Self-adaptive transverse and longitudinal coupling vehicle dynamics model construction method

Abstract

The invention relates to a self-adaptive transverse and longitudinal coupling vehicle dynamics model construction method, which comprises the steps of constructing a tire dynamics model, constructing a vehicle body dynamics model based on the tire dynamics model, and constructing a self-adaptive transverse and longitudinal coupling vehicle dynamics model in combination with the tire dynamics model and the vehicle body dynamics model. The step of building the tire dynamic model comprises the following steps: 1, building a linear saturated tire model; the construction of the vehicle body dynamic model comprises the following steps: 1, when the front wheel rotation angle of the vehicle is small, constructing a small front wheel rotation angle three-degree-of-freedom vehicle body dynamic model; 2, when the large front wheel rotation angle of the vehicle is large, a large front wheel rotation angle three-degree-of-freedom vehicle body dynamics model is constructed; the self-adaptive transverse and longitudinal coupling vehicle dynamics model is obtained. By considering the influence of the front wheel turning angle on the vehicle dynamics coupling characteristic, a self-adaptive transverse and longitudinal coupling vehicle body dynamics model is constructed, and an accurate and complete vehicle dynamics model under different driving working conditions is constructed in combination with a linear saturated tire model.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle dynamics models, and specifically refers to a method for constructing an adaptive longitudinal and lateral coupling vehicle dynamics model. Background Technique

[0002] Vehicle models can be used to analyze the dynamic characteristics of vehicles under different driving conditions and construct the mapping relationship between vehicle inputs and key states. On the one hand, they can be applied to model-based control algorithms such as MPC and LQR to develop algorithms for trajectory tracking, obstacle avoidance control, and stability coordination. On the other hand, they can also be used as simplified models of the vehicle under test to assist in the rapid iterative optimization of algorithms.

[0003] Under different driving conditions, the dynamic characteristics of vehicles present different coupling characteristics of lateral and longitudinal movements and their nonlinear characteristics. Constructing an accurate vehicle dynamics model is the premise and foundation for research on vehicle dynamic characteristic analysis, stability control, and obstacle avoidance algorithm development.

[0004] Current main vehicle models such as the three-degree-of-freedom single-track vehicle dynamics model and the seven-degree-of-freedom vehicle dynamics model. Among them, simplified vehicle models often assume that the vehicle is within a linear range, the front wheel angle of the vehicle is small, and a linear tire model is used. Although to a certain extent, the model complexity is reduced, the overly simplified modeling assumptions lead to a narrow range of applicable working conditions for the vehicle and cannot accurately describe the vehicle state changes. While complex vehicle models can describe the nonlinear characteristics of vehicles and consider the influence of multiple actuators such as drive-by-wire, their operation real-time performance is poor and it is difficult to be actually applied. Therefore, current vehicle models always face the problem of balancing model fidelity and operation real-time performance. Existing vehicle dynamics models do not fully consider the operating characteristics of vehicles under different driving conditions, resulting in insufficient simulation accuracy or excessive simulation time of the models.

[0005] Therefore, the present invention provides a method for constructing an adaptive longitudinal and lateral coupling vehicle dynamics model, which can obtain relatively accurate simulation results of vehicle dynamic characteristics under any working condition at a relatively small cost of running time. Summary of the Invention

[0006] To solve the above technical problems, the present invention provides a method for constructing an adaptive longitudinal and lateral coupling vehicle dynamics model, which constructs a tire dynamics model and constructs a vehicle body dynamics model based on the tire dynamics model, and combines the tire dynamics model and the vehicle body dynamics model to construct an adaptive longitudinal and lateral coupling vehicle dynamics model.

