Method for controlling running stability of distributed wheel-driven heavy tractor

Abstract

A driving stability control method for a distributed wheel-side-driven heavy-duty tractor relates to the technical field of vehicle brake control and comprises the following steps: S1, establishing a two-degree-of-freedom three-axis vehicle handling stability model of the heavy-duty tractor, and calculating a side slip angle expected value and a yaw velocity expected value; s2, the stability of the automobile is judged according to the yaw velocity threshold value and the stability index; s3, if the vehicle is out of the stable region, establishing a three-axle vehicle prediction model based on a model prediction control theory, and deciding a front wheel additional rotation angle and an additional yaw moment which meet a control target; if so, the model prediction controller does not participate in work; s4, the decided front wheel additional turning angle directly acts on a front steering wheel; and the additional yawing moment of the whole vehicle is distributed to all the driving wheels through a regular driving force control distribution method, and the additional driving moment of all the driving wheels is obtained.

Description

Technical Field

[0001] The invention relates to the technical field of vehicle safety control, and in particular to a method for controlling the driving stability of a distributed wheel-side driven heavy-duty tractor. Background Art

[0002] Distributed wheel-drive vehicles have the advantages of being more reliable, coordinated and flexible than centralized drive vehicles because each drive wheel can be driven and braked independently, and the torque of each drive wheel can be distributed autonomously within a certain range.

[0003] In vehicle active safety control technology, since the direct yaw moment control system of distributed wheel-side drive vehicles can control the longitudinal force of each drive wheel to generate an accessory yaw moment to correct the motion state of the entire vehicle by differential movement of the inner and outer wheels, many current driving stability control methods have fully utilized the many advantages of distributed drive vehicles in active safety control.

[0004] However, for example, a distributed drive vehicle driving stability control method disclosed in Chinese patent publication number CN112644455A, and a distributed drive vehicle steering stability control system and control method thereof disclosed in Chinese patent publication number CN112644457A, the research on the driving stability control method of distributed drive vehicles in the prior art is mainly applied in the field of two-axle vehicle control, and is rarely applied in the field of heavy-duty commercial vehicles with three or more axles. In order to fill this technical gap, the present invention provides a distributed wheel-side drive heavy-duty tractor driving stability control method. Summary of the invention

[0005] The present invention provides a distributed wheel-side driven heavy-duty tractor driving stability control method, the main purpose of which is to solve the problems existing in the prior art.

[0006] The present invention adopts the following technical solution:

[0007] A distributed wheel-side driven heavy-duty tractor driving stability control method comprises the following steps:

[0008] Step S1: Establish a two-degree-of-freedom three-axis vehicle handling stability model for a heavy-duty tractor according to the driver's driving operation and the vehicle state, and consider the steady-state steering and adhesion limit state of the vehicle, thereby obtaining the expected value β of the center of mass sideslip angle exp and the expected value of the yaw rate ω exp ;

[0009]

[0010] Where: a is the distance from the center of mass of the car to the front axle; b is the distance from the center of mass of the car to the middle axle; c is the distance from the center of mass of the car to the rear axle; δ 1 is the front wheel steering angle; are the comprehensive cornering stiffness of the front wheel, middle wheel and rear wheel respectively; m is the total mass of the vehicle; u is the longitudinal velocity of the center of mass of the vehicle; μ is the road adhesion coefficient;

[0011] Step S2: Calculate the yaw rate deviation Δω, the center of mass sideslip angle β and the center of mass sideslip angular velocity based on the two-degree-of-freedom three-axis vehicle handling stability model And according to the yaw rate threshold value K ω and stability index S β Determine the stability of the car, stability index S β The calculation formula is:

[0012]

[0013] Where: k is the slope of the stable boundary line; c is the intercept of the boundary line;

