Longitudinal, transverse and vertical integrated control method and system, vehicle and medium

Abstract

The invention relates to a longitudinal, transverse and vertical integrated control method and system, a vehicle and a medium, and relates to the technical field of vehicle control, and the method comprises the steps: collecting dynamic parameters of the vehicle through a sensor, and building a multi-degree-of-freedom model of the vehicle in the longitudinal, transverse and vertical directions based on the dynamic parameters; obtaining a future motion state of the vehicle in a prediction time domain based on the dynamic parameters and a multi-degree-of-freedom model, and generating an optimal control instruction sequence based on the future motion state; based on the optimal control instruction sequence, carrying out integrated control on the vehicle, and carrying out unified optimal distribution on longitudinal, transverse and vertical forces of vehicle tires; and controlling each actuator of the vehicle to execute corresponding actions according to the optimal distribution result. According to the invention, the driving comfort of the vehicle under various bad working conditions can be improved.

Description

Technical Field

[0001] The present invention relates to the field of vehicle control technology, and in particular to a longitudinal, lateral and vertical integrated control method, system, vehicle and medium. Background Art

[0002] As cars are undergoing technological changes in electrification, intelligence, and networking, smart cars have more devices that can be controlled, and the requirements for the stability and safety of car driving are getting higher and higher. Traditional car control methods usually perform independent control or longitudinal and lateral integrated control in a specific direction. For example, longitudinal control mainly focuses on the vehicle's driving speed and braking system, lateral control mainly focuses on the vehicle's steering system, and vertical control mainly focuses on the vehicle's suspension system. However, these control methods may not achieve ideal driving results when dealing with complex road conditions and emergency driving situations. Summary of the invention

[0003] In view of the shortcomings of the prior art described above, an object of the present invention is to provide a longitudinal, lateral and vertical integrated control method, system, vehicle and medium to improve the driving comfort of the vehicle under various adverse working conditions.

[0004] To achieve the above purpose, the present invention adopts the following technical solution.

[0005] In a first aspect, the present invention provides a longitudinal, lateral and vertical integrated control method, which adopts the following technical solution: The dynamic parameters of the vehicle are collected by sensors, and a multi-degree-of-freedom model of the vehicle in the longitudinal, lateral and vertical directions is established based on the dynamic parameters; Based on the dynamic parameters and the multi-degree-of-freedom model, obtaining the future motion state of the vehicle in the prediction time domain, and generating an optimal control instruction sequence based on the future motion state; Based on the optimal control instruction sequence, the vehicle is integratedly controlled to uniformly optimize the longitudinal, lateral and vertical forces of the vehicle tires; According to the result of the optimization allocation, each actuator of the vehicle is controlled to perform corresponding actions.

[0006] Furthermore, in the above-mentioned longitudinal, lateral and vertical integrated control method, the future motion state of the vehicle in the prediction time domain is obtained based on the dynamic parameters and the multi-degree-of-freedom model, including: The dynamic parameters collected in real time are substituted into the multi-degree-of-freedom model to calculate the vehicle status at the current moment; Based on the current vehicle state, the future motion state of the vehicle within the prediction time domain is predicted through dynamic equations and control algorithms.

[0007] Furthermore, in the above-mentioned longitudinal, lateral and vertical integrated control method, the optimal control instruction sequence is generated by a model predictive control algorithm.

[0008] Furthermore, in the above longitudinal, lateral and vertical integrated control method, the integrated control of the vehicle based on the optimal control instruction sequence and the unified optimization distribution of the longitudinal, lateral and vertical forces of the vehicle tires include: Substituting the relationship between the vehicle resultant force and the four-wheel tire force into the multi-degree-of-freedom model to obtain the expected value of the vehicle kinematic control target; A unified optimization distribution method is adopted to uniformly optimize the distribution of the longitudinal force, lateral force and vertical force of the tire to eliminate the conflict between different chassis electronic control systems.

[0009] Furthermore, in the above-mentioned longitudinal, lateral and vertical integrated control method, the expected values ​​include longitudinal speed, lateral speed, vertical speed, pitch angle, roll angle and yaw angle.

