A cooperative control method, device and equipment for vehicle steering

Abstract

The application discloses a kind of vehicle steering collaborative control method, device and equipment, the method comprises: first using the real-time operating parameter of target vehicle, linearization is handled to the vehicle dynamics model constructed using its physical parameter, obtain linearized model;Then the model is discretized and differentiated, and the model after differentiation is obtained;According to the driving intention of target driver on target vehicle, the real-time state target value of target vehicle steering is calculated, and the steady-state feedforward control amount of target vehicle is calculated using real-time state target value and linearized model.And using real-time state target value and the model after differentiation, the feedback control amount of target vehicle is calculated based on LQR, then the accumulation of steady-state feedforward control amount and feedback control amount is used as the output control amount of target vehicle corresponding actuator, to carry out collaborative control to the steering of target vehicle, to realize the driving intention of target driver, improve control effect and driving experience.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicles, in particular to a cooperative control method, device and equipment for vehicle steering. BACKGROUND

[0002] With the improvement of people's living standards and the rapid development of social economy, the use rate of automobiles is gradually increasing, and more and more automobiles have entered people's life, bringing great convenience to all aspects of people's life. Among them, how to improve the driving and riding experience of users and ensure the safety and stability of vehicle driving is particularly important.

[0003] At present, the vehicle often appears understeering or oversteering phenomenon when turning, and cannot completely track the driving intention of the user. For this, the existing control method is to activate the vehicle dynamic control (VDC) function, and change the yaw angular velocity of the vehicle by increasing the braking force to one wheel of the vehicle, so as to improve the problem of inaccurate vehicle steering. However, this control method can only complete the stability control of the vehicle by applying the braking force to a single wheel of the vehicle, and during the activation of VDC, the longitudinal speed of the vehicle cannot be guaranteed, which violates the driving intention of the user and reduces the driving experience of the user. SUMMARY

[0004] The main purpose of the embodiments of the present application is to provide a cooperative control method, device and equipment for vehicle steering, which can realize cooperative control of vehicle steering, so as to guarantee the driving intention of the driver while minimizing the subjective perception of the driver to active intervention, thereby improving the steering control effect of the vehicle and the driving experience of the driver.

[0005] The embodiments of the present application provide a cooperative control method for vehicle steering, comprising:

[0006] Obtaining vehicle physical parameters of a target vehicle to be controlled, and constructing a vehicle dynamics model by using the vehicle physical parameters of the target vehicle;

[0007] Obtaining real-time running parameters of the target vehicle, and performing linearization processing on the vehicle dynamics model by using the real-time running parameters of the target vehicle to obtain a linearized vehicle dynamics model;

[0008] Discretizing the linearized vehicle dynamics model to obtain a discretized vehicle dynamics model, and differentiating the discretized vehicle dynamics model to obtain a differentiated vehicle dynamics model;

[0009] According to the driving intention of the target driver on the target vehicle, a real-time state target value of the target vehicle steering is calculated, and a steady-state feedforward control amount of the target vehicle is calculated by using the real-time state target value of the target vehicle steering and the linearized vehicle dynamics model;

[0010] A feedback control amount of the target vehicle is calculated based on a linear quadratic regulator (LQR) by using the real-time state target value of the target vehicle steering and the differentiated vehicle dynamics model;

[0011] An accumulated sum of the steady-state feedforward control amount and the feedback control amount is taken as an output control amount of an actuator corresponding to the target vehicle, and the steering of the target vehicle is cooperatively controlled by using the output control amount, so as to realize the driving intention of the target driver.

[0012] In an optional implementation, the vehicle physical parameters of the target vehicle include a front half track, a rear half track, a wheel track, a total vehicle mass, a yaw moment of inertia and front and rear wheel cornering stiffness of the target vehicle.

[0013] In an optional implementation, the vehicle dynamics model is constructed by using the vehicle physical parameters of the target vehicle, including:

[0014] The vehicle dynamics model is constructed by using the front half track, the rear half track, the wheel track, the total vehicle mass, the yaw moment of inertia and the front and rear wheel cornering stiffness of the target vehicle, while ignoring the force arm change of the longitudinal force caused by the front wheel steering angle.

[0015] In an optional implementation, the real-time running parameters of the target vehicle include a vehicle yaw rate, a center of mass cornering angle and a longitudinal speed of the target vehicle in a current running state; and the linearization processing of the vehicle dynamics model by using the real-time running parameters of the target vehicle to obtain the linearized vehicle dynamics model includes:

[0016] The linearization processing of the vehicle dynamics model by using the vehicle yaw rate, the center of mass cornering angle and the longitudinal speed of the target vehicle in the current running state to obtain the linearized vehicle dynamics model.

[0017] In an optional implementation, the real-time state target value of the target vehicle steering includes a vehicle yaw rate target value and a longitudinal vehicle speed target value of the target vehicle in the current running state.

[0018] In an optional implementation, the feedback control amount of the target vehicle is calculated based on the linear quadratic regulator (LQR) by using the real-time state target value of the target vehicle steering and the differentiated vehicle dynamics model, including:

[0019] The vehicle yaw rate target value and longitudinal speed target value under the current operating state of the target vehicle are used as control targets. Based on the vehicle dynamics model after differentiation, LQR is used to calculate the feedback control amount of the front wheel turning angle and the left and right wheel tire forces of the target vehicle.

