Vehicle control method, device, electronic equipment and program product

Abstract

This invention discloses a vehicle control method, device, electronic equipment, and program product, relating to the field of vehicle technology. The method includes: estimating a desired yaw moment and a desired longitudinal force based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, reference steering wheel feedback torque, and roll angle constraints using an upper-level decision-maker, and feeding this information back to a lower-level distributor; calculating the maximum available longitudinal force and the maximum yaw moment of each wheel of the current vehicle using the lower-level distributor; determining a target longitudinal force based on the desired longitudinal force and the maximum available longitudinal force; and determining a target front and rear wheel steering angle, a target braking force, and a target driving force based on the desired yaw moment and the maximum yaw moment; and controlling the steering system, drive system, and braking system of the current vehicle. The technical solution of this invention achieves coordinated control between the vehicle's steering system, braking system, and drive system, improving the stability of vehicle control.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, and in particular to a vehicle control method, device, electronic equipment, and program product. Background Technology

[0002] The vehicle's steer-by-wire system eliminates the mechanical connection between the steering wheel and the steering wheels, and transmits and executes steering commands through electronic signals, providing ample room for high-level autonomous driving and optimization of vehicle dynamics.

[0003] However, in existing vehicle steer-by-wire systems, the steering system often operates independently from the chassis systems such as the braking system and the drive system, lacking unified coordination and control. This can easily lead to conflicting control objectives, such as steering intervention and differential braking intervention canceling each other out, failing to form a combined control force, and potentially even inducing vehicle instability. Summary of the Invention

[0004] This invention provides a vehicle control method, device, electronic equipment, and program product, which realizes coordinated control between the vehicle's steering system, braking system, and drive system, thereby improving the stability of vehicle control.

[0005] According to one aspect of the present invention, a vehicle control method is provided, the method comprising: The upper-level decision-maker estimates the desired yaw moment and desired longitudinal force of the current vehicle based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, reference steering wheel feedback torque, and roll angle constraint, and feeds it back to the lower-level distributor. The lower-level distributor calculates the maximum available longitudinal force for each wheel of the current vehicle based on the current vehicle speed, the current yaw rate, the current center of gravity sideslip angle, the current braking deceleration, and the current vertical load. The lower-level distributor calculates the maximum yaw moment of the current vehicle based on the current vehicle speed, the current yaw rate, the current front and rear wheel rotation angles, the current lateral angular velocity, and the current wheel center distance. The lower distributor determines the target longitudinal force based on the desired longitudinal force and the maximum available longitudinal force, and determines the target front and rear wheel steering angles, target braking force, and target driving force based on the desired yaw moment and the maximum yaw moment. The lower-level distributor controls the steering system, drive system, and braking system of the current vehicle using the target longitudinal force, the target front and rear wheel steering angles, the target braking force, and the target driving force.

[0006] According to another aspect of the present invention, a vehicle control device is provided, the device comprising: an upper-level decision-maker and a lower-level distributor; wherein, The upper-level decision-maker is used to estimate the desired yaw moment and desired longitudinal force of the current vehicle based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, reference steering wheel feedback torque and roll angle constraint, and feed it back to the lower-level distributor. The lower-level distributor is used to calculate the maximum available longitudinal force of each wheel of the current vehicle based on the current vehicle speed, the current yaw rate, the current center of gravity sideslip angle, the current braking deceleration, and the current vertical load. The lower-level distributor is used to calculate the maximum yaw moment of the current vehicle based on the current vehicle speed, the current yaw rate, the current front and rear wheel rotation angles, the current lateral angular velocity, and the current distance between the wheel centers of the vehicle. The lower-level distributor is used to determine the target longitudinal force based on the desired longitudinal force and the maximum available longitudinal force, and to determine the target front and rear wheel steering angles, target braking force, and target driving force based on the desired yaw moment and the maximum yaw moment. The lower-level distributor is used to control the steering system, drive system, and braking system of the current vehicle using the target longitudinal force, the target front and rear wheel steering angles, the target braking force, and the target driving force.

[0007] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the vehicle control method according to any embodiment of the present invention.

[0008] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the vehicle control method according to any embodiment of the present invention.

[0009] According to another aspect of the present invention, a computer program product is provided, the computer program product comprising a computer program that, when executed by a processor, implements the vehicle control method according to any embodiment of the present invention.

[0010] The technical solution of this invention estimates the desired yaw moment and desired longitudinal force of the current vehicle through an upper-level decision-maker, and calculates the maximum available longitudinal force and maximum yaw moment of each wheel of the current vehicle through a lower-level distributor. Based on the desired longitudinal force and the maximum available longitudinal force, the target longitudinal force is determined. Based on the desired yaw moment and the maximum yaw moment, the target front and rear wheel steering angles, target braking force, and target driving force are determined. This allows for the control of the current vehicle's steering system, braking system, and drive system, achieving coordinated control among the vehicle's steering system, braking system, and drive system, and improving the stability of vehicle control.

[0011] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a flowchart of a vehicle control method provided according to Embodiment 1 of the present invention; Figure 2 This is a flowchart of a vehicle control method provided according to Embodiment 2 of the present invention; Figure 3 This is a system architecture diagram of a vehicle control device provided according to Embodiment 2 of the present invention; Figure 4 This is a schematic diagram of the vehicle control method provided in Embodiment 2 of the present invention; Figure 5 This is a schematic diagram of the vehicle control method provided in Embodiment 2 of the present invention; Figure 6 This is a schematic diagram of the vehicle control method provided in Embodiment 2 of the present invention; Figure 7 This is a schematic diagram of the structure of a vehicle control device according to Embodiment 3 of the present invention; Figure 8 This is a schematic diagram of the structure of an electronic device that implements the vehicle control method of this invention. Detailed Implementation

[0014] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0015] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0016] Example 1 Figure 1 This is a flowchart illustrating a vehicle control method according to Embodiment 1 of the present invention. This embodiment is applicable to controlling a vehicle's steer-by-wire system. The method can be executed by a vehicle control device, which can be implemented in hardware and / or software and can be configured within an electronic device that carries vehicle control functions.

[0017] See Figure 1 The vehicle control method shown includes: S101. The upper-level decision-maker estimates the desired yaw moment and desired longitudinal force of the current vehicle based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, reference steering wheel feedback torque, and roll angle constraint, and feeds it back to the lower-level decision-maker.