[0010] Furthermore, the above-mentioned longitudinal, lateral and vertical integrated control method further includes: Monitor the actual motion state of the vehicle in real time and compare it with the future motion state; The prediction of the future motion state is corrected and adjusted according to the comparison result.

[0011] In a second aspect, the present invention provides a longitudinal, lateral and vertical integrated control method, which adopts the following technical solution: The dynamic parameters of the vehicle are collected by sensors, and a multi-degree-of-freedom model of the vehicle in the longitudinal, lateral and vertical directions is established based on the dynamic parameters; Based on the dynamic parameters and the multi-degree-of-freedom model, the vehicle is subjected to hierarchical cooperative control; wherein the hierarchical cooperative control includes a first-layer control, a second-layer control, and a third-layer control; The first layer of control obtains the future motion state of the vehicle in the prediction time domain based on the dynamic parameters and the multi-degree-of-freedom model, and generates an optimal control instruction sequence based on the future motion state; The second layer of control performs integrated control of the vehicle based on the optimal control instruction sequence, and uniformly optimizes the longitudinal, lateral and vertical forces of the vehicle tires; The third level of control controls each actuator of the vehicle to perform corresponding actions according to the result of the optimized allocation.

[0012] Furthermore, in the above-mentioned longitudinal, lateral and vertical integrated control method, the first layer of control is used to control the overall stability of the vehicle; the second layer of control is used to distribute the grip between the tires and the ground; and the third layer of control is used to directly control the vehicle actuators.

[0013] In a third aspect, the present invention provides a longitudinal, lateral and vertical integrated control system, which adopts the following technical solution: A data acquisition module, at least used to collect dynamic parameters of the vehicle through sensors, and establish a multi-degree-of-freedom model of the vehicle in three directions, longitudinal, lateral and vertical, based on the dynamic parameters; The first-layer control module is at least used to obtain the future motion state of the vehicle in the prediction time domain based on the dynamic parameters and the multi-degree-of-freedom model, and generate an optimal control instruction sequence based on the future motion state; The second-layer control module is at least used to perform integrated control of the vehicle based on the optimal control instruction sequence and uniformly optimize the longitudinal, lateral and vertical forces of the vehicle tires; The third-layer control module is at least used to control each actuator of the vehicle to perform corresponding actions according to the result of the optimized allocation.

[0014] In a fourth aspect, the present invention provides a vehicle, which adopts the following technical solution: The vehicle is equipped with a longitudinal, lateral and vertical integrated control system as described in the third aspect above.

[0015] In a fifth aspect, the present invention provides a readable storage medium, which adopts the following technical solution: A readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, the longitudinal, lateral and vertical integrated control method as described in any one of the first aspect or the second aspect is implemented.

[0016] In summary, compared with the prior art, the present invention includes at least one of the following beneficial technical effects: The dynamic parameters of the vehicle are collected in real time through sensors, and a multi-degree-of-freedom model of the vehicle in the longitudinal, lateral and vertical directions is established based on these parameters. The model is then used to predict the future motion state of the vehicle and generate the optimal control instruction sequence to achieve integrated control of the vehicle. On this basis, the longitudinal, lateral and vertical forces of the tire are uniformly optimized and distributed, and the actions of each actuator are accurately controlled according to the optimization results. Compared with the prior art, the present invention significantly improves the vehicle's handling, stability and comfort by introducing a three-dimensional multi-degree-of-freedom model and an optimization allocation method, while effectively eliminating conflicts between chassis electronic systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0018] Figure 1 It is a flowchart of a specific embodiment of the longitudinal, transverse and vertical integrated control method of the present invention.

[0019] Figure 2 It is a flowchart of another specific embodiment of the longitudinal, lateral and vertical integrated control method of the present invention.

[0020] Figure 3 It is a flowchart of a specific embodiment of the longitudinal, transverse and vertical integrated control method of the present invention.

