicle parameters that fluctuate during operation (based on available data (and for that purpose, updates by the vehicle itself's onboard electronic control unit)), thereby incorporating such fluctuations into the calculation of the reference longitudinal acceleration.

[0026] For example, the vehicle mass may be updated in real time and / or after each start based on acceleration calculations during low-speed maneuvers. For example, during vehicle startup, a first maneuver may be used, which is almost certainly a low-speed maneuver (e.g., exiting a garage or parking lot) to detect vehicle acceleration and estimate mass upon vehicle restart, because the mass may differ from the last known data due to, for example, the presence of a larger number of occupants and / or a larger amount of fuel or cargo.

[0027] Regarding the calculation of the threshold force value at which the tire lifts off the ground, the computational load can generally be lower because, under many conditions, the variability of the vehicle mass does not significantly affect the calculation of the threshold force value. Thus, the weight distribution between the axles can be considered reasonably constant (or at least sufficiently constant for the purposes of the calculation), just like the front and rear wheelbase values ​​(all of which fundamentally depend on the position of the center of mass). Naturally, a more precise and dynamic mapping of the position of the vehicle's center of mass, and of the unfolding of the vehicle mass itself, will yield more accurate estimates, which can be relied upon according to the need, especially if the situation requires it.

[0028] In summary, the following list reports the input and output data complexes that characterize a preferred embodiment of the powertrain module 12.

[0029] Direct input data - Speed ​​of the wheels (front left, front right, rear left, rear right wheels) [rpm] or [rad / s] - Vehicle forward speed [m / s] -Engaged gear[- - Engine speed [rpm] or [rad / s] - Drive torque [Nm] - Steering angle [°] - Braking torque [Nm]

[0030] Indirect input data - Transverse resultant force F of tire / ground interface force y [N] - Estimated from module 14 (if any), or otherwise from CAN data. Required parameters - Tire turning radius [m] - For each wheel; - The transmission ratio between the engine and the wheels (in front-wheel drive or rear-wheel drive vehicles) or the torque distribution ratio between the front and rear axles (in four-wheel drive vehicles), mediated by the transmission ratio between the engine and the wheels. - Engine mass moment of inertia [kg·m2 ] -Mass moment of inertia of the wheel [kg·m] 2 ]-Regarding each wheel - Vehicle weight [kg] - Longitudinal aerodynamic drag coefficient C x [-] - Area of ​​the front of the vehicle [m²] 2 ]

[0031] Output data - Proximity to aquaplaning conditions [-] (Block 24) - Ground-type indication (block 26) Referring to Figures 7, 8, and 9, the block diagrams and operating logic of computation modules 14 and 16 are described, corresponding to the vehicle dynamics module (14) and the longitudinal wheel dynamics module (16), respectively. These computation modules, in parallel with module 12, implement a mapping of vehicle driving conditions that can be highly reliable under all conditions. In other words, each computation module 12, 14, and 16 has a confidence interval that covers a subset of the vehicle driving conditions, rather than the entire range. The confidence intervals of domains 12, 14, and 16 have overlapping areas that can be used as means for consistency control of decisions implemented by each module, and non-overlapping areas where modules that provide more reliable results can be used as references for vehicle control. The confidence intervals are influenced by the quality of the sensors on the vehicle. The more sophisticated the sensors on the vehicle (e.g., for autonomous vehicles), the wider the confidence interval. In this regard, in embodiments that include only module 12 or do not integrate module 12 with modules 14 and 16 as described above, the control of the vehicle and the onboard aquaplaning prevention system is optionally performed more cautiously in the intervention logic, thereby mitigating the influence at the confidence interval boundary based solely on the calculation results of module 12.

[0032] Referring to Figures 7 and 8, the vehicle's dynamics module 14, like module 12, employs a complex of information on the CAN network (or another data network of the vehicle) as its input data complex.