[0020] In an optional implementation, calculating the steady-state feedforward control variable of the target vehicle by using the real-time state target value of the target vehicle steering and the linearized vehicle dynamics model includes:

[0021] The center of mass sideslip angle of the target vehicle is set to zero, and the vehicle yaw rate target value and longitudinal speed target value of the target vehicle in the current operating state are used as control targets. Based on the linearized vehicle dynamics model, the steady-state feedforward control amount of the target vehicle is calculated.

[0022] Corresponding to the above-mentioned coordinated control method for vehicle steering, the present application proposes a coordinated control device for vehicle steering, comprising:

[0023] A construction unit, configured to obtain vehicle physical parameters of a target vehicle to be controlled, and construct a vehicle dynamics model using the vehicle physical parameters of the target vehicle;

[0024] a linearization unit, configured to obtain real-time operating parameters of the target vehicle and linearize the vehicle dynamics model using the real-time operating parameters of the target vehicle to obtain a linearized vehicle dynamics model;

[0025] a discretization unit, configured to discretize the linearized vehicle dynamics model to obtain a discretized vehicle dynamics model; and perform a differentiation process on the discretized vehicle dynamics model to obtain a differentiated vehicle dynamics model;

[0026] a first calculation unit, configured to calculate a real-time state target value of the target vehicle's steering according to a driving intention of a target driver on the target vehicle, and calculate a steady-state feedforward control variable of the target vehicle using the real-time state target value of the target vehicle's steering and the linearized vehicle dynamics model;

[0027] a second calculation unit, configured to calculate a feedback control variable of the target vehicle based on a linear quadratic regulator (LQR) by using the real-time state target value of the target vehicle's steering and the vehicle dynamics model after differentiation;

[0028] A control unit is used to use the cumulative sum of the steady-state feedforward control amount and the feedback control amount as the output control amount of the actuator corresponding to the target vehicle, and use the output control amount to coordinately control the steering of the target vehicle to achieve the driving intention of the target driver.

[0029] In an optional implementation, the vehicle physical parameters of the target vehicle include the front half wheelbase, rear half wheelbase, track width, vehicle mass, yaw moment of inertia, and front and rear wheel cornering stiffness of the target vehicle.

[0030] In an optional implementation, the construction unit is specifically configured to:

[0031] Ignoring the change in the moment arm of the longitudinal force caused by the front wheel turning angle, a vehicle dynamics model is constructed using the front half wheelbase, rear half wheelbase, track width, vehicle mass, yaw moment of inertia, and front and rear wheel cornering stiffness of the target vehicle.

[0032] In an optional implementation, the real-time operating parameters of the target vehicle include the vehicle yaw rate, center of mass sideslip angle, and longitudinal speed in the current operating state of the target vehicle; and the linearization unit is specifically configured to:

[0033] The vehicle dynamics model is linearized using the vehicle yaw rate, center of mass sideslip angle, and longitudinal speed of the target vehicle in a current operating state to obtain a linearized vehicle dynamics model.

[0034] In an optional implementation, the real-time state target value of the target vehicle steering includes a vehicle yaw angular velocity target value and a longitudinal vehicle speed target value under the current operating state of the target vehicle.

[0035] In an optional implementation, the second computing unit is specifically configured to:

[0036] The vehicle yaw rate target value and longitudinal speed target value under the current operating state of the target vehicle are used as control targets. Based on the vehicle dynamics model after differentiation, LQR is used to calculate the feedback control amount of the front wheel turning angle and the left and right wheel tire forces of the target vehicle.

[0037] In an optional implementation, the first computing unit is specifically configured to:

[0038] The center of mass sideslip angle of the target vehicle is set to zero, and the vehicle yaw rate target value and longitudinal speed target value of the target vehicle in the current operating state are used as control targets. Based on the linearized vehicle dynamics model, the steady-state feedforward control amount of the target vehicle is calculated.

[0039] The embodiment of the present application further provides a coordinated control device for vehicle steering, comprising: a processor, a memory, and a system bus;

[0040] The processor and the memory are connected via the system bus;

[0041] The memory is configured to store one or more programs, the one or more programs including instructions that, when executed by the processor, cause the processor to perform any one of the implementation manners of the cooperative control method of vehicle steering.

[0042] The embodiment of the present application further provides a computer readable storage medium, wherein instructions are stored in the computer readable storage medium, and when the instructions run on a terminal device, the terminal device executes any one of the implementation manners of the cooperative control method of vehicle steering.

[0043] Therefore, the embodiment of the present application has the following beneficial effects:

[0044] The embodiment of the present application provides a cooperative control method, device and equipment of vehicle steering. Firstly, vehicle physical parameters of a target vehicle to be controlled are acquired, and a vehicle dynamics model is constructed by using the vehicle physical parameters of the target vehicle. Then, real-time running parameters of the target vehicle are acquired, and the vehicle dynamics model is linearized by using the real-time running parameters of the target vehicle to obtain a linearized vehicle dynamics model. Next, the linearized vehicle dynamics model is discretized to obtain a discretized vehicle dynamics model, and the discretized vehicle dynamics model is differentiated to obtain a differentiated vehicle dynamics model. Furthermore, real-time state target values of target vehicle steering are calculated according to a driving intention of a target driver on the target vehicle, and a steady-state feedforward control amount of the target vehicle is calculated by using the real-time state target values of the target vehicle steering and the linearized vehicle dynamics model. In addition, a feedback control amount of the target vehicle is calculated based on a linear quadratic regulator (LQR) by using the real-time state target values of the target vehicle steering and the differentiated vehicle dynamics model. Finally, an accumulation of the steady-state feedforward control amount and the feedback control amount is taken as an output control amount of an actuator corresponding to the target vehicle, and the output control amount is used to cooperatively control the steering of the target vehicle, so as to realize the driving intention of the target driver.