[0007] The construction of the tire dynamics model includes Step 1: Construct a linear saturation tire model F y = min{K×α, F ypeak}, where the K, α, F ypeakThey are respectively the approximate fitting results of the tire cornering stiffness, the tire cornering angle, and the tire lateral force saturation value. The F y includes F yfl , F yfr , F yrl , F yrr , the F yfl , F yfr , F yrl , F yrr are respectively the lateral force of the left front wheel, the lateral force of the right front wheel, the lateral force of the left rear wheel, and the lateral force of the right rear wheel;

[0008] The construction of the vehicle body dynamics model includes Step 1: Taking ξ = [v x , v y , Ψ, w, X, Y] as the state variables and u = [δ f , F xfl , F xfr , F xrl , F xrr as the control variables, based on the linear saturated tire model, when the front wheel angle of the vehicle is small, simplifying the lateral-longitudinal coupling characteristics, and constructing a three-degree-of-freedom vehicle body dynamics model f dyn1 (ξ, u), where v x is the longitudinal speed, v y is the lateral speed, ψ is the vehicle yaw angle, w is the yaw angular velocity, X is the vehicle longitudinal displacement in the inertial coordinate system, Y is the vehicle lateral displacement in the inertial coordinate system, δ f is the front wheel angle, and the F xfl , F xfr , F xrl , F xrr are respectively the longitudinal force of the left front wheel, the longitudinal force of the right front wheel, the longitudinal force of the left rear wheel, and the longitudinal force of the right rear wheel;

[0009] Step 2: Taking ξ = [v x , v y , Ψ, w, X, Y] as the state variables and u = [δ f , F xfl , F xfr , F xrl , F xrr as the control variables, based on the linear saturated tire model, when the front wheel angle of the vehicle is large, considering the lateral-longitudinal coupling characteristics, and constructing a three-degree-of-freedom vehicle body dynamics model f dyn2 (ξ, u);

[0010] The construction of the adaptive lateral-longitudinal coupling vehicle dynamics model includes Step 1: Constructing a front wheel angle adjustment factor according to the vehicle dynamics characteristics at small front wheel angles and the vehicle dynamics characteristics at large front wheel angles;

[0011] Step 2: Construct an adaptive longitudinal and lateral coupling vehicle dynamics model \(f(\xi, u)\) by linearly weighting and combining the small front wheel angle three-degree-of-freedom vehicle body dynamics model and the large front wheel angle three-degree-of-freedom vehicle body dynamics model; the \(f(\xi, u)=\lambda\times f_{1}(\xi, u)+(1 - \lambda)\times f_{2}(\xi, u)\). dyn (\xi,u); the \(f\) dyn (\xi,u)=\lambda 1 \(\times f\) dyn2 (\xi,u)+(1-\lambda 1 )\(\times f\) dyn1 (\xi,u).

[0012] Compared with the prior art, the present invention has the following beneficial effects: By considering the influence of the front wheel angle on the vehicle dynamics coupling characteristics, an adaptive longitudinal and lateral coupling vehicle body dynamics model is constructed. Combining with the linear saturation tire model, an accurate and complete vehicle dynamics model under different driving conditions is constructed, which can be applied to vehicle dynamics characteristic analysis, model-based control algorithm development, and auxiliary algorithm rapid verification, etc.;

[0013] According to the changes in the longitudinal and lateral coupling characteristics of the vehicle under small front wheel angles and large front wheel angles, through the front wheel angle adjustment factor, a linear weighted combination of the small front wheel angle vehicle body dynamics model and the large front wheel angle vehicle body dynamics model is realized, and an adaptive longitudinal and lateral coupling vehicle dynamics model is constructed, which can realize the smooth transition of the vehicle model under different conditions, can achieve accurate tracking within any angle range, and can provide more accurate predicted values of vehicle states under a wider range of driving conditions, and obtain vehicle dynamics characteristic simulation results with higher accuracy under any condition at a relatively small operation time cost; By constructing a linear saturation tire model, while maintaining accurate fitting of the non-linear saturation characteristics of the tire under different loads and different adhesion conditions, the complexity of the vehicle dynamics model is reduced, the tire model is further simplified, and the real-time operation of the model in actual prediction is improved.