[0014] Step S3: If the vehicle is outside the stable region, a three-axis vehicle prediction model is established based on the model predictive control theory, and the driver's target vehicle speed and the actual value of the yaw angular velocity ω are used to predict the vehicle's rotation speed. r / Actual value of the sideslip angle β and the expected value of the yaw rate ω exp / Expected value of sideslip angle at center of mass β exp The deviation of the front wheel is used to determine the additional steering angle δ of the front wheel that meets the control target. 1 and the additional yaw moment T z ; If it is in the stable region, the model predictive controller does not participate in the work;

[0015] Step S4: The determined additional turning angle δ of the front wheel 1 Directly act on the front steering wheel; the vehicle additional yaw moment T is distributed by the regular driving force control method. z Distributed to each drive wheel, additional drive torque of each drive wheel is obtained.

[0016] Further, in step S1, the two-degree-of-freedom three-axle vehicle handling stability model adopts a three-axle heavy-duty tractor vehicle model supported on the ground by three lateral elastic tires and having two degrees of freedom, lateral and yaw, and its differential equation is:

[0017]

[0018] Where: I z is the moment of inertia of the vehicle; β is the sideslip angle of the vehicle's center of mass; is the lateral acceleration of the vehicle’s center of mass; ω r is the vehicle yaw angular velocity; is the vehicle's yaw angular acceleration.

[0019] Further, in step S2, the stability judgment standard of the vehicle is:

[0020] (1) If the stability index S β =0, the car is judged to be unstable;

[0021] (2) If the stability index S β ≠0 and yaw rate deviation Δω>K ω When the vehicle is judged to be unstable;

[0022] (3) If the stability index S β ≠0 and yaw rate deviation Δω≤K ω When the vehicle is determined to be stable, the vehicle stability will continue to be monitored.

[0023] Furthermore, in step S3, a two-degree-of-freedom three-axis vehicle handling stability model for a heavy-duty tractor with an additional yaw moment is used as a prediction model of the model predictive control theory, and its differential equation is:

[0024]

[0025] Where: T z is the additional yaw moment.

[0026] Further, in step S4, the rule driving force control allocation method is as follows:

[0027] (1) When it is necessary to correct the left understeer or right oversteer condition: the right wheel increases the driving torque, which generates a positive 1 / 4 additional yaw moment value; the left wheel reduces the driving torque, which generates a negative 1 / 4 additional yaw moment value;

[0028] (2) When it is necessary to correct the left oversteer or right understeer condition: the left wheel increases the driving torque, which generates a positive 1 / 4 additional yaw moment value; the right wheel reduces the driving torque, which generates a negative 1 / 4 additional yaw moment value.

[0029] Further, the additional yaw moment T is completed according to the rule-based driving force control distribution method. z After the control distribution, it should be further verified whether the sum of the driving torques of each driving wheel is equal to the total target driving torque:

[0030]

[0031] Where: T x_ij is the output torque of each wheel assembly of the wheel motor; r ij is the rolling radius of each driving wheel (ij=ml,mr,rl,rr represent the left wheel of the middle axle, the right wheel of the middle axle, the left wheel of the rear axle, and the right wheel of the rear axle respectively); Tx_req is the total target driving torque, which is calculated by the drive controller and obtained from the controller through the CAN bus.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] The main innovation of the present invention is to establish a two-degree-of-freedom three-axis vehicle handling stability model for heavy-duty tractors, and on this basis, based on the online real-time control characteristics of model predictive control and rule-based driving force distribution methods, additional yaw moment MPC control and driving force distribution are performed, thereby facilitating real-time control of the handling stability of distributed wheel-side drive heavy-duty tractors and improving the driving stability control efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a control flow chart of the present invention.

[0035] Figure 2 This is the two-degree-of-freedom three-axis vehicle handling stability model of the present invention.

[0036] Figure 3 This is a block diagram of the MPC control principle of the present invention. DETAILED DESCRIPTION

[0037] The specific implementation of the present invention is described below with reference to the accompanying drawings. In order to fully understand the present invention, many details are described below, but for those skilled in the art, the present invention can be implemented without these details.