[0018] The upper-level decision-maker estimates the desired yaw moment and desired longitudinal force that the current vehicle is expected to achieve. The lower-level distributor converts the desired yaw moment and desired longitudinal force output by the upper-level decision-maker into the target longitudinal force, target front and rear wheel steering angles, target braking force, and target driving force of the current vehicle, and controls the steering system, drive system, and braking system of the current vehicle.

[0019] The current vehicle is using a steer-by-wire system. The current vehicle speed is the speed of the current vehicle along its forward direction. The current yaw rate is the angular velocity of the current vehicle rotating about its vertical axis. The current yaw rate characterizes the rate of change of the vehicle's orientation. The current center-of-gravity deflection angle is the angle between the direction of the current vehicle's center-of-gravity velocity and the vehicle's longitudinal axis. The current center-of-gravity deflection angle characterizes the current vehicle's orientation. The current vehicle speed, current yaw rate, and current center-of-gravity deflection angle characterize the current vehicle's state. The reference steering wheel feedback torque is the feedback torque generated based on the driver's steering wheel input. The reference steering wheel feedback torque characterizes the driver's driving intention. The roll angle constraint characterizes the vehicle's roll angle. The roll angle is the tilt angle of the current vehicle about its longitudinal axis. The roll angle characterizes the degree of roll of the current vehicle.

[0020] The expected yaw moment is the desired value of the current vehicle's yaw moment, obtained by the upper decision-maker based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, reference steering wheel feedback torque, and roll angle constraints. The expected yaw moment is used to control the current vehicle's rotation about its vertical axis, thereby controlling the vehicle's heading. The expected longitudinal force is the desired value of the current vehicle's longitudinal force, obtained by the upper decision-maker based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, reference steering wheel feedback torque, and roll angle constraints. The expected longitudinal force is used to control the current vehicle's acceleration, deceleration, or speed maintenance, thereby controlling the vehicle's forward or backward movement.

[0021] Specifically, the upper-level decision-maker uses the Model Predictive Control (MPC) algorithm to estimate the desired yaw moment and desired longitudinal force of the current vehicle based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, reference steering wheel feedback torque, and roll angle constraints, and then feeds it back to the lower-level decision-maker.

[0022] In an optional embodiment of the present invention, before estimating the desired yaw moment and desired longitudinal force of the current vehicle based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, reference steering wheel feedback torque, and roll angle constraint by the upper-level decision-maker, the method further includes: estimating the estimated self-centering moment of the current vehicle on the current road surface based on the current vehicle speed, current steering wheel angle, and current yaw rate; calculating the reference steering wheel angle standard deviation and reference yaw rate peak value based on the reference steering wheel angle and reference yaw rate over a reference time period; identifying the reference steering wheel angle standard deviation and reference yaw rate peak value using a driving style recognition model and outputting a driving style coefficient; and using the driving style coefficient to synthesize the estimated self-centering moment, damping moment, and Coulomb friction to determine the reference steering wheel feedback torque.

[0023] The current road surface refers to the road surface the vehicle is currently traveling on. The estimated return torque is the return torque estimated based on the current vehicle speed, current steering wheel angle, and current yaw rate. The reference time period is the time period used to estimate the driver's driving style coefficient. The reference steering wheel angle is the steering wheel angle collected within the reference time period. The reference yaw rate is the yaw rate collected within the reference time period. There must be at least two reference steering wheel angles and reference yaw rates. The standard deviation of the reference steering wheel angle is the standard deviation of each reference steering wheel angle within the reference time period. The standard deviation of the reference steering wheel angle is used to characterize the degree of fluctuation in driver operation. It can be understood as the driver's operating characteristic. The peak reference yaw rate is the maximum yaw rate within the reference time period. The peak reference yaw rate is used to characterize the driver's willingness to control the current vehicle to its limits. It can be understood as the vehicle's dynamic response characteristic based on driver operation.

[0024] A driving style recognition model is used to identify a driver's driving style. The input data for the driving style recognition model are the standard deviation of the reference steering wheel angle and the peak value of the reference yaw rate; the output is a driving style coefficient. For example, the driving style recognition model can be a fuzzy logic classifier. The driving style coefficient is used to characterize the driver's driving style. For example, the coefficient range can be between [0.8, 1.2]. A driving style coefficient K > 1 can be interpreted as an "aggressive" driving style, enhancing road feel; a driving style coefficient K < 1 can be interpreted as a "mild" driving style, reducing road feel.

[0025] Damping torque is used to characterize the internal friction or hydraulic damping of the steering system of a current vehicle. Coulomb friction is used to characterize the dry friction between mechanical parts of a current vehicle. Damping torque and Coulomb friction torque are the inherent friction forces of a current vehicle. Damping torque and Coulomb friction torque can be determined through prior testing of the current vehicle.

[0026] Specifically, using an online learning rack force observer, the recursive least squares method is employed to estimate the estimated return torque of the current vehicle on the current road surface based on the current vehicle speed, current steering wheel angle, and current yaw rate.

[0027] Specifically, the standard deviation of each reference steering wheel angle within the reference time period is calculated to obtain the reference steering wheel angle standard deviation. The peak value of each reference yaw rate within the reference time period can also be calculated to obtain the reference yaw rate peak value.

[0028] Specifically, the reference steering wheel angle standard deviation and the reference yaw rate peak value are input into the driving style recognition model, and the driving style coefficient is output.

[0029] Specifically, the road feel synthesizer uses the following road feel synthesis formula and driving style coefficient to synthesize the estimated self-centering torque, damping torque, and Coulomb friction to determine the reference steering wheel feedback torque.

[0030] For example, the following formula can be used to characterize the road feel synthesis formula: ; In the formula, The reference steering wheel feedback torque is represented by K, which is the driving style coefficient. To estimate the restoring torque; This is the damping torque; This is the Coulomb friction force.

[0031] This solution takes into account the vehicle's condition, the actual interaction force between the tires and the ground under different road conditions, and the individual driving styles of different drivers in the process of generating the reference steering wheel feedback torque, thereby improving the accuracy of the reference steering wheel feedback torque and thus enhancing the human-machine interaction experience between the driver and the vehicle.

[0032] S102. Using the lower-level distributor, calculate the maximum available longitudinal force for each wheel of the current vehicle based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, current braking deceleration, and current vertical load.

[0033] Current braking deceleration is the longitudinal acceleration of the vehicle during braking. Current vertical load is the normal force exerted by a single tire of the vehicle when it is in contact with the ground. Maximum available longitudinal force is the maximum available longitudinal force that the tires of the vehicle can provide under the current vertical load. The maximum available longitudinal force is used to ensure the safety of the vehicle during driving.