[0014] Further, the small front wheel angle three-degree-of-freedom vehicle body dynamics model \(f_{1}(\xi, u)\) is dyn1 as

[0015]

[0016] The advantage of adopting the above step is that the vehicle body dynamic model can effectively fit the changes in vehicle state variables such as vehicle longitudinal speed, lateral speed, yaw angle, yaw angular velocity, longitudinal displacement, and lateral displacement under the input of the corresponding front wheel angle, left front wheel longitudinal force, right front wheel longitudinal force, left rear wheel longitudinal force, and right rear wheel longitudinal force.

[0017] Further, the large front wheel angle three-degree-of-freedom vehicle body dynamics model \(f_{2}(\xi, u)\) is dyn2 as

[0018]

[0019] The beneficial effect of adopting the previous step is that when the large front wheel angle acts, further considering the transverse and longitudinal coupling effects, the mapping relationship between the control input quantities such as the front wheel angle and the longitudinal forces of the four wheels and the changes in the vehicle state quantities such as the longitudinal speed, lateral speed, yaw angle, yaw angular velocity, longitudinal displacement, and lateral displacement is fitted, and the prediction of the changes in the vehicle state quantities can be realized.

[0020] Furthermore, the front wheel angle adjustment factor λ 1 The formula is:

[0021]

[0022] where δ flim1 and δ flim2 are the front wheel angle transition thresholds. According to the difference in the change rates of the cosine function and the sine function, the value of δ flim1 is 0.05 rad, and the value of δ flim2 is 0.32 rad.

[0023] The beneficial effect of adopting the previous step is that as the front wheel angle changes, a smooth transition of the vehicle dynamics model is achieved. When the front wheel angle is less than δ flim1 , λ 1 is equal to 0, and a three-degree-of-freedom vehicle body dynamics model with a small front wheel angle is adopted, that is, f dyn (ξ,u) = f dyn1 (ξ,u); when the front wheel angle value is greater than δ flim2 , λ 1 is equal to 1, and a three-degree-of-freedom vehicle body dynamics model with a large front wheel angle is adopted, that is, f dyn (ξ,u) = f dyn2 (ξ,u); when the front wheel angle is between δ flim1 and δ flim2 , λ 1 takes values in the interval [0,1], and the vehicle dynamics model is composed of a three-degree-of-freedom vehicle body dynamics model with a small front wheel angle and a three-degree-of-freedom vehicle body dynamics model with a large front wheel angle, that is, f dyn (ξ,u) = λ 1 ×f dyn2 (ξ,u)+(1 - λ 1 )×f dyn1 (ξ,u)

[0024] Furthermore, the linear saturation tire model F y = min{K×α,F ypeak}

[0025]

[0026] where μ 0, F z0 , K 0 , F ypeak0 are the road adhesion coefficient, vertical load, cornering stiffness, and peak lateral force corresponding to the reference values, respectively. The μ, F z , F x are the actual road adhesion coefficient, actual vertical load, and actual input longitudinal force, respectively. The C 1 , C 2 is the approximate fitting coefficient. The K, F ypeak are the approximate fitting results of the tire cornering stiffness and the tire lateral force saturation value, respectively. The α is the tire slip angle.

[0027] The advantage of adopting the previous step is that it can effectively describe the change of tire cornering characteristics under different road adhesion conditions and vertical load changes, considering the linear and saturation characteristics of the tire, simplifying the mapping relationship between the tire slip angle and the tire lateral force, and improving the real-time operation of the model on the premise of ensuring the accuracy of the tire model.

[0028] Further, the vertical load includes F zfl , F zfr , F zrl , F zrr , the F zfl , F zfr , F zrl , F zrr are the vertical loads of the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively.

[0029] Further, the formula for the vertical loads of the four wheels is:

[0030]

[0031] where L is the wheelbase, h is the center of mass height, a x is the longitudinal acceleration, and a y is the lateral acceleration.

[0032] The advantage of adopting the previous step is that it can effectively calculate the change of the vertical loads of the four vehicles based on the input of acceleration information, improving the accuracy of tire lateral force estimation.