[0038] The invention discloses a driving stability control method for a distributed wheel-side drive heavy-duty tractor. The main innovation of the control method is: establishing a two-degree-of-freedom three-axis vehicle handling stability model for a heavy-duty tractor, integrating stability indicators under nonlinear working conditions, and based on model predictive control with good online real-time performance, thereby performing MPC control of additional steering angle and additional yaw moment of the front wheels, and then using a regular driving force distribution method with small calculation amount and good control real-time performance to realize the distributed wheel-side drive distribution of the additional yaw moment, thereby maximally improving the driving stability and safety of the distributed wheel-side drive heavy-duty tractor.

[0039] like Figure 1 As shown, a distributed wheel-side drive heavy-duty tractor driving stability control method specifically includes the following steps:

[0040] Step S1: Establish a two-degree-of-freedom three-axis vehicle handling stability model for a heavy-duty tractor based on the driver's driving operation and the vehicle state, and consider the steady-state steering and adhesion limit state of the vehicle, thereby obtaining the expected value of the vehicle motion response, that is, the expected value of the center of mass sideslip angle β exp and the expected value of the yaw rate ω exp .

[0041] Specifically, the driver's driving operation and the vehicle state include but are not limited to the steering wheel angle operated by the driver, the longitudinal speed of the vehicle's center of mass, the lateral speed of the vehicle's center of mass, the position of the vehicle's center of mass, the wheel slip angle, the sideways stiffness, the vehicle's yaw rate, the longitudinal speed of the vehicle, the lateral speed of the vehicle and the sideslip angle of the vehicle's center of mass, etc. Among them, the longitudinal speed of the vehicle, the lateral speed of the vehicle and the sideslip angle of the center of mass cannot be obtained by sensors, so they need to be estimated by the vehicle speed estimator and the sideslip angle estimator.

[0042] like Figure 2 As shown, the two-degree-of-freedom three-axle vehicle handling stability model established according to the driver's driving operation and the vehicle state in this embodiment is based on a two-degree-of-freedom front-wheel steering three-axle heavy-duty tractor as an example. It is a vehicle model with two degrees of freedom, lateral and yaw, supported on the ground by three lateral elastic tires. The differential equation of the two-degree-of-freedom three-axle vehicle handling stability model of the heavy-duty tractor is:

[0043]

[0044] Where: m is the total mass of the vehicle; I z is the moment of inertia of the vehicle; β is the sideslip angle of the vehicle's center of mass; u is the longitudinal velocity of the vehicle's center of mass; v is the lateral velocity of the vehicle's center of mass; is the lateral acceleration of the vehicle’s center of mass; ω r is the vehicle yaw angular velocity; is the yaw angular acceleration of the vehicle; a is the distance from the center of mass of the vehicle to the front axle; b is the distance from the center of mass of the vehicle to the middle axle; c is the distance from the center of mass of the vehicle to the rear axle; L is the wheelbase of the front and rear axles; α 1 , α 2 , α 3 are the side slip angles of the front wheel, middle wheel and rear wheel respectively; δ 1 is the front wheel steering angle; They are the comprehensive cornering stiffness of the front wheel, middle wheel and rear wheel respectively.

[0045] In steady state, the car drives safely, so the yaw rate ω of the three-axis car handling stability model is r The steady-state response value of the sideslip angle β and the center of mass is used as the reference value for control. The steady-state response yaw rate ω r and the mass center sideslip angle β are both constant values, that is, the lateral acceleration of the vehicle's mass center Vehicle yaw acceleration From the above differential equation (1), we can get the yaw angular velocity ω r The calculation formula for the steady-state value of the center of mass sideslip angle β is:

[0046]

[0047] Where:

[0048] When the tire is in a saturated state, that is, when the car is in an adhesion limit state, the steady-state response value of the two-degree-of-freedom reference model is not suitable as a reference value. At this time, the reference value needs to be replaced by the boundary value.

