Vehicle control method, system, equipment and medium

Abstract

The invention relates to the technical field of automobile motion control, in particular to a vehicle control method, system and equipment and a medium. Combining the motion state parameter information and the driving state information to determine a theoretical yaw velocity value of the vehicle, calculating a target yaw velocity of the vehicle in a preset motion mode, calculating an additional yaw moment in a preset motion scene according to the target yaw velocity, and calculating a longitudinal moment of the vehicle according to the driving state parameter information, and according to the additional yawing moment and the longitudinal moment, the driving torque of each wheel in the vehicle is calculated, and according to the driving torque of each wheel, the corresponding wheel is controlled to be driven. In the application, the additional yaw moment is calculated according to the running mode and the running scene of the vehicle, so that the vehicle is adaptively matched with different operation characteristics according to different running modes and running scenes, and the performance of the vehicle in different running modes and running scenes is controlled, thereby realizing a more personalized manipulation feeling and a more excellent driving experience.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile motion control, and in particular to a vehicle control method, system, equipment and medium. Background Art

[0002] A vehicle with a distributed drive system means that the four wheels of the vehicle can be driven independently. Distributed drive vehicles have the advantages of good passability, high efficiency, and good maneuverability. However, the control of distributed drive vehicles is also difficult. The distributed drive system improves the maneuverability of the vehicle mainly by applying an additional yaw moment, and the purpose of the additional yaw moment control is to make the vehicle produce a reasonable target yaw rate. In general vehicle control systems, the additional yaw moment is mainly calculated based on the deviation between the target yaw rate and the actual yaw rate information, using feedback algorithms such as PID, but its target is the inherent maneuvering characteristics of the vehicle, and it is impossible to consider the needs of different driving modes and the differences in different driving scenarios, and it is impossible to achieve personalized manipulation. Summary of the invention

[0003] In view of this, embodiments of the present invention provide a vehicle control method, system, device and medium to solve the problem that personalized manipulation cannot be achieved in different driving modes and different driving scenarios.

[0004] In a first aspect, an embodiment of the present invention provides a vehicle control method, comprising: Acquire the motion state parameter information and driving state parameter information of each wheel of the vehicle in real time; Determine a theoretical yaw rate value of the vehicle by combining the motion state parameter information and the driving state information, and calculate a target yaw rate of the vehicle in a preset motion mode; Acquiring a preset motion scene of the vehicle, and calculating an additional yaw moment under the preset motion scene according to the target yaw angular velocity; The longitudinal moment of the vehicle is calculated according to the driving state parameter information, the driving torque of each wheel in the vehicle is calculated according to the additional yaw moment and the longitudinal moment, and the corresponding wheel is controlled to be driven according to the driving torque of each wheel.

[0005] In a second aspect, an embodiment of the present invention provides a vehicle control system, including: An acquisition module, used to acquire the motion state parameter information and driving state parameter information of each wheel of the vehicle in real time; A first calculation module, used for determining a theoretical yaw rate value of the vehicle by combining the motion state parameter information with the driving state information, and calculating a target yaw rate of the vehicle in a preset motion mode; A second calculation module is used to obtain a preset motion scene of the vehicle, and calculate an additional yaw moment under the preset motion scene according to the target yaw angular velocity; The third calculation module is used to calculate the longitudinal torque of the vehicle according to the driving state parameter information, calculate the driving torque of each wheel in the vehicle according to the additional yaw torque and the longitudinal torque, and control the driving of the corresponding wheel according to the driving torque of each wheel.

[0006] In a third aspect, an embodiment of the present invention provides a computer device, comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the vehicle control method as described in the first aspect when executing the computer program.

[0007] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the vehicle control method as described in the first aspect is implemented.