[0021] Figure 4 It is a structural schematic diagram of a specific embodiment of the longitudinal, transverse and vertical integrated control system of the present invention. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application. In addition, it should be understood that the specific implementation methods described herein are only used to illustrate and explain the present application, and are not used to limit the present application.

[0023] It should be noted that the description order of the following embodiments is not intended to limit the preferred order of the embodiments of the present application. In addition, in the following embodiments, the description of each embodiment has its own emphasis, and for parts not described in detail in one embodiment, reference can be made to the relevant description of other embodiments.

[0024] The method steps described in the embodiments of the present invention may be executed in the order described in the specific implementation manner, or the execution order of each step may be adjusted according to actual needs and on the premise that the technical problem can be solved, which will not be listed here one by one.

[0025] Reference Figure 1 The embodiment of the present invention provides a longitudinal, lateral and vertical integrated control method, including: S1, collecting dynamic parameters of the vehicle through sensors, and establishing a multi-degree-of-freedom model of the vehicle in the longitudinal, lateral and vertical directions based on the dynamic parameters; S2, obtaining the future motion state of the vehicle in the prediction time domain based on the dynamic parameters and the multi-degree-of-freedom model, and generating an optimal control instruction sequence based on the future motion state; S3, based on the optimal control instruction sequence, performing integrated control on the vehicle and uniformly optimizing the longitudinal, lateral and vertical forces of the vehicle tires; S4, controlling each actuator of the vehicle to perform corresponding actions according to the result of the optimization allocation.

[0026] Specifically, step S1 collects the dynamic parameters of the vehicle in real time through various sensors installed on the vehicle (such as speed sensors, acceleration sensors, steering wheel angle sensors, suspension sensors, brake pressure sensors, etc.). These dynamic parameters cover the motion state of the vehicle in the longitudinal, lateral and vertical directions, including the vehicle's speed, acceleration, steering angle, body height, roll angle, pitch angle and other information. Based on the collected dynamic parameters, a multi-degree-of-freedom dynamic model is established that can accurately reflect the motion state of the vehicle in three-dimensional space. The model contains the longitudinal, lateral and vertical motion equations of the vehicle, which can describe the dynamic behavior of the vehicle under different driving conditions and provide a mathematical basis for subsequent motion state prediction and control.

[0027] Step S2 first updates the current state of the vehicle based on the vehicle multi-degree-of-freedom model established in step S1 and the dynamic parameters collected in real time by sensors, and then predicts the vehicle's motion state in the short future by using a prediction algorithm (such as model predictive control MPC). In this process, the dynamic model combines the vehicle's current speed, acceleration, steering angle, body posture and other data to calculate the future motion trend of the vehicle in the longitudinal, lateral and vertical directions, and predicts the changes in its speed, pitch angle, roll angle and other parameters. Based on the prediction results, an optimal control instruction sequence is generated that enables the vehicle to maintain stability, controllability and comfort in the future time domain, ensuring that the best driving effect can be achieved under complex working conditions.

[0028] Step S3 performs integrated control of the longitudinal, lateral and vertical directions of the vehicle based on the optimal control instruction sequence generated in step S2. Specifically, by substituting the overall force of the vehicle and the longitudinal, lateral and vertical forces of each tire into the multi-degree-of-freedom dynamic model of the vehicle, the optimal force distribution of the tires in each direction is calculated. Next, a unified optimization distribution algorithm is used to reasonably distribute the vehicle's driving force, braking force, steering force and vertical adjustment force of the suspension system to ensure that the vehicle has the best grip and stability under different working conditions. Through this optimization distribution method, conflicts between different chassis electronic control systems (such as ABS, ESC, active suspension, etc.) can be effectively avoided, and their coordinated work can be enhanced to ensure the vehicle's handling and safety under complex road conditions.

[0029] Step S4 transmits the generated control instructions to various vehicle actuators, such as motors, brakes, steering systems, and suspension systems, based on the results of the optimization allocation in step S3. Specifically, the actuators perform corresponding actions according to the optimal instructions. For example, the motor accelerates or decelerates according to the optimized driving force instructions, the brake system adjusts the braking force to ensure stability, the steering system adjusts the wheel angle according to the steering force, and the suspension system optimizes the vehicle height or suspension hardness according to the vertical force. The precise actions of these actuators ensure that the vehicle's control targets in the longitudinal, lateral, and vertical directions are achieved, so that the vehicle's handling, safety, and comfort are improved under complex working conditions.

