Adhesion coefficient determination method, device and electronic equipment

Abstract

This application relates to the field of vehicle dynamics technology and discloses a method, device, and electronic device for determining an adhesion coefficient. The method comprises: obtaining a vehicle's wheel-end torque, wheel angular acceleration, wheel slip, and wheel vertical load; determining a first longitudinal force for each wheel based on the wheel-end torque and wheel angular acceleration; determining a base adhesion coefficient for each wheel based on the first longitudinal force and wheel vertical load; determining a second longitudinal force for each wheel based on the wheel slip and the tire model corresponding to the wheel; and, if the base adhesion coefficient is less than a preset adhesion coefficient threshold, correcting the base adhesion coefficient using the second longitudinal force to obtain a target adhesion coefficient for each wheel. This application facilitates timely understanding of the adhesion status of each wheel, reduces safety hazards caused by inaccurate adhesion coefficient calculation, and improves vehicle driving safety.

Description

Technical Field

[0001] The present application relates to the field of vehicle dynamics technology, and in particular to a method, device and electronic device for determining an adhesion coefficient. Background Art

[0002] In a vehicle's powertrain, distributed drive, due to its advantage of individually controllable four-wheel motors, can be combined with control algorithms to achieve independent control of all four wheels for different operating conditions and control objectives. Anti-skid control requires estimating the four-wheel adhesion coefficient to determine the maximum available driving force for all four wheels under the current operating conditions. This limits the maximum output torque of the anti-skid torque to ensure the vehicle maintains maximum power without slipping. Therefore, accurately determining the wheel adhesion coefficient improves the vehicle's anti-skid dynamics and stability.

[0003] In related technologies, the adhesion coefficient of the wheel is estimated based on the vehicle traction method. However, when the driving torque suddenly increases or decreases or the wheel acceleration suddenly changes, the estimation of the adhesion coefficient will have large deviations and fluctuations, which cannot effectively utilize the power of the power system or increase the slip of the wheel, resulting in a large error in the estimation of the wheel adhesion coefficient, thereby affecting the vehicle's anti-skid and stability. Summary of the Invention

[0004] To solve the above technical problems, embodiments of the present application provide a method, device, and electronic device for determining an adhesion coefficient.

[0005] According to one aspect of an embodiment of the present application, a method for determining an adhesion coefficient is provided, the determination method comprising: obtaining the vehicle's wheel-end torque, wheel angular acceleration, wheel slip rate and wheel vertical load; determining a first longitudinal force for each wheel based on the wheel-end torque and the wheel angular acceleration; determining a basic adhesion coefficient for each wheel based on the first longitudinal force and the wheel vertical load; determining a second longitudinal force for each wheel based on the wheel slip rate and a tire model corresponding to the wheel; if the basic adhesion coefficient is less than a preset adhesion coefficient threshold, using the second longitudinal force to correct the basic adhesion coefficient to obtain a target adhesion coefficient for each wheel.

[0006] According to one aspect of an embodiment of the present application, the use of the second longitudinal force to correct the basic adhesion coefficient to obtain a target adhesion coefficient for each wheel includes: obtaining the type of road surface on which the vehicle is located; if the road surface type is characterized as a uniform road surface, obtaining real-time operating condition data of the vehicle; determining a correction parameter corresponding to the second longitudinal force based on the real-time operating condition data, and correcting the basic adhesion coefficient based on the correction parameter and the second longitudinal force to obtain a target adhesion coefficient for each wheel.

[0007] According to one aspect of an embodiment of the present application, the correction parameter corresponding to the second longitudinal force is determined based on the real-time operating condition data, so as to correct the basic adhesion coefficient based on the correction parameter and the second longitudinal force to obtain the target adhesion coefficient of each wheel, including: determining a weighted parameter corresponding to the first longitudinal force according to the correction parameter, the sum of the weighted parameter and the correction parameter being 1; correcting the second longitudinal force according to the correction parameter to obtain a corrected second longitudinal force; and obtaining the target adhesion coefficient of each wheel according to the weighted parameter, the corrected second longitudinal force and the basic adhesion coefficient.

[0008] According to one aspect of an embodiment of the present application, determining the correction parameter corresponding to the second longitudinal force based on the real-time operating condition data includes: determining the throttle opening value of the vehicle based on the real-time operating condition data; if the throttle pedal opening value is greater than a preset throttle pedal opening value, determining the correction parameter corresponding to the second longitudinal force based on the throttle opening value, wherein the correction parameter is positively correlated with the throttle opening value.

[0009] According to one aspect of an embodiment of the present application, determining the correction parameter corresponding to the second longitudinal force based on the real-time operating condition data includes: determining the single-wheel torque change rate of the vehicle based on the real-time operating condition data; if the single-wheel torque change rate is greater than a preset torque change rate threshold, determining the correction parameter corresponding to the second longitudinal force based on the single-wheel torque change rate, and the positive correlation between the correction parameter and the single-wheel torque change rate is greater than the positive correlation between the correction parameter and the throttle opening value.

[0010] According to one aspect of an embodiment of the present application, determining the correction parameter corresponding to the second longitudinal force based on the real-time operating condition data includes: determining the basic adhesion coefficient difference between each wheel based on the real-time operating condition data, the basic adhesion coefficient difference including the maximum basic adhesion coefficient difference between the maximum basic adhesion coefficient and the minimum basic adhesion coefficient between the each wheel; determining the correction parameter corresponding to the second longitudinal force based on the maximum basic adhesion coefficient difference, the correction parameter being positively correlated with the maximum basic adhesion coefficient difference.

[0011] According to one aspect of an embodiment of the present application, the determination method also includes: obtaining the target adhesion coefficient difference between each wheel, the target adhesion coefficient difference including the maximum target adhesion coefficient difference between the maximum target adhesion coefficient and the minimum target adhesion coefficient between each wheel; if the maximum target adhesion coefficient difference is greater than a preset difference threshold, and the remaining target adhesion coefficient differences are all less than the preset difference threshold, determining the wheel to be corrected based on the maximum target adhesion coefficient difference; determining the average target adhesion coefficient corresponding to the target wheel of the vehicle, the target wheel being the other wheels in the vehicle except the wheel to be corrected, and correcting the target adhesion coefficient of the wheel to be corrected based on the average target adhesion coefficient.

[0012] According to one aspect of an embodiment of the present application, determining the correction parameter corresponding to the second longitudinal force based on the real-time operating condition data includes: determining the wheel instability state parameter based on the real-time operating condition data, wherein the wheel instability parameter includes the number of wheel slips, the wheel speed overshoot and the wheel slip duration; determining the correction parameter corresponding to the second longitudinal force based on any one or more of the number of wheel slips, the wheel speed overshoot and the wheel slip duration; wherein the correction parameter is positively correlated with the number of wheel slips, the wheel speed overshoot and the wheel slip duration.

[0013] According to one aspect of an embodiment of the present application, the determination method further includes: if the wheel slip rate is greater than a preset slip rate threshold, re-determining the basic adhesion coefficient of the wheel; obtaining the number of wheel slips of the vehicle within a preset time length; if the number of wheel slips is greater than a preset slip number threshold, and the wheel slip rate is greater than a preset slip rate threshold, updating the basic adhesion coefficient of each wheel.

[0014] According to one aspect of an embodiment of the present application, an adhesion coefficient determination device is provided, which includes: an acquisition module for acquiring the vehicle's wheel-end torque, wheel angular acceleration, wheel slip rate and wheel vertical load; a first determination module for determining the first longitudinal force of each wheel based on the wheel-end torque and the wheel angular acceleration; a second determination module for determining the basic adhesion coefficient of each wheel based on the first longitudinal force and the wheel vertical load; a third determination module for determining the second longitudinal force of each wheel based on the wheel slip rate and the tire model corresponding to the wheel; and a correction module for correcting the basic adhesion coefficient using the second longitudinal force to obtain a target adhesion coefficient for each wheel if the basic adhesion coefficient is less than a preset adhesion coefficient threshold.