[0034] Specifically, through the lower-level allocator, a pre-trained maximum available longitudinal force prediction model is used to calculate the maximum available longitudinal force of each wheel of the current vehicle based on the current vehicle speed, current yaw rate, current sideslip angle, current braking deceleration, and current vertical load. The input data for the maximum available longitudinal force prediction model are the current vehicle speed, current yaw rate, current sideslip angle, current braking deceleration, and current vertical load, and the output is the maximum available longitudinal force of each wheel of the current vehicle. For example, the maximum available longitudinal force prediction model can be a neural network model.

[0035] In an optional embodiment of the present invention, the maximum available longitudinal force of each wheel of the current vehicle is calculated by the lower layer distributor based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, current braking deceleration, and current vertical load. This includes: calculating the dynamic vertical force of each wheel of the current vehicle based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, current braking deceleration, and current vertical load by the lower layer distributor; and calculating the maximum available longitudinal force of each wheel of the current vehicle based on the dynamic vertical force of each wheel, the road adhesion coefficient, and the adhesion utilization rate by the lower layer distributor.

[0036] Dynamic vertical force is the normal force exerted by a single tire on the ground when the vehicle is in contact with the ground, taking into account its motion. In contrast, current vertical load is the sum of the normal forces exerted by a single tire on the vehicle on the ground. Current vertical load includes both static and dynamic vertical forces. Essentially, dynamic vertical force is the static vertical load that occurs when the vehicle is in motion, taking into account the load transfer caused by its motion.

[0037] The coefficient of adhesion (CTA) is the ratio between the maximum net force that a single tire of a vehicle can generate and the current vertical load. It characterizes the maximum force that the current road surface can withstand to prevent tire slippage. The CTA also characterizes the grip between a single tire of a vehicle and the current road surface. It reflects the physical properties of the contact surface between the tire and the road surface.

[0038] Adhesion utilization rate describes the proportion of actual grip exerted by a single tire of a vehicle relative to the maximum grip available on the current road surface. Additional utilization rate reflects how close a single tire of a vehicle is to its slip limit.

[0039] Specifically, the lower-level distributor uses a dynamic vertical force estimation model to calculate the dynamic vertical force of each wheel of the vehicle based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, current braking deceleration, and current vertical load. The lower-level distributor then uses the maximum available longitudinal force calculation formula to calculate the maximum available longitudinal force of each wheel of the vehicle based on the dynamic vertical force of each wheel, the road surface adhesion coefficient, and adhesion utilization rate.

[0040] For example, the following formula can be used to represent the formula for calculating the maximum available longitudinal force: ; In the formula, The maximum available longitudinal force; The road surface adhesion coefficient; For dynamic vertical force; For adhesion utilization rate.

[0041] This solution introduces dynamic vertical force as an intermediate variable, decomposing the originally uninterpretable end-to-end mapping into two stages with clear physical meaning. This allows the upper-level controller to directly obtain the real-time distribution of vertical loads on each wheel, thereby achieving explicit monitoring of the vehicle load transfer status and improving the system's debuggability and maintainability.

[0042] S103. Calculate the maximum yaw moment of the current vehicle using the lower-level distributor based on the current vehicle speed, current yaw rate, current front and rear wheel angles, current lateral angular velocity, and current wheel center distance.

[0043] The current front wheel steering angle is the angle between the center lines of the front and rear axles of the current vehicle and the longitudinal axis of the vehicle body. The current lateral angular velocity is the rate of rotation of the current vehicle's center of gravity relative to the longitudinal axis of the vehicle body. The current wheel center distance is the distance between the current vehicle's center of gravity and the front and rear axles. The current wheel center distance is used to determine the lever arm of the torque generated by the front and rear wheels of the current vehicle.

[0044] The maximum yaw moment is the maximum torque exerted by the tires on the vehicle's heading. The maximum yaw moment determines the speed at which the vehicle's heading adjusts. It also determines the vehicle's ability to resist lateral disturbances.

[0045] Specifically, the lower-level allocator uses a pre-trained maximum yaw moment estimation model to calculate the maximum yaw moment of the current vehicle based on the current vehicle speed, current yaw rate, current front and rear wheel angles, current lateral angular velocity, and current wheel center distance. The input data for the maximum yaw moment estimation model are the current vehicle speed, current yaw rate, current front and rear wheel angles, current lateral angular velocity, and current wheel center distance; the output of the maximum yaw moment estimation model is the maximum yaw moment. For example, the maximum yaw moment estimation model can be a neural network model.

[0046] S104. Through the lower-level distributor, determine the target longitudinal force based on the desired longitudinal force and the maximum available longitudinal force, and determine the target front and rear wheel steering angles, target braking force, and target driving force based on the desired yaw moment and the maximum yaw moment.

[0047] The target longitudinal force is the target for adjusting the longitudinal force of the current vehicle. The target front and rear wheel steering angles are the target for adjusting the front and rear wheel steering angles of the current vehicle. The target braking force is the target for adjusting the braking force of the current vehicle. The target driving force is the target for adjusting the driving force of the current vehicle. The target braking force and target driving force are used to compensate for the target front and rear wheel steering angles.

[0048] Specifically, through the lower-level distributor, a target longitudinal force output model is used to output the target longitudinal force based on the desired longitudinal force and the maximum available longitudinal force. A target yaw output model is used to output the target front and rear wheel angles, target braking force, and target driving force based on the desired yaw moment and the maximum yaw moment. The input data for the target longitudinal force output model are the desired longitudinal force and the maximum available longitudinal force, and the output is the target longitudinal force. The input data for the target yaw output model are the desired yaw moment and the maximum yaw moment, and the output is the target front and rear wheel angles, target braking force, and target driving force. For example, the target longitudinal force output model and the target yaw output model can be neural network models.

[0049] In an alternative embodiment of the invention, a desired longitudinal force and a maximum available longitudinal force are compared; a target longitudinal force is determined based on the smaller of the desired longitudinal force and the maximum available longitudinal force.

[0050] Specifically, the desired longitudinal force and the maximum available longitudinal force can be compared. The smaller of the desired longitudinal force and the maximum available longitudinal force can be selected as the target longitudinal force.

[0051] This solution improves the efficiency of determining the target longitudinal force by selecting the smaller value between the desired longitudinal force and the maximum available longitudinal force, thus ensuring the safety, stability, and comfort of vehicle operation.

