Vehicle anti-slip control method, device, system, storage medium and vehicle

Abstract

The application provides a vehicle anti-slip control method, device, system, storage medium and vehicle. The method comprises the following steps: obtaining a feedback compensation torque and an anti-slip control parameter of a driving wheel during vehicle driving; determining a feedforward compensation torque based on the anti-slip control parameter, a set target function, a constraint condition and a state equation by a model prediction control method such as MPC; obtaining a current anti-slip output torque by superimposing the feedforward compensation torque on the basis of the feedback compensation torque; and controlling the driving wheel based on the current anti-slip output torque to realize anti-slip control of the driving wheel. The method can predict the wheel slip trend, output the feedforward compensation torque as a compensation amount to inhibit slip in advance, improve the longitudinal stability of the vehicle, realize real-time control, dynamically adapt to different driving states of the vehicle, and achieve better control effect.

Description

Technical Field

[0001] This application relates to the field of vehicle control technology, and in particular to a vehicle anti-skid control method, device, system, storage medium, and vehicle. Background Technology

[0002] Vehicle anti-skid control technology is a core pillar of modern automotive safety. During start-up, rapid acceleration, or on low-traction surfaces (such as ice, snow, gravel, or wet surfaces), the drive wheels may spin and slip due to excessive power. This not only wastes power and accelerates tire wear but can also lead to loss of vehicle control. Vehicle anti-skid control technology reduces the vehicle's output torque or applies braking to the slipping wheels to suppress slippage, ensuring effective power transmission to the road surface and maintaining vehicle stability and directional controllability. The real-time performance and stability of anti-skid control are crucial for vehicle attitude control and safety.

[0003] However, the vehicle anti-skid control methods in related technologies either have large torque fluctuations when transitioning between icy and asphalt roads, or take a long time to implement control, resulting in poor real-time performance, large torque fluctuations, and insufficient dynamic adaptability. Summary of the Invention

[0004] This application provides a vehicle anti-skid control method, device, system, storage medium, and vehicle to solve the technical problems of vehicle anti-skid control methods in the related art, which either have large torque fluctuations when transitioning between icy and snowy roads and asphalt roads, or take a long time to control, resulting in poor real-time performance, large torque fluctuations, and insufficient dynamic adaptability.

[0005] This application provides a vehicle anti-skid control method applied to at least one drive wheel of a vehicle. The method includes: acquiring the feedback compensation torque and anti-skid control parameters of the drive wheel during vehicle operation; determining the feedforward compensation torque using a model predictive control method based on the anti-skid control parameters, a state equation, constraints, and an objective function; superimposing the feedforward compensation torque on the feedback compensation torque to obtain a current anti-skid output torque, and using the current anti-skid output torque to perform anti-skid control on the drive wheel; wherein the state equation is obtained based on the vehicle's longitudinal dynamics equation and a lightweight segmented affine tire model, the linear dividing point of the lightweight segmented affine tire model is determined based on the road adhesion coefficient of the road surface on which the vehicle travels, and the objective function includes the torque change rate and the slip ratio error, wherein the slip ratio error is the error between the predicted slip ratio and the reference slip ratio.

[0006] In one embodiment of this application, the construction method of the lightweight segmented affine tire model includes: obtaining a tire slip ratio calculation model of the drive wheel; determining the linear division boundary point based on the road adhesion coefficient, determining the linear region stiffness coefficient and the saturation region negative slope based on the peak adhesion coefficient, determining the peak longitudinal force based on the peak adhesion coefficient and the vertical load; and determining the lightweight segmented affine tire model based on the tire slip ratio calculation model, the linear division boundary point, the linear region stiffness coefficient, the saturation region negative slope, and the peak longitudinal force.

[0007] In one embodiment of this application, the state equation is constructed by: obtaining the vehicle longitudinal dynamics equation; deriving a continuous initial equation from the vehicle longitudinal dynamics equation; and performing Euler discretization on the continuous initial equation to obtain the state equation.

[0008] In one embodiment of this application, the initial equation includes the tire slip ratio change rate and the vehicle speed change rate, wherein the vehicle speed change rate is determined based on longitudinal force, driving resistance and vehicle mass, and the driving resistance is determined based on the vehicle speed and a preset driving resistance coefficient.

[0009] In one embodiment of this application, the objective function is constructed by: using the slip ratio error within the predicted time domain, the torque change rate within the controlled time domain, the slip ratio tracking weight, and the torque change rate penalty weight to construct the objective function, wherein the slip ratio tracking weight is determined based on vehicle speed, and the torque change rate penalty weight is determined based on the road surface adhesion coefficient.

[0010] In one embodiment of this application, the constraint conditions are determined based on the motor's output capability for driving torque, a preset torque change rate threshold, and an allowable slip ratio variation range. The output capability includes a maximum output torque and a minimum output torque. The allowable slip ratio variation range includes a maximum slip threshold and a minimum slip threshold. The maximum slip threshold is determined based on the linear dividing point. The preset torque change rate threshold is determined based on the road surface adhesion coefficient and the maximum output torque.