[0033] Further, the tire slip angle includes α yfl , α yfr , α yrl , α yrr , the α yfl , α yfr , α yrl , α yrr are the slip angles of the left front wheel, right front wheel, left rear wheel, and right rear wheel, respectively.

[0034] Further, the four vehicle tire sideslip angle formulas are as follows:

[0035]

[0036] The beneficial effect of adopting the previous step is as follows: By using a dual-rail vehicle dynamics model, the tire sideslip angles corresponding to the four wheels are calculated respectively, which helps to improve the prediction accuracy of the lateral forces of the four wheels. Description of the Drawings

[0037] Figure 1 is a flow chart of the vehicle body dynamics model and the tire dynamics model;

[0038] Figure 2 is a fitting effect diagram of the linear saturation tire model - the lateral fitting effect of the tire under different vertical loads;

[0039] Figure 3 is a fitting effect diagram of the linear saturation tire model - the lateral force fitting effect of the tire under different road adhesion coefficients;

[0040] Figure 4 is the model fidelity evaluation under the sine steering test - the comparison diagram of the yaw rate in the lateral response test of different vehicle models under simulation condition 1;

[0041] Figure 5 is the model fidelity evaluation under the sine steering test - the comparison diagram of the yaw rate in the lateral response test of different vehicle models under simulation condition 2;

[0042] Figure 6 is the model fidelity evaluation under the sine steering test - the comparison diagram of the yaw rate in the lateral response test of different vehicle models under simulation condition 3;

[0043] Figure 7 is the model fidelity evaluation under the sine steering test - the comparison diagram of the yaw rate in the lateral response test of different vehicle models under simulation condition 4;

[0044] Figure 8 is the model fidelity evaluation under the sine steering test - the comparison diagram of the maximum yaw rate deviation index of different vehicle models under different conditions;

[0045] Figure 9 is the model fidelity evaluation under the sine steering test - the comparison diagram of the average yaw rate deviation index of different vehicle models under different conditions;

[0046] Figure 10 is the model fidelity evaluation under the double lane change test - the expected obstacle avoidance trajectory diagram;

[0047] Figure 11Comparison chart of yaw rates of different vehicle models under simulation condition 1 for model fidelity evaluation in double lane change test;

[0048] Figure 12 Comparison chart of yaw rates of different vehicle models under simulation condition 2 for model fidelity evaluation in double lane change test;

[0049] Figure 13 Comparison chart of maximum yaw rate deviation index of different vehicle models under different conditions for model fidelity evaluation in double lane change test;

[0050] Figure 14 Comparison chart of average yaw rate deviation index of different vehicle models under different conditions for model fidelity evaluation in double lane change test. Detailed implementation mode

[0051] To better understand the technical solution of the present invention, the present invention will be further described below in conjunction with specific embodiments and the accompanying drawings of the specification.

[0052] Embodiment 1:

[0053] Please refer to Figures 1-14 , a method for constructing an adaptive longitudinal and lateral coupling vehicle dynamics model is provided according to this embodiment. A tire dynamics model is constructed and a vehicle body dynamics model is constructed based on the tire dynamics model. An adaptive longitudinal and lateral coupling vehicle dynamics model is constructed by combining the tire dynamics model and the vehicle body dynamics model; the construction of the tire dynamics model includes step one: constructing a linear saturated tire model F y =min{K×α,F ypeak}}, where K, α, and F ypeak are respectively the tire cornering stiffness, the tire cornering angle, and the approximate fitting result of the tire lateral force saturation value. F y includes F yfl , F yfr , F yrl , F yrr , F yfl , F yfr , F yrl , F yrr are respectively the lateral force of the left front wheel, the lateral force of the right front wheel, the lateral force of the left rear wheel, and the lateral force of the right rear wheel; the construction of the vehicle body dynamics model includes step one: taking ξ = [v x , v y , Ψ, w, X, Y] as state variables, and taking u = [δ f , F xfl , F xfr , F xrl , F xrrTaking ξ as the control variable, based on the linear saturated tire model, when the front wheel angle of the vehicle is small, the lateral-longitudinal coupling characteristics are simplified, and a three-degree-of-freedom vehicle body dynamics model f for small front wheel angles is constructed dyn1 (ξ, u), where the v x is the longitudinal speed, v y is the lateral speed, ψ is the yaw angle of the vehicle, w is the yaw angular velocity, X is the longitudinal displacement of the vehicle in the inertial coordinate system, Y is the lateral displacement of the vehicle in the inertial coordinate system, and the δ f is the front wheel angle, and the F xfl , F xfr , F xrl , F xrr are the longitudinal force of the left front wheel, the longitudinal force of the right front wheel, the longitudinal force of the left rear wheel, and the longitudinal force of the right rear wheel respectively; Step 2: Taking ξ = [v x , v y , Ψ, w, X, Y] as the state variables and u = [δ f , F xfl , F xfr , F xrl , F xrr as the control variable, based on the linear saturated tire model, when the front wheel angle of the vehicle is large, considering the lateral-longitudinal coupling characteristics, a three-degree-of-freedom vehicle body dynamics model f for large front wheel angles is constructed dyn2 (ξ, u); Step 3: According to the vehicle dynamics characteristics at small front wheel angles and the vehicle dynamics characteristics at large front wheel angles, a front wheel angle adjustment factor is constructed, and an adaptive lateral-longitudinal coupling vehicle dynamics model f dyn (ξ, u) is constructed by linearly weighted combination of the vehicle body dynamics model for small front wheel angles and the vehicle body dynamics model for large front wheel angles; The

[0054] f dyn (ξ, u) = λ 1 * f dyn2 (ξ, u) + (1 - λ 1 ) * f dyn1 (ξ, u), where the λ 1is the front wheel steering angle adjustment factor. By considering the influence of the front wheel steering angle on the vehicle dynamics coupling characteristics, an adaptive longitudinal and lateral coupling vehicle body dynamics model is constructed. Combining with the linear saturation tire model, an accurate and complete vehicle dynamics model under different driving conditions is constructed, which can be applied to vehicle dynamics characteristic analysis, model-based control algorithm development, and rapid verification of auxiliary algorithms. According to the changes in the longitudinal and lateral coupling characteristics of the vehicle under small and large front wheel steering angles, through the front wheel steering angle adjustment factor, a linear weighted combination of the vehicle body dynamics model under small front wheel steering angles and the vehicle body dynamics model under large front wheel steering angles is realized, and an adaptive longitudinal and lateral coupling vehicle dynamics model is constructed, which can achieve a smooth transition of the vehicle model under different conditions, can achieve accurate tracking within any steering angle range, and can provide more accurate predicted values of vehicle states under a wider range of driving conditions, and obtain high-accuracy vehicle dynamics characteristic simulation results under any condition at a relatively small operation time cost. By constructing a linear saturation tire model, while maintaining accurate fitting of the non-linear saturation characteristics of the tire under different loads and different adhesion conditions, the complexity of the vehicle dynamics model is reduced, the tire model is further simplified, and the real-time operation of the model in actual prediction is improved.

[0055] Based on the input of the current actual state variables and control variables, combined with the linear saturation tire model, the lateral forces corresponding to the four wheels can be effectively estimated, and the fitting effect is as Figure 2 and Figure 3 shown. Further substituting into the vehicle body dynamics model to assist in determining the changes in vehicle state variables;

[0056] To verify the model fidelity of the adaptive longitudinal and lateral coupling vehicle dynamics model (ACDD) proposed in this patent, using the joint simulation platform of Carsim and Simulink (Carsim) as the comparison benchmark, the kinematic model (KIM), the longitudinal and lateral decoupled single-track three-degree-of-freedom vehicle dynamics model (Decouple), and the longitudinal and lateral coupled double-track seven-degree-of-freedom vehicle dynamics model (7DOF) are selected as the control groups;

[0057] The comparison evaluation indicators are the yaw rate response under different conditions, the maximum value of the yaw rate deviation, and the average value of the yaw rate deviation.

