Vehicle lateral control method and device, vehicle and medium

Abstract

The application discloses a vehicle lateral control method and device, a vehicle and a medium. The method comprises the following steps: acquiring a general vehicle model constructed in advance; acquiring configuration parameters of a target vehicle, inputting the configuration parameters into the general vehicle model to obtain a target vehicle model corresponding to the target vehicle; constructing a linear matrix inequality according to the target vehicle model and a preset robustness expectation index, and solving the linear matrix inequality to obtain an LPV controller corresponding to the target vehicle; acquiring driving parameters of the target vehicle and inputting the driving parameters into the LPV controller to output a front wheel steering angle of the target vehicle, and converting the front wheel steering angle into a steering wheel steering angle of the target vehicle to perform lateral control on the target vehicle. The application can improve the lateral control performance of the vehicle under different road conditions and improve the stability of the lateral control of the vehicle by designing the LPV controller to perform lateral control on the target vehicle.

Description

TECHNICAL FIELD

[0001] The embodiment of the present application relates to the technical field of automatic driving, in particular to a vehicle lateral control method and device, vehicle and medium. BACKGROUND

[0002] In the modern vehicle control system, lateral control is a crucial link, which is directly related to the stability and safety of vehicle driving. The traditional PID (Proportion-Integral-Derivative) controller is widely used in the industry due to its simple structure, easy understanding and implementation. However, with the diversification of vehicle operating environment, especially the increasing demand for operating in highway scenarios and bad weather conditions such as rainy days, the challenges faced by the traditional PID controller are increasingly prominent. First of all, since the traditional PID controller relies on fixed parameter settings, when the vehicle driving environment changes, such as changes in vehicle speed, road conditions and weather conditions, the original parameters may not be able to adapt to the new working conditions, resulting in a decline in control performance. For example, on a wet and slippery road, the friction between the tire and the ground decreases, and the lateral response of the vehicle will slow down. At this time, if the parameters of the PID controller are not adjusted accordingly, oversteering or understeering may occur, commonly known as "drawing a dragon" phenomenon, which affects the stability and safety of vehicle driving. In order to solve this problem, the industry usually manually adjusts the PID parameters according to different operating scenarios, that is, adopts a variable parameter PID control strategy. Although this method can improve the control effect to some extent, the parameter adjustment process often requires a lot of time and effort. More importantly, the selection and adjustment of the variable parameter PID control strategy are mostly based on the experience of engineers and field trial and error, lacking mathematical stability guarantee, so it is difficult to guarantee the optimality or stability of the obtained parameters. In addition, due to the complexity of the vehicle system, different parameters may interact with each other, and simply relying on experience to adjust a single parameter may ignore the overall performance of the system. It can be seen that although the variable parameter PID alleviates the control problem of the traditional PID controller in complex scenarios to some extent, its inherent defects cannot be ignored. Therefore, finding a more advanced and stable vehicle lateral control method has become a problem to be solved in the current vehicle control field. SUMMARY

[0003] The embodiment of the present application provides a vehicle lateral control method, device, vehicle and medium, which aims to solve the problem of poor stability of the existing vehicle lateral control.

[0004] In a first aspect, the embodiment of the present application provides a vehicle lateral control method, which comprises:

[0005] acquiring a pre-constructed general vehicle model;

[0006] obtain a configuration parameter of the target vehicle, input the configuration parameter into the general vehicle model to obtain a target vehicle model corresponding to the target vehicle;

[0007] construct a linear matrix inequality according to the target vehicle model and a preset robustness expectation index, and solve the linear matrix inequality to obtain an LPV controller corresponding to the target vehicle;

[0008] obtain a driving parameter of the target vehicle, input the driving parameter into the LPV controller to output a front wheel steering angle of the target vehicle, and convert the front wheel steering angle into a steering wheel steering angle of the target vehicle to perform lateral control on the target vehicle.

[0009] In a second aspect, an embodiment of the present application further provides a vehicle lateral control device, which comprises a unit for executing the method.

[0010] In a third aspect, an embodiment of the present application further provides a vehicle, which comprises a memory and a processor, the memory stores a computer program, and the processor executes the computer program to implement the method.

[0011] In a fourth aspect, an embodiment of the present application further provides a computer readable storage medium, which stores a computer program, and the computer program is executable by a processor to implement the method.

