A method and device for adaptively estimating tire slip angle

Abstract

The present application relates to the field of new energy vehicles, and provides a method and device for adaptively estimating the tire sideslip angle. The method includes: collecting the motion state parameters of the vehicle during driving; respectively using a preset first tire sideslip angle estimator and a second tire sideslip angle estimator to process the motion state parameters to obtain first and second tire sideslip angle estimation values; based on a preset weight allocation strategy, determining a first weight coefficient assigned to the first tire sideslip angle estimation value and a second weight coefficient assigned to the second tire sideslip angle estimation value; based on the obtained real-time road condition information and vehicle load, adaptively adjusting the first and second weight coefficients to obtain a first adjusted weight coefficient and a second adjusted weight coefficient; based on the first and second adjusted weight coefficients, fusing the first and second tire sideslip angle estimation values to obtain a fused tire sideslip angle estimation value. The present application can effectively improve the estimation accuracy of the tire sideslip angle.

Description

Technical Field

[0001] This application relates to the field of new energy vehicles, and particularly to a method and device for adaptively estimating the tire sideslip angle. Background Art

[0002] The sideslip angle of a vehicle tire is an important variable used to characterize the lateral state stability of the vehicle. The tire sideslip angle has a great influence on the longitudinal and lateral adhesion coefficients of the tire and the optimal slip ratio. At the same time, the tire sideslip angle is one of the important parameters for calculating the lateral force of the vehicle tire, and the tire force is very important for the vehicle active safety control system. If the sideslip angle of the vehicle tire can be accurately and real-time estimated, the system can adjust the control strategy according to the current road conditions to improve the vehicle safety.

[0003] Currently, the measurement of the tire sideslip angle mainly has two methods: observation based on the dynamic model and measurement based on actual sensors. The existing observation based on the dynamic model mainly observes the sideslip angle of the center of mass, and the observation accuracy of the tire sideslip angle is not high; while for the measurement based on actual sensors, the measurement information is single, and there is still the problem of low observation accuracy of the tire sideslip angle.

[0004] Therefore, there is an urgent need to provide a method for estimating the tire sideslip angle with higher estimation accuracy. Summary of the Invention

[0005] In view of this, the embodiments of this application provide a method and device for adaptively estimating the tire sideslip angle to solve the problem of low observation accuracy of the tire sideslip angle in the prior art.

[0006] In the first aspect of the embodiments of this application, a method for adaptively estimating the tire sideslip angle is provided, including:

[0007] Collect the motion state parameters of the vehicle during driving, and the motion state parameters at least include the vehicle yaw rate, the longitudinal and lateral forces of the tire, the longitudinal and lateral accelerations of the vehicle, and the vehicle tire steering angle;

[0008] Use a preset first tire sideslip angle estimator to process the motion state parameters to obtain a first tire sideslip angle estimation value;

[0009] Use a preset second tire sideslip angle estimator to process the motion state parameters to obtain a second tire sideslip angle estimation value;

[0010] Based on a preset weight distribution strategy, determine a first weight coefficient assigned to the first tire sideslip angle estimation value and a second weight coefficient assigned to the second tire sideslip angle estimation value;

[0011] Based on the acquired real-time traffic information and vehicle load, adaptively adjust the first weight coefficient and the second weight coefficient to obtain the first adjusted weight coefficient and the second adjusted weight coefficient;

[0012] Based on the first adjusted weight coefficient and the second adjusted weight coefficient, fuse the first estimated tire sideslip angle and the second estimated tire sideslip angle to obtain the fused estimated tire sideslip angle.

[0013] In a second aspect of the embodiments of the present application, a device for adaptively estimating the tire sideslip angle is provided, including:

[0014] An acquisition module, configured to acquire the motion state parameters of the vehicle during driving, and the motion state parameters at least include the vehicle yaw rate, the longitudinal and lateral forces of the tire, the longitudinal and lateral accelerations of the vehicle, and the vehicle tire steering angle;

[0015] A first processing module, configured to process the motion state parameters by using a preset first tire sideslip angle estimator to obtain a first estimated tire sideslip angle;

[0016] A second processing module, configured to process the motion state parameters by using a preset second tire sideslip angle estimator to obtain a second estimated tire sideslip angle;

[0017] A determination module, configured to determine a first weight coefficient assigned to the first estimated tire sideslip angle and a second weight coefficient assigned to the second estimated tire sideslip angle;

[0018] An adjustment module, configured to adaptively adjust the first weight coefficient and the second weight coefficient based on the acquired real-time traffic information and vehicle load to obtain the first adjusted weight coefficient and the second adjusted weight coefficient;

[0019] A fusion module, configured to fuse the first estimated tire sideslip angle and the second estimated tire sideslip angle based on the first adjusted weight coefficient and the second adjusted weight coefficient to obtain the fused estimated tire sideslip angle.

[0020] In a third aspect of the embodiments of the present application, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the steps of the above method are implemented.

[0021] In a fourth aspect of the embodiments of the present application, a readable storage medium is provided, and the readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are implemented.