[0008] Compared with the prior art, the present invention has the following beneficial effects: The motion state parameter information and driving state parameter information of each wheel of the vehicle are obtained in real time, and the theoretical yaw rate value of the vehicle is determined by combining the motion state parameter information and the driving state information, and the target yaw rate of the vehicle in the preset motion mode is calculated, and the preset motion scene of the vehicle is obtained. According to the target yaw rate, the additional yaw moment in the preset motion scene is calculated, and according to the driving state parameter information, the longitudinal moment of the vehicle is calculated, and according to the additional yaw moment and the longitudinal moment, the driving torque of each wheel in the vehicle is calculated, and according to the driving torque of each wheel, the corresponding wheel is controlled to drive. In the present application, the additional yaw moment is calculated according to the operation mode and operation scene of the vehicle, so that the vehicle can adaptively match different operating characteristics according to different operation modes and operation scenes, and control the performance of the vehicle in different operation modes and operation scenes, so as to achieve a more personalized control feeling and a better driving experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0010] Figure 1 is a flow chart of a vehicle control method provided in Embodiment 1 of the present invention; Figure 2is a flow chart of a vehicle control method provided in Embodiment 2 of the present invention; Figure 3 is a flow chart of a vehicle control method provided in Embodiment 3 of the present invention; Figure 4 is a flow chart of a vehicle control method provided by Embodiment 4 of the present invention; Figure 5 is a flow chart of a vehicle control method provided in Embodiment 5 of the present invention; Figure 6 is a flow chart of a vehicle control method provided in Embodiment 6 of the present invention; Figure 7 is a structural block diagram of a vehicle control system provided by Embodiment 7 of the present invention; Figure 8 It is a structural diagram of a computer device provided in Embodiment 8 of the present invention. DETAILED DESCRIPTION

[0011] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0012] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, systems, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0013] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0014] It should also be understood that the term "and / or" used in the present description and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0015] As used in the present specification and the appended claims, the term "if" may be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" may be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]", depending on the context.

[0016] In addition, in the description of the present specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0017] References to "one embodiment" or "some embodiments" etc. described in the present specification mean that one or more embodiments of the present invention include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0018] It should be understood that the order of execution of the steps in the following embodiments does not imply a precedence of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0019] In order to illustrate the technical solution of the present invention, specific embodiments are provided below for illustration.

[0020] See also Figure 1 , is a flow chart of a vehicle control method provided by Embodiment 1 of the present invention, such as Figure 1 As shown, the vehicle control method may include the following steps.

[0021] S101: Acquire motion state parameter information and driving state parameter information of each wheel of the vehicle in real time.

[0022] In step S101, the motion state parameter information and driving state parameter information of each wheel of the vehicle are obtained in real time, wherein the motion state parameter information includes the wheel speed information, lateral acceleration information, longitudinal acceleration information and actual yaw angular velocity information of each wheel, and the driving state parameter information includes the accelerator pedal information, brake pedal information and steering wheel information.

[0023] In this embodiment, when acquiring the motion state parameter information and driving state parameter information of each wheel of the vehicle in real time, corresponding sensors can be used to collect and acquire the information, such as using a wheel speed sensor to collect the wheel speed of each wheel, using an acceleration sensor to collect the lateral acceleration and longitudinal acceleration, using a yaw angular velocity sensor to collect the actual yaw angular velocity, using an accelerator pedal sensor to collect accelerator pedal information, using a brake pedal sensor to collect brake pedal information, and using a steering wheel angle sensor to collect steering wheel information.

[0024] In this embodiment, the motion state parameter information and driving state parameter information of each wheel of the vehicle are acquired in real time, so as to control the vehicle in real time using the parameter information acquired in real time.

[0025] S102: Determine a theoretical yaw rate value of the vehicle by combining the motion state parameter information and the driving state information, and calculate a target yaw rate of the vehicle in a preset motion mode.

[0026] In step S102, the theoretical yaw rate value of the vehicle is determined by combining the motion state parameter information and the driving state information, and the target yaw rate of the vehicle in a preset motion mode is calculated, wherein the theoretical yaw rate value does not change with changes in motion scenes and driving conditions, that is, the yaw rate under steady-state operating characteristics, and the target yaw rate varies with different motion modes.

[0027] In this embodiment, when determining the theoretical yaw rate value of the vehicle in combination with the motion state parameter information and the driving state information, the vehicle speed and mass can be estimated according to a preset first vehicle control reference model, and the theoretical yaw rate can be calculated according to the vehicle speed and mass, wherein the preset first vehicle control reference model is a pre-trained model for estimating the vehicle speed and mass, and the input of the preset first vehicle control reference model is the motion state reference information and the driving state reference information, and the output can be the vehicle speed, mass, center of mass sideslip angle, road slope and road adhesion coefficient.