[0015] According to one aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the electronic device implements the determination method as described above.

[0016] According to one aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which computer-readable instructions are stored. When the computer-readable instructions are executed by a processor of a computer, the computer executes the determination method described above.

[0017] According to one aspect of an embodiment of the present application, a computer program product is further provided, including a computer program, which implements the steps in the above-mentioned determination method when executed by a processor.

[0018] In the technical solution provided in the embodiments of the present application, the first longitudinal force and the second longitudinal force of the wheel are obtained by comprehensively considering the vehicle's wheel-end data and the tire model, which can more comprehensively reflect the force state of the wheel during driving. The combined use of these two longitudinal forces can further improve the accuracy of the adhesion coefficient calculation. The basic adhesion coefficient is directly calculated by the ratio of the first longitudinal force to the vertical load, which can capture sudden changes in road adhesion within milliseconds. When the basic coefficient is lower than the threshold, the second longitudinal force calculated by the tire model is introduced for correction, avoiding the underestimation of the wheel adhesion coefficient due to the nonlinear characteristics of road friction, significantly improving the real-time, accuracy and adaptability of the adhesion coefficient estimation, providing more reliable basic data support for vehicle dynamics control, helping to timely understand the adhesion state of the wheel, reducing safety hazards caused by inaccurate adhesion coefficient calculation, and improving vehicle driving safety.

[0019] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and it is clear that a person of ordinary skill in the art can derive other drawings based on these drawings without inventive effort.

[0021] Figure 1 1 is a schematic diagram of an implementation environment for determining the adhesion coefficient during driving, showing an exemplary embodiment of the present application.

[0022] Figure 2 is a flow chart of a method for determining an adhesion coefficient shown in an exemplary embodiment of the present application.

[0023] Figure 3 An exemplary embodiment of the present application is shown Figure 2 Specific flow chart of step S250 in .

[0024] Figure 4 An exemplary embodiment of the present application is shown Figure 3 Specific flow chart of step S330 in .

[0025] Figure 5 The embodiment of this application shows Figure 3 Specific flowchart of step S330 in another embodiment.

[0026] Figure 6 The embodiment of this application shows Figure 3 Specific flowchart of step S330 in another embodiment.

[0027] Figure 7 This is shown in the embodiment of the present application Figure 3 Specific flow chart of step S330 in another embodiment.

[0028] Figure 8 FIG. 4 is a flow chart of a method for determining an adhesion coefficient according to another exemplary embodiment of the present application.

[0029] Figure 9 The embodiment of this application shows Figure 3 Specific flowchart of step S330 in another embodiment.

[0030] Figure 10 FIG. 4 is a flow chart of a method for determining an adhesion coefficient according to another exemplary embodiment of the present application.

[0031] Figure 11 It is a block diagram of an adhesion coefficient determination device shown in an exemplary embodiment of the present application.

[0032] Figure 12 A schematic diagram of the structure of a computer system suitable for implementing an electronic device according to an embodiment of the present application is shown.

[0033] Explanation of the accompanying drawings: intelligent terminal 110, adhesion coefficient determination device 1100, acquisition module 1110, first determination module 1120, second determination module 1130, third determination module 1140, correction module 1150, computer system 1200, CPU 1201, ROM 1202, RAM 1203, bus 1204, I / O interface 1205, input part 1206, output part 1207, storage part 1208, communication part 1209, drive 1210, removable medium 1211. DETAILED DESCRIPTION

[0034] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. When the following description refers to the drawings, identical numerals in different figures represent identical or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0035] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0036] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, while others may be combined or partially combined. Therefore, the actual execution order may vary depending on the actual situation.

[0037] In this application, "plurality" refers to two or more. "And / or" describes the relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can mean: A exists alone, A and B exist simultaneously, and B exists alone. The character " / " generally indicates that the related objects are in an "or" relationship.

[0038] The wheel adhesion coefficient refers to the static friction coefficient between the tire and the road surface, reflecting the tire's adhesion ability under different road conditions. In essence, it is the combined result of the mechanical bite, molecular adhesion and hysteresis loss of the tire and road surface microstructure. It determines the maximum longitudinal / lateral force that the vehicle can transmit under specific conditions, and directly affects the vehicle's acceleration limit, braking performance and steering response. The adhesion coefficient is affected by many factors, including tire characteristics (material, pattern, degree of wear, tire pressure), road conditions (dry, wet, snow, gravel), temperature (tire and road temperature), vehicle speed (affecting the tire's contact area and deformation), and vehicle load (affecting the tire's ground pressure distribution). The calculation method can be experimentally measured, usually through braking tests or traction tests, measuring the maximum braking force or driving force under a known vertical load, and then calculating the adhesion coefficient (μ).

[0039] Figure 1 FIG. 1 is a schematic diagram of an exemplary embodiment of the present application showing an implementation environment for determining the adhesion coefficient during vehicle driving. Figure 1As shown, during vehicle travel, the vehicle's wheel-end torque, wheel angular acceleration, wheel slip, and wheel vertical load can be obtained via the smart terminal 110. A first longitudinal force on the vehicle's wheel can then be calculated based on the wheel-end torque and wheel angular acceleration, and a basic wheel adhesion coefficient can be determined based on the first longitudinal force and wheel vertical load. The smart terminal 110 can then determine a second longitudinal force on the wheel based on the wheel slip and the tire model corresponding to the wheel. If the basic adhesion coefficient is less than a preset adhesion coefficient threshold, the second longitudinal force is used to correct the basic adhesion coefficient to obtain a target adhesion coefficient for the wheel. This allows for accurate estimation of the vehicle's adhesion coefficient on the road.

[0040] in, Figure 1 The smart terminal 110 shown can be any terminal device that supports data collection and processing, such as a vehicle-mounted device, a smart phone, a vehicle-mounted computer, a tablet computer, a laptop computer, or a wearable device, but is not limited thereto.

[0041] In a vehicle's powertrain, distributed drive, due to its advantage of individually controllable four-wheel motors, can be combined with control algorithms to achieve independent control of all four wheels for different operating conditions and control objectives. Anti-skid control requires estimating the four-wheel adhesion coefficient to determine the maximum available driving force for all four wheels under the current operating conditions. This limits the maximum output torque of the anti-skid torque to ensure the vehicle maintains maximum power without slipping. Therefore, accurately determining the wheel adhesion coefficient improves the vehicle's anti-skid dynamics and stability.

[0042] In related technologies, the adhesion coefficient of the wheel is estimated based on the vehicle traction method. However, when the driving torque suddenly increases or decreases or the wheel acceleration suddenly changes, the estimation of the adhesion coefficient will have large deviations and fluctuations, which cannot effectively utilize the power of the power system or increase the slip of the wheel, resulting in a large error in the estimation of the wheel adhesion coefficient, thereby affecting the vehicle's anti-skid performance.

[0043] The issues identified above are generally applicable to common travel scenarios. It can be seen that existing methods for calculating the adhesion coefficient are inaccurate, with large errors, which affect the vehicle's anti-skid performance. To address these issues, the present application provides, in various embodiments, a method for determining an adhesion coefficient, an apparatus for determining an adhesion coefficient, an electronic device, a computer-readable storage medium, and a computer program product. These embodiments are described in detail below.

[0044] See also Figure 2 , Figure 2 is a flow chart of a method for determining adhesion coefficient according to an exemplary embodiment of the present application. Figure 1The implementation environment shown is specifically executed by the smart terminal 110 in the implementation environment. It should be understood that the method can also be applied to other exemplary implementation environments and specifically executed by devices in other implementation environments. This embodiment does not limit the implementation environment to which the method is applicable.

[0045] like Figure 2 As shown, in an exemplary embodiment, the adhesion coefficient determination method includes at least steps S210 to S250, which are described in detail as follows:

[0046] Step S210: Obtain the vehicle's wheel end torque, wheel angular acceleration, wheel slip rate, and wheel vertical load.