[0045] Thus, the cooperative control of the target vehicle steering is realized, which not only ensures the driving intention of the target driver, but also reduces subjective perception caused by the active intervention of the target driver in the control function, thereby improving the steering control effect of the target vehicle and the driving experience of the target driver. BRIEF DESCRIPTION OF DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiment or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0047] Figure 1 A flowchart of a cooperative control method of vehicle steering provided for an embodiment of the present application;

[0048] Figure 2 An example diagram of the meanings of various parameter variables in a vehicle dynamics model provided for an embodiment of the present application;

[0049] Figure 3 An example simulation diagram of a cooperative control method of vehicle steering provided for an embodiment of the present application;

[0050] Figure 4 A composition schematic diagram of a cooperative control device of vehicle steering provided for an embodiment of the present application. DETAILED DESCRIPTION

[0051] In order to make the purposes, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0052] As is known, with the continuous progress of high-tech such as cloud computing, artificial intelligence, modern sensing, information fusion and communication, the future development speed of vehicles will also be accelerated, and people's perception and driving needs for vehicles are also gradually increasing. At present, under the promotion of the platformization of vehicle motion domain computing control and the standardization of the line control execution system, the vehicle motion domain can coordinate the control of the vehicle driving, braking and steering systems. For example, in the process of turning the car, in order to accurately realize the driving steering intention and improve the situation of insufficient / over steering, it can be realized by actively intervening the front wheel steering angle through the line control steering system, or by intervening the longitudinal force through the line control driving and braking system. Therefore, how to cooperatively allocate the control amount of the horizontal and longitudinal directions to achieve the optimal control effect is a problem that must be solved. However, the current vehicle control algorithm is basically a horizontal and longitudinal decoupling control method, and the stability correction strategy largely adopts experience control rules and simple allocation methods, which is difficult to achieve optimal control effect.

[0053] For example, when the vehicle is understeering or oversteering, the existing control method is to activate the VDC function, and change the yaw angular velocity of the vehicle by increasing the braking force of a certain wheel of the vehicle, so as to improve the problem of inaccurate vehicle steering. However, this control method can only complete the stability control of the vehicle by applying the braking force on a single wheel of the vehicle, and during the VDC activation, the longitudinal speed of the vehicle cannot be guaranteed, which violates the driving intention of the user. In addition, this control method cannot improve the steering performance of the vehicle by changing the front wheel steering angle, and the driver may need to constantly correct the steering wheel angle to ensure the correctness of the steering, which increases the burden of the driver on the vehicle and enhances the perception of the driver when the VDC intervenes, thereby reducing the driving experience of the user.

[0054] Therefore, the application provides a cooperative control method, device and equipment for vehicle steering, which can realize cooperative control of target vehicle steering, not only guaranteeing the driving intention of the following driver, but also minimizing the subjective perception of the driver caused by active intervention of the control function, thereby improving the steering control effect of the target vehicle and the driving experience of the driver.

[0055] The cooperative control method for vehicle steering provided by the embodiments of the application will be described in detail below with reference to the accompanying drawings. Referring to FIG. 1, a flowchart of an embodiment of the cooperative control method for vehicle steering provided by the application is shown, and the embodiment can include the following steps: Figure 1

[0056] S101: Obtain the vehicle physical parameters of a target vehicle to be controlled, and construct a vehicle dynamics model by using the vehicle physical parameters of the target vehicle.

[0057] ​In this embodiment, any vehicle that utilizes the method of the application to achieve cooperative control of steering is defined as a target vehicle to be controlled. In order to achieve cooperative control of steering of the target vehicle and improve the steering control effect of the target vehicle and the driving experience of the driver, the control scheme proposed by the application is: when the target vehicle is steering, the optimal control mode is solved by using the linear quadratic regulator (LQR) algorithm to balance the front wheel steering angle of the target vehicle and the size of the braking / driving force of the two sides of the vehicle. And by actively correcting the front wheel steering angle or applying different braking / driving force correction to the left and right sides of the vehicle, the vehicle yaw moment is changed, so that the requirements of the vehicle yaw angular velocity and the vehicle longitudinal speed can be met at the same time. At this time, due to the characteristics of the line control system, the steering wheel angle will not be changed, and the stroke of the brake / drive pedal will not be changed, thereby the subjective perception of the driver caused by the active intervention of the control function can be minimized while ensuring the following driving intention, and the steering control effect of the target vehicle and the driving experience of the driver are improved.

[0058] Specifically, first, the vehicle physical parameters of the target vehicle to be controlled need to be obtained, and the vehicle dynamics model is constructed using the vehicle physical parameters of the target vehicle to perform the subsequent step S102.

[0059] The vehicle physical parameters of the target vehicle can include but are not limited to the front half track of the target vehicle (hereinafter defined as a), the rear half track (hereinafter defined as b), the wheel track (hereinafter defined as t), the vehicle mass (hereinafter defined as m), the yaw moment of inertia (hereinafter defined as I z ), and the front and rear wheel cornering stiffness (hereinafter defined as C f and C r ).