[0033] Module 14 consists of five main functions, namely: - Obtaining data from the CAN network (or another data network in the vehicle) - To process the longitudinal dynamics (block 141) and transverse dynamics (block 142) of the vehicle. - Analyzing the development of grip force based on vehicle dynamics (Block 143) - Analyze the overall conditions of contact with the ground (block 144), - Define ground conditions based on instantaneous grip value and its development over time (Block 145) Execute this.

[0034] Module 14 is as follows: - Transverse grip (block 28) - Longitudinal grip (block 28) -Drift (Block 30) The system is configured to process data on the CAN network (or on another data network of the vehicle, e.g., from the vehicle's inertial platform) in a manner that obtains estimates of the values. This is useful for evaluating the overall grip conditions of the vehicle and for any initial assessment of the distribution of forces exchanged at the interface with the ground to the four tires. This is an assessment independent of the variables considered in the powertrain module 12, and therefore, as mentioned above, it should be noted that module 14 may provide different perspectives and different mappings of the vehicle's dynamic state.

[0035] The following list summarizes the input and output data complexes that characterize a preferred embodiment of the vehicle dynamics module 14.

[0036] Direct input data - Steering angle δ[°] - Longitudinal acceleration

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[0037] Indirect input data -none Required parameters - Vehicle mass m [kg] - Vehicle's mass moment of inertia (polar moment of inertia) I z [kg·m 2 ] - Position of the vehicle's center of mass (l f and l r (front wheelbase and rear wheelbase) and h g (Defined by the height of the center of mass from the ground) - Coefficient C of longitudinal aerodynamic drag x [-] - Coefficient C of vertical aerodynamic drag z [-] (Generally very small; this can generally affect the calculation of vertical forces acting on a powered vehicle, and ultimately, it can affect the vertical load acting on the wheels.) Output data - Lateral grip [N] - Longitudinal grip [N] - Drift angle [°] -slip The calculation of mass fluctuations resulting from vehicle use is performed by analyzing torque data for wheel and vehicle acceleration under normal grip conditions. With respect to the polar moment around axis z, due to its low sensitivity to fluctuations, it is possible to refer to a provided value without needing to update it during operation. Optionally, it is possible to update the value of the polar moment of inertia around axis z based on the vehicle mass, which is substantially the only component in the moment of inertia calculation that can fluctuate during operation. Specifically, increases or decreases in mass generate increases or decreases in the polar moment of inertia in an equivalent manner. In this regard, the same considerations previously observed regarding updating the vehicle mass value apply: it may be updated by detecting acceleration during a particular reference maneuver (e.g., low-speed maneuver), or it may be updated based on the overall dynamic balance of the vehicle, where fixed and known parameters (e.g., front and rear wheelbases) and values ​​available on the inertial platform are taken into consideration.

[0038] With regard to the lateral dynamics of the vehicle, the preferred theoretical assumption corresponds to the "two-wheeled vehicle shape" model shown in Figure 7A (obviously, other computational models are possible, so this two-wheeled vehicle shape model should be considered as an example). A theoretical reference for calculating the longitudinal dynamics of the vehicle in Module 14 is shown in Figure 7B.

[0039] In a preferred embodiment, module 14 operates based on data acquired from the vehicle's inertial platform, which includes acceleration components along axis x.

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[0040] By decomposing the forces on each individual wheel along x and y, and by estimating the distribution of longitudinal force Fx between the front and rear axles as a function of vertical force during acceleration or braking (load transfer), the mass (m) and the wheelbase (l) of the center of mass can be determined from the simple balance during lateral translation and rotation. f and l r (Front wheelbase and rear wheelbase) and the vehicle's polar moment of inertia I z By knowing the net approximation (resulting from the use of the aforementioned approximation), it is possible to determine the following forces by referring to the "two-wheeled vehicle shape" model in Figure 7A:

[0041] 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

[0042] Furthermore, by obtaining data on load transfer due to roll, which is also available from the inertial platform, it is possible to determine the force distribution mentioned above between the right and left sides (i.e., for each individual wheel).