[0028] See also Figure 2 , is a flow chart of a vehicle control method provided by Embodiment 2 of the present invention, wherein step S102 combines the motion state parameter information and the driving state information to determine the theoretical yaw rate value of the vehicle, including: S201: estimating the longitudinal speed and mass of the vehicle according to the wheel speed information, the lateral acceleration information and the longitudinal acceleration information of each wheel to obtain the estimated longitudinal speed and estimated mass of the vehicle; S202: Calculate a theoretical yaw rate value of the vehicle according to the estimated longitudinal velocity, the estimated mass and the steering wheel angle.

[0029] In this embodiment, the motion state parameter information includes wheel speed information, lateral acceleration information and longitudinal acceleration information of each wheel, and the driving parameter information includes the steering wheel angle. According to the wheel speed information, lateral acceleration information and longitudinal acceleration information of each wheel, the longitudinal speed and mass of the vehicle are estimated to obtain the estimated longitudinal speed and estimated mass of the vehicle, wherein when estimating the longitudinal speed and mass of the vehicle, the above-mentioned preset first vehicle control reference model is used for estimation, the wheel speed information, lateral acceleration information and longitudinal acceleration information of each wheel are input into the preset first vehicle control reference model, and the estimated longitudinal speed and estimated mass are output.

[0030] The theoretical yaw rate of the vehicle is calculated based on the estimated longitudinal velocity, estimated mass and steering wheel angle. The calculation formula of the theoretical yaw rate is as follows: in, is the theoretical yaw angular velocity, To estimate the longitudinal velocity, is the wheelbase of the vehicle, is the stability factor of the vehicle, is the front wheel turning angle of the vehicle, where There is a corresponding relationship with the steering wheel angle, which can be obtained by looking up the table.

[0031] in, The stability factor is calculated as follows: in, is the estimated mass of the vehicle, is the distance from the vehicle's center of mass to the front wheel, is the distance from the vehicle's center of mass to the rear wheel, is the front axle cornering stiffness of the vehicle, is the rear axle cornering stiffness of the vehicle, is the wheelbase of the vehicle.

[0032] It should be noted that the front axle cornering stiffness of the vehicle, the rear axle cornering stiffness of the vehicle and the wheelbase of the vehicle can be collected.

[0033] See also Figure 3 , is a flow chart of a vehicle control method provided by Embodiment 3 of the present invention, wherein step S102 calculates the target yaw rate of the vehicle in a preset motion mode, including: S301: Determine an adjustment coefficient of the vehicle according to a preset motion mode and an estimated longitudinal speed; S302: Calculate a target yaw rate according to the adjustment coefficient and the theoretical yaw rate.

[0034] In this embodiment, the vehicle adjustment coefficient is determined according to the preset motion mode and the estimated longitudinal speed, wherein the adjustment coefficient corresponds to the motion mode and the longitudinal speed, and therefore, the corresponding adjustment coefficient can be determined by looking up the table according to the preset motion mode and the estimated longitudinal speed. The target yaw rate is calculated according to the adjustment coefficient and the theoretical yaw rate.

[0035] It should be noted that the preset sports mode may include a comfort mode and a sports mode, among which the comfort mode is a mode in which the vehicle steering is slow and stable, that is, a mode corresponding to a small change rate of the steering wheel angle, and the sports mode is a mode in which the vehicle steering is sensitive and aggressive, that is, a mode corresponding to a large change rate of the steering wheel angle. In this embodiment, the mode in which the change rate of the steering wheel angle is less than the preset change rate may be determined as the comfort mode, and the mode in which the change rate of the steering wheel angle is not less than the preset change rate may be determined as the sports mode.

[0036] In this embodiment, when determining the adjustment coefficient of the vehicle according to the preset motion mode and the estimated longitudinal speed, when the preset motion mode is the comfort mode, the adjustment coefficient is less than 1, and when the preset motion mode is the sport mode, the adjustment coefficient is greater than 1. The target yaw rate is calculated as follows: in, is the target yaw rate, is the theoretical yaw angular velocity, is the adjustment coefficient.

[0037] In this embodiment, the corresponding adjustment coefficient is determined according to the preset sport mode, so that personalized vehicle steady-state operating characteristics in different sport modes can be achieved.

