Vehicle control method and system, vehicle, storage medium and program product

Abstract

The invention provides a vehicle control method and system, a vehicle, a storage medium and a program product, and relates to the technical field of vehicles. According to the vehicle control method, vehicle state information and the current yaw velocity of a target vehicle are obtained, the predicted yaw velocity and the target yaw velocity are determined according to the vehicle state information, the feed-forward yaw moment and the feedback yaw moment are further determined according to the current yaw velocity, the predicted yaw velocity and the target yaw velocity, and the feedback yaw moment is determined according to the feedback yaw moment and the feed-forward yaw moment. And then the target vehicle is controlled according to the feedforward yaw moment and the feedback yaw moment. According to the vehicle control method and device, the vehicle is controlled by combining the feedforward yaw moment and the feedback yaw moment, feedforward control and feedback control are combined, the vehicle control precision is improved, and then the vehicle control stability is improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle technology, and in particular to a vehicle control method, system, vehicle, storage medium, and program product. Background Art

[0002] With the rapid development of the automotive industry and the improvement of road conditions, vehicle speeds have increased significantly, and users' requirements for vehicle handling stability are also increasing. As one of the important components of a vehicle, the vehicle chassis control system plays a vital role in maintaining vehicle handling stability.

[0003] In related technologies, vehicle chassis control systems rely on a single feedback control mechanism to achieve vehicle control. Specifically, this feedback control mechanism monitors the vehicle's actual driving state in real time, compares it with a predefined target driving state, and determines the deviation. The chassis control system then determines a control strategy based on this deviation to achieve vehicle control.

[0004] However, the inventors have discovered that in some scenarios, this vehicle control method has the problem of poor vehicle handling stability. Summary of the Invention

[0005] The present application provides a vehicle control method, system, vehicle, storage medium and program product to solve the problem of poor vehicle handling stability in some scenarios when controlling a vehicle through a single feedback control strategy.

[0006] In a first aspect, the present application provides a vehicle control method, comprising: obtaining vehicle state information and a current yaw rate of a target vehicle; determining a predicted yaw rate and a target yaw rate based on the vehicle state information; determining a feedforward yaw torque and a feedback yaw torque based on the current yaw rate, the predicted yaw rate and the target yaw rate; and controlling the target vehicle based on the feedforward yaw torque and the feedback yaw torque.

[0007] In a possible implementation, controlling the target vehicle according to the feedforward yaw moment and the feedback yaw moment includes: determining a target yaw moment according to the feedforward yaw moment and the feedback yaw moment; and controlling the target vehicle according to the target yaw moment.

[0008] In one possible implementation, a target vehicle includes different vehicle actuators, and controlling the target vehicle according to a target yaw moment includes: traversing the different vehicle actuators based on a priority order of the different vehicle actuators, and determining the target vehicle actuator according to a current compensable yaw moment and the target yaw moment corresponding to each of the different vehicle actuators; and controlling the target vehicle according to the target vehicle actuator and the current compensable yaw moment corresponding to the target vehicle actuator.

[0009] In one possible implementation, a predicted yaw rate and a target yaw rate are determined based on vehicle state information, including: determining the predicted yaw rate based on the vehicle state information based on a seven-degree-of-freedom vehicle model; and determining the target yaw rate based on the vehicle state information based on a two-degree-of-freedom vehicle model.

[0010] In one possible implementation, a feedforward yaw torque and a feedback yaw torque are determined based on a current yaw rate, a predicted yaw rate, and a target yaw rate, including: determining a predicted yaw rate deviation based on the predicted yaw rate and the target yaw rate; and determining the feedforward yaw torque based on the predicted yaw rate deviation; determining a current yaw rate deviation based on the current yaw rate and the target yaw rate; and determining the feedback yaw torque based on the current yaw rate deviation.

[0011] In one possible implementation, the vehicle state information includes a driving mode, a vehicle speed, and a steering wheel angle. The feedback yaw torque is determined based on a current yaw rate deviation, including: searching for target PID parameters based on a preset PID parameter table according to the driving mode, the vehicle speed, and the steering wheel angle; and determining the feedback yaw torque based on the target PID parameters and the current yaw rate deviation.

[0012] In a second aspect, the present application provides a chassis domain control system for executing the vehicle control method provided in the first aspect, the chassis domain control system comprising: a vehicle dynamics model, a feedforward prediction controller, a feedback controller, and a vehicle domain control actuator allocation module, wherein the vehicle dynamics model comprises a seven-degree-of-freedom vehicle model and a two-degree-of-freedom vehicle model;

[0013] The seven-degree-of-freedom vehicle model is used to calculate the predicted yaw rate of the target vehicle based on the vehicle state information of the target vehicle.

[0014] Two-degree-of-freedom vehicle model: used to calculate the target yaw rate of the target vehicle based on vehicle state information;

[0015] Feedforward predictive controller: used to determine the feedforward yaw torque based on the predicted yaw rate deviation;

[0016] Feedback controller: used to determine the feedback yaw torque based on the current yaw rate deviation;

[0017] Vehicle domain control actuator allocation module: used to control the target vehicle based on the feedforward yaw moment and feedback yaw moment.