[0047] A vehicle's wheel-end torque refers to the actual driving torque output by the drive wheels. It is formed by the engine torque after being amplified or attenuated by the transmission system. Wheel-end torque can usually be obtained using a strain gauge sensor attached to the surface of the vehicle's drive shaft. Alternatively, the wheel-end torque can be determined by using the change in magnetic permeability of the magnetic material of a magnetic sensor under torque. In some pure electric or hybrid vehicles, the vehicle's wheel-end torque can also be determined by the drive motor's phase current and magnetic field parameters. Wheel angular acceleration can also be obtained by differentiating the vehicle's wheel speed signal, where the wheel angular velocity reflects the transient rate of change of tire rotation. Slip is a parameter that describes the degree of slip between the wheel and the road surface. It is defined as the ratio of the wheel's sliding velocity to the wheel's rolling velocity. Therefore, slip can be obtained from the wheel's rolling velocity and the wheel's rolling velocity, or by other methods. Wheel vertical load can be calculated using a suspension travel sensor combined with suspension stiffness, or by other methods.

[0048] Step S220: determining the first longitudinal force of each wheel based on the wheel end torque and the wheel angular acceleration.

[0049] Wheel torque refers to the torque acting on the wheels, typically generated by the motor or engine, while wheel angular acceleration is the vehicle's speed. Longitudinal force, on the other hand, should be considered the force exerted on the wheels in the direction of travel, often referred to as traction or braking force. Wheel angular acceleration can affect wheel slip, and thus the longitudinal force. If there is a discrepancy between wheel angular acceleration and wheel speed—in other words, when slip occurs—the longitudinal force may be determined not only by torque but also by slip.

[0050] Optionally, the theoretical longitudinal force is first calculated based on the wheel end torque and the wheel radius, and then corrected according to the vehicle speed. For example, when the vehicle speed is very high, the tire may approach or reach the adhesion limit, and the actual longitudinal force may be less than the theoretical calculated value. Alternatively, if the wheel speed corresponding to the wheel angular acceleration is inconsistent with the wheel speed calculated based on the torque, the efficiency or loss of the power transmission system may be involved. Alternatively, the wheel angular acceleration may be used to calculate the angular velocity of the wheel, and then combined with the torque to calculate the power, and then derive the force. In some feasible embodiments, the first longitudinal force of the vehicle's wheels can also be calculated by the traction method, wherein the traction method mainly calculates the longitudinal force of the vehicle based on the wheel end torque and the wheel angular acceleration, and then calculates the first longitudinal force of each wheel of the vehicle.

[0051]

[0052] in, is the first longitudinal force of the wheel, The wheel end torque of each wheel, is the wheel end moment of inertia of each wheel, is the wheel angular acceleration of each wheel, is the wheel radius.

[0053] Step S230: determining a basic adhesion coefficient of each wheel based on the first longitudinal force and the vertical wheel load.

[0054] For example, the basic adhesion coefficient of each wheel can be obtained according to the ratio of the first longitudinal force to the vertical load of the wheel. The basic adhesion coefficient is a key parameter in vehicle dynamics control. Its essence is the ratio of the maximum friction force between the tire and the road surface that can be utilized at the current moment. The first longitudinal force derived from the wheel end torque and wheel angular acceleration combined with the vertical load can quickly estimate the current road adhesion capacity, providing a benchmark for subsequent slip rate control and traction distribution. Therefore, the basic adhesion coefficient reflects the friction utilization potential of the tire under the current working conditions (to take into account the nonlinear effect of slip rate). Among them, the vertical load of the wheel includes the static load caused by the vehicle mass distribution, and the dynamic load affected by the pitch and roll motion of the vehicle.

[0055] Step S240 : determining the second longitudinal force of each wheel based on the wheel slip rate and the tire model corresponding to the wheel.

[0056] A tire model is a mathematical model used to describe the mechanical behavior of a tire in contact with the road. Its core objective is to quantify dynamic characteristics such as longitudinal force (driving / braking force), lateral force (cornering force), self-aligning torque (self-alignment torque), and vertical load distribution generated by the tire under different operating conditions. It is a core tool for vehicle dynamics analysis, control system design, and simulation. Common tire model types include magic formulas, brush models, and linear models. That is to say, once the road condition information is obtained and the appropriate tire model is selected, the second longitudinal force of the wheel can be calculated. Specifically, parameters such as road friction coefficient, road roughness, road material, road temperature and humidity can be input into the tire model; the current state of the tire, such as air pressure, degree of wear, temperature, etc., which will also affect the mechanical behavior of the tire, are determined, and then kinematic parameters such as wheel speed, slip rate, and sideslip angle are input. Then, based on the tire model and input parameters, the longitudinal force of the wheel is calculated. If it is in the magic formula, this usually involves a series of complex mathematical operations, including trigonometric functions, exponential functions, and polynomials, etc., and then the second longitudinal force of the wheel is output. This force is the result of the interaction between the tire and the road, taking into account the influence of road conditions and tire characteristics.

[0057] For example, the second longitudinal force is the transient longitudinal force exerted by the tire in nonlinear friction regimes (such as brake slip or drive slip), which directly impacts the response accuracy of vehicle stability control. By combining the slip ratio (λ) with a tire model, the tire's ultimate friction capacity can be dynamically predicted. The slip ratio represents the relative slip between the wheel and the ground, and can also be determined from the wheel's center velocity, rolling radius, and angular velocity.

[0058] In some feasible embodiments, a magic formula may be selected as the tire model, and then the second longitudinal force corresponding to each wheel of the vehicle is calculated according to the magic formula, as follows:

[0059]

[0060] in, is the second longitudinal force of the wheel, is the wheel slip ratio, , , , They are stiffness factor, shape factor, peak factor and curvature factor. , shape factor , crest factor and the curvature factor , can be determined based on the vehicle's tires and the characteristics of the road the vehicle is on. Therefore, during application, parameter adjustment and verification may be required based on factors such as different tire types, sizes, air pressures, and road conditions. The wheel slip rate is the ratio of the wheel's sliding degree relative to the pure rolling state.

[0061] Step S250: If the basic adhesion coefficient is less than the preset adhesion coefficient threshold, the second longitudinal force is used to correct the basic adhesion coefficient to obtain a target adhesion coefficient for each wheel.

[0062] For example, if the base adhesion coefficient is less than a preset threshold (e.g., 0.4 for wet roads), the adhesion coefficient calculated using the first longitudinal force is unreliable and a correction process needs to be initiated. Using a tire model (e.g., the magic formula), the actual longitudinal force (second longitudinal force) between the tire and the ground is calculated in real time. This can capture transient friction characteristics (e.g., nonlinear changes in friction due to slip), gradually increasing the target adhesion coefficient based on slip. The second longitudinal force correction increases with slip, minimizing the impact of wheel slip on the accuracy of the calculated adhesion coefficient. This allows the target adhesion coefficient to be calculated for each wheel of the vehicle.

[0063] In some embodiments of the present application, by comprehensively considering the vehicle's wheel-end data and the tire model to obtain the first longitudinal force and the second longitudinal force of the wheel, the force state of the wheel during driving can be more comprehensively reflected. The combined use of these two longitudinal forces can further improve the accuracy of the adhesion coefficient calculation. The basic adhesion coefficient is directly calculated by the ratio of the first longitudinal force to the vertical load, which can capture sudden changes in road adhesion within milliseconds. When the basic coefficient is lower than the threshold, the second longitudinal force calculated by the tire model is introduced for correction, avoiding the underestimation of the wheel adhesion coefficient due to the nonlinear characteristics of road friction, significantly improving the real-time, accuracy and adaptability of the adhesion coefficient estimation, providing more reliable basic data support for vehicle dynamics control, helping to timely understand the adhesion state of the wheel, reducing safety hazards caused by inaccurate adhesion coefficient calculation, and improving vehicle driving safety.