[0011] This application embodiment also provides a vehicle anti-skid control device applied to at least one drive wheel of a vehicle. The device includes: an acquisition module for acquiring the feedback compensation torque and anti-skid control parameters of the drive wheel during vehicle operation; a feedforward compensation torque determination module for determining the feedforward compensation torque using a model predictive control method based on the anti-skid control parameters, state equation, constraint conditions, and objective function; and an anti-skid control module for superimposing the feedforward compensation torque on the feedback compensation torque to obtain a current anti-skid output torque, and performing anti-skid control on the drive wheel using the current anti-skid output torque. The state equation is obtained based on the vehicle's longitudinal dynamics equation and a lightweight segmented affine tire model. The linear dividing point of the lightweight segmented affine tire model is determined based on the road adhesion coefficient of the road surface on which the vehicle travels. The objective function includes the torque change rate and slip ratio error, where the slip ratio error is the error between the predicted slip ratio and the reference slip ratio.

[0012] This application embodiment also provides a vehicle anti-skid control system, which includes a drive motor and a chassis domain controller, wherein: the chassis domain controller is used to acquire the feedback compensation torque and anti-skid control parameters of the drive wheels during vehicle operation; determine the feedforward compensation torque through a model predictive control method based on the anti-skid control parameters, state equation, constraint conditions, and objective function; and obtain the current anti-skid output torque by superimposing the feedforward compensation torque on the feedback compensation torque, wherein the state equation is obtained based on the vehicle longitudinal dynamics equation and a lightweight segmented affine tire model, the linear dividing point of the lightweight segmented affine tire model is determined based on the road adhesion coefficient of the road surface on which the vehicle is traveling, and the objective function includes the torque change rate and slip ratio error, wherein the slip ratio error is the error between the predicted slip ratio and the reference slip ratio; the drive motor is used to perform anti-skid control on the drive wheels through the current anti-skid output torque.

[0013] This application also provides an electronic device, including: a memory storing a computer program thereon; and a processor for executing the computer program in the memory to implement the steps of the method described in any of the above embodiments.

[0014] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the method described in any of the above embodiments.

[0015] This application also provides a vehicle that includes a vehicle anti-skid control system as described in the above embodiments, or performs the steps of the method described in any of the above embodiments.

[0016] Beneficial Effects: This application proposes a vehicle anti-skid control method, device, system, storage medium, and vehicle. The method acquires the feedback compensation torque and anti-skid control parameters of the drive wheels during vehicle operation. Based on these anti-skid control parameters, a set objective function, constraints, and state equations, a feedforward compensation torque is determined using model predictive control methods such as MPC. The feedforward compensation torque is then superimposed on the feedback compensation torque to obtain the current anti-skid output torque. Based on this current anti-skid output torque, the drive wheels are controlled to achieve anti-skid performance. By predicting wheel slippage trends, the feedforward compensation torque is output as a compensation amount to suppress slippage in advance, improving the vehicle's longitudinal stability. This method enables real-time control, dynamically adapts to different vehicle driving states, and achieves better control performance. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0018] In the attached diagram:

[0019] Figure 1 This is a schematic diagram illustrating an application scenario of a vehicle anti-skid control method provided in an embodiment of this application.

[0020] Figure 2 This is a schematic flowchart of a vehicle anti-skid control method provided in an embodiment of this application;

[0021] Figure 3 A schematic flowchart of a vehicle anti-skid control method provided in an embodiment of this application;

[0022] Figure 4 A schematic diagram of a vehicle anti-skid control device provided in an embodiment of this application;

[0023] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0024] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0025] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. The drawings only show the components related to this application and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0026] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the present application. However, it will be apparent to those skilled in the art that embodiments of the present application may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the present application.

[0027] In related technologies, the following strategies can be adopted for vehicle anti-skid control, but these strategies also have certain shortcomings, such as poor real-time performance, large torque fluctuations, insufficient dynamic adaptability, and the inability to meet user needs in terms of anti-skid effect, resulting in a poor user experience.

[0028] PID (Proportion-Integral-Derivative) control dynamically adjusts PID parameters based on vehicle speed and wheel speed errors, and uses feedforward compensation to cover driver torque requests. This algorithm can compensate for the poor accuracy of feedback control with feedforward control, but it cannot handle sudden road surface changes (such as ice-to-asphalt transitions), has poor predictability for slippage leading to excessive control overshoot, and its parameter scheduling relies on preset rules, making it difficult to adapt to unmodeled conditions, such as low-adhesion hill starts.

[0029] Pure MPC (Model Predictive Control) uses the Magic Formula tire model to predict the slip ratio and generates torque commands by solving a multi-objective optimization problem. This algorithm can predict wheel slip trends and output compensation to suppress slip in advance. However, its single solution time is greater than 5ms, it cannot meet the 10kHz control cycle, and it cannot handle actuator delay issues, resulting in slow control and execution response and poor real-time performance.

[0030] Fuzzy / adaptive PID control has a delayed response on ice surfaces and only adjusts PID parameters locally, failing to address the problem of sudden torque changes. In complex operating conditions (such as cornering acceleration), the rule base needs to be manually adjusted.