[0018] In one possible implementation, the vehicle domain control actuator allocation module is also used to send one or more of the rear turning angle, braking torque and driving torque to the seven-degree-of-freedom vehicle model, the two-degree-of-freedom vehicle model and the vehicle actuators contained in the target vehicle respectively.

[0019] In a third aspect, the present application provides a vehicle comprising a vehicle body and a chassis domain control system as provided in the second aspect above.

[0020] In a fourth aspect, the present application provides a computer-readable storage medium, which stores computer-executable instructions. When the computer-executable instructions are executed by a processor, they are used to implement the vehicle control method provided in the first aspect above.

[0021] In a fifth aspect, the present application provides a computer program product, comprising: a computer program, which, when executed by a processor, implements the vehicle control method provided in the first aspect above.

[0022] The vehicle control method, system, vehicle, storage medium, and program product provided herein obtain vehicle state information and current yaw rate of a target vehicle, determine a predicted yaw rate and a target yaw rate based on the vehicle state information, further determine a feedforward yaw torque and a feedback yaw torque based on the current yaw rate, the predicted yaw rate, and the target yaw rate, and then control the target vehicle based on the feedforward yaw torque and the feedback yaw torque. This application combines feedforward and feedback control to control the vehicle, improving vehicle control accuracy and, consequently, vehicle handling stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0024] Figure 1 A schematic diagram of the structure of a chassis domain control system provided in an embodiment of the present application;

[0025] Figure 2 It is a structural schematic diagram of each degree of freedom included in the seven-degree-of-freedom vehicle model;

[0026] Figure 3 Schematic diagram of the process of the vehicle control method provided in the embodiment of the present application Figure 1 ;

[0027] Figure 4 Schematic diagram of the process of the vehicle control method provided in the embodiment of the present application Figure 2 ;

[0028] Figure 5 A flowchart of a target actuator determination method according to an embodiment of the present application;

[0029] Figure 6 A schematic diagram of a structure for searching target PID parameters based on driving mode, vehicle speed, and steering wheel angle provided in an embodiment of the present application.

[0030] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0031] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0032] The following first explains the terms involved in the embodiments of the present application.

[0033] Feedforward control: In chassis-domain control systems, feedforward control is a control strategy that proactively predicts and addresses factors that could affect vehicle handling stability. Specifically, it accurately calculates the vehicle's predicted driving state and proactively adjusts chassis parameters to ensure stable driving under various driving conditions. Feedforward control offers rapid response and can control the vehicle before disturbances occur, effectively avoiding or minimizing the impact of disturbances on vehicle handling stability.

[0034] Feedback control: In chassis-domain control systems, feedback control is a control strategy that monitors the vehicle's actual driving state in real time, compares it with a predefined target state, and then adjusts the vehicle based on the deviation between the actual and target states. Feedback control precisely controls key parameters such as the vehicle's trajectory and speed, ensuring stable driving under a variety of complex driving conditions. Feedback control offers significant advantages in improving vehicle handling stability due to its high control accuracy and handling stability.

[0035] Seven-DoF Vehicle Model: The seven-DoF vehicle model can also be described as a seven-DoF vehicle handling model. It primarily encompasses seven degrees of freedom: longitudinal motion, lateral motion, yaw motion, left front wheel rotation, left rear wheel rotation, right front wheel rotation, and right rear wheel rotation. This seven-DoF vehicle model is particularly suitable for research into vehicle stability control algorithms, such as those for anti-lock braking systems (ABS) and electronic stability programs (ESP). Because it accurately captures the forces acting on each wheel, it can accurately predict vehicle states. For example, by iterating the control algorithm, the seven-DoF vehicle model can use known acceleration information to calculate the vehicle speed change for the next cycle, thereby predicting vehicle states for several future computation cycles. Because the software's execution cycle is very short, typically less than 10 milliseconds, even multi-step predictions using this seven-DoF vehicle model are performed without inaccurate calculation results, thereby avoiding significant deviations in the control variables.

[0036] The two-degree-of-freedom vehicle model, also known as the linear two-degree-of-freedom vehicle model, is an important simplified model in vehicle dynamics research and is often used to analyze and evaluate vehicle handling stability and ride comfort. The two-degree-of-freedom vehicle model simplifies the complex vehicle system into a mass system with two primary degrees of freedom: lateral motion and yaw motion about a vertical axis. This two-degree-of-freedom vehicle model ignores other complex vehicle motions, such as vertical, pitch, and roll, facilitating in-depth theoretical analysis and simulation verification of the vehicle's handling performance.

[0037] In related technologies, vehicle chassis control systems rely on a single feedback control strategy to achieve vehicle control. However, this feedback control strategy can suffer from response lag and insufficient control accuracy when dealing with complex and ever-changing driving scenarios, such as high-speed driving, emergency obstacle avoidance, and complex road conditions. This can affect the vehicle's handling stability and driving safety.