[0064] Based on the above examples, please refer to Figure 3 In one exemplary embodiment provided in this application, the specific implementation process of using the second longitudinal force to correct the basic adhesion coefficient to obtain the target adhesion coefficient of each wheel may further include steps S310 to S330, which are described in detail as follows:

[0065] Step S310, obtaining the road type on which the vehicle is located;

[0066] Step S320: If the road surface type is characterized as a uniform road surface, real-time operating condition data of the vehicle is obtained;

[0067] Step S330 : determining a correction parameter corresponding to the second longitudinal force based on the real-time working condition data, so as to correct the basic adhesion coefficient based on the correction parameter and the second longitudinal force to obtain a target adhesion coefficient for each wheel.

[0068] For example, pavement types can be categorized based on various factors, including pavement material, structural characteristics, and usage conditions. For example, while a vehicle is driving, onboard sensors (such as cameras, radar, and accelerometers) can collect information about pavement conditions, including surface roughness, friction coefficient, material type (e.g., asphalt, concrete, gravel), humidity, and temperature. Based on this information, machine learning algorithms or expert systems can be used to identify the pavement type. For example, by comparing this collected information with a database of known pavement types, the most suitable pavement type can be determined. Common pavement types in applications include: highway pavements, typically made of asphalt or concrete, with high smoothness and a moderate friction coefficient; urban road pavements, which may include asphalt, concrete, or masonry pavements, with high smoothness but may be affected by factors such as traffic flow and weather; rural road pavements, which may include dirt, gravel, or concrete / asphalt pavements, with low smoothness and a wide range of friction coefficients; and special surface types such as icy, slippery, and muddy roads. These pavement types significantly impact vehicle driving performance.

[0069] In addition, it is also possible to determine whether the road type on which the vehicle is located is a uniform road surface based on the size of the error between the basic adhesion coefficients of each wheel of the vehicle. If the size of the error is within the allowable error range, it can be determined that the road type on which the vehicle is located is a uniform road surface.

[0070] In some embodiments of the present application, real-time operating condition data can be used to determine the current vehicle parameters (e.g., vehicle speed, acceleration, driving or braking torque, wheel speed, slip ratio, vertical load, throttle opening value, single-wheel torque change rate, wheel instability parameters, basic adhesion coefficient, etc.). Wheel instability parameters include, but are not limited to, the number of wheel slips, wheel speed overshoot, and wheel slip duration. A correction parameter corresponding to the second longitudinal force can then be determined based on the real-time vehicle operating condition data. The logic for correcting the second longitudinal force based on the real-time vehicle operating condition information includes, but is not limited to, determining the correction parameter corresponding to the second longitudinal force based on acceleration and vehicle parameters (e.g., center of mass height, wheelbase) when the vehicle accelerates or brakes violently, causing load transfer between the front and rear wheels; determining the correction parameter corresponding to the second longitudinal force based on acceleration and vehicle parameters (e.g., center of mass height, wheelbase); determining the correction parameter corresponding to the second longitudinal force based on the ratio of actual torque to limit torque when dynamic torque approaches the tire's adhesion limit; determining the correction parameter corresponding to the second longitudinal force based on the estimated turning radius using a steering wheel angle or lateral acceleration sensor when cornering, where lateral acceleration affects the tire's longitudinal grip; or determining the correction parameter corresponding to the second longitudinal force based on the effects of tire temperature or wear on adhesion. Finally, the basic adhesion coefficient of the wheel is corrected by combining the correction parameter corresponding to the second longitudinal force and the second longitudinal force, thereby obtaining the target adhesion coefficient of the wheel.

[0071] In some embodiments of the present application, by comprehensively utilizing the basic adhesion coefficient, road type judgment, real-time working condition data and the second longitudinal force correction parameter, the force conditions of the wheels on the actual road surface can be more accurately reflected, thereby improving the accuracy of the adhesion coefficient calculation, and making the adhesion coefficient calculation more flexible and accurate, which helps to cope with complex and changeable road environments and improve the safety and stability of vehicle driving.

[0072] Based on the above examples, please refer to Figure 4 In one exemplary embodiment provided in this application, the specific implementation process of determining the correction parameter corresponding to the second longitudinal force based on the real-time operating condition data, and correcting the basic adhesion coefficient based on the correction parameter and the second longitudinal force to obtain the target adhesion coefficient of each wheel may further include steps S410 to S430, which are described in detail as follows:

[0073] Step S410, determining a weighted parameter corresponding to the first longitudinal force according to the correction parameter, where the sum of the weighted parameter and the correction parameter is 1;

[0074] Step S420, correcting the second longitudinal force according to the correction parameter to obtain a corrected second longitudinal force;

[0075] Step S430: Obtain a target adhesion coefficient for each wheel according to the weighted parameter, the corrected second longitudinal force, and the basic adhesion coefficient.

[0076] Continuing with the above-mentioned embodiments, a correction parameter is calculated based on real-time operating condition data (such as acceleration, torque, and lateral force). This parameter reflects the degree to which the current operating condition affects the adhesion coefficient. The correction parameter typically ranges from 0 to 1, with larger values ​​indicating a more significant operating condition impact. For example, a weighting coefficient corresponding to the first longitudinal force can be determined based on the correction parameter corresponding to the second longitudinal force. The sum of the weighting coefficient and the correction parameter is 1, and the weighting parameter and the correction parameter are complementary to ensure that the sum is 1. The weighting parameter is then applied to the base adhesion coefficient and simultaneously incorporated into the corrected second longitudinal force. The second longitudinal force is adjusted using the correction parameter. The larger the correction parameter, the greater the adjustment of the second longitudinal force. The base adhesion coefficient and the corrected second longitudinal force are then combined through weighted averaging or proportional blending to obtain the final target adhesion coefficient for each wheel. This is used to calculate the target adhesion coefficient for each wheel of the vehicle.

[0077] In some feasible embodiments, the adhesion coefficient corresponding to the wheel may be calculated using the first longitudinal force and the second longitudinal force of the wheel, as follows:

[0078]

[0079] in, is the target adhesion coefficient of the wheel, Represents the wheel, is the first longitudinal force of the wheel; is the second longitudinal force of the wheel; is the vertical load of each wheel; is the weighted coefficient corresponding to the first longitudinal force, is the correction parameter corresponding to the second longitudinal force, and then the target adhesion coefficient corresponding to the wheel can be determined according to the first longitudinal force and the second longitudinal force of the wheel. 1. When it is 0, is the basic adhesion coefficient corresponding to each wheel.

[0080] In some embodiments of the present application, by introducing weighted parameters associated with the correction parameters, comprehensively correcting the second longitudinal force and combining it with the basic adhesion coefficient to obtain the target adhesion coefficient, the vehicle driving state and road conditions can be more accurately adapted, significantly improving the accuracy of wheel adhesion coefficient estimation and vehicle control stability.

[0081] Next, based on the above embodiment, please refer to Figure 5 In one of the exemplary embodiments provided in this application, the specific implementation process of determining the correction parameter corresponding to the second longitudinal force based on the real-time working condition data may further include steps S510 and S520, which are described in detail as follows:

[0082] Step S510, determining the throttle opening value of the vehicle based on the real-time operating condition data;

[0083] Step S520: If the accelerator pedal opening value is greater than the preset accelerator pedal opening value, a correction parameter corresponding to the second longitudinal force is determined based on the accelerator opening value, wherein the correction parameter is positively correlated with the accelerator opening value.

[0084] Exemplarily, the position signal of the vehicle's accelerator pedal can be determined through the vehicle's communication bus or sensor system, wherein the position signal of the accelerator pedal can be converted into a throttle opening value. Thereafter, it is determined whether the throttle opening value is greater than a preset throttle opening threshold value, which is set according to vehicle performance and driving requirements. If the throttle opening value of the vehicle is greater than the preset throttle opening threshold value, the correction parameter determination link is entered, wherein the correction parameter corresponding to the second longitudinal force can be determined by a pre-established positive correlation between the throttle opening value and the correction parameter value, and then the second longitudinal force (such as driving torque or tire force) is adjusted according to the correction parameter to match the power requirement under high throttle opening, and combined with the positive correlation design to ensure that the deeper the accelerator is pressed, the more positive the correction to the wheel adhesion coefficient is.

