A Stability Control Method for Distributed Drive Vehicles Based on Extended State Observer

Abstract

The present invention discloses a stability control method for a distributed drive vehicle based on an extended state observer. A two-degree-of-freedom vehicle model with two nonlinear interference terms and an additional yaw moment is established. On this basis, an extended state observer is constructed again, and the additional yaw moment is controlled by an integral terminal sliding mode method. Finally, the weighted coordination control of the additional yaw moment is realized, so as to achieve the driving stability control of the distributed drive vehicle.

Description

Technical Field

[0001] The present invention relates to the field of new energy vehicle control, and particularly to a stability control method for distributed drive vehicles based on an extended state observer. Background Art

[0002] The ownership of traditional fuel vehicles has increased significantly, bringing a series of energy and environmental problems. As a type of new energy vehicle, distributed drive electric vehicles have great theoretical and practical significance in vehicle stability control. During the driving process of distributed drive vehicles with matched mechanical elastic electric wheels, the lateral stiffness of the tires will undergo uncertain perturbations. Summary of the Invention

[0003] Object of the Invention: The object of the present invention is to provide a stability control method for distributed drive vehicles based on an extended state observer, so that electric wheel vehicles can maintain vehicle stability when the lateral stiffness of the tires undergoes uncertain perturbations.

[0004] Technical Solution: The stability control method for distributed drive vehicles based on an extended state observer provided by the present invention includes the following steps:

[0005] 1) Based on the problem of uncertain perturbations in the cornering stiffness during the driving process of vehicles with matched electric wheels, establish a two-degree-of-freedom vehicle model with two nonlinear disturbance terms and an additional yaw moment. The two-degree-of-freedom vehicle model is as follows:

[0006]

[0007] Wherein, m is the vehicle mass, β is the sideslip angle of the vehicle's center of mass, is the derivative of β, γ is the yaw angular velocity of the vehicle, is the derivative of γ, k f is the equivalent cornering stiffness of the front wheels, k r is the equivalent cornering stiffness of the rear wheels, a is the distance from the front axle to the center of mass, b is the distance from the rear axle to the center of mass, u is the longitudinal speed of the vehicle, δ is the front wheel steering angle, I z is the moment of inertia of the vehicle about the Z-axis, Δd 1 is the lateral motion nonlinear disturbance term caused by the uncertain perturbation of the cornering stiffness, Δd 2 is the yaw motion nonlinear disturbance term caused by the uncertain perturbation of the cornering stiffness, and ΔM is the additional yaw moment;

[0008] 2) Based on the two-degree-of-freedom vehicle model established for the lateral motion nonlinear disturbance term Δd 1 , the yaw motion nonlinear disturbance term Δd 2 , and the additional yaw moment term ΔM, construct a yaw angular velocity extended state observer to observe the yaw motion nonlinear disturbance term Δd2 Similarly, a centroid sideslip angle extended state observer is constructed to observe the integrated nonlinear disturbance term Δd 3 , where Δd 3 = Δd 1 - Δd 2 ;

[0009] 3) Using the integral terminal sliding mode method, a yaw rate yaw moment controller including the yaw motion nonlinear disturbance term Δd 2 is established. The Δd 2 in the yaw rate yaw moment controller is observed and replaced by using the yaw motion nonlinear disturbance term Δd 2 in step 2). Similarly, using the integral terminal sliding mode method, a centroid sideslip angle yaw moment controller including the integrated nonlinear disturbance term Δd 3 is established. The Δd 3 in the centroid sideslip angle yaw moment controller is observed and replaced by using the integrated nonlinear disturbance term Δd 3 in step 2);

[0010] 4) Based on the yaw rate yaw moment controller and the centroid sideslip angle yaw moment controller, the additional yaw moment is obtained, and the additional yaw moment is weighted and coordinated to control the dynamic distribution of the wheels of the electric wheeled vehicle to adjust the vehicle stability.

