Method and device for estimating road adhesion coefficient, vehicle and storage medium

Abstract

The invention provides a method and device for estimating a road adhesion coefficient, a vehicle and a storage medium. When the vehicle is in a driving state, the method fuses the dynamic pavement adhesion coefficient and the kinematic pavement adhesion coefficient, so that the characteristics of the driving pavement can be reflected from various different angles, and the error caused by estimating the pavement adhesion coefficient by a single factor is reduced. And further, fusing the first road adhesion coefficient, a fourth road adhesion coefficient estimated by the acceleration and a utilization adhesion coefficient of the wheel, and determining a target road adhesion coefficient of the driving road. Therefore, the method can comprehensively consider the road adhesion coefficients of different sources, and effectively associate and fuse the various road adhesion coefficients to obtain the road adhesion coefficient which can better reflect the overall adhesion characteristics of the driving road, so that the estimation precision of the road adhesion coefficient under different driving conditions is improved, and the estimation accuracy of the road adhesion coefficient under different driving conditions is improved. Accurate control over the movement process of the vehicle is achieved.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and more specifically, to a method, a device, a vehicle and a storage medium for estimating a road adhesion coefficient in the field of vehicle technology. Background Art

[0002] With the continuous advancement of vehicle technology and the improvement of people's living standards, the audience of vehicles is becoming more and more extensive. However, there are also more and more vehicle-related problems, including the precise control of the vehicle's movement process.

[0003] The road adhesion coefficient is a key parameter for achieving precise control of the motion process. However, in the related art, the road adhesion coefficient is mainly estimated continuously through the tire dynamics model. The road adhesion coefficient determined by the related art is highly dependent on the tire dynamics model. Since the tire characteristics of the tire dynamics model will change during use due to the influence of temperature and tire pressure, this will affect the estimation accuracy of the road adhesion coefficient.

[0004] Therefore, there is an urgent need for a method for estimating the road adhesion coefficient in order to improve the estimation accuracy of the road adhesion coefficient and achieve precise control of the vehicle's motion process. Summary of the invention

[0005] The present application provides a method, device, vehicle and storage medium for estimating a road adhesion coefficient. The method can improve the estimation accuracy of the road adhesion coefficient and achieve precise control of the vehicle's motion process.

[0006] In a first aspect, a method for estimating a road adhesion coefficient is provided, the method comprising: when a vehicle is in a driving state, determining a first road adhesion coefficient of a driving road of the vehicle, the first road adhesion coefficient being obtained by fusing a second road adhesion coefficient and a third road adhesion coefficient, the second road adhesion coefficient being determined based on tire force in the vehicle, and the third road adhesion coefficient being determined based on a slip rate of a wheel in the vehicle; fusing the first road adhesion coefficient, a fourth road adhesion coefficient and a utilization adhesion coefficient of the wheel to determine a target road adhesion coefficient of the driving road, the fourth road adhesion coefficient being determined based on the acceleration of the vehicle, and the utilization adhesion coefficient being used to indicate an effective utilization rate of actual friction between the tire of the wheel and the driving road.

[0007] In the above technical solution, when the vehicle is in a driving state, the second road adhesion coefficient and the third road adhesion coefficient are fused to obtain the first road adhesion coefficient of the driving road surface. In other words, the dynamic road adhesion coefficient and the kinematic road adhesion coefficient are fused, which can reflect the characteristics of the driving road surface from multiple different angles and reduce the error when estimating the road adhesion coefficient by a single factor. Further, the first road adhesion coefficient, the fourth road adhesion coefficient estimated by acceleration and the utilization adhesion coefficient of the wheel are fused to determine the target road adhesion coefficient of the driving road surface. In this way, the method can comprehensively consider the road adhesion coefficients from different sources, effectively associate and fuse multiple road adhesion coefficients, and obtain a road adhesion coefficient that can better reflect the overall adhesion characteristics of the driving road surface, thereby improving the estimation accuracy of the road adhesion coefficient under different driving conditions and realizing precise control of the vehicle's motion process.

[0008] In combination with the first aspect, in certain possible implementations, the method for determining the third road adhesion coefficient includes: taking any wheel in the vehicle as a target wheel, and determining the lateral slip rate and longitudinal slip rate of the target wheel; determining the road composite slip rate of the target wheel based on the lateral slip rate and the target longitudinal slip rate, the target longitudinal slip rate being obtained based on the product of the longitudinal slip rate and a first coefficient, the first coefficient being used to indicate the degree of influence of the longitudinal slip rate on the tire friction performance of the target wheel; determining the road adhesion coefficient corresponding to the target wheel based on the road composite slip rate, the lateral slip rate, the longitudinal slip rate and the first coefficient; and determining the third road adhesion coefficient based on the road adhesion coefficients corresponding to each wheel in the vehicle.

[0009] In the above technical solution, any wheel in the vehicle is used as the target wheel, and the road surface composite slip rate of the target wheel is determined by the lateral slip rate of the target wheel and the longitudinal slip rate after considering the friction ellipse. This can determine the influence of the longitudinal slip rate on the tire friction performance of the target wheel, can more accurately reflect the distribution of the friction between the tire and the driving road surface during the actual driving process of the vehicle, and more accurately determine the road surface composite slip rate. Further, based on the road surface composite slip rate, the lateral slip rate, the longitudinal slip rate and the first coefficient, the road surface adhesion coefficient corresponding to the target wheel is determined. The road surface composite slip rate is used to describe the comprehensive slip of the target wheel in the longitudinal and lateral directions, which helps to more comprehensively evaluate the actual slip state of the target wheel on the driving road surface. The lateral slip rate and the longitudinal slip rate reflect the slip of the wheel from different directions respectively. By combining these factors, the friction characteristics between the tire and the driving road surface can be more accurately analyzed. In addition, there is friction between the driving road surface and each wheel. Based on the road surface adhesion coefficient corresponding to each wheel in the vehicle, the third road surface adhesion coefficient is determined, and the kinematic road surface adhesion coefficient of the driving road surface can be more accurately determined.

[0010] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, the road adhesion coefficient corresponding to the target wheel is determined based on the road surface composite slip rate, the lateral slip rate, the longitudinal slip rate and the first coefficient, including: determining the tangential force between the target wheel and the driving road surface based on the road surface composite slip rate; determining the road adhesion coefficient corresponding to the target wheel based on the tangential force, the road surface composite slip rate, the lateral slip rate, the longitudinal slip rate and the first coefficient.

[0011] In the above technical solution, the tangential force is determined based on the road surface composite slip rate of the target wheel, which can more accurately reflect the friction characteristics of the tire under the road surface composite slip rate when the tire is driving on the driving road surface. By comprehensively considering the lateral slip rate and the longitudinal slip rate, the actual friction performance of the tire under multi-directional force conditions can be more accurately reflected. In addition, the introduction of the first coefficient can further refine the description of the friction performance of the tire. Therefore, in this method, the road adhesion coefficient corresponding to the target wheel when the vehicle is driving can be accurately determined based on the tangential force, the road surface composite slip rate, the lateral slip rate, the longitudinal slip rate and the first coefficient.

[0012] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, determining a first road adhesion coefficient of the vehicle's driving road surface includes: determining the difference between the second road adhesion coefficient of the current iteration number and the third road adhesion coefficient of the current iteration number as the fifth road adhesion coefficient of the current iteration number; determining a first product between the fifth road adhesion coefficient and the Kalman gain of the current iteration number, and determining the first road adhesion coefficient based on the first product and the a priori estimated road adhesion coefficient of the current iteration number.

[0013] In the above technical solution, the dynamic road adhesion coefficient (second road adhesion coefficient) involves the tire force of the wheel, and the kinematic road adhesion coefficient (third road adhesion coefficient) is related to the motion state of the vehicle. By fusing the second road adhesion coefficient and the third road adhesion coefficient, the characteristics of the driving road surface can be reflected from multiple different angles, reducing the error when a single factor determines the road adhesion coefficient. Furthermore, the Kalman gain of the current iteration number can play a role of weight in the fusion process. Since the Kalman gain is related to the lateral road adhesion coefficient and the longitudinal road adhesion coefficient corresponding to each wheel, the weights of the second road adhesion coefficient and the third road adhesion coefficient in the fusion can be reasonably allocated based on the actual adhesion conditions of different wheels, so that the first road adhesion coefficient is closer to the true value. In addition, in the fusion process, the a priori estimated road adhesion coefficient is also introduced, which takes into account the previous judgment information on the road condition, which can correct the current estimated value of the road adhesion coefficient to a certain extent, especially when the change of the driving state of the vehicle is not very drastic, the a priori estimated road adhesion coefficient can provide a stable reference, further improving the estimation accuracy of the first road adhesion coefficient.