[0031] In view of this, a vehicle anti-skid control method is proposed, which constructs an anti-skid control algorithm with a two-layer collaborative control architecture of "MPC feedforward compensation + PID feedback correction". By constructing a piecewise affine tire real-time linearization oriented towards MPC, the real-time performance and stability of anti-skid control are improved, enhancing the vehicle's longitudinal stability. By penalizing the slip ratio and torque change rate, the method avoids the problems of sudden torque changes caused by introducing a torque change rate penalty term and dynamic safety constraints into the rolling optimization objective, and updating key parameters with the road adhesion coefficient, while only optimizing the slip ratio error. By associating the maximum slip threshold with the linear separation point of the slip ratio, the vehicle always operates within the linear stability region of the tire. By limiting the torque change rate and coupling it with the road adhesion coefficient, the method achieves the effect of maximizing vehicle performance on high-adhesion surfaces and ensuring control safety margins on low-adhesion surfaces. It should be noted that the high and low adhesion here can be determined using an adhesion classification threshold preset by those skilled in the art. Road surfaces with adhesion values ​​greater than the adhesion classification threshold are considered high-adhesion road surfaces, while those with adhesion values ​​less than the adhesion classification threshold are considered low-adhesion road surfaces. The adhesion classification threshold can be set by those skilled in the art based on at least one of the following factors: vehicle type, vehicle driving area, and current driving environment.

[0032] Please see Figure 1 , Figure 1 This is a schematic diagram illustrating an application scenario of a vehicle anti-skid control method provided in an embodiment of this application. For example... Figure 1 As shown in the diagram, this is a schematic of a car chassis. Taking a four-wheeled vehicle as an example, each wheel is equipped with a corresponding wheel speed sensor and drive motor. The chassis domain controller controls the lifting and lowering torque of the corresponding drive motor. Using the vehicle anti-slip control method provided in this embodiment, the current anti-slip output torque of the corresponding wheel can be determined, thereby achieving wheel anti-slip control. The wheel speed sensor can be used to calculate wheel speed error. The anti-slip control algorithm, through the chassis domain controller, controls the lifting and lowering torque of the vehicle motor to achieve wheel anti-slip control. Figure 1 The number of wheels, drive motors, and control methods of the drive motors in this embodiment are merely examples and do not limit the vehicle anti-skid control method provided in this embodiment to be applied only to this scenario. For example, the vehicle may not use a chassis domain controller, in which case the controller currently capable of controlling the drive motors can be used to control the lifting torque of the corresponding drive motors. Furthermore, the vehicle may not have a drive motor on every wheel; in this case, the method can be applied to the wheels equipped with drive motors, i.e., the drive wheels in this application, and is not limited to vehicles where every wheel is equipped with a drive motor.

[0033] It should be noted that the above scenario is only an example of an application scenario provided by the embodiments of this application. The embodiments of this application do not limit the actual form of various devices, components, etc. included in the scenario. In the specific application of the solution, it can be set according to actual needs.

[0034] The following example illustrates the vehicle anti-skid control method provided in this application by applying it to one drive wheel of a vehicle. Please refer to [link to relevant documentation]. Figure 2 , Figure 2 A schematic flowchart of a vehicle anti-skid control method provided in an embodiment of this application is shown below. Figure 2 As shown, the method includes the following steps:

[0035] Step S210: During vehicle operation, obtain the feedback compensation torque and anti-slip control parameters of the drive wheels.

[0036] The feedback compensation torque can be determined using methods known to those skilled in the art. For example, a PID control scheme can be used to obtain the output feedback compensation torque.

[0037] As an example, real-time errors can be eliminated by using feedback compensation torque. The feedback compensation torque is determined as follows:

[0038] Formula (1),

[0039] Formula (2),

[0040] In the formula, These are preset coefficients used for unit conversion; K is 1, and the unit is Nm. To provide feedback and compensation torque, For wheel speed error, , , These are the proportional coefficient, integral coefficient, and differential coefficient, respectively. For the target wheel speed, This is the actual wheel speed. The rate of change of wheel speed error can be determined by analyzing the wheel speed error. Differentiating yields the result.

[0041] The specific calculation method for the feedback compensation torque can be implemented in a manner known to those skilled in the art, and will not be elaborated here. The target wheel speed can be set according to the needs of those skilled in the art.

[0042] Anti-skid control parameters include, but are not limited to, at least one of the following: wheel angular velocity, wheel radius, wheel longitudinal velocity, road surface adhesion coefficient, peak adhesion coefficient, vertical load, wheel moment of inertia, drive torque, longitudinal force, longitudinal acceleration, vehicle mass, control cycle, preset driving resistance coefficient, preset time domain length, control time domain length, maximum output torque, minimum output torque, preset safety margin, target slip ratio, and relevant physical quantities used to construct the vehicle's longitudinal dynamics equations. The peak adhesion coefficient is the ratio of the maximum friction force that the tire can provide between the tire and the road surface to the vertical load on the tire. The controller cycle is the time required for the system to complete one full control cycle. The maximum output torque is the maximum torque value allowed to be output by the drive motor. The minimum output torque is the maximum torque value allowed to be output by the drive motor (generally a negative value). The prediction time domain length is the time range within which the controller predicts the future output of the system. The control time domain length is the time range within which the future control action sequence needs to be calculated and optimized.

[0043] Anti-skid control parameters can be obtained in a manner known to those skilled in the art, including but not limited to those collected by various sensors installed on the vehicle or calculated in a manner known to those skilled in the art.

[0044] As mentioned in the previous embodiments, the inventors found that if only PID control is used, the control effect is not good for sudden road surface changes and unmodeled working conditions. Therefore, if feedforward prediction compensation is added on this basis, the anti-skid control algorithm can be formulated through a two-layer collaborative control architecture of "MPC feedforward compensation + PID feedback correction" to make up for the above defects and improve the control effect.

[0045] Step S220: Based on the anti-slip control parameters, state equations, constraints, and objective function, determine the feedforward compensation torque using model predictive control methods.