[0038] S103: Obtain a preset motion scene of the vehicle, and calculate an additional yaw moment in the preset motion scene according to a target yaw angular velocity.

[0039] In step S103, a preset motion scene of the vehicle is obtained, and an additional yaw moment under the preset motion scene is calculated according to the target yaw angular velocity, wherein the preset motion scene includes a cornering motion scene and a cornering motion scene, and the additional yaw moment is the sum of the lateral moments of each vehicle.

[0040] In this embodiment, the additional yaw moment under the preset motion scene is calculated according to the target yaw angular velocity, wherein the preset motion scene includes a bend motion scene and an exit bend motion scene, and the bend motion scene and the exit bend motion scene can be determined according to the steering wheel angle and the rate of change of the steering wheel angle. For example, when the steering wheel angle is negative and the rate of change of the steering wheel angle is less than zero, or the steering wheel angle is positive and the rate of change of the steering wheel angle is greater than zero, the motion scene is determined to be a bend motion scene, and when the steering wheel angle is negative and the rate of change of the steering wheel angle is greater than zero, or the steering wheel angle is positive and the rate of change of the steering wheel angle is less than zero, the motion scene is determined to be an exit bend motion scene.

[0041] It should be noted that when calculating the additional yaw moment under the preset motion scenario based on the target yaw angular velocity, different preset motion scenarios correspond to different additional yaw moment feedforward values, that is, the transient characteristic response of the vehicle is different, which increases the stability of the vehicle when entering and exiting a corner.

[0042] See also Figure 4 , is a flow chart of a vehicle control method provided by a fourth embodiment of the present invention, wherein step S103 calculates an additional yaw moment under a preset motion scenario according to a target yaw angular velocity, including: S401: Calculating a yaw rate deviation according to target yaw rate and actual yaw rate information; S402: Calculate an additional yaw moment of the vehicle according to a preset motion scenario and a yaw angular velocity deviation.

[0043] In this embodiment, the motion state parameter information also includes actual yaw rate information, that is, the yaw rate acquired in real time during the vehicle driving process. The yaw rate deviation is calculated according to the target yaw rate and the actual yaw rate information. The calculation formula of the yaw rate deviation is as follows: in, is the yaw rate deviation, is the actual yaw angular velocity, is the target yaw rate.

[0044] According to the preset motion scene and the yaw rate deviation, the additional yaw moment of the vehicle is calculated. The calculation formula of the additional yaw moment is as follows: in, is the feedforward value of the additional yaw moment, is the additional yaw moment feedforward value, , , is the calibration parameter, is the yaw rate deviation at time t.

[0045] It should be noted that there is a mapping relationship between the feedforward value of the additional yaw moment and the motion scene, the road adhesion coefficient, and the longitudinal speed of the vehicle. The corresponding feedforward value of the additional yaw moment is obtained by looking up the table according to the corresponding preset motion scene, the estimated longitudinal speed, and the estimated road adhesion coefficient. Among them, the estimated longitudinal speed and the estimated road adhesion coefficient can be estimated according to the motion state parameters and the driving state parameters.

[0046] See also Figure 5 , is a flow chart of a vehicle control method provided by Embodiment 5 of the present invention, wherein step S402 calculates an additional yaw moment of the vehicle according to a preset motion scene and a yaw angular velocity deviation, including: S501: estimating the road adhesion coefficient of the vehicle according to the wheel speed information, the lateral acceleration information, and the longitudinal acceleration information of each wheel to obtain an estimated road adhesion coefficient; S502: determining a feedforward value of an additional yaw moment according to an estimated road adhesion coefficient, an estimated longitudinal speed, and a preset motion scenario; S503: Calculate the additional yaw moment of the vehicle according to the feedforward value of the additional yaw moment and the yaw rate deviation.

[0047] In this embodiment, the road adhesion coefficient of the vehicle is estimated according to the wheel speed information, lateral acceleration information, and longitudinal acceleration information of each wheel to obtain an estimated road adhesion coefficient. When estimating, the estimation is performed according to a preset second vehicle control reference model, that is, the wheel speed information, lateral acceleration information, and longitudinal acceleration information of each wheel are input into the preset second vehicle control reference model, and the estimated road adhesion coefficient is output. According to the estimated road adhesion coefficient, the estimated longitudinal speed, and the preset motion scene, a table is looked up to determine the feedforward value of the additional yaw moment. There is a mapping relationship between the feedforward value of the additional yaw moment and the motion scene, the road adhesion coefficient, and the longitudinal speed of the vehicle.