[0014] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, determining the first product between the fifth road adhesion coefficient and the Kalman gain of the current iteration number, and determining the first road adhesion coefficient based on the first product and the a priori estimated road adhesion coefficient, includes: determining the sum of the composite road slip rates of multiple wheels in the vehicle as the total slip rate; determining an excitation mode based on the total slip rate, the excitation mode being used to determine a way to update the Kalman gain in the process of iteratively determining the first road adhesion coefficient through the extended Kalman filter algorithm; updating the Kalman gain of the current iteration number based on the excitation mode to determine the updated Kalman gain; determining the first product between the fifth road adhesion coefficient and the updated Kalman gain, and determining the first road adhesion coefficient based on the first product and the a priori estimated road adhesion coefficient.

[0015] In the above technical solution, an excitation mode is determined based on the sum of the composite slip rates of the road surfaces of multiple wheels (total slip rate). The excitation mode is used to determine the way to update the Kalman gain in the process of iteratively determining the first road surface adhesion coefficient through the extended Kalman filter algorithm. Further, based on the excitation mode, the Kalman gain of the current iteration number is updated. The method determines the first road surface adhesion coefficient by using the target iteration number through the EKF algorithm, and updates the Kalman gain, which can speed up the fusion of the dynamic road surface adhesion coefficient and the kinematic road surface adhesion coefficient, so that the method determines the first road surface adhesion coefficient with a reduced number of iterations. Therefore, the method can fuse the first road surface adhesion coefficient at a faster speed.

[0016] In combination with the first aspect and the above-mentioned implementation manner, in some possible implementation manners, the first road adhesion coefficient, the fourth road adhesion coefficient and the utilization adhesion coefficient of the wheel are integrated to determine the target road adhesion coefficient of the driving road surface, including any one of the following: determining the maximum adhesion coefficient among the first road adhesion coefficient, the fourth road adhesion coefficient and the utilization adhesion coefficient as the target road adhesion coefficient; determining the average adhesion coefficient among the first road adhesion coefficient, the fourth road adhesion coefficient and the utilization adhesion coefficient as the target road adhesion coefficient; weighting the first road adhesion coefficient by a first weight to obtain a first coefficient; weighting the fourth road adhesion coefficient by a second weight to obtain a second coefficient; weighting the utilization adhesion coefficient by a third weight to obtain a third coefficient; and determining the sum of the first coefficient, the second coefficient and the third coefficient as the target road adhesion coefficient; wherein the first weight is used to indicate the contribution of the first road adhesion coefficient when determining the target road adhesion coefficient, the second weight is used to indicate the contribution of the fourth road adhesion coefficient when determining the target road adhesion coefficient, and the third weight is used to indicate the contribution of the utilization adhesion coefficient when determining the target road adhesion coefficient.

[0017] In the above technical solution, determining the target road adhesion coefficient by multiple methods can avoid the situation where the target road adhesion coefficient cannot be determined, and can also meet different requirements when determining the target road adhesion coefficient. In addition, the target road adhesion coefficient determined by the first method is the maximum road adhesion coefficient, which can ensure that the vehicle can travel in the safest way under various driving conditions. The average adhesion coefficient determined by the second method can balance the advantages and disadvantages of road adhesion coefficients from different sources and obtain a road adhesion coefficient that can better reflect the overall adhesion characteristics of the driving road. Compared with the second method, the weighted fusion adhesion coefficient of the third method is more accurate. This is because the third method can take into account the different contributions of road adhesion coefficients from different sources in determining the target road adhesion coefficient under the current driving conditions.

[0018] In combination with the first aspect and the above-mentioned implementation methods, in some possible implementation methods, the method for determining the first weight, the second weight and the third weight includes: determining the degree of wear of the tire of the wheel in the vehicle; when the degree of wear is less than or equal to a preset degree, determining the first weight, the second weight and the third weight based on a first ratio between a first preset value and the total number corresponding to the weight, and the first weight, the second weight and the third weight are the same; when the degree of wear is greater than the preset degree, determining the second weight based on the first ratio and the deviation amplitude of the degree of wear relative to the preset degree; determining the first weight and the third weight based on the first preset value and the second weight.

[0019] In the above technical solution, the degree of tire wear will affect the accuracy of the road adhesion coefficients from different sources. Specifically, the degree of tire wear has the smallest impact on the accuracy of the fourth road adhesion coefficient, followed by the utilization adhesion coefficient of the wheel, and finally the first road adhesion coefficient. This is because the degree of tire wear does not affect the acceleration in the process of determining the fourth road adhesion coefficient, but affects the tire force in the process of determining the utilization adhesion coefficient, and even more affects the tire force and slip rate in the process of determining the first road adhesion coefficient. Therefore, based on the above theory, this method can accurately evaluate the contribution of the road adhesion coefficients from different sources when determining the target road adhesion coefficient, that is, the first weight, the second weight, and the third weight, through the degree of tire wear.

[0020] In a second aspect, a device for estimating a road adhesion coefficient is provided, the device comprising: a determination module for determining a first road adhesion coefficient of a road surface on which the vehicle is traveling when the vehicle is in a traveling state, the first road adhesion coefficient being obtained by fusing a second road adhesion coefficient and a third road adhesion coefficient, the second road adhesion coefficient being determined based on tire force in the vehicle, and the third road adhesion coefficient being determined based on a slip rate of a wheel in the vehicle; a fusion module for fusing the first road adhesion coefficient, a fourth road adhesion coefficient and a utilization adhesion coefficient of the wheel to determine a target road adhesion coefficient of the road surface, the fourth road adhesion coefficient being determined based on the acceleration of the vehicle, and the utilization adhesion coefficient being used to indicate an effective utilization rate of actual friction between the tire of the wheel and the road surface.

[0021] In combination with the second aspect, in some possible implementations, the determination module is specifically used to: take any wheel in the vehicle as a target wheel, and determine the lateral slip rate and longitudinal slip rate of the target wheel; determine the road surface composite slip rate of the target wheel based on the lateral slip rate and the target longitudinal slip rate, the target longitudinal slip rate is obtained based on the product between the longitudinal slip rate and a first coefficient, and the first coefficient is used to indicate the degree of influence of the longitudinal slip rate on the tire friction performance of the target wheel; determine the road surface adhesion coefficient corresponding to the target wheel based on the road surface composite slip rate, the lateral slip rate, the longitudinal slip rate and the first coefficient; determine the third road surface adhesion coefficient based on the road surface adhesion coefficients corresponding to each wheel in the vehicle.

[0022] In combination with the second aspect and the above-mentioned implementation methods, in some possible implementation methods, the determination module is specifically used to: determine the tangential force between the target wheel and the driving road surface based on the composite slip rate of the road surface; determine the road adhesion coefficient corresponding to the target wheel based on the tangential force, the composite slip rate of the road surface, the lateral slip rate, the longitudinal slip rate and the first coefficient.

[0023] In combination with the second aspect and the above-mentioned implementation methods, in some possible implementation methods, the determination module is specifically used to: determine the difference between the second road adhesion coefficient of the current iteration number and the third road adhesion coefficient of the current iteration number as the fifth road adhesion coefficient of the current iteration number; determine the first product between the fifth road adhesion coefficient and the Kalman gain of the current iteration number, and determine the first road adhesion coefficient based on the first product and the prior estimated road adhesion coefficient.

[0024] In combination with the second aspect and the above-mentioned implementation methods, in some possible implementation methods, the determination module is specifically used to: determine the sum of the composite road surface slip rates of multiple wheels in the vehicle as the total slip rate; based on the total slip rate, determine an excitation mode, and the excitation mode is used to determine a method for updating the Kalman gain in the process of iteratively determining the first road surface adhesion coefficient through the extended Kalman filter algorithm; based on the excitation mode, update the Kalman gain of the current iteration number to determine the updated Kalman gain; determine the first product between the fifth road surface adhesion coefficient and the updated Kalman gain, and determine the first road surface adhesion coefficient based on the first product and the a priori estimated road surface adhesion coefficient of the current iteration number.

[0025] In combination with the second aspect and the above-mentioned implementation methods, in some possible implementation methods, the fusion module is specifically used for any one of the following: determining the maximum adhesion coefficient among the first road adhesion coefficient, the fourth road adhesion coefficient and the utilization adhesion coefficient as the target road adhesion coefficient; determining the average adhesion coefficient among the first road adhesion coefficient, the fourth road adhesion coefficient and the utilization adhesion coefficient as the target road adhesion coefficient; weighting the first road adhesion coefficient by a first weight to obtain a first coefficient; weighting the fourth road adhesion coefficient by a second weight to obtain a second coefficient; weighting the utilization adhesion coefficient by a third weight to obtain a third coefficient; determining the sum of the first coefficient, the second coefficient and the third coefficient as the target road adhesion coefficient; wherein the first weight is used to indicate the contribution of the first road adhesion coefficient when determining the target road adhesion coefficient, the second weight is used to indicate the contribution of the fourth road adhesion coefficient when determining the target road adhesion coefficient, and the third weight is used to indicate the contribution of the utilization adhesion coefficient when determining the target road adhesion coefficient.