[0085] Optionally, as shown in Table 1 below, taking the preset throttle opening threshold as 80% as an example, a positive correlation between the vehicle's throttle opening value and the correction parameter can be pre-set and mapped to a corresponding numerical relationship.

[0086] Table 1

[0087]

[0088] After the throttle opening value of the vehicle is determined according to the real-time working condition data of the vehicle, the correction parameter corresponding to the second longitudinal force and the weighting coefficient corresponding to the first longitudinal force can be quickly determined according to Table 1.

[0089] In some embodiments of the present application, the throttle opening value is accurately obtained based on real-time operating condition data, and an opening threshold is set to trigger a correction mechanism. When the throttle pedal opening value reaches a preset value or above, the correction parameter is positively correlated with the throttle opening value, which can dynamically adapt to the driver's acceleration intention and vehicle power requirements, and timely and accurately adjust the second longitudinal force correction parameter, effectively improving the accuracy of the vehicle's adhesion coefficient estimation under different acceleration conditions, enhancing the vehicle's power response and driving stability during acceleration, avoiding the risk of insufficient power output or wheel slippage due to adhesion coefficient estimation deviation, and improving driving safety and control experience.

[0090] Based on the above examples, please refer to Figure 6In one of the exemplary embodiments provided in this application, the specific implementation process of determining the correction parameter corresponding to the second longitudinal force based on the real-time working condition data may further include steps S610 and S620, which are described in detail as follows:

[0091] Step S610, determining a single wheel torque change rate of the vehicle based on real-time operating condition data;

[0092] In step S620, if the single-wheel torque change rate is greater than the preset torque change rate threshold, a correction parameter corresponding to the second longitudinal force is determined based on the single-wheel torque change rate, and the positive correlation between the correction parameter and the single-wheel torque change rate is greater than the positive correlation between the correction parameter and the throttle opening value.

[0093] For example, the torque signal corresponding to each wheel of the vehicle can be obtained through the vehicle's communication bus or wheel speed sensor, and the vehicle's single-wheel torque change rate can be calculated based on the torque signal. The single-wheel torque change rate is the rate of change of the torque of a single wheel of the vehicle per unit time. The real-time single-wheel change rate value can be obtained by performing differential or difference processing on the wheel torque signal. The single-wheel torque change rate is then compared with a preset torque change rate threshold. The preset torque change rate threshold can be set based on the vehicle's powertrain and control requirements. If the single-wheel torque change rate is greater than the preset torque change rate threshold, the process of determining the correction parameter corresponding to the second longitudinal force is entered. For example, a positive correlation can be established between the single-wheel torque change rate and the correction parameter, and the greater the single-wheel torque change rate, the higher the value of the correction parameter, and its growth rate is faster than the correction parameter related to the throttle opening.

[0094] Optionally, as shown in Table 2 below, taking the preset single-wheel torque change rate as 50 as an example (unit: Nm / 100ms), a positive correlation between the vehicle's single-wheel torque change rate and the correction parameter can be preset and mapped to a corresponding numerical relationship.

[0095] Table 2

[0096]

[0097] After determining the single-wheel torque change rate of the vehicle based on the real-time operating data of the vehicle, the correction parameter corresponding to the second longitudinal force and the weighting coefficient corresponding to the first longitudinal force can be quickly determined based on Table 2.

[0098] In some embodiments of the present application, the vehicle's single-wheel torque change rate is determined by real-time operating condition data, and a preset threshold is used as a judgment basis. When the single-wheel torque change rate exceeds the threshold, the correction parameter of the second longitudinal force is determined based on it, and a stronger positive correlation is given between the single-wheel torque change rate and the correction parameter. This can more sensitively capture the drastic fluctuations in single-wheel torque during vehicle driving, and quickly and accurately adjust the correction parameter. Compared with only considering the throttle opening value, it can more promptly and effectively respond to changes in adhesion caused by sudden torque changes under complex working conditions, significantly improve the accuracy of the vehicle's adhesion coefficient estimation under conditions such as rapid acceleration and sudden lane changes, enhance vehicle driving stability and safety, and optimize handling performance.

[0099] Based on the above examples, please refer to Figure 7 In one of the exemplary embodiments provided in this application, the specific implementation process of determining the correction parameter corresponding to the second longitudinal force based on the real-time working condition data may further include steps S710 and S720, which are described in detail as follows:

[0100] Step S710, determining a basic adhesion coefficient difference between each wheel of the vehicle based on the real-time working condition data, where the basic adhesion coefficient difference includes a maximum basic adhesion coefficient difference between a maximum basic adhesion coefficient and a minimum basic adhesion coefficient between each wheel;

[0101] Step S720 : If the maximum basic adhesion coefficient difference is greater than the first preset difference threshold, a correction parameter corresponding to the second longitudinal force is determined based on the maximum basic adhesion coefficient difference, where the correction parameter is positively correlated with the maximum basic adhesion coefficient difference.

[0102] Following the above embodiment, the basic adhesion coefficient corresponding to each wheel of the vehicle can be determined based on the real-time working condition data of the vehicle through the above embodiment, for example, the left front wheel , right front wheel , left rear wheel , right rear wheel , then find the maximum value from the basic adhesion coefficients of all wheels and minimum value , and calculate the maximum value and minimum value The maximum base adhesion coefficient difference between The difference reflects the difference in adhesion between each wheel of the vehicle and the road surface (such as split road, partial slip or uneven ice and snow coverage), and determines the maximum basic coefficient difference. The relationship between the maximum basic adhesion coefficient difference and the first preset difference threshold, wherein the first preset difference threshold is a threshold set according to the vehicle dynamics characteristics and control requirements. If the difference is greater than the first preset difference threshold, the maximum basic adhesion difference can be established. The positive correlation between the correction parameters corresponding to the second longitudinal force and the maximum basic adhesion coefficient difference The larger the value, the higher the correction parameter, reflecting the more significant impact of uneven road adhesion on control. The correction parameter is used to adjust the secondary longitudinal force (such as drive torque distribution or brake pressure) to compensate for adhesion differences between wheels. The positive correlation design ensures that the greater the adhesion difference, the more aggressive the system's correction of the adhesion coefficient.

[0103] Optionally, as shown in Table 3 below, taking the first preset difference threshold as 0.05 as an example, a positive correlation between the maximum basic adhesion coefficient difference of the vehicle and the correction parameter can be preset and mapped to a corresponding numerical relationship.

[0104] Table 3

[0105]

[0106] After determining the maximum basic adhesion coefficient difference between the basic adhesion coefficients of the vehicle wheels based on the real-time working condition data of the vehicle, the correction parameter corresponding to the second longitudinal force and the weighting coefficient corresponding to the first longitudinal force can be quickly determined based on Table 3.

[0107] In some embodiments of the present application, the basic adhesion coefficient difference between each wheel of the vehicle (especially the maximum basic adhesion coefficient difference) is calculated through real-time working condition information, and a first preset difference threshold is used as a judgment standard. When the difference exceeds the limit, the correction parameter of the second longitudinal force is determined based on it, and the two are positively correlated. The system can keenly perceive the difference in adhesion conditions between the wheels, and adjust the correction parameter in a timely and accurate manner when significant differences occur. It can effectively deal with uneven wheel adhesion caused by factors such as uneven road surface and vehicle tilt, significantly improve the accuracy of the vehicle's adhesion coefficient estimation on complex adhesion roads, enhance vehicle driving stability and safety, and optimize the vehicle's handling performance under different road conditions.

[0108] Based on the above examples, please refer to Figure 8 In one of the exemplary embodiments provided in this application, the specific implementation process of the above-mentioned adhesion coefficient determination method may further include steps S810 to S840, which are described in detail as follows:

[0109] Step S810, obtaining target adhesion coefficient differences between the wheels, where the target adhesion coefficient differences include a maximum target adhesion coefficient difference between a maximum target adhesion coefficient and a minimum target adhesion coefficient between the wheels;

[0110] Step S820: If the maximum target adhesion coefficient difference is greater than the preset difference threshold, and the remaining target adhesion coefficient differences are all less than the preset difference threshold, then determining the wheel to be corrected based on the maximum target adhesion coefficient difference;

[0111] Step S830, determining an average target adhesion coefficient corresponding to target wheels of the vehicle, where the target wheels are wheels other than the wheel to be corrected, and correcting the target adhesion coefficient of the wheel to be corrected based on the average target adhesion coefficient.