[0038] Based on the problems existing in the related technology, the embodiments of the present application combine feedforward control and feedback control, adjust the predicted driving state of the vehicle in advance based on the feedforward yaw moment, and adjust the actual driving state of the vehicle based on the feedback yaw moment, thereby improving the vehicle control accuracy and thus improving the vehicle handling stability.

[0039] Figure 1 This is a schematic diagram of the structure of the chassis domain control system provided in the embodiment of this application. Figure 1As shown, the chassis domain control system includes a vehicle dynamics model, a feedforward prediction controller, a feedback controller and a vehicle domain control actuator allocation module. The vehicle dynamics model includes a seven-degree-of-freedom vehicle model and a two-degree-of-freedom vehicle model.

[0040] Among them, the seven-degree-of-freedom vehicle model is used to calculate the predicted yaw velocity of the target vehicle based on the vehicle status information of the target vehicle; the two-degree-of-freedom vehicle model is used to calculate the target yaw velocity of the target vehicle based on the vehicle status information; the feedforward prediction controller is used to determine the feedforward yaw torque based on the predicted yaw velocity deviation; the feedback controller is used to determine the feedback yaw torque based on the current yaw velocity deviation; the vehicle domain control actuator allocation module is used to control the target vehicle based on the feedforward yaw torque and the feedback yaw torque.

[0041] For example, Figure 1 As shown in , the vehicle state information includes a steering wheel angle signal input by the driver, a braking torque requested by the driver, a driving torque requested by the driver, and one or more of the target vehicle's current rear wheel angle, braking torque, and driving torque output by the vehicle domain control actuator allocation module. The steering wheel angle signal may include a steering wheel rotation angle and a steering wheel rotation angular velocity. The driver-requested braking torque may be the braking torque generated by the driver applying the brake pedal of the target vehicle. The driver-requested driving torque may be the driving torque generated by the driver applying the accelerator pedal of the target vehicle. The rear steering angle may be the rotation angle of the target vehicle's rear wheels relative to the longitudinal axis of the target vehicle.

[0042] Figure 2 This is a structural diagram of the various degrees of freedom included in the seven-degree-of-freedom vehicle model.

[0043] like Figure 2 As shown, the seven-degree-of-freedom vehicle model includes the vehicle longitudinal motion , lateral movement of the vehicle , vehicle yaw motion , rotation of the left front wheel, rotation of the left rear wheel, rotation of the right front wheel and rotation of the right rear wheel.

[0044] Among them, the rotation of the left front wheel can be controlled by the longitudinal force of the left front wheel and the lateral force on the left front wheel Indicates that the rotation of the left rear wheel can be controlled by the longitudinal force of the left rear wheel and the lateral force on the left rear wheel Indicates that the rotation of the right front wheel can be controlled by the longitudinal force of the right front wheel and the lateral force on the right front wheel Indicates that the rotation of the right rear wheel can be controlled by the longitudinal force of the right rear wheel and the lateral force on the right rear wheel express.

[0045] For example, the seven-degree-of-freedom vehicle model provided in the embodiment of the present application has the main function of compensating for the lag caused by signal delay and actuator response time by predicting the yaw rate deviation. For example, assuming that the operating cycle of the software is 10ms, the delay from the actuator receiving the instruction to the execution of the instruction is 60ms, and there is a 20ms delay in signal transmission. In this case, the seven-degree-of-freedom vehicle model needs to calculate the driving state of the target vehicle after 80ms in order to effectively control the target vehicle. This ensures that the adjustment of the driving state of the target vehicle is based on the current actual driving state. If such a prediction is not performed, the predicted yaw rate deviation of the input feedforward prediction controller will be inaccurate, which will lead to inaccurate control of the target vehicle. In the embodiment of the present application, by adopting the seven-degree-of-freedom vehicle model to obtain the predicted yaw rate deviation, the chassis domain control system can respond more accurately to the dynamic changes of the driving state of the target vehicle to improve the vehicle handling stability.

[0046] For example, a two-degree-of-freedom vehicle model can well reflect the operating state of the vehicle. Therefore, the present application uses a two-degree-of-freedom vehicle model to calculate the target yaw angular velocity.

[0047] For example, the control strategy of a feedforward predictive controller can be model predictive control (MPC). The essence of MPC is to solve an open-loop optimal control problem. The basic idea is to solve a finite-time open-loop optimal problem based on the current measurement information at each sampling moment, send the currently solved control variable to the controlled object, and then proceed to the next sampling moment. The above process is repeated, and the optimization problem is updated with the new measurement value, and then the problem is solved again to form a closed-loop control system. Through rolling optimization, MPC can minimize the deviation between the future predicted output of the controlled object and the expected output, and can compensate for errors caused by system instability.

[0048] It is understandable that when a vehicle changes lanes at high speeds, due to its own nonlinearity and external environmental interference, there is often a deviation between the actual value of the vehicle's driving state and the desired reference value. It is necessary to apply an additional yaw moment to the vehicle to track and adjust the vehicle's yaw rate so that it approaches the desired reference value. Therefore, to achieve stable driving during high-speed lane changes, the chassis-domain control system provided in the embodiments of this application uses the yaw moment as the control variable to derive the vehicle's driving state-space equation under MPC control. Based on this vehicle driving state-space equation, the feedforward yaw moment is derived by predicting the yaw rate deviation.