[0052] In an optional embodiment of the present invention, determining the target front and rear wheel steering angles, target braking force, and target driving force based on the desired yaw moment and the maximum yaw moment includes: comparing the desired yaw moment and the maximum yaw moment; if the desired yaw moment is less than or equal to the maximum yaw moment, then the desired yaw moment is determined as the target front wheel yaw moment, and the target front and rear wheel steering angles are calculated based on the target front wheel yaw moment; if the desired yaw moment is greater than the maximum yaw moment, then the maximum yaw moment is determined as the target front wheel yaw moment, and the target front and rear wheel steering angles are calculated based on the target front wheel yaw moment; and the target braking force or target driving force of each wheel of the current vehicle is calculated based on the target moment difference between the desired yaw moment and the target front wheel yaw moment.

[0053] The target front wheel yaw moment is the adjustment target for the current front wheel yaw moment of the vehicle. The target moment difference is the difference between the desired yaw moment and the maximum yaw moment (or the target front wheel yaw moment).

[0054] Specifically, the expected yaw moment and the maximum yaw moment are compared. If the expected yaw moment is less than or equal to the maximum yaw moment, then the expected yaw moment is determined as the target front wheel yaw moment. The target front and rear wheel steering angles are then calculated based on the target front wheel yaw moment. If the expected yaw moment is greater than the maximum yaw moment, then the maximum yaw moment is determined as the target front wheel yaw moment. The target front and rear wheel steering angles are then calculated based on the target front wheel yaw moment. The difference between the expected yaw moment and the target front wheel yaw moment can be calculated to obtain the target torque difference. This target torque difference is then determined as the target braking force or target driving force for each wheel of the current vehicle.

[0055] This solution prioritizes using the active steering of the front wheels to generate yaw moment for steering control of the current vehicle. When the active steering of the front wheels reaches its physical limit and is insufficient to generate the required yaw moment, the target braking force or target driving force is used in a coordinated manner to compensate for the yaw moment of the front wheels, thereby improving the coordination of the current vehicle's steer-by-wire system control.

[0056] S105. Through the lower-level distributor, the steering system, drive system and braking system of the current vehicle are controlled by the target longitudinal force, target front and rear wheel steering angle, target braking force and target driving force.

[0057] A steer-by-wire system may include a steering system, a drive system, and a braking system. The steering system controls the direction of the vehicle. The drive system controls the acceleration of the vehicle and assists in steering. The braking system controls the deceleration of the vehicle and assists in steering.

[0058] Specifically, the lower-level distributor controls the vehicle's steering system using the target front and rear wheel angles. It also controls the vehicle's drive system using target longitudinal force and target driving force, and its braking system using target longitudinal force and target braking force.

[0059] The technical solution of this invention estimates the desired yaw moment and desired longitudinal force of the current vehicle through an upper-level decision-maker, and calculates the maximum available longitudinal force and maximum yaw moment of each wheel of the current vehicle through a lower-level distributor. Based on the desired longitudinal force and the maximum available longitudinal force, the target longitudinal force is determined. Based on the desired yaw moment and the maximum yaw moment, the target front and rear wheel steering angles, target braking force, and target driving force are determined. This allows for the control of the current vehicle's steering system, braking system, and drive system, achieving coordinated control among the vehicle's steering system, braking system, and drive system, and improving the stability of vehicle control.

[0060] Example 2 Figure 2This is a flowchart of a vehicle control method provided in Embodiment 2 of the present invention. Based on the above embodiments, this embodiment further adds the following to the existing method of "controlling the current vehicle using target longitudinal force, target front and rear wheel steering angles, target braking force, and target driving force through a lower-level distributor": "When a system fault is detected in the target system, the system fault of the target system is reviewed to obtain a target fault review result; wherein, the target system includes a steering system, a drive system, and a braking system; if the target fault review result indicates a fault exists, a fault-tolerant control mode is adopted to replace the target system; if the target fault review result indicates no fault exists, the target system is restored within a first preset time period." By using different processing methods based on the target fault review result when a system fault is detected in the target system, the fault tolerance of vehicle control is improved. It should be noted that parts not detailed in this embodiment can be found in the descriptions of other embodiments.

[0061] See Figure 2 The vehicle control method shown includes: S201. Through the upper-level decision-maker, based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, reference steering wheel feedback torque, and roll angle constraint, estimate the desired yaw moment and desired longitudinal force of the current vehicle.

[0062] S202. Using the lower-level distributor, calculate the maximum available longitudinal force for each wheel of the current vehicle based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, current braking deceleration, and current vertical load.

[0063] S203. Through the lower-level distributor, calculate the maximum yaw moment of the current vehicle based on the current vehicle speed, current yaw rate, current front and rear wheel rotation angles, current lateral angular velocity, and current wheel center distance.

[0064] S204. Through the lower-level distributor, determine the target longitudinal force based on the desired longitudinal force and the maximum available longitudinal force, and determine the target front and rear wheel steering angles, target braking force, and target driving force based on the desired yaw moment and the maximum yaw moment.

[0065] S205. Through the lower-level distributor, using the target longitudinal force, target front and rear wheel steering angles, target braking force, and target driving force, while controlling the steering system, drive system, and braking system of the current vehicle, when a system fault is detected in the target system, the system fault of the target system is reviewed to obtain the target fault review result of the target system.

[0066] The target system is a subsystem within the steer-by-wire system that exhibits a system fault. For example, the target system includes the steering system, drive system, and braking system. The target fault verification result is the verification result of the system faults within the target system. For example, the target fault verification result may include whether a fault exists or not.

[0067] Specifically, when a system fault is detected in the target system, other subsystems in the steer-by-wire system can be isolated to verify whether a system fault exists in the target system, and the target fault verification result of the target system can be obtained.

[0068] S206. If the target fault verification result indicates that a fault exists, then the fault-tolerant control mode is adopted to replace the target system.

[0069] The fault-tolerant control mode is a mode in which other subsystems in the steer-by-wire system are used to replace the target system.

[0070] Specifically, if the target fault verification result indicates that a fault exists, then other subsystems in the current vehicle's steer-by-wire system are used to replace the target system.

[0071] S207. If the target fault verification result is that there is no fault, then the target system shall be restored within the first preset time period.

[0072] The first preset time period is the time period for restoring the target system. The first preset time period can be preset and adjusted by technical personnel based on experience.

[0073] Specifically, if the target fault verification result is that there is no fault, then the target system will be restored within the first preset time period.