[0022] Compared with the prior art, the beneficial effects of the embodiments of the present application at least include: by collecting the motion state parameters of the vehicle during driving, the first and second tire sideslip angle estimators are respectively used to process the motion state parameters to obtain the first and second tire sideslip angle estimation values; then, based on the preset weight distribution strategy, the first and second weight coefficients assigned to the first and second tire sideslip angle estimation values are determined; at the same time, fully considering the real-time road condition information and vehicle load of the vehicle, the first and second weight coefficients are adaptively adjusted, and finally, according to the first and second adjusted weight coefficients after adaptive adjustment, the first and second tire sideslip angle estimation values are fused to obtain the fused tire sideslip angle estimation value, which can effectively improve the estimation accuracy of the tire sideslip angle. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings in the following descriptions are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0024] Figure 1 is a schematic flow chart of a method for adaptively estimating the tire sideslip angle provided by an embodiment of the present application;

[0025] Figure 2 is a schematic diagram of a vehicle's overall vehicle dynamics model used in the method for adaptively estimating the tire sideslip angle provided by an embodiment of the present application;

[0026] Figure 3 is a schematic flow chart of a weight value search process in the method for adaptively estimating the tire sideslip angle provided by an embodiment of the present application;

[0027] Figure 4 is a schematic diagram of a device for adaptively estimating the tire sideslip angle provided by an embodiment of the present application;

[0028] Figure 5 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0029] In the following description, specific details such as specific system structures and technologies are proposed for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.

[0030] In the embodiments of this application, a new energy vehicle refers to a vehicle that uses new energy (non - traditional petroleum and diesel energy) and has advanced technologies. These vehicles adopt new power systems, which can effectively reduce vehicle emissions, reduce the impact on the environment, and improve energy utilization efficiency. The new energy vehicles in the embodiments of this application include, but are not limited to, the following types of vehicles: electric vehicles (EV), battery - electric vehicles (BEV), fuel - cell electric vehicles (FCEV), plug - in hybrid electric vehicles (PHEV), and hybrid electric vehicles (HEV), etc.

[0031] During the driving process of a vehicle, the center position of the wheel is subjected to a lateral force exerted by the vehicle suspension. There are many factors that generate the lateral force. For example, a laterally inclined driving road surface, a lateral cross - wind, or the vehicle being subjected to the action of centrifugal force when driving in a curve, etc. Under the action of the lateral force, the ground generates a corresponding lateral reaction force on the wheel, which is called the side - slip force. Under the action of the side - slip force, the direction of the speed vector of the vehicle wheel's travel deviates from being parallel to the wheel rotation plane, and the included angle between the two is called the tire side - slip angle.

[0032] Next, a method and device for adaptively estimating the tire side - slip angle according to the embodiments of this application will be described in detail with reference to the accompanying drawings.

[0033] Figure 1 It is a schematic flowchart of a method for adaptively estimating the tire side - slip angle provided by the embodiments of this application. Figure 1 The method for adaptively estimating the tire side - slip angle can be executed by the vehicle's integrated controller of the new energy vehicle. As Figure 1 shown, the method for adaptively estimating the tire side - slip angle includes:

[0034] Step S101: Collect the motion state parameters of the vehicle during driving. The motion state parameters at least include the vehicle's yaw rate, tire longitudinal force and lateral force, vehicle longitudinal and lateral accelerations, and vehicle tire steering angle.

[0035] The vehicle's yaw rate is mainly used to describe the steering behavior of the vehicle during driving. The yaw rate is usually expressed in degrees per second (° / s) or radians per second (rad / s).

[0036] The center - of - mass side - slip angle refers to the offset angle of the center of mass relative to the wheel center when the vehicle body rolls during driving.

[0037] Step S102: Use a preset first tire side - slip angle estimator to process the motion state parameters to obtain a first tire side - slip angle estimated value.

[0038] The first tire side - slip angle estimator can be a tire side - slip angle observer constructed based on the vehicle's overall vehicle dynamics model.

[0039] In the embodiments of the present application, the vehicle's overall vehicle dynamics model adopts the two-degree-of-freedom model as shown in Figure 2 . The wind resistance, the vehicle's vertical direction, and the vehicle's pitching and rolling motions are ignored, and only the lateral and yaw motions of the vehicle are considered. According to Newton's second law, the vehicle's motion equation is as shown in Equation (1):

[0040]

[0041] In Equation (1), m is the mass of the vehicle; F x and F y are the longitudinal force and lateral force of the tire respectively; δ is the tire angle of the vehicle, that is, the front wheel angle of the vehicle; a x and a y are the longitudinal and lateral accelerations of the vehicle respectively; I is the moment of inertia of the vehicle about the Z-axis; λ is the yaw angular velocity of the vehicle; a and b are the distances from the front axle and the rear axle to the vehicle's center of mass respectively. The dot above λ represents the derivative of the vehicle's yaw angular velocity.

[0042] When the tire side slip angle is relatively small, the tire side slip angle can be approximated as Equation (2):

[0043]

[0044] In Equation (2), α is the tire side slip angle; v x and v y are the longitudinal and lateral speeds of the vehicle respectively; a and b are the distances from the front axle and the rear axle to the vehicle's center of mass respectively; λ is the yaw angular velocity of the vehicle.

[0045] Figure 2 The β in

[0046] is the sideslip angle of the center of mass. In an exemplary embodiment, the tire side slip angle observer can adopt the hyperbolic tangent function tanh(ε),

[0047]

[0048] where ε > 0. Therefore, the mathematical expression of the front wheel side slip angle of the tire side slip angle observer is as shown in Equation (3):

[0049] Similarly, the mathematical expression of the rear wheel side slip angle of the tire side slip angle observer is as shown in Equation (4):

[0050]

[0051] In Equation (4), ρ2 is the sliding mode gain of the rear wheel slip angle of the tire slip angle observer, and L2 is the feedback gain of the rear wheel slip angle of the tire slip angle observer.