[0058] The comparative tests mainly include the sine steering test and the double lane change test. The sine test mainly includes four sets of test conditions, namely, the vehicle speed of 121 km / h and the steering wheel steering amplitude of 15 deg (condition 1), the vehicle speed of 65 km / h and the steering wheel steering amplitude of 60 deg (condition 2), the vehicle speed of 18 km / h and the steering wheel steering amplitude of 300 deg (condition 3), and the vehicle speed of 8 km / h and the steering wheel steering amplitude of 540 deg (condition 4), with the road adhesion coefficient being 0.85; the double lane change test includes two sets of test conditions, namely, the vehicle speed of 100 km / h (condition 1) and the vehicle speed of 60 km / h (condition 2), and the road adhesion coefficient is 0.5 for both.

[0059] Figures 4-7 and Figures 11-12 The comparison of the yaw rate responses under different test trials is shown. The adaptive longitudinal and lateral coupling vehicle dynamics model proposed in this patent can accurately fit the change of the yaw rate under different conditions and is close to the reference value.

[0060] Figures 8-9 and Figures 13-14 The comparison of the maximum yaw rate deviation and the average yaw rate deviation under different test trials is shown. The maximum yaw rate deviation and the average yaw rate deviation of the adaptive longitudinal and lateral coupling vehicle dynamics model proposed in this patent are generally lower than those of the control group under different conditions, which proves the fitting accuracy of the adaptive longitudinal and lateral coupling vehicle dynamics model;

[0061] Figure 10 The vehicle driving trajectory of the double lane change test is shown. In the case of low adhesion, the double lane change test can effectively activate the vehicle stability control system to determine the yaw rate response of the vehicle under stable control;

[0062] The three-degree-of-freedom vehicle body dynamics model f of the small front wheel angle dyn1 (ξ,u) is

[0063]

[0064] The vehicle body dynamic model can effectively fit the changes of vehicle state variables such as vehicle longitudinal speed, lateral speed, yaw angle, yaw rate, longitudinal displacement, and lateral displacement under the input of corresponding front wheel angles, left front wheel longitudinal force, right front wheel longitudinal force, left rear wheel longitudinal force, and right rear wheel longitudinal force.

[0065] The three-degree-of-freedom vehicle body dynamics model f of the large front wheel angle dyn2 (ξ,u) is

[0066]

[0067] When the large front wheel angle acts, further considering the lateral-longitudinal coupling effect, the mapping relationship between the control input variables such as the front wheel angle and the longitudinal forces of the four wheels and the changes in the vehicle state variables such as the longitudinal speed, lateral speed, yaw angle, yaw angular velocity, longitudinal displacement, and lateral displacement is fitted, and the prediction of the changes in the vehicle state variables can be realized.

[0068] The front wheel angle adjustment factor λ 1 The formula is: The δ flim1 and δ flim2 are the front wheel angle transition thresholds. According to the difference in the change rates of the cosine function and the sine function, the δ flim1 takes a value of 0.05 rad, and the δ flim2 takes a value of 0.32 rad. As the front wheel angle changes, a smooth transition of the vehicle dynamics model is achieved. When the front wheel angle is less than δ flim1 , λ 1 is equal to 0, and a three-degree-of-freedom vehicle body dynamics model with a small front wheel angle is adopted, that is, f dyn (ξ,u) = f dyn1 (ξ,u); when the front wheel angle value is greater than δ flim2 , λ 1 is equal to 1, and a three-degree-of-freedom vehicle body dynamics model with a large front wheel angle is adopted, that is, f dyn (ξ,u) = f dyn2 (ξ,u); when the front wheel angle is between δ flim1 and δ flim2 , λ 1 takes a value in the interval [0,1], and the vehicle dynamics model is composed of a three-degree-of-freedom vehicle body dynamics model with a small front wheel angle and a three-degree-of-freedom vehicle body dynamics model with a large front wheel angle, that is, f dyn (ξ,u) = λ 1 ×f dyn2 (ξ,u)+(1 - λ 1 )×f dyn1 (ξ,u)

