Vehicle speed estimation method, vehicle speed estimation device and vehicle

Abstract

The invention provides a vehicle speed estimation method and device and a vehicle, and the method relates to the field of vehicles, and comprises the steps: obtaining the wheel center speed of each wheel in the vehicle, the longitudinal acceleration of the vehicle and the driving state information of the vehicle; wherein the driving state information is used for representing whether the vehicle is in a slip state; obtaining an initial longitudinal speed of the vehicle based on the longitudinal acceleration; determining a first weight coefficient of each wheel and a second weight coefficient of the vehicle based on the driving state information; and determining a target longitudinal speed of the vehicle based on the wheel center speed, the first weight coefficient, the initial longitudinal speed and the second weight coefficient. According to the method, the accuracy of the estimated longitudinal vehicle speed can be improved, so that the safety of the vehicle is improved.

Description

Technical Field

[0001] The present application relates to the field of vehicles, and more specifically, to a vehicle speed estimation method, an estimation device and a vehicle in the field of vehicles. Background Art

[0002] The longitudinal speed of a vehicle refers to the speed component of the vehicle in the forward or backward direction during driving. The accuracy of the longitudinal speed is crucial to the safety control of the vehicle. However, in the prior art, when calculating the longitudinal speed of a vehicle, it is easily affected by interference factors (for example, signal noise, zero drift, wheel slip rate, wheel rolling radius and other interference factors), resulting in low calculation accuracy of the longitudinal speed of the vehicle.

[0003] Therefore, how to improve the accuracy of the estimated longitudinal vehicle speed, thereby improving the safety of the vehicle, is a technical problem that needs to be solved at present. Summary of the invention

[0004] The present application provides a vehicle speed estimation method, an estimation device and a vehicle. The method can determine a first weight coefficient and a second weight coefficient according to the vehicle's driving state information (whether the vehicle is in a slip state); determine the vehicle's longitudinal speed according to the wheel center speed, the first weight coefficient, the initial longitudinal speed and the second weight coefficient; ensure that the influence of the vehicle slip on the longitudinal speed can be taken into account, improve the accuracy of the longitudinal speed, and thus improve the safety of the vehicle.

[0005] In a first aspect, a method for estimating vehicle speed is provided, the method comprising:

[0006] Obtaining the wheel center speed of each wheel in the vehicle, the longitudinal acceleration of the vehicle and the driving state information of the vehicle; wherein the driving state information is used to indicate whether the vehicle is in a slip state;

[0007] Based on the longitudinal acceleration, the initial longitudinal speed of the vehicle is obtained;

[0008] Based on the driving state information, determine a first weight coefficient of each wheel and a second weight coefficient of the vehicle; wherein the first weight coefficient is used to represent the weight coefficient corresponding to the wheel center speed of each wheel in the vehicle, and the second weight coefficient is used to represent the weight coefficient corresponding to the initial longitudinal vehicle speed;

[0009] A target longitudinal vehicle speed of the vehicle is determined based on the wheel center speed, the first weight coefficient, the initial longitudinal vehicle speed and the second weight coefficient.

[0010] It should be noted that when the vehicle's driving state information is different (the vehicle is in a slip state or the vehicle is not in a slip state), the credibility of the vehicle's wheel center speed and the vehicle's longitudinal acceleration is different; wherein the credibility is used to indicate the reliability and accuracy of the data.

[0011] In the embodiment of the present application, the first weight coefficient of each wheel and the second weight coefficient of the vehicle are determined according to the driving state information of the vehicle; the target longitudinal speed of the vehicle is determined according to the wheel center speed, the first weight coefficient, the initial longitudinal speed and the second weight coefficient. Since the credibility of the wheel center speed and the longitudinal acceleration of the vehicle is different when the driving state information of the vehicle is different; therefore, the first weight coefficient and the second weight coefficient are determined according to the driving state information of the vehicle; it is ensured that the influence of the driving state information of the vehicle on the wheel center speed and the longitudinal acceleration can be taken into account, that is, it is ensured that the influence of the slip state of the vehicle on the wheel center speed and the longitudinal acceleration of the vehicle can be taken into account. Compared with the prior art that directly determines the longitudinal speed of the vehicle according to the wheel center speed and / or the longitudinal acceleration, this solution takes into account the influence of the vehicle slip situation on the relevant measurement data of the wheel center speed and the longitudinal acceleration of the vehicle, and therefore, a more accurate target longitudinal speed can be calculated.

[0012] Furthermore, since the longitudinal vehicle speed is the basic input of the vehicle dynamics control system, it can be applied to the vehicle's anti-lock braking system, traction control system, electronic stability control system and adaptive cruise control to ensure the stability and safety of the vehicle during driving; therefore, the present solution can obtain a more accurate target longitudinal vehicle speed, and use the more accurate target longitudinal vehicle speed as the basic input, which is applied to the control system of the above-mentioned vehicle, thereby effectively improving the safety and stability of the vehicle.

[0013] In combination with the first aspect, in some implementations of the first aspect, determining a first weight coefficient of each wheel and a second weight coefficient of the vehicle based on the driving state information includes:

[0014] If the driving state information indicates that the vehicle is in a slipping state, determining a first preset value as a first weight coefficient, and determining a second preset value as a second weight coefficient;

[0015] If the driving state information indicates that the vehicle is not in a slip state, determining a first weight coefficient and a second weight coefficient based on a first parameter of the vehicle;

[0016] The first parameter includes: the road adhesion coefficient of the vehicle's current road condition, the vehicle's current actual speed and the current acceleration change rate.

[0017] Exemplarily, the first preset value may be a zero value.

[0018] In the embodiment of the present application, if the vehicle is in a slipping state, that is, the vehicle is in a skidding state, the wheel center speed of the vehicle is in a completely untrustworthy state; therefore, the first preset value (for example, zero value) is determined as the first weight coefficient, and the second preset value is determined as the second weight coefficient. If the vehicle is not in a slipping state, the credibility of the wheel center speed of the vehicle and the longitudinal acceleration will be affected by the slip rate of the vehicle; therefore, the first weight coefficient and the second weight coefficient of the vehicle are determined according to the first parameter; it is ensured that the first weight coefficient and the second weight coefficient can be determined in different ways according to the driving state information of the vehicle and taking into account the slip rate of the vehicle.

[0019] In combination with the first aspect and the above implementations, in some implementations of the first aspect, determining the first weight coefficient and the second weight coefficient based on the first parameter of the vehicle includes:

[0020] Determining an initial first weight coefficient and an initial second weight coefficient based on a road adhesion coefficient;

[0021] Determining a first adjustment amount corresponding to an initial first weight coefficient and a second adjustment amount corresponding to an initial second weight coefficient based on a current actual vehicle speed and a current acceleration change rate;

[0022] The initial first weight coefficient is adjusted based on the first adjustment amount to obtain the first weight coefficient, and the initial second weight coefficient is adjusted based on the second adjustment amount to obtain the second weight coefficient.

[0023] In the embodiment of the present application, since the slip rate of the vehicle is different when the road adhesion coefficient is different, that is, the risk of skidding of the vehicle is different; therefore, different road adhesion coefficients have different effects on the credibility of the wheel center speed and the credibility of the longitudinal acceleration of the vehicle. The weight coefficient is initially set according to the road adhesion coefficient to obtain the initial first weight coefficient and the initial second weight coefficient to ensure that the influence of the road adhesion coefficient can be taken into account. Adjustments are made on the basis of the initial first weight coefficient and the initial second weight coefficient to obtain the first weight coefficient and the second weight coefficient to ensure that the influence of multiple factors such as the actual vehicle speed and the acceleration change rate of the vehicle on the first weight coefficient and the second weight coefficient are taken into account at the same time.

[0024] In combination with the first aspect and the above implementations, in some implementations of the first aspect, determining the first weight coefficient and the second weight coefficient based on the first parameter of the vehicle includes:

[0025] Determine a first weight coefficient based on a first parameter of the vehicle and a first mapping relationship; wherein the first weight coefficient in the first mapping relationship is positively correlated with a road adhesion coefficient, the first weight coefficient is negatively correlated with an actual vehicle speed, and the first weight coefficient is negatively correlated with an acceleration change rate of the vehicle;

[0026] Based on the first parameter of the vehicle and the second mapping relationship, a second weight coefficient is determined; wherein, in the second mapping relationship, the second weight coefficient is negatively correlated with the road adhesion coefficient, the second weight coefficient is positively correlated with the actual speed of the vehicle, and the second weight coefficient is positively correlated with the acceleration change rate of the vehicle.

[0027] In combination with the first aspect and the above implementations, in some implementations of the first aspect, determining the target longitudinal speed of the vehicle based on the wheel center speed, the first weight coefficient, the initial longitudinal speed and the second weight coefficient includes:

[0028] Determine a first value corresponding to each wheel based on the wheel center speed and the first weight coefficient; determine a second value based on the initial longitudinal vehicle speed and the second weight coefficient;

[0029] The sum of the first value and the second value is determined as a third value; the sum of the first weight coefficient and the second weight coefficient of each wheel is determined as a fourth value;

[0030] The ratio of the third value to the fourth value is determined as the target longitudinal vehicle speed.