[0046] The objective function is established with the goal of maximizing vehicle performance on high-adhesion surfaces and ensuring control safety margins on low-adhesion surfaces.

[0047] The state equation is derived from the vehicle's longitudinal dynamics equation and the lightweight segmented affine tire model. The linear dividing point of the lightweight segmented affine tire model is determined based on the road adhesion coefficient of the road surface on which the vehicle travels. The objective function includes the torque change rate and the slip ratio error, where the slip ratio error is the error between the predicted slip ratio and the reference slip ratio.

[0048] In one embodiment, the construction method of the lightweight segmented affine tire model includes: obtaining a tire slip ratio calculation model of the drive wheel; determining the linear division boundary point based on the road adhesion coefficient, determining the linear region stiffness coefficient and the saturation region negative slope based on the peak adhesion coefficient, determining the peak longitudinal force based on the peak adhesion coefficient and the vertical load; and determining the lightweight segmented affine tire model based on the tire slip ratio calculation model, the linear division boundary point, the linear region stiffness coefficient, the saturation region negative slope, and the peak longitudinal force.

[0049] For example, the linear dividing point is used because the tire longitudinal force increases approximately linearly with the slip ratio in the linear region, and the increase of the tire longitudinal force slows down and decays after reaching a peak in the saturation region. Therefore, a linear dividing point is set to express the tire longitudinal force.

[0050] Peak adhesion coefficient represents the ratio of the maximum friction force that the tire can provide between the tire and the road surface to the vertical load on the tire.

[0051] Peak longitudinal force represents the maximum longitudinal force that the ground can provide to the tire when the wheel is not slipping.

[0052] The inventors discovered that the computationally complex precise tire models in related technologies (such as Magic Formula) cannot meet the real-time requirements of MPC, and the fixed linear model has an error of >30% on low-friction surfaces. Therefore, a segmented affine tire model can be constructed to perform the relevant calculations. It should be noted that the units of the parameters provided in this embodiment are only examples, and those skilled in the art can choose according to their needs, which will not be elaborated further below.

[0053] The tire slip ratio calculation model can be obtained based on the tire slip ratio calculation formula known to those skilled in the art. In one example of related technology, the tire slip ratio can be calculated as follows: first, calculate the product of the wheel angular velocity and the wheel radius; then, subtract the product from the wheel longitudinal velocity to obtain the difference; finally, use the quotient of this difference and the wheel longitudinal velocity as the tire slip ratio.

[0054] To avoid abnormalities caused by the longitudinal speed of the wheel being 0, the denominator is adjusted to the form of formula (3).

[0055] As an example, the adjusted tire slip ratio calculation formula (tire slip ratio calculation model) is as follows:

[0056] Formula (3),

[0057] in, This refers to the tire slip ratio; The wheel's angular velocity is expressed in rad / s. Let the radius of the wheel be m; The longitudinal speed of the wheel (i.e., vehicle speed, which will not be elaborated further) is in m / s. The value "0.1" can also be set according to the needs of those skilled in the art; this is just an example.

[0058] As an example, a lightweight segmented affine tire model is shown below:

[0059] Formula (4),

[0060] in, Tire slip ratio The corresponding longitudinal force; The linear dividing point, , The estimated road surface adhesion coefficient; The stiffness coefficient for the linear region is N / %. , Peak adhesion coefficient; The slope is negative in the saturation region, N / %. ; The peak longitudinal force is N. , For vertical load, N; The saturation slip ratio is the critical point at which the longitudinal force reaches full saturation. Beyond this point, the tire force no longer changes significantly with increasing slip ratio (or even decreases), and the vehicle completely loses its steering ability. For example, a constant value of 0.3 can be used. This refers to the tire slip ratio.

[0061] As an example, the linear division boundary point, linear region stiffness coefficient, and saturation region negative slope of the segmented affine tire model are all related to the road adhesion coefficient. This allows the specific numerical value of the longitudinal force to be adaptively adjusted and updated in real time based on the road adhesion coefficient of the currently driven road surface, thereby improving the accuracy of anti-skid control. The determination of peak longitudinal force, vertical load, peak adhesion coefficient, and road adhesion coefficient can be achieved using methods known to those skilled in the art.

[0062] In one embodiment, the state equation is constructed by: obtaining the vehicle's longitudinal dynamics equation; deriving a continuous initial equation from the vehicle's longitudinal dynamics equation; and performing Euler discretization on the continuous initial equation to obtain the state equation.

[0063] The initial equations include the tire slip ratio change rate and the vehicle speed change rate. The vehicle speed change rate is determined based on the longitudinal force, driving resistance, and vehicle mass, while the driving resistance is determined based on the vehicle speed and a preset driving resistance coefficient. The vehicle speed here is the same as the wheel longitudinal speed mentioned earlier.

[0064] As an example, continuous initial equations can be derived based on the vehicle's longitudinal dynamics equations. One example of initial equations is as follows:

[0065]

[0066] In the formula, This refers to the tire slip ratio; Let the radius of the wheel be m; For the moment of inertia of the wheel, ; For the longitudinal speed of the vehicle, To drive torque, ; For longitudinal force, ; For longitudinal acceleration, ; The resistance to travel is N; For the overall vehicle quality, , This represents the rate of change of tire slip ratio. This represents the rate of change of vehicle speed.

