Vehicle body posture control method and device, computer readable storage medium, electronic device, and computer program product

Abstract

The present application discloses a vehicle body posture control method and device, a computer-readable storage medium, an electronic device, and a computer program product. The vehicle body posture control method includes: determining the current driving scene of the vehicle according to the road condition information of the road where the vehicle is located, the state information of the vehicle, and the operation instructions of the target object; determining the current driving mode of the vehicle in response to the selection instruction of the target object; determining the target vehicle body posture of the vehicle according to the driving scene and the driving mode; and when the current vehicle body posture of the vehicle does not match the target vehicle body posture, controlling the actions of multiple actuators of the vehicle so that the adjusted current vehicle body posture matches the target vehicle body posture. By accurately identifying the driving scene and intelligently matching the driving mode, the target vehicle body posture of the vehicle can be dynamically adjusted to ensure that the vehicle can maintain optimal controllability and stability under various conditions.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of vehicle control technology, and more specifically, to a vehicle body posture control method and device, a computer-readable storage medium, an electronic device, and a computer program product. Background Art

[0002] With the rapid development of the pure electric vehicle industry, users have higher and higher performance requirements for pure electric vehicles. The key factor affecting the performance of pure electric vehicles is the chassis of the vehicle. During the driving process of pure electric vehicles, especially electric four-wheel drive vehicles, the lateral, longitudinal and vertical control of the vehicle has a particularly important impact on the body posture.

[0003] In related technologies, the control of vehicle motion often focuses on a single dimension. For example, the drive control system controls the acceleration of the vehicle, the brake control system controls the deceleration and stopping of the vehicle, the steering system controls the steering of the vehicle, and the suspension system controls the vertical motion of the vehicle.

[0004] However, the vehicle control method in the related art cannot keep the vehicle in a good posture in different driving scenarios and driving modes. Summary of the invention

[0005] Embodiments of the present application provide a vehicle body posture control method and device, a computer-readable storage medium, an electronic device, and a computer program product.

[0006] According to one aspect of an embodiment of the present application, a vehicle body posture control method is provided, the method comprising: determining a current driving scene of the vehicle based on road condition information of a road on which the vehicle is located, status information of the vehicle, and operation instructions of a target object; determining a current driving mode of the vehicle in response to a selection instruction of a target object; determining a target vehicle body posture of the vehicle based on the driving scene and the driving mode; and, when the current vehicle body posture of the vehicle does not match the target body posture, controlling the actions of multiple actuators of the vehicle so that the adjusted current vehicle body posture matches the target body posture.

[0007] In an exemplary embodiment, determining the target body posture of the vehicle based on the driving scenario and the driving mode includes: determining the constraint boundary conditions of the vehicle based on physical parameter information of the vehicle; determining the vehicle motion state expected by the target object based on the operation instructions of the target object; determining the target vehicle motion state based on the driving scenario and the vehicle motion state expected by the target object, wherein the target vehicle motion state satisfies the constraint boundary conditions; determining the target body posture of the vehicle based on the target vehicle motion state and the driving mode.

[0008] In an exemplary embodiment, when the current body posture of the vehicle does not match the target body posture, controlling multiple actuator actions of the vehicle includes: acquiring the current body posture of the vehicle; when the current body posture of the vehicle does not match the target body posture, determining the adjustment requirement of the body posture; determining the control target type of the body posture according to the driving scenario and the adjustment requirement of the body posture; and controlling corresponding multiple actuator actions according to the control target type of the body posture.

[0009] In an exemplary embodiment, the control target type according to the vehicle body posture controls the corresponding multiple actuator actions, including: determining multiple corresponding target actuators according to the control target type; determining the priority order of the multiple target actuator actions according to the driving mode; and controlling the multiple target actuator actions according to the priority order to achieve the control target corresponding to the control target type.

[0010] In an exemplary embodiment, the method further includes: determining response characteristics of each actuator of the vehicle based on design parameters of each actuator of the vehicle, wherein the response characteristics include the adjustment amplitude of the actuator on the vehicle body posture, the response speed of the actuator, and the degree of influence of the actuator on the vehicle comfort when the actuator is in action; and determining the priority order of multiple actuator actions in each driving mode based on the response characteristics of each actuator.

[0011] In an exemplary embodiment, controlling the actions of multiple target actuators according to the priority order to achieve the control target corresponding to the control target type includes: determining control strategies for the multiple target actuators according to the priority order, wherein the control strategies include at least one of the following: lateral control strategy, longitudinal control strategy, and vertical control strategy of the vehicle; determining control parameters of the multiple target actuators according to the control target corresponding to the control target type; and controlling the multiple target actuators to adjust to corresponding control parameters according to the control strategies to achieve the control target corresponding to the control target type.

[0012] In an exemplary embodiment, determining the current driving scene of the vehicle based on traffic condition information of the road on which the vehicle is located, status information of the vehicle, and operating instructions of a target object includes: determining the current scene features of the vehicle based on traffic condition information of the road on which the vehicle is located, status information of the vehicle, and operating instructions of a target object; using the current scene features of the vehicle to perform matching in a preset scene library, and determining the scene with the highest matching degree with the current scene features of the vehicle as the current driving scene of the vehicle.

[0013] According to another aspect of the embodiment of the present application, there is also provided a vehicle body posture control device, comprising:

[0014] A scene determination module, used to determine the current driving scene of the vehicle according to the road condition information of the road where the vehicle is located, the state information of the vehicle and the operation instruction of the target object;

[0015] a mode determination module, for determining a current driving mode of the vehicle in response to a selection instruction of a target object;

[0016] A posture determination module, used to determine a target body posture of the vehicle according to the driving scene and the driving mode;

[0017] The posture control module is used to control the actions of multiple actuators of the vehicle when the current body posture of the vehicle does not match the target body posture, so that the current body posture of the vehicle after adjustment matches the target body posture.

[0018] According to another aspect of the embodiment of the present application, a computer-readable storage medium is provided, in which a computer program is stored, wherein the computer program is configured to execute the above-mentioned vehicle body posture control method when running.

[0019] According to another aspect of an embodiment of the present application, an electronic device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the vehicle body posture control method through the computer program.

[0020] According to another aspect of the embodiments of the present application, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps of the method described in each embodiment of the present application are implemented.

[0021] The above-mentioned vehicle body posture control method first determines the current driving scene of the vehicle according to the road condition information of the road where the vehicle is located, the status information of the vehicle and the operation instructions of the target object, so as to facilitate the subsequent accurate control of the vehicle body posture. In response to the selection instruction of the target object, the current driving mode of the vehicle is determined, so as to obtain the driving requirements of the target object, so that the subsequent control of the vehicle body posture can meet the requirements of the target object. According to the driving scene and driving mode, the target body posture of the vehicle is determined, so as to obtain the optimal body posture that best meets the current situation, and the body posture can ensure the vehicle's controllability, stability and comfort. When the current body posture of the vehicle does not match the target body posture, the multiple actuators of the vehicle are controlled to act so that the adjusted current body posture of the vehicle matches the target body posture, thereby realizing the control of the body posture. In summary, the method of the present application can dynamically adjust the target body posture of the vehicle by accurately identifying the driving scene and intelligently matching the driving mode, ensuring that the vehicle can maintain the optimal control performance and stability under various driving conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] 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.

[0023] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0024] Figure 1 It is a hardware structure block diagram of the vehicle terminal of the vehicle body posture control method of the embodiment of the present application;

[0025] Figure 2 is a flow chart of a method for controlling a vehicle body posture according to an embodiment of the present application;

[0026] Figure 3 is a second flow chart of a method for controlling a vehicle body posture according to an embodiment of the present application;

[0027] Figure 4 is a flowchart of a vehicle body posture control method according to an embodiment of the present application;

[0028] Figure 5 is a fourth flow chart of a method for controlling a vehicle body posture according to an embodiment of the present application;

[0029] Figure 6 is a fifth flow chart of a method for controlling a vehicle body posture according to an embodiment of the present application;

[0030] Figure 7 is a sixth flow chart of a method for controlling a vehicle body posture according to an embodiment of the present application;

[0031] Figure 8 is a flowchart of a vehicle body posture control method according to an embodiment of the present application;

[0032] Fig. 9 is a schematic diagram of a coordinated control architecture of a vehicle controller according to an embodiment of the present application;

[0033] Fig.10 It is a structural block diagram of an optional vehicle body posture control device according to an embodiment of the present application. DETAILED DESCRIPTION

[0034] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution 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, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0035] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, the process, method, system, product or equipment comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0036] The method embodiments provided in the embodiments of the present application can be executed in a vehicle-mounted terminal or a similar computing device. Taking running on a vehicle-mounted terminal as an example, Figure 1 1 is a hardware structure block diagram of a computer terminal of the vehicle body posture control method of the embodiment of the present application. Figure 1 As shown, the computer terminal may include one or more ( Figure 1Only one is shown in the figure) a processor 102 (the processor 102 may include but is not limited to a microprocessor (Microprocessor Unit, referred to as MPU) or a programmable logic device (Programmable logic device, referred to as PLD)) and a memory 104 for storing data. In an exemplary embodiment, the vehicle terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the vehicle-mounted terminal. Figure 1 More or fewer components as shown, or with Figure 1 Equivalent functions or comparisons shown Figure 1 A different configuration with more features is shown.