[0011] Advantageous effects: Compared with the prior art, the remarkable feature of the present invention is to establish a two-degree-of-freedom vehicle model with two nonlinear disturbance terms and an additional yaw moment. On this basis, an extended state observer is constructed again, and the additional yaw moment is controlled by the integral terminal sliding mode method, and finally the weighted coordination control of the additional yaw moment is realized, so as to realize the driving stability of the distributed drive vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 is a schematic flow chart of the present invention;

[0013] Figure 2 is a schematic diagram of the yaw rate of the present invention;

[0014] Figure 3 is a schematic diagram of the centroid sideslip angle of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0015] The present invention will be further described in detail below with reference to the drawings and specific embodiments.

[0016] Please refer to Figure 1 shown. A distributed drive vehicle stability control method based on an extended state observer provided by the present invention includes the following steps:

[0017] 1) In the process of vehicle driving, there is an uncertain perturbation problem in the cornering stiffness of a vehicle based on a matched electric wheel. A two-degree-of-freedom vehicle model with two nonlinear disturbance terms and an additional yaw moment is established. The two-degree-of-freedom vehicle model is as follows:

[0018]

[0019] Among them, m is the vehicle mass, β is the sideslip angle of the vehicle's center of mass, γ is the yaw angular velocity of the vehicle, k f , k r are the equivalent cornering stiffnesses of the front and rear wheels respectively, a and b are the distances from the front and rear axles to the center of mass respectively, u is the longitudinal speed of the vehicle, δ is the front wheel steering angle, I z is the moment of inertia of the vehicle about the Z-axis, Δd 1 is the nonlinear disturbance term of the lateral motion caused by the uncertain perturbation of the cornering stiffness, Δd 2 is the nonlinear disturbance term of the yaw motion caused by the uncertain perturbation of the cornering stiffness, and ΔM is the additional yaw moment;

[0020] 2) Based on the two-degree-of-freedom vehicle model established for the nonlinear disturbance term Δd 1 of the lateral motion, the nonlinear disturbance term Δd 2 of the yaw motion, and the additional yaw moment term ΔM, a yaw angular velocity extended state observer is constructed to observe the nonlinear disturbance term Δd 2 of the yaw motion. Similarly, a sideslip angle of the center of mass extended state observer is constructed to observe the integrated nonlinear disturbance term Δd 3 , where Δd 3 =Δd 1 -Δd 2 ;

[0021] Construct a yaw angular velocity extended state observer, expand the nonlinear disturbance term Δd 2 in the second term of Equation (1) into a new state variable, and form a system as shown in Equation (8):

[0022]

[0023] In the formula, the function η(t) is the derivative of the nonlinear disturbance term Δd 2 of the yaw motion. The above system is designed as the following yaw angular velocity extended state observer:

[0024]

[0025] Among them, e 1 is the observation error of the extended state observer for the yaw angular velocity γ, z 1 is the observed value of the extended state observer for the yaw angular velocity γ, is z1 The derivative of z 2 is the observed value of the nonlinear interference term Δd of the yaw motion by the extended state observer 2 ; is the derivative of z 2 with respect to β 01 and β 02 are error correction coefficients, and the expression of the nonlinear function fal(e 1 ,α 1 ,ξ) is as follows:

[0026]

[0027] where α 1 is the nonlinear function of the system; ξ is the filtering function of the system, and the observed value of Equation (8) can be obtained by the above extended state observer;

[0028] Construct a centroidal side slip angle extended state observer, and design the system obtained from Equation (8) as the following centroidal side slip angle extended state observer:

[0029]

[0030] where e 3 is the observation error of the centroidal side slip angle with respect to the centroidal side slip angle β of the vehicle; β 03 and β 04 are error correction coefficients, z 3 is the observed value of the centroidal side slip angle with respect to β; z 4 is the observed value of the centroidal side slip angle with respect to the nonlinear interference term Δd 3 ;

[0031] The expression of the nonlinear function fal(e 1 ,α 1 ,ξ)) is as follows:

[0032]

[0033] 3) Use the integral terminal sliding mode method to establish a yaw rate yaw moment controller including the nonlinear interference term Δd 2 of the yaw motion. Use the nonlinear interference term Δd in step 2 2 to observe and replace Δd in the yaw rate yaw moment controller. Similarly, use the integral terminal sliding mode method to establish a centroidal side slip angle yaw moment controller including the integrated nonlinear interference term Δd 2 and use the integrated nonlinear interference term Δd in step 2 3 to observe and replace Δd in the centroidal side slip angle yaw moment controller; 3 3 3 ;

[0034] The yaw rate yaw force controller includes an additional yaw moment, and the calculation formula is as follows:

[0035] Establish an integral-type nonlinear terminal sliding mode surface:

[0036]

[0037] e γ = γ - γ d (3)

[0038] where sgn(e) is the sign function, e γ is the yaw rate error, and γ d is the yaw rate value;

[0039] Taking the derivative of the above integral terminal sliding mode surface, the sliding mode control law can be obtained:

[0040]

[0041]

[0042] where ε is a constant. In the sliding mode control law, due to the special structure of the sign function, chattering will occur when the control system switches at the switching surface. To suppress this chattering, the saturation function sat(s / p) is used to replace the sign(s) function to ensure the smoothness and continuity of the input of the control system at the switching surface. Therefore, the reaching law of the sliding mode control law can be designed as:

[0043]

[0044] In the formula, is the proportional coefficient; p 1 is the boundary layer thickness.

[0045] From equations (2) to (6), the yaw moment ΔM including the additional yaw rate can be obtained γ :

[0046]

[0047] I z is the moment of inertia of the vehicle about the Z-axis;

[0048] Combining equations (7) and (9), the yaw rate integral terminal sliding mode control law based on the yaw rate extended state observer can be obtained:

[0049]

[0050] The proof of the accuracy of the yaw rate extended state observer is as follows. Since the perturbation of the mechanical elastic tire cornering stiffness uncertainty is bounded, η(t) ≤ η0 , η 0 is a constant value, then there is:

[0051]

[0052] By selecting appropriate coefficients β 01 and β 02 of the yaw rate extended state observer, the observation error can be made small enough;

[0053] The centroid side slip angle yaw moment controller includes an additional yaw moment, and the calculation formula is as follows:

[0054] Make the following modifications to Equation (5) and transform it into an expression with the additional yaw moment ΔM β as the control variable as follows:

[0055]

[0056] In the formula,

[0057] Δd 3 = Δd 1 - Δd 2 .

[0058] Establish an integral-type terminal sliding mode surface:

[0059]

[0060] e β = β - β d (14)

[0061] where β d is the ideal centroid side slip angle;

[0062] Taking the derivative of the above integral terminal sliding mode surface, the sliding mode control law can be obtained:

[0063]

[0064]

[0065] The reaching law of the integral terminal sliding mode control law can be designed as:

[0066]

[0067] From Equation (16) and Equation (17), the yaw moment ΔM β of the additional centroid side slip angle can be obtained:

[0068]

[0069] The formula contains a mixed integrated non - linear interference term Δd for lateral motion and yaw motion 3 , in practical engineering applications, this term cannot be directly measured, and an extended state observer is used to observe this term in real time;

[0070] By combining Equation (18) and Equation (19), the integral terminal sliding mode control law of the sideslip angle based on the yaw moment controller of the center of mass can be obtained:

[0071]

[0072] 4) Obtain the additional yaw moment based on the yaw rate yaw moment controller and the sideslip angle yaw moment controller, and perform weighted coordination control on the additional yaw moment to dynamically distribute the rotating wheels of the electric wheeled vehicle to adjust the vehicle stability;

[0073] Using the double - straight - line method, divide the phase plane into a "stable region", a "critical region" and an "unstable region", and define the weighted coordination weight coefficient ρ as:

[0074]

[0075] Then the additional yaw moment after weighted coordination is:

[0076] ΔM = ρΔM β +(1 - ρ)ΔM γ (23)

[0077] The additional yaw moment obtained by weighted coordination is distributed using the quadratic programming method. The specific process is as follows:

[0078] First, define the objective function with the minimum tire utilization rate as the goal:

[0079]

[0080] In the optimal distribution of the additional yaw moment, it is necessary to consider the constraints of the additional yaw moment and the wheel longitudinal force in the upper - layer controller, the limit of the peak torque of the in - wheel motor built in the mechanical elastic electric wheel, and the influence of the road surface adhesion conditions. Therefore, the quadratic programming algorithm adopted can be expressed as:

[0081]

[0082] In the formula, F xi (i = l1, l2, r1, r2) is the longitudinal force of each wheel, c is the wheelbase, R is the tire rolling radius, F zi (i = l1, l2, r1, r2) is the vertical load of each wheel, F xl1 = F xr1 = F xl2 = Fxr2 = F xi (i = l1, l2, r1, r2) are the longitudinal forces of each wheel, T xi (i = l1, l2, r1, r2) are the driving torques of each wheel of the vehicle, and μ is the road surface adhesion coefficient;

[0083] Thus, the expressions of each parameter have been determined, and the quadratic programming function in Matlab can be used for solution. The solution command is [x, fval, exitflag] = quadprog(G, f, [], [], A eq , b eq , lb, ub,), and the obtained x value is the driving torque of each wheel.

[0084] Embodiment 1

[0085] Based on the simulation results of the stability control method for a distributed drive vehicle based on an extended state observer, the simulation condition is the extreme condition with a road surface adhesion coefficient of 0.3 and a vehicle speed of 108 km / h.

[0086] Please refer to Figure 2 As shown, under the condition of a wet and slippery road surface, both the stability control method for a distributed drive vehicle based on an extended state observer designed by the present invention and the simple sliding mode control method in the prior art can control the yaw rate of the vehicle to be stable. However, the amplitude of the yaw rate of the vehicle under the control of the present invention is smaller, proving that the stability control effect is better;

[0087] Please refer to Figure 3 As shown, under the condition of a wet and slippery road surface, both the stability control method for a distributed drive vehicle based on an extended state observer designed by the present invention and the simple sliding mode control method in the prior art can control the sideslip angle of the vehicle's center of mass to be stable. However, the sideslip angle curve of the vehicle under the control of the present invention is smoother, proving that the stability control effect of the vehicle is better.