[0048] It should be noted that the sports scenarios include cornering and exiting. In the cornering scenario, the feedforward value of the additional yaw torque is relatively large, which increases the vehicle's transient handling characteristic response and reduces the driver's steering pressure when cornering. In the exiting scenario, the feedforward value of the additional yaw torque is relatively small, which reduces the vehicle's transient handling characteristic response, avoids yaw overshoot when exiting the corner, and increases the exiting stability.

[0049] See also Figure 6 , is a flow chart of a vehicle control method provided by Embodiment 6 of the present invention. Before step S103 calculates the additional yaw moment under the preset motion scene according to the target yaw angular velocity, it also includes: S601: estimating the center of mass sideslip angle of the vehicle according to the wheel speed information, the lateral acceleration information, and the longitudinal acceleration information of each wheel to obtain an estimated center of mass sideslip angle; S602: When the estimated center of mass sideslip angle and the estimated road adhesion coefficient meet preset conditions, calculate an additional yaw moment under a preset motion scenario.

[0050] In this embodiment, the vehicle's center of mass sideslip angle is estimated according to the wheel speed information, lateral acceleration information, and longitudinal acceleration information of each wheel to obtain an estimated center of mass sideslip angle. That is, the wheel speed information, lateral acceleration information, and longitudinal acceleration information of each wheel are input into a preset third vehicle control reference model, and the estimated center of mass sideslip angle is output. The additional yaw moment is constrained according to the estimated center of mass sideslip angle and the estimated road adhesion coefficient, that is, when calculating the additional yaw moment, the estimated road adhesion coefficient must be less than the preset maximum road adhesion coefficient, and the estimated center of mass sideslip angle must be less than the preset eccentric angle. When the estimated road adhesion coefficient is not less than the preset maximum road adhesion coefficient, or the estimated center of mass sideslip angle is not less than the preset eccentric angle, the additional yaw moment is recalculated to determine that when calculating the additional yaw moment, the estimated center of mass sideslip angle and the estimated road adhesion coefficient meet the preset conditions, that is, the estimated road adhesion coefficient must be less than the preset maximum road adhesion coefficient, and the estimated center of mass sideslip angle must be less than the preset eccentric angle.

[0051] S104: Calculate the longitudinal moment of the vehicle according to the driving state parameter information, calculate the driving torque of each wheel in the vehicle according to the additional yaw moment and the longitudinal moment, and control the driving of the corresponding wheel according to the driving torque of each wheel.

[0052] In step S104, the longitudinal moment of the vehicle is calculated according to the driving state parameter information, wherein the longitudinal moment is the moment in the longitudinal direction of the vehicle, that is, the sum of the moments in the longitudinal direction of each wheel. The driving torque of each wheel in the vehicle is calculated according to the additional yaw moment and the longitudinal moment, that is, the additional yaw moment is distributed to the lateral direction of each wheel, and the longitudinal moment is distributed to the longitudinal direction of each wheel, and the corresponding wheel is controlled to be driven according to the driving torque of each wheel.

[0053] In this embodiment, the longitudinal torque of the vehicle is calculated based on the driving state parameter information, that is, the longitudinal torque of the vehicle is calculated based on the accelerator pedal parameter information and the brake pedal parameter information, and the driving torque of each wheel in the vehicle is calculated based on the additional yaw moment and the longitudinal torque. The lateral driving torque and longitudinal driving torque to be allocated to each wheel are calculated based on the additional yaw moment and the longitudinal torque, so as to control the driving motor on the corresponding wheel to drive the wheel with the corresponding driving torque, thereby realizing personalized control of the wheel.

[0054] Optionally, the driving torque of each wheel in the vehicle is calculated according to the additional yaw moment and the longitudinal moment, including: The longitudinal moment of the vehicle is calculated based on the pedal information, and the driving torque of each wheel is calculated based on the additional yaw moment and the longitudinal moment, with the goal of maximizing the vehicle's driving efficiency and the vehicle's road adhesion.

