Road adhesion coefficient estimation method and equipment

Abstract

The invention discloses a road adhesion coefficient estimation method, device and equipment, and the method at least comprises the steps: determining a current target driving stage of a vehicle based on the driving data of the vehicle, the target driving stage being used for pointing to the change of the motion state of the vehicle; determining a target estimation mode for road adhesion coefficient estimation in a plurality of estimation modes based on the target driving stage; and estimating a target road surface adhesion coefficient of each wheel in the vehicle on the driving road surface based on the target estimation mode. According to the scheme, the accuracy of the road adhesion coefficient of each wheel is improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to, but not limited to, a method and device for estimating a road adhesion coefficient. Background Art

[0002] Determining the vehicle's adhesion coefficient on the road is crucial for vehicle control. Its accuracy directly affects braking distance, obstacle avoidance strategies, and comfort.

[0003] Related technologies typically use sliding mode variable structure control theory to estimate tire forces, and then infer the adhesion coefficient based on the relationship between tire forces and adhesion coefficient. This method does not match the actual situation and has low accuracy. Summary of the Invention

[0004] In order to solve the above problems, the present application at least provides a method, device and equipment for estimating the road adhesion coefficient, which improves the accuracy of the road adhesion coefficient of each wheel.

[0005] The technical solution of this application is achieved as follows:

[0006] In a first aspect, the present application provides a method for estimating a road surface adhesion coefficient, the method comprising:

[0007] Determining a current target driving phase of the vehicle based on the vehicle's driving data, where the target driving phase is used to indicate a change in the vehicle's motion state;

[0008] determining a target estimation method for estimating a road adhesion coefficient from among a plurality of estimation methods based on a target driving phase;

[0009] A target road adhesion coefficient of each wheel of the vehicle on the driving road is estimated based on a target estimation method.

[0010] In a second aspect, the present application provides a device for estimating a road adhesion coefficient, comprising:

[0011] a first determining unit, configured to determine a current target driving phase of the vehicle based on driving data of the vehicle, wherein the target driving phase is used to indicate a change in a motion state of the vehicle;

[0012] a second determining unit for determining a target estimation method for estimating the road adhesion coefficient from among a plurality of estimation methods based on the target driving phase;

[0013] The estimation unit is used to estimate a target road adhesion coefficient of each wheel of the vehicle on the driving road based on a target estimation method.

[0014] In a third aspect, the present application provides a vehicle device, the electronic device including a memory and a processor, the memory storing a computer program or instructions, and the computer program or instructions, when executed by the processor, implements the method provided in the first aspect.

[0015] In a fourth aspect, the present application further provides a storage medium storing a computer program or instruction, which, when executed by a processor, implements any one of the methods provided in the first aspect.

[0016] In a fifth aspect, the present application also provides a computer program product, which includes a computer program or instructions. When the computer program or instructions are executed by a processor, any one of the methods provided in the first aspect above is implemented.

[0017] The road adhesion coefficient estimation scheme provided in this application includes, but is not limited to, a road adhesion coefficient estimation method, apparatus, device, storage medium, and program product. The method includes at least: determining a vehicle's current target driving phase based on vehicle driving data, where the target driving phase refers to a change in the vehicle's motion state; determining a target estimation method for estimating the road adhesion coefficient from among multiple estimation methods based on the target driving phase; and estimating a target road adhesion coefficient for each wheel of the vehicle on the driving road based on the target estimation method.

[0018] This road adhesion coefficient estimation scheme first identifies a target driving phase for the vehicle. A target estimation method that matches this target driving phase is then selected from multiple estimation methods. The target road adhesion coefficient for each wheel of the vehicle on the road surface is estimated using this target estimation method. This method matches the target driving phase, allowing the target road adhesion coefficient to be estimated using a method that satisfies the target driving phase. This method aligns with the vehicle's actual driving conditions and provides high accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A schematic diagram of an optional flow chart for an application scenario of the road adhesion coefficient estimation solution provided in an embodiment of the present application;

[0020] Figure 2 A schematic diagram of a first optional flow chart of a method for estimating a road adhesion coefficient provided in an embodiment of the present application;

[0021] Figure 3 A second optional flow chart of the method for estimating the road adhesion coefficient provided in an embodiment of the present application;

[0022] Figure 4 A third optional flow chart of the method for estimating the road adhesion coefficient provided in the embodiment of the present application;

[0023] Figure 5 A fourth optional flow chart of the method for estimating the road adhesion coefficient provided in an embodiment of the present application;

[0024] Figure 6 A fifth optional flow chart of the method for estimating the road adhesion coefficient provided in the embodiment of the present application;

[0025] Figure 7 A sixth optional flow chart of the method for estimating the road adhesion coefficient provided in an embodiment of the present application;

[0026] Figure 8 A seventh optional flow chart of the method for estimating the road adhesion coefficient provided in the embodiment of the present application;

[0027] Figure 9 An optional flowchart of a process for determining the adhesion coefficient of each wheel provided in an embodiment of the present application;

[0028] Figure 10 A schematic diagram of an optional structure of a device for estimating a road adhesion coefficient provided in an embodiment of the present application;

[0029] Figure 11 This is a schematic diagram of an optional structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0030] To make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the specific technical solutions of the application will be further described in detail below in conjunction with the drawings in the embodiments of the present application. The following embodiments are used to illustrate the present application but are not intended to limit the scope of the present application.

[0031] In the following description, reference is made to “some embodiments”, which describes a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0032] In the following description, the terms "first, second, and third" are used merely as examples to distinguish between different objects and do not represent a specific order or precedence for the objects. It is understood that the specific order or precedence of "first, second, and third" can be interchanged where permitted, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein.

[0033] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0034] Embodiments of the present application provide a method, apparatus, device, storage medium, and program product for estimating a road adhesion coefficient. In practical applications, the method for estimating a road adhesion coefficient can be implemented by an apparatus for estimating a road adhesion coefficient. The functional entities within the apparatus can be collaboratively implemented by hardware resources of an electronic device (e.g., computing resources such as a processor, and communication resources). For example, the electronic device can be a controller within a vehicle.

[0035] Below, various embodiments of the road adhesion coefficient estimation method, device, equipment, storage medium and program product provided in the embodiments of the present application are described.

[0036] In the first aspect, an embodiment of the present application provides a method for estimating a road adhesion coefficient. The functions implemented by the method can be implemented by calling program codes by an electronic device. Of course, the program codes can be stored in a computer storage medium. It can be seen that the electronic device includes at least a processor and a processor.

[0037] First, the application scenario of the road adhesion coefficient estimation scheme is explained.

[0038] refer to Figure 1 The content shown includes a vehicle 10 and a road surface 20 , wherein the vehicle 10 is traveling on the road surface 20 .

[0039] The vehicle 10 is used to perform the following: determining a current target driving phase of the vehicle based on the vehicle's driving data, the target driving phase being used to indicate a change in the vehicle's motion state; determining a target estimation method for estimating a road adhesion coefficient from among a plurality of estimation methods based on the target driving phase; and estimating a target road adhesion coefficient of each wheel in the vehicle on a driving road surface based on the target estimation method.

[0040] The present embodiment does not limit the type of vehicle 10 and can be determined based on actual conditions. For example, the vehicle 10 may include, but is not limited to, any of the following: a sedan, a sports car, a commercial vehicle, an electric vehicle, a gasoline vehicle, a hydrogen vehicle, etc.

[0041] The present embodiment does not limit the type of road surface 20 and can be determined according to actual conditions. For example, the road surface 20 may include, but is not limited to, any of the following: asphalt concrete road surface, cement concrete road surface, masonry road surface, flexible road surface, rigid road surface, sandstone road surface, gravel road surface, cobblestone road surface, and wet mud road surface.