[0069] The linear saturation tire model F y = min{K×α,F ypeak}

[0070]

[0071] The μ 0 ,F z0 ,K 0 ,F ypeak0 are the road adhesion coefficient, vertical load, cornering stiffness, and reference value corresponding to the lateral force peak respectively. The μ,F z ,F xare the actual road adhesion coefficient, the actual vertical load, and the actual input longitudinal force, respectively. 1 ,C 2 is an approximate fitting system, where K, F ypeak They are the approximate fitting results of tire cornering stiffness and tire lateral force saturation value, respectively, and α is the tire slip angle. It can effectively describe the changes in tire cornering characteristics under different road adhesion conditions and vertical load changes, taking into account the linear characteristics and saturation characteristics of the tire, simplifying the mapping relationship between the tire slip angle and the tire lateral force, and improving the real-time performance of the model operation while ensuring the accuracy of the tire model.

[0072] The vertical load includes F zfl , F zfr , F zrl , F zrr , the F zfl , F zfr , F zrl , F zrr They are the vertical load on the left front wheel, the vertical load on the right front wheel, the vertical load on the left rear wheel, and the vertical load on the right rear wheel.

[0073] The vertical load formulas for the four wheels are:

[0074]

[0075] L is the wheelbase, h is the height of the center of mass, and a x is the longitudinal acceleration, a y is the lateral acceleration. The four vehicle vertical load changes can be effectively calculated based on the acceleration information input, improving the accuracy of tire lateral force estimation.

[0076] The tire side slip angle includes α yfl , α yfr , α yrl , α yrr , the α yfl , α yfr , α yrl , α yrr They are the left front wheel slip angle, right front wheel slip angle, left rear wheel slip angle, and right rear wheel slip angle respectively.

[0077] The four vehicle tire slip angle formulas are:

[0078]

[0079] A dual-track vehicle dynamics model is used to calculate the tire slip angles corresponding to the four wheels, which helps to improve the accuracy of lateral force prediction for the four wheels.

[0080] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative efforts belong to the scope of protection of the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for constructing an adaptive lateral and longitudinal coupled vehicle dynamics model, characterized in that: It includes constructing a tire dynamics model and a vehicle body dynamics model based on the tire dynamics model, and constructing an adaptive lateral and longitudinal coupled vehicle dynamics model by combining the tire dynamics model and the vehicle body dynamics model; The tire dynamics model construction comprises the following steps:

1. Constructing a linear saturated tire model F y =min{K×α,F ypeak }, K, α, F ypeak are the approximate fitting results of tire cornering stiffness, tire slip angle and tire lateral force saturation value, respectively. y Including F yfl , F yfr , F yrl , F yrr , the F yfl , F yfr , F yrl , F yrr They are the left front wheel lateral force, the right front wheel lateral force, the left rear wheel lateral force, and the right rear wheel lateral force respectively; The vehicle body dynamics model is constructed by step 1: taking ξ=[v x ,v y ,Ψ,w,X,Y] is the state variable, with u=[δ f ,F xfl ,F xfr ,F xrl ,F xrr ] is the control variable. Based on the linear saturated tire model, when the front wheel turning angle of the vehicle is small, the lateral and longitudinal coupling characteristics are simplified to construct a three-degree-of-freedom vehicle dynamics model f with a small front wheel turning angle. dyn1 (ξ,u), the v x is the longitudinal velocity, v y is the lateral velocity, ψ is the vehicle yaw angle, w is the yaw angular velocity, X is the vehicle longitudinal displacement in the inertial coordinate system, Y is the vehicle lateral displacement in the inertial coordinate system, and the δ f is the front wheel turning angle, the F xfl ,F xfr ,F xrl ,F xrr They are the left front wheel longitudinal force, the right front wheel longitudinal force, the left rear wheel longitudinal force, and the right rear wheel longitudinal force; Step 2: ξ=[v x ,v y ,Ψ,w,X,Y] is the state variable, with u=[δ f ,F xfl ,F xfr ,F xrl ,F xrr ] control variables, based on the linear saturated tire model, when the vehicle has a large front wheel turning angle, the lateral and longitudinal coupling characteristics are considered to construct a three-degree-of-freedom vehicle dynamics model with a large front wheel turning angle. dyn2 (ξ,u); The construction of the adaptive lateral and longitudinal coupling vehicle dynamics model comprises the following steps: first, constructing a front wheel turning angle adjustment factor λ1 according to the vehicle dynamics characteristics at a small front wheel turning angle and the vehicle dynamics characteristics at a large front wheel turning angle; Step 2: Construct an adaptive lateral and longitudinal coupling vehicle dynamics model by linearly weighted combination of the small front wheel steering three-degree-of-freedom vehicle dynamics model and the large front wheel steering three-degree-of-freedom vehicle dynamics model dyn (ξ,u); the f dyn (ξ,u)=λ1×f dyn2 (ξ,u)+(1-λ1)×f dyn1 (ξ,u).