[0055] In this embodiment, the driving parameter information also includes pedal information, that is, the longitudinal moment of the vehicle is calculated according to the accelerator pedal parameter information and the brake pedal parameter information, and the driving torque of each wheel is calculated according to the additional yaw moment and the longitudinal moment, with the maximum driving efficiency of the vehicle and the maximum road adhesion of the vehicle as the goal. That is, after the longitudinal moment and the additional yaw moment are distributed to each wheel, the driving efficiency and road adhesion of the vehicle are calculated to determine whether the driving efficiency of the vehicle has reached the maximum value and whether the road adhesion of the vehicle has reached the maximum value. If the driving efficiency of the vehicle has reached the maximum value and the road adhesion of the vehicle has reached the maximum value, the driving torque of each wheel is determined as the final driving torque, and the driving motor on each wheel is driven according to the corresponding driving torque. If the driving efficiency of the vehicle has not reached the maximum value or the road adhesion of the vehicle has not reached the maximum value, the driving torque on each wheel is redistributed until the driving efficiency of the vehicle is maximized and the road adhesion of the vehicle is maximized.

[0056] It should be noted that if the driving efficiency of the vehicle and the road adhesion of the vehicle cannot reach the maximum value at the same time, the driving efficiency of the vehicle can be used as a target to calculate the driving torque of each wheel. Alternatively, the driving torque of each wheel can be calculated with the maximum road adhesion of the vehicle as a target. This embodiment does not limit this.

[0057] The motion state parameter information and driving state parameter information of each wheel of the vehicle are obtained in real time, and the theoretical yaw rate value of the vehicle is determined by combining the motion state parameter information and the driving state information, and the target yaw rate of the vehicle in the preset motion mode is calculated, and the preset motion scene of the vehicle is obtained. According to the target yaw rate, the additional yaw moment in the preset motion scene is calculated, and according to the driving state parameter information, the longitudinal moment of the vehicle is calculated, and according to the additional yaw moment and the longitudinal moment, the driving torque of each wheel in the vehicle is calculated, and according to the driving torque of each wheel, the corresponding wheel is controlled to drive. In the present application, the additional yaw moment is calculated according to the operation mode and operation scene of the vehicle, so that the vehicle can adaptively match different operating characteristics according to different operation modes and operation scenes, and control the performance of the vehicle in different operation modes and operation scenes, so as to achieve a more personalized control feeling and a better driving experience.

[0058] See also Figure 7 , Figure 7is a structural block diagram of a vehicle control system provided by Embodiment 7 of the present invention. For the sake of convenience, only the parts related to the embodiment of the present application are shown. Figure 7 The vehicle control system 70 includes an acquisition module 71 , a first calculation module 72 , a second calculation module 73 , and a third calculation module 74 .

[0059] The acquisition module 71 is used to acquire the motion state parameter information and driving state parameter information of each wheel of the vehicle in real time.

[0060] The first calculation module 72 is used to determine the theoretical yaw rate value of the vehicle by combining the motion state parameter information and the driving state information, and calculate the target yaw rate of the vehicle in a preset motion mode.

[0061] The second calculation module 73 is used to obtain a preset motion scene of the vehicle and calculate an additional yaw moment in the preset motion scene according to a target yaw angular velocity.

[0062] The third calculation module 74 is used to calculate the longitudinal moment of the vehicle according to the driving state parameter information, calculate the driving torque of each wheel in the vehicle according to the additional yaw moment and the longitudinal moment, and control the driving of the corresponding wheel according to the driving torque of each wheel.

[0063] Optionally, the first calculation module 72 includes: The estimation unit is used to estimate the longitudinal speed and mass of the vehicle according to the wheel speed information, lateral acceleration information and longitudinal acceleration information of each wheel, so as to obtain the estimated longitudinal speed and estimated mass of the vehicle.

[0064] The first calculation unit is used to calculate a theoretical yaw rate value of the vehicle according to the estimated longitudinal speed, the estimated mass and the steering wheel angle.

[0065] Optionally, the first calculation module 72 includes: The determination unit is used to determine the adjustment coefficient of the vehicle according to the preset motion mode and the estimated longitudinal speed.