[0112] Following the above-described embodiment, after calculating the target adhesion coefficients corresponding to each wheel of the vehicle, the target adhesion coefficient differences between the target adhesion coefficients of the vehicle wheels can be calculated. Specifically, the maximum and minimum target adhesion coefficients are determined, and the difference between them, i.e., the maximum target adhesion coefficient difference, is calculated. The calculated maximum target adhesion coefficient difference is then compared with a preset difference threshold. This preset difference threshold is set based on the vehicle's design, performance requirements, and safety considerations. Simultaneously, it is necessary to check whether the target adhesion coefficient differences between the remaining wheels are all less than the preset difference threshold. This ensures that only the maximum target adhesion coefficient difference is significantly excessive, while the other differences are within an acceptable range. If the maximum target adhesion coefficient difference is greater than the preset difference threshold, and the remaining target adhesion coefficient differences are all less than the preset difference threshold, it can be determined that the target adhesion coefficient of one wheel is significantly different from that of the other wheels. This wheel is the wheel to be corrected, and the target wheels are the remaining wheels in the vehicle excluding the wheel to be corrected. The target adhesion coefficients of these target wheels can then be averaged, i.e., the average target adhesion coefficient. Based on this average target adhesion coefficient, the target adhesion coefficient of the wheel to be corrected can then be corrected. The goal of this correction is to bring the target adhesion coefficient of the wheel to be corrected closer to that of the other wheels, thereby improving vehicle stability and safety. After correcting the target adhesion coefficient of the wheel to be corrected, the target adhesion coefficient differences between the wheels need to be rechecked to ensure that the maximum target adhesion coefficient difference has been reduced to an acceptable range and that other differences remain within reasonable levels.

[0113] In addition, in some feasible embodiments, after the target adhesion coefficient of the wheel is updated, if the slip rate of the wheel is less than the preset slip rate threshold within the preset time period after the target adhesion coefficient is updated, the target adhesion coefficient of the wheel may no longer be continuously updated; if it continues for the preset time period, the target adhesion coefficient of the currently calculated wheel can be compared with the target adhesion coefficient corresponding to the wheel at the previous moment, and the larger value can be taken as the current target adhesion coefficient of the wheel, and the "take the larger" rule can be followed at subsequent moments to ensure that the target adhesion coefficient of the wheel does not decrease.

[0114] In some embodiments of the present application, by obtaining the target adhesion coefficient difference between each wheel of the vehicle and setting a difference threshold for logical judgment, when only the maximum target adhesion coefficient difference exceeds the threshold and the remaining differences are all less than the threshold, the wheel with an abnormal adhesion coefficient (i.e., the wheel to be corrected) can be accurately identified. Subsequently, by calculating the average target adhesion coefficient of the remaining normal wheels (target wheels), and using this as a benchmark to correct the adhesion coefficient of the abnormal wheel, it can quickly respond to and handle the problem of uneven distribution of adhesion coefficients between wheels, avoiding vehicle instability or performance degradation caused by single-wheel adhesion abnormality, and by introducing the average adhesion coefficient, ensure that the corrected adhesion coefficient meets the overall vehicle dynamics requirements while avoiding other potential risks caused by over-correction, thereby effectively improving the vehicle's driving stability, safety and controllability.

[0115] Based on the above examples, please refer to Figure 9 In one of the exemplary embodiments provided in this application, the implementation process of determining the correction parameter corresponding to the second longitudinal force based on the real-time working condition data may further include steps S910 to S930, which are described in detail as follows:

[0116] Step S910, determining wheel instability parameters based on real-time working condition data, wherein the wheel instability parameters include the number of wheel slips, wheel speed overshoot, and wheel slip duration;

[0117] Step S920, determining a correction parameter corresponding to the second longitudinal force based on any one or more of the number of wheel slips, the wheel speed overshoot, and the wheel slip time;

[0118] In step S930, the correction parameter is positively correlated with the number of wheel slips, the wheel speed overshoot, and the wheel slip duration.

[0119] For example, relevant sensors (such as wheel speed sensors) can be used to obtain real-time wheel speed, acceleration, and other data for each wheel, determine whether each wheel is in a slipping state (e.g., wheel speed exceeds a threshold or differs significantly from a reference vehicle speed), and count the number of slipping wheels. For slipping wheels, the difference between the actual wheel speed and the ideal wheel speed (based on the vehicle reference speed) is calculated to reflect the severity of the slip, and the duration from the start of the slip to the return to stability reflects the duration of the slip. The number of wheel slips, wheel speed overshoot, and wheel slip duration all reflect the degree of vehicle instability, but their importance varies. For example, the correction parameter corresponding to the second longitudinal force has the highest positive correlation with the number of wheel slips (directly affecting vehicle stability), followed by wheel speed overshoot (reflecting the severity of the slip), and finally the wheel slip duration (reflecting the duration of the slip, but may have a smaller impact due to the recovery strategy).

[0120] Optionally, as shown in Table 4, a positive correlation between wheel instability factors (eg, number of wheel slips, wheel slip time, and wheel speed overshoot) and correction parameters may be established in advance and mapped to corresponding numerical relationships.

[0121] Table 4

[0122]

[0123] Optionally, Table 5 shown below can be obtained by combining Tables 1-4 above, so that during vehicle operation, when the vehicle is traveling on a uniform road surface, the correction parameters corresponding to the second longitudinal force and the weighting coefficient corresponding to the first longitudinal force can be determined according to Table 5 below, thereby obtaining the target adhesion coefficient corresponding to the wheel.

[0124] Table 5

[0125]

[0126] If the factors in Table 5 above appear at the same time, the corresponding The corresponding average value determines the weighting coefficient corresponding to the first longitudinal force, and the corresponding The correction coefficient corresponding to the second longitudinal force is determined by the corresponding average value, and then the target adhesion coefficient of the wheel is calculated.

[0127] In some embodiments of the present application, wheel instability state parameters including the number of wheel slips, wheel speed overshoot and slip duration are determined through real-time working condition data, and correction parameters of the second longitudinal force are determined based on one or more of them. At the same time, the positive correlation degree between each parameter and the correction parameter is reasonably set. This can comprehensively consider various wheel instability factors, more accurately reflect the abnormal state of the wheels during vehicle driving, and then adjust the correction parameters in a timely and targeted manner, effectively improving the vehicle's ability to cope with wheel instability under complex working conditions, enhancing driving stability and safety, and optimizing vehicle handling performance.

[0128] Further, based on the above embodiment, please refer to Figure 10 In one of the exemplary embodiments provided in this application, the specific implementation process of the above-mentioned adhesion coefficient determination method may further include steps S1010 to S1030, which are described in detail as follows:

[0129] Step S1010: if the wheel slip rate is greater than a preset slip rate threshold, re-determine the basic adhesion coefficient of the wheel;

[0130] Step S1020, obtaining the number of wheel slips of the vehicle within a preset time period;

[0131] Step S1030: If the number of wheel slips is greater than the preset slip number threshold, and the wheel slip rate is greater than the preset slip rate threshold, the basic adhesion coefficient of each wheel is updated.

[0132] For example, the wheel speed, actual vehicle speed, and overall vehicle motion state can be obtained. For each slipping wheel, the slip ratio is calculated: slip ratio = (vehicle reference speed - actual wheel speed) / vehicle reference speed × 100%. The vehicle reference speed refers to the vehicle's forward speed under ideal conditions (i.e., no wheel slip). A slip ratio threshold (e.g., slip ratio > 20%) is then pre-set to identify severe slip conditions.