[0074] In an optional embodiment of the present invention, while restoring the target system within a first preset time period, the method further includes: collecting the target measured value of the target system within a second preset time period; comparing the target measured value with a reference estimated value to obtain a target comparison result; and detecting the system stability of the target system based on the target comparison result to obtain a target stability detection result.

[0075] The second preset time period is the period for conducting stability testing on the target system. This second preset time period can be set and adjusted by technical personnel based on experience. Optionally, the second preset time period can be greater than or equal to the first preset time period.

[0076] The target measured value is the measured value of the target system during the recovery process. The target measured value represents the actual state of the target system. The reference estimate is the estimated value of the target system under normal conditions. The reference estimate is used to characterize the normal state of the target system.

[0077] The target comparison result is the comparison between the measured target value and the reference estimate. The target comparison result is used to characterize the degree of closeness between the measured target value and the reference estimate.

[0078] The target stability test results are used to characterize the stability of the target system during the recovery process. For example, the target stability test results may include whether the target system is stable or unstable during the recovery process.

[0079] Specifically, while restoring the target system within the first preset time period, the measured values ​​of the target system can be collected within a second preset time period. The similarity between the measured values ​​and the reference estimated values ​​can be calculated to obtain a target comparison result. If the target comparison result is greater than or equal to a preset similarity threshold, the target system is determined to be stable during the restoration process; if the target comparison result is less than the preset similarity threshold, the target system is determined to be unstable during the restoration process. The preset similarity threshold is a pre-defined minimum similarity value between the measured values ​​and the reference estimated values ​​when the target system is stable during the restoration process. The preset similarity threshold can be preset and adjusted by technical personnel based on experience.

[0080] This solution detects the system stability of the target system by comparing the measured value and the reference estimated value of the target system during the first preset time period while restoring the target system. This results in a target stability detection result, thereby improving the stability of the target system during the recovery process and enhancing its fault tolerance.

[0081] The technical solution of this invention, when a system fault is detected in the target system, verifies the system fault of the target system to obtain the target fault verification result. If the target fault verification result indicates that a fault exists, a fault-tolerant control mode is adopted to replace the target system. If the target fault verification result indicates that no fault exists, the target system is restored within a first preset time period. This realizes that when a system fault is detected in the target system, different processing methods are adopted based on the target fault verification result of the target system, thereby improving the fault tolerance of vehicle control.

[0082] In existing technologies, steer-by-wire systems eliminate the mechanical connection between the steering wheel and the steering wheels, transmitting and executing steering commands via electronic signals, thus providing ample room for advanced autonomous driving and vehicle dynamics optimization. However, existing steer-by-wire systems still suffer from the following significant drawbacks: First, the road feel feedback lacks realism and personalization. Specifically, existing technologies mostly use fixed torque feedback models, making it difficult to accurately reproduce the real interaction force between the tire and the ground under different road surfaces (such as low-adhesion ice or high-adhesion asphalt). The relationship between feedback torque and vehicle speed and steering angle is simplistic and cannot adapt to the personalized preferences of different drivers (such as some preferring a light feel while others prefer a stable feel), resulting in a poor human-machine interaction experience.

[0083] Secondly, the coordination of stability control is insufficient. Specifically, under extreme conditions (such as high-speed emergency obstacle avoidance or cornering on low-traction surfaces), the active steering system often operates independently from the chassis systems such as braking and drive, lacking unified and coordinated control. This can easily lead to conflicting control objectives, such as steering intervention and differential braking intervention canceling each other out, failing to form a combined control force, and potentially even inducing vehicle instability.

[0084] Finally, the fault tolerance is limited and the cost is high. To ensure safety, existing solutions mostly adopt simple hardware redundancy (such as dual motors or dual ECUs), which significantly increases system cost and complexity. At the same time, their fault tolerance strategies are mostly designed for single points of failure, lacking effective comprehensive diagnosis and response mechanisms for multiple and concurrent failures that may occur in sensors, actuators, and communication systems, and the system's functional safety level needs to be improved.

[0085] Therefore, there is an urgent need for an intelligent steer-by-wire solution that can achieve realistic and personalized road feel, integrated chassis control, and high reliability and low cost tolerance. This solution aims to improve the realism and personalization of road feel feedback, enhance the vehicle's collaborative stability control under extreme conditions, and achieve cost-effective active fault-tolerant control, thereby comprehensively improving the vehicle's handling, safety, and driving experience.

[0086] Based on the above embodiments, the present invention provides a preferred embodiment of a vehicle control device. For example... Figure 3 As shown, the vehicle control device includes: a road feel simulation feedback unit, a steering execution unit, a vehicle state perception unit, an electronic control unit, and a chassis cooperative system (i.e., a steer-by-wire system).

[0087] The electronic control unit includes: a personalized road feel feedback module, a multi-system cooperative stability control module, and a multi-system cooperative stability control module. The personalized road feel feedback module generates personalized reference steering wheel feedback torque based on vehicle status and driver input. The multi-system cooperative stability control module calculates coordinated steering and drive / braking control commands based on vehicle status and driver intent. The hierarchical active fault-tolerant control module performs system status monitoring, fault diagnosis, and control reconfiguration under fault conditions.

[0088] Among them, such as Figure 4As shown, the execution logic of the personalized road feel feedback module is as follows: Based on vehicle state signals (including current steering wheel angle, current vehicle speed, and current yaw rate) and driver operations (including reference steering wheel angle and reference yaw rate over a reference time period), a rack force observer based on an online learning algorithm estimates the vehicle state signals in real time to obtain the estimated self-centering torque acting on the front wheels. The estimated self-centering torque, damping torque, and Coulomb friction are added together to form the basic feedback torque. Through a driver style online recognition submodule, a fuzzy logic classifier (i.e., a driving style recognition model) is used to analyze the driver's steering operation feature signals in real time (i.e., feature extraction of the reference directional deflection angle standard deviation and reference yaw rate peak over a reference time period), and outputs a personalized adjustment coefficient (i.e., a driving style coefficient) to dynamically adjust the strength and gradient of the basic feedback torque, thus obtaining the road feel motor control signal (i.e., the reference steering wheel feedback torque).

[0089] Specifically, the implementation process of personalized road feel feedback includes: A rack force observer takes the current steering wheel angle, current vehicle speed, and current yaw rate as inputs, and uses an online learning algorithm based on recursive least squares to dynamically update model parameters to accurately estimate the estimated self-centering torque under different road surface adhesions. The driver style recognition submodule takes the standard deviation of the reference steering wheel angle and the peak value of the reference yaw rate within a time window (i.e., the reference time period) as features, inputs them into a pre-trained fuzzy logic classifier (i.e., the driving style recognition model), and outputs a personalized adjustment coefficient K (i.e., the driving style coefficient) between 0.8 and 1.2. If the identified style is "aggressive," the output K>1, enhancing road feel; if the identified style is "mild," the output K<1, weakening road feel. The final reference steering wheel feedback torque = K × (estimated self-centering torque + damping torque + Coulomb friction).