[0066] The second calculation unit is used to calculate the target yaw rate according to the adjustment coefficient and the theoretical yaw rate.

[0067] Optionally, the second calculation module 73 includes: The third calculation unit is used to calculate the yaw rate deviation according to the target yaw rate and the actual yaw rate information.

[0068] The fourth calculation unit is used to calculate the additional yaw moment of the vehicle according to the preset motion scene and the yaw angular velocity deviation.

[0069] Optionally, the fourth calculation unit includes: The estimation subunit is used to estimate the road adhesion coefficient of the vehicle according to the wheel speed information, lateral acceleration information and longitudinal acceleration information of each wheel to obtain the estimated road adhesion coefficient.

[0070] The determination subunit is used to determine a feedforward value of the additional yaw moment according to the estimated road adhesion coefficient, the estimated longitudinal speed and the preset motion scenario.

[0071] The calculation subunit is used to calculate the additional yaw moment of the vehicle according to the feedforward value of the additional yaw moment and the yaw angular velocity deviation.

[0072] Optionally, the vehicle control system 70 further includes: The estimation module is used to estimate the vehicle's center of mass sideslip angle according to the wheel speed information, lateral acceleration information, and longitudinal acceleration information of each wheel to obtain an estimated center of mass sideslip angle.

[0073] The judgment module is used to calculate the additional yaw moment under a preset motion scenario when the estimated center of mass sideslip angle and the estimated road adhesion coefficient meet preset conditions.

[0074] Optionally, the third calculation module 74 includes: The fifth calculation unit is used to calculate the longitudinal moment of the vehicle according to the pedal information, and calculate the driving torque of each wheel according to the additional yaw moment and the longitudinal moment with the goal of maximizing the driving efficiency of the vehicle and the road adhesion of the vehicle.

[0075] It should be noted that the information interaction, execution process and other contents between the above-mentioned modules are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0076] Figure 8 Schematic diagram of the structure of a computer device provided by Embodiment 8 of the present invention. Figure 8 As shown, the computer device of this embodiment includes: at least one processor ( Figure 8 Only one is shown in the figure), a memory, and a computer program stored in the memory and executable on at least one processor, wherein when the processor executes the computer program, the steps in any of the above-mentioned vehicle control method embodiments are implemented.

[0077] The computer device may include, but is not limited to, a processor and a memory. Those skilled in the art will appreciate that Figure 8 This is merely an example of a computer device and does not constitute a limitation on the computer device. The computer device may include more or fewer components than those shown in the figure, or a combination of certain components, or different components. For example, it may also include a network interface, a display screen, and an input device.

[0078] The processor may be a CPU, or other general-purpose processors, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0079] The memory includes a readable storage medium, an internal memory, etc., wherein the internal memory may be the memory of a computer device, and the internal memory provides an environment for the operation of the operating system and computer-readable instructions in the readable storage medium. The readable storage medium may be a hard disk of a computer device, and in other embodiments, it may also be an external storage device of the computer device, for example, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the computer device. Further, the memory may also include both an internal storage unit of the computer device and an external storage device. The memory is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of a computer program, etc. The memory may also be used to temporarily store data that has been output or is to be output.

[0080] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned device can refer to the corresponding process in the above-mentioned method embodiment, which will not be repeated here. If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned method embodiment can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device capable of carrying computer program code, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0081] The present application implements all or part of the processes in the above-mentioned embodiment method, and may also be completed through a computer program product. When the computer program product runs on a computer device, the computer device can implement the steps in the above-mentioned method embodiment when executing the computer program product.

[0082] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0083] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0084] In the embodiments provided in the present application, it should be understood that the disclosed devices / computer equipment and methods can be implemented in other ways. For example, the device / computer equipment embodiments described above are only schematic, for example, the division of modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0085] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0086] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A vehicle control method, characterized in that: include: Acquire the motion state parameter information and driving state parameter information of each wheel of the vehicle in real time; Determine a theoretical yaw rate value of the vehicle by combining the motion state parameter information and the driving state information, and calculate a target yaw rate of the vehicle in a preset motion mode; Acquiring a preset motion scene of the vehicle, and calculating an additional yaw moment under the preset motion scene according to the target yaw angular velocity; The longitudinal moment of the vehicle is calculated according to the driving state parameter information, the driving torque of each wheel in the vehicle is calculated according to the additional yaw moment and the longitudinal moment, and the corresponding wheel is controlled to be driven according to the driving torque of each wheel.