[0037] The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the vehicle body posture control method in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, that is, to implement the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the vehicle-mounted terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0038] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the vehicle terminal. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0039] The control systems for controlling the lateral, longitudinal and vertical directions of the vehicle in the related technology are usually designed independently, and each optimizes its own function, but ignores the mutual influence and coupling relationship between the dimensions of vehicle movement in different driving scenarios and modes. In scenarios such as high-speed cornering, emergency obstacle avoidance, and driving on complex roads (such as split roads and butted roads), the vehicle's yaw, roll, pitch and vertical translation control requirements will appear at the same time, and there may be conflicts between these requirements. For example, in emergency obstacle avoidance, the vehicle requires a large yaw moment to change direction quickly, but at the same time, the suspension system may need to respond quickly to suppress roll. If these control requirements cannot be properly coordinated, the vehicle posture may be unstable and even affect the vehicle's driving safety and the driver's driving experience. In addition, different driving modes, such as economic mode, sports mode, off-road mode, etc., have different performance requirements for vehicles. For example, in economic mode, the vehicle's energy efficiency and comfort are the main considerations; in sports mode, the vehicle's handling and stability are more critical. If the systems cannot adapt quickly and make corresponding adjustments when switching driving modes, it may also lead to poor performance of the vehicle in different modes and fail to meet the user's expectations for vehicle performance in a specific driving mode. In summary, the vehicle motion control system in the prior art is insufficient in processing multi-dimensional control requirements and adapting to different driving scenarios and modes. Especially when simultaneous control of the horizontal, longitudinal and vertical directions is required, it is impossible to effectively coordinate the work of the actuators and it is difficult to keep the vehicle in a good posture, thus affecting the overall driving performance and safety of the vehicle.

[0040] Based on the above technical problems, this embodiment provides a vehicle body posture control method, which is applied to a vehicle-mounted terminal. Figure 2 : is a flow chart of an optional vehicle body posture control method according to an embodiment of the present application, the process includes the following steps S200-S230:

[0041] Step S200, determining the current driving scene of the vehicle based on the road condition information of the vehicle, the vehicle status information and the operation instruction of the target object.

[0042] Specifically, the driving scenario is determined based on the road condition information of the vehicle, the real-time status information of the vehicle itself, and the operation instructions of the target object (driver or autonomous driving system). This process is the basis for realizing intelligent control and can ensure that the control strategy is consistent with the actual driving needs.

[0043] For example, road condition information collection: using on-board sensors such as cameras, radars, and lidars to detect road conditions in real time, including road material (such as dry, wet, ice, snow), obstacle distribution, road geometry (such as curves, slopes), etc. Vehicle status monitoring: continuously monitoring vehicle speed, acceleration, steering angle, brake pressure, suspension status, battery power, motor temperature and other indicators to evaluate the dynamic performance and health of the vehicle. Operation instruction analysis: analyzing the driver's throttle, brake, steering wheel input, and the control instructions of the autonomous driving system to understand the driver's control intentions and the system's behavioral goals. Scene recognition algorithm: using machine learning or deep learning algorithms, the collected road condition information, vehicle status and operation instructions are input into the trained model to output the most likely driving scenario at the moment, such as urban driving, high-speed driving, emergency obstacle avoidance, driving on slippery roads, etc.

[0044] Step S210, in response to the selection instruction of the target object, determining the current driving mode of the vehicle.

[0045] Specifically, the choice of driving mode reflects the target object's preference for vehicle performance, such as economy mode, sports mode, comfort mode, etc. This step ensures that the subsequent control strategy can meet the needs of the target object.

[0046] For example, driving mode recognition: receiving the target object's mode selection instructions through the human-computer interaction interface or the vehicle's internal sensors to understand the driver's specific needs. Mode matching logic: establishing a mapping table between driving modes and vehicle performance parameters. When the target object selects a certain mode, the system automatically adjusts the vehicle's response characteristics according to the mapping table, such as adjusting power output, steering sensitivity, suspension hardness, etc. Mode switching mechanism: designing a smooth transition strategy for mode switching to avoid sudden changes in vehicle performance when switching modes, and ensure driving safety and comfort.

[0047] Step S220, determining a target body posture of the vehicle according to the driving scene and the driving mode.

[0048] Specifically, once the driving scenario and mode are determined, the system needs to calculate the optimal vehicle body posture that suits the current situation to improve the vehicle's handling, stability and comfort.

[0049] Exemplarily, multi-degree-of-freedom model application: Based on driving scenarios and modes, the multi-degree-of-freedom vehicle model is used to calculate the ideal yaw, roll, pitch and vertical translation posture that the vehicle should maintain. Control target setting: Set specific target posture parameters, such as target yaw angular velocity, target roll angle, etc. These parameters reflect the optimal performance that the vehicle should achieve in the current scenario. Constraint boundary determination: According to the physical limitations and safety requirements of the vehicle, determine the feasible range of the target body posture to avoid control instructions exceeding the capabilities of the actuator.

[0050] Step S230, when the current body posture of the vehicle does not match the target body posture, multiple actuators of the vehicle are controlled to act so that the current body posture of the vehicle after adjustment matches the target body posture.

[0051] Specifically, when a deviation between the actual posture of the vehicle and the target posture is detected, the method of the present invention will intelligently control multiple actuators (such as a drive motor, a braking system, a steering system, and a suspension system) to adjust the vehicle posture to achieve the target state.

[0052] Exemplarily, posture deviation detection: monitor the vehicle's actual yaw rate, sideslip angle, roll angle, pitch angle, vertical displacement and other parameters through sensors, compare them with the target posture, and detect deviations. Actuator coordination control: formulate coordination control rules based on the control target type and the selected actuator, optimize the torque distribution between actuators, and ensure rapid adjustment of the vehicle's posture. Control instruction generation and execution: generate and execute specific control instructions for each actuator based on the size and direction of the deviation, such as adjusting the drive torque, braking force, steering angle, and suspension stiffness. Fault-tolerant redundancy mechanism: when an actuator fails, the system will automatically dispatch other healthy actuators to replace the function of the failed actuator, or downgrade when necessary to ensure vehicle safety.

[0053] In this embodiment, the current driving scene of the vehicle is first determined according to the road condition information of the road where the vehicle is located, the state information of the vehicle and the operation instructions of the target object, so as to facilitate the subsequent accurate control of the vehicle's body posture. In response to the selection instruction of the target object, the current driving mode of the vehicle is determined, so as to obtain the driving requirements of the target object, so that the subsequent control of the vehicle's body posture can meet the requirements of the target object. According to the driving scene and driving mode, the target body posture of the vehicle is determined, so as to obtain the optimal body posture that best meets the current situation, and the body posture can ensure the vehicle's controllability, stability and comfort. In the case that the current body posture of the vehicle does not match the target body posture, the multiple actuators of the vehicle are controlled to act so that the adjusted current body posture of the vehicle matches the target body posture, thereby realizing the control of the body posture. In summary, the method of the present application can dynamically adjust the target body posture of the vehicle by accurately identifying the driving scene and intelligently matching the driving mode, ensuring that the vehicle can maintain the optimal control performance and stability under various driving conditions.

[0054] In one embodiment, Figure 3 As shown, step S220 determines the target body posture of the vehicle according to the driving scene and driving mode. It includes: steps S300-S330. Among them:

[0055] Step S300, determining the constraint boundary conditions of the vehicle according to the physical parameter information of the vehicle.

[0056] Specifically, the constraint boundary conditions are set based on the physical parameter information of the vehicle, which defines the range in which the vehicle can operate safely and efficiently in different scenarios, ensuring that the control instructions do not exceed the capabilities of the actuator or cause vehicle instability.