[0049] Exemplarily, the feedback controller may be a PID controller.

[0050] It should be noted that, in the chassis domain control system provided in the embodiment of the present application, a five-degree-of-freedom vehicle model can also be used to calculate the target yaw angular velocity.

[0051] like Figure 1 As shown in , a possible implementation method of controlling a vehicle based on the chassis domain control system may include the following steps:

[0052] 1) The driver outputs a steering wheel angle signal, a requested braking torque, and a requested driving torque to the seven-degree-of-freedom vehicle model, the two-degree-of-freedom vehicle model, and the target vehicle, respectively. The vehicle domain control actuator allocation module outputs one or more of the rear wheel angle, braking torque, and driving torque to the seven-degree-of-freedom vehicle model, the two-degree-of-freedom vehicle model, and the target vehicle, respectively.

[0053] 2) The seven-degree-of-freedom vehicle model calculates a predicted yaw rate based on the vehicle state information from step 1). The two-degree-of-freedom vehicle model calculates a target yaw rate based on the vehicle state information from step 1). The target vehicle performs vehicle maneuvers based on the vehicle state information from step 1 and obtains its current yaw rate.

[0054] 3) Based on the feedforward algorithm, the minimum difference between the predicted yaw rate and the target yaw rate is calculated and used as the predicted yaw rate deviation. Based on the feedback algorithm, the minimum difference between the current yaw rate and the target yaw rate is calculated and used as the current yaw rate deviation.

[0055] 4) The predicted yaw rate deviation is input into the feedforward predictive controller to obtain the feedforward yaw torque output by the feedforward predictive controller. The current yaw rate deviation is input into the feedback controller to obtain the feedback yaw torque output by the feedback controller.

[0056] 5) The feedforward yaw moment and the feedback yaw moment vector are summed to obtain the target yaw moment, and the target yaw moment is input into the vehicle domain control actuator allocation module to control the target vehicle based on the target yaw moment.

[0057] Optionally, the vehicle domain control actuator allocation module is also used to send one or more of the rear turning angle, braking torque and driving torque to the seven-degree-of-freedom vehicle model, the two-degree-of-freedom vehicle model and the vehicle actuators contained in the target vehicle respectively.

[0058] For example, the vehicle actuators included in the target vehicle may be a rear wheel steering actuator, a drive distribution actuator, a brake distribution actuator, and a continuous damping control (CDC) in an active suspension.

[0059] Exemplarily, when the actuator used to compensate for the target yaw moment is a rear-wheel steering actuator, the vehicle domain control actuator allocation module sends the rear turning angle to the seven-degree-of-freedom vehicle model, the two-degree-of-freedom vehicle model and the vehicle actuators included in the target vehicle respectively; when the actuator used to compensate for the target yaw moment is a drive allocation actuator, the vehicle domain control actuator allocation module sends the drive torque to the seven-degree-of-freedom vehicle model, the two-degree-of-freedom vehicle model and the vehicle actuators included in the target vehicle respectively; when the actuator used to compensate for the target yaw moment is a brake allocation actuator, the vehicle domain control actuator allocation module sends the braking torque to the seven-degree-of-freedom vehicle model, the two-degree-of-freedom vehicle model and the vehicle actuators included in the target vehicle respectively, etc.

[0060] It can be understood that the chassis domain control system provided in the embodiment of the present application is a chassis domain control system that cooperates with feedforward control and feedback control. The chassis domain control system achieves precise and rapid control of the chassis domain system by combining the rapid response capability of feedforward control and the high-precision stability of feedback control. In the chassis domain control system, feedforward control can adjust the chassis parameters in advance according to the predicted vehicle driving state and potential disturbances, thereby effectively compensating for the impact of these disturbances on the vehicle's handling stability. At the same time, feedback control can monitor the actual driving state of the vehicle in real time, and make precise adjustments based on the deviation to ensure that the vehicle can maintain a stable driving state under various driving conditions. Through this combination, the response speed, control accuracy and adaptability of the chassis domain control system can be improved, thereby providing the driver with a safer and more comfortable driving experience.

[0061] The following is the above Figure 1 The chassis domain control system shown in is an actuator. Combined with specific embodiments, the vehicle control method provided in the embodiment of the present application is described in detail.

[0062] Figure 3 Schematic diagram of the process of the vehicle control method provided in the embodiment of the present application Figure 1 .like Figure 3 As shown, the specific implementation of the vehicle control method includes the following steps:

[0063] S301, obtaining vehicle state information and current yaw angular velocity of the target vehicle.

[0064] Exemplarily, the vehicle status information includes a steering wheel angle signal input by the driver, a braking torque requested by the driver, a driving torque requested by the driver, and one or more of the current rear wheel angle, braking torque, and driving torque of the target vehicle output by the vehicle domain control actuator allocation module.

[0065] Illustratively, the current yaw rate is a real-time yaw rate of the target vehicle obtained when the target vehicle performs vehicle maneuvering based on the vehicle state information.