[0030] Based on this, the longitudinal, lateral and vertical integrated control method described in the embodiment of the present invention significantly improves the vehicle's handling, stability and comfort under complex road conditions, optimizes the collaboration between different chassis electronic control systems, eliminates system conflicts, and ensures that the vehicle's overall performance under sharp turns, acceleration, braking and other working conditions is more stable and efficient.

[0031] Furthermore, as an embodiment of the present invention, the future motion state of the vehicle in the prediction time domain is obtained based on the dynamic parameters and the multi-degree-of-freedom model, including: substituting the dynamic parameters collected in real time into the multi-degree-of-freedom model to calculate the vehicle state at the current moment; based on the current vehicle state, predicting the future motion state of the vehicle in the prediction time domain through dynamic equations and control algorithms.

[0032] Specifically, the sensors collect the dynamic parameters of the vehicle in real time, such as the vehicle's current speed (such as 100km / h), acceleration (such as 3m / s 2 ), steering wheel angle (such as 15 degrees), vehicle height (such as 150mm), and longitudinal and lateral forces of tires. These real-time parameters are then substituted into the vehicle's multi-degree-of-freedom dynamics model, which contains the vehicle's longitudinal, lateral, and vertical motion equations. For example, the Newton-Euler equation is used to calculate the vehicle's current state (such as longitudinal velocity, lateral acceleration, pitch angle, roll angle, etc.). Next, based on the current vehicle state, the dynamics equation and control algorithm, such as the model predictive control (MPC) algorithm, are used to predict the vehicle's motion state in the future time domain (such as within 2 seconds), and calculate future speed changes (such as deceleration from 100km / h to 90km / h), steering angle changes (such as increasing from 15 degrees to 30 degrees), and vehicle posture (such as a 2-degree change in pitch angle and a 3-degree change in roll angle).

[0033] Furthermore, based on the generated future motion state, an optimal control instruction sequence is generated through a model predictive control algorithm.

[0034] Specifically, first, based on the predicted future motion state of the vehicle, such as the vehicle's longitudinal speed is expected to slow down from 100km / h to 85km / h in the next 2 seconds, the roll angle increases from 2 degrees to 4 degrees, and the pitch angle decreases from 1 degree to 0 degrees. Through the model predictive control algorithm (MPC), these future motion states are used as input, combined with the vehicle's dynamic model, current road conditions and system constraints (such as the maximum tire grip is 8000 Newtons, and the suspension travel limit is 100mm), to calculate and generate the optimal control instruction sequence. Specifically, MPC will generate instructions, such as adjusting the motor power to 80%, the braking system applies a braking force of 2000 Newtons, the suspension system lowers the body height by 20mm within 1 second to reduce roll, and the steering system adjusts the front wheel angle to 25 degrees to ensure that the vehicle maintains stable, efficient handling and comfort in the next time period.

[0035] Model Predictive Control (MPC) is an advanced control algorithm that predicts the state changes of the system in the future by establishing a mathematical model of the system, and generates the optimal control instructions based on the prediction results. In the embodiment of the present invention, MPC can be used to collect current state data (such as the speed, acceleration, steering angle, etc. of the vehicle) in real time, combined with the multi-freedom model of the vehicle, to predict the future state changes in a certain time domain (such as the movement trajectory of the vehicle in the next few seconds). Based on the predicted results, MPC will generate a series of control instructions (such as acceleration, braking, and steering adjustments) to optimize the performance of the system and ensure that control objectives such as stability, safety, and comfort are met. The advantage of MPC is that it can handle systems with multiple variables and complex constraints, and is suitable for real-time optimization control.