[0052] According to Equations (1)-(4), the tire slip angles of the front and rear wheels of the vehicle can be calculated, and the first estimated tire slip angle value can be obtained.

[0053] The hyperbolic tangent function tanh(ε) is used as the switching function of the sliding mode control, which is suitable for occasions where the switching function is differentiated, applicable to the vehicle driving scenarios of various composite working conditions, with less vibration of the sliding mode and higher calculation accuracy of the tire slip angle.

[0054] Step S103: Process the motion state parameters by using a preset second tire slip angle estimator to obtain a second estimated tire slip angle value.

[0055] The second tire slip angle estimator can be an existing neural network model, logistic regression model, support vector machine model, etc.

[0056] In an example, the second tire slip angle estimator is taken as an RBF (Radial Basis Function) neural network model for illustration. The RBF neural network has the advantages of strong non-linear mapping, fast convergence speed, and not being easily trapped in local optimum. Moreover, when the training sample coverage is wide enough and the amount of data contained in the training samples is large enough, it can achieve an infinite approximation of the true state of any object, and is applicable to the adaptive estimation of the vehicle tire slip angle under various complex and changeable working conditions, which is beneficial to improving the accuracy of the adaptive estimation of the tire slip angle.

[0057] First, collect a training data set, which includes multiple training data. One training data is the motion state parameters of a vehicle during driving, and the motion state parameters include the vehicle yaw rate, tire longitudinal force and lateral force, vehicle longitudinal and lateral accelerations, and vehicle tire steering angle.

[0058] In an implementation manner, the training data set for training the second tire slip angle estimation model (i.e., the second tire slip angle estimator) can be directly collected by means of big data mining.

[0059] In another implementation manner, it is also possible to use the method of training a joint learning model. Each participant in the joint learning uses its own local data to train the second tire slip angle estimation model. This method is equivalent to indirectly collecting the training data set for training the second tire slip angle estimation model.

[0060] Secondly, use the above - collected training data set to train the RBF neural network built in MATLAB until the preset convergence condition is met (such as the number of training rounds reaches the preset round threshold, or the model accuracy reaches the preset accuracy, etc.), and obtain the second tire sideslip angle estimation model.

[0061] In practical applications, collect the motion state parameters of the vehicle during driving, input the motion state parameters into the second tire sideslip angle estimation model obtained by the above training for processing, and output the estimated value of the second tire sideslip angle.

[0062] Step S104: Based on the preset weight distribution strategy, determine the first weight coefficient assigned to the first tire sideslip angle estimated value and the second weight coefficient assigned to the second tire sideslip angle estimated value.

[0063] Step S105: Based on the obtained real - time road condition information and vehicle load, adaptively adjust the first weight coefficient and the second weight coefficient to obtain the first adjusted weight coefficient and the second adjusted weight coefficient.

[0064] Step S106: Based on the first adjusted weight coefficient and the second adjusted weight coefficient, fuse the first tire sideslip angle estimated value and the second tire sideslip angle estimated value to obtain the fused tire sideslip angle estimated value.

[0065] The technical solution provided by the embodiment of the present application, by collecting the motion state parameters of the vehicle during driving, respectively uses the first and second tire sideslip angle estimators to process the motion state parameters to obtain the first and second tire sideslip angle estimated values; then, based on the preset weight distribution strategy, determines the first and second weight coefficients assigned to the first and second tire sideslip angle estimated values; at the same time, fully considering the real - time road condition information and vehicle load of the vehicle, adaptively adjusts the first and second weight coefficients, and finally, according to the first and second adjusted weight coefficients after adaptive adjustment, fuses the first and second tire sideslip angle estimated values to obtain the fused tire sideslip angle estimated value, which can effectively improve the estimation accuracy of the tire sideslip angle.

[0066] It should be noted that Figure 1 the tire sideslip angle adaptive estimation method can also be executed by a server (such as a cloud server, a background server, etc.) connected to the new energy vehicle.

[0067] By analyzing the principles of different estimation methods, it is found that there are differences in the estimation accuracy of different estimation methods for different targets at different times, that is, there is a phenomenon of "drift" in the estimation accuracy of a certain estimation method at a certain time. In order to suppress the large fluctuations in the estimation accuracy of the final tire sideslip angle caused by the decrease in the estimation accuracy of a certain estimation method at some times, the embodiment of the present application determines the first weight coefficient assigned to the first tire sideslip angle estimation value and the second weight coefficient assigned to the second tire sideslip angle estimation value based on a preset weight distribution strategy, specifically including:

[0068] Obtain a first tire sideslip angle reference value corresponding to the first tire sideslip angle estimation value and a second tire sideslip angle reference value corresponding to the second tire sideslip angle estimation value;

[0069] Calculate a first error value between the first tire sideslip angle estimation value and the first tire sideslip angle reference value;

[0070] Calculate a second error value between the second tire sideslip angle estimation value and the second tire sideslip angle reference value;

[0071] Determine the first weight coefficient assigned to the first tire sideslip angle estimation value and the second weight coefficient assigned to the second tire sideslip angle estimation value according to the first error value and the second error value.