[0066] S302: Determine a predicted yaw rate and a target yaw rate according to the vehicle state information.

[0067] For example, the predicted yaw rate can be a prediction of the target vehicle's yaw rate over a period of time in the future based on the target vehicle's current driving state and a vehicle model. The predicted yaw rate is used in the feedforward control of the chassis control system to improve vehicle handling stability.

[0068] For example, the target yaw rate can be an ideal yaw rate calculated based on the driver's input and predefined vehicle behavior. The target yaw rate is used to represent the rotational speed that the target vehicle should ideally achieve in order to achieve the driver's intended control.

[0069] In this step, in a possible implementation, the predicted yaw rate and the target yaw rate may be determined based on a vehicle dynamics model and according to vehicle state information.

[0070] S303 : Determine a feedforward yaw moment and a feedback yaw moment according to the current yaw rate, the predicted yaw rate, and the target yaw rate.

[0071] In a possible implementation, a feedforward yaw torque is determined based on the predicted yaw rate and the target yaw rate; and a feedback yaw torque is determined based on the current yaw rate and the target yaw rate.

[0072] S304 : Control the target vehicle according to the feedforward yaw moment and the feedback yaw moment.

[0073] In an embodiment of the present application, vehicle state information and current yaw rate of a target vehicle are acquired, and a predicted yaw rate and a target yaw rate are determined based on the vehicle state information. A feedforward yaw torque and a feedback yaw torque are further determined based on the current yaw rate, the predicted yaw rate, and the target yaw rate. The target vehicle is then controlled based on the feedforward yaw torque and the feedback yaw torque. In an embodiment of the present application, the vehicle is controlled by combining the feedforward yaw torque and the feedback yaw torque, achieving a combination of feedforward and feedback control, improving vehicle control accuracy and, consequently, vehicle handling stability.

[0074] The following combination Figure 4 A possible implementation of controlling the target vehicle according to the feedforward yaw moment and the feedback yaw moment in step S304 is described in detail.

[0075] Figure 4 Schematic diagram of the process of the vehicle control method provided in the embodiment of the present application Figure 2 .like Figure 4As shown, a possible implementation of controlling the target vehicle according to the feedforward yaw moment and the feedback yaw moment in the vehicle control method may include the following steps:

[0076] S401 : Determine a target yaw moment according to the feedforward yaw moment and the feedback yaw moment.

[0077] Exemplarily, in some embodiments, the vector sum of the feedforward yaw moment and the feedback yaw moment is calculated, and the vector sum is used as the target yaw moment; in some embodiments, the first product of the feedforward yaw moment and the preset proportional coefficient, and the second product of the feedback yaw moment and the preset proportional coefficient are calculated respectively, and then the vector sum of the first product and the second product is used as the target yaw moment.

[0078] For example, the preset proportional coefficient may be 0.5. The embodiment of the present application does not limit the size of the preset proportional coefficient, which can be determined according to actual application requirements.

[0079] It can be understood that the feedforward yaw moment includes a positive and negative sign, and its positive and negative signs are used to indicate the torque direction of the feedforward yaw moment, and the feedback yaw moment includes a positive and negative sign, and its positive and negative signs are used to indicate the torque direction of the feedback yaw moment.

[0080] For example, when the torque direction of the feedforward yaw moment is clockwise, the feedforward yaw moment is determined to be positive, and when the torque direction of the feedforward yaw moment is counterclockwise, the feedforward yaw moment is determined to be negative; or when the torque direction of the feedforward yaw moment is clockwise, the feedforward yaw moment is determined to be negative, and when the torque direction of the feedforward yaw moment is counterclockwise, the feedforward yaw moment is determined to be positive, etc. The positive and negative signs of the feedback yaw moment are similar and are not further described here.

[0081] S402: Control the target vehicle according to the target yaw moment.

[0082] Optionally, in one possible implementation, based on the priority order of different vehicle actuators included in the target vehicle, different vehicle actuators are traversed, and the target vehicle actuator is determined according to the current compensable yaw moment and the target yaw moment corresponding to each vehicle actuator among the different vehicle actuators; and the target vehicle is controlled according to the target vehicle actuator and the current compensable yaw moment corresponding to the target vehicle actuator.

[0083] For example, the different vehicle actuators may be a rear wheel steering actuator, a drive distribution actuator, a brake distribution actuator, and the like.

[0084] For example, the priority order of different vehicle actuators from high to low may be a drive distribution actuator, a rear wheel steering actuator, and a brake distribution actuator.

[0085] For example, the priority order of different vehicle actuators is determined based on the driver's perception of the actuator execution results.