[0012] The embodiment of the present application provides a vehicle lateral control method, device, vehicle and medium. The method comprises the following steps: obtaining a general vehicle model constructed in advance; obtaining a configuration parameter of a target vehicle, inputting the configuration parameter into the general vehicle model to obtain a target vehicle model corresponding to the target vehicle; constructing a linear matrix inequality according to the target vehicle model and a preset robustness expectation index, and solving the linear matrix inequality to obtain an LPV controller corresponding to the target vehicle; obtaining a driving parameter of the target vehicle, inputting the driving parameter into the LPV controller to output a front wheel steering angle of the target vehicle, and converting the front wheel steering angle into a steering wheel steering angle of the target vehicle to perform lateral control on the target vehicle. The LPV controller is established according to the target vehicle model of the target vehicle, and the LPV controller is used to perform lateral control on the target vehicle, so that the lateral control performance of the vehicle under different road conditions can be improved, and the stability of the vehicle lateral control can be improved. BRIEF DESCRIPTION OF DRAWINGS

[0013] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments description. Obviously, the drawings described in the following embodiments are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative effort based on these drawings.

[0014] Figure 1 A schematic diagram of a vehicle lateral control method provided by an embodiment of the present application is shown in FIG. 1.

[0015] Figure 2 A schematic diagram of a sub-step flow of a vehicle lateral control method provided by an embodiment of the present application is shown in FIG. 2.

[0016] Figure 3 A schematic diagram of a lateral mechanics analysis of a vehicle lateral control method provided by an embodiment of the present application is shown in FIG. 3.

[0017] Figure 4 A flowchart of a vehicle lateral control method provided by another embodiment of the present application is shown in FIG. 4.

[0018] Figure 5 A flowchart of a vehicle lateral control method provided by still another embodiment of the present application is shown in FIG. 5.

[0019] Figure 6 A schematic block diagram of a vehicle lateral control device provided by an embodiment of the present application is shown in FIG. 6.

[0020] Figure 7 A schematic block diagram of a vehicle provided by an embodiment of the present application is shown in FIG. 7. DETAILED DESCRIPTION

[0021] 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, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort belong to the scope of protection of the present application.

[0022] It should be understood that, when used in the specification and the appended claims, the terms "comprise" and "include" indicate the presence of the described features, integers, steps, operations, elements, and / or components, but do not exclude one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0023] It should also be understood that the terms used herein are for the purpose of describing particular embodiments and are not intended to limit the application. As used in this specification and the appended claims, the singular forms "a," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0024] It should also be further understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items, as well as to the lack of combinations when interpreted in the alternative ("or").

[0025] As used in this specification and the appended claims, the term "if" can be construed to mean "when" or "once" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [a described condition or event] is detected" can be construed to mean "once it is determined" or "in response to determining" or "once [the described condition or event] is detected" or "in response to detecting [the described condition or event]," depending on the context.

[0026] Reference is made to Figure 1 , Figure 1 A flow chart of a vehicle lateral control method according to an embodiment of the application is provided. The vehicle lateral control method will be described in detail below. As shown in Figure 1 The method comprises the following steps: S110-S140.

[0027] S110, obtaining a pre-constructed general vehicle model.

[0028] In the embodiment, the general vehicle model refers to a general vehicle dynamics model, which is a mathematical model describing the motion characteristics of a vehicle. It is constructed based on physical principles (mainly Newton's laws of motion and the law of conservation of energy) to analyze and predict the dynamic response of a vehicle under different driving conditions. Such a model takes into account the interaction forces between the vehicle and the road surface, including driving force, braking force, lateral force (grip force), gravity, centrifugal force, etc., while also taking into account the dynamic characteristics of the vehicle itself, such as mass, moment of inertia, suspension system characteristics, tire model, and the influence of the vehicle control system, etc. According to the complexity, the vehicle dynamics model can be divided into different levels, from a simple two-degree-of-freedom model (only considering lateral motion and yaw motion) to a complex multi-degree-of-freedom model (including longitudinal, lateral, vertical, and rotational motion around three orthogonal axes), which is not limited in the embodiment. After the general vehicle model is pre-constructed, when a new vehicle is tested, the general vehicle model can be directly obtained and combined with the data of the new vehicle to construct a vehicle model belonging to the new vehicle.

[0029] In an embodiment, as Figure 2As shown, the construction step of the general vehicle model comprises: S111-S112.

[0030] S111, constructing a lateral dynamics model of the vehicle based on configuration parameters of the vehicle and driving parameters, the configuration parameters comprising: mass, front wheel track, rear wheel track and moment of inertia of the vehicle, the driving parameters comprising: longitudinal speed, slip angle, yaw rate, external disturbance and front wheel steering angle of the vehicle.