[0090] Among them, such as Figure 5 As shown, the multi-system collaborative stability control module adopts a hierarchical control architecture. The upper-level decision-maker uses a model predictive control algorithm to calculate a generalized desired yaw moment and desired longitudinal force in real time based on the vehicle's state (including current vehicle speed, current yaw rate, and current center of gravity sideslip angle) and driver intent (i.e., reference steering wheel feedback torque), while also incorporating roll stability constraints (i.e., roll angle constraints). The lower-level distributor receives the output from the upper-level decision-maker and, through a constrained optimization algorithm, dynamically distributes the generalized desired yaw moment and desired longitudinal force to the front-wheel active steering system and the distributed drive / braking system, ensuring that the output of each actuator is within its physical limits.

[0091] Specifically, the multi-system collaborative stability control module's workflow during high-speed emergency obstacle avoidance includes: the upper-level decision-maker plans a safe obstacle avoidance path for the current vehicle based on its current speed, yaw rate, center of gravity sideslip angle, and reference steering wheel feedback torque, and calculates the desired yaw rate required to track this path. Simultaneously, considering the possibility of rollover during emergency steering, a roll angle constraint is added to the upper-level decision-maker's optimization objective to prevent rollover. Based on the desired yaw rate and roll angle constraint, the upper-level controller solves for a generalized desired yaw moment ΔM and desired longitudinal force F that enable the vehicle to stably track the safe obstacle avoidance path. x The inputs to the lower-level distributor are the generalized desired yaw moment ΔM and the desired longitudinal force F. x The optimal target longitudinal force is calculated based on the current vertical load of each tire of the vehicle, the road adhesion coefficient, and the adhesion utilization rate.

[0092] The specific processing flow is as follows: (1) Based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, current braking deceleration and current vertical load, the dynamic vertical force of the four wheels of the current vehicle is estimated in real time, and the maximum available longitudinal force of each tire of the current vehicle is calculated based on the road adhesion coefficient and adhesion utilization rate. The smaller value between the expected longitudinal force and the maximum available longitudinal force can be determined as the target longitudinal force. (2) Based on the efficiency-first allocation strategy, in most cases, the front wheel active steering is used first to generate yaw moment for compensation; when the steering reaches the physical limit of the front wheel active steering or is insufficient to generate the required yaw moment, a slight target driving force or target braking force is applied to the inner rear wheel in a coordinated manner to generate a supplementary yaw moment. (3) The distributor sends the calculated target front and rear wheel steering angles to the front and rear wheel steering actuator motors, and sends the calculated target driving force / target braking force of the current vehicle wheels to the drive controller / brake controller to execute the operation command to change the vehicle state, and feeds back to the upper decision-maker to form a closed-loop control.

[0093] Among them, such as Figure 6 As shown, the execution logic of the hierarchical active fault-tolerant control module is as follows: An improved adaptive extended Kalman filter algorithm is used to perform multi-source information fusion estimation of the system's critical states. When a sensor malfunctions, the estimated value replaces the output of the faulty sensor. When a serious fault is diagnosed in the steering system of the steer-by-wire system, the controller switches to the differential steering fault-tolerant control mode. By sending commands to the distributed drive / braking system, a difference in driving / braking force is generated between the left and right wheels of the vehicle, thereby generating a substitute yaw moment to maintain the vehicle's steering capability.

[0094] Specifically, the process of the hierarchical active fault-tolerant control module handling steering motor failures includes: the system diagnoses steering system failure by monitoring abnormalities in motor current and steering angle feedback. The fault-tolerant control module immediately activates the differential steering fault-tolerant control mode. The desired yaw torque output by the original path tracking controller is transmitted to the distributed drive system. The distributed drive system precisely generates the required yaw torque by controlling the drive motors of the left and right wheels to output different torques, enabling the vehicle to maintain lane position or safely pull over even without mechanical steering. When verification confirms that there is no fault (transient interference), the system executes the following step-by-step data recovery process: First, the signal previously marked as "temporarily unreliable" is re-added to the control loop. Simultaneously, the reference estimate is retained as a comparison verification signal and continuously monitored for 200ms to ensure stability. If the system has not yet entered the fault-tolerant control mode (still in normal mode but with a fault flag), the flag is directly cleared, and the original controller (i.e., personalized road feel feedback + multi-system collaborative stability control) continues to be used. If the system has briefly entered a fault-tolerant control mode, a smooth transition must be performed, linearly increasing from 0 to 1, with a transition time (i.e., the first preset time period) of approximately 50ms. This avoids sudden changes in control values ​​that could cause steering wheel vibration or vehicle yaw. Finally, the "false alarm fault" event is written to the system log, including a timestamp, signal name, instantaneous outlier value, and the result of the target fault review. This information is then uploaded to the cloud via the vehicle network or displayed on the dashboard as "System self-check recovered, no fault."

[0095] This solution achieves a leap from a one-size-fits-all approach to personalized road feedback through a closed-loop "perception-recognition-adaptation" process, significantly enhancing the driver's situational awareness and confidence, resulting in an excellent human-machine interaction experience. Furthermore, by coordinating lateral, longitudinal, and vertical control, the steering, drive, and braking systems are integrated into a single control unit. This maximizes tire force utilization under extreme conditions, effectively preventing vehicle instability, improving active safety, and significantly enhancing overall vehicle stability. Simultaneously, a fault-tolerant system based on intelligent algorithms and backed by hardware redundancy is constructed. This ensures high system reliability while significantly reducing costs associated with excessive hardware redundancy, facilitating large-scale commercialization and ensuring a balance between functional safety and economic benefits. Finally, this system can accurately execute path-tracking commands issued by the autonomous driving system and autonomously maintain vehicle stability during execution. It is a key underlying technology for achieving Level 3 and above autonomous driving, providing a high-performance execution interface for autonomous driving.

[0096] Example 3 Figure 7This is a schematic diagram of a vehicle control device provided in Embodiment 3 of the present invention. This embodiment of the present invention is applicable to controlling the steer-by-wire system of a vehicle. The device can execute vehicle control methods and can be implemented in hardware and / or software. The device can be configured in an electronic device that carries vehicle control functions.