[0060] When constructing the vehicle dynamics model, the application considers that the vehicle is moving on a horizontal plane, ignores the vertical related degrees of freedom of the vehicle, and ignores the change of the force arm of the longitudinal force caused by the front wheel steering angle. The vehicle dynamics model established by using the vehicle physical parameters of the target vehicle, such as the front half track, the rear half track, the wheel track, the vehicle mass, the yaw moment of inertia, and the front and rear wheel cornering stiffness, is as follows:

[0061]

[0062] Wherein, a represents the front half track; b represents the rear half track; t represents the wheel track; m represents the vehicle mass; I z represents the yaw moment of inertia; δ represents the front wheel steering angle; represents the rate of change of the vehicle yaw angular velocity; represents the rate of change of the vehicle mass center cornering angle; Indicates the rate of change of the vehicle's longitudinal velocity (i.e., the vehicle's longitudinal acceleration); F xfl ,F xfr ,F xrl ,F xrr Respectively represent the longitudinal forces of the vehicle's left front, right front, left rear, and right rear wheels; F yfl ,F yfr ,F yrl ,F yrr Respectively represent the lateral forces of the left front, right front, left rear and right rear wheels of the vehicle. The meaning of each variable is as follows: Figure 2 shown.

[0063] Furthermore, if the front wheel steering angle δ is small (e.g., δ is 5 degrees), we can approximate sinδ = δ, cosδ = 1. In this case, the above vehicle dynamics model can be converted into the following formula:

[0064]

[0065] Among them, a represents the front half wheelbase; b represents the rear half wheelbase; t represents the wheelbase; m represents the vehicle mass; I z represents the yaw moment of inertia; Indicates the rate of change of the vehicle's yaw rate; Indicates the rate of change of the vehicle's center of mass sideslip angle; Indicates the rate of change of the vehicle's longitudinal velocity (i.e. longitudinal acceleration); F yf Indicates the total lateral force on the front axle of the vehicle, that is, F yf =F yfl +F yfr ; F yr Indicates the total lateral force on the rear axle of the vehicle, that is, F yr =F yrl +F yrr ; F xl Indicates the total longitudinal force on the left side of the vehicle, that is, F xl =F xfl +F xrl ; F xr Indicates the total longitudinal force on the right side of the vehicle, that is, F xr =F xfr +F xrr .

[0066] According to the existing lateral force definition

[0067]

[0068]

[0069] Where γ represents the vehicle's yaw rate; β represents the vehicle's sideslip angle; v x Indicates the vehicle's longitudinal speed.

[0070] The above vehicle dynamics model formula can be converted into the following nonlinear model form:

[0071]

[0072] Where x represents the state vector value of the vehicle, which can be x=[γ β v x ] T ; u represents the output control quantity of the corresponding actuator of the vehicle, and its value can be u=[δ F xl F xr ] T .

[0073] S102: Acquire real-time operating parameters of the target vehicle, and use the real-time operating parameters of the target vehicle to linearize the vehicle dynamics model to obtain a linearized vehicle dynamics model.

[0074] In this embodiment, in order to achieve coordinated control of the steering of the target vehicle and improve the steering control effect of the target vehicle and the driving experience of the driver, after constructing the vehicle dynamics model using the vehicle physical parameters of the target vehicle in step S101, the real-time operating parameters of the target vehicle can be further obtained, and the real-time operating parameters can be used to linearize the vehicle dynamics model to obtain the linearized vehicle dynamics model for executing the subsequent step S103.

[0075] Among them, the real-time operating parameters of the target vehicle (using x * The yaw rate of the target vehicle in the current operating state (using γ * Indicated), center of mass side slip angle (using β * ) and longitudinal speed (using Indicates), such as x * It can be expressed as:

[0076] Specifically, after obtaining the real-time operating parameters x of the target vehicle * After that, the current longitudinal speed of the target vehicle can be used Current yaw rate γ * , the current vehicle center of mass sideslip angle β * , calculate the front wheel turning angle δ that satisfies the following formula * :

[0077]

[0078] The meaning of each letter is as described above and will not be repeated here.

[0079] Furthermore, at the current working point (i.e. the real-time operating parameter of the target vehicle is x * , the front wheel turning angle is δ * ), the vehicle dynamics model is linearized to obtain the linearized vehicle dynamics model. The specific processing formula is as follows:

[0080]

[0081] in, Represents the rate of change of the vehicle's real-time state vector value (i.e., real-time operating parameters); the values ​​of matrix A and matrix B are as follows:

[0082]

[0083]

[0084] The meaning of each letter is as described above and will not be repeated here.

[0085] S103: performing discretization processing on the linearized vehicle dynamics model to obtain a discretized vehicle dynamics model; and performing differentiation processing on the discretized vehicle dynamics model to obtain a differentiated vehicle dynamics model.

[0086] In this embodiment, after obtaining the linearized vehicle dynamics model in step S102, since the model is a continuous system model, in order to meet the actual application of the vehicle controller, the linearized vehicle dynamics model can be further discretized to obtain a discretized vehicle dynamics model, and the discretized vehicle dynamics model can be differentiated to obtain a differentiated vehicle dynamics model for executing the subsequent step S104.

[0087] Specifically, the linearized vehicle dynamics model is discretized, and the calculation formula of the discretized vehicle dynamics model is as follows:

[0088] x k+1 =A d x k +B d u k

[0089] Among them, A d and B d u k is calculated as follows:

[0090]

[0091]

[0092] Where I represents the unit matrix, and its dimension is the same as that of the matrix A; k represents the kth moment; ΔT represents the discrete sampling time, and its specific value is not limited and can be set according to actual conditions and experience, for example, 5 milliseconds.