[0026] In combination with the second aspect and the above-mentioned implementation methods, in some possible implementation methods, the determination module is specifically used to: determine the degree of wear of the tires of the wheels in the vehicle; when the degree of wear is less than or equal to a preset degree, determine the first weight, the second weight and the third weight based on a first ratio between a first preset value and the total number corresponding to the weights, and the first weight, the second weight and the third weight are the same; when the degree of wear is greater than the preset degree, determine the second weight based on the first ratio and the deviation amplitude of the degree of wear relative to the preset degree; determine the first weight and the third weight based on the first preset value and the second weight.

[0027] In a third aspect, a vehicle is provided, comprising a memory and a processor. The memory is used to store executable program code, and the processor is used to call and run the executable program code from the memory, so that the vehicle executes the method in the first aspect or any possible implementation of the first aspect.

[0028] In a fourth aspect, a computer-readable storage medium is provided, which stores an executable program code. When the executable program code runs on a computer, the computer executes the method in the above-mentioned first aspect or any possible implementation of the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 is a schematic diagram of a scenario of using a vehicle provided in an embodiment of the present application; Figure 2 is a schematic flow chart of a method for estimating a road adhesion coefficient provided in an embodiment of the present application; Figure 3 is a schematic block diagram of estimating a road adhesion coefficient provided in an embodiment of the present application; Figure 4 is a schematic flow chart of estimating a road adhesion coefficient provided in an embodiment of the present application; Figure 5 It is a structural schematic diagram of a device for estimating a road adhesion coefficient provided in an embodiment of the present application; Figure 6 It is a structural schematic diagram of a vehicle provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] The technical solution in the present application will be described clearly and in detail below in conjunction with the accompanying drawings. In the description of the embodiments of the present application, unless otherwise specified, " / " means or, for example, A / B can mean A or B: "and / or" in the text is only a description of the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, "multiple" means two or more than two.

[0031] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features.

[0032] Figure 1 It is a schematic diagram of a scenario of using a vehicle provided in an embodiment of the present application.

[0033] It should be understood that the road adhesion coefficient is a key parameter for achieving precise control of the vehicle's motion process. For example, through the road adhesion coefficient, the vehicle control system can more accurately determine the safe distance of the vehicle during driving, thereby issuing timely warnings in potential dangerous situations and improving driving safety. For example, Figure 1 As shown, if the safety distance is determined by an inaccurate road adhesion coefficient, this will increase the probability of a traffic accident occurring when vehicle A is traveling based on the safety distance.

[0034] In the related art, the road adhesion coefficient is mainly estimated continuously through the tire dynamics model. The road adhesion coefficient determined by the related art is highly dependent on the tire dynamics model. Since the tire characteristics of the tire dynamics model will change during use due to the influence of temperature and tire pressure, this will affect the estimation accuracy of the road adhesion coefficient.

[0035] In order to solve the above problems, this application proposes a method for estimating the road adhesion coefficient to improve the estimation accuracy of the road adhesion coefficient and realize accurate control of the vehicle's motion process. The specific implementation steps can be found in Figure 2 .

[0036] Figure 2 It is a schematic flow chart of a method for estimating a road adhesion coefficient provided in an embodiment of the present application.

[0037] It should be understood that the method for estimating the road adhesion coefficient provided in the embodiment of the present application can be applied to the following examples: Figure 1 The vehicle controller in the vehicle shown.

[0038] For example, Figure 2As shown, the method 200 includes: Step 201, when the vehicle is in driving state, the vehicle controller determines a first road adhesion coefficient of the vehicle's driving road surface, the first road adhesion coefficient is obtained by integrating a second road adhesion coefficient and a third road adhesion coefficient, the second road adhesion coefficient is determined based on the tire force in the vehicle, and the third road adhesion coefficient is determined based on the slip rate of the wheels in the vehicle.

[0039] It should be understood that in the above step 201, the "second road adhesion coefficient" can be regarded as the dynamic road adhesion coefficient of the driving road surface, and the dynamic road adhesion coefficient is the road adhesion coefficient estimated by the dynamic model of the vehicle, which involves the tire force in the vehicle. The method of dynamic model estimation can more accurately reflect the dynamic response of the vehicle under different road conditions. The "third road adhesion coefficient" can be regarded as the kinematic road adhesion coefficient of the driving road surface, and the kinematic road adhesion coefficient is the road adhesion coefficient estimated by the kinematic model of the vehicle (involving slip rate, etc.). This method infers the road adhesion coefficient based on the motion state of the vehicle.

[0040] In some embodiments, the method for determining the second road adhesion coefficient in step 201 includes: the vehicle controller takes any wheel in the vehicle as a target wheel, determines the lateral utilization adhesion coefficient of the target wheel based on the lateral tire force and vertical tire force of the target wheel, and determines the longitudinal utilization adhesion coefficient of the target wheel based on the longitudinal tire force and vertical tire force of the target wheel; the vehicle controller determines the second road adhesion coefficient based on the lateral utilization adhesion coefficient and longitudinal utilization adhesion coefficient of each wheel in the vehicle.

[0041] In some embodiments, the vehicle controller determines the lateral utilization adhesion coefficient of the target wheel based on the lateral tire force and the vertical tire force of the target wheel, and determines the longitudinal utilization adhesion coefficient of the target wheel based on the longitudinal tire force and the vertical tire force of the target wheel, including: the vehicle controller determines the lateral utilization adhesion coefficient of the target wheel and the longitudinal utilization adhesion coefficient of the target wheel based on the following formula (1) and formula (2); (1) (2) in, For the target wheel The lateral adhesion coefficient is For the target wheel The longitudinal utilization adhesion coefficient, For the target wheel The lateral tire force, For the target wheel The vertical tire force, For the target wheel Longitudinal tire force.

[0042] In some embodiments, the vehicle controller determines the second road adhesion coefficient based on the lateral adhesion coefficient and the longitudinal adhesion coefficient of each wheel in the vehicle, including: the vehicle determines the second road adhesion coefficient based on the following formula (3); (3) in, is the second road adhesion coefficient, is the lateral utilized adhesion coefficient of the first wheel in the vehicle, is the longitudinal adhesion coefficient of the first wheel, is the lateral utilized adhesion coefficient of the second wheel in the vehicle, is the longitudinal adhesion coefficient of the second wheel, For the vehicle The lateral adhesion coefficient of the wheel, that is, the wheel The lateral adhesion coefficient is For this The longitudinal adhesion coefficient of the wheel, that is, the wheel It should be understood that the second road adhesion coefficient is determined by the lateral adhesion coefficient and the longitudinal adhesion coefficient of each wheel in the vehicle.

[0043] In some embodiments, when the total number of wheels in the vehicle is 4, The value of is 4, the second road adhesion coefficient .

[0044] In one possible implementation, the method for determining the third road adhesion coefficient in step 201 includes: the vehicle controller takes any wheel in the vehicle as a target wheel, and determines the lateral slip rate and longitudinal slip rate of the target wheel; the vehicle controller determines the road composite slip rate of the target wheel based on the lateral slip rate and the target longitudinal slip rate, and the target longitudinal slip rate is obtained based on the product between the longitudinal slip rate and a first coefficient, and the first coefficient is used to indicate the degree of influence of the longitudinal slip rate on the tire friction performance of the target wheel; the vehicle controller determines the road adhesion coefficient corresponding to the target wheel based on the road composite slip rate, the lateral slip rate, the longitudinal slip rate and the first coefficient; the vehicle controller determines the third road adhesion coefficient based on the road adhesion coefficients corresponding to each wheel in the vehicle.

[0045] It should be understood that when a vehicle is driving, the tire will be affected by the combined effects of longitudinal friction (such as when accelerating or braking) and lateral friction (such as when turning). There is a limit value for the friction between the tire and the road surface. The resultant force between the longitudinal friction and the lateral friction cannot exceed the friction limit value represented by the ellipse (friction ellipse). The "first coefficient" in the above scheme is a proportional coefficient added before the lateral slip rate after considering the friction ellipse. The friction ellipse is used to indicate that there is a mutual constraint relationship between the longitudinal friction and the lateral friction, and the longitudinal slip rate and the lateral slip rate cannot be simply combined directly to obtain a composite slip rate. By considering the influence of the friction ellipse, this method can more accurately reflect the distribution of friction between the tire and the road surface during actual driving of the vehicle, thereby more accurately determining the composite slip rate of the road surface.