[0067] The tire slip ratio can be calculated based on formula (2), the longitudinal force can be calculated based on formula (3), and the wheel radius, wheel moment of inertia, vehicle longitudinal speed, driving torque, and vehicle mass can be obtained based on the acquired anti-skid control parameters or through other means known to those skilled in the art.

[0068] As an example, one method for determining driving resistance is illustrated below:

[0069] Formula (6),

[0070] In the formula, For driving resistance, , , The coefficient for calculating driving resistance is determined based on coasting tests of different vehicle models, and can also be set by those skilled in the art as needed. For the longitudinal speed of the vehicle, .

[0071] To ensure real-time computation, the continuous initial equations are discretized using Euler methods as follows:

[0072] Formula (7),

[0073] In the formula, To control the cycle; Let K be the tire slip ratio at time k+1. Let k be the tire slip ratio at time k; Let be the longitudinal velocity of the vehicle at time k+1; Let k be the longitudinal velocity of the vehicle at time k. The radius of the wheel; For the moment of inertia of the wheel The driving torque at time k; Let be the longitudinal force at time k, considering the tire slip ratio. ; Let k be the longitudinal acceleration at time k. Let K be the driving resistance at time k; For the overall vehicle weight.

[0074] In one embodiment, the objective function is constructed by using the slip ratio error within the predicted time domain, the torque change rate within the controlled time domain, the slip ratio tracking weight, and the torque change rate penalty weight to construct the objective function, wherein the slip ratio tracking weight is determined based on the vehicle speed, and the torque change rate penalty weight is determined based on the road surface adhesion coefficient.

[0075] As an example, the objective function is as follows:

[0076] Formula (8),

[0077] In the formula, To predict the length of the time domain; To control the length of the time domain, ; Target slip ratio; The rate of change of torque; This is the predicted value of the tire slip ratio at the current time k+i. For slip ratio tracking weights, The penalty weight for the rate of change of torque, This is the predicted value of the torque change rate at time k+i in the future.

[0078] As an example, the slip ratio tracking weight and torque change rate penalty weight are determined as follows. Of course, those skilled in the art can use other setting methods as needed. The following is only an example:

[0079] Formula (9),

[0080] In the formula, The slip ratio tracking weight can be adaptively adjusted at speed; This is a constant value; as an example, it can be initially set to 50, but those skilled in the art can adjust it according to the control effect of the controller. The longitudinal speed of the wheel is denoted as , in m / s.

[0081] Formula (10),

[0082] In the formula, Weighted for the rate of change of torque; This is a constant value; as an example, it can be initially set to 0.5, but those skilled in the art can adjust it according to the control effect of the controller. The value is the estimated road surface adhesion coefficient; "0.01" is a preset constant, which is only an example and can be modified according to the needs of those skilled in the art.

[0083] By penalizing slip ratio and torque change rate, the problem of sudden torque changes caused by optimizing slip ratio error alone is avoided.

[0084] As an example, the feedforward compensation torque is determined by model predictive control based on the anti-slip control parameters, state equation, constraints, and objective function. This includes updating parameters such as the constraints and penalty terms in the objective function based on real-time anti-slip control parameters, and solving for a series of torque change rates at multiple future time points. The feedforward compensation torque is then determined using the torque change rate at the current time and the output torque at the current time in this torque change rate series.

[0085] In one embodiment, the constraints are determined based on the motor's output capability for driving torque, a preset torque change rate threshold, and an allowable slip ratio variation range. The output capability includes the maximum output torque and the minimum output torque, and the allowable slip ratio variation range includes the maximum slip threshold and the minimum slip threshold. The maximum slip threshold is determined based on the linearity dividing point, and the preset torque change rate threshold is determined based on the road surface adhesion coefficient and the maximum output torque.

[0086] As an example, the constraints for MPC control are:

[0087] Formula (11),

[0088] In the formula, Minimum output torque; This is the maximum output torque; The output torque at the current moment k; Let k be the rate of change of torque at the current moment; The preset torque change rate threshold; The maximum slip threshold; Minimum slip threshold; This is the predicted value of the tire slip ratio at time k+i in the future.

[0089] As an example, the preset torque change rate threshold can be determined in the following way:

[0090] Formula (12),

[0091] In the formula, The preset torque change rate threshold; This is the maximum output torque; "0.2" represents the estimated road surface adhesion coefficient; "0.2" is a pre-set constant, which can be set by those skilled in the art as needed, and is merely an example here. This limiting method allows for the limitation of torque variation rate on low-adhesion road surfaces.

[0092] As an example, the maximum slip threshold can be determined as follows:

[0093] Formula (13),

[0094] In the formula, The maximum slip threshold; The linear dividing point is "0.05". "0.05" is a preset constant, which can be set by those skilled in the art as needed. This is just an example, representing a 5% safety margin.

[0095] By linking the maximum slip threshold to the linear dividing point of the slip ratio and reserving a 5% safety margin, the vehicle can be ensured to always operate within the linear stability region of the tires, preventing it from easily entering the saturation zone even with control errors or sudden road surface changes. On icy and snowy roads, the rate of torque change is strictly limited (only small increases or decreases in torque are allowed each time) to prevent wheel slippage due to sudden torque changes; while on dry roads, a larger rate of torque change is allowed to improve response speed. This is achieved by dynamically coupling the tire's physical boundaries with the actuator's dynamic limiting: high-friction surfaces allow the vehicle to reach its performance limits, while low-friction surfaces ensure a control safety margin.