[0042] Below, the method for estimating the road adhesion coefficient provided in the embodiment of the present application is described using an electronic device as the execution subject.

[0043] refer to Figure 2 The process may include but is not limited to the following S201 to S203.

[0044] S201. The electronic device determines a current target driving phase of the vehicle based on driving data of the vehicle.

[0045] The target driving phase is used to refer to the change in the vehicle's motion state.

[0046] The target driving phase here may include but is not limited to any of the following: a starting driving phase, a transition driving phase, and a stable driving phase.

[0047] Starting phase: The process from when the vehicle starts from a stationary state until it reaches an initial stable speed, such as 5-10 kilometers per hour (km / h). This usually corresponds to the initial stage when the driver presses the accelerator pedal and the power system starts to output torque.

[0048] Transition driving phase: The acceleration, deceleration, or steering process after the vehicle starts to enter the stable driving state, covering the dynamic stage of changes in parameters such as speed, acceleration, and steering wheel angle (such as accelerating from 10 km / h to 20 km / h)

[0049] Stable driving stage: The vehicle travels within a set speed range or fixed operating conditions, or performs uniform circular motion within a set steering angle range (such as driving at a constant speed around an island). At this time, the vehicle is under balanced forces, the motion state does not change significantly, and the slip rate is stable.

[0050] The vehicle's driving data may include but is not limited to: vehicle speed, start-up time, etc.

[0051] In a possible implementation, S201 may be implemented as follows: the electronic device may determine the current target driving phase of the vehicle based on the startup duration of the vehicle.

[0052] In another possible implementation, S201 may be implemented as follows: the electronic device determines the current target driving phase of the vehicle based on the driving speed of the vehicle.

[0053] Of course, the target driving phase can also be determined through other driving data, which will not be listed here one by one.

[0054] S202: The electronic device determines a target estimation method for estimating the road adhesion coefficient from among multiple estimation methods based on the target driving phase.

[0055] The road adhesion coefficient reflects the strength of the road's "grip" and is generally expressed in μ. The larger μ is, the less likely the tire is to slip and the better the vehicle's handling stability; the smaller μ is, the smoother the road surface (such as icy and snowy roads) and the easier it is for the vehicle to lose control.

[0056] Road adhesion is the ratio of the maximum tangential reaction force to the vertical reaction force exerted by the ground on the vehicle's wheels. It depends primarily on factors such as the road surface material and condition (dry, wet, icy, etc.), the tire structure and tread pattern, and the vehicle's speed. It can be thought of as the static friction coefficient between the tire and the road, reflecting the degree of adhesion between the tire and the road.

[0057] The slip coefficient is the ratio of friction (i.e., the sum of the forces acting on the tire) to vertical load when the tire slides on the road. It reflects the grip between the tire and the road, affecting braking and other performance. Tire forces can include driving force and / or braking force, so the slip coefficient is only related to the wheel's driving force, wheel braking force, and vertical load.

[0058] Different driving stages correspond to different estimation methods for estimating the road adhesion coefficient, that is, a starting driving stage corresponds to one estimation method, a transition driving stage corresponds to one driving method, and a stable driving stage corresponds to one estimation method.

[0059] S202 may be implemented as follows: the electronic device determines, based on the target driving phase, from among multiple estimation methods, an estimation method corresponding to the target driving phase as a target estimation method for estimating the road adhesion coefficient. For example, after determining the target driving phase, the electronic device searches for configuration information for the estimation method and determines the target estimation method corresponding to the target driving phase from the configuration information. The configuration information may be a table or other method.

[0060] S203: The electronic device estimates a target road adhesion coefficient of each wheel of the vehicle on the driving road based on the target estimation method.

[0061] The electronic device uses an independent calculation method for each wheel in the vehicle to determine the target road adhesion coefficient of each wheel on the driving road through a target estimation method.

[0062] The method for estimating the road adhesion coefficient provided by this embodiment includes at least: determining the vehicle's current target driving stage based on the vehicle's driving data, the target driving stage being used to indicate a change in the vehicle's motion state; determining a target estimation method for estimating the road adhesion coefficient from a plurality of estimation methods based on the target driving stage; and estimating the target road adhesion coefficient of each wheel in the vehicle on the driving road surface based on the target estimation method.

[0063] This road adhesion coefficient estimation scheme first identifies a target driving phase for the vehicle. A target estimation method that matches this target driving phase is then selected from multiple estimation methods. The target road adhesion coefficient for each wheel of the vehicle on the road surface is estimated using this target estimation method. This method matches the target driving phase, allowing the target road adhesion coefficient to be estimated using a method that satisfies the target driving phase. This method aligns with the vehicle's actual driving conditions and provides high accuracy.

[0064] Next, the process of determining a target estimation method for estimating the road adhesion coefficient from among multiple estimation methods by the electronic device in S202 based on the target driving phase will be described.

[0065] This process may include but is not limited to any one of the following cases 1 to 3.

[0066] Case 1: When the target driving phase includes a starting driving phase, the electronic device determines that the target estimation method includes a first estimation method; the first estimation method is related to the acceleration of the wheel.

[0067] During the starting phase, the vehicle's wheels are prone to slipping. Electronic equipment can determine whether the wheels are slipping through acceleration. The first estimation method is an estimation method related to wheel acceleration. The target road adhesion coefficient can be determined based on the acceleration. This is more in line with the driving conditions during the starting phase and is more accurate.

[0068] Case 2: When the target driving phase includes a transition driving phase, the electronic device determines that the target estimation method includes a second estimation method; the second estimation method is related to the wheel acceleration and the slip rate.

[0069] During the transition driving phase, the vehicle overcomes static friction and enters the acceleration phase, but the driving is still unstable and easily disturbed. Therefore, determining the target road adhesion coefficient through the second estimation method related to wheel acceleration and slip rate is more in line with the characteristics of the transition driving phase, and the obtained target road adhesion coefficient is more accurate.

[0070] Case 3: When the target driving phase includes a stable driving phase, the electronic device determines that the target estimation method includes a third estimation method; the third estimation method is related to the slip ratio.

[0071] During the stable driving phase, the wheels are in a stable rolling state. Determining the target road adhesion coefficient by the third method related to the slip rate is more in line with the characteristics of the stable driving phase, and the obtained target road adhesion coefficient is more accurate.

[0072] In this way, the target road adhesion coefficient is determined through different estimation methods in each driving stage, and each estimation method can meet the characteristics of each driving stage, so the target road adhesion coefficient is more accurate, and controlling the vehicle based on the adhesion coefficient is safer and the experience is better.

[0073] Next, the process of the electronic device estimating the target road adhesion coefficient of each wheel of the vehicle on the driving road based on the target estimation method in S203 is described.

[0074] The process may include but is not limited to any one of the following methods 1 to 3.

[0075] Mode 1: When the target driving phase includes a starting driving phase, the electronic device estimates a target road adhesion coefficient of each wheel of the vehicle on the driving road surface based on a target estimation mode; the target estimation mode is a first estimation mode;

[0076] Mode 2: When the target driving phase includes a stable driving phase, the electronic device estimates a target road adhesion coefficient of each wheel of the vehicle on the driving road surface based on a target estimation mode; the target estimation mode is a third estimation mode;

[0077] Mode 3: When the target driving phase includes a transition driving phase, the electronic device estimates the target road adhesion coefficient of each wheel in the vehicle on the driving road surface based on the target estimation mode; the target estimation mode is the second estimation mode.

[0078] Next, a description will be given of a process in which the electronic device estimates a target road adhesion coefficient for each wheel of the vehicle on the road surface based on the target estimation method when the target driving phase includes a start driving phase in method 1.