[0049] Yaw angular velocity boundary value ω rbound The calculation formula is:

[0050]

[0051] Where: μ is the road adhesion coefficient.

[0052] Boundary value of center of mass sideslip angle β bound The calculation formula is:

[0053] |β bound |≤tan -1 (0.02μg) (4).

[0054] Therefore, considering the steady-state steering and adhesion limit state of the vehicle, the control system expected value model is:

[0055]

[0056] Where: β exp is the expected value of the sideslip angle at the center of mass; ω exp is the expected value of the yaw rate.

[0057] Step S2: Based on the two-degree-of-freedom three-axis vehicle handling stability model of the heavy tractor, the yaw rate deviation Δω, the center of mass sideslip angle β and the center of mass sideslip angular velocity are obtained. And according to the yaw rate threshold value K ω and stability index S β Determine the stability of the car. This step includes the following sub-steps:

[0058] Step S2.1: The longitudinal velocity u of the center of mass of the vehicle and the front wheel turning angle δ 1 The current road adhesion coefficient μ is input into the two-degree-of-freedom three-axis vehicle handling stability model in step 1 to obtain the yaw rate deviation Δω, the center of mass sideslip angle β and the center of mass sideslip angular velocity

[0059] Specifically, this step can be combined with the above formulas (1)-(5) to first calculate the expected value of the yaw angular velocity ω: exp 、Vehicle yaw angular velocity ω r and the sideslip angle β, then according to the expected value of the yaw rate ω exp and the vehicle's yaw rate ω rThe absolute difference between the yaw rate deviation Δω is obtained, and the center of mass sideslip angle β is further derived to obtain the center of mass sideslip angular velocity

[0060] Step S2.2: Substitute the center of mass slip angle β and the center of mass slip angular velocity Substitute into the stability index formula to calculate the stability index S β In this step, the stability index S is obtained. β The specific method of calculating the formula includes the following sub-steps:

[0061] Step S2.2.1: Obtain a second-order autonomous system based on the two-degree-of-freedom three-axle vehicle handling stability model of a heavy tractor:

[0062]

[0063] At a given center of mass longitudinal velocity u and front wheel steering angle δ 1 Next, different initial values ​​(β 0 ,ω r0 ), draw the phase trajectory of the system, and obtain the center of mass slip angle β-center of mass slip angular velocity Phase plane diagram.

[0064] Step S2.2.2: Divide using the two-line method The boundary equation of the vehicle stability region is constructed by the phase plane diagram method:

[0065]

[0066] Where k is the slope of the stable boundary line; c is the intercept of the boundary line; the values ​​of k and c are related to the factors affecting the phase plane.

[0067] Step S2.2.3: Define the shortest distance from the vehicle state point in the stability domain to the boundary of the stability domain as the instability, and further obtain the stability index formula as:

[0068]

[0069] In the phase plane, the state point satisfy When , the car is in the stable region of the phase plane; the state point satisfy The car is in the unstable area.

[0070] Step S23: According to the yaw rate threshold value K ω and stability index S β Determine the stability of the car. Specifically, the stability judgment criteria of the car are:

[0071] (1) If the stability index S β =0, the car is judged to be unstable;

[0072] (2) If the stability index S β ≠0 and yaw rate deviation Δω>K ω When the vehicle is judged to be unstable;

[0073] (3) If the stability index S β ≠0 and yaw rate deviation Δω≤K ω When the vehicle is determined to be stable, the vehicle stability will continue to be monitored.

[0074] Among them, K ω is the yaw rate threshold value. Different vehicle speeds correspond to different yaw rate threshold values.