[0096] Feedforward predicts future slip risk using MPC, and outputs the compensation amount as follows:

[0097] Formula (14),

[0098] In the formula, For feedforward compensation torque, The torque is calculated for the MPC feedforward controller.

[0099] Step S230: The current anti-slip output torque is obtained by superimposing the feedforward compensation torque on the feedback compensation torque, and the drive wheel is controlled for anti-slip by the current anti-slip output torque.

[0100] As an example, the current anti-slip output torque is determined as follows:

[0101] Formula (15),

[0102] In the formula, This is the current anti-slip output torque; For feedforward compensation torque; This is for feedback compensation torque.

[0103] The above example illustrates the method using a drive wheel of a vehicle as an example.

[0104] As mentioned above, the drive wheels can be wheels controlled by a corresponding motor. As an example, this method can be applied to vehicles in a broader sense, such as "four-wheel drive" and "two-wheel drive" vehicles.

[0105] When this method is applied to a two-wheel drive vehicle with four tires, the relevant parameters at the wheel end in the embodiment can be replaced by the relevant parameters at the axle end when collecting anti-skid control parameters. In other words, in such cases, the relevant parameters at the wheel end mentioned in the embodiments of this application are actually the relevant parameters at the axle end.

[0106] In another embodiment, the method can also be applied to one or more drive wheels in the vehicle to achieve anti-skid measures for one or more wheels. Of course, applying the method provided in this embodiment to each drive wheel can achieve a better anti-skid effect. However, those skilled in the art can also choose to apply the anti-skid control method provided in this embodiment to some wheels of the vehicle, while using anti-skid control methods known to those skilled in the art to other wheels; or choose to apply the anti-skid control method provided in this embodiment to some wheels of the vehicle, while not using anti-skid control methods to other wheels; or choose to apply the anti-skid control method provided in this embodiment to some wheels of the vehicle, while not using anti-skid control methods to other wheels, and using anti-skid control methods known to those skilled in the art to the remaining wheels.

[0107] In another embodiment, the anti-skid control strategy for the wheels can be switched as needed during vehicle operation, and different anti-skid control strategies can be applied to the same wheel on different road sections.

[0108] The vehicle anti-skid control method provided in the above embodiments acquires the feedback compensation torque and anti-skid control parameters of the drive wheel during vehicle operation. Based on the anti-skid control parameters, the set objective function, constraints, and state equations, a feedforward compensation torque is determined using a model predictive control method such as MPC. The feedforward compensation torque is then superimposed on the feedback compensation torque to obtain the current anti-skid output torque. Based on this current anti-skid output torque, the drive wheel is controlled to achieve anti-skid operation. By predicting the wheel slippage trend, the feedforward compensation torque is output as a compensation amount to suppress slippage in advance, improving the longitudinal stability of the vehicle. This method enables real-time control, dynamically adapts to different driving states of the vehicle, and achieves better control performance.

[0109] The vehicle anti-skid control method provided in the above embodiments reduces overshoot and torque fluctuations on icy-asphalt roads and improves response speed through three core technologies: lightweight model (constructing a lightweight segmented affine tire model), innovative optimization targets (dynamic weights), and adaptive constraints (binding tire characteristics). Dynamic constraints eliminate the risk of loss of control, and dynamic actuator limiting suppresses sudden torque changes on icy and snowy roads, providing a highly reliable control kernel for drive-by-wire chassis. Specifically:

[0110] The lightweight segmented affine tire model construction solves the problems of traditional accurate tire models (such as Magic Formula) being computationally complex and unable to meet the real-time requirements of MPC, as well as the fixed linear model having an error of >30% on low-friction surfaces.

[0111] Rolling optimization objective function creation: By penalizing slip ratio and torque change rate, the problem of torque abrupt changes caused by optimizing only slip ratio error is avoided.

[0112] Dynamic safety constraint design: By associating the maximum slip threshold with the linear separation point of the slip ratio, the vehicle always operates within the linear stability region of the tires; by coupling the rate of change of torque with the road adhesion coefficient, the vehicle's performance is maximized on high-adhesion roads and control safety margins are ensured on low-adhesion roads.

[0113] The dual-layer collaborative control architecture of MPC feedforward compensation + PID feedback correction: MPC feedforward control can predict wheel slippage trends and output compensation to suppress slippage in advance, thereby improving the longitudinal stability of the vehicle.

[0114] In summary, the anti-skid control algorithm, which constructs a two-layer collaborative control architecture of "MPC feedforward compensation + PID feedback correction", improves the real-time performance and stability of anti-skid control and enhances the longitudinal stability of the vehicle by building a segmented affine tire real-time linearization model oriented towards MPC, introducing a torque change rate penalty term and dynamic safety constraints into the rolling optimization objective, and updating key parameters online with the road adhesion coefficient.

[0115] As an example, see Figure 3 , Figure 3 A specific flowchart illustrating a vehicle anti-skid control method provided in an embodiment of this application is shown below. Figure 3 As shown, when the vehicle driver requests torque, it triggers the steps of feedforward compensation from the MPC controller and feedback compensation from the PID controller. The feedforward compensation torque and feedback compensation torque are calculated respectively, and the current anti-slip output torque is calculated based on both. Figure 3 The total torque is transmitted to the vehicle system, controlling the corresponding drive wheels of the vehicle, which will result in a corresponding change in the vehicle state. Then, new anti-slip control parameters are collected under the new vehicle state, and the objective function, constraints, state equations, etc. are updated. A new feedforward compensation torque is calculated, and so on, to achieve real-time control of the vehicle.

