Vehicle active suspension control method and application for flexible chassis extension connection

Abstract

The present invention discloses a vehicle active suspension control method for flexible chassis extension connection, including: establishing a whole vehicle dynamics model, building a dynamics control model of a single active suspension system, and using a consensus algorithm to design a distributed control strategy. Among them, establishing the whole vehicle dynamics model includes: the dynamics model of the vehicle body and all active suspension systems; establishing the dynamics control model of a single active suspension system includes: the dynamics model of the vehicle body module and the dynamics control model of a single wheel suspension module; designing a distributed control strategy includes: designing a control strategy for the dynamics control model of a single active suspension system, and using a consensus algorithm to achieve optimal control of the whole vehicle. The present invention can achieve optimal control of the dynamic parameters of the whole vehicle under various continuous random road conditions, improve the vehicle's driving smoothness and handling stability, significantly reduce the calculation cost and calculation time of the active suspension control system, and reduce the requirements for the active suspension controller.

Description

Technical Field

[0001] The present invention relates to the field of vehicle active suspension control, and specifically relates to a vehicle active suspension control method that can be used for flexible chassis expansion connection and its application. Background Art

[0002] The automotive chassis consists of the drive system, braking system, steering system, and suspension system. As the part of the vehicle that contacts the ground, its overall performance has a decisive impact on the safety and comfort of the vehicle during driving. Currently, higher requirements are being placed on vehicle flexibility, comfort, and passenger space in vehicle design. In order to more flexibly adapt to different driving scenarios and mission requirements, a new chassis system with greater versatility, modular design, and modular control is needed. A flexible automotive chassis is composed of functional modules such as drive, braking, steering, suspension, and control. It adopts a modular design, scalable structure, universal electronic and electrical architecture, and multi-modal control, enabling the vehicle to flexibly adapt to different driving scenarios and mission requirements.

[0003] As a key component of the vehicle chassis, the automotive suspension significantly impacts ride comfort and handling stability. Passive suspension is currently widely used in most passenger cars due to its low cost and energy-saving nature. However, passive suspension cannot adapt suspension stiffness and damping to the vehicle's dynamic characteristics in real time, nor can it output active control forces. Consequently, passive suspension cannot adjust its control effectiveness based on road conditions and vehicle dynamics, resulting in poor control of vehicle dynamics under rapidly changing road conditions. Semi-active suspension uses less energy to control suspension stiffness or damping, achieving better control than passive suspension. With the continuous decline in the cost of semi-active suspension, its application in automobiles is becoming increasingly widespread. Semi-active suspensions based on air springs with magnetorheological dampers and air springs with CDC dampers have already been widely adopted in mid- to high-end passenger cars. However, semi-active suspensions still rely on the traditional "stiffness-damping" model, resulting in limited improvements in ride comfort and handling, making it difficult to achieve a higher-quality ride experience. Compared to the previous two, active suspension offers superior control and can output active control force while the car is in motion, directly acting on the vehicle body to achieve better control of ride comfort. However, current active suspensions suffer from drawbacks such as high energy consumption, complex structure, and high cost. Furthermore, the placement of actuators such as motors on the suspension presents challenges. These issues and shortcomings have significantly limited their widespread adoption in passenger cars, and they are currently only used on a few high-end models.

[0004] Active suspensions can output active control forces in real time based on road input to the wheels and changes in vehicle body dynamics. Their complex functionality places high demands on their control algorithms. Proportional-integral-derivative (PID) is a typical control algorithm with advantages such as fast response and simple design. However, it suffers from low control accuracy and poor stability when dealing with nonlinearities associated with suspension vibration. The linear quadratic regulator (LQR) effectively handles multi-input and multi-output (MIMO) problems, but it fails to consider control variable constraints when solving the optimal feedback matrix, potentially causing the output force to exceed the maximum force the actuator can provide, resulting in model distortion. Model predictive control (MPC) is a model-based optimal control algorithm that has been widely used in scenarios such as path planning for intelligent connected vehicles. For suspension systems, MPC's predictive nature and ability to account for hardware constraints by setting control variable limits have garnered widespread attention in the suspension control field. However, MPC requires high computational performance from the onboard controller and is time-consuming, making it difficult to achieve real-time control of the suspension system while the vehicle is in motion. While the use of MPC for suspension control has been widely studied, these factors have limited the application of model predictive control in automotive suspension control.