Claims

1. A distributed drive vehicle stability control method based on extended state observer, It is characterized in that The following steps are involved: 1) Based on the uncertainty perturbation problem of the cornering stiffness of the vehicle matched with electric wheels during driving, a two-degree-of-freedom vehicle model with two nonlinear interference terms and additional yaw moment is established. The two-degree-of-freedom vehicle model is as follows: where m is the vehicle mass, β is the sideslip angle of the vehicle's center of mass, is the derivative of β, γ is the yaw rate of the vehicle, is the derivative of γ, k f is the equivalent cornering stiffness of the front wheels, k r is the equivalent cornering stiffness of the rear wheels, a is the distance from the front axle to the center of mass, b is the distance from the rear axle to the center of mass, u is the longitudinal speed of the vehicle, δ is the front wheel steering angle, I z is the moment of inertia of the vehicle about the Z-axis, Δd 1 is the nonlinear lateral motion disturbance term caused by the perturbation of the cornering stiffness uncertainty, Δd 2 is the nonlinear yaw motion disturbance term caused by the perturbation of the cornering stiffness uncertainty, ΔM is the additional yaw moment; 2) For the lateral motion non-linear interference term Δd 1 , the yaw motion non-linear interference term Δd 2 , and the additional yaw moment term ΔM, based on the two-degree-of-freedom vehicle model established, construct a yaw rate extended state observer to observe the yaw motion non-linear interference term Δd 2 . Similarly, construct a sideslip angle of the center of mass extended state observer to observe the integrated non-linear interference term Δd 3 , where Δd 3 = Δd 1 - Δd 2 . The formula for the yaw rate extended state observer is as follows: where, e 1 is the observation error of the yaw rate γ by the extended state observer, z 1 is the observed value of the yaw rate γ by the extended state observer, is the derivative of z 1 , z 2 is the observed value of the non - linear interference term Δd 2 of the yaw motion by the extended state observer, is the derivative of z 2 , β 01 , β 02 are error correction coefficients, and the expression of the non - linear function fal(e 1 , α 1 , ξ) is as follows: where α 1 is the non-linear function of the system, and ξ is the filtering function of the system; 3) Using the integral terminal sliding mode method, a yaw rate yaw moment controller including the yaw motion nonlinear interference term Δd 2 is established. The Δd 2 in the yaw rate yaw moment controller is observed and substituted by using the Δd 2 in the yaw motion nonlinear interference term obtained in step 2). Similarly, using the integral terminal sliding mode method, a center of mass side slip angle yaw moment controller including the integrated nonlinear interference term Δd 3 is established. The Δd 3 in the center of mass side slip angle yaw moment controller is observed and substituted by using the Δd 3 in the integrated nonlinear interference term obtained in step 2); the yaw rate yaw moment controller includes a yaw moment ΔM γ with an additional yaw rate, and the calculation formula is as follows: Combining the yaw moment expression of the additional yaw rate with the yaw rate extended state observer expression, we get the yaw rate integral terminal sliding mode control law based on the yaw rate extended state observer: where sgn(e) is the sign function, and I z is the moment of inertia of the vehicle about the Z-axis; 4) Based on the yaw rate yaw moment controller and the center of mass sideslip angle yaw moment controller, the additional yaw moment is calculated, the additional yaw moment is weighted and coordinated controlled, and the turning wheels of the electric wheeled vehicle are dynamically allocated to adjust the vehicle stability.

2. The distributed drive vehicle stability control method based on the extended state observer according to claim 1, It is characterized in that In step 2), the center of mass sideslip angle expansion state observer is constructed, and the formula is as follows: where, e 3 is the observation error of the yaw angle β of the vehicle's center of mass by the extended state observer; β 03 , β 04 are error correction coefficients, z 3 is the observed value of β by the extended state observer, is the derivative of z 3 , z 4 is the observed value of the non - linear interference term Δd 3 by the extended state observer, is the derivative of z 4 , and the expression of the non - linear function fal(e 1 , α 1 , ξ) is as follows: where α 2 is the non - linear function of the system, and ξ is the filtering function of the system.

3. The distributed drive vehicle stability control method based on extended state observer according to claim 1 or 2, It is characterized in that In step 3), an integral terminal sliding mode method is adopted to establish a sideslip angle yaw moment controller including an integrated nonlinear interference term Δd 3 The sideslip angle yaw moment controller includes a yaw moment ΔM of an additional sideslip angle β , and the calculation formula is as follows: The yaw moment expression of the additional center of mass sideslip angle is combined with the center of mass sideslip angle expansion state detector expression to obtain the center of mass sideslip angle integral terminal sliding mode control law based on the center of mass sideslip angle yaw moment controller:

4. The distributed drive vehicle stability control method based on extended state observer according to claim 1, It is characterized in that In step 4), the quadratic programming method is used to dynamically allocate the wheels of the electric wheeled vehicle, and the objective function is defined with the minimum tire utilization as the goal: Among them, F xi is the longitudinal force in each round, and the solved x value is the driving torque of each wheel.

5. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, It is characterized in that When the processor executes the computer program, the steps of the method according to claim 1 to claim 4 are implemented.

6. A computer-readable storage medium having a computer program stored thereon, It is characterized in that When the computer program is executed by a processor, the steps of the method according to claim 1 to claim 4 are implemented.

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