[0116] In one embodiment, a vehicle anti-skid control device is provided, which is used to execute the vehicle anti-skid control method provided in any of the above embodiments and is applied to at least one drive wheel of a vehicle. See also... Figure 4 , Figure 4 A schematic diagram of a vehicle anti-skid control device provided in an embodiment of this application is shown below. Figure 4 As shown, the vehicle anti-skid control device 400 includes an acquisition module 410, a feedforward compensation torque determination module 420, and an anti-skid control module 430. The acquisition module 410 acquires the feedback compensation torque and anti-skid control parameters of the drive wheels during vehicle operation. The feedforward compensation torque determination module 420 determines the feedforward compensation torque using a model predictive control method based on the anti-skid control parameters, state equation, constraints, and objective function. The anti-skid control module 430 superimposes the feedforward compensation torque onto the feedback compensation torque to obtain the current anti-skid output torque, and performs anti-skid control based on the current anti-skid output torque. The state equation is based on the vehicle's longitudinal dynamics equation and a lightweight segmented affine tire model. The linear dividing point of the lightweight segmented affine tire model is determined based on the road adhesion coefficient of the road surface on which the vehicle travels. The objective function includes the torque change rate and the slip ratio error, where the slip ratio error is the error between the predicted slip ratio and the reference slip ratio.

[0117] In one embodiment, the device further includes a dynamic update module for updating the objective function and constraints based on anti-skid control parameters, and for selecting sub-models in the lightweight segmented affine tire model.

[0118] Specific limitations regarding vehicle anti-skid control devices can be found in the limitations of vehicle anti-skid control methods described above, and will not be repeated here. Each module in the aforementioned vehicle anti-skid control device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in the electronic device, or stored in the memory of the electronic device as software, so that the processor can call and execute the corresponding operations of each module.

[0119] In this embodiment, the vehicle anti-skid control device is essentially equipped with multiple modules to execute the vehicle anti-skid control method in any of the above embodiments. The specific functions and technical effects can be referred to in the above embodiments, and will not be repeated here.

[0120] See Figure 5 , Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of this application is shown below. Figure 5 As shown, this embodiment of the invention also provides an electronic device 500, including a processor 501, a memory 502, and a communication bus 503; the communication bus 503 is used to connect the processor 501 and the memory 502; the processor 501 is used to execute a computer program stored in the memory 502 to implement the method provided in any of the above embodiments.

[0121] In one embodiment, a vehicle anti-skid control system is provided, comprising a drive motor and a chassis domain controller, wherein: the chassis domain controller is used to acquire the feedback compensation torque and anti-skid control parameters of the drive wheels during vehicle operation; determine the feedforward compensation torque through a model predictive control method based on the anti-skid control parameters, state equation, constraints, and objective function; and obtain the current anti-skid output torque by superimposing the feedforward compensation torque on the feedback compensation torque, wherein the state equation is obtained based on the vehicle longitudinal dynamics equation and a lightweight segmented affine tire model, the linear dividing point of the lightweight segmented affine tire model is determined based on the road adhesion coefficient of the road surface on which the vehicle is traveling, and the objective function includes the torque change rate and the slip ratio error, the slip ratio error being the error between the predicted slip ratio and the reference slip ratio; the drive motor is used to perform anti-skid control on the drive wheels using the current anti-skid output torque.

[0122] Following the above embodiments, the vehicle anti-skid control system also includes a wheel speed sensor for collecting the actual wheel speed and determining the feedback supplementary torque based on the actual wheel speed and the target wheel speed.

[0123] Specific limitations regarding vehicle anti-skid control systems can be found in the limitations of vehicle anti-skid control methods described above, and will not be repeated here. Each module in the aforementioned vehicle anti-skid control system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in the electronic device, or stored in the memory of the electronic device as software, so that the processor can call and execute the corresponding operations of each module.

[0124] In one embodiment, a vehicle is provided that includes the electronic equipment provided in any of the above embodiments, or performs the method provided in any of the above embodiments, or performs the vehicle anti-skid control system provided in any of the above embodiments. The specific functions and technical effects of this vehicle can be referred to the above embodiments, and will not be repeated here.

[0125] This invention also provides a computer-readable storage medium having a computer program stored thereon, the computer program being used to cause a computer to perform the method described in any of the above embodiments.

[0126] This application also provides a computer-readable storage medium storing one or more modules (programs) that, when applied to a device, enable the device to execute the instructions included in the steps provided in this application.

[0127] This application also provides a computer program product, including a computer program or instructions, which, when executed by a processor, can implement the steps and corresponding content of the aforementioned method embodiments.

[0128] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0129] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0130] Computer program code for performing the operations of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0131] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of methods and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0132] It should be understood that the terms "first," "second," etc., used in this application are used to distinguish similar objects and do not necessarily indicate a specific order or sequence. The technical features to which these terms are used can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in a sequence other than that shown in the figures or text.

[0133] It should be understood that although the flowcharts provided in the embodiments of this application indicate the various steps with arrows, the order indicated by the arrows does not necessarily limit the implementation order of these steps. Those skilled in the art can perform these steps in other orders according to different implementation scenarios and requirements.

[0134] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this application should still be covered by the claims of this application.