[0072] The first tire sideslip angle reference value and the second tire sideslip angle reference value usually refer to the theoretical values of the tire sideslip angle obtained based on vehicle dynamics model analysis.

[0073] The first error value can be calculated according to Equation (5).

[0074]

[0075] In Equation (5), η 11 is the first error value of the front wheel tire sideslip angle of the vehicle; η 12 is the first error value of the rear wheel tire sideslip angle of the vehicle; α 11 and α fw are respectively the first tire sideslip angle estimation value and the theoretical value of the front wheel of the vehicle; α 12 and α rw are respectively the first tire sideslip angle estimation value and the theoretical value of the rear wheel of the vehicle.

[0076] Similarly, the second error value can be calculated according to Equation (6).

[0077]

[0078] In Equation (6), η 21 is the second error value of the front wheel tire sideslip angle of the vehicle; η 22is the second error value of the side slip angle of the rear wheel tire of the vehicle; α 21 and α fw are respectively the estimated value and the theoretical value of the second tire side slip angle of the front wheel of the vehicle; α 22 and α rw are respectively the estimated value and the theoretical value of the second tire side slip angle of the rear wheel of the vehicle.

[0079] In some embodiments, according to the first error value and the second error value, determine the first weight coefficient assigned to the first estimated tire side slip angle, and the second weight coefficient assigned to the second estimated tire side slip angle, including:

[0080] Initialize the weight value search interval, and the weight value search interval is a numerical interval composed of the first search endpoint value to the second search endpoint value;

[0081] According to the preset unit search interval, loop to determine whether the first error value, the second error value, and the i-th search weight value meet the preset weight distribution condition, where the i-th search weight value is within the weight value search interval;

[0082] If the first error value, the second error value, and the i-th search weight value meet the preset weight distribution condition, end the search, and determine the first weight coefficient corresponding to the first estimated tire side slip angle and the second weight coefficient corresponding to the second estimated tire side slip angle based on the i-th search weight value.

[0083] As an example, first, set the weight value accuracy θ, initialize the weight value search interval [T1, R1] and W1, where T1 represents the first search endpoint value, R1 represents the second search endpoint value, and W1 = (T1 + T2) / 2. The preset unit search interval is to divide the weight value search interval into equal parts, and one part represents the unit search interval. For example, if the weight value search interval is [0, 1] and it is divided into 20 equal parts, then the unit search interval is 0.05.

[0084] Secondly, combined with Figure 3 , taking the side slip angle of the front wheel tire of the vehicle as an example, judge whether η 11 < η 21 ×(1 - W i ) holds. Where W i represents the i-th search weight value. For example, if the weight value search interval is [0, 1] and the unit search interval is 0.05, then j = 1, 2, 3......20. If η 11 < η 21 ×(1 - W i ) holds, then let T i = W i ; if η 11 < η 21×(1 - W i ) does not hold, then let R i = W i . Next, let Then, continue to judge whether |T i - R i | > θ holds; if it holds, return to judge whether η 11 < η 21 ×(1 - W i ) holds; if it does not hold, end the search process and output the i-th search weight value.

[0085] Next, according to the i-th search weight value, determine the proportional relationship between the first error value and the second error value of the front wheel tire slip angle of the vehicle, and then convert this proportional relationship into the first weight coefficient and the second weight coefficient. Exemplarily, assume that the i-th search weight value is 0.65, then the ratio of the first error value to the second error value is 0.65. Thus, the first weight coefficient can be determined as 0.65 and the second weight coefficient can be determined as 0.35.

[0086] Similarly, the determination method of the first and second weight coefficients for the rear wheel tire slip angle of the vehicle can refer to the above determination method of the first and second weight coefficients for the front wheel tire slip angle of the vehicle, which will not be elaborated here.

[0087] By determining the first and second weight coefficients of the front and rear wheel tire slip angles of the vehicle through the above method, the search time can be saved, the determination efficiency of the weight coefficients can be improved. At the same time, through the reasonable distribution of the weight coefficients, the phenomenon that the estimation accuracy of a certain estimation method decreases at some moments, resulting in a large fluctuation in the estimation accuracy of the final tire slip angle, can be effectively suppressed, so that the estimation accuracy of the tire slip angle can be maintained at a relatively stable and high level.

[0088] In some embodiments, based on the acquired real-time road condition information and vehicle load, adaptively adjust the first weight coefficient and the second weight coefficient to obtain the first adjusted weight coefficient and the second adjusted weight coefficient, including:

[0089] According to the real-time road condition information, determine the road surface type, and the real-time road condition information includes real-time road surface feature information;

[0090] Based on the collected real-time driving speed and converted wheel speed, estimate the current road surface adhesion coefficient of the vehicle;

[0091] According to the road surface type, correct the current road surface adhesion coefficient to obtain the corrected road surface adhesion coefficient;

[0092] According to the corrected road surface adhesion coefficient and vehicle load, adaptively adjust the first weight coefficient and the second weight coefficient to obtain the first adjusted weight coefficient and the second adjusted weight coefficient.

[0093] Road surface types, including but not limited to cement concrete road surfaces, asphalt concrete road surfaces, hot mix asphalt macadam road surfaces, regular stone block road surfaces (i.e., road surfaces paved with regular stone blocks), etc.