[0046] In the above technical solution, any wheel in the vehicle is used as the target wheel, and the vehicle controller determines the road surface composite slip rate of the target wheel through the lateral slip rate of the target wheel and the longitudinal slip rate after considering the friction ellipse. This can determine the influence of the longitudinal slip rate on the tire friction performance of the target wheel, can more accurately reflect the distribution of friction between the tire and the driving road surface during the actual driving process of the vehicle, and more accurately determine the road surface composite slip rate. Further, the vehicle controller determines the road surface adhesion coefficient corresponding to the target wheel based on the road surface composite slip rate, lateral slip rate, longitudinal slip rate and the first coefficient. The road surface composite slip rate is used to describe the comprehensive slip of the target wheel in the longitudinal and lateral directions, which helps to more comprehensively evaluate the actual slip state of the target wheel on the driving road surface. The lateral slip rate and the longitudinal slip rate reflect the slip of the wheel from different directions respectively. Combining these factors can more accurately analyze the friction characteristics between the tire and the driving road surface. In addition, there is friction between the driving road surface and each wheel. The vehicle controller determines the third road adhesion coefficient based on the road adhesion coefficient corresponding to each wheel in the vehicle, which can more accurately determine the kinematic road adhesion coefficient of the driving road surface.

[0047] In some embodiments, the vehicle controller determines the lateral slip rate and the longitudinal slip rate of the target wheel, including: the vehicle controller determines the lateral slip rate and the longitudinal slip rate of the target wheel based on the following formula (4) and formula (5); (4) (5) in, Target wheel The lateral slip rate, Target wheel The longitudinal slip rate, Target wheel The rotation speed, Target wheel The rolling radius of the tire, Target wheel The lateral speed of the wheel center, Target wheel The longitudinal speed of the wheel center.

[0048] In some embodiments, the vehicle controller determines the road surface composite slip rate of the target wheel based on the lateral slip rate and the target longitudinal slip rate, including: the vehicle controller determines the road surface composite slip rate of the target wheel based on the following formula (6); (6) in, For the target wheel The composite slip rate of the road surface, is the first coefficient.

[0049] In some embodiments, the vehicle controller determines the third road adhesion coefficient based on the road adhesion coefficient corresponding to each wheel in the vehicle, including: the vehicle controller determines the third road adhesion coefficient based on the following formula (7); (7) in, is the third road adhesion coefficient, is the lateral road adhesion coefficient corresponding to the first wheel of the vehicle, is the longitudinal road adhesion coefficient corresponding to the first wheel, is the lateral road adhesion coefficient corresponding to the second wheel of the vehicle, is the longitudinal road adhesion coefficient corresponding to the second wheel, For the vehicle The lateral road adhesion coefficient corresponding to the wheel, that is, the wheel The corresponding lateral road adhesion coefficient is, For this The longitudinal road adhesion coefficient corresponding to the wheel, that is, the wheel Corresponding longitudinal road adhesion coefficient. It should be understood that the third road adhesion coefficient is determined by the lateral road adhesion coefficient and the corresponding longitudinal road adhesion coefficient corresponding to each wheel in the vehicle.

[0050] In some embodiments, when the total number of wheels in the vehicle is 4, The value of is 4, the third road adhesion coefficient .

[0051] In one possible implementation, the vehicle controller determines the road adhesion coefficient corresponding to the target wheel based on the road surface composite slip rate, the lateral slip rate, the longitudinal slip rate and the first coefficient, including: the vehicle controller determines the tangential force between the target wheel and the driving road surface based on the road surface composite slip rate; the vehicle controller determines the road adhesion coefficient corresponding to the target wheel based on the tangential force, the road surface composite slip rate, the lateral slip rate, the longitudinal slip rate and the first coefficient.

[0052] It should be understood that the "tangential force between the target wheel and the driving road surface" in the above solution can be regarded as the tire force between the target wheel and the driving road surface in theory.

[0053] In the above technical solution, the tangential force is determined based on the road surface composite slip rate of the target wheel, which can more accurately reflect the friction characteristics of the tire under the road surface composite slip rate when the tire is driving on the driving road surface. By comprehensively considering the lateral slip rate and the longitudinal slip rate, the actual friction performance of the tire under multi-directional force conditions can be more accurately reflected. In addition, the introduction of the first coefficient can further refine the description of the friction performance of the tire. Therefore, in this method, the vehicle controller can accurately determine the road adhesion coefficient corresponding to the target wheel when the vehicle is driving based on the tangential force, the road surface composite slip rate, the lateral slip rate, the longitudinal slip rate and the first coefficient.

[0054] In some embodiments, the vehicle controller determines the tangential force between the target wheel and the driving road surface based on the composite slip rate of the road surface, including: the vehicle controller determines the tangential force based on the following formula (8); (8) in, is the tangential force determined based on the composite slip rate of the road surface. Formula (8) can be understood as the mapping relationship between the tangential force between the wheel and the ground and the slip rate established by the wheel-ground contact model (such as the Burckhardt longitudinal and lateral coupled tire model). , and are the fitting parameters in the wheel-ground contact model.

[0055] In some embodiments, the vehicle controller determines the road adhesion coefficient corresponding to the target wheel based on the tangential force, the road composite slip rate, the lateral slip rate, the longitudinal slip rate and the first coefficient, including: the vehicle controller determines the road adhesion coefficient corresponding to the target wheel based on the following formula (9); (9) in, For the target wheel The corresponding lateral road adhesion coefficient in the road adhesion coefficient is: For the target wheel The corresponding longitudinal road adhesion coefficient in the road adhesion coefficient is: is the initial estimated road adhesion coefficient.

[0056] In one possible implementation, the vehicle controller in step 201 determines a first road adhesion coefficient of the vehicle's driving road surface, including: the vehicle controller determines the difference between the second road adhesion coefficient of the current iteration number and the third road adhesion coefficient of the current iteration number as the fifth road adhesion coefficient of the current iteration number; the vehicle controller determines a first product between the fifth road adhesion coefficient and the Kalman gain of the current iteration number, and determines the first road adhesion coefficient based on the first product and the a priori estimated road adhesion coefficient.

[0057] It should be understood that the above scheme describes the use of an extended Kalman filter (EKF) algorithm, using the Kalman gain of the current iteration number corresponding to the EKF algorithm and the a priori estimated road adhesion coefficient to fuse the second road adhesion coefficient and the third road adhesion coefficient of the current iteration number to determine the first road adhesion coefficient of the current iteration number, except that the current iteration number may be the last iteration number, and the first road adhesion coefficient of the current iteration number is used as the first road adhesion coefficient in step 201.

[0058] It should also be understood that the Kalman gain of the current iteration number is related to the lateral road adhesion coefficient and the corresponding longitudinal road adhesion coefficient of each wheel in the third road adhesion coefficient. In addition, the Kalman gain of the current iteration number is specifically a Kalman gain matrix.

[0059] In the above technical solution, the dynamic road adhesion coefficient (second road adhesion coefficient) involves the tire force of the wheel, and the kinematic road adhesion coefficient (third road adhesion coefficient) is related to the motion state of the vehicle. By fusing the second road adhesion coefficient and the third road adhesion coefficient, the characteristics of the driving road surface can be reflected from multiple different angles, reducing the error when a single factor determines the road adhesion coefficient. Furthermore, the Kalman gain of the current iteration number can play a role of weight in the fusion process. Since the Kalman gain is related to the lateral road adhesion coefficient and the longitudinal road adhesion coefficient corresponding to each wheel, the vehicle controller can reasonably allocate the weights of the second road adhesion coefficient and the third road adhesion coefficient in the fusion based on the actual adhesion conditions of different wheels, so that the first road adhesion coefficient is closer to the true value. In addition, in the fusion process, the vehicle controller also introduces a priori estimated road adhesion coefficient, which takes into account the previous judgment information on the road condition, which can correct the current estimated value of the road adhesion coefficient to a certain extent, especially when the change of the vehicle's driving state is not very drastic, the a priori estimated road adhesion coefficient can provide a stable reference, further improving the estimation accuracy of the first road adhesion coefficient.

[0060] In some embodiments, the method for determining the Kalman gain of the current iteration number includes: the vehicle controller determines the covariance matrix of the road adhesion coefficient estimated a priori for the current iteration number based on the Jacobian system matrix corresponding to the extended Kalman filter, the covariance matrix of the road adhesion coefficient estimated a priori for the previous iteration number, and the covariance matrix of the process noise; the vehicle controller determines the Kalman gain of the current iteration number based on the covariance matrix of the road adhesion coefficient estimated a priori for the current iteration number, the Jacobian observation matrix of the current iteration number corresponding to the extended Kalman filter, and the covariance matrix of the measurement noise.