[0079] The following uses a wheel in a vehicle as an example to illustrate the process. Figure 3 The process may include but is not limited to the following S301 to S304.

[0080] S301: The electronic device obtains the longitudinal speed of the wheel.

[0081] In a possible implementation, the electronic device detects the longitudinal speed of the wheel based on a speed sensor installed on the vehicle, and then transmits the longitudinal speed of the wheel to the electronic device. S301 can be implemented as follows: the electronic device receives data sent by the speed sensor to obtain the longitudinal speed of the wheel.

[0082] In another possible implementation, S301 may be implemented as follows: the electronic device reads the speed configured for each wheel in the vehicle controller, thereby obtaining the longitudinal speed of each vehicle.

[0083] S302: The electronic device determines the longitudinal acceleration of the wheel based on the longitudinal velocity of the wheel.

[0084] The electronic device takes the derivative of the longitudinal velocity of the wheel to obtain the longitudinal acceleration of the vehicle.

[0085] Then, the relationship between the longitudinal acceleration and the first threshold is determined. If the longitudinal acceleration is less than or equal to the first threshold, the following S303 is executed. If the longitudinal acceleration is greater than the first threshold, the following S304 is executed.

[0086] S303: When the longitudinal acceleration is less than or equal to the first threshold, the electronic device determines the target road adhesion coefficient of the wheel as the reference adhesion coefficient.

[0087] The first threshold is used to indicate whether the wheel is slipping. The embodiment of the present application does not limit the value of the first threshold, and can be configured based on experience. Generally, the first threshold is related to the roughness of the road surface and the tire parameters of the vehicle.

[0088] Exemplarily, the first threshold may be determined to be 1g.

[0089] The longitudinal acceleration is less than or equal to the first threshold, indicating that the vehicle is not skidding.

[0090] The reference adhesion coefficient can be determined based on experience. For example, for different road surfaces, a reference adhesion coefficient corresponding to the road surface is determined. The rougher the road surface, the larger the corresponding reference adhesion coefficient.

[0091] For example, for ordinary roads, the reference adhesion coefficient can be set to 0.8.

[0092] When the longitudinal acceleration is less than or equal to the first threshold, it is considered that the road adhesion coefficient is sufficient to prevent slipping, and the electronic device determines the target road adhesion coefficient of the wheel as the reference adhesion coefficient.

[0093] S304: When the longitudinal acceleration is greater than the first threshold, the electronic device determines the target road adhesion coefficient of the wheel as the utilized adhesion coefficient of the wheel.

[0094] The longitudinal acceleration is greater than the first threshold, indicating that the vehicle is skidding.

[0095] The slip coefficient is the ratio of friction (i.e., the sum of the forces acting on the tire) to vertical load when the tire slides on the road. It reflects the grip between the tire and the road, affecting braking and other performance. Tire forces can include driving force and / or braking force, so the slip coefficient is only related to the wheel's driving force, wheel braking force, and vertical load.

[0096] When the longitudinal acceleration is greater than the first threshold, it is considered that the road adhesion coefficient has exceeded the adhesion limit and slipping may occur. The electronic device determines the target road adhesion coefficient of the wheel as the utilized adhesion coefficient of the wheel.

[0097] In this embodiment, during the starting driving phase, due to the sudden change in tire slip rate, the target road adhesion coefficient determined based on the slip rate is inaccurate. Therefore, the target road adhesion coefficient is determined by acceleration, which matches the characteristics of the starting driving phase and improves the accuracy of the target road adhesion coefficient.

[0098] Next, in the case where the target driving phase includes the steady driving phase in the second mode, the target road surface adhesion coefficient of each wheel in the vehicle on the driving road surface is estimated based on the target estimation mode.

[0099] The following uses a wheel in a vehicle as an example to illustrate the process. Figure 4 The process may include but is not limited to the following S401 to S403.

[0100] S401: The electronic device determines a slip rate of the wheel based on the longitudinal wheel speed and longitudinal angular velocity of the wheel.

[0101] For example, the electronic device may determine the slip rate of the wheel based on the longitudinal wheel speed and longitudinal angular velocity of the wheel and formula (1).

[0102]

[0103] In formula (1), i represents the i-th wheel; represents the slip rate of the i-th wheel, v i represents the longitudinal speed of the i-th wheel, w i represents the longitudinal angular velocity of the i-th wheel, and R represents the free rolling radius of the wheel.

[0104] The longitudinal wheel speed here is converted based on the vehicle's center of mass position speed.

[0105] For example, i It can be obtained by the following formula (2).

[0106]

[0107] In formula (2), v1, v2, v3, and v4 represent the speeds along the rolling directions of the front left, front right, rear left, and rear right wheels, respectively. f , d r are front and rear wheelbases respectively; a, b are front and rear wheelbases respectively; V x , V y are the longitudinal and lateral velocities at the vehicle's center of mass, respectively; δ iiis the turning angle corresponding to each wheel.

[0108] S402: The electronic device determines a first relationship based on the slip rate of the wheel, the utilization adhesion coefficient of the wheel, and a tire model.

[0109] The first relationship is the relationship between the adhesion coefficient and the slip rate of the wheel.

[0110] The electronic device may determine the first relationship by referring to the following formula (3).

[0111]

[0112] In formula (3), μ ip is the road adhesion coefficient, s ip Slip ratio corresponding to the road adhesion coefficient; μ xi , s wi are the tire adhesion coefficient and tire slip rate calculated above.

[0113] S403: The electronic device determines a target road adhesion coefficient based on the first relationship.

[0114] The electronic device processes formula (3) based on the recursive least squares method. Since formula (3) is the relationship between the adhesion coefficient and the slip rate, the maximum μ is identified based on the recursive least squares method. ip , as the target road adhesion coefficient.

[0115] In this embodiment, during the stable driving phase, the slip rate and the utilized adhesion coefficient of the wheel are first determined, and then a first relationship is determined. Based on the first relationship, the maximum adhesion coefficient is determined as the target road adhesion coefficient. This achieves clear logic and complies with the wheel law during the stable driving phase, and the obtained target road adhesion coefficient is highly accurate.

[0116] The method provided in the embodiment of the present application may also include an explanation using a process of determining an adhesion coefficient.

[0117] The electronic device can determine the utilization adhesion coefficient based on the following formula (4).

[0118]

[0119] In formula (4), is the adhesion coefficient of each wheel, F zi is the vertical force of each wheel, F i The driving force for the wheels.

[0120] In one possible embodiment, the utilization adhesion coefficient of the wheel is determined directly based on formula (4).

[0121] In another possible implementation, an extended state observer may be configured based on formula (4), and the utilized adhesion coefficient of the wheel may be determined based on the state observer.

[0122] In one embodiment, reference Figure 5 As shown in the content, the process of determining the adhesion coefficient may include but is not limited to the following S501 and S502.

[0123] S501: The electronic device determines a vertical load of a wheel based on driving data and structural data of the vehicle.

[0124] The electronic device collects the vehicle's driving data, reads the vehicle's structural data, and then determines the vertical load of the wheel based on formula (5).

[0125]

[0126] In formula (5), F z1 、F z2 、F z3 、F z4 are the vertical loads on the left front, right front, left rear and right rear tires of the vehicle, respectively. x is the vehicle longitudinal acceleration uploaded by the vehicle chassis, a y represents the lateral acceleration, w v represents the yaw rate, m represents the vehicle mass, L f Indicates the vehicle's front wheelbase, L r Indicates the vehicle's rear wheelbase, h g represents the height of the vehicle's center of mass, g represents the acceleration due to gravity, and B represents the vehicle's wheelbase.

[0127] S502: The electronic device processes the vertical load of the wheel through the extended state observer to obtain the utilization adhesion coefficient of the wheel.