2. The method for constructing an adaptive lateral and longitudinal coupled vehicle dynamics model according to claim 1, characterized in that: The small front wheel turning angle three-degree-of-freedom vehicle body dynamics model f dyn1 (ξ,u) is The a and b are the longitudinal distances from the center of mass to the front axle and the rear axle, respectively. z is the moment of inertia of the vehicle around the z axis, d is the wheelbase, and F drag is the longitudinal resistance, which includes rolling resistance and air resistance, m is the vehicle mass, and δ f is the front wheel turning angle.

3. The method for constructing an adaptive lateral and longitudinal coupled vehicle dynamics model according to claim 2, characterized in that: The large front wheel turning angle three-degree-of-freedom vehicle body dynamics model f dyn2 (ξ,u) is 4. The method for constructing an adaptive lateral and longitudinal coupled vehicle dynamics model according to claim 1, characterized in that: The formula of the front wheel steering angle adjustment factor λ1 is: The δ flim1 and δ flim2 is the front wheel angle transition threshold. According to the difference in the rate of change of the cosine function and the sine function, the δ flim1 The value is 0.05rad, and the δ flim2 The value is 0.32rad.

5. The method for constructing an adaptive lateral and longitudinal coupled vehicle dynamics model according to claim 1, characterized in that: The linear saturated tire model F y =min{K×α,F ypeak } μ0,F z0 ,K0,F ypeak0 are the road adhesion coefficient, vertical load, cornering stiffness, and lateral force peak corresponding benchmark values. z ,F x are the actual road adhesion coefficient, the actual vertical load, and the actual input longitudinal force, respectively; C1 and C2 are approximate fitting coefficients; K and F ypeak are the approximate fitting results of tire cornering stiffness and tire lateral force saturation value, respectively, and α is the tire slip angle.

6. The method for constructing an adaptive lateral and longitudinal coupled vehicle dynamics model according to claim 5, characterized in that: The vertical load includes F zfl , F zfr , F zrl , F zrr , the F zfl , F zfr , F zrl , F zrr They are the vertical load on the left front wheel, the vertical load on the right front wheel, the vertical load on the left rear wheel, and the vertical load on the right rear wheel.

7. The method for constructing an adaptive lateral and longitudinal coupled vehicle dynamics model according to claim 6, characterized in that: The calculation formula for the vertical loads of the four wheels is: L is the wheelbase, h is the height of the center of mass, and a x is the longitudinal acceleration, a y is the lateral acceleration.

8. The method for constructing an adaptive lateral and longitudinal coupled vehicle dynamics model according to claim 5, characterized in that: The tire side slip angle includes α yfl , α yfr , α yr l , α yrr , the α yfl , α yfr , α yrl , α yrr They are the left front wheel slip angle, right front wheel slip angle, left rear wheel slip angle, and right rear wheel slip angle respectively.

9. The method for constructing an adaptive lateral and longitudinal coupled vehicle dynamics model according to claim 8, characterized in that: The calculation formulas for the four vehicle tire side slip angles are:

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