[0075] Step S3: If the vehicle is out of the stable region (i.e., the vehicle is determined to be unstable in step S2), a three-axis vehicle prediction model is established based on the model predictive control theory, and the driver's target vehicle speed and the actual value of the yaw angular velocity ω are used to predict the vehicle's stability. r / Actual value of the sideslip angle β and the expected value of the yaw rate ω exp / Expected value of sideslip angle at center of mass β exp The deviation of the front wheel is used to determine the additional steering angle δ of the front wheel that meets the control target. 1 and the additional yaw moment T z If the vehicle is in the stable region (i.e. the vehicle is determined to be stable by step S2), the model predictive controller does not participate in the operation.

[0076] like Figure 3 As shown, if it is outside the stable domain, the specific processing flow includes the following steps:

[0077] Step S3.1: A two-degree-of-freedom three-axis vehicle handling stability model for heavy-duty tractors with an additional yaw moment is used as a prediction model for model predictive control, and its differential equation is:

[0078]

[0079] Where: m is the total mass of the vehicle; I z is the moment of inertia of the vehicle; β is the sideslip angle of the vehicle's center of mass; u is the longitudinal velocity of the vehicle's center of mass; v is the lateral velocity of the vehicle's center of mass; is the lateral acceleration of the vehicle’s center of mass; ω r is the vehicle yaw angular velocity; is the yaw angular acceleration of the vehicle; a is the distance from the center of mass of the vehicle to the front axle; b is the distance from the center of mass of the vehicle to the middle axle; c is the distance from the center of mass of the vehicle to the rear axle; L is the wheelbase of the front and rear axles; δ 1 is the front wheel steering angle; are the comprehensive cornering stiffness of the front wheel, middle wheel and rear wheel respectively; TZ is the additional yaw moment.

[0080] Let the state vector be X = [β ω r ] T , the input vector is U=[δ 1 T z ] T , the output vector is Y = [β ω r a y ] T , the prediction model of formula (9) is written as the state equation:

[0081]

[0082] Where: a y is the lateral acceleration of the vehicle's center of mass.

[0083] Furthermore, the prediction model is discretized and rewritten as an incremental model:

[0084]

[0085] In the formula, ΔX(k)=X(k)-X(k-1); ΔU(k)=U(k)-U(k-1); A and B are discrete matrices.

[0086] According to the predictive control principle, the initial condition is the latest measured value, and the future process is dynamically predicted based on the predictive model. The prediction time domain is set to p, the control time domain is set to n, and n <p。

[0087] X(k+i|k) represents the state prediction at time k for time k+i, and the k after the symbol "|" represents the current time. Y(k+i|k) is the output, ΔU(k+i) is the control increment, and ΔU(k+i)=0 outside the control time domain, i≥n.

[0088] Define a vector:

[0089] Y p (k+1|k)=[Y(k+1|k) Y(k+2|k) ... Y(k+p|k)] T

[0090] ΔU p (k)=[ΔU(k) ​​ΔU(k+1) ... ΔU(k+n-1)] T

[0091] The following equation is used to calculate the future system p-step output prediction:

[0092] Y p (k+1|k)=Sx ΔX(k)+IY(k)+S u ΔU(k) ​​(12)

[0093] In the formula, I=[I 2*2 I 2*2 ... I 2*2 ] T ;

[0094]

[0095] Step S3.2: Based on the above prediction results, perform rolling optimization to solve the following equation:

[0096] J = ‖Γ y (Y p (k+1|k)-R(k+1))‖ 2 +‖Γ u ΔU(k)‖ 2 (13)

[0097] In the formula, Γ y =diag(Γ y,1 , Γ y,2 , ..., Γ y,p ) is the deviation penalty coefficient matrix, Γ u =diag(Γ u,1 , Γ u,2 , ..., Γ u,n ) is the control increment penalty coefficient matrix, R(k+1) is the expected output value in the prediction time domain, that is, the expected value of the yaw angular velocity ω obtained based on the two-degree-of-freedom three-axis model exp and the expected value of the sideslip angle β exp , R(k+1)=[r(k+1) r(k+2) ... r(k+p)] T .