[0057] Exemplarily, vehicle physical parameter evaluation: collect and analyze the physical parameters of the vehicle, such as maximum yaw rate, roll angle limit, pitch angle limit, maximum torque of the drive motor, maximum pressure of the braking system, maximum travel and stiffness range of the suspension system, etc. Dynamic constraint boundary calculation: combine real-time vehicle status information (such as speed, acceleration, tire contact force, etc.) and road information (such as slope, curve curvature, road adhesion coefficient, etc.) to calculate the dynamic constraint boundary of the vehicle in the current scenario to reflect the physical capabilities and safety requirements of the vehicle. Constraint boundary adjustment strategy: formulate a constraint boundary adjustment strategy, dynamically adjust the constraint boundary according to the diagnostic information of the actuator (such as fault status, performance degradation, etc.) and the overall energy management requirements of the vehicle to ensure that the vehicle can drive safely under various conditions.

[0058] Step S310, determining the vehicle motion state expected by the target object according to the operation instruction of the target object.

[0059] Specifically, the vehicle motion state expected by the target object reflects the driver's control intention or the driving strategy of the autonomous driving system, and is the basis for adjusting the vehicle posture and actuator control.

[0060] Exemplarily, operation instruction analysis: through the human-computer interaction interface of the vehicle (such as steering wheel, accelerator pedal, brake pedal) or the input of the automatic driving system, the operation instructions of the target object are analyzed to determine its requirements for the vehicle's motion state, such as acceleration, steering, braking, etc. Driving intention recognition: using machine learning algorithms, according to a series of operation instructions of the target object, its driving style (such as aggressive, conservative) and driving intention (such as emergency obstacle avoidance, comfortable driving) are identified. Motion state prediction: based on driving intention and operation instructions, combined with the physical characteristics of the vehicle, the target object's expected vehicle motion state is predicted, including parameters such as expected yaw rate, sideslip angle, roll angle, pitch angle and vertical displacement. The expected yaw rate of the vehicle is calculated based on the multi-degree-of-freedom vehicle model and driving mode, for example, the expected yaw rate of the vehicle is obtained by combining the steering wheel angle, vehicle speed, based on the two-degree-of-freedom model of the vehicle, and considering the road adhesion limit.

[0061] Step S320, determining the target vehicle motion state according to the driving scene and the target object's expected vehicle motion state.

[0062] Among them, the motion state of the target vehicle satisfies the constraint boundary conditions.

[0063] Specifically, the target vehicle motion state is the vehicle motion state that matches the current driving scenario based on consideration of constraint boundary conditions and target object expectations, ensuring that the vehicle can respond to driving intentions safely and efficiently.

[0064] Exemplarily, scene-motion state matching: According to the recognition results of the driving scene (such as urban traffic, high-speed driving, and slippery roads), match it with the expected motion state of the target object to determine the optimal motion state that meets the constraint boundary conditions in the current scene. Motion state optimization: Using a multi-objective optimization algorithm, comprehensively consider the physical parameters of the vehicle, the expectations of the target object, and the road constraints to optimize the motion state of the target vehicle to ensure that while meeting the needs of the target object, the vehicle operates in a safe and energy-efficient range. Control target screening: Extract specific control targets from the motion state of the target vehicle, such as yaw control, roll suppression, pitch control, and vertical translation control. These control targets will become the basis for subsequent coordinated control.

[0065] Step S330, determining a target vehicle body posture according to the target vehicle motion state and driving mode.

[0066] Specifically, the target body posture is determined based on the target vehicle motion state and driving mode, which guides the control strategy of the actuator to achieve the best performance of the vehicle in a specific scenario.

[0067] Exemplarily, driving mode analysis: according to the driving mode selected by the target object (such as economy mode, sports mode, off-road mode), analyze the priority of vehicle performance in this mode, such as power, handling stability, comfort, etc. Target posture setting: Based on the analysis results of the target vehicle's motion state and driving mode, set the vehicle's target posture parameters, such as target yaw rate, target roll angle, target pitch angle and target vertical displacement, to ensure that the vehicle posture matches the driving intention and scenario requirements. Coordinated control strategy: Based on the target vehicle body posture and the diagnostic information of the actuator, design a coordinated control strategy to ensure that each actuator (such as drive, braking, steering, suspension) can work together efficiently to achieve the target posture, while considering fault-tolerant redundancy to deal with possible failures of the actuator.

[0068] In this embodiment, by accurately evaluating the physical parameter information of the vehicle, reasonable constraint boundary conditions are set to ensure that the vehicle can operate safely in any driving scenario. At the same time, by parsing the operation instructions of the target object and identifying its driving intention, the target vehicle motion state can be intelligently determined, and combined with the driving mode, the target vehicle body posture that meets the needs of the target object and the scene requirements is set. This series of processes not only optimizes the vehicle's handling performance and improves the driving experience, but also effectively avoids conflicts between actuators and improves the system's fault tolerance and safety.

[0069] In one embodiment, Figure 4 As shown, step S230, when the current body posture of the vehicle does not match the target body posture, controls the actions of multiple actuators of the vehicle. It includes: steps S400-S430. Among them:

[0070] Step S400, obtaining the current body posture of the vehicle.

[0071] Specifically, the current body posture of the vehicle refers to the actual yaw, roll, pitch and vertical translation states of the vehicle during driving, which is the basic information for posture adjustment and control.

[0072] For example, sensor data acquisition: using inertial measurement unit (IMU), wheel speed sensor, lateral acceleration sensor, longitudinal acceleration sensor, roll sensor, pitch sensor, etc., to monitor the vehicle's state parameters such as yaw rate, roll angle, pitch angle and vertical displacement in real time. Data fusion and processing: through sensor data fusion algorithms, such as Kalman filtering or complementary filtering, the collected data is processed to eliminate noise interference and obtain an accurate estimate of the vehicle's current body posture. Vehicle state estimation: using vehicle state estimation algorithms, such as state estimation based on multi-degree-of-freedom vehicle models, combined with real-time monitored vehicle parameters (such as vehicle speed, acceleration, steering angle, etc.), the current posture information of the vehicle is further refined to ensure the accuracy of control instructions.

[0073] Step S410: When the current body posture of the vehicle does not match the target body posture, the adjustment requirement of the body posture is determined.

[0074] Specifically, after comparing the current vehicle body posture with the target body posture, if there is a deviation, it is necessary to determine the specific adjustment requirements to provide a basis for subsequent control strategies.

[0075] Exemplarily, posture deviation calculation: compare the acquired vehicle's current posture information with the target posture, and calculate the yaw rate deviation, roll angle deviation, pitch angle deviation, and vertical displacement deviation. Adjustment requirement level classification: according to the size and urgency of the deviation, the adjustment requirements are divided into different levels, such as slight adjustment, medium adjustment, and emergency adjustment, to determine the actuator's response level and control strategy. Control requirement priority judgment: based on the driving scenario and driving mode, judge the priority of the adjustment requirement. For example, in an emergency obstacle avoidance scenario, yaw control will have the highest priority to ensure that the vehicle can respond quickly and avoid accidents.

[0076] Step S420: determining the control target type of the vehicle body posture according to the driving scenario and the adjustment requirements of the vehicle body posture.

[0077] Specifically, the control target type refers to the specific vehicle body posture adjustment that can be achieved through coordinated control, such as yaw pre-stabilization, roll suppression, pitch control, vertical translation control, etc.

[0078] Exemplarily, control target type identification: Based on the determined body posture adjustment requirements and the driving scenario in which the vehicle is located, identify the control target type that needs to be adjusted first. For example, on slippery roads, roll control and yaw control may need to be simultaneously focused on as key control targets. Actuator capability matching: Evaluate the capabilities and response characteristics of each actuator (such as the drive motor, braking system, steering system, and suspension system) to determine which actuators are most suitable for achieving the current control target type. Control target type arbitration: Taking into account the mutual influence between actuators, as well as the differences in driving modes and driving intentions, the final control target type is determined through intelligent arbitration algorithms, such as rule-based expert systems or machine learning models, to ensure that the actuators can work together to achieve optimal vehicle posture adjustment.