[0031] In the embodiment of the present application, since the first weight coefficient is the weight coefficient corresponding to the wheel center speed, and the second weight coefficient is the weight coefficient of the initial longitudinal vehicle speed, the first value corresponding to the weighted wheel center speed is obtained based on the wheel center speed and the first weight coefficient, and the second value corresponding to the weighted initial longitudinal vehicle speed is obtained based on the initial longitudinal vehicle speed and the second weight coefficient. The sum of the first value and the second value is determined as the third value; the ratio of the third value to the fourth value is determined as the target longitudinal vehicle speed, ensuring that the target longitudinal vehicle speed can be calculated based on the wheel center speed, the first weight coefficient, the initial longitudinal vehicle speed and the second weight coefficient.

[0032] In combination with the first aspect and the above implementations, in some implementations of the first aspect, the following further includes:

[0033] determining a correction factor for each wheel based on a slip rate of the vehicle and / or a wheel radius of each wheel;

[0034] Get the wheel center speed of each wheel in the vehicle, including:

[0035] Based on the third parameter and the correction coefficient, the wheel center speed of each wheel is determined; wherein the third parameter includes the wheelbase of the vehicle, the wheel angle of each wheel, the yaw angular velocity of the vehicle, and the wheel linear velocity of each wheel.

[0036] In an embodiment of the present application, the wheel center speed of each wheel is determined based on the third parameter and the correction coefficient. Since the correction coefficient is obtained based on the slip rate and / or wheel radius of the vehicle, it is ensured that when calculating the wheel center speed, the error caused by the slip rate can be compensated and the wheel radius error can be corrected; thereby ensuring that a more accurate wheel center speed can be obtained, and a more accurate target longitudinal vehicle speed can be obtained based on the more accurate wheel center speed.

[0037] In combination with the first aspect and the above implementations, in some implementations of the first aspect, obtaining driving state information of the vehicle includes:

[0038] Determining whether each wheel is in a slip state based on the wheel center speed of each wheel and / or the wheel center acceleration of each wheel;

[0039] If all wheels in the vehicle are in a slipping state, determining that the driving state information indicates that the vehicle is in a slipping state;

[0040] If all wheels in the vehicle are not in a slipping state, it is determined that the driving state information indicates that the vehicle is not in a slipping state.

[0041] In an embodiment of the present application, the slip state of the vehicle is determined based on the slip state of each wheel, ensuring that the slip state of the vehicle can be judged based on the basic parameters of the wheel (wheel center speed or wheel center acceleration), thereby determining the vehicle's driving state information.

[0042] In combination with the first aspect and the above implementations, in some implementations of the first aspect, obtaining driving state information of the vehicle includes:

[0043] Based on the working condition of the vehicle, determine the target wheel among the wheels; wherein the working condition includes the braking working condition and the driving working condition of the vehicle, and the target wheel is the wheel with the largest wheel center speed among the wheels, or the wheel with the smallest wheel center speed among the wheels;

[0044] If the target wheel is in a slipping state, it is determined that the driving state information indicates that the vehicle is in a slipping state.

[0045] In the embodiment of the present application, the slip state of the vehicle is determined according to the slip state of the target wheel; that is, when it is determined that the target wheel is in a slip state, the vehicle is determined to be in a slip state. Compared with determining the slip state of the vehicle according to the slip state of each wheel, this solution performs calculations according to the slip state of the target wheel, which has a smaller amount of calculations and can effectively improve the efficiency of determining the slip state of the vehicle.

[0046] In combination with the first aspect and the above implementations, in some implementations of the first aspect, obtaining the initial longitudinal speed of the vehicle based on the longitudinal acceleration includes:

[0047] Determining an initial longitudinal speed of the vehicle based on the second parameter and the longitudinal acceleration;

[0048] Among them, the second parameter includes the longitudinal speed of the vehicle at a first moment, the longitudinal acceleration of the vehicle and a preset time period; the first moment is the moment before the current moment, and the preset time period is the time difference between the previous moment and the current moment.

[0049] In the embodiment of the present application, the longitudinal acceleration is a measured value, and the initial longitudinal acceleration is a longitudinal acceleration obtained by calculation based on the measured longitudinal acceleration.

[0050] In a second aspect, a vehicle speed estimation device is provided, the device comprising:

[0051] An acquisition module, used to acquire the wheel center speed of each wheel in the vehicle, the longitudinal acceleration of the vehicle and the driving state information of the vehicle; wherein the driving state information is used to indicate whether the vehicle is in a slip state;

[0052] The processing module is used to obtain the initial longitudinal speed of the vehicle based on the longitudinal acceleration; determine the first weight coefficient of each wheel and the second weight coefficient of the vehicle based on the driving state information; wherein the first weight coefficient is used to represent the weight coefficient corresponding to the wheel center speed of each wheel in the vehicle, and the second weight coefficient is used to represent the weight coefficient corresponding to the initial longitudinal speed; determine the target longitudinal speed of the vehicle based on the wheel center speed, the first weight coefficient, the initial longitudinal speed and the second weight coefficient.

[0053] In combination with the second aspect, in certain implementations of the second aspect, the processing module is specifically used to: if the driving status information indicates that the vehicle is in a slipping state, determine the first preset value as the first weight coefficient, and determine the second preset value as the second weight coefficient; if the driving status information indicates that the vehicle is not in a slipping state, determine the first weight coefficient and the second weight coefficient based on a first parameter of the vehicle; wherein the first parameter includes: the road adhesion coefficient of the vehicle's current road conditions, the vehicle's current actual speed and acceleration change rate.

[0054] In combination with the second aspect and the above-mentioned implementation methods, in some implementation methods of the second aspect, the processing module is specifically used to: determine an initial first weight coefficient and an initial second weight coefficient based on the road adhesion coefficient; determine a first adjustment amount corresponding to the initial first weight coefficient and a second adjustment amount corresponding to the initial second weight coefficient based on the current actual vehicle speed and the current acceleration change rate; adjust the initial first weight coefficient based on the first adjustment amount to obtain the first weight coefficient, and adjust the initial second weight coefficient based on the second adjustment amount to obtain the second weight coefficient.

[0055] In combination with the second aspect and the above-mentioned implementation methods, in some implementation methods of the second aspect, the processing module is specifically used to: determine a first weight coefficient based on a first parameter of the vehicle and a first mapping relationship; wherein the first weight coefficient in the first mapping relationship is positively correlated with the road adhesion coefficient, the first weight coefficient is negatively correlated with the actual vehicle speed, and the first weight coefficient is negatively correlated with the acceleration change rate of the vehicle; determine a second weight coefficient based on the first parameter of the vehicle and a second mapping relationship; wherein the second weight coefficient in the second mapping relationship is negatively correlated with the road adhesion coefficient, the second weight coefficient is positively correlated with the actual vehicle speed, and the second weight coefficient is positively correlated with the acceleration change rate.

[0056] In combination with the second aspect and the above-mentioned implementation methods, in some implementation methods of the second aspect, the processing module is specifically used to: determine the first value corresponding to each wheel based on the wheel center speed and the first weight coefficient; determine the second value based on the initial longitudinal vehicle speed and the second weight coefficient; determine the sum of the first value and the second value as the third value; determine the sum of the first weight coefficient and the second weight coefficient of each wheel as a fourth value; and determine the ratio of the third value to the fourth value as the target longitudinal vehicle speed.

[0057] In combination with the second aspect and the above-mentioned implementation methods, in some implementation methods of the second aspect, the acquisition module is also used to: determine the correction coefficient of each wheel based on the vehicle's slip rate and / or the wheel radius of each wheel; determine the wheel center speed of each wheel based on a third parameter and the correction coefficient; wherein the third parameter includes the vehicle's wheelbase, the wheel angle of each wheel, the vehicle's yaw angular velocity, and the wheel linear speed of each wheel.

[0058] In combination with the second aspect and the above-mentioned implementation methods, in some implementation methods of the second aspect, the acquisition module is specifically used to: determine the target wheel among the wheels based on the operating condition of the vehicle; wherein the operating condition includes the braking condition and the driving condition of the vehicle, and the target wheel is the wheel with the largest wheel center speed among the wheels, or the wheel with the smallest wheel center speed among the wheels; if at least one wheel among the wheels is in a slipping state, determine whether the target wheel is included in at least one wheel; if the target wheel is included in at least one wheel, determine that the driving state information indicates that the vehicle is in a slipping state.

[0059] In combination with the second aspect and the above-mentioned implementation methods, in some implementation methods of the second aspect, the processing module is specifically used to: determine the initial longitudinal speed of the vehicle based on the second parameter and the longitudinal acceleration; wherein the second parameter includes the longitudinal speed of the vehicle at a first moment, the longitudinal acceleration of the vehicle and a preset time length; the first moment is the moment before the current moment, and the preset time period is the time difference between the previous moment and the current moment.

[0060] In a third aspect, a vehicle is provided, comprising a memory and a processor, wherein 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 above-mentioned first aspect or any possible implementation of the first aspect.

[0061] In a fourth aspect, a computer program product is provided, comprising: a computer program code, which, when executed on a computer, enables the computer to execute the method in the first aspect or any possible implementation of the first aspect.

[0062] In a fifth aspect, a computer-readable storage medium is provided, which stores a computer program. When the computer program is executed, the method in the above-mentioned first aspect or any possible implementation manner of the first aspect is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] Figure 1 It is a kinetic model diagram provided in the embodiment of the present application;

[0064] Figure 2 is a schematic flow chart of a vehicle speed estimation method provided in an embodiment of the present application;

[0065] Figure 3 is a schematic flow chart of another vehicle speed estimation method provided in an embodiment of the present application;

[0066] Figure 4 is a schematic diagram of the structure of a vehicle speed estimation device provided in an embodiment of the present application;

[0067] Figure 5 It is a structural schematic diagram of a vehicle provided in an embodiment of the present application. DETAILED DESCRIPTION

[0068] 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.