[0128] First, the vehicle single wheel dynamics equation is constructed using the following formula (6).

[0129]

[0130] In formula (6), I z is the vehicle's Z-axis moment of inertia, is the angular acceleration of each wheel, T bi is the braking torque of each wheel, T di is the driving torque of each wheel, F i is the driving force of each wheel, R is the free rolling radius of the wheel, and K is the vehicle dynamic feature identification coefficient, which is mainly used to judge the vehicle's driving direction and working status. bi +T di >0, K=1; if T bi +Tdi <0, K=-1; otherwise K=0.

[0131] Among them, F i It can be obtained based on the following formula (7).

[0132]

[0133] In formula (7), is the adhesion coefficient of each wheel, F zi is the vertical force of each wheel, F i For the driving force of each wheel.

[0134] Then, a typical first-order extended state observer is used to determine the utilization adhesion coefficient. For example, the utilization adhesion coefficient is determined according to the following formula (8).

[0135]

[0136] In formula (8), is the estimated utilization adhesion coefficient, F zi is the vertical force of each wheel, R is the free rolling radius of the wheel, I z is the vehicle's Z-axis moment of inertia, is the parameter value determined based on the extended state observer.

[0137] In this embodiment, the adhesion coefficient is determined based on an extended state observer, which is more accurate.

[0138] Next, a description will be given of a process for estimating a target road surface adhesion coefficient for each wheel of the vehicle on the road surface based on the target estimation method when the target driving phase includes a transitional driving phase in Method 3.

[0139] refer to Figure 6 The process may include but is not limited to the following S601 to S603.

[0140] S601: The electronic device determines the current driving time of the vehicle.

[0141] The electronic device reads the vehicle's driving time from the time it was started to the current time in the controller. The driving time here is measured based on the speed.

[0142] S602: The electronic device determines a first coefficient and a second coefficient based on the driving duration.

[0143] In one possible implementation, the electronic device determines the first coefficient and the second coefficient based on the driving duration, the first duration threshold, and the second duration threshold.

[0144] The first duration threshold is a critical duration between the starting driving phase and the transition driving phase.

[0145] The second duration threshold is a critical duration between the transition driving phase and the stable driving phase.

[0146] For example, the first coefficient and the second coefficient may be determined based on formula (9).

[0147]

[0148] In formula (9), Q1 represents the first coefficient, Q2 represents the second coefficient, x represents the current driving duration, τ1 represents the first duration threshold, and τ2 represents the second duration threshold.

[0149] S603: The electronic device determines a target road adhesion coefficient based on the first coefficient, the second coefficient, the first road adhesion coefficient, and the second road adhesion coefficient.

[0150] Among them, the first road adhesion coefficient is the road adhesion coefficient estimated based on the first estimation method, and the second road adhesion coefficient is the road adhesion coefficient estimated based on the third estimation method; the first estimation method is related to the acceleration of the wheel; the third estimation method is related to the slip rate.

[0151] The first road adhesion coefficient is a target road adhesion coefficient determined based on the method of S301 to S304, for example, it can be a reference road adhesion coefficient, and the second road adhesion coefficient is a road adhesion coefficient determined based on the method of S401 to S403.

[0152] The electronic device can determine the target road adhesion coefficient based on the following formula (10).

[0153] μ xi =Q1μ xif +Q2μ xir Formula (10);

[0154] In formula (10), μ xi represents the target road adhesion coefficient, Q1 represents the first coefficient, Q2 represents the second coefficient, μ xif Represents the first road adhesion coefficient, μ xir Represents the second road adhesion coefficient.

[0155] In this embodiment, during the transition driving stage, the target road adhesion coefficient is determined by fusing the first estimation method (the estimation method for the starting driving stage) and the third estimation method (the estimation method for the stable driving stage), which is more in line with the driving characteristics of the transition driving stage, and the obtained target road adhesion coefficient is highly accurate.

[0156] Next, the process of the electronic device determining the first coefficient and the second coefficient based on the driving duration in S602 is described.

[0157] In a possible implementation, the process may include but is not limited to the following S6021 to S6023.

[0158] S6021. The electronic device determines a first intermediate value based on a difference between the second duration threshold and the first duration threshold.

[0159] The first intermediate value is the inverse of the difference.

[0160] Among them, the first time threshold is the critical time between the starting driving stage and the transition driving stage; the second time threshold is the critical time between the transition driving stage and the stable driving stage; the second time threshold is greater than the first time threshold.

[0161] The embodiment of the present application does not limit the values of the first duration threshold and the second duration threshold, and can be configured according to actual needs. For example, the first duration threshold can be 3 seconds, and the second duration threshold can be 5 seconds.

[0162] S6021 may be implemented as follows: the electronic device subtracts the first duration threshold from the second duration threshold to obtain a difference, and then calculates a derivative of the difference to obtain a first intermediate value.

[0163] S6022: The electronic device subtracts the third intermediate value from the second intermediate value to determine the difference as the first coefficient.

[0164] The second intermediate value is the product of the first intermediate value and the second duration threshold; the third intermediate value is the product of the first intermediate value and the driving duration.

[0165] S6022 can be implemented as follows: the electronic device first calculates the product of the first intermediate value and the second duration threshold to obtain the second intermediate value, calculates the product of the first intermediate value and the driving duration to obtain the third intermediate value, and then subtracts the difference between the second intermediate value and the third intermediate value to determine it as the first coefficient.

[0166] S6023. The electronic device determines the difference between the third intermediate value and the fourth intermediate value as the second coefficient; the fourth intermediate value is the product of the first intermediate value and the first duration threshold.

[0167] The fourth intermediate value is a product of the first intermediate value and the first duration threshold.

[0168] S6023 can be implemented as follows: the electronic device first calculates the product of the first intermediate value and the first duration threshold to obtain a fourth intermediate value, and then subtracts the difference between the third intermediate value and the fourth intermediate value to determine the second coefficient.

[0169] In this embodiment, the effects of the driving duration, the first duration threshold, and the second duration threshold on the fusion coefficient (the first coefficient and the second coefficient) are taken into consideration when determining the first coefficient and the second coefficient, thereby achieving a smooth transition.

[0170] In another possible implementation, the first coefficient and the second coefficient may also be determined based on empirical values.

[0171] The following describes the process of determining the first duration threshold and the second duration threshold.

[0172] In a possible implementation, the first duration threshold and the second duration threshold may be determined based on empirical values.

[0173] In another possible implementation, determining the first duration threshold and the second duration threshold may include: determining the first duration threshold based on the slip rate; determining the offset value based on the adhesion level of the road surface; and determining the sum of the first duration threshold and the offset value as the first duration threshold.

[0174] The higher the attachment level, the larger the offset value. For example, one attachment level corresponds to one offset value. For example, a low attachment level corresponds to an offset value of 1 second, and a high attachment level corresponds to an offset value of 3 seconds.

[0175] In this embodiment, the second duration threshold is determined based on the offset value, taking into account the influence of the adhesion level of the road surface on the second duration threshold, thereby improving the accuracy.

[0176] Next, the process of the electronic device estimating the target road adhesion coefficient of each wheel of the vehicle on the driving road based on the target estimation method in S203 is described.

[0177] In one possible implementation, reference Figure 7 The process may include but is not limited to the following S701 to S703.

[0178] S701: The electronic device estimates the longitudinal adhesion coefficient of each wheel based on a target estimation method.

[0179] The implementation process may refer to any one of the above-mentioned methods 1 to 3 to determine the longitudinal adhesion coefficient. The detailed descriptions of methods 1 to 3 may be referred to and will not be repeated here.