[0097] See Figure 7 The vehicle control device shown includes: an upper-level decision-maker 701 and a lower-level distributor 702; wherein, the upper-level decision-maker is used to estimate the desired yaw moment and desired longitudinal force of the current vehicle based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, reference steering wheel feedback torque, and roll angle constraint, and feeds it back to the lower-level distributor; the lower-level distributor is used to calculate the maximum available longitudinal force of each wheel of the current vehicle based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, current braking deceleration, and current vertical load; the lower-level distributor is used to calculate the maximum available longitudinal force of each wheel of the current vehicle based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, current braking deceleration, and current vertical load; the lower-level distributor is used to calculate the maximum available longitudinal force of each wheel of the current vehicle based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, current braking deceleration, and current vertical load. The system calculates the maximum yaw moment of the current vehicle based on the speed, current yaw rate, current front and rear wheel angles, current lateral angular velocity, and current wheel center distance. The lower-level distributor determines the target longitudinal force based on the desired longitudinal force and the maximum available longitudinal force, and determines the target front and rear wheel angles, target braking force, and target driving force based on the desired yaw moment and the maximum yaw moment. The lower-level distributor controls the steering system, drive system, and braking system of the current vehicle using the target longitudinal force, the target front and rear wheel angles, the target braking force, and the target driving force.

[0098] The technical solution of this invention estimates the desired yaw moment and desired longitudinal force of the current vehicle through an upper-level decision-maker, and calculates the maximum available longitudinal force and maximum yaw moment of each wheel of the current vehicle through a lower-level distributor. Based on the desired longitudinal force and the maximum available longitudinal force, the target longitudinal force is determined. Based on the desired yaw moment and the maximum yaw moment, the target front and rear wheel steering angles, target braking force, and target driving force are determined. This allows for the control of the current vehicle's steering system, braking system, and drive system, achieving coordinated control among the vehicle's steering system, braking system, and drive system, and improving the stability of vehicle control.

[0099] In an optional embodiment of the present invention, the device further includes: an estimated self-centering torque estimation module, used to estimate the estimated self-centering torque of the current vehicle on the current road surface based on the current vehicle speed, current steering wheel angle, and current yaw rate before estimating the desired yaw torque and desired longitudinal force of the current vehicle through the upper-level decision-maker based on the current vehicle speed, current steering wheel angle, current center of gravity sideslip angle, reference steering wheel feedback torque, and roll angle constraint; a reference data calculation module, used to calculate the reference steering wheel angle standard deviation and reference yaw rate peak value based on the reference steering wheel angle and reference yaw rate over a reference time period; a driving style coefficient output module, used to identify the reference steering wheel angle standard deviation and the reference yaw rate peak value using a driving style recognition model, and output a driving style coefficient; and a reference steering wheel feedback torque determination module, used to synthesize the estimated self-centering torque, damping torque, and Coulomb friction force using the driving style coefficient to determine the reference steering wheel feedback torque.

[0100] In an optional embodiment of the present invention, the lower-level distributor is specifically configured to: calculate the dynamic vertical force of each wheel of the current vehicle based on the current vehicle speed, the current yaw rate, the current center of gravity sideslip angle, the current braking deceleration, and the current vertical load; and calculate the maximum available longitudinal force of each wheel of the current vehicle based on the dynamic vertical force of each wheel, the road surface adhesion coefficient, and the adhesion utilization rate.

[0101] In an optional embodiment of the invention, the lower-level distributor is specifically configured to: compare the desired longitudinal force and the maximum available longitudinal force; and determine the target longitudinal force based on the smaller of the desired longitudinal force and the maximum available longitudinal force.

[0102] In an optional embodiment of the present invention, the lower-level distributor is specifically configured to: compare the desired yaw moment with the maximum yaw moment; if the desired yaw moment is less than or equal to the maximum yaw moment, then determine the desired yaw moment as the target front wheel yaw moment, and calculate the target front and rear wheel steering angles based on the target front wheel yaw moment; if the desired yaw moment is greater than the maximum yaw moment, then determine the maximum yaw moment as the target front wheel yaw moment, and calculate the target front and rear wheel steering angles based on the target front wheel yaw moment; and calculate the target braking force or target driving force of each wheel of the current vehicle based on the target moment difference between the desired yaw moment and the target front wheel yaw moment.

[0103] In an optional embodiment of the present invention, the device further includes: a fault system verification module, configured to, while controlling the current vehicle through the lower-level distributor using the target longitudinal force, the target front and rear wheel steering angles, the target braking force, and the target driving force, verify the system fault of the target system when a system fault is detected in the target system, and obtain a target fault verification result of the target system; wherein the target system includes a steering system, a drive system, and a braking system; a fault-tolerant control module, configured to, if the target fault verification result indicates the presence of a fault, use a fault-tolerant control mode to replace the target system; and a target system recovery module, configured to, if the target fault verification result indicates the absence of a fault, restore the target system within a first preset time period.

[0104] In an optional embodiment of the present invention, the apparatus further includes: a target measured value acquisition module, used to acquire target measured values ​​of the target system in a second preset time period while the target system is being restored in a first preset time period; a target comparison result generation module, used to compare the target measured values ​​with reference estimated values ​​to obtain a target comparison result; and a target system stability detection module, used to detect the system stability of the target system based on the target comparison result to obtain a target stability detection result.

[0105] The vehicle control device provided in the embodiments of the present invention can execute the vehicle control method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0106] The acquisition, storage, and application of data such as current vehicle speed, current yaw rate, current center of gravity sideslip angle, reference steering wheel feedback torque, roll angle constraint, current braking deceleration, current vertical load, current front and rear wheel rotation angles, current lateral angular velocity, and current vehicle wheel center distance in the technical solutions of this invention comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0107] Example 4 Figure 8 A schematic diagram of an electronic device 800 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0108] like Figure 8 As shown, the electronic device 800 includes at least one processor 801 and a memory, such as a read-only memory (ROM) 802 and a random access memory (RAM) 803, communicatively connected to the at least one processor 801. The memory stores computer programs executable by the at least one processor. The processor 801 can perform various appropriate actions and processes based on the computer program stored in the ROM 802 or loaded into the RAM 803 from storage unit 808. The RAM 803 can also store various programs and data required for the operation of the electronic device 800. The processor 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0109] Multiple components in electronic device 800 are connected to I / O interface 805, including: input unit 806, such as keyboard, mouse, etc.; output unit 807, such as various types of displays, speakers, etc.; storage unit 808, such as disk, optical disk, etc.; and communication unit 809, such as network card, modem, wireless transceiver, etc. Communication unit 809 allows electronic device 800 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0110] Processor 801 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 801 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 801 performs the various methods and processes described above, such as vehicle control methods.