[0079] Exemplarily, the control target type may include no intervention, which means that the user selects a custom driving mode and chooses to turn off the control of the vehicle body posture. Or there is no need for intervention in the driving scene. The control target type may also include but is not limited to: extreme obstacle avoidance control, open road control, docking road control, lateral shift function, one-key exit function, etc. The control target type of extreme obstacle avoidance control includes the control of the yaw, roll, drive (electric brake), brake, and vertical direction of the vehicle body posture. The control target type of open road control includes the control of the yaw, drive, and brake of the vehicle body posture. The control target type of docking road control includes the control of the yaw, drive, and brake of the vehicle body posture. The control target type of the lateral shift function includes the control of the drive, yaw, and lateral direction of the vehicle body posture. The control target type of the one-key exit function includes the control of the yaw, brake, and drive of the vehicle body posture. It is also possible to automatically determine the control target type required for coordinated control based on the current state of the vehicle, including the control of the yaw, lateral deviation, roll, and pitch of the vehicle body posture.

[0080] Based on the vehicle configuration, driving mode, driving scenario, etc., determine the type of control target required for coordinated control. For example, linear yaw rate gain: For vehicles with forward and rear turns configured with wire control, an appropriate yaw rate gain can be set to improve the user's steering experience. Flexible small radius turning: For vehicles with only rear-wheel steering, the turning angle can be reversed to the front wheel in the low-speed section to reduce the turning radius and improve the vehicle's low-speed flexibility. Acceleration vector control: Perform acceleration vector control of the vehicle in three dimensions: horizontal, longitudinal, and vertical.

[0081] Step S430 , controlling the corresponding multiple actuator actions according to the control target type of the vehicle body posture.

[0082] Specifically, according to the determined vehicle body posture control target type, the present invention controls the corresponding actuator to act to adjust the current posture of the vehicle to match the target posture.

[0083] Exemplarily, actuator dynamics command conversion: convert the control target type into specific actuator dynamics commands, such as the torque demand of the drive motor, the pressure distribution of the braking system, the angle command of the steering system, the height and stiffness adjustment of the suspension system, etc. Actuator scheduling and control: according to the converted dynamics command, the actuator is scheduled and controlled to perform actions. At the same time, considering the interaction between the actuators, a coordinated control algorithm such as sliding mode control, optimal control or fuzzy control is applied to ensure that the control effect of each actuator is maximized and control conflicts are avoided. Actuator response monitoring and feedback: real-time monitoring of the actuator's response effect, collection of the vehicle's new posture information, formation of closed-loop control, and adjustment of the control command based on feedback to ensure that the vehicle's posture is adjusted quickly, smoothly and accurately.

[0084] In this embodiment, the target body posture of the vehicle, as well as the adjustment requirements and control target types of the body posture are intelligently determined according to the driving scene and driving mode. The accuracy of the vehicle posture adjustment is ensured through precise data collection and state estimation. At the same time, based on the effective actuator scheduling and coordinated control of the control target type, the optimal posture control of the vehicle in different scenarios is achieved, which significantly improves the driving safety and comfort of the vehicle, as well as the overall driving performance. In the event of an actuator failure, this method can also achieve smooth degradation processing through a fault-tolerant redundancy mechanism, maintain basic vehicle control functions, and ensure driving safety.

[0085] In one embodiment, a fault-tolerant redundant mechanism can also be designed, based on the various actuators of the vehicle, such as the drive motor, brake system, steering system and suspension system, each of which has a specific function in the coordinated control of the vehicle's lateral, longitudinal and vertical directions. When an actuator fails, the mechanism can intelligently dispatch other actuators to replace the function of the failed actuator according to the urgency of the failure and the current control target of the vehicle, or, if it is irreplaceable, ensure that the vehicle can park smoothly and safely through degradation processing.

[0086] Fault-tolerant redundancy mechanism implementation method: Actuator fault diagnosis: The status of the actuator is monitored in real time using the vehicle's self-diagnosis system. Once a fault is detected, the fault-tolerant redundancy mechanism is immediately activated. Fault diagnosis includes hardware faults (such as motor damage, sensor failure) and software faults (such as control algorithm failure, communication interruption). Actuator capability evaluation: After a fault occurs, the system will re-evaluate the capabilities and response characteristics of the remaining actuators to determine which actuators can replace the functions of the faulty actuators and the maximum control effect that can be provided. Functional substitution scheduling: Based on the actuator capability evaluation, the coordinated control algorithm will intelligently select other actuators to achieve the control objectives originally undertaken by the faulty actuator. For example, if the front-wheel steering system fails, the rear-wheel steering system can replace the front-wheel steering in certain driving modes and scenarios to maintain the vehicle's yaw control. Degraded processing strategy: When a replacement actuator cannot be found or the replacement actuator cannot fully meet the control objectives, the system will initiate a degraded processing strategy. This may include limiting the vehicle's maximum driving speed, disabling certain high-perception functions (such as extreme obstacle avoidance control), and guiding the vehicle to decelerate smoothly and stop safely to avoid the risk of loss of control due to actuator failure. Dynamic adjustment of control rules: The fault-tolerant redundancy mechanism dynamically adjusts the coordinated control rules according to the availability of the remaining actuators and the priority of the control objectives to ensure optimal control of the vehicle posture in the event of a fault while maintaining driving safety and comfort.

[0087] Improved system robustness: Even in the event of a failure of a key actuator, the system can still maintain basic vehicle control functions by dispatching other actuators to ensure stable driving of the vehicle in emergency situations. Enhanced driving safety: The fault-tolerant redundancy mechanism can quickly respond to actuator failures and ensure that the vehicle can park safely through a degradation processing strategy, avoiding the risk of loss of control due to actuator failure. Maintained driving experience: In the event of an actuator failure, the impact on the driving experience is minimized as much as possible through functional substitution scheduling, ensuring the vehicle's operating performance and comfort in a faulty state. Optimized control strategy: The fault-tolerant redundancy mechanism ensures that the optimal solution for vehicle posture control can be achieved in multiple actuator failure scenarios through dynamic adjustment of control rules, avoiding control conflicts and improving control efficiency and effectiveness.

[0088] In this embodiment, by designing a fault-tolerant redundancy mechanism and using intelligent scheduling and degradation processing strategies, the robustness and driving safety of the system are significantly improved, which plays a vital role in ensuring the stability and reliability of smart electric vehicles in complex driving environments.

[0089] In one embodiment, Figure 5 As shown, step S430 controls the corresponding multiple actuator actions according to the control target type of the vehicle body posture. It includes: steps S500-S520. Among them:

[0090] Step S500: determining a plurality of corresponding target actuators according to the control target type.

[0091] Specifically, the target actuator refers to the specific actuator system that needs to intervene to adjust the vehicle posture according to the current control target type, such as steering, driving, braking and suspension.

[0092] For example, control target type analysis: According to the driving scenario and the adjustment requirements of the vehicle body posture, identify the control target type that needs to be achieved at present, such as yaw pre-stabilization, roll suppression, etc. Actuator capability evaluation: Based on the driving mode and the current state of the vehicle, evaluate the capabilities and response characteristics of each actuator to determine which actuators are most suitable for achieving the current control target type. Actuator selection: Using expert systems, machine learning or fuzzy logic algorithms, intelligently select one or more groups of actuators from the drive motor, brake system, steering system, and suspension system as target actuators to ensure that the control target can be achieved efficiently. According to the vehicle control target type, the required actuators include forward rotation, rear rotation, drive, brake, and suspension. In addition, the main and auxiliary actuators need to be selected according to the control target type. For yaw and side slip control targets, the main actuators are forward rotation, rear rotation, brake, and drive (four-wheel independent drive configuration vehicle). The auxiliary actuators are suspension and drive (front and rear axle dual motor configuration vehicle). For roll and pitch control targets, the main actuator is suspension, and the auxiliary actuators are drive and brake. If both yaw and roll control requirements exist, their respective main actuator control targets will be responded to first, such as forward rotation, backward rotation, braking, etc. will give priority to yaw requirements, and the suspension will give priority to roll requirements.

[0093] Step S510: determining the priority order of the actions of the multiple target actuators according to the driving mode.

[0094] Specifically, the priority order is determined to solve how to avoid control conflicts and ensure maximum control effect in multi-actuator intervention scenarios.

[0095] For example, driving mode analysis: According to the driving mode selected by the target object (driver or autonomous driving system), analyze the requirements for vehicle performance in this mode, such as more emphasis on energy consumption and comfort in economic mode, and more emphasis on handling response and stability in sports mode. Control strategy design: Design a control strategy based on the driving mode, clarify the intervention logic and control weight of each target actuator in different modes to reflect the priority order of the mode. Actuator priority setting: According to the control strategy, automatically set the priority order of multiple target actuator actions to ensure that when executing control instructions, the actuator with a high priority can respond first, avoid conflicts between control instructions, and improve control efficiency.