[0036] Furthermore, as an implementation mode of the present invention, step S3, based on the optimal control instruction sequence, performs integrated control on the vehicle, and uniformly optimizes and distributes the longitudinal, lateral, and vertical forces of the vehicle tires, including: substituting the relationship between the vehicle resultant force and the four-wheel tire force into the multi-degree-of-freedom model to obtain the expected value of the vehicle kinematic control target; using a unified optimization allocation method to uniformly optimize and distribute the longitudinal force, lateral force, and vertical force of the tires to eliminate conflicts between different chassis electronic control systems.

[0037] Specifically, based on the generated optimal control instruction sequence, the combined force of the vehicle and the longitudinal, lateral and vertical forces of each tire are substituted into the multi-degree-of-freedom dynamic model of the vehicle to calculate the expected values ​​of the vehicle's kinematic control targets, such as longitudinal speed, lateral speed, vertical speed, pitch angle, roll angle and yaw angle. Then, a unified optimization allocation method is used to optimize the distribution of force for each tire to ensure that the longitudinal (acceleration or braking), lateral (steering) and vertical (suspension system) forces are reasonably distributed. For example, when making a sharp turn, a larger lateral force is calculated and allocated to the outer tire to reduce roll, while optimizing the response of the braking system and suspension system to ensure vehicle stability. Through this optimized allocation, the possible conflicts between various chassis electronic control systems (such as ABS, ESC, active suspension, etc.) can be effectively eliminated to ensure that they work together to improve the vehicle's handling and safety.

[0038] Further, as an embodiment of the present invention, refer to Figure 2 , the method further comprises: S5, monitoring the actual motion state of the vehicle in real time and comparing it with the future motion state; S6, correcting and adjusting the prediction of the future motion state according to the comparison result.

[0039] Specifically, in step S5, during the driving process of the vehicle, the current motion state of the vehicle is monitored in real time through sensors, including specific parameters such as longitudinal speed, lateral acceleration, steering angle, vehicle height, and tire stress. For example, the current longitudinal speed of the vehicle is 85km / h, the lateral acceleration is 0.5g, and the pitch angle is 1 degree. These real-time data will be compared with the future motion state predicted in step S2, and whether there is a deviation, such as the predicted speed is 90km / h, but the actual speed is 85km / h, or the roll angle deviates by 2 degrees.

[0040] Based on the comparison results in step S5, the cause of the deviation is analyzed and the future motion state prediction is dynamically adjusted. For example, if the actual speed of the vehicle is lower than the predicted value, it may be that the road friction is large or the braking force is insufficient. The future motion trajectory of the vehicle can be recalculated and corrected. Through the model predictive control (MPC) algorithm, the control instructions are updated in real time, the tire force distribution and vehicle posture adjustment are optimized, and the vehicle is always operated according to the optimal control strategy. The corrected control instructions may include increasing the motor output power, adjusting the suspension height, or more precise steering angle control, so as to ensure the stability and handling of the vehicle under complex working conditions.

[0041] By monitoring the actual motion state of the vehicle in real time and comparing it with the predicted state, the deviation from the predicted result during actual driving can be effectively detected, and the control instructions can be dynamically adjusted and corrected according to the comparison results. This process significantly improves the accuracy and response speed of the vehicle control system, ensuring that the vehicle maintains higher stability and controllability under complex working conditions. At the same time, the adaptive ability of the control algorithm is enhanced, and it can be adjusted in real time according to changes in actual road conditions and driving environment, thereby optimizing driving safety, comfort and energy efficiency.

[0042] Reference Figure 3 The embodiment of the present invention further provides a longitudinal, lateral and vertical integrated control method, including: A1, collecting dynamic parameters of the vehicle through sensors, and establishing a multi-degree-of-freedom model of the vehicle in the longitudinal, lateral and vertical directions based on the dynamic parameters; A2, performing hierarchical collaborative control on the vehicle based on the dynamic parameters and the multi-degree-of-freedom model; wherein the hierarchical collaborative control includes a first layer control, a second layer control and a third layer control.