[0005] As vehicle applications and mission requirements expand, different scenarios and missions place varying demands on the number of axles. Traditional centralized control architectures must consider the number of axles during initial design phases. Changes in the number of axles require a complete redesign of the entire control architecture. Furthermore, while centralized control architectures theoretically achieve globally optimal control performance using a single control unit, their high integration requirements, difficulty in functional expansion, and excessive computational complexity limit their application. The automotive flexible chassis, a new type of chassis system with enhanced versatility, modular design, and controllability, utilizes a modular design, scalable structure, a universal electrical and electronic architecture, and multimodal control to distribute the control problem of the traditional chassis system to individual subsystems. This approach allows for flexible adaptation to diverse driving scenarios and mission requirements while significantly reducing the overall control load, making it a valuable research topic. Traditional centralized control methods, however, require simultaneous computation of all controller outputs, making them unsuitable for flexible chassis systems. There is an urgent need for a modular control strategy suitable for flexible chassis, which can independently control each module in the chassis system and achieve optimal control of the entire vehicle through communication between each module. Summary of the Invention

[0006] In order to solve the above-mentioned problems in active suspension control and application, the present invention proposes a vehicle active suspension control method for flexible chassis extension connection, so as to achieve optimal control of the dynamic parameters of the whole vehicle under various continuous random road conditions, while improving the vehicle's driving smoothness and handling stability, thereby significantly reducing the computational cost and calculation time of the active suspension control system, and lowering the requirements for the active suspension controller and the application cost.

[0007] In order to achieve the above-mentioned object, the present invention adopts the following technical solutions:

[0008] The vehicle active suspension control method for flexible chassis extension connection of the present invention is characterized by being performed according to the following steps:

[0009] Step 1: For a multi-axle active suspension system of a whole vehicle, establish the motion differential equations of the wheel suspension module and the body module of the whole vehicle respectively; wherein the motion differential equations of the wheel suspension module of the whole vehicle include: the vertical motion equation of the wheel;

[0010] The motion differential equations of the vehicle body module include: the vertical, pitch and roll motion equations of the vehicle body;

[0011] Step 2: Establish a correlation equation between the differential equations of motion of the wheel suspension module and the body module to obtain the forces generated by the suspension system and output to the vehicle body, as well as the vertical displacement generated by the vertical, pitch, and roll motions of the vehicle body and output to the individual active suspension systems;

[0012] Step 3: Based on the differential equations of motion and the correlation equations of the wheel suspension module and the body module, a vehicle dynamics model is established, and a dynamics control model of a single active suspension system is constructed;

[0013] The vehicle dynamics model includes: a dynamics model of the vehicle body and all active suspension systems;

[0014] The dynamic control model of the single active suspension system includes: a dynamic model of the body module and a dynamic control model of a single wheel suspension module;

[0015] Step 4: Based on the dynamic control model of a single wheel suspension module, with the optimal vehicle posture as the objective function and the dynamic response of the vehicle body as the control state variable, a model predictive control strategy is used to control any single active suspension system, thereby obtaining the active control force output by the single active suspension system;

[0016] Step 5: Use the influence of each wheel suspension module on the vertical acceleration of the vehicle body's center of mass and the body's roll and pitch angular acceleration as the consensus quantity between the wheel suspension modules, and use the consensus algorithm to adjust the active control force output by each active suspension system. The adjusted active control force is obtained and output, thereby achieving optimal control of the multi-axle vehicle's active suspension system to achieve the optimal posture of the entire vehicle.

[0017] The vehicle active suspension control method for flexible chassis extension connection according to the present invention is also characterized in that the vertical motion equations of the wheels in step 1 are as shown in equations (1) and (2):

[0018] (1)

[0019] (2)

[0020] In formula (1) and formula (2), 、 、 are the state matrix, input matrix, and interference matrix of the i-th wheel suspension module, respectively. express The derivative of represents the state matrix of the vertical motion of the body corner to which the i-th wheel suspension module is connected, is the output matrix of the i-th wheel suspension module, 、 、 、 、 、 、 and There are 8 coefficient matrices respectively, and there are:

[0021] (3)

[0022] (4)

[0023] (5)