Claims

1. A vehicle anti-skid control method, characterized in that, Applied to at least one drive wheel of a vehicle, the method includes: During vehicle operation, the feedback compensation torque and anti-slip control parameters of the drive wheels are acquired; Based on the anti-slip control parameters, state equations, constraints, and objective function, the feedforward compensation torque is determined using a model predictive control method. The current anti-slip output torque is obtained by superimposing the feedforward compensation torque on the feedback compensation torque, and the drive wheel is controlled for anti-slip by using the current anti-slip output torque; The state equation is derived from the vehicle's longitudinal dynamics equation and a lightweight segmented affine tire model. The linear dividing point of the lightweight segmented affine tire model is determined based on the road adhesion coefficient of the road surface on which the vehicle travels. The objective function includes torque change rate and slip ratio error. The slip ratio error is the error between the predicted slip ratio and the reference slip ratio. The objective function is constructed by using the slip ratio error in the predicted time domain, the torque change rate in the controlled time domain, the slip ratio tracking weight, and the torque change rate penalty weight. The slip ratio tracking weight is determined based on the vehicle speed, and the torque change rate penalty weight is determined based on the road adhesion coefficient.

2. The vehicle anti-skid control method as described in claim 1, characterized in that, The construction method of the lightweight segmented affine tire model includes: Obtain the tire slip ratio calculation model for the drive wheel; The linear zone boundary point is determined based on the road surface adhesion coefficient, the linear zone stiffness coefficient and the saturation zone negative slope are determined based on the peak adhesion coefficient, and the peak longitudinal force is determined based on the peak adhesion coefficient and the vertical load. The lightweight segmented affine tire model is determined based on the tire slip ratio calculation model, the linear region boundary point, the linear region stiffness coefficient, the negative slope of the saturation region, and the peak longitudinal force.

3. The vehicle anti-skid control method as described in claim 2, characterized in that, The state equations are constructed in the following ways: Obtain the longitudinal dynamic equations of the vehicle; The longitudinal dynamics equations of the vehicle are derived to obtain continuous initial equations; The state equations are obtained by Euler discretization of the continuous initial equations.

4. The vehicle anti-skid control method as described in claim 3, characterized in that, The initial equation includes the tire slip ratio change rate and the vehicle speed change rate. The vehicle speed change rate is determined based on longitudinal force, driving resistance, and vehicle mass. The driving resistance is determined based on vehicle speed and a preset driving resistance coefficient.

5. The vehicle anti-skid control method according to any one of claims 1-4, characterized in that, The constraints are determined based on the motor's output capability for driving torque, a preset torque change rate threshold, and an allowable slip ratio variation range. The output capability includes the maximum output torque and the minimum output torque. The allowable slip ratio variation range includes the maximum slip threshold and the minimum slip threshold. The maximum slip threshold is determined based on the linear dividing point. The preset torque change rate threshold is determined based on the road surface adhesion coefficient and the maximum output torque.

6. A vehicle anti-skid control device, characterized in that, The device is applied to at least one drive wheel of a vehicle and includes: The acquisition module is used to acquire the feedback compensation torque and anti-slip control parameters of the drive wheel during vehicle operation. The feedforward compensation torque determination module is used to determine the feedforward compensation torque based on the anti-slip control parameters, state equations, constraints and objective functions, using a model predictive control method. The anti-slip control module is used to obtain the current anti-slip output torque by superimposing the feedforward compensation torque on the feedback compensation torque, and to perform anti-slip control on the drive wheel using the current anti-slip output torque; The state equation is derived from the vehicle's longitudinal dynamics equation and a lightweight segmented affine tire model. The linear dividing point of the lightweight segmented affine tire model is determined based on the road adhesion coefficient of the road surface on which the vehicle travels. The objective function includes torque change rate and slip ratio error. The slip ratio error is the error between the predicted slip ratio and the reference slip ratio. The objective function is constructed by using the slip ratio error in the predicted time domain, the torque change rate in the controlled time domain, the slip ratio tracking weight, and the torque change rate penalty weight. The slip ratio tracking weight is determined based on the vehicle speed, and the torque change rate penalty weight is determined based on the road adhesion coefficient.

7. A vehicle anti-skid control system, characterized in that, The vehicle anti-skid control system includes a drive motor and a chassis domain controller, wherein: The chassis domain controller is used to acquire the feedback compensation torque and anti-slip control parameters of the drive wheels during vehicle operation; based on the anti-slip control parameters, state equation, constraints, and objective function, the feedforward compensation torque is determined using a model predictive control method; the current anti-slip output torque is obtained by superimposing the feedforward compensation torque on the feedback compensation torque, wherein the state equation is obtained based on the vehicle longitudinal dynamics equation and a lightweight segmented affine tire model, the linearity dividing point of the lightweight segmented affine tire model is determined based on the road adhesion coefficient of the road surface on which the vehicle is traveling, the objective function includes the torque change rate and slip ratio error, the slip ratio error being the error between the predicted slip ratio and the reference slip ratio, the objective function being constructed by using the slip ratio error in the predicted time domain, the torque change rate in the control time domain, the slip ratio tracking weight, and the torque change rate penalty weight, wherein the slip ratio tracking weight is determined based on the vehicle speed, and the torque change rate penalty weight is determined based on the road adhesion coefficient; The drive motor is used to perform anti-slip control on the drive wheel using the current anti-slip output torque.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

9. A vehicle, characterized in that, The vehicle includes the vehicle anti-skid control system as described in claim 7, or performs the steps of the method as described in any one of claims 1 to 5.

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