[0069] 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.

[0070] The longitudinal speed of a vehicle refers to the speed component of the vehicle in the forward or backward direction during driving. The accuracy of the longitudinal speed is crucial to the safety control of the vehicle. However, in the prior art, when calculating the longitudinal speed of a vehicle, it is easily affected by interference factors (for example, interference factors such as signal noise, zero drift, wheel slip rate, and wheel rolling radius), resulting in low calculation accuracy of the longitudinal speed of the vehicle. Therefore, how to improve the accuracy of the estimated longitudinal speed, thereby improving the safety of the vehicle, is a technical problem that needs to be solved at present.

[0071] In view of this, the present application provides a vehicle speed estimation method, an estimation device and a vehicle, which determine a first weight coefficient and a second weight coefficient according to the vehicle's driving state information (whether the vehicle is in a slip state); determine the vehicle's longitudinal speed according to the wheel center speed, the first weight coefficient, the initial longitudinal speed and the second weight coefficient. Through the estimation method of the present application, it is ensured that the impact of vehicle slip on the longitudinal speed can be taken into account, and the accuracy of the longitudinal speed is improved, thereby improving the safety of the vehicle.

[0072] Figure 1 It is a kinetic model diagram provided in an embodiment of the present application.

[0073] like Figure 1 The vehicle dynamics model 100 is shown; wherein 110 is the front wheel of the vehicle, 120 is the rear wheel of the vehicle, 130 is the center of mass of the vehicle, δ r represents the rear wheel turning angle, δ f Represents the front wheel turning angle, V y Indicates the lateral speed of the vehicle, V x represents the longitudinal speed of the vehicle, V represents the actual speed of the vehicle (i.e. the combined speed of the vehicle), and L represents the wheelbase of the vehicle (the distance from the front axle to the rear axle of the vehicle) ω r . Represents the vehicle's yaw angular velocity.

[0074] Combine the following Figure 1 The dynamic model in Figure 2 The method for estimating the vehicle speed in will be further explained.

[0075] Figure 2 It is a schematic flow chart of a vehicle speed estimation method provided in an embodiment of the present application.

[0076] For example, Figure 2 The illustrated method 200 may be performed by a vehicle; or may be performed by a processor or chip in a vehicle.

[0077] like Figure 2As shown, the vehicle speed estimation method 200 includes S210 to S240 , which will be described in detail below.

[0078] S210, obtaining the wheel center speed of each wheel in the vehicle, the longitudinal acceleration of the vehicle and the driving state information of the vehicle.

[0079] The wheel center speed of each wheel refers to the translation speed of the center point of the wheel relative to the ground, which reflects the actual motion state of the vehicle and is related to the longitudinal speed of the vehicle.

[0080] It is understandable that there is a difference between the vehicle's wheel center speed and the vehicle's wheel linear speed; the wheel linear speed refers to the instantaneous linear speed of the contact point between the vehicle's tire tread and the ground, and the wheel linear speed reflects the relative motion state between the vehicle's tire and the ground; the wheel linear speed can be directly measured by a wheel speed sensor installed at the wheel, and the wheel center speed can be calculated in combination with the wheel linear speed. The following is a detailed description of the method for determining the wheel center speed of each wheel.

[0081] In one implementation, a correction coefficient of each wheel is determined based on the vehicle's slip rate and / or the wheel radius of each wheel; the wheel center speed of each wheel is determined based on a third parameter and the correction coefficient; wherein the third parameter includes the vehicle's wheelbase, the wheel angle of each wheel, the vehicle's yaw angular velocity, and the wheel linear speed of each wheel.

[0082] Exemplarily, the correction coefficient of each wheel is determined according to the slip rate and / or wheel radius of the vehicle; for example, the correction coefficient of each wheel is determined according to the wheel radius of the vehicle, and the tire radius may change due to tire pressure, wear or load changes. The correction coefficient is used to compensate for the radius error; when the vehicle is stationary, the tire radius is inferred by the known vehicle speed, or the tire radius is determined in real time according to sensor data; the ratio of the nominal radius of the tire (the standard radius of the tire) to the tire radius is determined as the correction coefficient. For example, the correction coefficient is determined according to the slip rate, and the slip rate and the third parameter are used as historical data for model training to predict the correction coefficient; wherein the input correction coefficient is positively correlated with the slip rate.

[0083] It can be understood that due to the wear of the vehicle's wheels and the slip of the vehicle, there will be a difference between the theoretical wheel center speed and the actual wheel center speed; the correction coefficient is used to eliminate the error between the theoretical wheel center speed and the actual wheel center speed; among them, the correction coefficient determined according to the wheel radius is used to compensate for the error between the theoretical wheel center speed and the actual wheel center speed caused by wheel wear, and the correction coefficient determined according to the slip rate of the vehicle is used to eliminate the error between the theoretical wheel center speed and the actual wheel center speed caused by vehicle slip; the correction coefficient determined according to the slip rate and wheel radius of the vehicle is used to eliminate both errors caused by wheel wear and vehicle slip.

[0084] Exemplarily, after determining the correction coefficient of each wheel, the wheel center speed of each wheel is calculated according to the third parameter and the correction coefficient using Formula 1 to Formula 4; wherein Formula 1 is a calculation formula for the wheel center speed of the left front wheel, Formula 2 is a calculation formula for the wheel center speed of the right front wheel, Formula 3 is a calculation formula for the wheel center speed of the left rear wheel, and Formula 4 is a calculation formula for the wheel center speed of the right rear wheel:

[0085]

[0086] Among them, v fl_cog represents the wheel center speed of the left front wheel of the vehicle, v fl represents the linear speed of the left front wheel, δ fl Indicates the left front wheel angle, Fct fl Indicates the left front wheel correction coefficient, b f represents the front wheel track, ω r Represents the vehicle's yaw angular velocity.

[0087]

[0088] Among them, v fr_cog represents the wheel center speed of the right front wheel of the vehicle, v fr represents the linear speed of the right front wheel, δ fr Indicates the right front wheel turning angle, Fct fr Indicates the correction coefficient of the right front wheel, b f represents the front wheel track, ω r Represents the vehicle's yaw angular velocity.

[0089]

[0090] Among them, v rl_cog represents the wheel center speed of the left rear wheel of the vehicle, v rl represents the linear speed of the left rear wheel, δ rl Indicates the left rear wheel turning angle, Fct rl Indicates the correction factor of the left rear wheel, b r represents the rear wheel track, ω r Represents the vehicle's yaw angular velocity.

[0091]

[0092] Among them, v rr_cong represents the wheel center speed of the left rear wheel of the vehicle, v rr represents the linear speed of the left rear wheel, δ rr Indicates the left rear wheel turning angle, Fct rr Indicates the correction factor of the left rear wheel, b r represents the rear wheel track, ω r Represents the vehicle's yaw angular velocity.

[0093] In an embodiment of the present application, the wheel center speed of each wheel is determined based on the third parameter and the correction coefficient. Since the correction coefficient is obtained based on the slip rate and / or wheel radius of the vehicle, it is ensured that when calculating the wheel center speed, the error caused by the slip rate can be compensated and the wheel radius error can be corrected; thereby ensuring that a more accurate wheel center speed can be obtained, and a more accurate target longitudinal vehicle speed can be obtained based on the more accurate wheel center speed.

[0094] In a possible implementation, the wheel center speed of each wheel of the vehicle is determined based on the wheel turning angle of each wheel of the vehicle, the wheel linear speed of each wheel, the front wheel track, the rear wheel track, the yaw angular velocity of the whole vehicle and the wheelbase of the vehicle.

[0095] Specifically, according to the average turning angle of the front wheels (i.e., the average turning angle of the left front wheel and the right front wheel), the average turning angle of the rear wheels (i.e., the average turning angle of the left rear wheel and the right rear wheel), and the wheelbase of the vehicle (the distance from the front axle to the rear axle, such as Figure 1 The first coefficient and the second coefficient are determined according to the wheel angle, the wheel linear speed of each wheel, the front wheel track, the first coefficient and the yaw rate of the whole vehicle; the wheel center speed of the left rear wheel and the right rear wheel are determined according to the wheel angle, the wheel linear speed of each wheel, the rear wheel track, the second coefficient and the yaw rate of the whole vehicle.

[0096] For example, according to the average turning angle of the front wheels, the average turning angle of the rear wheels and the wheelbase of the vehicle, the first coefficient is calculated using Formula 5, and the second coefficient is calculated using Formula 6:

[0097]

[0098] Among them, L ɑ represents the first coefficient, L b represents the second coefficient, L represents the wheelbase, δ f represents the average turning angle of the front wheels; δ r Represents the average rear wheel turning angle.

[0099] Exemplarily, according to each wheel turning angle, each wheel linear speed, front wheel track, first coefficient and vehicle yaw rate, the wheel center speed of the left front wheel is calculated by formula 7, and the wheel center speed of the right front wheel is calculated by formula 8.

[0100]

[0101] Among them, v fl_cong represents the wheel center speed of the left front wheel of the vehicle, v fl represents the linear speed of the left front wheel, δ fl represents the left front wheel turning angle, b f Indicates the front wheel track, L ɑ represents the first coefficient, ω rRepresents the vehicle's yaw angular velocity.