[0043] Specifically, the first level of control is based on the dynamic parameters and multi-degree-of-freedom model to obtain the future motion state of the vehicle in the predicted time domain, and based on the future motion state, generates an optimal control instruction sequence; the first level of control is to predict the motion state of the vehicle in the future time domain based on the dynamic parameters and the dynamic model, and generate the optimal control instruction sequence to ensure the driving stability of the vehicle under complex working conditions.

[0044] The second level of control performs integrated control of the vehicle based on the optimal control instruction sequence, and uniformly optimizes the distribution of the longitudinal, lateral and vertical forces of the vehicle tires; the second level of control utilizes the generated optimal control instructions to optimize the distribution of the longitudinal force, lateral force and vertical force of the vehicle tires, ensure the balance of force in the three-dimensional movement of the vehicle, and avoid conflicts between different systems (such as braking, steering, suspension, etc.).

[0045] The third level of control controls the vehicle's actuators to perform corresponding actions based on the results of the optimization allocation. The third level of control adjusts the operation of each actuator by executing these optimization instructions, such as adjusting motor power, braking force, steering angle, and suspension height, to ensure that the actual movement state of the vehicle meets expectations.

[0046] In this control method, the first level of control is responsible for monitoring and adjusting the overall stability of the vehicle to ensure that the vehicle remains balanced and does not lose control under various driving conditions, such as by adjusting the speed, steering and posture to maintain stable driving. The second level of control is responsible for allocating the grip between the tires and the ground, and according to the longitudinal, lateral and vertical forces of each tire, ensures that the vehicle can obtain the best traction and grip when accelerating, braking or turning to avoid tire slippage or loss of control. The third level of control directly manipulates the vehicle's actuators, such as motors, brakes, steering systems and suspensions, and adjusts the physical movements of the vehicle by accurately executing control instructions to ensure the realization of the overall control goals.

[0047] The embodiment of the present invention also discloses a longitudinal, lateral and vertical integrated control system.

[0048] Reference Figure 4 The longitudinal, lateral and vertical integrated control system includes a data acquisition module 1, a first-layer control module 2, a second-layer control module 3 and a third-layer control module 4.

[0049] The data acquisition module 1 is connected to various sensors of the vehicle to collect the dynamic parameters of the vehicle in real time. These parameters may include the longitudinal speed, lateral acceleration, steering angle, suspension height, brake pressure, tire force, etc. of the vehicle. The data acquisition module 1 inputs these real-time collected parameters into the system and establishes a multi-degree-of-freedom dynamic model of the vehicle in the longitudinal, lateral and vertical directions based on these data. This model can accurately describe the movement of the vehicle in three-dimensional space, and serves as the basis for subsequent prediction of the future movement state of the vehicle and generation of control instructions. By continuously acquiring and updating dynamic parameters, the data acquisition module ensures that the control system can accurately reflect the actual state of the vehicle and support precise integrated control.

[0050] Based on the real-time dynamic parameters and multi-degree-of-freedom model received from the data acquisition module 1, the first-layer control module 2 uses the model predictive control (MPC) algorithm to first calculate and update the current state information of the vehicle (such as current speed, acceleration, pitch angle, roll angle, etc.). Then, based on the current state of the vehicle, the vehicle's motion state in the future time domain is predicted, such as longitudinal speed changes, steering angles, body postures, etc. in the next few seconds. Based on the prediction results, the first-layer control module 2 generates the optimal control command sequence, which may include acceleration, braking, steering angle adjustment, and suspension adjustment, etc., to ensure that the vehicle can maintain stability, controllability, and comfort during future driving.

[0051] The second-layer control module 3 is based on the optimal control instruction sequence generated by the first-layer control module 2. The second-layer control module 3 is responsible for integrated control of the longitudinal, lateral and vertical movements of the vehicle. The second-layer control module 3 calculates and optimizes the force distribution of each tire by substituting the combined force of the vehicle and the longitudinal, lateral and vertical forces of each tire into the multi-degree-of-freedom dynamic model to ensure that the grip of each tire is reasonably distributed. For example, when turning, the outer tire may need a larger lateral force to maintain the stability of the vehicle, while the suspension system needs to be adjusted according to the vertical force. By uniformly optimizing the longitudinal, lateral and vertical forces of the tires, the second-layer control module 3 ensures the stability, handling and safety of the vehicle under different working conditions, and avoids conflicts between different chassis control systems (such as ABS, ESC, etc.).