[0031] In this embodiment, the construction of the general vehicle model is divided into two steps, the first step is to construct a lateral dynamics model of the vehicle, and the second step is to construct a state space of the vehicle. For the first step, as shown in FIG. 1, the lateral dynamics model of the vehicle is constructed based on the configuration parameters of the vehicle and the driving parameters. Figure 3As shown, based on the understanding of the above vehicle dynamics model, the vehicle lateral dynamics model of the embodiment is a mathematical model for describing the motion characteristics of the vehicle in the lateral direction, which is mainly used to analyze the change law of the vehicle's attitude, lateral acceleration, yaw angular velocity and tire-road lateral force and other parameters under the conditions of turning, obstacle avoidance, crosswind interference, etc. In the vehicle's lateral dynamics model, the key equations usually include the vehicle's mass center motion equation, yaw motion equation and tire force generation equation. Through these equations, the steady-state and transient response of the vehicle when affected by steering input, lateral wind force, road inclination and other factors can be analyzed, and the corresponding control algorithm can be designed to improve the vehicle's handling stability, path tracking performance and safety. Among them, the vehicle mass center motion equation describes how the mass center position of the vehicle changes over time when it is moving laterally. In simple terms, when a car turns, the vehicle as a whole does not travel in a straight line, but deviates to the left or right from the straight path. This equation is used to study the dynamics of the vehicle moving left and right in the horizontal plane, which focuses on the relationship between lateral force (such as tire-road friction during turning) and vehicle mass center lateral acceleration, which is embodied in formula (1) in this embodiment. The yaw motion equation describes the rotational motion of the vehicle around its vertical axis (i.e. the front-to-back direction of the vehicle), which is commonly known as vehicle "yaw". When driving a car turns, the vehicle body will tilt to a certain extent. The more the steering wheel is turned, the greater the body tilt angle will be. The yaw motion equation is used to analyze how the yaw angle (yaw angle) and yaw angular velocity change with the vehicle's driving state and control input (such as steering wheel angle), which is embodied in formula (2) in this embodiment. The tire force generation equation is used to calculate the force generated by the interaction between the tire and the road, and to explore the force generated when the tire contacts the road, especially the lateral force, which is the key to the vehicle's smooth turning and stable driving. The tire force generation equation reflects how the lateral grip force of the tire changes at different slip angles (the angle between the tire and the forward direction). When the vehicle turns, the tire must generate enough lateral force to overcome the centrifugal force so that the vehicle can travel along the intended trajectory, which is embodied in formulas (3) and (4) in this embodiment. More specifically, the lateral dynamics model of the embodiment is:

[0032]

[0033]

[0034] where m is the mass, V x is the longitudinal velocity, β is the slip angle, γ is the yaw rate, F yf is the lateral force of the front wheel, F yr is the lateral force of the rear wheel, I z is the moment of inertia, l f is the front wheel track, lr is the rear wheel track, M z is the external disturbance; the F yf and the F yf is expressed as:

[0035] F yf = C yf α f (3)

[0036] F yr = C yr α r (4)

[0037] wherein C yf is the front wheel cornering stiffness, C yr is the rear wheel cornering stiffness, C yf and C yr are constants, α f is the front wheel slip angle, α r is the rear wheel slip angle, the α f and α r are expressed as:

[0038]

[0039]

[0040] wherein δ is the front wheel steering angle.

[0041] S112, taking the transpose matrix of the slip angle and the yaw rate as the state variable of the state space, taking the front wheel steering angle as the input variable of the state space, taking the external disturbance as the disturbance of the state space, and constructing the state space of the vehicle according to the lateral dynamic model, the state space being used to express the general vehicle model.

[0042] After the first step of constructing the vehicle lateral dynamics, the second step of constructing the state space of the vehicle is performed. The state space refers to the set of all possible states of a system, each state being unique in the state space and can be represented by a state vector. The main role of the state space is to facilitate system analysis and modeling. The state space representation is a mathematical model that represents a physical system as a set of inputs, outputs, and states, and the relationship between the inputs, outputs, and states can be described by first-order differential equations. This method is particularly suitable for the analysis of multi-input, multi-output systems, and there is no restriction on the coefficients and initial conditions of the system. Therefore, in this embodiment, the state space is used to describe the dynamic behavior of the vehicle, which facilitates the design of the controller. The state space equation established in this embodiment is also the general vehicle model. Specifically, the basic expression of the state space is formula (7), where x is the state variable, u is the input variable, and w is the disturbance or noise, i.e., x = [β γ] T ,u = δ, w = M z , then the state space of the vehicle can be expressed as:

[0043]

[0044]

[0045] where A and B1 and B2 are state space matrices. The above first step and second step complete the construction of the general vehicle model, which provides a basis for the subsequent design of the LPV controller.

[0046] S120, obtaining the configuration parameters of the target vehicle, and inputting the configuration parameters into the general vehicle model to obtain a target vehicle model corresponding to the target vehicle.