[0102]

[0103] Among them, v fr_cog represents the wheel center speed of the right front wheel of the vehicle, v fr represents the linear speed of the right front wheel, δ fr represents the right front wheel turning angle, b f Indicates the front wheel track, L ɑ represents the first coefficient, ω r Represents the vehicle's yaw angular velocity.

[0104]

[0105] Among them, v rl_cog represents the wheel center speed of the left rear wheel of the vehicle, v rl represents the linear speed of the left rear wheel, δ rl represents the left rear wheel turning angle, b r Indicates rear wheel track, L b represents the second coefficient, ω r Represents the vehicle's yaw angular velocity.

[0106]

[0107] Among them, v rr_cog represents the wheel center speed of the left rear wheel of the vehicle, v rr represents the linear speed of the left rear wheel, δ rr represents the left rear wheel turning angle, b r Indicates rear wheel track, L b represents the second coefficient, ω r Represents the vehicle's yaw angular velocity.

[0108] Optionally, determining the driving status information of the vehicle includes: determining whether each wheel is in a slipping state based on the wheel center speed of each wheel and / or the wheel center acceleration of each wheel; if each wheel in the vehicle is in a slipping state, determining that the driving status information indicates that the vehicle is in a slipping state; if each wheel in the vehicle is not in a slipping state, determining that the driving status information indicates that the vehicle is not in a slipping state.

[0109] For example, determine whether the wheel is in a slipping state based on the wheel center speed of the wheel: calculate the wheel center speed of each wheel in the vehicle, and determine the average value of the wheel center speed within a preset number of cycles; calculate a first difference between the wheel center speed and the average value of the wheel center speed; if the absolute value of the first difference is greater than a preset value 1, determine that the wheel is in a slipping state (slipping state).

[0110] The period may be a collection period or a calculation period of the wheel center speed. For example, the third parameter is collected once every 5 milliseconds (ms) and the wheel center speed is calculated. The period is 5 ms. If the preset number is 4, the average value of the wheel center speed in the last 4 periods is calculated. The preset value 1 is a preset value determined according to a calibration table. The calibration table is a table obtained by testing and calibration in a real vehicle or simulation environment covering all working conditions (acceleration, braking, coasting) and the full speed range of the vehicle (from the lowest speed to the highest speed).

[0111] For example, the wheel center speed of each wheel of the vehicle, the estimated longitudinal speed (obtained based on multi-sensor fusion), the actual longitudinal acceleration, and the road adhesion coefficient (reference value, which can be set through experiments or simulations) are collected, the average wheel center speed is calculated, the deviation between the actual wheel center speed and the average is calculated, and the slip events are marked. The estimated longitudinal speed and the actual longitudinal acceleration are used as inputs, and the slip threshold (preset value 1) is used as output to obtain Table 1. The table for determining preset value 1 is shown in Table 1:

[0112] Table 1

[0113] Estimated longitudinal speed (km / h) <![CDATA[Actual longitudinal acceleration (m / s 2 )]]> Default value 1 <![CDATA[V 1 ]]> <![CDATA[a 1 ]]> <![CDATA[b 1 ]]> <![CDATA[V 2 ]]> <![CDATA[a 2 ]]> <![CDATA[b 2 ]]>

[0114] For example, if the current estimated longitudinal speed is V 1 , the actual longitudinal acceleration is a 1 , then when the absolute value of the first difference is detected to be greater than b 1 , it is determined that the wheel is in a slipping state.

[0115] It can be understood that when the first difference between the wheel center speed of the vehicle wheel and the average speed of the wheel center speed is greater than the preset value 1, it indicates that the wheel may be in a slipping state (driving slip or braking lock).

[0116] It should be noted that, under the current estimated longitudinal vehicle speed and actual longitudinal acceleration, different first differences (i.e., the speed difference between the wheel center speed and the average value of the wheel center speed) are determined by changing the wheel center speed; and when the first differences are different, the slip state of the wheel is marked to determine the critical value of the wheel in the slip state, which is the preset value 1 corresponding to the estimated longitudinal vehicle speed and the actual longitudinal acceleration; the estimated longitudinal vehicle speed and the actual longitudinal acceleration are changed to determine the preset value 1 under different estimated longitudinal vehicle speeds and actual longitudinal accelerations, and the corresponding relationship shown in Table 1 is obtained.

[0117] Exemplarily, the slip state of the wheel is determined based on the wheel center acceleration of each wheel: the wheel speed is differentiated to determine the wheel center acceleration, and the actual longitudinal acceleration of the vehicle is determined; the second difference between the wheel center acceleration and the actual longitudinal acceleration is calculated; if the absolute value of the second difference is greater than a preset value 2, it is determined that the wheel is in a slip state; wherein the preset value 2 is a preset value determined based on a calibration table, wherein the calibration table is a table obtained by testing and calibration in a real vehicle or simulation environment covering all operating conditions (acceleration, braking, coasting) and all vehicle speed ranges.

[0118] It is understandable that if the wheel center acceleration of the wheel deviates too much from the actual longitudinal acceleration of the vehicle, it means that the wheel may be in a slipping state. The table for determining the preset value 2 is shown in Table 2:

[0119] Table 2

[0120] Estimated longitudinal speed (km / h) <![CDATA[Actual longitudinal acceleration (m / s 2 )]]> Default value 2 <![CDATA[V 1 ]]> <![CDATA[a 1 ]]> <![CDATA[c 1 ]]> <![CDATA[V 2 ]]> <![CDATA[a 2 ]]> <![CDATA[c 2 ]]>

[0121] It should be noted that, under the current estimated longitudinal vehicle speed and actual longitudinal acceleration, different second differences (i.e., the acceleration difference between the wheel center acceleration and the actual longitudinal acceleration) are determined by changing the wheel center acceleration; and when the second differences are different, the slip state of the wheel is marked to determine the critical value of the wheel in the slip state, which is the preset value 2 corresponding to the estimated longitudinal vehicle speed and the actual longitudinal acceleration; the estimated longitudinal vehicle speed and the actual longitudinal acceleration are changed to determine the preset value 2 under different estimated longitudinal vehicle speeds and actual longitudinal accelerations, and the table shown in Table 2 is obtained.

[0122] For example, if all wheels of the vehicle are in a slipping state, it is determined that the vehicle is in a slipping state; if all wheels of the vehicle are not in a slipping state, it is determined that the vehicle is not in a slipping state. If some wheels of the vehicle are in a slipping state and some wheels are not in a slipping state, further judgment is required.

[0123] Specifically, obtaining the driving state information of the vehicle includes: determining a target wheel among the wheels based on the working condition of the vehicle; wherein the working condition includes the braking working condition and the driving working condition of the vehicle, and the target wheel is a wheel with the largest wheel center speed among the wheels, or a wheel with the smallest wheel center speed among the wheels; if the target wheel is in a slipping state, determining that the driving state information indicates that the vehicle is in a slipping state; or if at least one wheel among the wheels is in a slipping state, determining whether the target wheel is included in at least one wheel; if the target wheel is included in at least one wheel, determining that the driving state information indicates that the vehicle is in a slipping state.

[0124] Exemplarily, if the vehicle is in a driving condition, the wheel with the largest wheel center speed is determined as the target wheel; if the vehicle is in a braking condition, the wheel with the smallest wheel center speed is determined as the target wheel. Determine whether the target wheel is in a slipping state, if the target wheel is in a slipping state, determine that the vehicle is in a slipping state, and if the target wheel is not in a slipping state, determine that the vehicle is not in a slipping state.

[0125] In the embodiment of the present application, the slip state of the vehicle is determined according to the slip state of the target wheel; that is, when it is determined that the target wheel is in a slip state, the vehicle is determined to be in a slip state. Compared with determining the slip state of the vehicle according to the slip state of each wheel, this solution performs calculations according to the slip state of the target wheel, which has a smaller amount of calculations and can effectively improve the efficiency of determining the slip state of the vehicle.

[0126] Optionally, determine the activation state of the lift torque of the slip control of the front axle and the rear axle of the vehicle; determine the slip state of the vehicle based on the activation state of the lift torque of the front axle and the rear axle; if the front axle lift torque is in an activated state, determine that the front wheels of the vehicle (left front wheel and right front wheel) are in a slip state (slipping state); if the rear axle lift torque is in an activated state, determine that the rear wheels of the vehicle (left rear wheel and right rear wheel) are in a slip state; wherein, slip control is a key function to prevent wheel slippage, which is usually achieved by adjusting the driving torque or braking force, and the front axle lift torque activation and the rear axle lift torque activation are a strategy in slip control, which are used to determine whether the front wheels or rear wheels enter a slipping state.

[0127] It should be noted that when the front wheels of the vehicle enter a slipping state, the system suppresses slipping by reducing the front axle drive torque or increasing the front axle braking force, that is, the front axle lifting torque is in an activated state; when the rear wheels of the vehicle enter a slipping state, the system suppresses slipping by reducing the rear axle drive torque or increasing the rear axle braking force, that is, the rear axle lifting torque is in an activated state. Therefore, the slipping state of the front and rear wheels of the vehicle can be determined by the lifting torque state of the front and rear axles.