[0094] Real-time road surface characteristic information mainly includes characteristic information for characterizing road surface types, as well as road information for straight, curved, uphill / downhill sections.

[0095] Based on the collected real-time driving speed and converted wheel speed, estimate the current road surface adhesion coefficient of the vehicle. Specifically, the wheel speed change rate of each wheel can be calculated by taking the derivative of the wheel speed; the converted wheel speed of each wheel is calculated through the vehicle's yaw angular velocity, the distance from the front axle to the vehicle's center of mass, the front wheel track width, and the real-time driving speed; the actual slip ratio of each wheel is calculated through the real-time wheel speed and the converted wheel speed collected by the wheel speed sensor; with the actual slip ratio of the wheel as the horizontal axis and the wheel speed change rate of the wheel as the vertical axis, query the predetermined adhesion coefficient mapping relationship table to obtain the current road surface adhesion coefficient corresponding to each wheel.

[0096] Since the vehicle is driving on roads of different road surface types, there are certain differences in the current road surface adhesion coefficient of its wheels. For example, when the vehicle is driving at a low speed on a straight cement concrete road surface, the current road surface adhesion coefficient of its wheels is relatively high, while when driving at a low speed on a curved cement concrete road surface, the current road surface adhesion coefficient of its wheels is lower than the former.

[0097] Based on the road surface type, correct the current road surface adhesion coefficient so that the obtained corrected road surface adhesion coefficient can be closer to the actual situation of the road surface adhesion coefficient corresponding to the wheels when the vehicle is driving on roads of different road surface types, which is beneficial to improving the accuracy of subsequent adaptive estimation of the tire side slip angle.

[0098] Furthermore, the vehicle load also has a certain impact on the tire side slip angle of the vehicle, especially when the vehicle is driving on a turning section, the impact of the vehicle load on the tire side slip angle is relatively large. Therefore, in the embodiments of the present application, the first weight coefficient and the second weight coefficient are adaptively adjusted in combination with the corrected road surface adhesion coefficient and the vehicle load to obtain the first adjusted weight coefficient and the second adjusted weight coefficient.

[0099] In some embodiments, adaptively adjusting the first weight coefficient and the second weight coefficient according to the corrected road surface adhesion coefficient and the vehicle load to obtain the first adjusted weight coefficient and the second adjusted weight coefficient includes:

[0100] If it is determined that the vehicle is in the first vehicle state based on the corrected road surface adhesion coefficient and the vehicle load, increase the first weight coefficient to obtain a first adjusted weight coefficient, and decrease the second weight coefficient to obtain a second adjusted weight coefficient, where the increase ratio of the first weight coefficient is equal to the decrease ratio of the second weight coefficient;

[0101] If it is determined that the vehicle is in the second vehicle state based on the corrected road surface adhesion coefficient and the vehicle load, decrease the first weight coefficient to obtain a first adjusted weight coefficient, and increase the second weight coefficient to obtain a second adjusted weight coefficient, where the decrease ratio of the first weight coefficient is equal to the increase ratio of the second weight coefficient.

[0102] As an example, assume that it is determined that the vehicle is in the first vehicle state (such as fully loaded with high adhesion, that is, the vehicle is in a fully loaded state, and the corrected road surface adhesion coefficient of each wheel of the vehicle is within the preset high adhesion range) according to the corrected road surface adhesion coefficient and the vehicle load. Then, an increase compensation is performed on the first weight coefficient. Generally, the increase amplitude (i.e., the increase ratio) does not exceed the unit search interval described above. For example, if the unit search interval is 0.05, then the increase ratio cannot exceed 0.05. Correspondingly, the second weight coefficient is decreased.

[0103] As another example, assume that it is determined that the vehicle is in the first vehicle state (such as unloaded with low adhesion, that is, the vehicle is in an unloaded state, and the corrected road surface adhesion coefficient of each wheel of the vehicle is within the preset low adhesion range) according to the corrected road surface adhesion coefficient and the vehicle load. Then, the first weight coefficient is decreased. Generally, the decrease amplitude (i.e., the increase ratio) does not exceed the unit search interval described above. For example, if the unit search interval is 0.05, then the decrease ratio cannot exceed 0.05. Correspondingly, the second weight coefficient is increased.

[0104] In the embodiments of the present application, the first weight coefficient and the second weight coefficient are appropriately adjusted by further combining the vehicle load and the road surface adhesion coefficient, which can effectively suppress the phenomenon that the estimation accuracy of a certain estimation method decreases at some moments, resulting in a large fluctuation in the estimation accuracy of the final tire sideslip angle, so that the estimation accuracy of the tire sideslip angle can be maintained at a relatively stable and high level.

[0105] In some embodiments, based on the first adjusted weight coefficient and the second adjusted weight coefficient, the first tire sideslip angle estimated value and the second tire sideslip angle estimated value are fused to obtain a fused tire sideslip angle estimated value, including:

[0106] Calculate a first fused estimated value based on the first adjusted weight coefficient and the first tire sideslip angle estimated value;

[0107] Calculate a second fused estimated value based on the second adjusted weight coefficient and the second tire sideslip angle estimated value;

[0108] Superimpose the first fusion estimation value and the second fusion estimation value to obtain a fused tire slip angle estimation value.

[0109] Specifically, the first fusion estimation value can be calculated according to Equation (7).