[0052] The third-layer control module 4 directly controls the various actuators of the vehicle according to the distribution results of the longitudinal, lateral and vertical forces of the tires optimized by the second-layer control module 3 to ensure that these instructions are accurately executed. Specifically, the third-layer control module 4 adjusts the acceleration, braking force, steering angle and suspension height of the vehicle by sending control signals to actuators such as motors, brakes, steering systems and suspension systems. For example, when the vehicle needs to turn, the steering system will adjust the angle of the front wheels according to the optimal instructions, while the suspension system adjusts the height of the vehicle body according to the vertical force, and the brakes distribute the braking force as needed. Through the precise control of these actuators, the third-layer control module 4 ensures that the actual motion state of the vehicle is consistent with the predicted target, thereby improving the stability, handling and comfort of the vehicle.

[0053] The longitudinal, lateral and vertical integrated control system described in the embodiment of the present invention realizes precise control of the vehicle in the longitudinal, lateral and vertical directions through the collaborative work of various modules. First, the system can establish an accurate multi-degree-of-freedom model by collecting dynamic parameters in real time, and provide comprehensive vehicle dynamic information. Secondly, based on the predictive control and optimal allocation of the model, the system can reasonably allocate the longitudinal, lateral and vertical forces of the tires to ensure that the vehicle maintains stability and controllability under different road conditions and working conditions. In addition, through the precise control of each actuator, the system effectively reduces the conflict between the various electronic control systems of the chassis (such as ABS, ESC, etc.), improves the overall collaborative work efficiency, and thus significantly improves the safety, comfort and responsiveness of the vehicle.

[0054] An embodiment of the present invention further discloses a vehicle, wherein the vehicle is equipped with a longitudinal, lateral and vertical integrated control system as described in the above embodiment.

[0055] A vehicle equipped with an integrated longitudinal, lateral and vertical control system can collect and analyze its longitudinal, lateral and vertical dynamic parameters in real time, accurately predict future motion states through a multi-degree-of-freedom model, and generate optimal control instructions. The control system equipped on the vehicle can optimize the distribution of longitudinal, lateral and vertical forces of the tires, and then achieve vehicle stability, controllability and comfort by precisely controlling actuators (such as motors, brakes, steering systems and suspension systems). Compared with traditional vehicles, this configuration can effectively improve the driving experience under complex road conditions, improve safety and driving efficiency.

[0056] The embodiment of the present invention also discloses a readable storage medium.

[0057] A readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the longitudinal, lateral and vertical integrated control method described in any one of the above embodiments. Computer-readable storage media may include: any entity or device capable of carrying a computer program, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), and a software distribution medium, etc. The computer program includes a computer program code. The computer program code may be in source code form, object code form, an executable file or some intermediate form, etc. The computer-readable storage medium may include: any entity or device capable of carrying a computer program code, a recording medium, a USB flash drive, a mobile hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), and a software distribution medium, etc.

[0058] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0059] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, apparatus or device (such as a computer-based system, a system including a processing module, or other system that can fetch instructions from an instruction execution system, apparatus or device and execute instructions), or used in combination with these instruction execution systems, apparatuses or devices.

[0060] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A longitudinal, lateral and vertical integrated control method, characterized in that: include: The dynamic parameters of the vehicle are collected by sensors, and a multi-degree-of-freedom model of the vehicle in the longitudinal, lateral and vertical directions is established based on the dynamic parameters; Based on the dynamic parameters and the multi-degree-of-freedom model, obtaining the future motion state of the vehicle in the prediction time domain, and generating an optimal control instruction sequence based on the future motion state; Based on the optimal control instruction sequence, the vehicle is integratedly controlled to uniformly optimize the longitudinal, lateral and vertical forces of the vehicle tires; According to the result of the optimization allocation, each actuator of the vehicle is controlled to perform corresponding actions.