[0128] In one implementation, whether the wheel exits the slip state is determined based on the vehicle's wheel center speed, the average wheel center speed, the wheel center acceleration, the lifting torque state of the front and rear axles, and the difference between the wheel center speed and the estimated longitudinal vehicle speed. If the difference between the actual wheel speed and the average wheel speed of the wheel in the latest n cycles is less than or equal to a preset value 1, the difference between the wheel center acceleration and the actual longitudinal acceleration is less than or equal to a preset value 2, the lifting torque state of the front and rear axles of the vehicle are both in an inactive state, and the difference between the wheel center speed and the estimated longitudinal vehicle speed is less than or equal to a preset value 3; wherein the preset value 3 is obtained by real vehicle simulation calibration based on the absolute value of the estimated longitudinal vehicle speed and the absolute value of the actual longitudinal acceleration.

[0129] In one possible implementation, if none of the vehicle's wheels are in a slipping state, or the vehicle is stationary (the estimated longitudinal vehicle speed is less than a preset value, which is a smaller vehicle speed value), it is determined that the vehicle is not in a slipping state; or if the difference between the wheel center speed of each wheel in the vehicle and the wheel center speed of the target vehicle speed is less than a preset value 4, it is determined that the vehicle is not in a slipping state; wherein the preset value 4 is obtained by real vehicle simulation calibration based on the estimated absolute value of the longitudinal vehicle speed and the actual absolute value of the longitudinal acceleration.

[0130] Optionally, the process of determining the preset value 3 and the preset value 4 may refer to the relevant description of the process of determining the preset value 1 and the preset value 2, which will not be repeated here.

[0131] S220: Obtain an initial longitudinal speed of the vehicle based on the longitudinal acceleration.

[0132] In one implementation, the initial longitudinal speed of the vehicle is determined based on a second parameter and the longitudinal acceleration; wherein the second parameter includes the longitudinal speed of the vehicle at a first moment, the longitudinal acceleration of the vehicle and a preset time period; the first moment is the moment before the current moment, and the preset time period is the time difference between the previous moment and the current moment.

[0133] Specifically, the product of the longitudinal acceleration and the duration of the preset period is determined as the change in longitudinal vehicle speed; the sum of the longitudinal vehicle speed at the first moment and the change in longitudinal vehicle speed is determined as the initial longitudinal vehicle speed of the vehicle. For example, the initial longitudinal vehicle speed of the vehicle can be calculated using Formula 11:

[0134] V x初始 =(V x (k-1)+a x ΔT); (Formula 11)

[0135] Among them, V x初始 represents the initial longitudinal vehicle speed, V x (k-1) represents the longitudinal speed at the first moment, a x represents the longitudinal acceleration, and ΔT represents the preset period (the time difference from the first moment to the current moment).

[0136] S230: Determine a first weight coefficient of each wheel and a second weight coefficient of the vehicle based on the driving state information.

[0137] The first weight coefficient is used to represent the weight coefficient corresponding to the wheel center speed of each wheel in the vehicle, and the second weight coefficient is used to represent the weight coefficient corresponding to the initial longitudinal vehicle speed. The method for determining the first weight coefficient and the second weight coefficient is described in detail below.

[0138] In one implementation, if the driving status information indicates that the vehicle is in a slipping state, the first preset value is determined as the first weight coefficient, and the second preset value is determined as the second weight coefficient; if the driving status information indicates that the vehicle is not in a slipping state, the first weight coefficient and the second weight coefficient are determined based on a first parameter of the vehicle; wherein the first parameter includes: the road adhesion coefficient of the vehicle's current road condition, the vehicle's current actual speed and the current acceleration change rate.

[0139] It can be understood that the current actual speed of the vehicle is the current driving speed of the vehicle, that is, the longitudinal speed V of the vehicle. x The lateral speed V of the vehicle y The combined speed (e.g. Figure 1 The vehicle speed V).

[0140] For example, if the vehicle is in a slipping state, that is, the vehicle is in a skidding state, the wheel center speed of the vehicle is in a completely unreliable state; therefore, the first preset value (for example, zero value) is determined as the first weight coefficient, and the second preset value is determined as the second weight coefficient. If the vehicle is not in a slipping state, the credibility of the wheel center speed of the vehicle and the longitudinal acceleration will be affected by the slip rate of the vehicle; therefore, the first weight coefficient and the second weight coefficient of the vehicle are determined according to the first parameter; it is ensured that the first weight coefficient and the second weight coefficient can be determined in different ways according to the driving state information of the vehicle and taking into account the slip rate of the vehicle.

[0141] For example, if the vehicle is in a slipping state, the wheel linear velocity is in an unreliable state, that is, the wheel center velocity calculated according to the wheel linear velocity is in an unreliable state. Therefore, the first weight coefficient corresponding to the wheel center velocity is 0, and the acceleration weight coefficient is 1.

[0142] Exemplarily, when determining the first weight coefficient and the second weight coefficient according to the first parameter, there are two possible implementations, and the two implementations are described below respectively.

[0143] Implementation method 1: Determine an initial first weight coefficient and an initial second weight coefficient based on the road adhesion coefficient; determine a first adjustment amount corresponding to the initial first weight coefficient and a second adjustment amount corresponding to the initial second weight coefficient based on the current actual vehicle speed and the current acceleration change rate; adjust the initial first weight coefficient based on the first adjustment amount to obtain the first weight coefficient, and adjust the initial second weight coefficient based on the second adjustment amount to obtain the second weight coefficient.

[0144] The initial first weight coefficient is positively correlated with the road adhesion coefficient, and the initial second weight coefficient is negatively correlated with the road adhesion coefficient.

[0145] For example, when the road adhesion coefficient is different, the vehicle's slip rate is different, that is, the vehicle's skidding risk is different; therefore, when the road adhesion coefficient is different, the credibility of the vehicle's wheel center speed and the credibility of the longitudinal acceleration are different. The weight coefficient is initially set according to the road adhesion coefficient to obtain the initial first weight coefficient and the initial second weight coefficient, ensuring that the influence of the road adhesion coefficient can be taken into account. Adjustments are made on the basis of the initial first weight coefficient and the initial second weight coefficient to obtain the first weight coefficient and the second weight coefficient, ensuring that the influence of multiple factors such as the actual vehicle speed and the acceleration change rate of the vehicle on the first weight coefficient and the second weight coefficient are simultaneously taken into account.

[0146] For example, the initial setting is first performed according to the road adhesion condition. The initial first weight coefficient corresponding to the high adhesion coefficient is 0.8, and the initial second weight coefficient is 0.2; the initial first weight coefficient corresponding to the low adhesion coefficient is 0.7, and the initial second weight coefficient is 0.3. When the vehicle is traveling on a low adhesion road, if the vehicle is traveling steadily at a medium or low speed (i.e., the actual vehicle speed of the vehicle is less than the preset vehicle speed threshold, and the acceleration change rate is less than the preset threshold), the initial setting is kept unchanged; if the vehicle is in a high-speed and stable driving state (for example, the actual vehicle speed of the vehicle is detected to be greater than the preset vehicle speed threshold, and the acceleration change rate is less than the preset threshold), the corresponding first adjustment amount of the initial first weight coefficient is +0.05, and the second adjustment amount of the initial second weight coefficient is -0.05. The initial first weight coefficient is adjusted according to the first adjustment amount, and the first weight coefficient is determined to be 0.75; the initial second weight coefficient is adjusted according to the second adjustment amount, and the second weight coefficient is determined to be 0.25.

[0147] It should be noted that the above is a schematic illustration of the numerical values ​​of the first weight coefficient and the second weight coefficient, and the present application does not specifically limit the numerical values ​​of the first weight coefficient and the second weight coefficient.

[0148] Implementation method 2: Based on the first parameter of the vehicle and the first mapping relationship, determine the first weight coefficient; wherein, in the first mapping relationship, the first weight coefficient is positively correlated with the road adhesion coefficient, the first weight coefficient is negatively correlated with the actual speed of the vehicle, and the first weight coefficient is negatively correlated with the acceleration change rate of the vehicle; based on the first parameter of the vehicle and the second mapping relationship, determine the second weight coefficient; wherein, in the second mapping relationship, the second weight coefficient is negatively correlated with the road adhesion coefficient, the second weight coefficient is positively correlated with the actual speed of the vehicle, and the second weight coefficient is positively correlated with the acceleration change rate of the vehicle.

[0149] The first mapping relationship is used to represent the mapping relationship between different first parameters and weight coefficients corresponding to wheel center speeds; the second mapping relationship is used to represent the mapping relationship between different first parameters and weight coefficients corresponding to initial longitudinal vehicle speeds.

[0150] It can be understood that, according to the current first parameter of the vehicle (including the road adhesion coefficient of the current road condition, the current actual vehicle speed and the current acceleration change) and the first mapping relationship, the weight coefficient corresponding to the current wheel center speed of the vehicle is determined, that is, the first weight coefficient of the vehicle is determined. According to the current first parameter of the vehicle and the second mapping relationship, the weight coefficient corresponding to the current initial longitudinal speed of the vehicle is determined, that is, the second weight coefficient of the vehicle is determined.

[0151] For example, a low adhesion coefficient road surface (e.g., a slippery road surface or an ice-covered road surface) easily causes the wheel to be in a slip state (wheel skidding), and the wheel speed weight coefficient should be appropriately reduced at this time; when the vehicle speed is high, considering the accuracy of the wheel speed sensor, the calculated wheel speed is affected by noise at this time, and the first weight coefficient is appropriately reduced, the risk of wheel skidding is low, but the acceleration change is more significant, so the acceleration weight coefficient can be increased; when the longitudinal acceleration change rate of the vehicle is large (e.g., the vehicle accelerates or decelerates rapidly), the acceleration weight coefficient is increased to more accurately reflect the dynamic change of the vehicle. Based on this, the relationship between the first parameter and the first weight coefficient is determined (the first weight coefficient is positively correlated with the road adhesion coefficient, the first weight coefficient is negatively correlated with the actual vehicle speed, and the first weight coefficient is negatively correlated with the acceleration change rate of the vehicle) and the relationship between the first parameter and the second weight coefficient (the second weight coefficient is negatively correlated with the road adhesion coefficient, the second weight coefficient is positively correlated with the actual vehicle speed, and the second weight coefficient is positively correlated with the acceleration change rate of the vehicle).