[0047] In this embodiment, the configuration parameters of different vehicle models are different. Since the general vehicle model is constructed based on the configuration parameters and driving parameters of the vehicle, different configuration parameters have different vehicle models. Therefore, by inputting the configuration parameters of the target vehicle into the general vehicle model, the target vehicle model of the target vehicle can be obtained, wherein the configuration parameters of the target vehicle are obtained through config. The configuration parameters in this embodiment include: m, I z , l f , l r For example, when a new vehicle is put into production, in order to obtain the vehicle model of the new vehicle, the configuration parameters of the new vehicle are input into the general vehicle model, and the vehicle model of the new vehicle can be obtained.

[0048] S130, constructing a linear matrix inequality according to the target vehicle model and a preset robustness expectation index, and solving the linear matrix inequality to obtain an LPV controller corresponding to the target vehicle.

[0049] In the embodiment, the LPV controller refers to a linear parameter-varying (LPV) controller, the dynamic characteristics of which vary with the change of one or more time-varying parameters, which can be a function of physical parameters, operating conditions or external environment of the system, and the design goal of the LPV controller is to adapt to these changes by adjusting the parameters of the controller, so as to achieve optimal control of the system. In other words, in the LPV controller, the coefficients of the system matrix are no longer constant, but depend on certain measurable time-varying parameters, and the design goal of the LPV controller is to effectively control the behavior of such systems, that is, to ensure that the performance indicators of the system meet the expected requirements even when the system parameters vary within their allowable range. In specific embodiments, the design goal of the LPV controller is to ensure the stability of vehicle lateral control under high-speed driving and wet road surface scenarios.

[0050] The main steps of the design of the LPV controller are first to establish a mathematical model that can describe the relationship between the dynamic characteristics of the system and the change of the parameters, that is, the target vehicle model established in the embodiment; then determine the control target, which in the embodiment is the pre-set robustness expectation index, then construct a linear matrix inequality (LMI) based on the target vehicle model and the robustness expectation index, and finally solve the linear matrix inequality to obtain the LPV controller. The linear matrix inequality can be solved using the LMI toolbox (such as YALMIP in MATLAB with SeDuMi, SDPT3, etc. solver) to solve the LMI, and the solving process will produce a set of gain matrices that meet the requirements of the controller design. The construction process of the linear matrix inequality is as follows:

[0051] First, obtain the solving parameters for solving the linear matrix inequality, including: the range of vehicle speed, the range of vehicle speed change rate, the side stiffness of the front wheel, the side stiffness of the rear wheel, the range of road friction coefficient and the maximum change rate of the road friction coefficient. Among them, the range of vehicle speed, that is, V xmin -V xmax , is obtained through vehicle config; the range of vehicle speed change rate, that is, V , represents the vehicle acceleration and deceleration limit capability, which is also obtained through vehicle config; the side stiffness of the front wheel is C yf , and the side stiffness of the rear wheel is C yr , wherein C yf =f1(μ), C yr= f2(μ), f1 and f2 are obtained by the tire config of the vehicle; the road friction coefficient μ is obtained using an online estimation algorithm, for example, the least square method, the range of the road friction coefficient is set according to the vehicle use scenario; the maximum change rate of the road friction coefficient is set to a small constant value. The solving parameters are all constants, after obtaining the solving parameters, the matrix X and Y need to be found to satisfy the following inequalities (8) and (9):

[0052]

[0053]

[0054] Where G comes from:

[0055]

[0056] And the elements in G are defined as:

[0057]

[0058] Where z and d are robustness indexes, the above solving parameters are embodied in A(μ), finally X and Y satisfying the above inequalities are found, and the LPV controller is constructed as follows:

[0059]

[0060] Where M and N are two matrices satisfying N (i) M (i)T = I - Y (i) X (i) After the linear matrix inequality is constructed, the LPV controller obtained by solving is as follows:

[0061]

[0062] Where A, B, C, D are the matrices of the LPV controller, V x is the current vehicle speed, μ is the road friction coefficient, u is the front wheel steering angle output by the LPV controller, x is the input of the LPV controller, x includes the vehicle lateral state, the vehicle lateral state is expressed as [β γ] T , y is the output of the LPV controller, y is composed of the vehicle lateral state and the front wheel steering angle output by the LPV controller. It should be noted that the construction process of the above LMI is an example, and those skilled in the art can also construct according to the actual needs, which is not limited here.

[0063] S140, obtaining a driving parameter of the target vehicle and inputting the driving parameter into the LPV controller to output a front wheel steering angle of the target vehicle, and converting the front wheel steering angle into a steering wheel steering angle of the target vehicle to perform lateral control on the target vehicle.