[0024] In formula (3), is the vertical velocity of the i-th wheel suspension module, is the vertical displacement of the i-th wheel suspension module, is the active suspension force output by the i-th wheel suspension module, is the vertical excitation of the road surface on the i-th wheel suspension module, is the vertical velocity of the body corner to which the i-th wheel suspension module is connected, is the vertical displacement of the body corner to which the i-th wheel suspension module is connected, is the force output from the i-th wheel suspension module to the vehicle body, and T represents the transpose;

[0025] In formula (4) and formula (5), is the unsprung mass of the i-th wheel suspension module, is the wheel tire stiffness of the i-th wheel suspension module, is the suspension spring stiffness of the i-th wheel suspension module, is the suspension damping coefficient of the i-th wheel suspension module.

[0026] Furthermore, the vertical, pitch, and roll motion equations of the vehicle body in step 1 are shown in equation (6):

[0027] (6)

[0028] In formula (6), is the state matrix of the vehicle body, express The coefficient matrix of express The coefficient matrix of n is the number of wheel suspension modules, and there are:

[0029] (7)

[0030] In formula (7), is the vertical velocity of the body module, is the vertical displacement of the body module, is the roll angular velocity of the body module, is the roll angle of the body module, is the pitch angular velocity of the body module, is the pitch angle of the body module; is the mass of the body module, is the moment of inertia of the body module along the x-axis, is the moment of inertia of the body module along the y-axis, represents the vertical distance between the i-th wheel suspension module and the xz plane where the center of mass of the vehicle body is located, represents the vertical distance between the i-th wheel suspension module and the center of mass of the vehicle body on the xy plane;

[0031] The correlation equation between the motion differential equations of the wheel suspension module and the body module in step 2 is shown in equation (8):

[0032] (8)

[0033] In formula (8), is the coefficient matrix of the association equation between the wheel suspension module and the body module, and:

[0034] (9).

[0035] Furthermore, the vehicle dynamics model in step 3 is shown in formula (10):

[0036] (10)

[0037] The dynamic control model of the i-th active suspension system in step 3 is shown in formula (11):

[0038] (11)

[0039] In formula (11), represents the body state matrix of the dynamic control model of the i-th active suspension system, is the interference term of the i-th wheel suspension module itself and interference from all other wheel suspension modules The total interference term is composed of k≠i, and there is:

[0040] (12)

[0041] In formula (12), represents the output matrix of the k-th wheel suspension module, express The coefficient matrix of .

[0042] Furthermore, the objective function in step 4 is shown in formula (13):

[0043] (13)

[0044] In formula (13), Indicates the prediction step length, j is the current step number, is the state quantity of the body module at step j, is the desired body module state, represents the desired active force of the i-th active suspension system at the j-th step, represents the state of the body module at step j+1, is the state quantity of the i-th wheel suspension module in the j-th step, represents the total interference term of the i-th wheel suspension module at the j-th step, is the minimum value of the active force output by the active suspension actuator, The maximum value of the active force output by the active suspension actuator; 、 and There are three coefficient matrices respectively 、 and The three coefficient matrices after discretization are: is the time step.

[0045] Furthermore, the consensus algorithm in step 5 includes:

[0046] Step 5.1. Initialize j = 0 and calculate the output of the i-th wheel suspension module in the j-th step. The acceleration generated at the center of mass of the vehicle ;

[0047] Step 5.2: For the k-th wheel suspension module in step j, collect the output of the i-th wheel suspension module in step j. The acceleration generated at the center of mass of the vehicle body , ;

[0048] Step 5.3: For the k-th wheel suspension module in step j, Added to formula (11) In, that is , ; Thus, the dynamic control model of the kth active suspension system after the jth step update is obtained;

[0049] Step 5.4: Solve the objective function to obtain the optimal active force output by the active suspension of the k-th wheel suspension module in step j. ;

[0050] Step 5.5, Substitute into equations (1) and (2) to obtain the output of the k-th wheel suspension module in step j+1: And calculate the output of the kth wheel suspension module in the j+1th step through formula (14) The acceleration generated at the center of mass of the vehicle ;

[0051] (14)

[0052] In formula (14), represents the update coefficient, and ;

[0053] Step 5.6: If , then stop the calculation and output ; Otherwise, execute step 5.7, where represents the consensus threshold;

[0054] Step 5.7, let Assign to Afterwards, if , then stop the calculation and output Otherwise, return to step 5.2 and execute in sequence, where: Indicates the maximum number of iterations allowed.