[0180] S702: When the first condition is met, the electronic device determines a lateral adhesion coefficient based on the lateral acceleration of the vehicle.

[0181] The first condition includes: a steering wheel angle of the vehicle is greater than a steering angle threshold, and a lateral acceleration is greater than a lateral acceleration threshold.

[0182] The values of the angle threshold and the lateral acceleration threshold can be determined according to actual needs and are not limited in the present embodiment. For example, the angle threshold can be 0.05 radians (rad) and the lateral acceleration threshold can be 0.5 meters per second squared (m / s^2).

[0183] S702 may be implemented as follows: when the first condition is met, the electronic device determines the ratio of the lateral acceleration of the vehicle to the acceleration due to gravity as the lateral adhesion coefficient.

[0184] S703: The electronic device determines a target road adhesion coefficient based on the longitudinal adhesion coefficient and the lateral adhesion coefficient of the wheel.

[0185] For example, the electronic device may determine a target road adhesion coefficient based on the elliptical theory of the vehicle's tires.

[0186] For example, the target road adhesion coefficient can be determined based on the following formula (11).

[0187]

[0188] In formula (11), μ f Represents the target road adhesion coefficient, μ xi represents the longitudinal adhesion coefficient, μ y represents the lateral adhesion coefficient.

[0189] In this embodiment, when determining the target road adhesion coefficient, both the longitudinal adhesion coefficient and the lateral adhesion coefficient are considered, which can match driving conditions such as cornering and improve the accuracy of the target road adhesion coefficient in these conditions.

[0190] When the first condition is not met, the longitudinal adhesion coefficient is directly determined as the target road adhesion coefficient.

[0191] Next, the process of determining the current target driving phase of the vehicle by the electronic device based on the driving data of the vehicle in S201 will be described.

[0192] refer to Figure 8 The process may include but is not limited to the following S801 to S804.

[0193] S801. The electronic device obtains the current driving time of the vehicle.

[0194] The implementation of S801 may refer to the description in S601 and will not be described in detail here.

[0195] After obtaining the current driving time of the vehicle, the relationship between the driving time and the first time threshold and the second time threshold is determined.

[0196] The second duration threshold is greater than the first duration threshold.

[0197] If the driving time is less than or equal to the first time threshold, execute the following S802; if the driving time is greater than the first time threshold and less than the second time threshold, execute the following S803; if the driving time is greater than or equal to the second time threshold, execute the following S804.

[0198] S802: If the driving duration is less than or equal to the first duration threshold, the electronic device determines that the target driving phase is a starting driving phase.

[0199] The embodiment of the present application does not limit the value of the first duration threshold, and can be configured according to actual needs. For example, the first duration threshold can be 6 seconds.

[0200] S803: If the driving duration is greater than the first duration threshold and less than the second duration threshold, the electronic device determines that the target driving phase is a transition driving phase.

[0201] The embodiment of the present application does not limit the value of the second duration threshold, and can be configured according to actual needs. For example, the second duration threshold can be 30 seconds.

[0202] S804: If the driving duration is greater than or equal to the second duration threshold, the electronic device determines that the target driving phase is a stable driving phase.

[0203] In this embodiment, the target driving stage is determined based on the driving duration, which is simple and convenient to implement; and the process does not require the participation of sensors, so the cost is low.

[0204] Next, a new energy vehicle is taken as an example, and an embodiment is used as an example to illustrate the estimation process of the road adhesion coefficient of the new energy vehicle.

[0205] Driven by the global demand for clean energy, the electrification of the automotive industry is accelerating. Electric vehicles already command a significant share of the market. Furthermore, due to their simple structure and ease of deployment, new technologies, such as drive-by-wire chassis and in-wheel motors, are emerging. The technological reserves of traditional gasoline-powered vehicles are clearly insufficient to meet the development needs of electric vehicles. Distributed drive technology is the greatest advantage of electric vehicles over gasoline-powered vehicles. Because distributed vehicles have controllable torque per wheel, they exhibit enhanced dynamic characteristics and are more challenging to control, making traditional gasoline-powered vehicle methods inadequate. To achieve distributed drive control in electric vehicles, the status of each wheel must be monitored. The tire-road adhesion coefficient is a key parameter, determining maximum wheel adhesion and playing a crucial role in the design of the vehicle's drive control system.

[0206] Road adhesion coefficient estimation primarily uses the slip slope method. This method derives the vehicle's driving and braking forces based on vehicle acceleration and slope information. The front and rear axle slip rates and vertical forces are then used to calculate the slope between the vehicle's utilization adhesion coefficient and the slip rate. The slope values for various existing road surfaces are then referenced to identify the road surface corresponding to the calculated slope, thereby determining the road adhesion coefficient at that point. This method assumes the vehicle is traveling on a uniform surface with consistent tire material, making it impossible to estimate the road adhesion coefficient for each tire individually. This leads to low estimation accuracy on split and butted surfaces. Furthermore, slip rate errors are large during the vehicle's starting phase, leading to distorted slip slopes and increased errors in starting estimation. Finally, the estimation is based on tire driving and braking forces, but it fails to account for the influence of tire lateral forces, resulting in underestimation under cornering conditions.

[0207] This embodiment uses an extended state estimator based on a single-wheel vehicle dynamics model to determine the adhesion coefficient of each wheel. To address the sudden change in the vehicle's slip rate during takeoff, a wheel acceleration threshold monitoring method is used to determine the road adhesion coefficient at takeoff. After the vehicle takes off, the recursive least squares (RLS) method is combined with a tire model to determine the road adhesion coefficient after takeoff. An information fusion method is then used to achieve a smooth transition between the pre- and post-takeoff road adhesion coefficients. Finally, to address the issue of underestimating the road adhesion coefficient during cornering, lateral acceleration is used to compensate for the road adhesion coefficient. This approach significantly improves the accuracy of the road adhesion coefficient estimation during daily driving conditions, particularly during start-up and cornering.

[0208] The technical effects of this embodiment include: Based on the vehicle's single-wheel dynamics model, an extended state estimator is used to obtain the utilized adhesion coefficient of each wheel. To address the sudden change in slip rate during vehicle launch, a wheel acceleration threshold monitoring method is used to accurately estimate the road adhesion coefficient at launch. After launch, the RLS method combined with the tire model is used for continuous measurement. A unique information fusion method is used to achieve a smooth transition between the road adhesion coefficient before and after launch. Lateral acceleration is also used to compensate for the road adhesion coefficient during vehicle cornering, enabling the estimation of each tire's adhesion coefficient independently, maintaining high accuracy even on split and intersecting roads.

[0209] This embodiment effectively addresses numerous issues with existing road adhesion coefficient estimation methods in situations such as split / jointed roads, vehicle start-up, and cornering. It significantly improves the accuracy of road adhesion coefficient estimation in everyday driving conditions, particularly during start-up and cornering. This is of great significance for optimizing distributed drive control in electric vehicles and improving vehicle dynamic characteristics and safety.

[0210] This embodiment addresses the problem of estimating the tire-road adhesion coefficient of distributed drive electric vehicles under dynamic conditions and proposes a wheel-by-wheel independent estimation method based on a single-wheel dynamics model. This method breaks through the assumption of uniform road surface adhesion coefficients and, based on the Extended State Observer (ESO) theory, achieves real-time independent estimation of the four-wheel road adhesion coefficients through a fusion architecture of wheel acceleration monitoring, recursive least squares parameter identification, and lateral force compensation. This solves three major challenges: split / jointed road surfaces, starting slip distortion, and lateral force coupling in steering conditions. It can more accurately and reliably estimate the single-wheel road adhesion coefficient of distributed drive vehicles, providing a more accurate state reference for the vehicle control system, thereby improving various vehicle performance characteristics such as handling stability, comfort, and safety.