[0061] In some embodiments, the vehicle controller determines the covariance matrix of the road adhesion coefficient estimated a priori for the current iteration number based on the Jacobian system matrix corresponding to the extended Kalman filter, the covariance matrix of the road adhesion coefficient estimated a priori for the previous iteration number, and the covariance matrix of the process noise, including: the vehicle controller determines the covariance matrix of the road adhesion coefficient estimated a priori for the current iteration number based on the following formula (10); and the vehicle controller determines the Kalman gain for the current iteration number based on the covariance matrix of the road adhesion coefficient estimated a priori for the current iteration number, the Jacobian observation matrix of the current iteration number corresponding to the extended Kalman filter, and the covariance matrix of the measurement noise, including: the vehicle controller determines the Kalman gain for the current iteration number based on the following formula (11); (10) (11) in, The current iteration number The covariance matrix of the a priori estimated road adhesion coefficient, is the Jacobian system matrix, which refers to the number of iterations The Jacobian system matrix when estimating the first road adhesion coefficient is, The number of previous iterations The covariance matrix of the posterior estimated road adhesion coefficient, is the transpose of the Jacobi system matrix, is the covariance matrix of process noise, Current iteration number The Kalman gain, The current number of iterations corresponding to the extended Kalman filter The Jacobian measurement matrix of is the covariance matrix of the measurement noise. is given by the following formula (12). In addition, since the first road adhesion coefficient is determined by iteration, the method also gives the current iteration number by the following formula (13): Covariance matrix of the posterior estimated road adhesion coefficients.

[0062] (12) (13) It should be understood that the "covariance matrix of the road adhesion coefficient estimated a priori at the current iteration number" in the above scheme is not a covariance matrix determined when the observation data (Jacobian observation matrix of the current iteration number) is known. The "covariance matrix of the road adhesion coefficient estimated a posteriori at the current iteration number" is a covariance matrix determined when the observation data (Jacobian observation matrix of the current iteration number) is known. In the case of the Jacobian observation matrix), the covariance matrix of the road adhesion coefficient estimated a priori at the current iteration number is corrected.

[0063] In some embodiments, the vehicle controller determines a first product between the fifth road adhesion coefficient and the Kalman gain of the current iteration number, and determines the first road adhesion coefficient based on the first product and the a priori estimated road adhesion coefficient, including: the vehicle controller determines the first road adhesion coefficient based on the following formula (14); (14) It should be understood that and The size of and The same number of rows, and The number of columns is the same, The number of rows is the same as ( ) keep the same number of columns, The number of columns and ( ) keep the number of rows consistent. When the total number of wheels in the vehicle is 4, The size is 8*1, The size is 8*1, ( ) is 8*1 in size, The size is 1*8. It should also be understood that It can be regarded as the actual measured road adhesion coefficient (actual value) of the current iteration number, It can be regarded as the road adhesion coefficient (measured value) predicted by the measurement of the current iteration number.

[0064] in, Current iteration number The first road adhesion coefficient is actually an intermediate variable for determining the first road adhesion coefficient of the current iteration number. The corresponding first road adhesion coefficient of the current iteration number is , Current iteration number The a priori estimated road adhesion coefficient is actually to determine the current number of iterations The intermediate variable of the a priori estimated road adhesion coefficient, corresponding to the actual current iteration number The a priori estimated road adhesion coefficient is , Current iteration number The second road adhesion coefficient, Current iteration number The third road adhesion coefficient.

[0065] In one possible implementation, the vehicle controller determines the first product between the fifth road adhesion coefficient and the Kalman gain of the current iteration number, and determines the first road adhesion coefficient based on the first product and the a priori estimated road adhesion coefficient, including: the vehicle controller determines the sum of the composite road slip rates of multiple wheels in the vehicle as the total slip rate; the vehicle controller determines an excitation mode based on the total slip rate, and the excitation mode is used to determine the way to update the Kalman gain in the process of iteratively determining the first road adhesion coefficient through the extended Kalman filter algorithm; the vehicle controller updates the Kalman gain of the current iteration number based on the excitation mode to determine the updated Kalman gain; the vehicle controller determines the first product between the fifth road adhesion coefficient and the updated Kalman gain, and determines the first road adhesion coefficient based on the first product and the a priori estimated road adhesion coefficient.

[0066] It should be understood that when determining the first road adhesion coefficient through the EKF algorithm, the target number of iterations will be set in advance. In the process of fusing the first road adhesion coefficient through the EKF algorithm, the method also judges the sum of the composite slip rates of the roads of multiple wheels (total slip rate) and determines the total slip rate to determine the way to update the Kalman gain in the process of determining the first road adhesion coefficient. In this way, in the iterative process of determining the first road adhesion coefficient, the update process of the Kalman gain can be controlled, which can also indirectly control the number of iterations, so that the first road adhesion coefficient is determined with an iteration number less than the target number of iterations.

[0067] It should also be understood that the "Kalman gain" of the current iteration number in the above scheme is determined by the covariance matrix of the road adhesion coefficient estimated a priori at the current iteration number. Therefore, the "excitation mode" in the above scheme is specifically used to determine the way to update the covariance matrix of the a priori estimated road adhesion coefficient in the process of iteratively determining the first road adhesion coefficient through the extended Kalman filter algorithm.

[0068] It should also be understood that the process of "the vehicle controller determines the first product between the fifth road adhesion coefficient and the updated Kalman gain, and determines the first road adhesion coefficient based on the first product and the a priori estimated road adhesion coefficient" in the above scheme is similar to the process of "the vehicle controller determines the first product between the fifth road adhesion coefficient and the Kalman gain of the current iteration number, and determines the first road adhesion coefficient based on the first product and the a priori estimated road adhesion coefficient", which will not be repeated here.

[0069] In the above technical solution, the vehicle controller determines the excitation mode based on the sum of the composite slip rates of the road surfaces of multiple wheels (total slip rate). The excitation mode is used to determine the way to update the Kalman gain in the process of iteratively determining the first road adhesion coefficient through the extended Kalman filter algorithm. Furthermore, the vehicle controller updates the Kalman gain of the current iteration number based on the excitation mode. The vehicle controller determines the first road adhesion coefficient by using the target iteration number through the EKF algorithm, and updates the Kalman gain, which can speed up the fusion of the dynamic road adhesion coefficient and the kinematic road adhesion coefficient, so that the vehicle controller determines the first road adhesion coefficient with a reduced number of iterations. Therefore, this method can fuse the first road adhesion coefficient at a faster speed.

[0070] In some embodiments, the vehicle controller determines an excitation mode based on the total slip rate, including: when the total slip rate is greater than or equal to a first preset slip rate, the vehicle controller determines the excitation mode to be a first mode, and the first mode is used to indicate that the Kalman gain is updated at a first update speed; when the total slip rate is less than the first preset slip rate, the vehicle controller determines the excitation mode to be a second mode, and the second mode is used to indicate that the Kalman gain is updated at a second update speed, and the first update speed is greater than the second update speed, and the second update speed is the speed at which the Kalman gain is updated by the covariance matrix of the road adhesion coefficient estimated a priori, the Jacobian observation matrix, and the covariance matrix of the process noise in the extended Kalman filter algorithm.

[0071] It should be understood that the "second update speed is the speed of updating the Kalman gain by the covariance matrix of the a priori estimated road adhesion coefficient, the Jacobian observation matrix and the covariance matrix of the measurement noise in the extended Kalman filter algorithm" in the above scheme can be understood as the speed of updating the Kalman gain by formula (11). In the case where the excitation mode is specifically used to determine the way to update the covariance matrix of the a priori estimated road adhesion coefficient in the process of iteratively determining the first road adhesion coefficient by the extended Kalman filter algorithm, the second update speed is the speed of updating the covariance matrix of the a priori estimated road adhesion coefficient by the covariance matrix of the a posteriori estimated road adhesion coefficient, the Jacobian system matrix and the covariance matrix of the process noise in the extended Kalman filter algorithm, specifically the speed of updating the covariance matrix of the a priori estimated road adhesion coefficient by formula (10).

[0072] It should also be understood that the "first mode" in the above scheme can be regarded as an urgent update mode, and the "second mode" can be regarded as a slow update mode.

[0073] In some embodiments, the vehicle controller updates the Kalman gain of the current iteration number based on the excitation mode and determines the updated Kalman gain, including: when the excitation mode is the first mode, the vehicle controller determines the sum of the Kalman gain of the current iteration number and the target preset value as the updated Kalman gain; when the excitation mode is the second mode, the vehicle controller determines the Kalman gain of the current iteration number as the updated Kalman gain.

[0074] It should be understood that the above scheme describes that when the excitation mode is the first mode, the vehicle controller increases the target preset value based on the Kalman gain of the current iteration number to obtain a larger Kalman gain, that is, the Kalman gain is further increased on the basis of the Kalman gain originally updated by formula (11) in the EKF algorithm. When the excitation mode is the second mode, the vehicle controller only updates the Kalman gain by formula (11) in the EKF algorithm.