[0055] The electronic device of the present invention includes a memory and a processor, and is characterized in that the memory is used to store a program that supports the processor to execute the vehicle active suspension control method, and the processor is configured to execute the program stored in the memory.

[0056] The present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program executes the steps of the vehicle active suspension control method when the computer program is executed by a processor.

[0057] Compared with the prior art, the beneficial effects of the present invention are embodied in:

[0058] 1. The present invention decomposes the original control problem of the high-dimensional mathematical model of the active suspension of the whole vehicle into the control problem of the low-dimensional mathematical model of each wheel suspension system in the control problem of the whole vehicle suspension system, thereby reducing the consumption of computing resources and computing time in the control process. In the traditional control problem of the active suspension of the whole vehicle, when control algorithms such as LQR and MPC are used to uniformly control the suspension system of the whole vehicle, the model is too complex and the control algorithm takes a long time to calculate, which limits the application of active suspension in passenger cars to a certain extent. The distributed automobile suspension control algorithm proposed in the present invention decomposes the original control problem of the whole vehicle suspension into the control problem of a single wheel suspension model, reducing the hardware cost and the time cost of calculation, thereby realizing the application of active suspension in passenger cars.

[0059] 2. When designing a control strategy for active suspension, the present invention uses the dynamic response of the vehicle body as the state variable to be controlled by the model predictive control strategy of the individual wheel suspension module controller. Since only the two-degree-of-freedom model of each suspension is controlled, the control effect of this distributed control strategy is inferior to that of the integrated suspension control strategy, but the model complexity and calculation speed are superior to the integrated control strategy. To improve the control effect of this control strategy on the entire vehicle, a consensus coordination algorithm is used to coordinate the active control force output by each active suspension actuator to achieve better control of the entire vehicle.

[0060] 3. In the control problem of active suspension system, the present invention adopts the following method to coordinate the active control force output by each suspension system actuator to achieve the optimal control effect of the dynamic response of the whole vehicle. Figure 5The consensus coordination algorithm shown is used to coordinate the main power output of each suspension. In traditional two-degree-of-freedom suspension systems, only the dynamic response of the suspension connecting to the vehicle body corner is considered when controlling the suspension. This makes it difficult to achieve optimal control of the dynamic response of the entire vehicle when controlling the entire vehicle. The present invention adopts a consensus coordination method to iteratively coordinate the output force of each wheel suspension system. By controlling the number of iterations, it balances the contradiction between computational cost and control effect, and achieves optimal control effect for the entire vehicle using a control method similar to the two-degree-of-freedom suspension model.

[0061] 4. The present invention greatly reduces the cost of redesigning the vehicle model when the number of axles of the vehicle needs to be changed, shortens the time required for design, and thus realizes a more convenient modification of the number of axles of the vehicle and the control of the suspension system. The present invention can create a vehicle with different numbers of axles by adding or subtracting wheel suspension modules. Unlike the traditional vehicle model, which requires the whole vehicle to be remodeled, the present invention only modifies the vehicle model by changing the body model. At the same time, since only the body parameter items need to be changed when designing the controller after modifying the vehicle model, the difficulty of controller design is also reduced, the design process of the vehicle suspension system is simplified, the design cycle of the vehicle suspension system is shortened, and the vehicle's adaptability to different application scenarios and task requirements is enhanced. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 It is a schematic diagram of a single wheel suspension module;

[0063] Figure 2 A schematic diagram of a body module of a multi-axle vehicle;

[0064] Figure 3 It is a schematic diagram of the body module of a two-axle vehicle;

[0065] Figure 4 This is the flow chart of the distributed control strategy for the active suspension;

[0066] Figure 5 Flowchart for achieving consensus coordination between wheel suspension modules. DETAILED DESCRIPTION