[0096] Step S520, controlling the actions of multiple target actuators according to the priority order to achieve the control target corresponding to the control target type.

[0097] Specifically, according to the determined priority order, the plurality of target actuators are controlled to achieve the control target corresponding to the control target type.

[0098] Exemplarily, dynamic instruction generation: Generate actuator dynamic instructions based on the control target type and the capabilities of the target actuator, including parameters such as torque, braking force, steering angle and suspension adjustment. Actuator scheduling: Schedule the target actuator to perform actions according to the dynamic instructions in the set priority order. The actuator with high priority is controlled first to ensure the timeliness and effectiveness of its actions. Control instruction coordination: Apply coordinated control algorithms such as sliding mode control, optimal control or fuzzy control to ensure that the control instructions between multiple actuators do not interfere with each other and form a consistent control effect. Dynamic adjustment and optimization: During the control process, continuously monitor the response effect of the actuator and the changes in the vehicle posture, and adjust the control instructions in real time to achieve the optimization of the control target and ensure that the vehicle can maintain the best body posture in various driving modes.

[0099] In this embodiment, the optimal posture control of the vehicle in different driving modes and scenarios is achieved by intelligently selecting multiple target actuators and determining the priority order of their actions. After the control target type is determined, this method accurately selects the most suitable actuator combination, avoiding resource waste and improving control efficiency. The analysis of driving modes and the setting of priority order ensure that the actuator actions are closely matched with the target object requirements, and improve the performance of the vehicle in various driving modes, such as energy saving in economic mode and maneuverability in sports mode. The coordination of actuator scheduling and control instructions effectively avoids control conflicts between actuators, ensures the consistency of control effects and smooth adjustment of vehicle posture, and improves driving safety and comfort. The dynamic adjustment and optimization mechanism enables vehicle posture control to adapt to changing driving scenarios, achieve continuous optimization, and enhance the overall driving experience.

[0100] In one embodiment, as Figure 6 shown, the method further includes steps S600 - S610. Among them:

[0101] Step S600: Determine the response characteristics of each actuator of the vehicle according to the design parameters of each actuator of the vehicle.

[0102] Among them, the response characteristics include the adjustment range of the actuator for the vehicle body attitude, the response speed of the actuator, and the influence degree of the actuator on the vehicle comfort when the actuator acts.

[0103] Specifically, the response characteristics of the actuator determine its effectiveness and applicability in vehicle attitude control, including the adjustment range, response speed, and influence on comfort. These characteristics are crucial for formulating a coordinated control strategy.

[0104] Exemplarily, design parameter analysis: Collect and analyze the design parameters of each actuator, such as the torque range of the drive motor, the pressure adjustment range of the braking system, the angular velocity range of the steering system, the height and stiffness adjustment range of the suspension system, etc. Response characteristic modeling: Based on the design parameters, establish a response model of the actuator, which includes the description of the adjustment range of the vehicle body attitude, the response speed of the actuator, and the influence degree of the actuator on the vehicle comfort when the actuator acts. Adjustment range: Through experiments or simulations, evaluate the influence degree of each actuator on the vehicle body attitude at different working points, such as the influence of the drive motor torque change on the vehicle yaw angular velocity. Response speed: Measure the time from when the actuator receives the control command to when it generates an effective action, which characterizes the dynamic performance of the actuator. Comfort influence: Evaluate the influence of the actuator on vehicle vibration, noise, and driving experience when the actuator acts to quantify its contribution or negative impact on comfort. Response characteristic calibration: Conduct calibration experiments to verify the accuracy and applicability of the actuator response model to ensure that the model can truly reflect the actual performance of the actuator under different driving conditions.

[0105] Step S610: Determine the priority order of multiple actuator actions in each driving mode according to the response characteristics of each actuator.

[0106] Specifically, different driving modes have different requirements and expectations for the actuator. Therefore, the present invention proposes a method for determining the priority order of actuator actions based on response characteristics to optimize the control effect and meet the specific requirements of the driving mode.

[0107] For example, driving mode feature extraction: analyze the core features of each driving mode, such as the economic mode focuses on energy consumption, the sports mode emphasizes handling performance, and the off-road mode emphasizes passability and stability. Response characteristic matching: According to the characteristics of the driving mode, evaluate the degree of matching between the response characteristics of each actuator and the mode requirements. For example, in the sports mode, the response speed and adjustment range of the steering system and the drive system are particularly important. Priority order setting: Using a multi-objective optimization algorithm, comprehensively consider the response characteristics of the actuator and the requirements of the driving mode, determine the priority order of the actuator action under this driving mode, and ensure that actuators with high priority can respond to control instructions earlier and more effectively.

[0108] In this embodiment, by deeply analyzing the design parameters of each actuator of the vehicle, the response characteristics of the actuator are evaluated and determined, including the adjustment amplitude, response speed and the degree of influence on comfort. This series of response characteristic evaluations enables the vehicle control strategy to be dynamically adjusted according to the actual actuator capabilities, avoiding the problem of overuse or insufficient response of the actuator, and ensuring the effective execution of the control instructions. By analyzing the characteristics of the driving mode and matching it with the response characteristics of the actuator, this method can intelligently adjust the intervention order of the actuator, which not only improves the performance of the vehicle in a specific driving mode, such as the handling in the sports mode and the passability in the off-road mode, but also optimizes the comprehensive comfort of the vehicle and reduces the discomfort that may be caused by the actuator action. In addition, the setting of the priority order effectively avoids the control conflict between the actuators and ensures the stability and reliability of the control system in complex driving scenarios. In summary, through the refined evaluation of the actuator response characteristics and the setting of the priority order based on the driving mode, the optimal posture control of the vehicle in different driving modes and scenarios is achieved, which significantly improves the vehicle performance and the satisfaction of the target object, and has important technical progress significance and market application value.

[0109] In one embodiment, Figure 7 As shown, step S520 controls the actions of multiple target actuators according to the priority order to achieve the control target corresponding to the control target type. It includes: steps S700-S720. Among them:

[0110] Step S700, determining control strategies for multiple target actuators according to a priority order.

[0111] The control strategy includes at least one of the following: a lateral control strategy, a longitudinal control strategy, and a vertical control strategy of the vehicle.

[0112] Specifically, the control strategy defines how to utilize the target actuators to achieve control of the vehicle's lateral, longitudinal, and vertical attitude, taking into account the actuator's response characteristics and the specific requirements of the driving mode.

[0113] Exemplarily, control strategy classification: control strategies are divided into lateral control strategies, longitudinal control strategies and vertical control strategies, each strategy is aimed at adjusting the posture of the vehicle in a specific direction. Lateral control strategy: a control strategy designed to adjust the lateral posture parameters of the vehicle, such as the yaw rate and sideslip angle, such as through the coordinated control of the steering system and the drive system to achieve stable driving of the vehicle in a curve. Longitudinal control strategy: a strategy is formulated to control the acceleration, deceleration and stability of the vehicle, such as using the coordination of the drive motor and the braking system to achieve smooth acceleration and deceleration of the vehicle under different road conditions. Vertical control strategy: a control strategy designed to adjust the roll angle, pitch angle and vertical displacement of the vehicle, such as through the intelligent adjustment of the suspension system to improve the driving comfort and stability of the vehicle under complex road conditions. Control strategy optimization: according to the driving mode and the response characteristics of the actuator, the above control strategies are optimized to ensure that the driving comfort and safety are improved while meeting the vehicle posture adjustment requirements.

[0114] For example, for the extreme obstacle avoidance control type: the rear wheel steering angle requirement is calculated based on the actual yaw rate and the expected yaw rate deviation. In the initial stage, the rear wheel steering angle is controlled to be in the same direction as the front wheel steering angle to delay vehicle oversteering. At the same time, torque control is used to reduce vehicle speed. The vehicle body posture is improved through braking torque. The body roll state is also improved through the suspension.

[0115] For the control type of the on-road road: According to the left and right adhesion coefficients, and the actual yaw rate and the expected yaw rate deviation, the required rear wheel turning angle for the vehicle to keep going straight is calculated, and more aggressive traction control parameters are used to improve the acceleration performance on the on-road road. More aggressive anti-lock braking system control parameters are used to shorten the braking distance on the on-road road.