[0098] The algorithm assumes that the expected value is a constant in the prediction time domain and is equal to the current value, that is, r(k+i)=r(k). Solving the equation, we get the following optimal control output sequence:

[0099]

[0100] Where: Control deviation E p (k+1|k)=R(k+1)-S x ΔX(k)-IY(k) can be calculated online.

[0101] According to the principle of model predictive control, in the prediction time domain, the algorithm assumes that the expected value of model predictive control remains unchanged, and the expected value is the output value of the reference model. The controller performs optimization calculations based on the penalty coefficient. In the objective function, the weight coefficient is adjusted by weighting the tracking deviation and the control amount to ensure reasonable control.

[0102] Step S4: Determined additional front wheel turning angle δ 1 Directly act on the front steering wheel; the vehicle additional yaw moment T is distributed by the regular driving force control method. z The additional driving torque of each driving wheel is distributed to each driving wheel to obtain the additional driving torque of each driving wheel, and it is ensured that the sum of the driving torque of each driving wheel is equal to the total target driving torque.

[0103] In this step, the additional yaw moment T is applied according to the following driving force control distribution method. z Control allocation:

[0104] (1) When it is necessary to correct the left understeer or right oversteer condition: the right wheel increases the driving torque, which generates a positive 1 / 4 additional yaw moment value; the left wheel reduces the driving torque, which generates a negative 1 / 4 additional yaw moment value;

[0105] (2) When it is necessary to correct the left oversteer or right understeer condition: the left wheel increases the driving torque, which generates a positive 1 / 4 additional yaw moment value; the right wheel reduces the driving torque, which generates a negative 1 / 4 additional yaw moment value.

[0106] At the same time, threshold control is set in the allocation algorithm to prevent negative values ​​of the driving torque of each wheel.

[0107] The additional yaw moment T is completed according to the rule-based driving force control distribution method. z After the control distribution, it is necessary to further verify whether the sum of the driving torques of each driving wheel is equal to the total target driving torque. Specifically, the longitudinal driving force F of the tire of each driving wheel x_ij The output torque of the wheel motor can be controlled:

[0108]

[0109] Where: T x_ij is the output torque of each wheel assembly of the wheel motor; r ij is the rolling radius of each driving wheel (ij=ml,mr,rl,rr represent the left wheel of the middle axle, the right wheel of the middle axle, the left wheel of the rear axle, and the right wheel of the rear axle respectively); T x_req is the total target driving torque, which can be calculated by the drive controller and obtained from the controller through the CAN bus.

[0110] Additional yaw moment T zThe longitudinal driving force of the control input is expressed as follows:

[0111] T z =B[F x_ml F x_mr F x_rl F x_rr ] T ,F x_ij ≥0 (16)

[0112] In the formula, d m is the center axle track; d r Rear axle track.

[0113] The above is only a specific implementation of the present invention, but the design concept of the present invention is not limited thereto. Any non-substantial changes to the present invention using this concept shall be deemed as an infringement of the protection scope of the present invention.