[0133] Optionally, the wheel speed of each wheel and the overall vehicle motion state can be acquired in real time using sensors such as wheel speed sensors. For each wheel, the difference between its actual wheel speed and the ideal wheel speed based on the vehicle's reference speed is calculated. If the difference exceeds a preset slip threshold (e.g., the wheel speed is significantly higher than the reference speed), the wheel is determined to be slipping. Over a preset duration (e.g., 1 second), the number of wheels in a slipping state is continuously counted. For example, if 2 or more of the 4 wheels continuously slip for 1 second, the number of slipping wheels is recorded as ≥ 2. Based on the vehicle's dynamic characteristics and control requirements, a pre-set threshold (e.g., ≥ 2 slipping wheels) is pre-set. If the number of slipping wheels reaches or exceeds the preset threshold within the preset duration, and the slip rates of all slipping wheels exceed the preset slip rate threshold, the next step is to re-determine the base adhesion coefficient to update the base adhesion coefficient of the wheel. The detailed implementation of the base adhesion coefficient determination scheme can be found in the aforementioned embodiments and will not be further elaborated here.

[0134] In some embodiments of the present application, the number of slipping wheels within a preset time period is counted through real-time working condition data, and when the number exceeds a preset threshold, the slip rate of the slipping wheels is further obtained. If the slip rates all exceed the preset threshold, the basic adhesion coefficient of the wheel is re-determined. Through multi-level condition judgment, the severe slipping condition of the vehicle is accurately captured, and the basic adhesion coefficient is re-evaluated in time. This can effectively deal with large-scale severe slipping of vehicles under complex road conditions, improve the accuracy of adhesion coefficient estimation, provide a more reliable basis for vehicle control, and enhance vehicle driving stability and safety.

[0135] like Figure 11As shown, the exemplary adhesion coefficient determination device 1100 includes: an acquisition module 1110, used to obtain the vehicle's wheel end torque, wheel angular acceleration, wheel slip rate and wheel vertical load; a first determination module 1120, used to determine the first longitudinal force of each wheel based on the wheel end torque and wheel angular acceleration; a second determination module 1130, used to determine the basic adhesion coefficient of each wheel based on the first longitudinal force and the wheel vertical load; a third determination module 1140, used to determine the second longitudinal force of each wheel based on the wheel slip rate and the tire model corresponding to the wheel; and a correction module 1150, used to correct the basic adhesion coefficient using the second longitudinal force if the basic adhesion coefficient is less than a preset adhesion coefficient threshold, so as to obtain the target adhesion coefficient of each wheel.

[0136] According to one aspect of an embodiment of the present application, the correction module 1150 is also used to obtain the type of road surface on which the vehicle is located; if the road surface type is characterized as a uniform road surface, the real-time operating condition data of the vehicle is obtained; based on the real-time operating condition data, a correction parameter corresponding to the second longitudinal force is determined, so as to correct the basic adhesion coefficient based on the correction parameter and the second longitudinal force to obtain the target adhesion coefficient of each wheel.

[0137] According to one aspect of an embodiment of the present application, the above-mentioned correction module 1150 is also used to determine a weighted parameter corresponding to the first longitudinal force based on the correction parameter, and the sum of the weighted parameter and the correction parameter is 1; correct the second longitudinal force according to the correction parameter to obtain a corrected second longitudinal force; and obtain the target adhesion coefficient of each wheel based on the weighted parameter, the corrected second longitudinal force and the basic adhesion coefficient.

[0138] According to one aspect of an embodiment of the present application, the above-mentioned correction module 1150 is also used to determine the throttle opening value of the vehicle based on real-time operating condition data; if the throttle pedal opening value is greater than the preset throttle pedal opening value, then the correction parameter corresponding to the second longitudinal force is determined based on the throttle opening value, wherein the correction parameter is positively correlated with the throttle opening value.

[0139] According to one aspect of an embodiment of the present application, the correction module 1150 is further used to determine the single-wheel torque change rate of the vehicle based on real-time operating condition data; if the single-wheel torque change rate is greater than a preset torque change rate threshold, a correction parameter corresponding to the second longitudinal force is determined based on the single-wheel torque change rate, and the positive correlation between the correction parameter and the single-wheel torque change rate is greater than the positive correlation between the correction parameter and the throttle opening value.

[0140] According to one aspect of an embodiment of the present application, the correction module 1150 is also used to determine the basic adhesion coefficient difference between each wheel based on real-time working condition data, where the basic adhesion coefficient difference includes the maximum basic adhesion coefficient difference between the maximum basic adhesion coefficient and the minimum basic adhesion coefficient between each wheel; and determine the correction parameter corresponding to the second longitudinal force based on the maximum basic adhesion coefficient difference, where the correction parameter is positively correlated with the maximum basic adhesion coefficient difference.

[0141] According to one aspect of an embodiment of the present application, the correction module 1150 is further used to obtain target adhesion coefficient differences between each wheel, the target adhesion coefficient differences including the maximum target adhesion coefficient difference between the maximum target adhesion coefficient and the minimum target adhesion coefficient between each wheel; if the maximum target adhesion coefficient difference is greater than a preset difference threshold, and the remaining target adhesion coefficient differences are all less than the preset difference threshold, then the wheel to be corrected is determined based on the maximum target adhesion coefficient difference; the average target adhesion coefficient corresponding to the target wheel of the vehicle is determined, the target wheel is the other wheels in the vehicle except the wheel to be corrected, and the target adhesion coefficient of the wheel to be corrected is corrected based on the average target adhesion coefficient.

[0142] According to one aspect of an embodiment of the present application, the correction module 1150 is also used to determine wheel instability state parameters based on real-time working condition data, wherein the wheel instability parameters include the number of wheel slips, wheel speed overshoot and wheel slip duration; and determine the correction parameter corresponding to the second longitudinal force based on any one or more of the number of wheel slips, wheel speed overshoot and wheel slip duration; wherein the correction parameter is positively correlated with the number of wheel slips, wheel speed overshoot and wheel slip duration.

[0143] According to one aspect of an embodiment of the present application, the above-mentioned second determination module 1130 is also used to, if the wheel slip rate is greater than a preset slip rate threshold, re-determine the basic adhesion coefficient of the wheel; obtain the number of wheel slips of the vehicle within a preset time length; if the number of wheel slips is greater than a preset slip number threshold, and the wheel slip rate is greater than the preset slip rate threshold, update the basic adhesion coefficient of each wheel.

[0144] It should be noted that the adhesion coefficient determination device provided in the above-mentioned embodiment and the determination method provided in the above-mentioned embodiment are based on the same concept. The specific manner in which the various modules and units perform their operations has been described in detail in the method embodiments and will not be repeated here. In actual applications, the adhesion coefficient determination device provided in the above-mentioned embodiment can, as needed, allocate the aforementioned functions to different functional modules, i.e., divide the internal structure of the device into different functional modules to perform all or part of the functions described above. This is not a limitation herein.

[0145] An embodiment of the present application also provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, which, when executed by one or more processors, enables the electronic device to implement the determination methods provided in the above-mentioned embodiments.

[0146] Figure 12 The following is a schematic diagram showing the structure of a computer system suitable for implementing an electronic device according to an embodiment of the present application. Figure 12 The computer system 1200 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0147] like Figure 12 As shown, computer system 1200 includes a central processing unit (CPU) 1201, which can perform various appropriate actions and processes, such as executing the methods described in the above embodiments, based on programs stored in read-only memory (ROM) 1202 or programs loaded from storage 1208 into random access memory (RAM) 1203. RAM 1203 also stores various programs and data required for system operation. CPU 1201, ROM 1202, and RAM 1203 are interconnected via a bus 1204. An input / output (I / O) interface 1205 is also connected to bus 1204.

[0148] The following components are connected to the I / O interface 1205: an input section 1206 including a keyboard, mouse, and the like; an output section 1207 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and speakers; a storage section 1208 including a hard disk; and a communication section 1209 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 1209 performs communication processing via a network such as the Internet. A drive 1210 is also connected to the I / O interface 1205 as needed. Removable media 1211, such as magnetic disks, optical disks, magneto-optical disks, and semiconductor memories, are installed in the drive 1210 as needed, allowing computer programs read from these media to be installed in the storage section 1208 as needed.