2. The longitudinal, lateral and vertical integrated control method according to claim 1, characterized in that: The obtaining of the future motion state of the vehicle in the prediction time domain based on the dynamic parameters and the multi-degree-of-freedom model includes: The dynamic parameters collected in real time are substituted into the multi-degree-of-freedom model to calculate the vehicle status at the current moment; Based on the current vehicle state, the future motion state of the vehicle within the prediction time domain is predicted through dynamic equations and control algorithms.

3. The longitudinal, lateral and vertical integrated control method according to claim 2 is characterized in that: The optimal control instruction sequence is generated by a model predictive control algorithm.

4. The longitudinal, lateral and vertical integrated control method according to claim 1, characterized in that: The method of performing integrated control on the vehicle based on the optimal control instruction sequence and uniformly optimizing the longitudinal, lateral and vertical forces of the vehicle tires includes: Substituting the relationship between the vehicle resultant force and the four-wheel tire force into the multi-degree-of-freedom model to obtain the expected value of the vehicle kinematic control target; A unified optimization distribution method is adopted to uniformly optimize the distribution of the longitudinal force, lateral force and vertical force of the tire to eliminate the conflict between different chassis electronic control systems.

5. The longitudinal, lateral and vertical integrated control method according to claim 4 is characterized in that: The expected values ​​include longitudinal velocity, lateral velocity, vertical velocity, pitch angle, roll angle and yaw angle.

6. The longitudinal, lateral and vertical integrated control method according to claim 1, characterized in that: The method further comprises: Monitor the actual motion state of the vehicle in real time and compare it with the future motion state; The prediction of the future motion state is corrected and adjusted according to the comparison result.

7. A longitudinal, lateral and vertical integrated control method, characterized in that: The method comprises: The dynamic parameters of the vehicle are collected by sensors, and a multi-degree-of-freedom model of the vehicle in the longitudinal, lateral and vertical directions is established based on the dynamic parameters; Based on the dynamic parameters and the multi-degree-of-freedom model, the vehicle is subjected to hierarchical cooperative control; wherein the hierarchical cooperative control includes a first-layer control, a second-layer control, and a third-layer control; The first layer of control obtains the future motion state of the vehicle in the prediction time domain based on the dynamic parameters and the multi-degree-of-freedom model, and generates an optimal control instruction sequence based on the future motion state; The second layer of control performs integrated control of the vehicle based on the optimal control instruction sequence, and uniformly optimizes the longitudinal, lateral and vertical forces of the vehicle tires; The third level of control controls each actuator of the vehicle to perform corresponding actions according to the result of the optimized allocation.

8. The longitudinal, lateral and vertical integrated control method according to claim 7 is characterized in that: The first level of control is used to control the overall stability of the vehicle; the second level of control is used to distribute the grip between the tires and the ground; and the third level of control is used to directly control the vehicle actuators.

9. A longitudinal, lateral and vertical integrated control system, characterized in that: include: A data acquisition module, at least used to collect dynamic parameters of the vehicle through sensors, and establish a multi-degree-of-freedom model of the vehicle in three directions, longitudinal, lateral and vertical, based on the dynamic parameters; The first-layer control module is at least used to obtain the future motion state of the vehicle in the prediction time domain based on the dynamic parameters and the multi-degree-of-freedom model, and generate an optimal control instruction sequence based on the future motion state; The second-layer control module is at least used to perform integrated control of the vehicle based on the optimal control instruction sequence and uniformly optimize the longitudinal, lateral and vertical forces of the vehicle tires; The third-layer control module is at least used to control each actuator of the vehicle to perform corresponding actions according to the result of the optimized allocation.

10. A vehicle, characterized in that: The vehicle is equipped with the longitudinal, lateral and vertical integrated control system as claimed in claim 9.

11. A readable storage medium, characterized in that: The readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, the longitudinal, lateral and vertical integrated control method as described in any one of claims 1-6 or 7-8 is implemented.

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