[0043] By knowing the vertical force Fz (which is also obtained from the mass, here again from the inertial platform, and especially the value Iy, i.e., the polar moment of inertia around axis y and ω), y This is due to aerodynamic loads and longitudinal load transmission caused by pitch, which depend on the pitch speed (see Figure 7B). It is possible to determine the vertical forces Fzf and Fsr acting on the front and rear axles, and ultimately the coefficient of friction μ for each individual wheel of the vehicle.

[0044] Analysis of the difference in friction coefficients between the front and rear axles allows us to infer the possible existence of aquaplaning conditions, because this phenomenon essentially concerns the front wheels (in other low-grip situations such as driving on icy ground, the front and rear friction coefficients should be similar or identical).

[0045] The determination of forces Fxf, Fxr, Fyf, and Fyr is specifically derived from the well-known complex of dynamic balance equations, as follows: (Overall balance in the longitudinal and transverse directions)

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[0046] 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, that is, by recalculating the longitudinal Fxf(δ) and transverse Fyf(δ) components with reference to the center plane of the steered wheel, and thus obtaining the following: Fyf(δ)=Fyf·sen(δ)+Fxf·cos(δ) Fxf(δ)=Fxf·[0]cos(δ)+Fyf·sen(δ) As already mentioned with reference to Module 12, several simplified assumptions are made in the calculations because various parameters involved in the dynamic balance equations, which can be described by referring to the diagrams in Figures 7A and 7B, can fluctuate during operation. For example, the position of the center of mass can fluctuate during operation, and generally speaking, it is required to repeatedly update the values ​​of parameters that affect the dynamic balance of the vehicle. However, the method according to the present invention makes it possible to solve this computational problem by providing output data in a discrete configuration through output data of different magnitude levels (as mentioned above). Through this differentiation, it is not necessary to know, for example, the exact position of the vehicle's center of mass or the vehicle's mass over time.

[0047] Naturally, provided that the computational load does not pose a problem and that output data can be determined continuously, it will be necessary to update the vehicle parameters, which may vary during operation, according to one or more models available in the literature and currently used in the electronic control of vehicle dynamics.

[0048] It is possible to set up a dynamic balance assessment to define the average value of the forces released to the ground by each tire, which are obviously mediated by the weight distribution along the vehicle and depend only on the input values ​​from the inertial platform.

[0049] Once the grip coefficients for each tire 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 grips of the front and rear axles. This allows for a simultaneous first analysis of the ground conditions. For example, if the longitudinal grip coefficient is detected to reach 1.1, it is reasonable to rule out the presence of icy ground. However, if the vehicle must deal with an aquaplaning event, the calculation of the longitudinal grip coefficient provides a value that can cause this condition to be confused with driving on icy ground. In this regard, the quantitative analysis schematically shown in Figure 8A is combined with the logical analysis shown in Figure 8B. The purpose of such an analysis is to determine the difference in the longitudinal grip coefficients between the front and rear axles. The theoretical assumption is directly derived from the physical properties of aquaplaning: essentially, it affects the front axle of the vehicle, while the rear axle is only slightly involved, because almost all of the water film is blown away by the passage of the front axle. Based on such considerations, it becomes possible to distinguish various ground types from one another and, therefore, distinguish driving on one of these ground types as opposed to aquaplaning conditions.

[0050] Module 16 (or "wheel module") has the function of repeating the evaluation of the grip coefficient of the wheels driven for the same purpose as Module 14 (i.e., distinguishing different ground surfaces based on the grip coefficient), but it performs calculations using other parameters available on the vehicle's data network (CAN or other) to increase the level of reliability of critical conditions.

[0051] Referring to Figures 9 and 9A, the wheel module 16, here as well, utilizes information on the CAN network (or another vehicle network) as its input data complex, in exactly the same way as modules 12 and 14.

[0052] Module 16 has five main functions, namely: - Obtaining data from the CAN network (or another network in the vehicle) - To handle slippage in each wheel, - Calculate the dynamic balance of each driven wheel and the longitudinal friction / grip coefficient. - Analyzing loss of control, - Defining ground conditions Execute this.