Claims

1. A distributed wheel-drive heavy-duty tractor driving stability control method, characterized in that: The steps include: Step S1: Establish a two-degree-of-freedom three-axis vehicle handling stability model for a heavy-duty tractor according to the driver's driving operation and the vehicle state, and consider the steady-state steering and adhesion limit state of the vehicle, thereby obtaining the expected value β of the center of mass sideslip angle exp and the expected value of the yaw rate ω exp ; Where: a is the distance from the center of mass of the car to the front axle; b is the distance from the center of mass of the car to the middle axle; c is the distance from the center of mass of the car to the rear axle; v1 is the front wheel steering angle; are the comprehensive cornering stiffness of the front wheel, middle wheel and rear wheel respectively; m is the total mass of the vehicle; u is the longitudinal velocity of the center of mass of the vehicle; μ is the road adhesion coefficient; Step S2: Calculate the yaw rate deviation Δω, the center of mass sideslip angle β and the center of mass sideslip angular velocity based on the two-degree-of-freedom three-axis vehicle handling stability model And according to the yaw rate threshold value K ω and stability index S β Determine the stability of the car, stability index S β The calculation formula is: Where: k is the slope of the stable boundary line; c is the intercept of the boundary line; Step S3: If the vehicle is outside the stable region, a three-axis vehicle prediction model is established based on the model predictive control theory, and the driver's target vehicle speed and the actual value of the yaw angular velocity ω are used to predict the vehicle's rotation speed. r / Actual value of the sideslip angle β and the expected value of the yaw rate ω exp / Expected value of sideslip angle of center of mass β exp The deviation of the front wheel is used to determine the additional front wheel steering angle δ1 and additional yaw moment T that meet the control target. z ; If it is in the stable region, the model predictive controller does not participate in the work; Step S4: The determined additional front wheel turning angle δ1 directly acts on the front steering wheel; the additional yaw moment T of the whole vehicle is distributed by the regular driving force control method. z Distributed to each drive wheel, additional drive torque of each drive wheel is obtained.

2. A distributed wheel-drive heavy-duty tractor driving stability control method as claimed in claim 1, characterized in that: In step S1, the two-degree-of-freedom three-axle vehicle handling stability model adopts a three-axle heavy-duty tractor vehicle model supported on the ground by three lateral elastic tires and having two degrees of freedom, lateral and yaw, and its differential equation is: Where: I z is the moment of inertia of the car; β is the side slip angle of the vehicle’s center of mass; is the lateral acceleration of the vehicle’s center of mass; ω r is the vehicle yaw angular velocity; is the vehicle's yaw angular acceleration.

3. A distributed wheel-drive heavy-duty tractor driving stability control method as claimed in claim 1, characterized in that: In step S2, the stability judgment standard of the vehicle is: (1) If the stability index S β =0, the car is judged to be unstable; (2) If the stability index S β ≠0 and yaw rate deviation Δω>K ω When the vehicle is judged to be unstable; (3) If the stability index S β ≠0 and yaw rate deviation Δω≤K ω When the vehicle is determined to be stable, the vehicle stability will continue to be monitored.

4. A distributed wheel-drive heavy-duty tractor driving stability control method as claimed in claim 1, characterized in that: In step S3, a two-degree-of-freedom three-axis vehicle handling stability model for a heavy-duty tractor with an additional yaw moment is used as a prediction model of the model predictive control theory, and its differential equation is: Where: T z is the additional yaw moment.

5. A distributed wheel-drive heavy-duty tractor driving stability control method as claimed in claim 1, characterized in that: In step S4, the rule-driven force control allocation method is as follows: (1) When it is necessary to correct the left understeer or right oversteer condition: the right wheel increases the driving torque, which generates a positive 1 / 4 additional yaw moment value; the left wheel reduces the driving torque, which generates a negative 1 / 4 additional yaw moment value; (2) When it is necessary to correct the left oversteer or right understeer condition: the left wheel increases the driving torque, which generates a positive 1 / 4 additional yaw moment value; the right wheel reduces the driving torque, which generates a negative 1 / 4 additional yaw moment value.

6. A distributed wheel-drive heavy-duty tractor driving stability control method as claimed in claim 1, characterized in that: The additional yaw moment T is completed according to the rule-based driving force control distribution method. z After the control distribution, it should be further verified whether the sum of the driving torques of each driving wheel is equal to the total target driving torque: Where: T x_ij is the output torque of each wheel assembly of the wheel motor; r ij is the rolling radius of each driving wheel (ij=ml,mr,rl,rr represent the left wheel of the middle axle, the right wheel of the middle axle, the left wheel of the rear axle, and the right wheel of the rear axle respectively); T x_req is the total target driving torque, which is calculated by the drive controller and obtained from the controller through the CAN bus.

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