[0110]

[0111] In Equation (7), are the first fusion estimation values of the tire slip angles of the front wheels and rear wheels of the vehicle respectively; ω1 is the first adjustment weight coefficient; α 11 , α 12 are the first tire slip angle estimation values of the front wheels and rear wheels of the vehicle respectively.

[0112] Calculate the second fusion estimation value according to Equation (8).

[0113]

[0114] In Equation (8), are the second fusion estimation values of the tire slip angles of the front wheels and rear wheels of the vehicle respectively; ω2 is the second adjustment weight coefficient; α 21 , α 22 are the second tire slip angle estimation values of the front wheels and rear wheels of the vehicle respectively.

[0115] Calculate the fused tire slip angle estimation value according to Equation (9).

[0116]

[0117] In Equation (9), are the fused tire slip angle estimation values of the front wheels and rear wheels of the vehicle respectively.

[0118] In some embodiments, the above method further includes:

[0119] Determine whether the fused tire slip angle estimation value reaches a preset tire slip angle critical value;

[0120] If the fused tire slip angle estimation value reaches the preset tire slip angle critical value, trigger an active braking strategy and output an alarm message.

[0121] The tire slip angle critical value refers to the maximum allowable tire slip angle during vehicle driving. If this maximum tire slip angle is exceeded, the vehicle will experience tire skidding and thus lose its stability.

[0122] The active braking strategy refers to actively and compulsorily controlling the torque of the vehicle to reduce the tire slip angle of the vehicle, avoid tire skidding of the vehicle, and thus improve the stability of the vehicle.

[0123] An alarm message can be a voice / text / graphical message, etc. For example, when the estimated value of the combined tire slip angle is greater than or equal to the critical value of the tire slip angle, a voice alarm message is output through the in-vehicle voice system to prompt the vehicle owner to pay attention to adjusting the vehicle's steering wheel in a timely manner, etc., to avoid tire skidding of the vehicle, and at the same time take corresponding protective measures to ensure the personal safety of the passengers and drivers.

[0124] Any combination of the above optional technical solutions can form an optional embodiment of the present application, which will not be elaborated one by one here.

[0125] The following is an embodiment of the device of the present application, which can be used to execute the method embodiment of the present application. For details not disclosed in the device embodiment of the present application, please refer to the method embodiment of the present application.

[0126] Figure 4 It is a schematic diagram of a tire slip angle adaptive estimation device provided by an embodiment of the present application. As Figure 4 shown, the tire slip angle adaptive estimation device includes:

[0127] An acquisition module 401, configured to acquire the motion state parameters of the vehicle during driving, and the motion state parameters at least include the vehicle yaw rate, tire longitudinal force and lateral force, vehicle longitudinal and lateral accelerations, and vehicle tire rotation angle;

[0128] A first processing module 402, configured to process the motion state parameters by using a preset first tire slip angle estimator to obtain a first tire slip angle estimated value;

[0129] A second processing module 403, configured to process the motion state parameters by using a preset second tire slip angle estimator to obtain a second tire slip angle estimated value;

[0130] A determination module 404, configured to determine a first weight coefficient assigned to the first tire slip angle estimated value and a second weight coefficient assigned to the second tire slip angle estimated value based on a preset weight distribution strategy;

[0131] An adjustment module 405, configured to adaptively adjust the first weight coefficient and the second weight coefficient based on the acquired real-time road condition information and vehicle load to obtain a first adjusted weight coefficient and a second adjusted weight coefficient;

[0132] A fusion module 406, configured to fuse the first tire slip angle estimated value and the second tire slip angle estimated value based on the first adjusted weight coefficient and the second adjusted weight coefficient to obtain a fused tire slip angle estimated value.

[0133] The technical solution provided by the embodiments of the present application collects the motion state parameters of a vehicle during driving, and respectively processes the motion state parameters by using a first tire slip angle estimator and a second tire slip angle estimator to obtain first and second tire slip angle estimation values; then, based on a preset weight allocation strategy, first and second weight coefficients assigned to the first and second tire slip angle estimation values are determined; meanwhile, fully considering the real-time road condition information and vehicle load of the vehicle, the first and second weight coefficients are adaptively adjusted, and finally, according to the first and second adjusted weight coefficients after adaptive adjustment, the first and second tire slip angle estimation values are fused to obtain a fused tire slip angle estimation value, which can effectively improve the estimation accuracy of the tire slip angle.

[0134] In some embodiments, the determining module 404 includes:

[0135] An obtaining unit, configured to obtain a first tire slip angle reference value corresponding to the first tire slip angle estimation value, and a second tire slip angle reference value corresponding to the second tire slip angle estimation value;

[0136] A first calculation unit, configured to calculate a first error value between the first tire slip angle estimation value and the first tire slip angle reference value;

[0137] A second calculation unit, configured to calculate a second error value between the second tire slip angle estimation value and the second tire slip angle reference value;

[0138] A coefficient determining unit, configured to determine a first weight coefficient assigned to the first tire slip angle estimation value and a second weight coefficient assigned to the second tire slip angle estimation value according to the first error value and the second error value.