[0111] In some embodiments, the vehicle control method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 808. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 800 via ROM 802 and / or communication unit 809. When the computer program is loaded into RAM 803 and executed by processor 801, one or more steps of the vehicle control method described above may be performed. Alternatively, in other embodiments, processor 801 may be configured to perform the vehicle control method by any other suitable means (e.g., by means of firmware).

[0112] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0113] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0114] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0115] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0116] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0117] A computing system can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system. It addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability.

[0118] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0119] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A vehicle control method, characterized in that, The method includes: The upper-level decision-maker estimates the desired yaw moment and desired longitudinal force of the current vehicle based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, reference steering wheel feedback torque, and roll angle constraint, and feeds it back to the lower-level distributor. The lower-level distributor calculates the maximum available longitudinal force for each wheel of the current vehicle based on the current vehicle speed, the current yaw rate, the current center of gravity sideslip angle, the current braking deceleration, and the current vertical load. The lower-level distributor calculates the maximum yaw moment of the current vehicle based on the current vehicle speed, the current yaw rate, the current front and rear wheel rotation angles, the current lateral angular velocity, and the current wheel center distance. The lower distributor determines the target longitudinal force based on the desired longitudinal force and the maximum available longitudinal force, and determines the target front and rear wheel steering angles, target braking force, and target driving force based on the desired yaw moment and the maximum yaw moment. The lower-level distributor controls the steering system, drive system, and braking system of the current vehicle using the target longitudinal force, the target front and rear wheel steering angles, the target braking force, and the target driving force.

2. The method according to claim 1, characterized in that, Before estimating the desired yaw moment and desired longitudinal force of the current vehicle through the upper-level decision-maker based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, reference steering wheel feedback torque, and roll angle constraints, the process further includes: Based on the current vehicle speed, current steering wheel angle, and current yaw rate, estimate the estimated self-centering torque of the current vehicle on the current road surface; Calculate the standard deviation of the reference steering wheel angle and the peak value of the reference yaw rate based on the reference steering wheel angle and reference yaw rate over the reference time period. A driving style recognition model is used to identify the standard deviation of the reference steering wheel angle and the peak value of the reference yaw rate, and output the driving style coefficient. Using the driving style coefficient, the estimated self-centering torque, damping torque, and Coulomb friction are synthesized to determine the reference steering wheel feedback torque.

3. The method according to claim 1, characterized in that, The process involves using a lower-level distributor to calculate the maximum available longitudinal force on each wheel of the current vehicle based on the current vehicle speed, current yaw rate, current sideslip angle, current braking deceleration, and current vertical load. The lower-level distributor calculates the dynamic vertical force of each wheel of the current vehicle based on the current vehicle speed, the current yaw rate, the current center of gravity sideslip angle, the current braking deceleration, and the current vertical load. The lower distributor calculates the maximum available longitudinal force of each wheel of the current vehicle based on the dynamic vertical force of each wheel, the road adhesion coefficient, and the adhesion utilization rate.

4. The method according to claim 1, characterized in that, Determining the target longitudinal force based on the desired longitudinal force and the maximum available longitudinal force includes: The desired longitudinal force and the maximum available longitudinal force are compared; The target longitudinal force is determined based on the smaller of the desired longitudinal force and the maximum available longitudinal force.

5. The method according to claim 1, characterized in that, The step of determining the target front and rear wheel steering angles, target braking force, and target driving force based on the expected yaw moment and the maximum yaw moment includes: The desired yaw moment and the maximum yaw moment are compared; If the desired yaw moment is less than or equal to the maximum yaw moment, then the desired yaw moment is determined as the target front wheel yaw moment, and the target front and rear wheel steering angles are calculated based on the target front wheel yaw moment. If the desired yaw moment is greater than the maximum yaw moment, then the maximum yaw moment is determined as the target front wheel yaw moment, and the target front and rear wheel steering angles are calculated based on the target front wheel yaw moment. Based on the target moment difference between the desired yaw moment and the target front wheel yaw moment, the target braking force or target driving force of each wheel of the current vehicle is calculated.

6. The method according to claim 1, characterized in that, While controlling the current vehicle through the lower-level distributor using the target longitudinal force, the target front and rear wheel steering angles, the target braking force, and the target driving force, the method also includes: When a system fault is detected in the target system, the system fault of the target system is reviewed to obtain the target fault review result of the target system; wherein, the target system includes a steering system, a drive system and a braking system; If the target fault verification result indicates that a fault exists, then a fault-tolerant control mode is adopted to replace the target system; If the target fault verification result is that there is no fault, then the target system will be restored within the first preset time period.

7. The method according to claim 6, characterized in that, In addition to restoring the target system within the first preset time period, the method also includes: Collect the target measured values ​​of the target system during a second preset time period; The measured value of the target is compared with the reference estimated value to obtain the target comparison result; Based on the target comparison results, the system stability of the target system is tested to obtain the target stability test results.

8. A vehicle control device, characterized in that, The device includes: an upper-level decision-maker and a lower-level allocator; wherein... The upper-level decision-maker is used to estimate the desired yaw moment and desired longitudinal force of the current vehicle based on the current vehicle speed, current yaw rate, current center of gravity sideslip angle, reference steering wheel feedback torque and roll angle constraint, and feed it back to the lower-level distributor. The lower-level distributor is used to calculate the maximum available longitudinal force of each wheel of the current vehicle based on the current vehicle speed, the current yaw rate, the current center of gravity sideslip angle, the current braking deceleration, and the current vertical load. The lower-level distributor is used to calculate the maximum yaw moment of the current vehicle based on the current vehicle speed, the current yaw rate, the current front and rear wheel rotation angles, the current lateral angular velocity, and the current distance between the wheel centers of the vehicle. The lower-level distributor is used to determine the target longitudinal force based on the desired longitudinal force and the maximum available longitudinal force, and to determine the target front and rear wheel steering angles, target braking force, and target driving force based on the desired yaw moment and the maximum yaw moment. The lower-level distributor is used to control the steering system, drive system, and braking system of the current vehicle using the target longitudinal force, the target front and rear wheel steering angles, the target braking force, and the target driving force.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the vehicle control method according to any one of claims 1-7.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the data storage method according to any one of claims 1-7.

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