[0064] In this embodiment, after obtaining the LPV controller of the target vehicle, the LPV controller is used to perform lateral control on the vehicle. Specifically, first, a driving parameter of the target vehicle is obtained, the driving parameter including a yaw rate, a slip angle, a longitudinal speed and a road friction coefficient of the vehicle. The longitudinal speed of the vehicle can be obtained by fusing the GPS speed and the wheel speed. The yaw rate can be obtained by a gyroscope or an inertial measurement unit (IMU) installed on the vehicle. The slip angle can be calculated by a dynamic model of the vehicle, a tire model and sensor data (such as wheel speed, lateral acceleration, yaw rate, etc.). The road friction coefficient can be obtained by a side slip instrument, by measuring the side slip angle of the vehicle to estimate the road friction coefficient. It can be understood that the driving parameter can also be obtained by other ways, which is not limited herein. After obtaining the driving parameter of the target vehicle, the driving parameter is input into the LPV controller, and the LPV controller outputs a front wheel steering angle of the target vehicle, the front wheel steering angle being a front wheel deflection angle. There is a transmission ratio between the front wheel steering angle and a steering wheel steering angle, the transmission ratio being determined by a steering mechanism of the vehicle. The steering wheel steering angle can be calculated from the front wheel steering angle according to the transmission ratio, so as to control the steering of the front wheel of the vehicle, thereby realizing the lateral control on the target vehicle.

[0065] In an embodiment, the vehicle lateral control method further comprises steps S201-S203. Figure 4

[0066] S201, performing road test on the target vehicle by the LPV controller to obtain a road test result;

[0067] S202, judging whether the road test result meets a road test passing condition;

[0068] S203, if the road test result does not meet the road test passing condition, adjusting the robustness expected index according to the road test result, and returning to the step of performing road test on the target vehicle by the LPV controller to obtain a road test result, until the road test result meets the road test passing condition, and outputting the LPV controller.

[0069] ​In this embodiment, after the LPV controller is constructed, road test is also performed using the LPV controller. The road test can be a test of the vehicle under different roads and different road conditions, or a simulation of different roads and different road conditions. The road test passing condition is usually a series of performance indicators, such as control accuracy, reaction time, decision correctness, etc. The vehicle needs to reach or exceed these indicators in the test to be considered to pass the road test. If the road test does not pass, it means that the control strategy of the LPV controller has not reached the optimal state, and further adjustment of the LPV controller is needed. Analysis of the feedback of the road test results can identify the areas of insufficient robustness. According to the test feedback, it can be determined which indicators need to be improved and set new target values. Specifically, the parameters of the LPV controller can be adjusted according to the adjustment needs of the robustness indicators, such as changing the controller gain, adjusting the weight matrix, redesigning the state feedback matrix, etc. After the adjustment, the LPV model of the system needs to be updated to reflect the new control strategy and parameters. After applying the new parameter settings, the road test is performed again to verify the improvement of robustness. This process may need to be iterated multiple times, and each iteration is based on the feedback of the road test structure. After each iteration, it needs to be verified whether the predetermined robustness indicators are met. If the requirements are met, it can be considered that the road test is passed. If not, further analysis is needed and the next round of adjustment is performed. It should be noted that when adjusting the robustness indicators, the trade-off between stability and performance needs to be considered. Improving robustness may sacrifice certain performance indicators, so the overall performance needs to be considered in the adjustment process.

[0070] In an embodiment, as Figure 5 , the vehicle lateral control method further comprises steps S204-S207.

[0071] S204, make the vehicle run in different working condition scenes, and control the target vehicle through the LPV controller to obtain the gain scheduling strategy of the LPV controller at this time;

[0072] S205, adjust the PID controller according to the gain scheduling strategy, and perform road test on the target vehicle through the adjusted PID controller to obtain road test results;

[0073] S206, judge whether the road test results meet the road test passing condition;

[0074] S207, if the road test results do not meet the road test passing condition, adjust the PID controller according to the road test results until the road test results meet the road test passing condition, and output the PID controller.