[0075] In step 202, the vehicle controller combines the first road adhesion coefficient, the fourth road adhesion coefficient and the utilization adhesion coefficient of the wheel to determine the target road adhesion coefficient of the driving road surface. The fourth road adhesion coefficient is determined based on the acceleration of the vehicle, and the utilization adhesion coefficient is used to indicate the effective utilization rate of the actual friction force between the tire of the wheel and the driving road surface.

[0076] It should be understood that the specific solution described in the above step 202 is to set the first road adhesion coefficient ( is the current iteration number, specifically the last iteration number), the fourth road adhesion coefficient and using the adhesion coefficient In addition, in step 202, the fourth road adhesion coefficient can be regarded as the road adhesion coefficient estimated by acceleration. The utilization adhesion coefficient refers to the minimum road adhesion coefficient required for no wheel lock under a specific braking intensity. The utilization adhesion coefficient is used to describe the relationship between the actual adhesion provided by the road surface and the maximum braking force required by the vehicle during the braking process. N The maximum adhesion coefficient of the wheels is equivalent to , the utilization adhesion coefficient of each wheel can be determined by the bracketed part in the following formula (16). N is a positive integer greater than or equal to 2.

[0077] It should also be understood that if the current number of iterations does not reach the target number of iterations, it is necessary to continue to update the road adhesion coefficient using the following formula (15) to determine the target road adhesion coefficient.

[0078] (15) In some embodiments, the method for determining the fourth road adhesion coefficient in step 202 includes: the vehicle controller determines the fourth road adhesion coefficient based on the following formula (16); (16) in, is the lateral acceleration of the vehicle, is the longitudinal acceleration of the vehicle, is the acceleration due to gravity, is the slope angle of the road surface.

[0079] In some embodiments, the method for determining the utilization adhesion coefficient of the wheel in step 202 includes: the vehicle controller determines the utilization adhesion coefficient of the wheel based on the following formula (17); , From 1 to N (17) in, For wheels The lateral tire force, For wheels The longitudinal tire force, For wheels The vertical tire force, N is the total number of wheels in the vehicle. It should be understood that the utilization coefficient of the wheel is Is in this vehicle N The maximum adhesion coefficient among the utilized adhesion coefficients of the wheels.

[0080] In a possible implementation, the vehicle controller in step 202 integrates the first road adhesion coefficient, the fourth road adhesion coefficient and the utilization adhesion coefficient of the wheel to determine the target road adhesion coefficient of the driving road, including any one of the following: the vehicle controller determines the maximum adhesion coefficient among the first road adhesion coefficient, the fourth road adhesion coefficient and the utilization adhesion coefficient as the target road adhesion coefficient; the vehicle controller determines the average adhesion coefficient among the first road adhesion coefficient, the fourth road adhesion coefficient and the utilization adhesion coefficient as the target road adhesion coefficient; the vehicle controller uses the first weight to determine the first road adhesion coefficient The vehicle controller weights the fourth road adhesion coefficient by a second weight to obtain a second coefficient; the vehicle controller weights the utilization adhesion coefficient by a third weight to obtain a third coefficient; the vehicle controller determines the sum of the first coefficient, the second coefficient and the third coefficient as the target road adhesion coefficient; wherein the first weight is used to indicate the contribution of the first road adhesion coefficient when determining the target road adhesion coefficient, the second weight is used to indicate the contribution of the fourth road adhesion coefficient when determining the target road adhesion coefficient, and the third weight is used to indicate the contribution of the utilization adhesion coefficient when determining the target road adhesion coefficient.

[0081] It should be understood that the above scheme provides three methods for determining the target road adhesion coefficient of the driving road. Specifically, the first method is: selecting the maximum adhesion coefficient among the first road adhesion coefficient, the fourth road adhesion coefficient and the utilized adhesion coefficient; the second method is: selecting the average adhesion coefficient among the first road adhesion coefficient, the fourth road adhesion coefficient and the utilized adhesion coefficient; the third method is: selecting the adhesion coefficient after weighted fusion of the first road adhesion coefficient, the fourth road adhesion coefficient and the utilized adhesion coefficient.

[0082] It should also be understood that the target road adhesion coefficient determined by the first method mentioned above is the maximum road adhesion coefficient, which can ensure that the vehicle can travel in the safest way under various driving conditions. For example, when the vehicle brakes, setting the braking strategy with the maximum road adhesion coefficient as the target can make the vehicle stop in the shortest distance and make full use of the maximum friction provided by the driving road surface. When the vehicle accelerates, the maximum road adhesion coefficient is used as the basis to optimize the power output of the vehicle so that the vehicle can increase the speed as quickly as possible without slipping. The average adhesion coefficient determined by the second method can balance the advantages and disadvantages of road adhesion coefficients from different sources and obtain a road adhesion coefficient that can better reflect the overall adhesion characteristics of the driving road surface. The average adhesion coefficient can provide a relatively accurate road condition reference for the driving process of the vehicle to better adjust the vehicle state. The weighted fusion adhesion coefficient determined by the third method and the average adhesion coefficient determined by the second method are both road adhesion coefficients that can reflect the overall adhesion characteristics of the driving road surface, but compared with the second method, the weighted fusion adhesion coefficient of the third method is more accurate. This is because the third method can take into account the different contributions of road adhesion coefficients from different sources in determining the target road adhesion coefficient under the current driving condition.

[0083] In the above technical solution, determining the target road adhesion coefficient by multiple methods can avoid the situation where the target road adhesion coefficient cannot be determined, and can also meet different requirements when determining the target road adhesion coefficient. In addition, the target road adhesion coefficient determined by the first method is the maximum road adhesion coefficient, which can ensure that the vehicle can travel in the safest way under various driving conditions. The average adhesion coefficient determined by the second method can balance the advantages and disadvantages of road adhesion coefficients from different sources and obtain a road adhesion coefficient that can better reflect the overall adhesion characteristics of the driving road. Compared with the second method, the weighted fusion adhesion coefficient of the third method is more accurate. This is because the third method can take into account the different contributions of road adhesion coefficients from different sources in determining the target road adhesion coefficient under the current driving conditions.

[0084] In one possible implementation, the method for determining the first weight, the second weight and the third weight includes: the vehicle controller determines the degree of wear of the tires of the wheels in the vehicle; when the degree of wear is less than or equal to a preset degree, the vehicle controller determines the first weight, the second weight and the third weight based on a first ratio between a first preset value and the total number corresponding to the weights, and the first weight, the second weight and the third weight are the same; when the degree of wear is greater than the preset degree, the vehicle controller determines the second weight based on the first ratio and the deviation amplitude of the degree of wear relative to the preset degree; the vehicle controller determines the first weight and the third weight based on the first preset value and the second weight.

[0085] It should be understood that in the above scheme, the "first preset value" is 1 and the "total number corresponding to the weight" is 3, because the method 200 includes a total of three weights, namely the first weight, the second weight and the third weight. It should also be understood that the "preset degree" in the above scheme is used to indicate the degree of wear that does not affect the accuracy of multiple vehicle parameters after the tire of the wheel is worn. The multiple vehicle parameters include the tire force of the wheel, the slip rate and the rolling resistance of the tire. The wear degree and the preset degree are both expressed in percentages.

[0086] It should also be understood that in the above scheme, when the degree of wear is less than or equal to the preset degree, the vehicle determines the first weight, second weight and third weight to be 1 / 3, 1 / 3 and 1 / 3 respectively based on the first ratio between the first preset value 1 and the total number 3 corresponding to the weight.

[0087] In the above technical solution, the degree of tire wear will affect the accuracy of the road adhesion coefficients from different sources. Specifically, the degree of tire wear has the least influence on the accuracy of the fourth road adhesion coefficient, followed by the utilization adhesion coefficient of the wheel, and finally the first road adhesion coefficient. This is because the degree of tire wear does not affect the acceleration in the process of determining the fourth road adhesion coefficient, but affects the tire force in the process of determining the utilization adhesion coefficient, and even more affects the tire force and slip rate in the process of determining the first road adhesion coefficient. Therefore, in this method, the vehicle controller can accurately evaluate the contribution of the road adhesion coefficients from different sources when determining the target road adhesion coefficient, that is, the first weight, the second weight, and the third weight, based on the above theory through the degree of tire wear.

[0088] In some embodiments, the degree of wear of the tire of the wheel is N The maximum, average or minimum wear degree of the tires of each wheel.

[0089] In some embodiments, the method for determining the deviation amplitude of the wear degree relative to the preset degree includes: the vehicle controller determines the difference between the wear degree and the preset degree as the deviation amplitude.

[0090] In some embodiments, the vehicle controller determines the degree of wear of the tires of the wheels in the vehicle, including: the vehicle controller obtains the height deviation between the current height of the pattern on the tire of any wheel and the target height of the wear mark on the tire; the vehicle controller determines a second ratio between the height deviation and the target height; the vehicle controller determines the difference between the first preset value and the second ratio as the degree of wear.