[0139] In some embodiments, the coefficient determining unit includes:

[0140] An initialization component, configured to initialize a weight value search interval, where the weight value search interval is a numerical interval formed by a first search endpoint value to a second search endpoint value;

[0141] A judgment component, configured to cyclically judge whether the first error value, the second error value, and the i-th search weight value satisfy a preset weight allocation condition at a preset unit search interval, where the i-th search weight value is within the weight value search interval;

[0142] A determination component, configured to end the search if the first error value, the second error value, and the i-th search weight value satisfy the preset weight allocation condition, and determine a first weight coefficient corresponding to the first tire slip angle estimation value and a second weight coefficient corresponding to the second tire slip angle estimation value based on the i-th search weight value.

[0143] In some embodiments, the above-mentioned adjustment module 405 includes:

[0144] A road surface determination unit configured to determine the road surface type according to real-time road condition information, where the real-time road condition information includes real-time road surface feature information;

[0145] An estimation unit configured to estimate the current road surface adhesion coefficient of the vehicle based on the collected real-time driving speed and converted wheel speed;

[0146] A correction unit configured to correct the current road surface adhesion coefficient according to the road surface type to obtain a corrected road surface adhesion coefficient;

[0147] A coefficient adjustment unit configured to adaptively adjust the first weight coefficient and the second weight coefficient according to the corrected road surface adhesion coefficient and the vehicle load to obtain a first adjusted weight coefficient and a second adjusted weight coefficient.

[0148] In some embodiments, the above-mentioned coefficient adjustment unit includes:

[0149] A first determination component configured to, if it is determined based on the corrected road surface adhesion coefficient and the vehicle load that the vehicle is in a first vehicle state, increase the first weight coefficient to obtain a first adjusted weight coefficient and decrease the second weight coefficient to obtain a second adjusted weight coefficient, where the increase ratio of the first weight coefficient is equal to the decrease ratio of the second weight coefficient;

[0150] A second determination component configured to, if it is determined based on the corrected road surface adhesion coefficient and the vehicle load that the vehicle is in a second vehicle state, decrease the first weight coefficient to obtain a first adjusted weight coefficient and increase the second weight coefficient to obtain a second adjusted weight coefficient, where the decrease ratio of the first weight coefficient is equal to the increase ratio of the second weight coefficient.

[0151] In some embodiments, the above-mentioned fusion module 406 includes:

[0152] A first fusion unit configured to calculate a first fusion estimation value based on the first adjusted weight coefficient and the first tire side slip angle estimation value;

[0153] A second fusion unit configured to calculate a second fusion estimation value based on the second adjusted weight coefficient and the second tire side slip angle estimation value;

[0154] A third fusion unit configured to superimpose the first fusion estimation value and the second fusion estimation value to obtain a fused tire side slip angle estimation value.

[0155] In some embodiments, the above-mentioned device further includes:

[0156] A judgment module, configured to judge whether an estimated value of a combined tire slip angle reaches a preset critical value of the tire slip angle;

[0157] An alarm module, configured to trigger an active braking strategy and output an alarm message if the estimated value of the combined tire slip angle reaches the preset critical value of the tire slip angle.

[0158] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The order of execution of each process should be determined according to its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0159] Figure 5 It is a schematic diagram of an electronic device 5 provided by an embodiment of the present application. As Figure 5 shown, the electronic device 5 of this embodiment includes: a processor 501, a memory 502, and a computer program 503 stored in the memory 502 and executable on the processor 501. When the processor 501 executes the computer program 503, the steps in the above various method embodiments are implemented. Alternatively, when the processor 501 executes the computer program 503, the functions of each module / unit in the above various device embodiments are implemented.

[0160] The electronic device 5 may be a desktop computer, a notebook, a palm computer, a cloud server, or other electronic devices. The electronic device 5 may include, but is not limited to, the processor 501 and the memory 502. Those skilled in the art can understand that Figure 5 merely examples of the electronic device 5, and do not constitute a limitation to the electronic device 5, and may include more or fewer components than those shown in the figure, or different components.

[0161] The processor 501 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0162] The memory 502 may be an internal storage unit of the electronic device 5. For example, it can be the hard disk or memory of the electronic device 5. The memory 502 can also be an external storage device of the electronic device 5. For example, it can be a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, etc. equipped on the electronic device 5. The memory 502 can also include both the internal storage unit and the external storage device of the electronic device 5. The memory 502 is used to store computer programs and other programs and data required by the electronic device.

[0163] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiments can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated units can be implemented in the form of hardware or in the form of software functional units.

[0164] If the integrated module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium (such as a computer-readable storage medium). Based on this understanding, to implement all or part of the processes in the above method embodiments of the present application, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above method embodiments can be implemented. The computer program can include computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable storage medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0165] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included within the protection scope of the present application.

Claims

1. A method for adaptively estimating the tire slip angle, characterized in that Including: Collecting the motion state parameters of the vehicle during driving, where the motion state parameters at least include vehicle yaw rate, tire longitudinal force and lateral force, vehicle longitudinal and lateral acceleration, and vehicle tire steering angle; Processing the motion state parameters by using a preset first tire slip angle estimator to obtain a first tire slip angle estimation value; Processing the motion state parameters by using a preset second tire slip angle estimator to obtain a second tire slip angle estimation value; Based on a preset weight distribution strategy, determining a first weight coefficient assigned to the first tire slip angle estimation value and a second weight coefficient assigned to the second tire slip angle estimation value; Based on the acquired real-time road condition information and vehicle load, adaptively adjusting the first weight coefficient and the second weight coefficient to obtain a first adjusted weight coefficient and a second adjusted weight coefficient; Based on the first adjusted weight coefficient and the second adjusted weight coefficient, fusing the first tire slip angle estimation value and the second tire slip angle estimation value to obtain a fused tire slip angle estimation value.