[0075] In this embodiment, after the LPV controller is constructed, the parameters of a PID (Proportional, Integral, Derivative) controller can also be tuned by the LPV controller. Specifically, first, the gains of the LPV controller how to change with the system parameters or time need to be analyzed, the main trends and characteristics of these gain changes are determined, specifically, the vehicle is made to travel in different operating condition intervals, the gain scheduling strategy of the LPV controller is extracted, which can include the size of the gain, the range of change, and how they respond to the change of the system parameters. Then the parameters of the PID controller are selected, the PID controller is composed of three parts: proportional (P), integral (I) and derivative (D), each part has its corresponding gain parameters Kp, Ki, Kd, one or more of which are adjusted. Next, according to the change characteristics of the LPV gain, a preliminary mapping strategy is developed. If the LPV gain mainly affects the response speed of the system, then these gains can be mapped to the proportional coefficient Kp of the PID controller, the proportional coefficient directly determines the degree of response of the PID controller to the error, therefore by adjusting Kp, the control effect of the LPV gain on the response speed can be approximately realized. If the change of the LPV gain is related to the integral action of the system, that is, in order to eliminate the steady-state error, then the integral time constant Ti of the PID controller can be considered for adjustment, the integral action is mainly used to eliminate the steady-state error of the system, therefore by adjusting Ti, the influence of the LPV gain on the steady-state error can be simulated. If the change of the LPV gain is related to the dynamic performance of the system, for example, affecting the overshoot or oscillation frequency of the system, then the derivative time constant Td of the PID controller can be adjusted, the derivative action is mainly used to improve the dynamic performance of the system, by adjusting Td, the influence of the LPV gain on the dynamic characteristics of the system can be simulated. The initial mapping may not be accurate, therefore iteration optimization is needed, simulation or experimental data is used to evaluate the performance of the PID controller, and Kp, Ti and Td are adjusted as needed. The interaction between parameters needs to be considered when tuning, there is interaction between the three parameters Kp, Ti and Td, adjusting one parameter may affect the effect of other parameters, therefore, the changes of the three parameters need to be considered comprehensively during the mapping process, and appropriate coordination and adjustment are needed. Gradually adjust the PID parameters, which is usually an iterative process, and needs to be adjusted and tested multiple times. In the specific parameter tuning process, in order to improve the parameter tuning efficiency, an optimization algorithm (such as genetic algorithm, particle swarm optimization, etc.) can be used to automatically find the optimal PID parameters. After each parameter tuning, continue road testing until the road testing requirements are met. After the PID parameters are determined, a final verification test is performed to ensure that the system can perform well under all expected operating conditions.

[0076] Figure 6 is a schematic block diagram of a vehicle lateral control device 300 provided by an embodiment of the present application. As shown inFigure 6 Corresponding to the above vehicle lateral control method, the present application also provides a vehicle lateral control device 300. The vehicle lateral control device 300 includes a unit for executing the above vehicle lateral control method, and the device can be configured in a computer device. Specifically, please refer to Figure 6 The vehicle lateral control device 300 includes a general model unit 301, a target model unit 302, an LPV unit 303, and a lateral control unit 304.

[0077] The general model unit 301 is configured to obtain a pre-constructed general vehicle model; the target model unit 302 is configured to obtain configuration parameters of a target vehicle and input the configuration parameters into the general vehicle model to obtain a target vehicle model corresponding to the target vehicle; the LPV unit 303 is configured to construct a linear matrix inequality according to the target vehicle model and a preset robustness expectation index, and solve the linear matrix inequality to obtain an LPV controller corresponding to the target vehicle; and the lateral control unit 304 is configured to obtain driving parameters of the target vehicle and input the driving parameters into the LPV controller to output a front wheel steering angle of the target vehicle, and convert the front wheel steering angle into a steering wheel steering angle of the target vehicle to perform lateral control on the target vehicle.

[0078] In an embodiment, the general model unit includes a first construction unit and a second construction unit.

[0079] The first construction unit is configured to construct a lateral dynamics model of a vehicle based on configuration parameters and driving parameters of the vehicle, the configuration parameters including mass, front wheel track, rear wheel track, and moment of inertia of the vehicle, and the driving parameters including longitudinal speed, slip angle, yaw rate, external disturbance, and front wheel steering angle of the vehicle; and the second construction unit is configured to take a transpose matrix of the slip angle and the yaw rate as a state variable of a state space, take the front wheel steering angle as an input variable of the state space, take the external disturbance as a disturbance of the state space, and construct a state space of the vehicle according to the lateral dynamics model, the state space being used to represent a general vehicle model.

[0080] In an embodiment, the lateral dynamics model in the general model unit is:

[0081]

[0082]

[0083] wherein m is the mass, V x is the longitudinal speed, β is the slip angle, γ is the yaw rate, F yf is a lateral force of the front wheel, and F yrI is the lateral force for the rear wheel, z I is the moment of inertia for the rear wheel, f I is the front wheel track, r I is the rear wheel track, z M is the external disturbance; F yf F is the lateral force for the front wheel, yr F is given by:

[0084] F = C yf α yf α f

[0085] F = C yr α yr α r

[0086] where C yf is the cornering stiffness for the front wheel, C yr is the cornering stiffness for the rear wheel, C yf and C yr are constants, α f is the front wheel slip angle, α r is the rear wheel slip angle, the α f and α r are given by:

[0087]

[0088]

[0089] where δ is the front wheel steering angle.