[0211] The process may include but is not limited to the following steps 1 to 3.

[0212] Step 1: Utilize the estimation of adhesion coefficient.

[0213] Step 1.1. Calculate the vertical load on a single wheel of the vehicle.

[0214] Receive the vehicle longitudinal acceleration a uploaded by the vehicle chassis x , lateral acceleration a y , yaw angular velocity w v , combined with the vehicle mass m, the vehicle's front wheelbase L f , vehicle rear wheelbase L r , vehicle center of mass height h g , gravitational acceleration g, vehicle wheelbase B, and the vertical load on each wheel are obtained using the above formula (5).

[0215] Step 1.2: Construction of extended state observer.

[0216] According to the vehicle single wheel dynamics equation (the above formula (6)), ignoring the tire rolling resistance:

[0217] The adhesion coefficient is determined based on the above formula (7).

[0218] Based on the above, the vehicle single-wheel dynamic model can be expressed as the following state space equation formula (12).

[0219]

[0220] Define the nonlinear link f(x1, t) as the extended state variable x2, and formula (12) becomes the following formula (13)

[0221]

[0222] Among them, x1, x2, b, and u in formula (13) can be determined according to the following formula (14).

[0223]

[0224] Expanding the above formula, we can obtain a typical first-order extended state observer, refer to formula (14).

[0225]

[0226] In formula (14), z1 and z2 are the estimated values of x1 and x2, respectively; a1, a2, and δ are the adjustable gain coefficients of the extended state observer; and fal is a typical nonlinear feedback structure. Based on the above, the estimated value of the utilization adhesion coefficient of each wheel can be obtained as the above formula (8).

[0227] Step 2: Calculation of road adhesion coefficient.

[0228] The calculation of the road adhesion coefficient is divided into two parts: 1. At the start (equivalent to the aforementioned starting driving phase); 2. After the start (equivalent to the aforementioned stable driving phase). This is because the tire slip rate changes abruptly during the start, resulting in a significant deviation from the true value. Therefore, the method of using the tire slip rate to derive the road adhesion coefficient is no longer applicable. Therefore, during the start, the road adhesion coefficient is determined using wheel acceleration detection. After the start, the tire slip rate gradually stabilizes, and the tire model is used to identify the road adhesion coefficient using the RLS algorithm. Finally, an information fusion method is used to achieve a smooth transition between the start and post-start adhesion coefficients.

[0229] Step 2.1: Calculate the road adhesion coefficient at start.

[0230] The road adhesion coefficient is usually in the range of 0.2-0.8, so the wheel acceleration threshold (equivalent to the first threshold mentioned above) is selected

[0231] when When , it is considered that the road adhesion is sufficient, and the road adhesion coefficient is given a default constant value of 0.8 (equivalent to the above reference adhesion coefficient); if It is considered that the adhesion force has exceeded the adhesion limit, and the adhesion coefficient is close to the utilization adhesion coefficient at this moment. The utilization adhesion coefficient at the current moment is taken as the road adhesion coefficient.

[0232] Step 2.2: Calculate the road adhesion coefficient after starting.

[0233] After starting, the wheel slip rate is relatively stable. The slip rate calculation formula can refer to the above formula (1).

[0234] After obtaining the slip rate and the utilization adhesion coefficient of each wheel, a relatively simple and parameter-less classic tire model formula is used to describe the road adhesion coefficient. The classic tire model formula can refer to the above formula (3).

[0235] Based on this empirical formula, the recursive least squares (RLS) method is used to find μ ip First, the empirical formula is transformed into a linear form suitable for estimation, referring to the following formula (15).

[0236]

[0237] In formula (15), A = 2μ ip s ip , B=s ip 2 .

[0238] The recursive least squares formula can refer to the following formulas (16) to (18).

[0239] The calculation of the gain vector γ can refer to the following formula (16).

[0240]

[0241] The update of the value to be identified θ can refer to the following formula (17).

[0242]

[0243] The update of the covariance matrix P(k) can refer to the following formula (18).

[0244]

[0245] In formulas (16) to (18), ρ is the forgetting factor, which is used to update the road adhesion coefficient value at all times to cope with sudden changes in road conditions; y(k+1) is the measurement output at the moment; and I is the unit matrix. The value of is obtained based on the following formula (19).

[0246]

[0247] In formula (19), A = 2μ ip s ip , B=s ip 2 .

[0248] Based on the above, the road adhesion coefficient μ can be obtained in real time xi Estimated value.

[0249] Step 2.3: Fusion of road adhesion coefficients during and after starting.

[0250] Because the acceleration threshold method is used to calculate the road adhesion coefficient during vehicle launch, there is a certain error between the estimated value and the actual value. Furthermore, the estimated value at launch, as input, can affect the convergence speed and accuracy of the subsequent RLS algorithm. Therefore, this embodiment proposes a time-delayed method to fuse the road adhesion coefficients at launch and after launch, achieving a smooth transition between the two states.

[0251] Define the time coefficients τ1, τ2 (τ1<τ2), and the fusion estimation value of the road adhesion coefficient can refer to the above formula (10).

[0252] The expressions of Q1 and Q2 are expressed by the following piecewise function f(x). The expression of f(x) can refer to the following formula (20).

[0253]

[0254] In formula (20), f(x) represents a piecewise function, Q1 and Q2 represent coefficients in formula (10), τ1 represents a first duration threshold, and τ2 represents a second duration threshold.

[0255] Step 3: Compensation of lateral adhesion coefficient.

[0256] The road adhesion coefficient estimated using longitudinal force is relatively accurate when the vehicle is traveling straight or making shallow turns. However, when the vehicle is in a sharp turn, due to the limitations of the tire adhesion ellipse, the lateral and longitudinal forces are deeply coupled. Estimating only the longitudinal force will result in an underestimation of the adhesion coefficient, limiting the vehicle's actual capabilities. Therefore, the overall lateral adhesion coefficient of the vehicle is calculated, and then the road adhesion coefficient is compensated based on the adhesion ellipse to improve estimation accuracy in cornering conditions.

[0257] Step 3.1: Steering state recognition.

[0258] (1) Left turn: When the vehicle's left-turn steering wheel angle is greater than 0.05 rad and the lateral acceleration is greater than 0.5 m / s^2, the vehicle is judged to be in a large left turn state and the lateral adhesion coefficient calculation is enabled.

[0259] (2) Right turn: Similarly, when the vehicle's right-turn steering wheel angle is greater than 0.05 rad and the lateral acceleration is greater than 0.5 m / s^2, the vehicle is judged to be in a large right turn state and the lateral adhesion coefficient calculation is enabled.

[0260] (3) Straight driving: When the vehicle steering wheel angle is less than 0.05 rad and the lateral acceleration is less than 0.5 m / s^2, the vehicle is judged to be in a straight driving state and the lateral adhesion coefficient is not calculated.

[0261] Step 3.2: Compensation of lateral adhesion coefficient.

[0262] After determining the vehicle's large-scale turning condition, calculate the vehicle's lateral adhesion coefficient.

[0263] According to the vehicle tire adhesion ellipse theory, the final road adhesion coefficient estimation value is obtained.

[0264] refer to Figure 9 As shown in the content, the process of determining the adhesion coefficient of each wheel may include but is not limited to the following S901 to S909.

[0265] S901. Calculation of vehicle-borne vertical loads.

[0266] S902: Convert center of mass velocity and calculate wheel slip rate.

[0267] S903: Calculate based on ESO using adhesion coefficient.

[0268] S904: Calculate the adhesion coefficient before starting.

[0269] S905: Calculate the adhesion coefficient after starting.

[0270] S906: Fusion of adhesion coefficients before and after starting.