[0116] For the road surface control type: according to the status of the front wheels, preview the status of the rear axle, and combine the lateral stability requirements, increase or decrease the torque of the rear wheels in advance.

[0117] For the lateral shift function: after controlling the front and rear wheels to the outward-facing position, for four-wheel drive vehicles, the front and rear wheel slip rate is controlled to control the front and rear wheel speeds in the opposite direction, so that the longitudinal force of the wheel in the lateral direction of the vehicle is greater than the lateral force of the wheel in the lateral direction of the vehicle, so as to achieve lateral movement of the vehicle. For vehicles with dual motors on the front and rear axles, in addition to the front and rear axle drive slip rate control, timely intervention of the four-wheel brake is also required to ensure the consistency of the four-wheel slip rate.

[0118] For the one-key exit function: after locking the rear wheels through braking, control the front wheel steering to the maximum value, and at the same time control the front wheel slip rate to achieve one-key exit of the vehicle on the spot.

[0119] When there is no stability control requirement, comfort and convenience are the control requirements, including but not limited to the following controls:

[0120] Linear yaw rate gain: Coordinated control of forward and backward steer-by-wire to achieve linear yaw rate gain.

[0121] Flexible small-radius turning: Coordinated control of rearward turning and braking to achieve convenient low-speed turning of the vehicle.

[0122] Acceleration vector control: Coordinated control of steering, drive, braking and suspension to avoid sudden changes in vehicle acceleration, achieve continuous vector changes in acceleration, and improve user driving comfort.

[0123] Step S710, determining control parameters of multiple target actuators according to the control target corresponding to the control target type.

[0124] Specifically, control parameters are specific values ​​for implementing the target actuator control strategy, such as torque, braking force, steering angle, etc., which directly determine the actuator's movement amplitude and effect.

[0125] For example, control target conversion: convert the control target corresponding to the control target type (such as the desired yaw rate, the desired roll angle, etc.) into the control parameter requirements of the specific actuator. Parameter setting: set the control parameters of the actuator, such as steering angle, drive torque, braking force, and suspension stiffness, based on the response characteristics and control targets of the actuator. Parameter optimization: use optimization algorithms, such as particle swarm optimization, genetic algorithm, or gradient descent method, to dynamically adjust the control parameters according to the vehicle state and road conditions to achieve the best control effect.

[0126] Exemplarily, the control parameters, such as roll, are determined by obtaining a roll control requirement based on an actual roll angle.

[0127] Yaw: Based on the actual yaw rate and the expected yaw rate deviation, the actual center of mass slip angle and the expected center of mass slip angle deviation, the total expected yaw moment requirement is obtained through sliding mode control. Then, based on the center of mass slip angle, yaw rate, and the response characteristics of each actuator, the minimum tire force constraint is considered, and the expected yaw moment of each actuator is obtained through optimal control. In addition, by adjusting the suspension characteristics and, for vehicles with dual motors on the front and rear axles, adjusting the drive torque distribution between the front and rear axles, the vertical load of each wheel is affected, which indirectly affects the yaw pre-stabilization control.

[0128] Pitch: The pitch control requirement can be obtained based on the actual pitch angle.

[0129] Step S720: Control multiple target actuators to adjust to corresponding control parameters according to the control strategy to achieve the control target corresponding to the control target type.

[0130] Specifically, after determining the control strategy and parameters of the actuator, the present invention achieves the control target by precisely controlling the actuator so that the actuator adjusts the vehicle posture according to the set parameters.

[0131] Exemplarily, actuator instruction generation: convert the determined control parameters into specific control instructions for the actuator. Dynamic control execution: dynamically adjust the control parameters of the actuator according to the control strategy to ensure that the vehicle can quickly respond to control instructions and adjust to the target posture in different driving modes and scenarios. Actuator response monitoring: real-time monitoring of the response effect of the actuator, including the actual changes in the vehicle posture and the health of the actuator, to ensure the accuracy of the control effect and the reliability of the actuator. Parameter feedback adjustment: establish a closed-loop control system, feed back the data of the actuator response monitoring to the control strategy optimization module, adjust the control parameters according to the actual effect, and achieve more precise vehicle posture control.

[0132] In this embodiment, efficient and precise control of the vehicle body posture is achieved by determining the control strategy and control parameters of the target actuator. First, by classifying the control strategies into lateral, longitudinal and vertical directions, the present invention can comprehensively cover all aspects of vehicle posture adjustment, ensuring the stability and maneuverability of the vehicle in complex driving scenarios. Secondly, through the precise setting and dynamic optimization of control parameters, it is ensured that the actuator can adjust the vehicle posture in the most suitable manner, improving the accuracy and response speed of control, while reducing energy consumption and improving comfort. Finally, the introduction of a closed-loop control mechanism enables the system to continuously monitor the actuator response and changes in body posture, and adjust the control parameters in real time according to feedback, thereby achieving continuous optimization of the control effect and ensuring the excellent performance of the vehicle in various driving modes.

[0133] In one embodiment, Figure 8 As shown, step S200 determines the current driving scene of the vehicle according to the road condition information of the road where the vehicle is located, the state information of the vehicle and the operation instruction of the target object. It includes: steps S800-S810. Among them:

[0134] Step S800, determining the current scene features of the vehicle based on the road condition information of the vehicle, the vehicle status information and the operation instructions of the target object.

[0135] Specifically, the vehicle's current scene features refer to a comprehensive assessment of the current driving environment and vehicle status based on the road condition information of the vehicle, the vehicle status information, and the operating instructions of the target object (driver or autonomous driving system) to determine the most accurate scene description.

[0136] For example, road condition information collection: using on-board sensors (such as cameras, radars, lidars, satellite positioning, inertial sensors, etc.) to obtain road information, including road types (such as urban streets, highways, rural roads, off-road roads), road conditions (such as slippery, potholes, flatness, slopes), traffic conditions (such as congestion, smoothness, traffic density), etc. Vehicle status information monitoring: real-time monitoring of various status information of the vehicle, such as vehicle speed, acceleration, steering angle, brake pressure, suspension height, vertical load distribution, driver operation instructions (such as accelerator pedal, brake pedal, steering wheel position), etc., to reflect the real-time operating status of the vehicle. Scene feature extraction: Based on the above information, through data fusion and machine learning algorithms (such as support vector machines, random forests, neural networks), extract key features reflecting the current scene, such as road curvature, slippery degree, vehicle yaw angular velocity, roll angle, etc.

[0137] Step S810, using the current scene features of the vehicle to perform matching in a preset scene library, and determining the scene with the highest matching degree with the current scene features of the vehicle as the current driving scene of the vehicle.

[0138] Specifically, the driving scenario refers to finding the best matching scenario description in the preset scenario library based on the current scenario characteristics of the vehicle, thereby providing more specific scenario information and control strategy basis for vehicle posture control.

[0139] Exemplarily, establish a scenario library: collect and analyze the features of various typical driving scenarios, establish a scenario database, and the scenario library contains a combination of different road conditions, vehicle states and driving operation instructions, as well as the control requirements and goals for each scenario. Scene matching algorithm: design a matching algorithm, such as the nearest neighbor algorithm based on Euclidean distance and the scene recognition algorithm based on similarity, to compare the current scene features of the vehicle with the features in the scenario library, and find the scene with the highest matching degree as the current driving scene. Scene decision: Based on the matching results, the decision system automatically identifies the current driving scene and passes the scene information to the control strategy optimization module to adjust the control strategy and parameters of the actuator to achieve optimal control of the vehicle posture.

[0140] In this embodiment, by acquiring the road condition information of the road on which the vehicle is located, the vehicle status information and the operation instructions of the target object, the current scene features of the vehicle are accurately determined, providing key information for the intelligent control of the vehicle in a complex environment. The extraction of scene features utilizes advanced data fusion and machine learning technologies to ensure the comprehensiveness and accuracy of information. The scene features are matched in the preset scene library to determine the scene with the highest matching degree with the current scene features of the vehicle as the current driving scene. This process greatly improves the pertinence and effectiveness of vehicle posture control. The establishment of the scene library and the design of the scene matching algorithm enable the system to flexibly respond to various driving conditions, such as urban congestion, high-speed turns, slippery roads, off-road bumps, etc., providing the vehicle with the best control strategy and parameter settings, ensuring the stability and safety of the vehicle in different scenarios.