[0152] Optionally, the first mapping relationship and the second mapping relationship may be a mapping relationship in a table form or a mapping relationship in a mathematical function form, or a mapping relationship in other forms. The present application does not limit the specific form of the mapping relationship.

[0153] S240: Determine a target longitudinal speed of the vehicle based on the wheel center speed, the first weight coefficient, the initial longitudinal speed and the second weight coefficient.

[0154] The target longitudinal speed of the vehicle represents the longitudinal speed at the center of mass of the vehicle; Figure 1 V x shown.

[0155] In one implementation, a first value corresponding to each wheel is determined based on the wheel center speed and the first weight coefficient; a second value is determined based on the initial longitudinal vehicle speed and the second weight coefficient; the sum of the first value and the second value is determined as a third value; the sum of the first weight coefficient and the second weight coefficient of each wheel is determined as a fourth value; and the ratio of the third value to the fourth value is determined as the target longitudinal vehicle speed.

[0156] Specifically, the target longitudinal speed of the vehicle can be calculated using Formula 12:

[0157]

[0158] Among them, V x (k) represents the target vehicle speed threshold at time k (current time), k i Represents the first weight coefficient of each wheel, k ax represents the second weight coefficient, a x represents the longitudinal acceleration of the vehicle, V x (k-1) represents the longitudinal speed at the first moment (the moment before the current moment), a x represents the longitudinal acceleration, ΔT represents the preset time period (the interval from the first moment to the current moment), V x_cog represents the wheel center speed of each wheel, and i represents each wheel in the vehicle.

[0159] Optionally, the target longitudinal speed of the vehicle may be calculated using Formula 13:

[0160]

[0161] Among them, k i Represents the first weight coefficient of each wheel, k ax represents the second weight coefficient, V x_cog represents the wheel center speed of each wheel, i represents each wheel in the vehicle, V x初始 Indicates the initial longitudinal vehicle speed.

[0162] In the embodiment of the present application, since the first weight coefficient is the weight coefficient corresponding to the wheel center speed, and the second weight coefficient is the weight coefficient of the initial longitudinal vehicle speed, the first value corresponding to the weighted wheel center speed is obtained based on the wheel center speed and the first weight coefficient, and the second value corresponding to the weighted initial longitudinal vehicle speed is obtained based on the initial longitudinal vehicle speed and the second weight coefficient. The sum of the first value and the second value is determined as the third value; the ratio of the third value to the fourth value is determined as the target longitudinal vehicle speed, ensuring that the target longitudinal vehicle speed can be calculated based on the wheel center speed, the first weight coefficient, the initial longitudinal vehicle speed and the second weight coefficient.

[0163] In one possible implementation, if the vehicle is not in a completely slipping state, determine the first wheel in the vehicle that is in a slipping state; adjust the first weight coefficient of the first wheel and the second weight coefficient of the vehicle; wherein, the vehicle is not in a completely slipping state indicates that there are both wheels in a slipping state and wheels that are not in a slipping state in the vehicle.

[0164] Specifically, if the vehicle is not in a complete slip state, determine the first wheel that is in a slip state; the first weight coefficient of the first wheel is negatively correlated with the longitudinal slip rate of the first wheel, the first weight coefficient of the first wheel is positively correlated with the acceleration change rate of the first wheel, the second weight coefficient of the first wheel is positively correlated with the longitudinal slip rate of the first wheel, and the second weight coefficient of the first wheel is positively correlated with the acceleration change rate of the first wheel.

[0165] For example, the initial first weight coefficient corresponding to the road adhesion coefficient is 0.7, and the initial second weight coefficient is 0.3; assuming that the left front wheel slips and the longitudinal acceleration change rate is greater than the preset value, the left front wheel enters the non-steady-state range. When the longitudinal slip rate of the left front wheel is greater than 70%, the first weight coefficient is reduced to 0, and the second weight coefficient is increased to 1.

[0166] It should be noted that the above is an example of the first weight coefficient and the second weight coefficient, and the present application does not specifically limit the specific values ​​of the first weight coefficient and the second weight coefficient.

[0167] In an embodiment of the present application, when some wheels of the vehicle are in a slip state (i.e., there are non-stable wheels in the vehicle), based on the longitudinal slip rate and the longitudinal acceleration change rate of the wheels in the slip state, the first weight coefficient corresponding to the non-stable wheels is gradually reduced as the longitudinal slip rate increases, and the second weight coefficient is increased at the same time, to ensure that the influence of wheel slip on the accuracy of target longitudinal vehicle speed estimation can be reduced.

[0168] Optionally, when determining the target longitudinal vehicle speed, in order to avoid sudden changes in the estimated target longitudinal vehicle speed, the estimated target longitudinal vehicle speed is smoothed. For example, the target longitudinal vehicle speed within a preset time period is averaged based on a time series to achieve smoothing. For example, a queue (or list) of fixed length is defined to store several recent speed values, and each time the target longitudinal vehicle speed of a calculation cycle is obtained, it is added to the queue, and the earliest value is removed, and the average of all values ​​in the queue is taken as the current smoothed speed value.

[0169] It should be noted that due to sensor noise, signal delay and changes in road conditions, the estimated longitudinal vehicle speed may change suddenly or be discontinuous, thus affecting the performance of the control system. This solution effectively solves the problem of sudden or discontinuous longitudinal vehicle speed by smoothing the target longitudinal vehicle speed.

[0170] In the above embodiment, the first weight coefficient of each wheel and the second weight coefficient of the vehicle are determined according to the driving state information of the vehicle; the target longitudinal speed of the vehicle is determined according to the wheel center speed, the first weight coefficient, the initial longitudinal speed and the second weight coefficient. Since the credibility of the wheel center speed and the longitudinal acceleration of the vehicle is different when the driving state information of the vehicle is different; therefore, the first weight coefficient and the second weight coefficient are determined according to the driving state information of the vehicle; it is ensured that the influence of the driving state information of the vehicle on the wheel center speed and the longitudinal acceleration can be taken into account, that is, it is ensured that the influence of the slip state of the vehicle on the wheel center speed and the longitudinal acceleration of the vehicle can be taken into account. Compared with the prior art that directly determines the longitudinal speed of the vehicle according to the wheel center speed and / or the longitudinal acceleration, this solution takes into account the influence of the vehicle slip situation on the measurement data of the vehicle, and therefore, a more accurate target longitudinal speed can be calculated.

[0171] Figure 3 It is a schematic flow chart of another vehicle speed estimation method provided in an embodiment of the present application.

[0172] Figure 3 The illustrated method 300 may be performed by a vehicle; or may be performed by a processor or chip in a vehicle.

[0173] like Figure 3 As shown, the vehicle speed estimation method 300 includes S301 to S310, and S301 to S310 are described in detail below.

[0174] S301, obtaining the longitudinal acceleration of the vehicle, a third parameter and a correction coefficient of each wheel.

[0175] Exemplarily, the longitudinal acceleration of the vehicle is the acceleration measured by an acceleration sensor in the vehicle; the third parameter includes the vehicle's wheelbase, the wheel angle of each wheel, the vehicle's yaw angular velocity, and the wheel linear velocity of each wheel; the correction coefficient of each wheel is a correction coefficient determined based on the vehicle's slip rate and / or wheel radius, and different wheels may correspond to different correction coefficients.

[0176] S302: Determine the wheel center speed of each wheel according to the third parameter of the vehicle and the correction coefficient of each wheel.

[0177] Exemplarily, the third parameter of the vehicle and the correction coefficient of each wheel are substituted into the calculation formula of the wheel center speed in S210 to calculate the wheel center speed of each wheel.

[0178] Optionally, the implementation of S301 and S302 can refer to Figure 2 The relevant description of S210 is not repeated here.

[0179] S303: determining an initial longitudinal vehicle speed according to the longitudinal acceleration.

[0180] Exemplarily, the initial longitudinal speed of the vehicle is calculated according to the calculation method in Formula 11.

[0181] S304: Determine the slip state of each wheel according to the wheel center speed of each wheel.

[0182] Exemplarily, the wheel center speed of each wheel in the vehicle is calculated to determine the average value of the wheel center speed within a preset number of cycles; a first difference between the wheel center speed and the average value of the wheel center speed is calculated; if the absolute value of the first difference is greater than a preset value 1, it is determined that the wheel is in a slip state.

[0183] S305: Determine the driving state information of the vehicle according to the slip state of the wheels.

[0184] Exemplarily, if all wheels in the vehicle are in a slipping state, it is determined that the vehicle is in a slipping state; if all wheels in the vehicle are not in a slipping state, it is determined that the vehicle is not in a slipping state; if some wheels in the vehicle are in a slipping state, it is determined whether the wheels in the slipping state include a target wheel, and if the target wheel is included, it is determined that the vehicle is in a slipping state; if the target wheel is not included, it is determined that the vehicle is not in a slipping state.

[0185] S306, determine whether the driving status information indicates that the vehicle is in a slipping state; if so, execute S307; if not, execute S308.