[0053] Therefore, module 16 is as follows: - Slip-based indications that define conditions for loss of grip potentially caused by ground with a low grip coefficient, so as to provide indications of the causes of loss of control to other modules 12, 14; - Indication of forces acting on the dynamic balance of each individual wheel: Calculation of grip / friction coefficient based on the powertrain. It is configured to process data on the CAN network (or another network on the vehicle) in a manner that acquires this data.

[0054] Based on the following summary and partial predictions of the discussion, the following list summarizes the input and output data complexes that characterize a preferred embodiment of the wheel module 16.

[0055] Direct input data Complex 1 - Speed ​​of the wheels (front left, front right, rear left, rear right) [rpm] or [rad / s] - Vehicle forward speed [m / s]

[0056] Complex 2 -Engaged gear[- - Speed ​​of the wheels (front left, front right, rear left, rear right) [rpm] or [rad / s] - Drive torque [Nm] - Braking torque [Nm]

[0057] Complex 3 - Longitudinal acceleration [m / s²] 2 ] -Transverse acceleration [m / s 2 ]

[0058] Indirect input data -none Required parameters - Wheel turning radius [m] or [mm]; - (In the case of front-wheel drive or rear-wheel drive vehicles) the transmission ratio between the engine and the wheels, mediated by the transmission ratio T_ratio or (In the case of four-wheel drive vehicles) the torque distribution ratio between the front axle and the rear axle; -Mass moment of inertia of the wheel I zW [kgm 2 ]; Output data - Longitudinal grip [N]; -Longitudinal slip[-].

[0059] The function of the wheel module 16 is to work synergistically with the vehicle dynamics module 14 for calculating the longitudinal dynamics of the vehicle in such a way that it broadens the effective range of both and integrates them with module 12 (which, here again, is essentially related to longitudinal dynamics), thus broadening the global effective range of the method according to the present invention.

[0060] For example, modeling the braking behavior of a vehicle under conditions of strong braking action is not easy. Therefore, calculations of grip / friction coefficients based on analysis of the powertrain assembly are inconsistent, while the calculation model is more efficient when based on the vehicle's inertial platform, as it is implemented in module 14.

[0061] However, there may be other conditions under which the model of the dynamic balance of the wheels is most consistent and accurate, because the force distribution for various wheels is not estimated, but rather calculated directly.

[0062] Referring to Figure 9C, the slip is calculated based on the input data for Complex 1 and according to a model known in the literature. Slip ij (S ij )=[(ω ij ·R ij ) / v ij -1] Here: ω ij = Rotational speed of the right / left wheels (i) of the front / rear axle (j) R ij = Turning radius of the right / left wheel (i) of the front / rear axle (j) v w_ij = Longitudinal velocity of the right / left wheels (i) of the front / rear axle (j). This is the sum of the product of the vehicle's longitudinal velocity v and yaw rate r, for the front / rear axle. Radius of curvature D of the track at the right / left wheel (i) of (j) ij It is equal to the value multiplied by [the specified factor].

[0063] Figure 9B shows a longitudinal dynamic balance model of a tire, which is involved in the calculation process of the wheel module 16 based on the values ​​of module 12. With respect to Figure 9C, it strictly refers to module 16 for parameters describing the longitudinal dynamics of the vehicle. Parameters describing transverse dynamics are essentially related to module 14, for example, the value Fy_ij, which can be derived from the transverse grip values ​​Fyf and Fyr.

[0064] More specifically, data on the vehicle's (complex 2) CAN network (or another network) is used to determine the value of the longitudinal force released to the ground by each individual wheel.

[0065] The dynamic balance equation is very simple and is as follows:

[0066] F x_ij =M eng_ij -M brk_ij -I w_ij ωij ' Here:

[0067] F x_ij This is the longitudinal force released to the ground by the right / left wheels (i) of the front / rear axle (j), M eng_ij This is the driving torque acting on the right / left wheels (i) of the front / rear axle (j). M brk_ij This is the braking torque acting on the right / left wheels (i) of the front / rear axle (j). I w_ij This is the moment of inertia of the mass of the right / left wheels (i) of the front / rear axle (j), ω ij ' represents the angular acceleration value of the right / left wheel (i) of the front / rear axle (j).