[0141] In one embodiment, Fig. 9 As shown, a schematic diagram of a coordinated control architecture of a vehicle motion controller (VMC) is provided, which is used to implement the control method of the vehicle body posture in any of the above embodiments, and can control the motion state of the vehicle to achieve coordinated control in the lateral, longitudinal and vertical directions. The VMC architecture includes multiple structural layers: information acquisition layer, target determination layer, coordinated control layer, and execution layer. Among them:

[0142] The information acquisition layer includes:

[0143] Vehicle state and road parameter estimation module, vehicle state estimation: This part is responsible for real-time monitoring and estimation of the key state parameters of the vehicle, collecting and estimating the real-time state of the vehicle and road environment parameters. Including but not limited to vehicle speed, sideslip angle, roll angle, pitch angle, vertical load, etc. These estimates are the basis for subsequent control decisions. Reference vehicle speed estimation: obtain the instantaneous speed of the vehicle. Center of mass sideslip angle estimation: estimate the position deviation of the center of mass of the vehicle relative to the driving direction. Roll angle estimation: measure the lateral tilt angle of the vehicle. Pitch angle estimation: measure the tilt angle of the vehicle front and rear. Four-wheel vertical load estimation: estimate the vertical load borne by each wheel of the vehicle. Vehicle mass estimation: calculate the total mass of the vehicle in real time.

[0144] Road parameter estimation: This module collects and analyzes road conditions, such as slope, road adhesion coefficient, etc., to provide real-time environmental information to the control system. Specifically, it can include: Slope estimation: determine the slope of the current road. Road adhesion coefficient estimation: evaluate the friction performance of the road surface.

[0145] Actuator response characteristic estimation module: Capacity evaluation: evaluate the maximum control capability of each actuator (such as drive motor, brake system, steering system, suspension system) under current conditions. Response speed: measure the time from the actuator receiving the control signal to the actuator responding, reflecting its dynamic performance. Response quality: evaluate the impact of the actuator on vehicle stability, comfort, etc. when it moves. Specifically, it can include the quality of yaw effect, side slip suppression, roll suppression, pitch suppression, vertical translation suppression, etc.

[0146] The target determination layer includes: the control target calculation module, which can calculate the desired control target of the vehicle based on the multi-degree-of-freedom vehicle model and driving mode by obtaining the control requirements and considering the constraint boundary conditions. Calculate the desired yaw rate: set the yaw control target based on the vehicle dynamic model and driving requirements. Formulate the constraint boundaries of the center of mass sideslip angle, roll angle, pitch angle, and vertical translation to ensure vehicle stability and safety.

[0147] Multi-DOF vehicle model: Combines the vehicle’s dynamic characteristics, such as yaw, roll, pitch, etc., to calculate the desired control objectives under the current driving mode and scenario.

[0148] Coordination control layer:

[0149] The VMC control target type arbitration module determines the vehicle's current main control target type based on the driving mode and driving scenario. Specifically, it includes non-intervention: no active control in user-defined mode or in driving scenarios without control requirements. High-perception functions such as extreme obstacle avoidance, on-road and butted roads: arbitrate the most appropriate control target type based on scenario requirements. Pre-stability control: intervene in control in advance before the vehicle enters an unstable state. Comfort control: improve vehicle driving comfort when there is no threat to stability. Control target type: arbitrate the most appropriate control target type based on driving mode and driving scenario, such as yaw, roll, tilt, pitch, vertical translation, etc.

[0150] VMC actuator intervention status arbitration module, actuator selection: intelligently select the most appropriate actuator combination based on the control target type and actuator response characteristics.

[0151] The coordination control rule formulation module formulates the optimal coordination control rules to ensure the coordinated work between actuators.

[0152] Rule formulation: Based on the control target type and the selected actuator, the optimal coordinated control rules are formulated to ensure that the work between the actuators does not conflict and the body posture is adjusted to the optimal level. Rule formulation: Formulate control rules for yaw following, roll suppression, drive torque, roll suppression, pitch suppression, and vertical translation suppression. Dynamic adjustment rules: Consider the actuator characteristics and scenario requirements, and dynamically adjust the control rules to optimize the control effect.

[0153] Execution layer:

[0154] The actuator target arbitration module selects the most appropriate actuator to respond to the arbitrated control target type. Select the optimal actuator: Select the master actuator based on actuator diagnosis, vehicle status and scenario requirements. When an actuator fails, other actuators are dispatched to achieve functional replacement.

[0155] Actuator dynamics command conversion module, the coordinated control rules are converted into specific dynamics commands for each actuator. Command generation: Convert the coordinated control target into specific dynamics commands for each actuator, such as torque, braking force, steering angle, etc. Command sending: Send the dynamics command to the corresponding actuator to make it perform control actions and adjust the vehicle posture. Convert the control rules into control commands for actuators such as front-wheel steering, rear-wheel steering, drive, brake, suspension, etc. Send the control command to each actuator to perform specific control actions. For example, in the horizontal direction, the front-wheel steering and rear-wheel steering can be controlled. In the longitudinal direction, the torque of the drive motor and the braking system (electromechanical brake (EMB / hydraulic brake)) can be controlled. In the vertical direction, the height and stiffness of the air spring, the current of the CDC, and the damping of the vehicle can be changed.

[0156] The specific control method has been described in the above embodiments and will not be repeated here.

[0157] In this embodiment, the VCM control architecture effectively integrates vehicle status information, road parameters, actuator characteristics, driving modes and scenario requirements, and realizes coordinated control of the vehicle in three dimensions: horizontal, vertical and vertical. Through multi-level control strategies, including target arbitration, actuator arbitration and coordinated control rule formulation, the present invention ensures that the vehicle can maintain the best body posture under different driving modes and complex road conditions, improving driving safety and comfort.

[0158] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, disk, CD), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of each embodiment of the present application.

[0159] In this embodiment, a vehicle body posture control device is also provided, and the vehicle body posture control device is used to implement the above-mentioned embodiments and preferred embodiments, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware for a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0160] Fig.10 is a structural block diagram of an optional vehicle body posture control device according to an embodiment of the present application. Fig.10 As shown, including:

[0161] The scene determination module 1001 is used to determine the current driving scene of the vehicle according to the road condition information of the road on which the vehicle is located, the state information of the vehicle and the operation instruction of the target object.

[0162] The mode determination module 1002 is used to determine the current driving mode of the vehicle in response to the selection instruction of the target object.

[0163] The posture determination module 1003 is used to determine the target body posture of the vehicle according to the driving scene and driving mode.

[0164] The posture control module 1004 is used to control the actions of multiple actuators of the vehicle when the current body posture of the vehicle does not match the target body posture, so that the current body posture of the vehicle after adjustment matches the target body posture.

[0165] Through the above device, the current driving scene of the vehicle is first determined according to the road condition information of the road where the vehicle is located, the state information of the vehicle and the operation instructions of the target object, so as to facilitate the subsequent accurate control of the vehicle's body posture. In response to the selection instruction of the target object, the current driving mode of the vehicle is determined, so as to obtain the driving requirements of the target object, so that the subsequent control of the vehicle's body posture can meet the needs of the target object. According to the driving scene and driving mode, the target body posture of the vehicle is determined, so as to obtain the optimal body posture that best meets the current situation, and the body posture can ensure the vehicle's controllability, stability and comfort. When the current body posture of the vehicle does not match the target body posture, the multiple actuators of the vehicle are controlled to act so that the adjusted current body posture of the vehicle matches the target body posture, thereby realizing the control of the body posture. In summary, the method of the present application can dynamically adjust the target body posture of the vehicle by accurately identifying the driving scene and intelligently matching the driving mode, ensuring that the vehicle can maintain the optimal control performance and stability under various driving conditions.

[0166] In an exemplary embodiment, the above-mentioned posture determination module 1003 is also used to determine the constraint boundary conditions of the vehicle according to the physical parameter information of the vehicle. According to the operation instruction of the target object, the desired vehicle motion state of the target object is determined. According to the driving scene and the desired vehicle motion state of the target object, the target vehicle motion state is determined, wherein the target vehicle motion state satisfies the constraint boundary conditions. According to the target vehicle motion state and the driving mode, the target body posture of the vehicle is determined.

[0167] In an exemplary embodiment, the posture control module 1004 is also used to obtain the current body posture of the vehicle. When the current body posture of the vehicle does not match the target body posture, the adjustment requirement of the body posture is determined. According to the driving scene and the adjustment requirement of the body posture, the control target type of the body posture is determined. According to the control target type of the body posture, the corresponding multiple actuator actions are controlled.