[0086] Figure 5 This is a flow chart of a target actuator determination method provided in an embodiment of the present application. Figure 5 As shown, the target actuator is determined in the following manner: based on the priority order of different vehicle actuators, firstly, a first difference between the target yaw moment and the current compensable yaw moment corresponding to the drive distribution actuator is calculated, and it is determined whether the first difference is less than or equal to 0. If the first difference is less than or equal to 0, the drive distribution actuator is determined to be the target actuator and the drive torque is output; if the first difference is greater than 0, a second difference between the first difference and the current compensable yaw moment corresponding to the rear-wheel steering actuator is calculated, and it is determined whether the second difference is less than or equal to 0. If the second difference is less than or equal to 0, the target actuator is determined to be the output drive torque; If the second difference is greater than 0, the drive distribution actuator and the rear-wheel steering actuator are determined to be the target actuators, and the drive torque and rear wheel steering angle are output; if the second difference is greater than 0, a third difference between the second difference and the current compensable yaw moment corresponding to the brake distribution actuator is calculated to determine whether the third difference is less than or equal to 0; if the third difference is less than or equal to 0, the drive distribution actuator, the rear-wheel steering actuator, and the brake distribution actuator are determined to be the target actuators, and the drive torque, rear wheel steering angle, and braking torque are output; if the third difference is greater than 0, the Electronic Stability Control (ESC) system is activated.

[0087] For example, when the target yaw moment is 100 NM and the current compensable yaw moment corresponding to the drive distribution actuator is 60 NM, the difference between the two is greater than 0, which means that the target yaw moment cannot be compensated by the drive distribution actuator alone, and the rear-wheel steering actuator is required to compensate for the remaining target yaw moment. If the current compensable yaw moment corresponding to the rear-wheel steering actuator is 200 NM, which is much larger than the remaining 40 NM target yaw moment, the remaining target yaw moment can be compensated by the rear-wheel steering actuator without the intervention of the brake distribution actuator.

[0088] It is understood that in this step, the amount of vehicle yaw torque that can be provided by adjusting the drive distribution actuator, namely, the current compensable yaw torque of the drive distribution actuator, is first calculated, and the drive torque is simultaneously output. When the drive distribution actuator reaches its maximum yaw torque adjustment capacity, if there is any remaining target yaw torque that has not been implemented by an actuator, the remaining target yaw torque is distributed to the next vehicle actuator in the order of priority until all target yaw moments are compensated. If the different vehicle actuators cannot compensate for the entire target yaw torque, that is, the chassis domain control system cannot restore the target vehicle to a stable driving state, the ESC system intervenes to restore the target vehicle to a stable driving state.

[0089] In the embodiment of the present application, a target yaw moment is determined based on the feedforward yaw moment and the feedback yaw moment, and a target vehicle is controlled based on the target yaw moment to improve vehicle handling stability.

[0090] It can be understood that in the vehicle control method provided in the embodiment of the present application, when the feedback yaw moment can be ignored, the vehicle can be controlled to return to a stable driving state based on the feedforward yaw moment; when the feedback yaw moment is large, the target vehicle can be controlled to return to a stable driving state based on the feedforward yaw moment and the feedback yaw moment; when the target vehicle cannot be controlled to return to a stable driving state based on the feedforward yaw moment and the feedback yaw moment, the ESC system is accessed to control the target vehicle to return to a stable driving state, thereby improving the vehicle handling stability.

[0091] Optionally, a possible implementation of step S302 for determining the predicted yaw rate and the target yaw rate based on the vehicle state information may be: determining the predicted yaw rate based on the vehicle state information based on a seven-degree-of-freedom vehicle model; or determining the target yaw rate based on the vehicle state information based on a two-degree-of-freedom vehicle model.

[0092] The vehicle status information is similar to the above and will not be repeated here.

[0093] Exemplarily, the vehicle state information is input into a seven-degree-of-freedom vehicle model to obtain a predicted yaw angular velocity output by the seven-degree-of-freedom vehicle model.

[0094] Exemplarily, the vehicle state information is input into a two-degree-of-freedom vehicle model to obtain a target yaw angular velocity output by the two-degree-of-freedom vehicle model.

[0095] In a possible implementation, the vehicle state information may be input into a five-degree-of-freedom vehicle model to obtain a target yaw angular velocity output by the five-degree-of-freedom vehicle model.

[0096] Optionally, a possible implementation manner of determining the feedforward yaw torque and the feedback yaw torque according to the current yaw angular velocity, the predicted yaw angular velocity, and the target yaw angular velocity in step S303 may be as follows: determining a predicted yaw angular velocity deviation according to the predicted yaw angular velocity and the target yaw angular velocity; and determining the feedforward yaw torque according to the predicted yaw angular velocity deviation; determining the current yaw angular velocity deviation according to the current yaw angular velocity and the target yaw angular velocity; and determining the feedback yaw torque according to the current yaw angular velocity deviation.

[0097] For example, based on a feedforward algorithm, a difference between the predicted yaw rate and the target yaw rate is calculated and used as the predicted yaw rate deviation. The feedforward algorithm may be an algorithm that minimizes the difference between the predicted yaw rate and the target yaw rate.

[0098] Exemplarily, the feedforward algorithm may be an MPC prediction algorithm.

[0099] Illustratively, the predicted yaw rate deviation may be positive or negative, and the positive and negative signs are used to indicate the rotation direction of the predicted yaw rate deviation.

[0100] For example, based on a feedback algorithm, a difference between the current yaw rate and the target yaw rate is calculated and used as the current yaw rate deviation. The feedback algorithm may be an algorithm that minimizes the difference between the current yaw rate and the target yaw rate.