2. The vehicle control method according to claim 1, characterized in that: The motion state parameter information includes wheel speed information, lateral acceleration information and longitudinal acceleration information of each wheel, and the driving parameter information includes a steering wheel angle; Combining the motion state parameter information with the driving state information to determine a theoretical yaw rate value of the vehicle includes: estimating the longitudinal speed and mass of the vehicle according to the wheel speed information of each wheel, the lateral acceleration information and the longitudinal acceleration information to obtain an estimated longitudinal speed and an estimated mass of the vehicle; A theoretical yaw rate value of the vehicle is calculated according to the estimated longitudinal speed, the estimated mass and the steering wheel angle.

3. The vehicle control method according to claim 2, characterized in that: The calculating the target yaw rate of the vehicle in the preset motion mode includes: determining an adjustment factor for the vehicle based on the preset motion pattern and the estimated longitudinal velocity; A target yaw rate is calculated according to the adjustment coefficient and the theoretical yaw rate.

4. The vehicle control method according to claim 2, characterized in that: The motion state parameter information also includes actual yaw angular velocity information; The calculating, according to the target yaw angular velocity, the additional yaw moment in the preset motion scene comprises: Calculating a yaw rate deviation according to the target yaw rate and the actual yaw rate information; An additional yaw moment of the vehicle is calculated according to the preset motion scenario and the yaw angular velocity deviation.

5. The vehicle control method according to claim 4, characterized in that: The calculating the additional yaw moment of the vehicle according to the preset motion scene and the yaw angular velocity deviation includes: estimating the road adhesion coefficient of the vehicle according to the wheel speed information of each wheel, the lateral acceleration information, and the longitudinal acceleration information to obtain an estimated road adhesion coefficient; determining a feedforward value of the additional yaw moment according to the estimated road adhesion coefficient, the estimated longitudinal speed and the preset motion scenario; The additional yaw moment of the vehicle is calculated according to the feedforward value of the additional yaw moment and the yaw rate deviation.

6. The vehicle control method according to claim 5, characterized in that: Before calculating the additional yaw moment of the vehicle according to the preset motion scene, the target yaw angular velocity and the actual yaw angular velocity information, the method further includes: estimating a sideslip angle of the center of mass of the vehicle according to the wheel speed information of each wheel, the lateral acceleration information, and the longitudinal acceleration information to obtain an estimated sideslip angle of the center of mass; When the estimated sideslip angle of the center of mass and the estimated road adhesion coefficient meet a preset condition, an additional yaw moment under a preset motion scenario is calculated.

7. The vehicle control method according to claim 6, characterized in that: The driving parameter information also includes pedal information; The step of calculating the driving torque of each wheel of the vehicle according to the additional yaw moment and the longitudinal moment comprises: The longitudinal moment of the vehicle is calculated according to the pedal information, and the driving torque of each wheel is calculated according to the additional yaw moment and the longitudinal moment with the goal of maximizing the driving efficiency of the vehicle and the road adhesion of the vehicle.

8. A vehicle control system, characterized in that: include: An acquisition module, used to acquire the motion state parameter information and driving state parameter information of each wheel of the vehicle in real time; A first calculation module, used for determining a theoretical yaw rate value of the vehicle by combining the motion state parameter information with the driving state information, and calculating a target yaw rate of the vehicle in a preset motion mode; A second calculation module is used to obtain a preset motion scene of the vehicle, and calculate an additional yaw moment under the preset motion scene according to the target yaw angular velocity; The third calculation module is used to calculate the longitudinal torque of the vehicle according to the driving state parameter information, calculate the driving torque of each wheel in the vehicle according to the additional yaw torque and the longitudinal torque, and control the driving of the corresponding wheel according to the driving torque of each wheel.

9. A computer device, characterized in that: The computer device includes a processor, a memory, and a computer program stored in the memory and executable on the processor, and the computer device is used to execute the vehicle control method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the vehicle control method according to any one of claims 1 to 7 is implemented.

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