[0149] In particular, according to embodiments of the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for executing the methods illustrated in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via the communication section 1209 and / or installed from removable media 1211. When executed by the central processing unit (CPU) 1201, the computer program performs the various functions defined in the system of the present application.

[0150] It should be noted that the computer-readable medium described in the embodiments of this application may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may, for example, be an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying a computer-readable computer program. This propagated data signal may take a variety of forms, including, but not limited to, an electromagnetic signal, an optical signal, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. A computer program embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, or any suitable combination thereof.

[0151] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. Among them, each box in the flowchart or block diagram can represent a module, program segment, or part of the code, and the above-mentioned module, program segment, or part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0152] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. In some cases, the names of these units do not constitute limitations on the units themselves.

[0153] Another aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the aforementioned determination method. The computer-readable storage medium may be included in the electronic device described in the above embodiments, or may exist independently and not be incorporated into the electronic device.

[0154] Another aspect of the present application further provides a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the determination method provided in each of the above embodiments.

[0155] The above content is only a preferred exemplary embodiment of the present application and is not intended to limit the implementation scheme of the present application. Ordinary technicians in this field can easily make corresponding changes or modifications based on the main ideas and spirit of the present application. Therefore, the scope of protection of the present application shall be based on the scope of protection required by the claims.

Claims

1. A method for determining an adhesion coefficient, characterized in that: The determination method includes: Obtain the vehicle's wheel end torque, wheel angular acceleration, wheel slip rate and wheel vertical load; determining a first longitudinal force of each wheel based on the wheel end torque and the wheel angular acceleration; determining a basic adhesion coefficient of each wheel based on the first longitudinal force and the wheel vertical load; determining a second longitudinal force of each wheel based on the wheel slip rate and a tire model corresponding to the wheel; If the basic adhesion coefficient is less than a preset adhesion coefficient threshold, the basic adhesion coefficient is corrected using the second longitudinal force to obtain a target adhesion coefficient for each wheel, including: Obtaining the type of road surface on which the vehicle is located, and determining whether the road surface type on which the vehicle is located is a uniform road surface based on the error between the basic adhesion coefficients of each wheel of the vehicle; if the error is within the allowable error range, determining that the road surface type on which the vehicle is located is a uniform road surface; If the road surface type is characterized as a uniform road surface, obtaining real-time operating condition data of the vehicle; Determining a correction parameter corresponding to the second longitudinal force based on the real-time operating condition data, and correcting the basic adhesion coefficient based on the correction parameter and the second longitudinal force to obtain a target adhesion coefficient for each wheel, including: determining a weighted parameter corresponding to the first longitudinal force according to the correction parameter, wherein the sum of the weighted parameter and the correction parameter is 1; Correcting the second longitudinal force according to the correction parameter to obtain a corrected second longitudinal force; A target adhesion coefficient of each wheel is obtained according to the weighted parameter, the corrected second longitudinal force and the basic adhesion coefficient.

2. The determination method according to claim 1, wherein: The determining, based on the real-time operating condition data, a correction parameter corresponding to the second longitudinal force includes: Determining a throttle opening value of the vehicle based on the real-time operating condition data; If the throttle opening value is greater than a preset throttle opening value, a correction parameter corresponding to the second longitudinal force is determined based on the throttle opening value, wherein the correction parameter is positively correlated with the throttle opening value.

3. The determination method according to claim 2, wherein: The determining, based on the real-time operating condition data, a correction parameter corresponding to the second longitudinal force includes: Determining a single-wheel torque change rate of the vehicle based on the real-time operating condition data; If the single-wheel torque change rate is greater than a preset torque change rate threshold, a correction parameter corresponding to the second longitudinal force is determined based on the single-wheel torque change rate, and the positive correlation between the correction parameter and the single-wheel torque change rate is greater than the positive correlation between the correction parameter and the throttle opening value.

4. The determination method according to claim 1, wherein: The determining, based on the real-time operating condition data, a correction parameter corresponding to the second longitudinal force includes: determining a basic adhesion coefficient difference between each wheel based on the real-time operating condition data, wherein the basic adhesion coefficient difference includes a maximum basic adhesion coefficient difference between a maximum basic adhesion coefficient and a minimum basic adhesion coefficient between each wheel; A correction parameter corresponding to the second longitudinal force is determined based on the maximum basic adhesion coefficient difference, and the correction parameter is positively correlated with the maximum basic adhesion coefficient difference.

5. The determination method according to any one of claims 1 to 4, characterized in that: The determination method further includes: Obtaining target adhesion coefficient differences between the wheels, the target adhesion coefficient differences comprising a maximum target adhesion coefficient difference between a maximum target adhesion coefficient and a minimum target adhesion coefficient between the wheels; If the maximum target adhesion coefficient difference is greater than a preset difference threshold, and the remaining target adhesion coefficient differences are all less than the preset difference threshold, determining the wheel to be corrected based on the maximum target adhesion coefficient difference; An average target adhesion coefficient corresponding to target wheels of the vehicle is determined, where the target wheels are wheels other than the wheel to be corrected in the vehicle, and the target adhesion coefficient of the wheel to be corrected is corrected based on the average target adhesion coefficient.

6. The determination method according to claim 1, wherein: The determining, based on the real-time operating condition data, a correction parameter corresponding to the second longitudinal force includes: Determining wheel instability parameters based on the real-time operating condition data, wherein the wheel instability parameters include the number of wheel slips, wheel speed overshoot, and wheel slip duration; determining a correction parameter corresponding to the second longitudinal force based on any one or more of the number of wheel slips, the wheel speed overshoot, and the wheel slip time; The correction parameter is positively correlated with the number of wheel slips, the wheel speed overshoot, and the wheel slip duration.

7. The determination method according to claim 1, wherein: The determination method further includes: If the wheel slip rate is greater than a preset slip rate threshold, re-determining the basic adhesion coefficient of the wheel; Get the number of wheel slips of the vehicle within a preset time period; If the number of wheel slips is greater than a preset slip number threshold, and the wheel slip rate is greater than a preset slip rate threshold, the basic adhesion coefficient of each wheel is updated.

8. An adhesion coefficient determination device, characterized in that: The determining device comprises: An acquisition module, used to acquire the vehicle's wheel end torque, wheel angular acceleration, wheel slip rate and wheel vertical load; a first determining module, configured to determine a first longitudinal force of each wheel based on the wheel end torque and the wheel angular acceleration; a second determining module, configured to determine a basic adhesion coefficient of each wheel based on the first longitudinal force and the wheel vertical load; a third determining module, configured to determine a second longitudinal force of each wheel based on the wheel slip rate and a tire model corresponding to the wheel; a correction module, configured to, if the basic adhesion coefficient is less than a preset adhesion coefficient threshold, use the second longitudinal force to correct the basic adhesion coefficient to obtain a target adhesion coefficient for each wheel, including: obtaining a road surface type on which the vehicle is located, and determining whether the road surface type on which the vehicle is located is a uniform road surface based on an error between the basic adhesion coefficients of each wheel of the vehicle; if the error is within an allowable error range, determining that the road surface type on which the vehicle is located is a uniform road surface; if the road surface type is characterized as a uniform road surface, obtaining real-time operating condition data of the vehicle; determining a correction parameter corresponding to the second longitudinal force based on the real-time operating condition data, and correcting the basic adhesion coefficient based on the correction parameter and the second longitudinal force to obtain a target adhesion coefficient for each wheel, including: determining a weighting parameter corresponding to the first longitudinal force based on the correction parameter, wherein the sum of the weighting parameter and the correction parameter is 1; correcting the second longitudinal force based on the correction parameter to obtain a corrected second longitudinal force; and obtaining the target adhesion coefficient for each wheel based on the weighting parameter, the corrected second longitudinal force, and the basic adhesion coefficient.

9. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs, which, when executed by the one or more processors, enables the electronic device to implement the determination method according to any one of claims 1 to 7.

Images