[0101] Exemplarily, the feedback algorithm may be a PID algorithm, a fuzzy PID algorithm, or a sliding mode control algorithm.

[0102] Illustratively, the current yaw rate deviation may be positive or negative, and the positive and negative signs are used to indicate the rotation direction of the current yaw rate deviation.

[0103] For example, a possible implementation method for determining the feedforward yaw torque according to the predicted yaw rate deviation may be: inputting the predicted yaw rate deviation into a feedforward predictive controller to obtain the feedforward yaw torque output by the feedforward predictive controller.

[0104] Optionally, the vehicle status information provided in embodiments of the present application may also include driving mode, vehicle speed, and steering wheel angle. One possible implementation for determining the feedback yaw torque based on the current yaw rate deviation may include searching for target PID parameters based on a preset PID parameter table, the driving mode, vehicle speed, and steering wheel angle, and determining the feedback yaw torque based on the target PID parameters and the current yaw rate deviation.

[0105] For example, the driving mode may be a sports mode, an economy mode, a comfort mode, a snow mode, and the like.

[0106] Figure 6 The schematic diagram of the structure of searching the target PID parameters according to the driving mode, vehicle speed and steering wheel angle provided in the embodiment of the present application. Figure 6 As shown, there are three tables for searching parameter P, such as Table 1, Table 2 and Table 3, and different tables correspond to different driving modes; there are three tables for searching parameter I, such as Table 4, Table 5 and Table 6, and different tables correspond to different driving modes; there are three tables for searching parameter D, such as Table 7, Table 8 and Table 9, and different tables correspond to different driving modes.

[0107] Exemplarily, in one possible implementation, when searching for parameter P, when the driving mode is sport mode, the parameter P is searched in Table 1 based on the vehicle speed and the steering wheel angle to obtain the target parameter P; when the driving mode is economy mode, the parameter P is searched in Table 2 based on the vehicle speed and the steering wheel angle to obtain the target parameter P; when the driving mode is snow mode, the parameter P is searched in Table 3 based on the vehicle speed and the steering wheel angle to obtain the target parameter P.

[0108] For example, in one possible implementation, the parameter P may be searched in a table corresponding to the driving mode based on the absolute value of the vehicle speed and the absolute value of the steering wheel angle.

[0109] The search for parameters I and D is similar to the search for parameter P described above and will not be repeated here.

[0110] It should be noted that the embodiment of the present application does not specifically limit the correspondence between the lookup tables corresponding to the driving modes and the parameters PID, and can be determined based on actual application requirements.

[0111] For example, a possible implementation method for determining the feedback yaw torque based on the target PID parameters and the current yaw rate deviation may be: respectively calculating the products of the current yaw rate deviation and the target parameter P, the target parameter I, and the target parameter D, and using the sum of the calculated products as the feedback yaw torque.

[0112] In summary, the vehicle control method and chassis domain control system provided by the embodiments of the present application have the following beneficial effects:

[0113] 1) Compared to conventional chassis control systems in related technologies that rely on a single feedback control mechanism, i.e., real-time monitoring of the vehicle's actual driving state and adjustments based on the deviation between the vehicle's actual driving state and a predefined target driving state, resulting in a slow response speed, the vehicle control method and chassis domain control system provided in the embodiments of the present application, by introducing feedforward control, can predict and compensate for the impact of potential disturbances on vehicle handling stability in advance. Feedforward control, based on the vehicle's target driving state and predictions of potential disturbances, can adjust the vehicle before disturbances occur, significantly accelerating the response speed of the chassis domain control system.

[0114] 2) Compared to the low control accuracy of traditional chassis control systems, the vehicle control method and chassis domain control system provided by the embodiments of this application, through the combination of feedforward and feedback control, can more comprehensively consider the various factors affecting the dynamic characteristics of the chassis system. Feedforward control is responsible for quickly responding to and compensating for potential disturbances, while feedback control is responsible for precisely adjusting the vehicle's driving state. This combination of feedforward and feedback control improves control accuracy.

[0115] 3) Compared with the vehicle signal transmission and actuator delay problems existing in traditional chassis control systems, the vehicle control method and chassis domain control system provided in the embodiments of the present application, through the combination of a feedforward predictive controller and a seven-degree-of-freedom vehicle model, can more accurately predict the vehicle's driving state, prevent shaking when controlling the vehicle, and ensure that the vehicle can maintain a stable driving state under various driving conditions.

[0116] 4) Compared with the traditional chassis control system in the related art, many control variables may be selected for control, such as yaw rate, center of mass sideslip angle and roll angle to control the vehicle together to improve handling stability and safety. However, too many control variables will make the vehicle extremely easy to intervene in control, which will show the driver problems such as insufficient vehicle stability and reduced handling performance. There are too many actuators and they cannot be decoupled, which causes all actuators to intervene in control, making it easier for the vehicle to overshoot and cause instability. The vehicle control method and chassis domain control system provided in the embodiment of the present application combine feedforward control and feedback control, and only use the vehicle's yaw rate to control the vehicle. The vehicle is controlled by calculating the target yaw rate and the predicted yaw rate. The control quantity is controlled only by the yaw torque, which is easy to analyze into the control quantity of the actuator, which can improve the control accuracy and provide the driver with a safer and more comfortable driving experience.