[0068] Therefore, ratio F x_ij / F z_ij The friction / grip coefficient μ for each wheel is defined as follows: x_ij It is possible to obtain the value of F, where z_ij This represents the vertical load acting on the right / left wheels (i) of the front / rear axle (j), which is known from the value of Complex 3, making it possible to estimate the values ​​of longitudinal load transmission and transverse load transmission.

[0069] Wheel dynamics (F x_ij ,μ x_ij ) and wheel slip (S ij The output data of the balance equation is used as input data for the following analysis, as shown in Figure 10.

[0070] Therefore, it is possible to do the following: - Defining the type of surface the vehicle is driving on. Using the typical performance of the onboard sensors, it is possible to categorize surface types into high / medium / low grip / friction. Furthermore, it is possible to detect irregular surfaces (mud / gravel, etc.) due to the frequency of slip fluctuations. -Regarding the vehicle's dynamic balance, it is possible to extract a complex of output data similar to that obtained in module 14 for the vehicle's longitudinal dynamics. As already explained above, providing similar complexes of output data from different computation modules can improve the reliability of the system and broaden its effective range. Furthermore, the wheel module 16 operates on the longitudinal component of the wheel, while module 14 is configured to handle forces emitted to the ground both laterally and longitudinally.

[0071] Overall, the combined computational implementation of modules 12, 14, and 16 results in the following three complexes of output data (see Figure 1 again, complex 10): i) Ground type ii) Grip conditions iii) Information on proximity to aquaplaning conditions.

[0072] In data complexes i) to iii), data complexes i) and iii) are discrete complexes, while complex ii) may be continuous (with real-time updates of vehicle parameters that fluctuate during operation) or discrete. A logical simplification is preferably performed to reduce each of complexes i) to iii) to a discrete complex in order to enable the combination of the results of the three calculation modules 12, 14, and 16.

[0073] Referring to Figure 10, the following simplification is performed:

[0074] Output data complex of module 12 PWTMDL_Drag_Level(block 24): This is a further drag force F determined by the method according to the present invention. D Corresponding to the value, it is categorized into three levels (all referring to each individual instance). - Level 0 (Block 24A): No further drag components were detected, and therefore the vehicle is not likely to be experiencing an aquaplaning event. -Level 1 (Block 24B): A substantial component of further drag has been detected, and therefore the vehicle is no longer in a standard state, and there is a concrete possibility of aquaplaning conditions occurring. -Level 2 (Block 24C): A component of drag is detected that is higher than the component that generates enough lift to lift the tire off the ground. Aquaplaning is certain.

[0075] PWTMDL_Drag_Type(Block 26): Further drag force F determined by the method according to the present invention D The value is also used for a first estimate of the type of ground the vehicle is driving over. 2-level classification: - Level 0 (Block 26A): Further drag values ​​are constant with respect to vehicle speed. This indicates loose ground (mud, gravel) or dry tarmac. -Level 1 (Block 26B): Further drag increases with vehicle speed. This is a possible indication of aquaplaning.

[0076] Complex output data of modules 14 and 16 VEHMDL_LatGrip_Level(block 144, block 28 - module 14, transverse grip), WHEMDL_LongGrip_Level(block 144, block 28 - module 14, longitudinal grip; block 162, block 32 - module 16, longitudinal grip): The longitudinal and transverse grip force values ​​calculated by modules 14 and 16, corresponding to the grip force values ​​Fxf, Fxr, Fyf, Fyr, and the values ​​Fx,ij shown in Figures 9B and 9C (for each single wheel) (where i=1 (front), 2 (rear), j=1 (left), 2 (right)), are combined into a resultant force and classified into three levels: - Level 0 (Blocks 28A, 32A): A high level of grip is detected. The vehicle is driving on a road where it is possible to exchange a high amount of force with the ground. - Level 1 (Blocks 28B, 32B): A decrease in grip is detected. This condition can include various ground surfaces (mud / gravel / snow). - Level 2 (Blocks 28C, 32C): Grip approaches zero. The vehicle may be experiencing aquaplaning or moving on ice.