[0271] S907: Identify wheel turning conditions.

[0272] S908: Calculate the lateral adhesion coefficient and perform adhesion coefficient compensation.

[0273] S909: Output the final adhesion coefficient estimate.

[0274] In a second aspect, the present application provides an estimation device for a road adhesion coefficient, such as Figure 10 As shown, the device 100 for estimating a road adhesion coefficient includes a first determining unit 1001 , a second determining unit 1002 and an estimating unit 1003 .

[0275] in:

[0276] A first determining unit 1001 is configured to determine a current target driving phase of the vehicle based on the vehicle's driving data, where the target driving phase refers to a change in the vehicle's motion state;

[0277] a second determining unit 1002 for determining a target estimation method for estimating the road adhesion coefficient from among a plurality of estimation methods based on the target driving phase;

[0278] The estimation unit 1003 is configured to estimate a target road adhesion coefficient of each wheel of the vehicle on the road surface based on a target estimation method.

[0279] In some embodiments, the second determination unit 1002 is also used to: when the target driving stage includes a starting driving stage, determine that the target estimation method includes a first estimation method; the first estimation method is related to the acceleration of the wheel; when the target driving stage includes a transition driving stage, determine that the target estimation method includes a second estimation method; the second estimation method is related to the wheel acceleration and the slip rate; when the target driving stage includes a stable driving stage, determine that the target estimation method includes a third estimation method; the third estimation method is related to the slip rate.

[0280] In some embodiments, the estimation unit 1003 is also used to: when the target driving phase includes a transition driving phase, perform: determining the current driving time of the vehicle; determining the first coefficient and the second coefficient based on the driving time; determining the target road adhesion coefficient based on the first coefficient, the second coefficient, the first road adhesion coefficient, and the second road adhesion coefficient; wherein the first road adhesion coefficient is a road adhesion coefficient estimated based on the first estimation method, and the second road adhesion coefficient is a road adhesion coefficient estimated based on the third estimation method; the first estimation method is related to the acceleration of the wheel; and the third estimation method is related to the slip rate.

[0281] In some embodiments, the estimation unit 1003 is also used to: determine the first intermediate value based on the difference between the second duration threshold and the first duration threshold; the first intermediate value is the reciprocal of the difference; the difference between the second intermediate value and the third intermediate value is determined as the first coefficient; the second intermediate value is the product of the first intermediate value and the second duration threshold; the third intermediate value is the product of the first intermediate value and the driving duration; the difference between the third intermediate value and the fourth intermediate value is determined as the second coefficient; the fourth intermediate value is the product of the first intermediate value and the first duration threshold; wherein the first duration threshold is the critical duration between the starting driving stage and the transition driving stage; the second duration threshold is the critical duration between the transition driving stage and the stable driving stage; the second duration threshold is greater than the first duration threshold.

[0282] In some embodiments, the estimation unit 1003 is further used to: determine a first duration threshold based on the slip rate; determine an offset value based on the adhesion level of the road surface; the higher the adhesion level, the larger the offset value; and determine the sum of the first duration threshold and the offset value as the first duration threshold.

[0283] In some embodiments, the estimation unit 1003 is further used to: when the target driving phase includes a starting driving phase, for each wheel in the vehicle, perform: obtaining the longitudinal velocity of the wheel; determining the longitudinal acceleration of the wheel based on the longitudinal velocity of the wheel; when the longitudinal acceleration is less than or equal to a first threshold, determining the target road adhesion coefficient of the wheel as a reference adhesion coefficient; the first threshold is used to characterize whether the wheel is slipping; when the longitudinal acceleration is greater than the first threshold, determining the target road adhesion coefficient of the wheel as the utilized adhesion coefficient of the wheel.

[0284] In some embodiments, the estimation unit 1003 is also used to: when the target driving phase includes a stable driving phase, for each wheel in the vehicle, perform: determining the slip rate of the wheel based on the longitudinal wheel speed and longitudinal angular velocity of the wheel; determining the utilized adhesion coefficient of the wheel based on the vertical load of the wheel; determining a first relationship based on the slip rate of the wheel, the utilized adhesion coefficient of the wheel and the tire model; the first relationship is the relationship between the adhesion coefficient of the wheel and the slip rate; and determining the target road adhesion coefficient based on the first relationship.

[0285] In some embodiments, the estimation unit 1003 is further used to: determine the vertical load of the wheel based on the vehicle's driving data and the vehicle's structural data; and process the vertical load of the wheel through an extended state observer to obtain the utilization adhesion coefficient of the wheel.

[0286] In some embodiments, the estimation unit 1003 is further used to: estimate the longitudinal adhesion coefficient of each wheel based on a target estimation method; determine the lateral adhesion coefficient based on the lateral acceleration of the vehicle when a first condition is met; the first condition includes: the steering wheel angle of the vehicle is greater than the angle threshold, and the lateral acceleration is greater than the lateral acceleration threshold; determine the target road adhesion coefficient based on the longitudinal adhesion coefficient and the lateral adhesion coefficient of the wheel.

[0287] In some embodiments, the first determination unit 1001 is also used to: obtain the current driving time of the vehicle; if the driving time is less than or equal to the first time threshold, the target driving stage is determined to be the starting driving stage; if the driving time is greater than the first time threshold and less than the second time threshold, the target driving stage is determined to be the transition driving stage; the second time threshold is greater than the first time threshold; if the driving time is greater than or equal to the second time threshold, the target driving stage is determined to be the stable driving stage.

[0288] It should be noted that the road adhesion coefficient estimation device provided in the embodiment of the present application includes the various units included, which can be implemented by a processor in an electronic device; of course, it can also be implemented by a specific logic circuit; in the implementation process, the processor can be a central processing unit (CPU), a microprocessor (MPU), a digital signal processor (DSP) or a field programmable gate array (FPGA), etc.

[0289] The description of the above device embodiment is similar to the description of the above method embodiment and has similar beneficial effects as the method embodiment. For technical details not disclosed in the device embodiment of this application, please refer to the description of the method embodiment of this application for understanding.

[0290] It should be noted that, in the embodiment of the present application, if the above-mentioned vehicle driving control method is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the relevant technology can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the methods of each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM), a magnetic disk or an optical disk. In this way, the embodiment of the present application is not limited to any specific combination of hardware and software.

[0291] In a third aspect, an embodiment of the present application provides an electronic device that can implement the method for estimating the road adhesion coefficient provided in the first aspect.

[0292] In one example, reference Figure 11 As shown, electronic device 110 includes: a processor 1101, at least one communication bus 1102, a user interface 1103, at least one external communication interface 1104, and a memory 1105. Communication line 1102 is configured to enable communication between these components. User interface 1103 may include a display screen, and external communication interface 1104 may include a standard wired interface and a wireless interface.

[0293] The memory 1105 is configured to store instructions and applications executable by the processor 1101, and can also cache data to be processed or processed by the processor 1101 and various modules in the electronic device (for example, image data, audio data, voice communication data, and video communication data), which can be implemented through flash memory (FLASH) or random access memory (RAM).

[0294] In some embodiments, an embodiment of the present application provides a vehicle, including a processor and a memory, wherein a computer program or instructions are stored in the memory, and when the computer program or instructions are executed by the processor, the method provided in the first aspect is implemented.

[0295] In a fourth aspect, an embodiment of the present application provides a storage medium, that is, a computer-readable storage medium, on which a computer program or instruction is stored. When the computer program or instruction is executed by a processor, the steps in any one of the road adhesion coefficient estimation methods provided in the first aspect of the above-mentioned embodiment are implemented.

[0296] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes a computer program or instructions. When the computer program or instructions are executed by a processor, the steps in any one of the road adhesion coefficient estimation methods provided in the first aspect of the above-mentioned embodiment are implemented.