[0186] Exemplarily, determine whether the driving status information indicates that the vehicle is in a slipping state; if so, determine a first weight coefficient and a second weight coefficient based on a first parameter; if the driving status information does not indicate that the vehicle is in a slipping state, determine a first preset value as the first weight coefficient and determine a second preset value as the second weight coefficient.

[0187] S307: Determine a first weight coefficient and a second weight coefficient according to the first parameter.

[0188] Optionally, the implementation of S307 can refer to Figure 2 The relevant descriptions of implementation method 1 and implementation method 2 in S230 are not repeated here.

[0189] S308: Determine the first preset value as the first weight coefficient, and determine the second preset value as the second weight coefficient.

[0190] Exemplarily, if the vehicle is not in a slip state, the first preset value is determined as the first weight coefficient, and the second preset value is determined as the second weight coefficient; wherein the first preset value may be 0; ensuring that when the vehicle is in a slip state, the wheel speed in an unreliable state will not affect the target longitudinal speed of the vehicle.

[0191] S309, determining a first value of each wheel according to the wheel center speed and the first weight coefficient, and determining a second value according to the second weight coefficient and the initial longitudinal vehicle speed.

[0192] Exemplarily, the product of the wheel center speed and the first weight coefficient is determined, the product of the wheel center speed and the first weight coefficient is determined as the first value of each wheel, and the product of the second weight coefficient and the initial longitudinal vehicle speed is determined as the second value.

[0193] S310, determining a target longitudinal vehicle speed based on the first value, the second value, the first weight coefficient, and the second weight coefficient.

[0194] Optionally, the implementation of S310 can refer to Figure 2 The relevant description of S240 is not repeated here.

[0195] It should be noted that there are certain deficiencies in estimating the longitudinal vehicle speed using only the wheel linear velocity or the longitudinal acceleration. For example, when estimating the longitudinal vehicle speed using the wheel linear velocity, no integral operation is required, and the cumulative error caused by signal noise or zero drift can be avoided. However, factors such as the change in the rolling radius of the vehicle's wheels and the wheel slip rate will affect the estimation accuracy. When estimating the vehicle speed based on the longitudinal acceleration integral, signal noise or zero drift will affect the estimation accuracy. Based on this, the present application estimates the longitudinal vehicle speed based on the wheel linear velocity and the wheel linear velocity fusion, and takes into account the weight of the integrated vehicle speed of the wheel linear velocity and the longitudinal acceleration, thereby reducing the error of a single solution and improving the estimation accuracy.

[0196] In the embodiment of the present application, the wheel center speed of each wheel is determined based on the third parameter and the correction coefficient, ensuring that the influence of the vehicle's slip rate and / or wheel radius on the wheel center speed is taken into account, thereby obtaining a more accurate wheel center speed. Further, the first weight coefficient and the second weight coefficient are determined based on the vehicle's driving state information; ensuring that the influence of the vehicle's driving state information on the wheel center speed and longitudinal acceleration can be taken into account, obtaining a more accurate first weight coefficient and a second weight coefficient, and then obtaining a more accurate target longitudinal vehicle speed.

[0197] Optionally, before estimating the longitudinal speed of the vehicle, determine whether the wheel speed sensor and inertial sensor (Inertial Measurement Unit, IMU) of the vehicle are not faulty and the signals are valid. If both the wheel speed sensor and the inertial sensor are not faulty and the signals are valid, the method for estimating the longitudinal speed is implemented. If the wheel speed sensor and / or the inertial sensor are faulty, a prompt message is output; wherein the prompt message is used to display the fault information of the wheel speed sensor and / or the inertial sensor.

[0198] It can be understood that the solution of the present application estimates the longitudinal vehicle speed based on the fusion of wheel speed and acceleration integral, evaluates the credibility of the wheel speed signal and acceleration signal according to the current vehicle driving state, and performs weighted averaging on the vehicle speeds obtained by the wheel speed and acceleration integrals respectively, so as to improve the accuracy of the longitudinal estimated vehicle speed.

[0199] Combination of the above Figures 1 to 3 The vehicle speed estimation method provided in the embodiment of the present application is described in detail; Figure 4 and Figure 5 The device embodiments of the present application are described in detail. It should be understood that the device in the embodiments of the present application can execute the various methods of the aforementioned embodiments of the present application, that is, the specific working processes of the following various products can refer to the corresponding processes in the aforementioned method embodiments.

[0200] Figure 4 It is a structural schematic diagram of a vehicle speed estimation device provided in an embodiment of the present application.

[0201] For example, Figure 4 As shown, the vehicle speed estimation device 400 includes:

[0202] The acquisition module 410 is used to acquire the wheel center speed of each wheel in the vehicle, the longitudinal acceleration of the vehicle and the driving state information of the vehicle; wherein the driving state information is used to indicate whether the vehicle is in a slip state;

[0203] The processing module 420 is used to obtain the initial longitudinal speed of the vehicle based on the longitudinal acceleration; determine the first weight coefficient of each wheel and the second weight coefficient of the vehicle based on the driving state information; wherein the first weight coefficient is used to represent the weight coefficient corresponding to the wheel center speed of each wheel in the vehicle, and the second weight coefficient is used to represent the weight coefficient corresponding to the initial longitudinal speed; determine the target longitudinal speed of the vehicle based on the wheel center speed, the first weight coefficient, the initial longitudinal speed and the second weight coefficient.

[0204] Optionally, as an embodiment, the processing module 420 is specifically used to: if the driving status information indicates that the vehicle is in a slipping state, determine the first preset value as the first weight coefficient, and determine the second preset value as the second weight coefficient; if the driving status information indicates that the vehicle is not in a slipping state, determine the first weight coefficient and the second weight coefficient based on a first parameter of the vehicle; wherein the first parameter includes: the road adhesion coefficient of the vehicle's current road condition, the vehicle's current actual speed and the current acceleration change rate.

[0205] Optionally, as an embodiment, the processing module 420 is specifically used to: determine an initial first weight coefficient and an initial second weight coefficient based on a road adhesion coefficient; determine a first adjustment amount corresponding to the initial first weight coefficient and a second adjustment amount corresponding to the initial second weight coefficient based on a current actual vehicle speed and a current acceleration change rate; adjust the initial first weight coefficient based on the first adjustment amount to obtain a first weight coefficient, and adjust the initial second weight coefficient based on the second adjustment amount to obtain a second weight coefficient.

[0206] Optionally, as an embodiment, the processing module 420 is specifically used to: determine a first weight coefficient based on a first parameter of the vehicle and a first mapping relationship; wherein, in the first mapping relationship, the first weight coefficient is positively correlated with the road adhesion coefficient, the first weight coefficient is negatively correlated with the actual vehicle speed, and the first weight coefficient is negatively correlated with the acceleration change rate of the vehicle; determine a second weight coefficient based on the first parameter of the vehicle and a second mapping relationship; wherein, in the second mapping relationship, the second weight coefficient is negatively correlated with the road adhesion coefficient, the second weight coefficient is positively correlated with the actual vehicle speed, and the second weight coefficient is positively correlated with the acceleration change rate of the vehicle.

[0207] Optionally, as an embodiment, the processing module 420 is specifically used to: determine a first value corresponding to each wheel based on the wheel center speed and the first weight coefficient; determine a second value based on the initial longitudinal vehicle speed and the second weight coefficient; determine the sum of the first value and the second value as a third value; determine the sum of the first weight coefficient and the second weight coefficient of each wheel as a fourth value; and determine the ratio of the third value to the fourth value as the target longitudinal vehicle speed.

[0208] Optionally, as an embodiment, the acquisition module 410 is also used to: determine a correction coefficient of each wheel based on the vehicle's slip rate and / or the wheel radius of each wheel; determine the wheel center speed of each wheel based on a third parameter and the correction coefficient; wherein the third parameter includes the vehicle's wheelbase, the wheel angle of each wheel, the vehicle's yaw angular velocity, and the wheel linear speed of each wheel.

[0209] Optionally, as an embodiment, the acquisition module 410 is specifically used to: determine a target wheel among the wheels based on the operating condition of the vehicle; wherein the operating condition includes the braking condition and the driving condition of the vehicle, and the target wheel is the wheel with the largest wheel center speed among the wheels, or the wheel with the smallest wheel center speed among the wheels; if at least one wheel among the wheels is in a slipping state, determine whether at least one wheel includes the target wheel; if at least one wheel includes the target wheel, determine that the driving state information indicates that the vehicle is in a slipping state.

[0210] Optionally, as an embodiment, the processing module 420 is specifically used to: determine the initial longitudinal speed of the vehicle based on the second parameter and the longitudinal acceleration; wherein the second parameter includes the longitudinal speed of the vehicle at a first moment, the longitudinal acceleration of the vehicle and a preset time duration; the first moment is the moment before the current moment, and the preset time period is the time difference between the previous moment and the current moment.

[0211] It should be noted that the above-mentioned vehicle speed estimation device is embodied in the form of a functional unit. The term "module" here can be implemented in the form of software and / or hardware, and is not specifically limited to this.

[0212] For example, a "module" may be a software program, a hardware circuit, or a combination of the two that implements the above functions. The hardware circuit may include an application specific integrated circuit (ASIC), an electronic circuit, a processor (such as a shared processor, a dedicated processor, or a group processor, etc.) and a memory for executing one or more software or firmware programs, a combined logic circuit, and / or other suitable components that support the described functions.