[0090] In an embodiment, the state space in the generic model unit is:

[0091]

[0092] where x is the state variable, u is the input variable, w is the disturbance, x = [β γ] T , u = δ, w = M z , A, Bi and B2 represent matrices, in particular:

[0093]

[0094] In an embodiment, the LPV controller in the LPV unit 303 is:

[0095]

[0096] where A, B, C, D are matrices of the LPV controller, V xis the current vehicle speed, μ is the road friction coefficient, u is the front wheel steering angle output by the LPV controller, x is the input of the LPV controller, x includes the vehicle lateral state, and the vehicle lateral state is represented as [β γ] T , y is the output of the LPV controller, and y is composed of the vehicle lateral state and the front wheel steering angle output by the LPV controller.

[0097] In an embodiment, the vehicle lateral control device 300 further includes a first road test unit, a first road test judgment unit, and a first adjustment unit.

[0098] The first road test unit is configured to perform road test on the target vehicle by the LPV controller to obtain a road test result; the first road test judgment unit is configured to judge whether the road test result meets a road test passing condition; and the first adjustment unit is configured to, if the road test result does not meet the road test passing condition, adjust the robustness expectation index according to the road test result, and return to the step of performing road test on the target vehicle by the LPV controller to obtain a road test result until the road test result meets the road test passing condition, and output the LPV controller.

[0099] In an embodiment, the vehicle lateral control device 300 further includes a gain acquisition unit, a parameter adjustment unit, a second road test judgment unit, and a second adjustment unit.

[0100] The gain acquisition unit is configured to make the vehicle run in different working condition scenes, perform lateral control on the target vehicle by the LPV controller, and acquire a gain scheduling strategy of the LPV controller at this time; the parameter adjustment unit is configured to adjust the PID controller according to the gain scheduling strategy, and perform road test on the target vehicle by the adjusted PID controller to obtain a road test result; the second road test judgment unit is configured to judge whether the road test result meets a road test passing condition; and the second adjustment unit is configured to, if the road test result does not meet the road test passing condition, adjust the PID controller according to the road test result until the road test result meets the road test passing condition, and output the PID controller.

[0101] The vehicle lateral control device 300 described above can be implemented in the form of a computer program, which can run on a vehicle as shown in Figure 7 .

[0102] Please refer to Figure 7 , Figure 7 is a schematic block diagram of a vehicle provided by an embodiment of the present application.

[0103] Please refer to Figure 7The vehicle 500 comprises a processor 502, a memory and a network interface 505 connected through a system bus 501, wherein the memory can comprise a non-volatile storage medium 503 and an internal memory 504.

[0104] The non-volatile storage medium 503 can store an operating system 5031 and a computer program 5032. The computer program 5032 comprises program instructions which, when executed, cause the processor 502 to perform a vehicle lateral control method.

[0105] The processor 502 is configured to provide computing and control capabilities to support the operation of the entire vehicle 500.

[0106] The internal memory 504 provides an environment for the computer program 5032 in the non-volatile storage medium 503 to run, which, when executed by the processor 502, causes the processor 502 to perform a vehicle lateral control method.

[0107] The network interface 505 is configured to perform network communication with other devices. Those skilled in the art can understand that, Figure 7 The structure shown in FIG. 5 is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the vehicle 500 to which the scheme of the present application is applied. Specifically, the vehicle 500 can comprise more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0108] The processor 502 is configured to run the computer program 5032 stored in the memory to implement the steps of the above method.

[0109] It should be understood that, in the embodiments of the present application, the processor 502 can be a central processing unit (CPU), and the processor 502 can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0110] Those skilled in the art can understand that all or part of the processes in the method of the above-mentioned embodiments can be completed by instructing the relevant hardware by a computer program. The computer program includes program instructions, and the computer program can be stored in a storage medium, which is a computer readable storage medium. The program instructions are executed by at least one processor in the computer system to realize the process steps of the above-mentioned embodiment of the method.

[0111] Therefore, the present application also provides a storage medium. The storage medium can be a computer readable storage medium. The storage medium stores a computer program, wherein the computer program includes program instructions. The program instructions are executed by the processor to make the processor execute the steps of the above-mentioned method.

[0112] The storage medium can be a U disk, a mobile hard disk, a read-only memory (ROM), a magnetic disk or an optical disk, and various computer readable storage media that can store program codes.

[0113] Those skilled in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be realized by electronic hardware, computer software or a combination of both. In order to clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been described in the above description in general terms. Whether the functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. A person skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0114] In several embodiments provided by the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of each unit is only a logical function division, and actual implementation can have another division manner. For example, a plurality of units or components can be combined or integrated into another system, or some features can be omitted or not executed.

[0115] The steps in the method of the embodiments of the present application can be adjusted, combined and deleted in sequence according to actual needs. The units in the device of the embodiments of the present application can be combined, divided and deleted according to actual needs. In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit.