[0077] Furthermore, the above explanation clarifies that the vehicle dynamics module 14 calculates the longitudinal grip value, that is, it is adapted to also calculate the longitudinal grip level (LongGrip_Level). Therefore, the calculation of transverse grip is performed by module 14, while the calculation of longitudinal grip is performed by both modules 14 and 16. Based on the reliability of both output signals from each module (which depend on different driving conditions), it is possible to select which reading to rely on. Only after a reliability check can the values ​​be combined.

[0078] VEHMDL_SideSlip_Level (Block 145, Block 30 - Module 14, Drift), WHEMDL_Slip_Level (Block 164, Block 34 - Module 16, Slip): The tire drift conditions or indications (tire side slip / vehicle drift angle) and longitudinal slip conditions calculated by modules 14 and 16 are classified into two levels: -Level 0: No slip and / or drift: Vehicle is under control (Block 30A, Block 34A) -Level 1: Slip and / or drift: The vehicle has lost control (block 30B, block 34B).

[0079] Referring to Figures 12 to 15, the proximity to aquaplaning conditions and ground type according to the method of the present invention are described here.

[0080] Proximity to aquaplaning conditions (Figure 12) The starting point is the powertrain module 12. Based on the output data from there, a double check is performed: a) Whether or not there are additional drag components. If so, a second check is performed. b) Whether or not additional drag components vary with speed. If they do, the possibility of aquaplaning exists; if they do not, the possibility of aquaplaning does not exist, and therefore the process terminates with the corresponding indication. If the vehicle is equipped with an aquaplaning system, the latter is kept in standby condition.

[0081] If checks a) and b) yield positive results, it is possible to pre-warn the vehicle driver regarding the possibility of aquaplaning, and furthermore, to pre-trigger or pre-alert conditions for the aquaplaning system (if any). In such situations, the vehicle may not have reached the aquaplaning conditions simply because its forward speed is not high enough, and therefore the additional drag generated is not sufficient to produce enough lift to lift the tires off the ground. The logic output corresponds to block 201 (Possibility of aquaplaning) or 202 (Proximity to aquaplaning) if the additional drag component is equal to or higher than the value that would exceed the threshold force value and produce enough lift to lift the tires off the ground.

[0082] In a preferred embodiment where all calculation modules 12, 14, and 16 are present, further checks can be performed, and thus the reliability of the results is increased due to modules 14 and 16.

[0083] Firstly, it is possible to detect the grip level. For this purpose, module 14 can calculate the transverse and longitudinal grip levels (VEHMDL_LatGrip_Level and VEHMDL_LongGrip_Level values, blocks 144 and 28), and block 16 can calculate the longitudinal grip (WHEMDL_LongGrip_Level value, blocks 162 and 32). Module 14 can also calculate vehicle drift (VEHMDL_SideSlip_Level value, blocks 145 and 30), and module 16 can calculate side slip (WHEMDL_Slip_Level, blocks 164 and 34). The condition for certainty of aquaplaning (block 203) is reached only when the complex of grip data VEHMDL_LatGrip_Level and WHEMDL_LongGrip_Level is at level 2, and the complex of slip data VEHMDL_SideSlip_Level and WHEMDL_Slip_Level is at level 1. In this situation, the vehicle driver receives a warning, and the aquaplaning system installed in the vehicle is activated in a manner that depends on the instantaneous values ​​of slip, grip, and drift, that is, by varying the power and its fluid flow rate as a function of such parameters.

[0084] Detection of loose ground (mud / gravel) or icy conditions - Figures 13 and 14 If an attempt is made to determine other low-grip conditions such as mud / gravel or ice, the detection process will differ from the process for determining proximity to aquaplaning conditions.