[0213] Therefore, the units of each example described in the embodiments of the present application can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present application.

[0214] Figure 5 It is a structural schematic diagram of a vehicle provided in an embodiment of the present application.

[0215] Exemplarily, vehicle 500 includes: a processor 510 , a memory 520 , and executable program code 530 .

[0216] Exemplarily, the vehicle 500 includes one or more processors 510, which can support the vehicle 500 to implement the vehicle speed estimation method in the method embodiment. The processor 510 can be a general-purpose processor or a special-purpose processor. For example, the processor 510 can be a central processing unit (CPU), a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, such as discrete gates, transistor logic devices, or discrete hardware components.

[0217] Exemplarily, the processor 510 may be used to control the vehicle 500, execute software programs, and process data of the software programs. The vehicle 500 may also include a communication unit to implement input (reception) and output (transmission) of signals.

[0218] Exemplarily, the vehicle 500 may include one or more memories 520 on which executable program code 530 is stored. The executable program code 530 can be executed by the processor 510 to generate instructions so that the processor 510 executes the vehicle speed estimation method described in the above method embodiment according to the instructions.

[0219] Optionally, data may be stored in the memory 520. Optionally, the processor 510 may read data stored in the memory 520, which may be stored at the same storage address as the executable program code 530, or may be stored at a different storage address from the executable program code 530.

[0220] Exemplarily, the processor 510 and the memory 520 may be provided separately or integrated together, for example, integrated on a system on chip (SOC) of the terminal device.

[0221] Exemplarily, the memory 520 can be used to store relevant programs of the vehicle speed estimation method provided in the embodiment of the present application, and the processor 520 can be used to call the executable program code 530 stored in the memory 520 when controlling the vehicle to execute the vehicle speed estimation method of the embodiment of the present application; for example, the wheel center speed of each wheel in the vehicle, the longitudinal acceleration of the vehicle and the driving state information of the vehicle are obtained; wherein the driving state information is used to indicate whether the vehicle is in a slip state; based on the longitudinal acceleration, the initial longitudinal speed of the vehicle is obtained; based on the driving state information, the first weight coefficient of each wheel and the second weight coefficient of the vehicle are determined; wherein the first weight coefficient is used to indicate the weight coefficient corresponding to the wheel center speed of each wheel in the vehicle, and the second weight coefficient is used to indicate the weight coefficient corresponding to the initial longitudinal speed; based on the wheel center speed, the first weight coefficient, the initial longitudinal speed and the second weight coefficient, the target longitudinal speed of the vehicle is determined.

[0222] The present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the vehicle speed estimation method of any of the aforementioned embodiments.

[0223] Among them, computer-readable storage media may include but are not limited to any type of disk, including floppy disks, optical disks, digital versatile disks (Digital Video Disc, DVD), compact disc read-only memory (Compact Disc Read-Only Memory, CD-ROM), microdrives and magneto-optical disks, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, EPROM), electrically erasable programmable read only memory (Electrically Erasable Programmable read only memory, EEPROM), dynamic random access memory (Dynamic Random Access Memory, DRAM), video random access memory (Video Random Access Memory, VRAM), flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0224] The present application 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 vehicle speed estimation method in the above-mentioned embodiment.

[0225] In addition, the vehicle provided in the embodiments of the present application may specifically be a chip, component or module, and the vehicle may include a connected processor and memory; wherein the memory is used to store instructions, and when the vehicle is running, the processor may call and execute instructions so that the chip executes a vehicle speed estimation method in the above-mentioned embodiment.

[0226] Among them, the vehicle, computer-readable storage medium, computer program product or chip provided in the present application are all used to execute the corresponding vehicle speed estimation method provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding vehicle speed estimation method provided above, and will not be repeated here.

[0227] 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.

[0228] 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.

[0229] 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 vehicle speed, characterized in that: The method comprises: Acquiring the wheel center speed of each wheel in the vehicle, the longitudinal acceleration of the vehicle and the driving state information of the vehicle; wherein the driving state information is used to indicate whether the vehicle is in a slip state; Based on the longitudinal acceleration, obtaining an initial longitudinal speed of the vehicle; Based on the driving state information, determining a first weight coefficient of each wheel and a second weight coefficient of the vehicle; wherein the first weight coefficient is used to represent a weight coefficient corresponding to the wheel center speed of each wheel in the vehicle, and the second weight coefficient is used to represent a weight coefficient corresponding to the initial longitudinal vehicle speed; A target longitudinal vehicle speed of the vehicle is determined based on the wheel center speed, the first weight coefficient, the initial longitudinal vehicle speed, and the second weight coefficient.

2. The method according to claim 1, characterized in that: The determining, based on the driving state information, the first weight coefficient of each wheel and the second weight coefficient of the vehicle comprises: If the driving state information indicates that the vehicle is in the slip state, determining a first preset value as the first weight coefficient, and determining a second preset value as the second weight coefficient; If the driving state information indicates that the vehicle is not in the slip state, determining the first weight coefficient and the second weight coefficient based on a first parameter of the vehicle; The first parameter includes: the road adhesion coefficient of the current road condition of the vehicle, the current actual speed of the vehicle and the current acceleration change rate.

3. The method according to claim 2, characterized in that The determining the first weight coefficient and the second weight coefficient based on the first parameter of the vehicle includes: Determining an initial first weight coefficient and an initial second weight coefficient based on the road adhesion coefficient; Determining a first adjustment amount corresponding to the initial first weight coefficient and a second adjustment amount corresponding to the initial second weight coefficient based on the current actual vehicle speed and the current acceleration change rate; The initial first weight coefficient is adjusted based on the first adjustment amount to obtain the first weight coefficient, and the initial second weight coefficient is adjusted based on the second adjustment amount to obtain the second weight coefficient.

4. The method according to claim 2, characterized in that: The determining the first weight coefficient and the second weight coefficient based on the first parameter of the vehicle includes: Determining the first weight coefficient based on the first parameter of the vehicle and the first mapping relationship; wherein, in the first mapping relationship, the first weight coefficient is positively correlated with the road adhesion coefficient, the first weight coefficient is negatively correlated with the actual vehicle speed, and the first weight coefficient is negatively correlated with the acceleration change rate of the vehicle; The second weight coefficient is determined based on the first parameter of the vehicle and the second mapping relationship; wherein, in the second mapping relationship, the second weight coefficient is negatively correlated with the road adhesion coefficient, the second weight coefficient is positively correlated with the actual vehicle speed, and the second weight coefficient is positively correlated with the acceleration change rate of the vehicle.

5. The method according to claim 1, characterized in that The step of determining the target longitudinal speed of the vehicle based on the wheel center speed, the first weight coefficient, the initial longitudinal speed and the second weight coefficient includes: Determine a first value corresponding to each wheel based on the wheel center speed and the first weight coefficient; determine a second value based on the initial longitudinal vehicle speed and the second weight coefficient; Determine the sum of the first value and the second value as a third value; determine the sum of the first weight coefficient of each wheel and the second weight coefficient as a fourth value; The ratio of the third value to the fourth value is determined as the target longitudinal vehicle speed.

6. The method according to claim 1, characterized in that Also includes: Determining a correction coefficient of each wheel based on a slip rate of the vehicle and / or a wheel radius of each wheel; The step of obtaining the wheel center speed of each wheel in the vehicle comprises: Based on the third parameter and the correction coefficient, the wheel center speed of each wheel is determined; wherein the third parameter includes the wheelbase of the vehicle, the wheel angle of each wheel, the yaw angular velocity of the vehicle, and the wheel linear velocity of each wheel.

7. The method according to claim 1, characterized in that The obtaining of the driving state information of the vehicle includes: Based on the working condition of the vehicle, determining a target wheel among the wheels; wherein the working condition includes a braking working condition and a driving working condition of the vehicle, and the target wheel is a wheel with the largest wheel center speed among the wheels, or a wheel with the smallest wheel center speed among the wheels; If the target wheel is in a slipping state, it is determined that the driving state information indicates that the vehicle is in the slipping state.

8. The method according to claim 1, characterized in that: The obtaining of the initial longitudinal speed of the vehicle based on the longitudinal acceleration comprises: Based on a second parameter and the longitudinal acceleration, the initial longitudinal speed of the vehicle is determined; wherein the second parameter includes the longitudinal speed of the vehicle at a first moment, the longitudinal acceleration of the vehicle and a preset duration; the first moment is a moment before the current moment, and the preset time period is a time difference between the previous moment and the current moment.

9. A vehicle speed estimation device, characterized in that: The device comprises: An acquisition module, used to acquire the wheel center speed of each wheel in the vehicle, the longitudinal acceleration of the vehicle and the driving state information of the vehicle; wherein the driving state information is used to indicate whether the vehicle is in a slip state; A processing module, used for obtaining the initial longitudinal speed of the vehicle based on the longitudinal acceleration; determining the first weight coefficient of each wheel and the second weight coefficient of the vehicle based on the driving state information; wherein the first weight coefficient is used to represent the weight coefficient corresponding to the wheel center speed of each wheel in the vehicle, and the second weight coefficient is used to represent the weight coefficient corresponding to the initial longitudinal speed; and determining the target longitudinal speed of the vehicle based on the wheel center speed, the first weight coefficient, the initial longitudinal speed and the second weight coefficient.

10. A vehicle, characterized in that: The vehicle comprises: A memory for storing executable program codes; A processor is used to call and run the executable program code from the memory so that the vehicle executes the method as claimed in any one of claims 1 to 8.

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