[0067] In this embodiment, the Figure 1 The wheel suspension system model shown and Figure 2 The multi-axis vehicle body system model shown in Figure 1 is used, and a vehicle suspension distributed control system based on model predictive control strategy is established, as shown in Figure 1. Figure 4As shown in the figure. To simplify the calculations during the modeling process, the following assumptions are made: the wheels are mounted perpendicular to the ground and can only move vertically; only the vertical, pitch, and roll motions of the vehicle body are considered; and the vehicle body is a rigid body. During vehicle operation, the active output force of the suspension acts directly on the vehicle body and wheels, thereby alleviating vehicle vibration and ensuring smooth driving. Specifically, using the seven-degree-of-freedom suspension system of a two-axle, four-wheel vehicle model as an example, the suspension control method is carried out according to the following steps:

[0068] Step 1: Establish a vehicle active suspension control method for flexible chassis expansion connection. Taking the seven-degree-of-freedom suspension system of a two-axle four-wheel vehicle model as an example, build the wheel suspension model and body model of the seven-degree-of-freedom suspension system, as shown in the following figure. Figure 1 and Figure 3 As shown, kinematic modeling is first performed on the wheel suspension module and the body module, and their motion differential equations are established respectively. Then, the state space equations of motion are established based on their motion differential equations.

[0069] Step 1.1: For the multi-axle active suspension system of the vehicle, establish the motion differential equations of the wheel suspension module and the body module of the vehicle respectively;

[0070] Step 1.1.1. The differential equation of motion of the wheel suspension module of the entire vehicle, including the vertical motion equation of the wheel, is used to write the state space equation of the motion of a single wheel suspension module:

[0071] Differential equations of motion for a single wheel suspension module:

[0072] (1)

[0073] Output of a single wheel suspension module to the body module:

[0074] (2)

[0075] In formula (1) and formula (2), is the vertical acceleration of the i-th wheel suspension module, is the vertical velocity of the i-th wheel suspension module, is the vertical displacement of the i-th wheel suspension module, is the active suspension force output by the i-th wheel suspension module, is the vertical excitation of the road surface on the i-th wheel suspension module, is the vertical velocity of the body corner to which the i-th wheel suspension module is connected, is the vertical displacement of the car body corner connected to the i-th suspension system, is the force output from the i-th wheel suspension module to the vehicle body, is the unsprung mass of the i-th wheel suspension module, is the wheel tire stiffness of the i-th wheel suspension module, is the suspension spring stiffness of the i-th wheel suspension module, is the suspension damping coefficient of the i-th wheel suspension module.

[0076] The state space equation of the motion of a single wheel suspension module of the established distributed model of the vehicle suspension system is as follows:

[0077] (3)

[0078] In formula (3), 、 、 are the state matrix, input matrix, and interference matrix of the i-th wheel suspension module, respectively. for The derivative of is the state matrix of the vertical motion of the body corner connected to the i-th wheel suspension module, is the output matrix of the i-th wheel suspension module, 、 、 、 、 、 、 and There are 8 coefficient matrices respectively, and there are:

[0079] (4)

[0080] (5)

[0081] (6)

[0082] In formula (4), T represents transposition;

[0083] Step 1.1.2: The differential equations of motion for the body module, including the vertical, pitch, and roll equations of motion for the body, are used to write the state-space equations for the body module during motion:

[0084] The differential equation of vehicle body motion is:

[0085] Vertical movement:

[0086] (7)

[0087] Rolling motion:

[0088] (8)

[0089] Pitching motion:

[0090] (9)

[0091] In formula (8) and formula (9): (10)

[0092] The state space equations of the body module motion of the established distributed model of the vehicle suspension system are as follows:

[0093] (11)

[0094] In formula (11), is the state matrix of the vehicle body, express The coefficient matrix of express The coefficient matrix of , and there are:

[0095] (12)

[0096] In formula (12), is the vertical velocity of the body module, is the vertical displacement of the body module, is the roll angular velocity of the body module, is the roll angle of the body module, is the pitch angular velocity of the body module, is the pitch angle of the body module; is the mass of the body module, is the moment of inertia of the body module along the x-axis, is the moment of inertia of the body module along the y-axis, represents the vertical distance between the i-th wheel suspension module and the xz plane where the center of mass of the vehicle body is located, represents the vertical distance between the i-th wheel suspension module and the center of mass of the vehicle body on the xy plane;

[0097] Step 1.2: Establish the correlation equations between the differential equations of motion of the wheel suspension module and the body module, so as to obtain the force generated by the suspension system and output to the body, as well as the vertical displacement generated by the vertical, pitch and roll motions of the body and output to the single active suspension system. By assuming that the body is a rigid body, the vertical motion of the center of mass of the body is Vertical movement of the body corners connected to each wheel suspension module The relationship between them is:

[0098] (13)

[0099] In formula (13), is the coefficient matrix of the association equation between the wheel suspension module and the body module, and:

[0100] (14)

[0101] Through the above steps, the dynamic modeling of the wheel suspension module and the body module has been completed respectively, and the establishment of the correlation equation between the motion differential equations of the body module and the wheel suspension module has been completed, that is, the force output from the wheel suspension module to the body module And the vertical displacement output from the body module to the wheel suspension module , through the above equations, the dynamic equation of the whole vehicle can be established;

[0102] Step 2: Based on the differential equations of motion and the correlation equations of the wheel suspension module and the body module, establish a vehicle dynamics model and a dynamics control model of a single active suspension system; based on the differential equations of motion of the wheel suspension module and the body module in step 1, and the correlation equations between the differential equations of motion of the body module and the wheel suspension module, establish a vehicle dynamics model based on the wheel suspension module and the body module:

[0103] (15)

[0104] Since the vehicle dynamics model includes the body model and all wheel models, it cannot be directly used to design the control strategy of a single active suspension. Therefore, a dynamic model that can be used for the control of a single active suspension in a distributed suspension system is established for a single wheel suspension module and a body module. Its specific form is as follows:

[0105] (16)

[0106] In formula (16), represents the body state matrix of the dynamic control model of the i-th active suspension system, is the interference term of the i-th wheel suspension module itself and interference from all other wheel suspension modules The total interference term composed of k≠i, and:

[0107] (17)

[0108] In formula (17), represents the output matrix of the k-th wheel suspension module, express The coefficient matrix of ;

[0109] Step 3: Based on the dynamic control model of a single wheel suspension module, with the optimal vehicle posture as the objective function and the dynamic response of the vehicle body as the control state, a model predictive control strategy is used to control any single active suspension system, thereby obtaining the active control force output by the single active suspension system. The objective function of the model predictive control strategy is shown in Equation (18):

[0110] (18)

[0111] In formula (18), Indicates the prediction step length, j is the current step number, is the state quantity of the body module at step j, is the desired state of the body module, represents the expected active force of the i-th active suspension system at the j-th step, represents the state of the body module at step j+1, is the state quantity of the i-th wheel suspension module in the j-th step, represents the total interference term of the i-th wheel suspension module at the j-th step, is the minimum value of the active force output by the active suspension actuator, The maximum value of the active force output by the active suspension actuator; 、 and are the coefficient matrices in formula (11) 、 and The three coefficient matrices after discretization are: The above control strategy is used to calculate the active suspension force required to control each suspension.

[0112] Step 4. Since only a single wheel suspension model is controlled in step 3, to achieve optimal control of the vehicle's posture, it is necessary to design a consensus coordination algorithm between control strategies for different wheel suspension models. The influence of each wheel suspension module on the vertical acceleration of the vehicle's center of mass and the body's roll and pitch acceleration is used as the consensus quantity between each wheel suspension module. The consensus algorithm is used to adjust the active control force output by each active suspension system, and the adjusted active control force is obtained and output, thereby achieving optimal control of the multi-axle vehicle's active suspension system to achieve the optimal posture of the vehicle. Through the consensus coordination algorithm, the main force output by each active suspension system is achieved to optimize the posture of the vehicle, so as to achieve optimal control of the vehicle. The execution logic of the designed consensus coordination algorithm is as follows: Figure 5 As shown, the specific iterative process is as follows:

[0113] Step 4.1. Initialize j = 0 and calculate the output of the i-th wheel suspension module in the j-th step The acceleration generated at the center of mass of the vehicle ;

[0114] Step 4.2: For the kth wheel suspension module in step j, collect the output of the ith wheel suspension module in step j. The acceleration generated at the center of mass of the vehicle , ;

[0115] Step 4.3: For the k-th wheel suspension module in step j, Added to formula (16) , thus obtaining the dynamic control model of the kth active suspension system after the jth step update, where , ;

[0116] Step 4.4: Solve the objective function to obtain the optimal active force output by the active suspension of the k-th wheel suspension module in step j. ;

[0117] Step 4.5, Substitute into equation (3) to obtain the output of the kth wheel suspension module in step j+1: And calculate the output of the kth wheel suspension module in the j+1th step through formula (19) The acceleration generated at the center of mass of the vehicle ;

[0118] (19)

[0119] In formula (19), represents the update coefficient, and ;

[0120] Step 4.6, if , then stop the calculation and output ; Otherwise, execute step 4.7, where represents the consensus threshold;

[0121] Step 4.7, let Assign to Afterwards, if , then stop the calculation and output Otherwise, return to step 4.2 and execute in sequence, where: Indicates the maximum number of iterations allowed.