[0093] Furthermore, in order to achieve coordinated control of the target vehicle steering in the subsequent steps, the output control amount of each vehicle actuator (such as δ, F xl 、F xr For example, if the value of δ is limited to change from 5 degrees to 6 degrees, and then gradually changed to 7 degrees, 8 degrees, 9 degrees, and 10 degrees, instead of directly changing from 5 degrees to 10 degrees, the discretized vehicle dynamics model can be differentiated to obtain the differentiated vehicle dynamics model as shown below:

[0094] x′ k+1 =A′x′ k +B′Δu k

[0095] The calculation method for each letter is as follows:

[0096]

[0097]

[0098]

[0099] Δu k =u k -u k-1

[0100] The meaning of each letter is as described above and will not be repeated here.

[0101] S104: Calculate the real-time state target value of the target vehicle's steering according to the driving intention of the target driver on the target vehicle, and calculate the steady-state feedforward control amount of the target vehicle using the real-time state target value of the target vehicle's steering and the linearized vehicle dynamics model.

[0102] In this embodiment, in order to achieve coordinated control of the steering of the target vehicle and improve the steering control effect of the target vehicle and the driving experience of the driver, it is also necessary to obtain the driving intention of the target driver on the target vehicle. For example, the driving intention can be determined by obtaining the angle at which the target driver rotates the steering wheel or the value of the accelerator pedal, and the real-time state target value of the target vehicle steering is calculated based on the driving intention. The real-time state target value of the target vehicle steering and the linearized vehicle dynamics model obtained through step S102 are used to calculate the steady-state feedforward control amount of the target vehicle to execute the subsequent step S105.

[0103] The real-time state target value of the target vehicle steering may include but is not limited to the target value of the vehicle yaw rate under the current running state of the target vehicle (using γ r Indicated), longitudinal vehicle speed target value (using ), and the target value of the vehicle's center of mass side slip angle (using β r (indicates) can be set to 0, that is, β r Always equal to 0.

[0104] Specifically, an optional implementation method is to obtain the real-time state target value of the target vehicle steering, and then calculate the vehicle center of mass side slip angle target value β r Set it to be equal to 0, and use the target value of the vehicle yaw rate γ under the current operating state of the target vehicle r , Longitudinal vehicle speed target value As the control target, based on the linearized vehicle dynamics model, the steady-state feedforward control quantity of the target vehicle is calculated (using u ff The specific calculation formula is as follows:

[0105] Ar+Bu ff =0

[0106] in, And the target value of the vehicle's center of mass side slip angle β r Set it to be always equal to 0; the meanings of other letters are still as described above and will not be repeated here.

[0107] S105: Calculating the feedback control amount of the target vehicle based on the linear quadratic regulator LQR using the real-time state target value of the target vehicle's steering and the differentiated vehicle dynamics model.

[0108] In this embodiment, in order to achieve coordinated control of the target vehicle's steering and improve the steering control effect of the target vehicle and the driver's driving experience, the vehicle yaw rate target value γ is obtained in step S104. r , Longitudinal vehicle speed target value After obtaining the real-time state target value of the target vehicle steering, the real-time state target value of the target vehicle steering and the vehicle dynamics model after differentiation obtained in step S103 can be further used to calculate the feedback control amount of the target vehicle based on LQR to execute the subsequent step S106.

[0109] Specifically, an optional implementation method is to obtain the real-time state target value of the target vehicle steering, and then use the vehicle yaw angular velocity target value γ contained therein to calculate the target value of the vehicle yaw angular velocity γ. r , Longitudinal vehicle speed target value As the control target, and set the vehicle center of mass side slip angle target value β rAfter being equal to 0, the LQR is used to calculate the feedback control amount of the front wheel steering angle and the left and right wheel tire forces of the target vehicle based on the vehicle dynamics model after differentiation.

[0110] In this implementation, the penalty matrix can be set as follows:

[0111]

[0112]

[0113] The values ​​of each matrix are as follows:

[0114]

[0115]

[0116] Among them, the diagonal elements q1, q2, q3 in Q are numbers greater than or equal to zero. The specific values ​​are not limited. For example, the values ​​can be 800, 800, and 50, which represent the controlled state variables γ, β, and v respectively. x The importance of the vehicle's yaw rate, center of mass sideslip angle, and longitudinal speed. The larger the value, the less tolerant the error of the corresponding state variable. The diagonal elements r1, r2, and r3 in R are also numbers greater than or equal to zero. The specific values ​​are not limited. For example, the values ​​can be 0.01, 0, and 0, respectively, indicating the importance of the control input variables δ and F. xl ,F xr The penalty degree of the absolute value of the vehicle's front wheel angle, the total longitudinal force on the left side of the vehicle, and the total longitudinal force on the right side of the vehicle. The larger the value, the smaller the corresponding control input variable value is expected to be. The diagonal elements r1′, r2′, and r3′ in R′ are also numbers greater than or equal to zero. The specific values ​​are not limited. For example, the values ​​can be 100, 0.1, and 0.1, which represent the changes in the control input variables (i.e., the changes in the vehicle's front wheel angle, the total longitudinal force on the left side of the vehicle, and the total longitudinal force on the right side of the vehicle) Δδ, ΔF, respectively. xl ,ΔF xr The larger the value, the smaller the change in the corresponding control input variable.