[0297] It should be noted that the descriptions of the above embodiments of the storage medium, device, apparatus, and program product are similar to the descriptions of the above method embodiments and have similar beneficial effects as the method embodiments. For technical details not disclosed in the embodiments of the storage medium, device, apparatus, and program product of this application, please refer to the description of the method embodiments of this application for understanding.

[0298] It should be understood that “one embodiment” or “an embodiment” mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, “in one embodiment” or “in some embodiments” appearing throughout the specification do not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application. The above-mentioned serial numbers of the embodiments of the present application are for description only and do not represent the advantages and disadvantages of the embodiments.

[0299] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0300] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of units is merely a logical function division. In actual implementation, there may be other division methods, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0301] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed across multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0302] In addition, all functional units in the embodiments of the present application can be integrated into one processing unit, or each unit can be a separate unit, or two or more units can be integrated into one unit; the above-mentioned integrated units can be implemented in the form of hardware or in the form of hardware plus software functional units.

[0303] Those skilled in the art will understand that all or part of the steps of implementing the above-mentioned method embodiment can be completed by hardware related to program instructions, and the aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above-mentioned method embodiment; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM), magnetic disks or optical disks, and other media that can store program codes.

[0304] Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the relevant technology can be embodied in the form of a software product, which is stored in a storage medium and includes a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods of each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROMs, magnetic disks, or optical disks.

[0305] The above are only implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the protection scope of the present application.

Claims

1. A method for estimating a road adhesion coefficient, characterized in that: The method comprises: determining a current target driving phase of the vehicle based on driving data of the vehicle, wherein the target driving phase is used to indicate a change in a motion state of the vehicle; determining a target estimation method for estimating a road adhesion coefficient from among a plurality of estimation methods based on the target driving phase; A target road adhesion coefficient of each wheel of the vehicle on a driving road is estimated based on the target estimation method.

2. The method according to claim 1, characterized in that The determining of a target estimation method for estimating the road adhesion coefficient from a plurality of estimation methods based on the target driving phase includes: In a case where the target driving phase includes a starting driving phase, determining that the target estimation method includes a first estimation method; the first estimation method is related to the acceleration of the wheel; In a case where the target driving phase includes a transition driving phase, determining that the target estimation method includes a second estimation method; the second estimation method is related to the wheel acceleration and the slip rate; In a case where the target driving phase includes a stable driving phase, determining the target estimation method includes a third estimation method; the third estimation method is related to the slip ratio.

3. The method according to claim 1 or 2, characterized in that In a case where the target driving phase includes a transition driving phase, estimating a target road adhesion coefficient of each wheel of the vehicle on the driving road based on the target estimation method includes: Determining the current driving time of the vehicle; determining a first coefficient and a second coefficient based on the driving duration; determining the target road adhesion coefficient based on the first coefficient, the second coefficient, the first road adhesion coefficient, and the second road adhesion coefficient; Among them, the first road adhesion coefficient is a road adhesion coefficient estimated based on a first estimation method, and the second road adhesion coefficient is a road adhesion coefficient estimated based on a third estimation method; the first estimation method is related to the acceleration of the wheel; and the third estimation method is related to the slip rate.

4. The method according to claim 3, characterized in that The determining of the first coefficient and the second coefficient based on the driving duration includes: Determining a first intermediate value based on a difference between the second duration threshold and the first duration threshold, wherein the first intermediate value is a reciprocal of the difference; The difference between the second intermediate value and the third intermediate value is determined as the first coefficient; the second intermediate value is the product of the first intermediate value and the second duration threshold; the third intermediate value is the product of the first intermediate value and the driving duration; Determine the second coefficient by subtracting the fourth intermediate value from the third intermediate value; the fourth intermediate value is the product of the first intermediate value and the first duration threshold; Among them, the first time threshold is the critical time between the starting driving stage and the transition driving stage; the second time threshold is the critical time between the transition driving stage and the stable driving stage; the second time threshold is greater than the first time threshold.

5. The method according to claim 4, characterized in that The method further comprises: determining a first duration threshold based on the slip ratio; determining an offset value based on the adhesion level of the road surface; the higher the adhesion level, the greater the offset value; The sum of the first duration threshold and the offset value is determined as the first duration threshold.

6. The method according to claim 1, characterized in that In a case where the target driving phase includes a starting driving phase, estimating a target road adhesion coefficient of each wheel of the vehicle on the driving road based on the target estimation method includes: For each wheel in the vehicle, execute: obtaining the longitudinal velocity of the wheel; determining a longitudinal acceleration of the wheel based on the longitudinal velocity of the wheel; determining the target road adhesion coefficient of the wheel as a reference adhesion coefficient when the longitudinal acceleration is less than or equal to a first threshold value, wherein the first threshold value is used to indicate whether the wheel is slipping; When the longitudinal acceleration is greater than the first threshold, the target road adhesion coefficient of the wheel is determined as the utilized adhesion coefficient of the wheel.

7. The method according to claim 1, characterized in that In a case where the target driving phase includes a stable driving phase, estimating a target road adhesion coefficient of each wheel of the vehicle on the driving road based on the target estimation method includes: For each wheel in the vehicle, execute: determining a slip ratio of the wheel based on the longitudinal wheel speed and the longitudinal angular velocity of the wheel; determining a first relationship based on the slip rate of the wheel, the utilized adhesion coefficient of the wheel, and a tire model; the first relationship being a relationship between the adhesion coefficient and the slip rate of the wheel; Based on the first relationship, the target road adhesion coefficient is determined.

8. The method according to claim 6 or 7, characterized in that The method further comprises: determining a vertical load of the wheel based on the driving data of the vehicle and the structural data of the vehicle; The vertical load of the wheel is processed by an extended state observer to obtain the utilization adhesion coefficient of the wheel.

9. The method according to claim 1 or 2, characterized in that Estimating a target road adhesion coefficient of each wheel of the vehicle on a driving road surface based on the target estimation method includes: estimating a longitudinal adhesion coefficient of each wheel based on the target estimation method; determining a lateral adhesion coefficient based on the lateral acceleration of the vehicle when a first condition is satisfied; the first condition comprising: a steering wheel angle of the vehicle being greater than a steering angle threshold and a lateral acceleration being greater than a lateral acceleration threshold; The target road adhesion coefficient is determined based on the longitudinal adhesion coefficient and the lateral adhesion coefficient of the wheel.

10. The method according to claim 1 or 2, characterized in that: Determining the current target driving phase of the vehicle based on the driving data of the vehicle includes: Obtaining the current driving time of the vehicle; If the driving duration is less than or equal to a first duration threshold, determining that the target driving phase is a starting driving phase; If the driving duration is greater than the first duration threshold and less than a second duration threshold, determining that the target driving phase is a transition driving phase; and the second duration threshold is greater than the first duration threshold; If the driving duration is greater than or equal to the second duration threshold, the target driving phase is determined to be a stable driving phase.

11. A device for estimating a road adhesion coefficient, characterized in that: The device comprises: a first determining unit, configured to determine a current target driving phase of the vehicle based on driving data of the vehicle, wherein the target driving phase is used to indicate a change in a motion state of the vehicle; a second determining unit, configured to determine a target estimation method for estimating a road adhesion coefficient from among a plurality of estimation methods based on the target driving phase; An estimating unit is used to estimate a target road adhesion coefficient of each wheel of the vehicle on a driving road based on the target estimation method.

12. A vehicle device, characterized in that: The vehicle equipment includes a memory and a processor, the memory is used to store computer programs or instructions, and when the computer program or instructions are executed by the processor, the method according to any one of claims 1 to 10 is implemented.

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