[0091] In some embodiments, the vehicle controller determines the second weight based on the first ratio and the deviation amplitude of the wear degree relative to the preset degree, including: the vehicle controller determines the second product between the first ratio and the deviation amplitude; the vehicle controller determines the sum of the second product and the first ratio as the second weight.

[0092] It should be understood that the "second weight" in the above scheme is a weighted coefficient of the road adhesion coefficient (fourth road adhesion coefficient) estimated by acceleration, and the degree of wear of the tire will not have a significant impact on the accuracy of the acceleration of the vehicle, and will not have a significant impact on the accuracy of the fourth road adhesion coefficient. In this way, when the degree of wear is greater than the preset degree, the fourth road adhesion coefficient is more accurate than the first road adhesion coefficient and the utilization adhesion coefficient, and therefore, its corresponding second weight is larger.

[0093] In some embodiments, the vehicle controller determines the first weight and the third weight based on the first preset value and the second weight, including: the vehicle controller determines the second difference between the first preset value and the second weight; the vehicle controller determines the first weight and the third weight based on the ratio between the second difference and the second preset value, and the first weight and the third weight are the same; or, the vehicle controller determines the third ratio between the second difference and the third preset value as the first weight, and determines the product of the third ratio and the second preset value as the third weight.

[0094] It should be understood that in the above scheme, the "second preset value" is 2 and the "third preset value" is 3. It should also be understood that in the above scheme, two ways of determining the first weight and the third weight are given. The first way is: divide the second difference into two equal parts, determine the first weight and the third weight, and the first weight and the third weight are the same. The second way is: divide the second difference into three equal parts, determine one of the equal parts as the first weight, and determine two of the equal parts as the third weight. This is because the first weight is a weighted coefficient of the first road adhesion coefficient, and the first road adhesion coefficient is affected by two factors, tire force and slip rate, while the third weight is a weighted coefficient of the utilization adhesion coefficient, and the utilization adhesion coefficient is only affected by one factor, tire force. Relatively speaking, the utilization adhesion coefficient is more accurate than the first road adhesion coefficient. Therefore, when determining the target road adhesion coefficient, the contribution of the utilization adhesion coefficient is greater than that of the first road adhesion coefficient, and the third weight accounts for a larger proportion of the second difference, while the first weight accounts for a smaller proportion of the second difference.

[0095] Figure 3 It is a schematic block diagram of estimating a road adhesion coefficient provided in an embodiment of the present application.

[0096] For example, Figure 3 As shown, the vehicle controller inputs the lateral slip rate and the longitudinal slip rate of the wheel into the kinematic model to determine the third road adhesion coefficient, and inputs the vertical tire force, longitudinal tire force and lateral tire force of the wheel into the dynamic model to determine the second road adhesion coefficient. The vehicle controller performs a first fusion of the second road adhesion coefficient and the third road adhesion coefficient to obtain the first road adhesion coefficient. The vehicle controller determines the fourth road adhesion coefficient through the acceleration of the vehicle, and determines the utilization adhesion coefficient through the vertical tire force, longitudinal tire force and lateral tire force of the wheel. The vehicle controller performs a second fusion of the first road adhesion coefficient, the fourth road adhesion coefficient and the utilization adhesion coefficient to obtain an estimated value of the road adhesion coefficient. The vehicle controller uses The estimated value is transformed to obtain the transformed estimated value, which is used to determine the first road adhesion coefficient in the next iteration, until the iteration number reaches the target iteration number, and the road adhesion coefficient finally determined is used as the target road adhesion coefficient. is a given.

[0097] Figure 4 It is a schematic flow chart of estimating a road adhesion coefficient provided in an embodiment of the present application.

[0098] For example, Figure 4As shown, the vehicle controller fuses the second road adhesion coefficient and the third road adhesion coefficient to obtain the first road adhesion coefficient. The vehicle controller fuses the first road adhesion coefficient, the fourth road adhesion coefficient and the utilization adhesion coefficient of the wheels in the vehicle to determine the target road adhesion coefficient of the vehicle's driving road. Among them, the second road adhesion coefficient is determined based on the tire force in the vehicle, the third road adhesion coefficient is determined based on the slip rate of the wheels in the vehicle, and the fourth road adhesion coefficient is determined based on the acceleration of the vehicle.

[0099] Figure 5 It is a schematic diagram of the structure of a device for estimating a road adhesion coefficient provided in an embodiment of the present application.

[0100] For example, Figure 5 As shown, the device 500 includes: A determination module 501 is used to determine a first road adhesion coefficient of a road surface on which the vehicle is traveling when the vehicle is in a traveling state, wherein the first road adhesion coefficient is obtained by integrating a second road adhesion coefficient and a third road adhesion coefficient, wherein the second road adhesion coefficient is determined based on a tire force in the vehicle, and the third road adhesion coefficient is determined based on a slip rate of a wheel in the vehicle; The fusion module 502 is used to fuse the first road adhesion coefficient, the fourth road adhesion coefficient and the utilization adhesion coefficient of the wheel to determine the target road adhesion coefficient of the driving road surface, the fourth road adhesion coefficient is determined based on the acceleration of the vehicle, and the utilization adhesion coefficient is used to indicate the effective utilization rate of the actual friction force between the tire of the wheel and the driving road surface.

[0101] Optionally, the determination module 501 is specifically used to: take any wheel in the vehicle as a target wheel, and determine the lateral slip rate and longitudinal slip rate of the target wheel; determine the road surface composite slip rate of the target wheel based on the lateral slip rate and the target longitudinal slip rate, the target longitudinal slip rate is obtained based on the product between the longitudinal slip rate and a first coefficient, and the first coefficient is used to indicate the influence of the longitudinal slip rate on the tire friction performance of the target wheel; determine the road surface adhesion coefficient corresponding to the target wheel based on the road surface composite slip rate, the lateral slip rate, the longitudinal slip rate and the first coefficient; determine the third road surface adhesion coefficient based on the road surface adhesion coefficients corresponding to each wheel in the vehicle.

[0102] Optionally, the determination module 501 is further specifically used to: determine the tangential force between the target wheel and the driving road surface based on the composite slip rate of the road surface; and determine the road adhesion coefficient corresponding to the target wheel based on the tangential force, the composite slip rate of the road surface, the lateral slip rate, the longitudinal slip rate and the first coefficient.

[0103] Optionally, the determination module 501 is further specifically used to: determine the difference between the second road adhesion coefficient of the current iteration number and the third road adhesion coefficient of the current iteration number as the fifth road adhesion coefficient of the current iteration number; determine the first product between the fifth road adhesion coefficient and the Kalman gain of the current iteration number, and determine the first road adhesion coefficient based on the first product and the prior estimated road adhesion coefficient of the current iteration number.

[0104] Optionally, the determination module 501 is further specifically used to: determine the sum of the composite road surface slip rates of multiple wheels in the vehicle as a total slip rate; determine an excitation mode based on the total slip rate, and the excitation mode is used to determine a method for updating the Kalman gain in the process of iteratively determining the first road surface adhesion coefficient through the extended Kalman filter algorithm; based on the excitation mode, update the Kalman gain of the current iteration number to determine the updated Kalman gain; determine a first product between the fifth road surface adhesion coefficient and the updated Kalman gain, and determine the first road surface adhesion coefficient based on the first product and the a priori estimated road surface adhesion coefficient.

[0105] Optionally, the fusion module 502 is specifically used for any one of the following: determining the maximum adhesion coefficient among the first road adhesion coefficient, the fourth road adhesion coefficient and the utilization adhesion coefficient as the target road adhesion coefficient; determining the average adhesion coefficient among the first road adhesion coefficient, the fourth road adhesion coefficient and the utilization adhesion coefficient as the target road adhesion coefficient; weighting the first road adhesion coefficient by a first weight to obtain a first coefficient; weighting the fourth road adhesion coefficient by a second weight to obtain a second coefficient; weighting the utilization adhesion coefficient by a third weight to obtain a third coefficient; determining the sum of the first coefficient, the second coefficient and the third coefficient as the target road adhesion coefficient; wherein the first weight is used to indicate the contribution of the first road adhesion coefficient when determining the target road adhesion coefficient, the second weight is used to indicate the contribution of the fourth road adhesion coefficient when determining the target road adhesion coefficient, and the third weight is used to indicate the contribution of the utilization adhesion coefficient when determining the target road adhesion coefficient.

[0106] Optionally, the determination module 501 is further specifically used to: determine the degree of wear of the tires of the wheels in the vehicle; when the degree of wear is less than or equal to a preset degree, determine the first weight, the second weight and the third weight based on a first ratio between a first preset value and the total number corresponding to the weights, and the first weight, the second weight and the third weight are the same; when the degree of wear is greater than the preset degree, determine the second weight based on the first ratio and the deviation amplitude of the degree of wear relative to the preset degree; determine the first weight and the third weight based on the first preset value and the second weight.