[0117] Thus, after solving the following Ricardi equation, we can obtain the matrix P:

[0118] A′ T P′+P′A′-P′B′R ′-1 B ′T P′+Q′=0

[0119] The feedback gain matrix K can be calculated as follows:

[0120] K=R′ -1 B′T P′

[0121] According to the calculation of the real-time state target value γ r , and β r is equal to 0, and the vehicle real-time state feedback amount The optimal feedback control increment can be calculated as follows:

[0122]

[0123] wherein, represents the feedback control variable value at the k-1 time, and can be defined as The calculation formula of the total feedback control amount (indicated by u ) at the k time is as follows:

[0124]

[0125] S106: The accumulated sum of the steady-state feedforward control amount and the feedback control amount is taken as the output control amount of the corresponding actuator of the target vehicle, and the steering of the target vehicle is cooperatively controlled by using the output control amount to realize the driving intention of the target driver.

[0126] In the embodiment, the steady-state feedforward control amount u ff of the target vehicle is calculated by step S104, and the feedback control amount u of the target vehicle at the k time is calculated by step S105, and then the two can be further accumulated to obtain the accumulated sum at the k time as follows:

[0127]

[0128] It can be understood that, wherein, u k can be taken as the output control amount of the corresponding actuator of the target vehicle, such as the vehicle front wheel steering angle at the k time (i.e. δ k ), the total longitudinal force on the left side of the vehicle (i.e. F xl,k ), and the total longitudinal force on the right side of the vehicle (i.e. F xr,k ), i.e. u k =[δ k F xl,k F xr,k ] T .

[0129] Further, the steering of the target vehicle can be cooperatively controlled by using these output control amounts of the corresponding actuators of the vehicle to realize the driving intention of the target driver, and the target vehicle is controlled to reach the real-time state target value of the steering, i.e. the target value γ r, the longitudinal speed reaches the target value wait.

[0130] It should be noted that in order to verify the accuracy of the above-mentioned coordinated control method for vehicle steering, the application also built the operating environment of the control method proposed in this application based on the MATLAB / Simulink platform, and carried out closed-loop simulation verification based on the controlled target vehicle model provided by CarSim. The simulation results are as follows: Figure 3 As shown. Figure 3 It can be seen that the controlled target vehicle can track the target set values ​​of yaw rate and longitudinal speed very well, and when more emphasis is placed on tracking yaw rate, the tracking requirement for longitudinal speed is relatively low; the smaller the vehicle's center of mass slip angle is, the better, but due to the constraints of physical variables between the center of mass slip angle and the vehicle's yaw angle and the vehicle's rear wheel center of mass slip angle, it is basically impossible to achieve complete control of zero, but its value can be within a smaller range, such as Figure 3 The result shows that the error is kept within a very small range (±0.01rad), which can also meet the preset actual control requirements and improve the driving experience.

[0131] Thus, by executing steps S101-106 above, relying on the vehicle motion domain computing platform and utilizing distributed systems such as brake-by-wire, steer-by-wire, drive-by-wire, and in-wheel motors, coordinated optimal control of the target vehicle during steering can be achieved, thereby improving the steering control effect of the target vehicle. Furthermore, through the coordinated control strategy, both the driver's lateral intention (target vehicle yaw rate) and longitudinal intention (target vehicle longitudinal velocity) can be tracked simultaneously, thereby enhancing the driver's driving experience.

[0132] In summary, the present embodiment provides a coordinated control method for vehicle steering, which first obtains vehicle physical parameters of a target vehicle to be controlled and constructs a vehicle dynamics model using the vehicle physical parameters of the target vehicle. Then, the real-time operating parameters of the target vehicle are obtained and the vehicle dynamics model is linearized using the real-time operating parameters of the target vehicle to obtain a linearized vehicle dynamics model. The linearized vehicle dynamics model is then discretized to obtain a discretized vehicle dynamics model. The discretized vehicle dynamics model is differentiated to obtain a differentiated vehicle dynamics model. The real-time state target value of the target vehicle's steering is calculated based on the driving intention of the target driver on the target vehicle, and the steady-state feedforward control quantity of the target vehicle is calculated using the real-time state target value of the target vehicle's steering and the linearized vehicle dynamics model. The real-time state target value of the target vehicle's steering and the differentiated vehicle dynamics model are used to calculate the feedback control quantity of the target vehicle based on the linear quadratic regulator LQR. Finally, the cumulative sum of the steady-state feedforward control quantity and the feedback control quantity is used as the output control quantity of the corresponding actuator of the target vehicle, and the output control quantity is used to coordinate the steering of the target vehicle to realize the driving intention of the target driver.

[0133] This achieves coordinated control of the target vehicle's steering, which not only ensures that the target driver's driving intention is followed, but also minimizes the target driver's subjective perception of the active intervention of the control function, thereby improving the target vehicle's steering control effect and the target driver's driving experience.

[0134] See also Figure 4 As shown, the present application also provides an embodiment of a coordinated control device for vehicle steering, which may include:

[0135] A construction unit 401 is configured to obtain vehicle physical parameters of a target vehicle to be controlled, and to construct a vehicle dynamics model using the vehicle physical parameters of the target vehicle;

[0136] a linearization unit 402 for acquiring real-time operating parameters of the target vehicle and performing linearization processing on the vehicle dynamics model using the real-time operating parameters of the target vehicle to obtain a linearized vehicle dynamics model;

[0137] a discretization unit 403 configured to discretize the linearized vehicle dynamics model to obtain a discretized vehicle dynamics model; and perform a differentiation process on the discretized vehicle dynamics model to obtain a differentiated vehicle dynamics model;

[0138] The first calculation unit 404 is configured to calculate a real-time state target value of the target vehicle steering according to a driving intention of a target driver on the target vehicle, and calculate a steady-state feedforward control amount of the target vehicle by using the real-time state target value of the target vehicle steering and the linearized vehicle dynamics model.