2. The method according to claim 1, wherein Based on a preset weight distribution strategy, determining a first weight coefficient assigned to the first tire slip angle estimation value and a second weight coefficient assigned to the second tire slip angle estimation value, including: Obtaining a first tire slip angle reference value corresponding to the first tire slip angle estimation value and a second tire slip angle reference value corresponding to the second tire slip angle estimation value; Calculating a first error value between the first tire slip angle estimation value and the first tire slip angle reference value; Calculating a second error value between the second tire slip angle estimation value and the second tire slip angle reference value; Based on the first error value and the second error value, determining the first weight coefficient assigned to the first tire slip angle estimation value and the second weight coefficient assigned to the second tire slip angle estimation value.

3. The method according to claim 2, characterized in that, Based on the first error value and the second error value, determining the first weight coefficient assigned to the first tire slip angle estimation value and the second weight coefficient assigned to the second tire slip angle estimation value, including: Initializing a weight value search interval, where the weight value search interval is a numerical interval composed of a first search endpoint value to a second search endpoint value; Cyclically determining whether the first error value, the second error value, and the i-th search weight value satisfy a preset weight distribution condition according to a preset unit search interval, where the i-th search weight value is within the weight value search interval; If the first error value, the second error value, and the i-th search weight value satisfy the preset weight distribution condition, end the search, and based on the i-th search weight value, determine the first weight coefficient corresponding to the first tire slip angle estimation value and the second weight coefficient corresponding to the second tire slip angle estimation value.

4. The method according to claim 1, characterized in that, Based on the acquired real-time road condition information and vehicle load, adaptively adjusting the first weight coefficient and the second weight coefficient to obtain a first adjusted weight coefficient and a second adjusted weight coefficient, including: Determining the road surface type according to the real-time road condition information, where the real-time road condition information includes real-time road surface feature information; Estimate the current road surface adhesion coefficient of the vehicle based on the collected real-time driving speed and converted wheel speed; Correct the current road surface adhesion coefficient according to the road surface type to obtain a corrected road surface adhesion coefficient; Adaptively adjust the first weight coefficient and the second weight coefficient according to the corrected road surface adhesion coefficient and vehicle load to obtain a first adjusted weight coefficient and a second adjusted weight coefficient.

5. The method according to claim 4, characterized in that, Adapting the first weight coefficient and the second weight coefficient according to the corrected road surface adhesion coefficient and vehicle load to obtain a first adjusted weight coefficient and a second adjusted weight coefficient includes: If it is determined that the vehicle is in a first vehicle state based on the corrected road surface adhesion coefficient and vehicle load, increase the first weight coefficient to obtain a first adjusted weight coefficient, and decrease the second weight coefficient to obtain a second adjusted weight coefficient, where the increase ratio of the first weight coefficient is equal to the decrease ratio of the second weight coefficient; If it is determined that the vehicle is in a second vehicle state based on the corrected road surface adhesion coefficient and vehicle load, decrease the first weight coefficient to obtain a first adjusted weight coefficient, and increase the second weight coefficient to obtain a second adjusted weight coefficient, where the decrease ratio of the first weight coefficient is equal to the increase ratio of the second weight coefficient.

6. The method according to claim 1, characterized in that Fusing the first tire sideslip angle estimated value and the second tire sideslip angle estimated value based on the first adjusted weight coefficient and the second adjusted weight coefficient to obtain a fused tire sideslip angle estimated value, including: Calculating a first fused estimated value based on the first adjusted weight coefficient and the first tire sideslip angle estimated value; Calculating a second fused estimated value based on the second adjusted weight coefficient and the second tire sideslip angle estimated value; Superimposing the first fused estimated value and the second fused estimated value to obtain a fused tire sideslip angle estimated value.

7. The method according to claim 1, characterized in that, The method further includes: Judging whether the fused tire sideslip angle estimated value reaches a preset tire sideslip angle critical value; If the fused tire sideslip angle estimated value reaches the preset tire sideslip angle critical value, trigger an active braking strategy and output an alarm message.

8. A tire slip angle adaptive estimation device, characterized in that, Including: A collection module configured to collect motion state parameters of the vehicle during driving, where the motion state parameters at least include vehicle yaw rate, tire longitudinal force and lateral force, vehicle longitudinal and lateral acceleration, and vehicle tire steering angle; A first processing module configured to process the motion state parameters by using a preset first tire sideslip angle estimator to obtain a first tire sideslip angle estimated value; A second processing module configured to process the motion state parameters by using a preset second tire sideslip angle estimator to obtain a second tire sideslip angle estimated value; A determination module configured to determine a first weight coefficient assigned to the first tire sideslip angle estimated value and a second weight coefficient assigned to the second tire sideslip angle estimated value based on a preset weight distribution strategy; An adjustment module, configured to adaptively adjust the first weight coefficient and the second weight coefficient based on the acquired real-time road condition information and vehicle load, to obtain a first adjusted weight coefficient and a second adjusted weight coefficient; A fusion module, configured to fuse the first tire slip angle estimated value and the second tire slip angle estimated value based on the first adjusted weight coefficient and the second adjusted weight coefficient, to obtain a fused tire slip angle estimated value.

9. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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