[0168] In an exemplary embodiment, the posture control module 1004 is further configured to determine a plurality of corresponding target actuators according to the control target type, determine a priority order of the actions of the plurality of target actuators according to the driving mode, and control the actions of the plurality of target actuators according to the priority order to achieve the control target corresponding to the control target type.

[0169] In an exemplary embodiment, the above device further includes:

[0170] The response determination module is used to determine the response characteristics of each actuator of the vehicle according to the design parameters of each actuator of the vehicle, wherein the response characteristics include the adjustment range of the actuator for the vehicle body posture, the response speed of the actuator, and the degree of influence of the actuator on the vehicle comfort when the actuator is in action.

[0171] The priority determination module is used to determine the priority order of the actions of multiple actuators in each driving mode according to the response characteristics of each actuator.

[0172] In an exemplary embodiment, the above-mentioned attitude control module 1004 is also used to determine the control strategy of multiple target actuators according to the priority order, wherein the control strategy includes at least one of the following: a lateral control strategy, a longitudinal control strategy, and a vertical control strategy of the vehicle. According to the control target corresponding to the control target type, the control parameters of the multiple target actuators are determined. According to the control strategy, the multiple target actuators are controlled to adjust to the corresponding control parameters to achieve the control target corresponding to the control target type.

[0173] In an exemplary embodiment, the scene determination module 1001 is further used to determine the current scene features of the vehicle according to the road condition information of the road on which the vehicle is located, the state information of the vehicle, and the operation instructions of the target object. The current scene features of the vehicle are used to match in a preset scene library, and the scene with the highest matching degree with the current scene features of the vehicle is determined as the current driving scene of the vehicle.

[0174] An embodiment of the present application further provides a storage medium, which includes a stored program, wherein the program executes any of the above methods when it is run.

[0175] Optionally, in this embodiment, the storage medium may be configured to store program codes for executing the following steps:

[0176] S1, determining the current driving scene of the vehicle according to the road condition information of the road on which the vehicle is located, the state information of the vehicle and the operation instruction of the target object.

[0177] S2, in response to the selection instruction of the target object, determining the current driving mode of the vehicle.

[0178] S3, determining a target body posture of the vehicle according to the driving scenario and the driving mode.

[0179] S4, when the current body posture of the vehicle does not match the target body posture, controlling the actions of multiple actuators of the vehicle to make the current body posture of the vehicle after adjustment match the target body posture.

[0180] An embodiment of the present application further provides an electronic device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor is configured to run the computer program to execute the steps in any one of the above method embodiments.

[0181] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0182] Optionally, in this embodiment, the processor may be configured to perform the following steps through a computer program:

[0183] S1, determining the current driving scene of the vehicle according to the road condition information of the road on which the vehicle is located, the state information of the vehicle and the operation instruction of the target object.

[0184] S2, in response to the selection instruction of the target object, determining the current driving mode of the vehicle.

[0185] S3, determining a target body posture of the vehicle according to the driving scenario and the driving mode.

[0186] S4, when the current body posture of the vehicle does not match the target body posture, controlling the actions of multiple actuators of the vehicle to make the current body posture of the vehicle after adjustment match the target body posture.

[0187] Optionally, in this embodiment, the above-mentioned storage medium may include but is not limited to: a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and other media that can store program codes.

[0188] An embodiment of the present application further provides a computer program product, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores the computer program product, and when the computer program is executed by a processor, the steps of the method in each embodiment of the present application are implemented.

[0189] Optionally, in this embodiment, the above computer program may be configured to implement the following steps when executed by a processor:

[0190] S1, determining the current driving scene of the vehicle according to the road condition information of the road on which the vehicle is located, the state information of the vehicle and the operation instruction of the target object.

[0191] S2, in response to the selection instruction of the target object, determining the current driving mode of the vehicle.

[0192] S3, determining a target body posture of the vehicle according to the driving scenario and the driving mode.

[0193] S4, when the current body posture of the vehicle does not match the target body posture, controlling the actions of multiple actuators of the vehicle to make the current body posture of the vehicle after adjustment match the target body posture.

[0194] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0195] Obviously, those skilled in the art should understand that the above modules or steps of the present application can be implemented by a general computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, and in some cases, the steps shown or described can be executed in a different order from that herein, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. Thus, the present application is not limited to any specific combination of hardware and software.

[0196] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for controlling a vehicle body posture, characterized in that: The method comprises: Determining a current driving scenario of the vehicle based on road condition information of the vehicle, status information of the vehicle, and an operation instruction of a target object; In response to a selection instruction of a target object, determining a current driving mode of the vehicle, wherein the driving mode is used to indicate a requirement of the target object for vehicle performance; Determining a target body posture of the vehicle according to the driving scenario and the driving mode; In the case where the current body posture of the vehicle does not match the target body posture, determining a body posture adjustment requirement; Determining a control target type of a vehicle body posture according to the driving scenario and the adjustment requirements of the vehicle body posture; According to the control target type, determining a plurality of corresponding target actuators; Determining the priority order of the actions of the plurality of target actuators according to the driving mode; The actions of the plurality of target actuators of the vehicle are controlled in the priority order so that the current body posture of the vehicle after adjustment matches the target body posture.

2. The vehicle body posture control method according to claim 1, characterized in that: The determining the target body posture of the vehicle according to the driving scene and the driving mode includes: Determining constraint boundary conditions of the vehicle according to physical parameter information of the vehicle; Determining a desired vehicle motion state of the target object according to the operation instruction of the target object; determining a target vehicle motion state according to the driving scene and the desired vehicle motion state of the target object, wherein the target vehicle motion state satisfies the constraint boundary condition; A target body posture of the vehicle is determined according to the target vehicle motion state and the driving mode.

3. The vehicle body posture control method according to claim 1, characterized in that: The method further includes: determining the response characteristics of each actuator of the vehicle according to the design parameters of each actuator of the vehicle, wherein the response characteristics include the adjustment range of the actuator on the vehicle body posture, the response speed of the actuator, and the influence degree of the actuator on the vehicle comfort when the actuator is in action; The priority order of multiple actuator actions in each driving mode is determined based on the response characteristics of each actuator.

4. The vehicle body posture control method according to claim 1, characterized in that: The controlling of the plurality of target actuator actions of the vehicle in the order of priority comprises: Determining control strategies of the plurality of target actuators according to the priority order, wherein the control strategy includes at least one of the following: a lateral control strategy, a longitudinal control strategy, and a vertical control strategy of the vehicle; Determining control parameters of the plurality of target actuators according to the control target corresponding to the control target type; According to the control strategy, the plurality of target actuators are controlled to adjust to corresponding control parameters so as to achieve the control target corresponding to the control target type.

5. The vehicle body posture control method according to any one of claims 1 to 4, characterized in that: The determining of the current driving scene of the vehicle according to the road condition information of the road on which the vehicle is located, the state information of the vehicle and the operation instruction of the target object includes: Determining the current scene characteristics of the vehicle according to the road condition information of the vehicle, the state information of the vehicle and the operation instruction of the target object; The current scene features of the vehicle are used to perform matching in a preset scene library, and a scene with the highest matching degree with the current scene features of the vehicle is determined as the current driving scene of the vehicle.

6. A vehicle body posture control device, characterized in that: include: A scene determination module, used to determine the current driving scene of the vehicle according to the road condition information of the road where the vehicle is located, the state information of the vehicle and the operation instruction of the target object; a mode determination module, configured to determine a current driving mode of the vehicle in response to a selection instruction of a target object, wherein the driving mode is used to indicate a requirement of the target object for vehicle performance; A posture determination module, used to determine a target body posture of the vehicle according to the driving scene and the driving mode; A posture control module is used to determine the adjustment requirements of the vehicle body posture when the current vehicle body posture does not match the target vehicle body posture; determine the control target type of the vehicle body posture according to the driving scenario and the adjustment requirements of the vehicle body posture; determine a plurality of corresponding target actuators according to the control target type; determine the priority order of the actions of the plurality of target actuators according to the driving mode; and control the actions of the plurality of target actuators of the vehicle according to the priority order so that the current vehicle body posture after adjustment matches the target body posture.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein the computer program implements the steps of the method described in any one of claims 1 to 5 when executed by a processor.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method described in any one of claims 1 to 5 are implemented.

9. A computer program product, characterized in that The invention comprises a computer program, which implements the steps of the method according to any one of claims 1 to 5 when being executed by a processor.

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