[0122] In this embodiment, an electronic device includes a memory and a processor, wherein the memory is used to store a program that supports the processor to execute the above method, and the processor is configured to execute the program stored in the memory.

[0123] In this embodiment, a computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method are executed.

[0124] In summary, the present invention reduces the requirements for the computing power of the hardware computing unit on the basis of ensuring the active suspension function, and realizes the application of active suspension on existing passenger cars at a lower cost on the basis of ensuring the basic functions of the active suspension. In addition, since the distributed suspension has the characteristics of modular design and an expandable structure, when increasing or decreasing the number of vehicle axles, it is only necessary to modify the body module in the distributed suspension model without having to reconstruct the model of the entire vehicle, which greatly improves the adaptability of the vehicle to different scenarios and task requirements. On the basis of the suspension, the driving, braking and steering functions of the entire vehicle chassis can be incorporated into the design of the wheel module to form a fully functional flexible chassis for the vehicle.

Claims

1. A vehicle active suspension control method for flexible chassis extension connection, characterized in that: The steps are as follows: Step 1: For a multi-axle active suspension system of a whole vehicle, establish the motion differential equations of the wheel suspension module and the body module of the whole vehicle respectively; wherein the motion differential equations of the wheel suspension module of the whole vehicle include: the vertical motion equation of the wheel; The motion differential equations of the vehicle body module include: the vertical, pitch and roll motion equations of the vehicle body; Step 2: Establish a correlation equation between the differential equations of motion of the wheel suspension module and the body module to obtain the forces generated by the suspension system and output to the vehicle body, as well as the vertical displacement generated by the vertical, pitch, and roll motions of the vehicle body and output to the individual active suspension systems; Step 3: Based on the differential equations of motion and the correlation equations of the wheel suspension module and the body module, a vehicle dynamics model is established, and a dynamics control model of a single active suspension system is constructed; The vehicle dynamics model includes: a dynamics model of the vehicle body and all active suspension systems; The dynamic control model of the single active suspension system includes: a dynamic model of the body module and a dynamic control model of a single wheel suspension module; Step 4: Based on the dynamic control model of a single wheel suspension module, with the optimal vehicle posture as the objective function and the dynamic response of the vehicle body as the control state variable, a model predictive control strategy is used to control any single active suspension system, thereby obtaining the active control force output by the single active suspension system; Step 5: Use the influence of each wheel suspension module on the vertical acceleration of the vehicle body's center of mass and the body's roll and pitch angular acceleration as the consensus quantity between the wheel suspension modules, and use the consensus algorithm to adjust the active control force output by each active suspension system. The adjusted active control force is obtained and output, thereby achieving optimal control of the multi-axle vehicle's active suspension system to achieve the optimal posture of the entire vehicle.

2. The vehicle active suspension control method for flexible chassis extension connection according to claim 1, characterized in that: The vertical motion equations of the wheels in step 1 are shown in equations (1) and (2): (1) (2) In formula (1) and formula (2), 、 、 are the state matrix, input matrix, and interference matrix of the i-th wheel suspension module, respectively. express The derivative of represents the state matrix of the vertical motion of the body corner to which the i-th wheel suspension module is connected, is the output matrix of the i-th wheel suspension module, 、 、 、 、 、 、 and There are 8 coefficient matrices respectively, and there are: (3) (4) (5) In formula (3), is the vertical velocity of the i-th wheel suspension module, is the vertical displacement of the i-th wheel suspension module, is the active suspension force output by the i-th wheel suspension module, is the vertical excitation of the road surface on the i-th wheel suspension module, is the vertical velocity of the body corner to which the i-th wheel suspension module is connected, is the vertical displacement of the body corner to which the i-th wheel suspension module is connected, is the force output from the i-th wheel suspension module to the vehicle body, and T represents the transpose; In formula (4) and formula (5), is the unsprung mass of the i-th wheel suspension module, is the wheel tire stiffness of the i-th wheel suspension module, is the suspension spring stiffness of the i-th wheel suspension module, is the suspension damping coefficient of the i-th wheel suspension module.