[0139] The second calculation unit 405 is configured to calculate a feedback control amount of the target vehicle based on a linear quadratic regulator (LQR) by using the real-time state target value of the target vehicle steering and the differentiated vehicle dynamics model.

[0140] The control unit is configured to take a sum of the steady-state feedforward control amount and the feedback control amount as an output control amount of an actuator corresponding to the target vehicle, and perform cooperative control on the steering of the target vehicle by using the output control amount, so as to realize the driving intention of the target driver.

[0141] In some possible implementation manners of the present application, the vehicle physical parameters of the target vehicle include a front half track, a rear half track, a wheel track, a total vehicle mass, a yaw moment of inertia, and front and rear wheel cornering stiffness of the target vehicle.

[0142] In some possible implementation manners of the present application, the construction unit 401 is specifically configured to:

[0143] The construction unit 401 is configured to construct the vehicle dynamics model by using the front half track, the rear half track, the wheel track, the total vehicle mass, the yaw moment of inertia, and the front and rear wheel cornering stiffness of the target vehicle, without considering a force arm change of a longitudinal force caused by a front wheel steering angle.

[0144] In some possible implementation manners of the present application, the real-time running parameters of the target vehicle include a vehicle yaw rate, a center of mass side slip angle, and a longitudinal speed of the target vehicle in a current running state; and the linearization unit 402 is specifically configured to:

[0145] The linearization unit 402 is configured to linearize the vehicle dynamics model by using the vehicle yaw rate, the center of mass side slip angle, and the longitudinal speed of the target vehicle in the current running state, to obtain the linearized vehicle dynamics model.

[0146] In some possible implementation manners of the present application, the real-time state target value of the target vehicle steering includes a vehicle yaw rate target value and a longitudinal vehicle speed target value of the target vehicle in the current running state.

[0147] In some possible implementation manners of the present application, the second calculation unit 405 is specifically configured to:

[0148] The vehicle yaw rate target value and longitudinal speed target value under the current operating state of the target vehicle are used as control targets. Based on the vehicle dynamics model after differentiation, LQR is used to calculate the feedback control amount of the front wheel turning angle and the left and right wheel tire forces of the target vehicle.

[0149] In some possible implementations of the present application, the first calculating unit 404 is specifically configured to:

[0150] The center of mass sideslip angle of the target vehicle is set to zero, and the vehicle yaw rate target value and longitudinal speed target value of the target vehicle in the current operating state are used as control targets. Based on the linearized vehicle dynamics model, the steady-state feedforward control amount of the target vehicle is calculated.

[0151] It can be seen from the above embodiments that the collaborative control device for vehicle steering provided in the embodiments of the present application first obtains the vehicle physical parameters of the target vehicle to be controlled, and uses the vehicle physical parameters of the target vehicle to construct a vehicle dynamics model, then obtains the real-time operating parameters of the target vehicle, and uses the real-time operating parameters of the target vehicle to linearize the vehicle dynamics model to obtain a linearized vehicle dynamics model; then discretizes the linearized vehicle dynamics model to obtain a discretized vehicle dynamics model; and differentiates the discretized vehicle dynamics model to obtain a differentiated vehicle dynamics model; and then calculates the real-time state target value of the target vehicle steering according to the driving intention of the target driver on the target vehicle, and uses the real-time state target value of the target vehicle steering and the linearized vehicle dynamics model to calculate the steady-state feedforward control quantity of the target vehicle. The real-time state target value of the target vehicle's steering and the differentiated vehicle dynamics model are used to calculate the feedback control quantity of the target vehicle based on the linear quadratic regulator LQR. Finally, the cumulative sum of the steady-state feedforward control quantity and the feedback control quantity is used as the output control quantity of the corresponding actuator of the target vehicle, and the output control quantity is used to coordinate the steering of the target vehicle to realize the driving intention of the target driver.

[0152] This achieves coordinated control of the target vehicle's steering, which not only ensures that the target driver's driving intention is followed, but also minimizes the target driver's subjective perception of the active intervention of the control function, thereby improving the target vehicle's steering control effect and the target driver's driving experience.

[0153] Furthermore, an embodiment of the present application also provides a coordinated control device for vehicle steering, comprising: a processor, a memory, and a system bus;

[0154] The processor and the memory are connected via the system bus;

[0155] The memory is used to store one or more programs, and the one or more programs include instructions. When the instructions are executed by the processor, the processor executes any one of the implementation methods of the above-mentioned coordinated control method for vehicle steering.

[0156] Furthermore, an embodiment of the present application also provides a computer-readable storage medium, which stores instructions. When the instructions are executed on a terminal device, the terminal device executes any implementation method of the above-mentioned vehicle steering collaborative control method.

[0157] Through the description of the above embodiments, it can be seen that those skilled in the art can clearly understand that all or part of the steps in the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a storage medium such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network communication device such as a media gateway, etc.) to execute the methods described in each embodiment of the present application or certain parts of the embodiments.