[0085] The starting point here, again, is the powertrain module 12, specifically the type of additional drag. In both the mud / gravel and ice cases, the additional drag should not be caused by viscous components and therefore should be constant at different speeds (PWTMDL_Drag_Type is at level 0). The temporal development of the additional drag can be investigated over relatively short time windows to understand whether its value actually changes with vehicle speed.

[0086] Therefore, in this context, the important parameter is slip (longitudinal slip and drift), that is, it describes the state of vehicle control. If the slip data VEHMDL_SideSlip_Level and WHEMDL_Slip_Level complex is at level 1, it can be inferred that the vehicle has lost grip to a level that has not yet been corrected by the stability control system (e.g., ESC). Therefore, it is possible to investigate the ground conditions that affect controllability and warn the driver accordingly.

[0087] Referring to Module 12, frozen ground (Figure 13) can be considered a road with little resistance to forward movement. Therefore, the additional drag calculated by Module 12 should be included in Level 0. Loose ground such as mud or gravel can change the additional drag from Level 0 to Level 1. In other words, in many cases it is equal to 1, but in some cases the grip level is Level 2The level is so low that it reaches [a certain value]. Slip frequency analysis (SFA) may be useful in finally distinguishing loose ground (block 300, Figure 13) from ice (block 400, Figure 14), in the latter case, where PWTMDL_Drag_Level is certainly at level 0. The aquaplaning prevention system is not activated (it is left in standby condition), and the driver is warned by conventional warning lights and vehicle stability controls associated with driving. The vehicle control unit may also provide useful information to regulate torque transmission, braking, or suspension stiffness to make driving safer and more comfortable.

[0088] Detection of snow cover ground conditions - Figure 15 On snow-covered ground, deductive logic is a kind of compromise between the logic used to determine proximity to aquaplaning conditions and the logic employed to distinguish low-grip ground such as mud / gravel or ice.

[0089] Snow generally generates a considerably high additional drag, and therefore PWTMDL_Drag_Level will certainly be at level 1 or level 2. On the other hand, PWTMDL_Drag_Type will certainly be at level 0 because the amount of additional drag is not of the viscous type and does not vary with speed. As far as the complex of grip values ​​VEHMDL_LatGrip_Level and WHEMDL_LongGrip_Level is considered, they will certainly not be at level 2 (which is the typical level of aquaplaning) and may be at level 0 or level 1. Detection of snow-covered ground (block 500) is optionally completed by loss of grip: in this case, the complex of slip values ​​VEHMDL_SideSlip_Level and WHEMDL_Slip_Level will be at level 1. The aquaplaning prevention system is not activated (it is left in standby condition) and the driver is warned via conventional warning lights and vehicle stability controls associated with driving.

[0090] As described and demonstrated in detail, the present invention leverages the synergy between modules 12, 14, and 16, enabling the selection of the most reliable and consistent data as a function of aquaplaning conditions, making it possible to distinguish not only the proximity to those conditions but also the type of ground the vehicle is moving on. Moreover, this does not require any further sensor equipment of any kind and results in complete integration with the vehicle and the aquaplaning prevention system mounted on the latter.

[0091] Naturally, the details of the implementation and embodiments may vary considerably from those described and illustrated herein without departing from the scope of the invention, as defined in the appended claims.

Claims

1. A method for determining the interface conditions between the tires and the ground in a powered vehicle, particularly for determining the onset of aquaplaning, - Reference longitudinal acceleration of the powered vehicle (a ＸＰＴＭＤＬ ) at the stage of deciding - The actual longitudinal acceleration of the powered vehicle (a ＸＣＡＮ ) The stage of measuring - A step of calculating the difference between the reference longitudinal acceleration and the actual longitudinal acceleration, - Further drag at the interface between the tire and the ground based on the above difference (F Ｄ , PWTMDL_Drag_Level), and the further resistance (F Ｄ The lift force at the interface between the tire and the ground (F) is based on this. Ｌ ) at the stage of deciding - A step of determining the threshold force that causes the tire to lift off the ground, - A step of comparing the lift force with the threshold force and determining the degree of proximity of the interface conditions between the tire and the ground to the aquaplaning conditions. A method that includes [a certain feature].