[0116] The integrated unit, if realized in the form of a software function unit and sold or used as an independent product, can be stored in a storage medium. Based on such understanding, the technical solutions of the present application essentially or say the part of the prior art that contributes to the present application, or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a vehicle to execute all or part of the steps of the method described in the various embodiments of the present application.

[0117] In the above embodiments, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0118] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, the modifications and variations of the present application also belong to the scope of the claims of the present application and its equivalent technologies, and the present application also intends to include these modifications and variations.

[0119] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical range disclosed by the present application, and these modifications or replacements should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A vehicle lateral control method, characterized in that: The method comprises: Get pre-built generic vehicle models; Acquiring configuration parameters of a target vehicle, and inputting the configuration parameters into the universal vehicle model to obtain a target vehicle model corresponding to the target vehicle; Constructing a linear matrix inequality according to the target vehicle model and a preset robustness expectation index, and solving the linear matrix inequality to obtain an LPV controller corresponding to the target vehicle; The driving parameters of the target vehicle are obtained and input into the LPV controller to output the front wheel angle of the target vehicle, and the front wheel angle is converted into the steering wheel angle of the target vehicle to perform lateral control on the target vehicle.

2. The method according to claim 1, characterized in that The steps of constructing the general vehicle model include: Constructing a lateral dynamics model of the vehicle based on configuration parameters and driving parameters of the vehicle, wherein the configuration parameters include: vehicle mass, front wheel wheelbase, rear wheel wheelbase, and moment of inertia; and the driving parameters include: vehicle longitudinal speed, slip angle, yaw rate, external disturbance, and front wheel steering angle; The transposed matrices of the slip angle and the yaw rate are used as state variables of a state space, the front wheel steering angle is used as an input variable of the state space, the external disturbance is used as a disturbance of the state space, and the state space of the vehicle is constructed according to the lateral dynamics model. The state space is used to represent a general vehicle model.

3. The method according to claim 2, characterized in that The lateral dynamics model is: Wherein, m is the mass, V x is the longitudinal velocity, β is the slip angle, γ is the yaw rate, F yf is the lateral force on the front wheel, F yr is the lateral force of the rear wheel, I z is the moment of inertia, l f is the front wheelbase, l r is the rear wheelbase, M z is the external disturbance; the F yf and the F yr Expressed as: F yf =C yf a f F yr =C yr a r Among them, C yf is the cornering stiffness of the front wheel, C yr is the cornering stiffness of the rear wheel, C yf and C yr is a constant, α f is the front wheel slip angle, α r is the rear wheel slip angle, the α f and α r The expression is: Wherein, δ is the front wheel turning angle.

4. The method according to claim 3, characterized in that The state space is: Wherein, the state variable is x, the input variable is u, the disturbance is w, and x=[β γ] T , u=δ,w=M z , A, B1 and B2 represent the matrices of the state space, as follows:

5. The method according to claim 4, characterized in that The LPV controller is: Among them, A, B, C, D are the matrices of the LPV controller, V x is the current vehicle speed, μ is the road friction coefficient, u is the front wheel steering angle output by the LPV controller, and x is the input of the LPV controller, where x includes the vehicle lateral state, which is expressed as [β γ] T , y is the output of the LPV controller, and y is composed of the vehicle lateral state and the front wheel angle output by the LPV controller.

6. The method according to claim 1, characterized in that The method further comprises: Performing a road test on the target vehicle by the LPV controller to obtain a road test result; Determining whether the drive test result meets the drive test pass condition; If the drive test result does not meet the drive test pass condition, the robustness expectation index is adjusted according to the drive test result, and the process returns to the step of performing a road test on the target vehicle through the LPV controller to obtain a drive test result, until the drive test result meets the drive test pass condition and is output to the LPV controller.

7. The method according to claim 6, characterized in that The method further comprises: Allowing the vehicle to travel under different operating conditions, performing lateral control on the target vehicle through the LPV controller, and obtaining a gain scheduling strategy of the LPV controller at this time; Adjusting the parameters of the PID controller according to the gain scheduling strategy, and performing a road test on the target vehicle using the adjusted PID controller to obtain a road test result; Determining whether the drive test result meets the drive test pass condition; If the drive test result does not meet the drive test pass condition, the PID controller is adjusted according to the drive test result until the drive test result meets the drive test pass condition and the PID controller is output.

8. A vehicle lateral control device, characterized in that: The method comprises a unit for executing the method according to any one of claims 1 to 7.

9. A vehicle, characterized in that: The vehicle includes a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that The storage medium stores a computer program, and when the computer program is executed by a processor, the computer program can implement the method according to any one of claims 1 to 7.

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