[0117] An embodiment of the present application also provides a vehicle, which includes a vehicle body and the chassis domain control system provided in the above embodiment.

[0118] An embodiment of the present application also provides a computer program product, including a computer program, which implements the above method when executed by a processor.

[0119] An embodiment of the present application further provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the above-mentioned method is implemented.

[0120] The readable storage medium may be implemented by any type of volatile or non-volatile memory device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium may be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0121] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0122] The division of units is merely a logical functional division; actual implementations may employ alternative divisions, such as combining or integrating multiple units or components into another system, or omitting or disabling certain features. Furthermore, any direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units, either through an interface, electrical, mechanical, or other means.

[0123] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0124] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0125] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of the present invention. The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0126] Those skilled in the art will appreciate that all or part of the steps in the above-described method embodiments can be implemented using hardware associated with program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0127] Finally, it should be noted that those skilled in the art will readily identify other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art not disclosed herein. The present invention is not limited to the precise structure described above and illustrated in the accompanying drawings, and various modifications and variations may be made without departing from the scope thereof. The scope of the present invention is limited solely by the appended claims.

Claims

1. A vehicle control method, characterized in that: include: Obtain vehicle status information and current yaw rate of the target vehicle; determining a predicted yaw rate and a target yaw rate according to the vehicle state information; determining a feedforward yaw moment and a feedback yaw moment according to the current yaw rate, the predicted yaw rate, and the target yaw rate; The target vehicle is controlled according to the feedforward yaw moment and the feedback yaw moment.

2. The vehicle control method according to claim 1, characterized in that: The controlling the target vehicle according to the feedforward yaw moment and the feedback yaw moment includes: determining a target yaw moment according to the feedforward yaw moment and the feedback yaw moment; The target vehicle is controlled according to the target yaw moment.

3. The vehicle control method according to claim 2, characterized in that: The target vehicle includes different vehicle actuators, and controlling the target vehicle according to the target yaw moment includes: traversing the different vehicle actuators based on a priority order of the different vehicle actuators, and determining a target vehicle actuator according to a current compensable yaw moment corresponding to each of the different vehicle actuators and the target yaw moment; The target vehicle is controlled according to the target vehicle actuator and a current compensable yaw moment corresponding to the target vehicle actuator.

4. The vehicle control method according to any one of claims 1 to 3, characterized in that: The step of determining a predicted yaw rate and a target yaw rate according to the vehicle state information includes: determining the predicted yaw rate based on the vehicle state information based on a seven-degree-of-freedom vehicle model; The target yaw rate is determined based on a two-degree-of-freedom vehicle model and according to the vehicle state information.

5. The vehicle control method according to any one of claims 1 to 3, characterized in that: The determining of the feedforward yaw moment and the feedback yaw moment according to the current yaw rate, the predicted yaw rate, and the target yaw rate includes: determining a predicted yaw rate deviation based on the predicted yaw rate and the target yaw rate; and determining the feedforward yaw torque based on the predicted yaw rate deviation; A current yaw rate deviation is determined according to the current yaw rate and the target yaw rate; and the feedback yaw torque is determined according to the current yaw rate deviation.

6. The vehicle control method according to claim 5, characterized in that: The vehicle state information includes a driving mode, a vehicle speed, and a steering wheel angle, and determining the feedback yaw moment according to the current yaw rate deviation includes: Based on a preset PID parameter table, searching for target PID parameters according to the driving mode, the vehicle speed, and the steering wheel angle; The feedback yaw torque is determined according to the target PID parameter and the current yaw rate deviation.

7. A chassis domain control system, characterized in that: Used to execute the vehicle control method according to any one of claims 1 to 6, the chassis domain control system comprises: a vehicle dynamics model, a feedforward prediction controller, a feedback controller, and a vehicle domain control actuator allocation module, the vehicle dynamics model comprising a seven-degree-of-freedom vehicle model and a two-degree-of-freedom vehicle model; The seven-degree-of-freedom vehicle model is used to calculate the predicted yaw rate of the target vehicle based on the vehicle state information of the target vehicle; The two-degree-of-freedom vehicle model is used to calculate the target yaw rate of the target vehicle based on the vehicle state information; The feedforward prediction controller is used to determine the feedforward yaw torque according to the predicted yaw rate deviation; The feedback controller is configured to determine a feedback yaw moment according to the current yaw rate deviation; The vehicle domain control actuator allocation module is used to control the target vehicle according to the feedforward yaw torque and the feedback yaw torque; and is also used to send one or more of the rear turning angle, braking torque and driving torque to the vehicle actuators contained in the seven-degree-of-freedom vehicle model, the two-degree-of-freedom vehicle model and the target vehicle respectively.

8. A vehicle, characterized in that: It comprises a vehicle body and a chassis domain control system as claimed in claim 7.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 6 when executed by a processor.

10. A computer program product, characterized in that include: A computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 6.

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