[0158] It should be noted that the various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the description of the methods.

[0159] It should also be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or device comprising the element.

[0160] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present application. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application is not limited to the embodiments shown herein, but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A coordinated control method for vehicle steering, characterized in that: include: Acquiring vehicle physical parameters of a target vehicle to be controlled, and constructing a vehicle dynamics model using the vehicle physical parameters of the target vehicle; Acquiring real-time operating parameters of the target vehicle, and using the real-time operating parameters of the target vehicle to linearize the vehicle dynamics model to obtain a linearized vehicle dynamics model; performing discretization processing on the linearized vehicle dynamics model to obtain a discretized vehicle dynamics model; and performing differentiation processing on the discretized vehicle dynamics model to obtain a differentiated vehicle dynamics model; Calculating a real-time state target value of the target vehicle's steering according to a target driver's driving intention on the target vehicle, and calculating a steady-state feedforward control amount of the target vehicle using the real-time state target value of the target vehicle's steering and the linearized vehicle dynamics model; Calculating a feedback control variable of the target vehicle based on a linear quadratic regulator (LQR) using the real-time state target value of the target vehicle's steering and the differentiated vehicle dynamics model; The cumulative sum of the steady-state feedforward control amount and the feedback control amount is used as the output control amount of the actuator corresponding to the target vehicle, and the output control amount is used to coordinately control the steering of the target vehicle to achieve the driving intention of the target driver.

2. The method according to claim 1, characterized in that The vehicle physical parameters of the target vehicle include the front half wheelbase, rear half wheelbase, wheelbase, vehicle mass, yaw moment of inertia and front and rear wheel cornering stiffness of the target vehicle.

3. The method according to claim 2, characterized in that The constructing of a vehicle dynamics model using the vehicle physical parameters of the target vehicle includes: Ignoring the change in the moment arm of the longitudinal force caused by the front wheel turning angle, a vehicle dynamics model is constructed using the front half wheelbase, rear half wheelbase, track width, vehicle mass, yaw moment of inertia, and front and rear wheel cornering stiffness of the target vehicle.

4. The method according to claim 1, wherein The real-time operating parameters of the target vehicle include the vehicle yaw rate, center of mass sideslip angle, and longitudinal velocity of the target vehicle in a current operating state; and the vehicle dynamics model is linearized using the real-time operating parameters of the target vehicle to obtain a linearized vehicle dynamics model, including: The vehicle dynamics model is linearized using the vehicle yaw rate, center of mass sideslip angle, and longitudinal speed of the target vehicle in a current operating state to obtain a linearized vehicle dynamics model.

5. The method according to claim 1, wherein The real-time state target value of the target vehicle steering includes a vehicle yaw rate target value and a longitudinal vehicle speed target value under the current running state of the target vehicle.

6. The method according to claim 5, characterized in that The method of calculating the feedback control amount of the target vehicle based on a linear quadratic regulator (LQR) using the real-time state target value of the target vehicle's steering and the vehicle dynamics model after differentiation includes: The vehicle yaw rate target value and longitudinal speed target value under the current operating state of the target vehicle are used as control targets. Based on the vehicle dynamics model after differentiation, LQR is used to calculate the feedback control amount of the front wheel turning angle and the left and right wheel tire forces of the target vehicle.

7. The method according to claim 5, characterized in that The method of calculating the steady-state feedforward control amount of the target vehicle by using the real-time state target value of the target vehicle steering and the linearized vehicle dynamics model includes: The center of mass sideslip angle of the target vehicle is set to zero, and the vehicle yaw rate target value and longitudinal speed target value of the target vehicle in the current operating state are used as control targets. Based on the linearized vehicle dynamics model, the steady-state feedforward control amount of the target vehicle is calculated.

8. A coordinated control device for vehicle steering, characterized in that: include: A construction unit, configured to obtain vehicle physical parameters of a target vehicle to be controlled, and construct a vehicle dynamics model using the vehicle physical parameters of the target vehicle; a linearization unit, configured to obtain real-time operating parameters of the target vehicle and linearize the vehicle dynamics model using the real-time operating parameters of the target vehicle to obtain a linearized vehicle dynamics model; a discretization unit, configured to discretize the linearized vehicle dynamics model to obtain a discretized vehicle dynamics model; and perform a differentiation process on the discretized vehicle dynamics model to obtain a differentiated vehicle dynamics model; a first calculation unit, configured to calculate a real-time state target value of the target vehicle's steering according to a driving intention of a target driver on the target vehicle, and calculate a steady-state feedforward control amount of the target vehicle using the real-time state target value of the target vehicle's steering and the linearized vehicle dynamics model; a second calculation unit, configured to calculate a feedback control variable of the target vehicle based on a linear quadratic regulator (LQR) by using the real-time state target value of the target vehicle's steering and the vehicle dynamics model after differentiation; A control unit is used to use the cumulative sum of the steady-state feedforward control amount and the feedback control amount as the output control amount of the actuator corresponding to the target vehicle, and use the output control amount to coordinately control the steering of the target vehicle to achieve the driving intention of the target driver.

9. A coordinated control device for vehicle steering, characterized in that: include: Processor, memory, system bus; The processor and the memory are connected via the system bus; The memory is configured to store one or more programs, wherein the one or more programs include instructions, and when the instructions are executed by the processor, the processor is enabled to perform the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions, and when the instructions are executed on a terminal device, the terminal device executes the method according to any one of claims 1 to 7.

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