3. The vehicle active suspension control method for flexible chassis extension connection according to claim 2, characterized in that: The vertical, pitch and roll motion equations of the vehicle body in step 1 are shown in equation (6): (6) In formula (6), is the state matrix of the vehicle body, express The coefficient matrix of express The coefficient matrix of n is the number of wheel suspension modules, and there are: (7) In formula (7), is the vertical velocity of the body module, is the vertical displacement of the body module, is the roll angular velocity of the body module, is the roll angle of the body module, is the pitch angular velocity of the body module, is the pitch angle of the body module; is the mass of the body module, is the moment of inertia of the body module along the x-axis, is the moment of inertia of the body module along the y-axis, represents the vertical distance between the i-th wheel suspension module and the xz plane where the center of mass of the vehicle body is located, represents the vertical distance between the i-th wheel suspension module and the center of mass of the vehicle body on the xy plane; The correlation equation between the motion differential equations of the wheel suspension module and the body module in step 2 is shown in equation (8): (8) In formula (8), is the coefficient matrix of the association equation between the wheel suspension module and the body module, and: (9)。 4. The vehicle active suspension control method for flexible chassis extension connection according to claim 3, characterized in that: The vehicle dynamics model in step 3 is shown in formula (10): (10) The dynamic control model of the i-th active suspension system in step 3 is shown in formula (11): (11) In formula (11), represents the body state matrix of the dynamic control model of the i-th active suspension system, is the interference term of the i-th wheel suspension module itself and interference from all other wheel suspension modules The total interference term composed of k≠i, and: (12) In formula (12), represents the output matrix of the k-th wheel suspension module, express The coefficient matrix of .

5. The vehicle active suspension control method for flexible chassis extension connection according to claim 4, characterized in that: The objective function in step 4 is shown in formula (13): (13) In formula (13), Indicates the prediction step length, j is the current step number, is the state quantity of the body module at step j, is the desired body module state, represents the desired active force of the i-th active suspension system at the j-th step, represents the state of the body module at step j+1, is the state quantity of the i-th wheel suspension module in the j-th step, represents the total interference term of the i-th wheel suspension module at the j-th step, is the minimum value of the active force output by the active suspension actuator, The maximum value of the active force output by the active suspension actuator; 、 and There are three coefficient matrices respectively 、 and The three coefficient matrices after discretization are: is the time step.

6. The vehicle active suspension control method for flexible chassis extension connection according to claim 5, characterized in that: The consensus algorithm in step 5 includes: Step 5.

1. Initialize j = 0 and calculate the output of the i-th wheel suspension module in the j-th step. The acceleration generated at the center of mass of the vehicle ; Step 5.2: For the k-th wheel suspension module in step j, collect the output of the i-th wheel suspension module in step j. The acceleration generated at the center of mass of the vehicle body , ; Step 5.3: For the k-th wheel suspension module in step j, Added to formula (11) In, that is , ; Thus, the dynamic control model of the kth active suspension system after the jth step update is obtained; Step 5.4: Solve the objective function to obtain the optimal active force output by the active suspension of the k-th wheel suspension module in step j. ; Step 5.5, Substitute into equations (1) and (2) to obtain the output of the k-th wheel suspension module in step j+1: And calculate the output of the kth wheel suspension module in the j+1th step through formula (14) The acceleration generated at the center of mass of the vehicle ; (14) In formula (14), represents the update coefficient, and ; Step 5.6: If , then stop the calculation and output ; Otherwise, execute step 5.7, where represents the consensus threshold; Step 5.7, let Assign to Afterwards, if , then stop the calculation and output ; Otherwise, return to step 5.2 and execute in sequence, where, Indicates the maximum number of iterations allowed.

7. An electronic device comprising a memory and a processor, characterized in that: The memory is used to store a program that supports the processor to execute the vehicle active suspension control method according to any one of claims 1 to 6, and the processor is configured to execute the program stored in the memory.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the vehicle active suspension control method according to any one of claims 1 to 6 are executed.

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