[0107] Figure 6 It is a structural schematic diagram of a vehicle provided in an embodiment of the present application.

[0108] For example, Figure 6 As shown, the vehicle 600 includes: a memory 601 and a processor 602, wherein the memory 601 stores an executable program code 603, and the processor 602 is used to call and execute the executable program code 603 to perform a method for estimating a road adhesion coefficient.

[0109] In addition, an embodiment of the present application also protects a device, which may include a memory and a processor, wherein the memory stores an executable program code, and the processor is used to call and execute the executable program code to execute a method for estimating a road adhesion coefficient provided in an embodiment of the present application.

[0110] In this embodiment, the functional modules of the device can be divided according to the above method example. For example, each functional module can be corresponded, or two or more functions can be integrated into one processing module. The above integrated module can be implemented in the form of hardware. It should be noted that the division of modules in this embodiment is schematic and is only a logical function division. There may be other division methods in actual implementation.

[0111] In the case of dividing each functional module according to each function, the device may further include a determination module and a fusion module, etc. It should be noted that all relevant contents involved in the above method embodiment can be referred to the functional description of the corresponding functional module, which will not be repeated here.

[0112] It should be understood that the device provided in this embodiment is used to execute the above-mentioned method for estimating the road adhesion coefficient, and thus can achieve the same effect as the above-mentioned implementation method.

[0113] In the case of an integrated unit, the device may include a processing module and a storage module. When the device is applied to a vehicle, the processing module may be used to control and manage the actions of the vehicle. The storage module may be used to support the vehicle in executing related executable program codes, etc.

[0114] The processing module may be a processor or a controller, which may implement or execute various exemplary logic blocks, modules and circuits shown in combination with the contents disclosed in this application. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of digital signal processing (DSP) and a microprocessor, etc. The storage module may be a memory.

[0115] In addition, the device provided in the embodiments of the present application may specifically be a chip, a component or a module, and the chip may include a connected processor and a memory; wherein the memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute a method for estimating the road adhesion coefficient provided in the above embodiment.

[0116] This embodiment also provides a computer-readable storage medium, which stores executable program code. When the executable program code runs on a computer, the computer executes the above-mentioned related method steps to implement a method for estimating a road adhesion coefficient provided in the above embodiment.

[0117] This embodiment also provides a computer program product. When the computer program product is run on a computer, the computer is enabled to execute the above-mentioned related steps to implement a method for estimating a road adhesion coefficient provided in the above-mentioned embodiment.

[0118] Among them, the device, computer-readable storage medium, computer program product or chip provided in this embodiment is used to execute the corresponding method provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method provided above, and will not be repeated here.

[0119] Through the description of the above implementation methods, technical personnel in the relevant field can understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0120] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0121] The above contents are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for estimating a road adhesion coefficient, characterized in that: The method comprises: When the vehicle is in a driving state, determining a first road adhesion coefficient of a driving road of the vehicle, the first road adhesion coefficient being obtained by integrating a second road adhesion coefficient and a third road adhesion coefficient, the second road adhesion coefficient being determined based on a tire force in the vehicle, and the third road adhesion coefficient being determined based on a slip rate of a wheel in the vehicle; The first road adhesion coefficient, the fourth road adhesion coefficient and the utilization adhesion coefficient of the wheel are integrated to determine the target road adhesion coefficient of the driving road surface, the fourth road adhesion coefficient is determined based on the acceleration of the vehicle, and the utilization adhesion coefficient is used to indicate the effective utilization rate of the actual friction force between the tire of the wheel and the driving road surface.

2. The method according to claim 1, characterized in that The method for determining the third road adhesion coefficient includes: Taking any wheel of the vehicle as a target wheel, determining a lateral slip rate and a longitudinal slip rate of the target wheel; determining a road surface composite slip rate of the target wheel based on the lateral slip rate and a target longitudinal slip rate, wherein the target longitudinal slip rate is obtained based on a product of the longitudinal slip rate and a first coefficient, wherein the first coefficient is used to indicate the influence of the longitudinal slip rate on the tire friction performance of the target wheel; Determining a road adhesion coefficient corresponding to the target wheel based on the road composite slip rate, the lateral slip rate, the longitudinal slip rate and the first coefficient; The third road adhesion coefficient is determined based on the road adhesion coefficient corresponding to each wheel in the vehicle.

3. The method according to claim 2, characterized in that The determining the road adhesion coefficient corresponding to the target wheel based on the road composite slip rate, the lateral slip rate, the longitudinal slip rate and the first coefficient includes: Determining a tangential force between the target wheel and the driving road surface based on the road surface composite slip rate; A road adhesion coefficient corresponding to the target wheel is determined based on the tangential force, the road surface composite slip rate, the lateral slip rate, the longitudinal slip rate and the first coefficient.

4. The method according to claim 1, characterized in that The determining of a first road surface adhesion coefficient of a driving road surface of the vehicle comprises: Determine the difference between the second road surface adhesion coefficient of the current iteration number and the third road surface adhesion coefficient of the current iteration number as the fifth road surface adhesion coefficient of the current iteration number; A first product between the fifth road adhesion coefficient and the Kalman gain of the current iteration number is determined, and the first road adhesion coefficient is determined based on the first product and the a priori estimated road adhesion coefficient of the current iteration number.

5. The method according to claim 4, characterized in that The determining of a first product between the fifth road adhesion coefficient and the Kalman gain of the current iteration number, and determining the first road adhesion coefficient based on the first product and the a priori estimated road adhesion coefficient, comprises: Determining the sum of the composite road slip rates of the plurality of wheels in the vehicle as the total slip rate; Based on the total slip ratio, determining an excitation mode, wherein the excitation mode is used to determine a manner of updating a Kalman gain in a process of iteratively determining a first road adhesion coefficient by using an extended Kalman filter algorithm; Based on the excitation mode, the Kalman gain of the current iteration number is updated to determine the updated Kalman gain; A first product between the fifth road adhesion coefficient and the updated Kalman gain is determined, and the first road adhesion coefficient is determined based on the first product and the a priori estimated road adhesion coefficient.

6. The method according to claim 1, characterized in that The step of fusing the first road adhesion coefficient, the fourth road adhesion coefficient and the utilization adhesion coefficient of the wheel to determine the target road adhesion coefficient of the driving road comprises any one of the following: determining the maximum adhesion coefficient among the first road surface adhesion coefficient, the fourth road surface adhesion coefficient and the utilized adhesion coefficient as the target road surface adhesion coefficient; determining an average adhesion coefficient among the first road surface adhesion coefficient, the fourth road surface adhesion coefficient and the utilization adhesion coefficient as the target road surface adhesion coefficient; The first road adhesion coefficient is weighted by a first weight to obtain a first coefficient; the fourth road adhesion coefficient is weighted by a second weight to obtain a second coefficient; the utilization adhesion coefficient is weighted by a third weight to obtain a third coefficient; and the sum of the first coefficient, the second coefficient and the third coefficient is determined as the target road adhesion coefficient; Among them, the first weight is used to indicate the contribution of the first road adhesion coefficient when determining the target road adhesion coefficient, the second weight is used to indicate the contribution of the fourth road adhesion coefficient when determining the target road adhesion coefficient, and the third weight is used to indicate the contribution of the adhesion coefficient used when determining the target road adhesion coefficient.

7. The method according to claim 6, characterized in that The method for determining the first weight, the second weight and the third weight includes: determining the degree of wear of tires of wheels in the vehicle; When the degree of wear is less than or equal to a preset degree, the first weight, the second weight and the third weight are determined based on a first ratio between a first preset value and a total number corresponding to the weight, and the first weight, the second weight and the third weight are the same; When the wear degree is greater than the preset degree, determining the second weight based on the first ratio and the deviation amplitude of the wear degree relative to the preset degree; Based on the first preset value and the second weight, the first weight and the third weight are determined.

8. A device for estimating a road adhesion coefficient, characterized in that: The device comprises: a determination module, for determining, when the vehicle is in a driving state, a first road adhesion coefficient of a driving road of the vehicle, the first road adhesion coefficient being obtained by fusing a second road adhesion coefficient and a third road adhesion coefficient, the second road adhesion coefficient being determined based on a tire force in the vehicle, and the third road adhesion coefficient being determined based on a slip rate of a wheel in the vehicle; A fusion module is used to fuse the first road adhesion coefficient, the fourth road adhesion coefficient and the utilization adhesion coefficient of the wheel to determine the target road adhesion coefficient of the driving road, wherein the fourth road adhesion coefficient is determined based on the acceleration of the vehicle.

9. A vehicle, characterized in that: The vehicle comprises: A memory for storing executable program codes; A processor, configured to call and run the executable program code from the memory, so that the vehicle executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores an executable program code, and when the executable program code is executed, the method according to any one of claims 1 to 7 is implemented.

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