2. The aforementioned further resistance (F Ｄ The step of determining PWTMDL_Drag_Level is, - The aforementioned further resistance (F Ｄ The step of classifying PWTMDL_Drag_Level) into multiple progression levels based on its value, where the multiple progression levels correspond to the further increasing values ​​of the drag. - A step in determining the existence of the further drag dependence (PWTMDL_Drag_Type) on the forward speed of the powered vehicle. The method according to claim 1, comprising:

3. - A step of signaling that the vehicle is moving on loose or low-grip ground when the value of the additional drag (PWTMDL_Drag_Level) is lower than the value that would produce a lift equal to or greater than the threshold force, and there is no dependence of the additional drag on the forward speed of the powered vehicle. - If there is a dependence of the further drag on the forward speed of the powered vehicle, and the value of the further drag (PWTMDL_Drag_Level) is lower than the value that would produce a lift equal to or greater than the threshold force, then the conditions for the possibility of aquaplaning are signaled. - A step of signaling the proximity condition to aquaplaning when the value of the further drag (PWTMDL_Drag_Level) is equal to or greater than the value that produces a lift equal to or greater than the threshold force, and there is a dependence of the further drag on the forward speed of the powered vehicle. The method according to claim 2, comprising:

4. - The step of determining the longitudinal grip force of the powered vehicle, - In the step of determining the transverse grip force of the powered vehicle, - A step of classifying the complex of the longitudinal grip force and transverse grip force (WHEMDL_LongGrip_Level, VEHMDL_LatGrip_Level) into a plurality of progression levels based on their resultant force, where the plurality of progression levels correspond to the decrease in the resultant force. The method according to claim 2 or 3, further comprising:

5. - The stage of determining the vehicle side slip indicator (VEHMDL_SideSlip_Level), - The step of determining the longitudinal slip (WHEMDL_Slip_Level) of the tires of the powered vehicle. The method according to claim 4, further comprising:

6. - If the value of the additional drag (PWTMDL_Drag_Level) is equal to or greater than the value that produces a lift equal to or greater than the threshold force, and there is a dependence of the additional drag on the forward speed of the powered vehicle, - When the complex of longitudinal grip force and transverse grip force of the powered vehicle is classified as the last level of progression, and - If at least one of the vehicle side slip indicator and longitudinal slip has a non-zero value, A stage that shows the conditions for the occurrence of aquaplaning. The method according to claim 5, comprising:

7. - If the value of the additional drag (PWTMDL_Drag_Level) is lower than the value that produces a lift equal to or greater than the threshold force, and there is no dependence of the additional drag on the forward speed of the powered vehicle, - When the complex of longitudinal and transverse grips of the powered vehicle is classified as an intermediate level of the progression level, and - If at least one of the vehicle side slip indicator and longitudinal slip has a non-zero value, This stage indicates that the vehicle is moving on loose ground, particularly mud or gravel. The method according to claim 5, further comprising:

8. - If the value of the additional drag (PWTMDL_Drag_Level) is classified as the first in the progression level, and there is no dependence of the additional drag on the forward speed of the powered vehicle, - When the complex of longitudinal grip force and transverse grip force of the powered vehicle is classified into the last level of the progression level, and - If at least one of the vehicle side slip indicator and longitudinal slip has a non-zero value, The stage of signaling the condition that the device is moving on frozen ground. The method according to claim 5, further comprising:

9. - If the value of the additional drag (PWTMDL_Drag_Level) is classified as an intermediate or final level of progress, and there is no dependence of the additional drag on the forward speed of the powered vehicle, - When the complex of longitudinal grip force and transverse grip force of the powered vehicle is classified into the first level or intermediate level of the progression level, and - If at least one of the vehicle side slip indicator and longitudinal slip has a non-zero value, The stage of signaling the condition that movement is occurring on a snow-covered ground surface. The method according to claim 5, further comprising:

10. The method according to claim 6, further comprising the step of activating the intervention of an aquaplaning prevention system mounted on the powered vehicle.

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