Vehicle control method, system, device and medium

Abstract

The present invention relates to the field of automobile motion control technology, and in particular to a vehicle control method, system, device and medium. In combination with motion state parameter information and driving state information, the theoretical yaw rate value of the vehicle is determined, the target yaw rate of the vehicle in a preset motion mode is calculated, and based on the target yaw rate, the additional yaw moment in a preset motion scenario is calculated. Based on the driving state parameter information, the longitudinal torque of the vehicle is calculated, and based on the additional yaw moment and the longitudinal torque, the driving torque of each wheel in the vehicle is calculated. Based on the driving torque of each wheel, the corresponding wheel is controlled to be driven. In the present application, the additional yaw moment is calculated according to the vehicle's operating mode and operating scenario, so that the vehicle can adaptively match different operating characteristics according to different operating modes and operating scenarios, and control the performance of the vehicle in different operating modes and operating scenarios, thereby achieving a more personalized handling feel and a better 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 is one in which each of the four wheels can be driven independently. Distributed drive vehicles offer advantages such as good maneuverability, high efficiency, and excellent maneuverability. However, controlling distributed drive vehicles is also challenging. Distributed drive systems improve vehicle maneuverability primarily by applying an additional yaw torque, which is controlled to achieve a reasonable target yaw velocity. Conventional vehicle control systems calculate the additional yaw torque based on the deviation between the target yaw velocity and the actual yaw velocity information, utilizing feedback algorithms such as PID. However, these algorithms primarily target the vehicle's inherent maneuverability characteristics and fail to account for the demands of different driving modes or the differences in different driving scenarios, making personalized maneuverability impossible. 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 of being unable to achieve personalized manipulation 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:

[0005] Real-time acquisition of motion state parameter information and driving state parameter information of each wheel of the vehicle;

[0006] Determining a theoretical yaw rate value of the vehicle by combining the motion state parameter information and the driving state information, and calculating a target yaw rate of the vehicle in a preset motion mode;

[0007] Obtaining 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;

[0008] The longitudinal moment of the vehicle is calculated based on the driving state parameter information, the driving torque of each wheel in the vehicle is calculated based on the additional yaw moment and the longitudinal moment, and the corresponding wheel is controlled to be driven based on the driving torque of each wheel.

[0009] In a second aspect, an embodiment of the present invention provides a vehicle control system, including:

[0010] An acquisition module is used to obtain the motion state parameter information and driving state parameter information of each wheel of the vehicle in real time;

[0011] a first calculation module, configured to 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;

[0012] a second calculation module, configured to obtain a preset motion scenario of the vehicle and calculate an additional yaw moment under the preset motion scenario according to the target yaw angular velocity;

[0013] The third calculation module is used to calculate the longitudinal torque of the vehicle based on the driving state parameter information, calculate the driving torque of each wheel in the vehicle based on the additional yaw torque and the longitudinal torque, and control the driving of the corresponding wheel based on the driving torque of each wheel.

[0014] 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.

[0015] 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.

[0016] Compared with the prior art, the present invention has the following beneficial effects:

[0017] The system obtains motion state parameter information and driving state parameter information for each wheel of the vehicle in real time, combines the motion state parameter information and driving state information to determine the theoretical yaw rate value of the vehicle, calculates the target yaw rate of the vehicle in a preset motion mode, obtains a preset motion scenario for the vehicle, calculates the additional yaw moment in the preset motion scenario based on the target yaw rate, calculates the longitudinal torque of the vehicle based on the driving state parameter information, calculates the driving torque of each wheel in the vehicle based on the additional yaw moment and the longitudinal torque, and controls the driving of the corresponding wheel based on the driving torque of each wheel. In this application, the additional yaw moment is calculated based on the vehicle's operating mode and operating scenario, so that the vehicle can adaptively match different operating characteristics according to different operating modes and operating scenarios, and controls the vehicle's performance in different operating modes and operating scenarios, thereby achieving a more personalized handling feel and a better driving experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0019] Figure 1 1 is a flow chart of a vehicle control method provided in the first embodiment of the present invention;

[0020] Figure 2 This is a flow chart of a vehicle control method provided in the second embodiment of the present invention;

[0021] Figure 3 1 is a flow chart of a vehicle control method provided in Embodiment 3 of the present invention;

[0022] Figure 4 1 is a flow chart of a vehicle control method provided in a fourth embodiment of the present invention;

[0023] Figure 5 1 is a flow chart of a vehicle control method provided in a fifth embodiment of the present invention;

[0024] Figure 6 1 is a flow chart of a vehicle control method provided in a sixth embodiment of the present invention;

[0025] Figure 7 This is a structural block diagram of a vehicle control system provided by Embodiment 7 of the present invention;

[0026] Figure 8 This is a structural diagram of a computer device provided in Example 8 of the present invention. DETAILED DESCRIPTION

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0028] In the following description, specific details such as particular system structures and techniques are provided for purposes of illustration and not limitation to facilitate a thorough understanding of the embodiments of the present invention. However, it will be apparent to those skilled in the art that the present invention may be practiced in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, systems, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

[0029] 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 preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0030] It will also be understood that the term "and / or" used in the present description and appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0031] 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.

[0032] 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.

[0033] References to "one embodiment" or "some embodiments" in the present specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present invention. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in yet other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0034] It should be understood that the order of execution of the steps in the following embodiments does not necessarily mean the order in which they are executed. The order in which each process is executed 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.

[0035] In order to illustrate the technical solution of the present invention, specific embodiments are provided below.

[0036] See also Figure 1 , is a flow chart of a vehicle control method provided by the first embodiment of the present invention, such as Figure 1As shown, the vehicle control method may include the following steps.

[0037] S101: Acquire motion state parameter information and driving state parameter information of each wheel of the vehicle in real time.

[0038] 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.

[0039] 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.

[0040] 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.

[0041] 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.

[0042] 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 the preset motion mode is calculated, wherein the theoretical yaw rate value does not change with changes in the motion scene and driving conditions, that is, the yaw rate under steady-state operating characteristics, and the target yaw rate varies with different motion modes.

[0043] 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 based on a preset first vehicle control reference model, and the theoretical yaw rate can be calculated based on the vehicle speed and mass. The preset first vehicle control reference model is a pre-trained model used to estimate the vehicle speed and mass. 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.

[0044] See also Figure 2, is a flow chart of a vehicle control method provided by a second embodiment of the present invention. Step S102 combines motion state parameter information and driving state information to determine a theoretical yaw rate value of the vehicle, including:

[0045] S201: estimating the longitudinal speed and mass of the vehicle based on the wheel speed information, lateral acceleration information, and longitudinal acceleration information of each wheel to obtain an estimated longitudinal speed and estimated mass of the vehicle;

[0046] S202: Calculate a theoretical yaw rate value of the vehicle based on the estimated longitudinal velocity, the estimated mass, and the steering wheel angle.

[0047] In this embodiment, the motion state parameter information includes wheel speed information, lateral acceleration information, and longitudinal acceleration information for each wheel, and the driving parameter information includes the steering wheel angle. The longitudinal velocity and mass of the vehicle are estimated based on the wheel speed information, lateral acceleration information, and longitudinal acceleration information for each wheel, resulting in an estimated longitudinal velocity and estimated mass. The estimation of the longitudinal velocity and mass of the vehicle is performed using the preset first vehicle control reference model. The wheel speed information, lateral acceleration information, and longitudinal acceleration information for each wheel are input into the preset first vehicle control reference model, which outputs the estimated longitudinal velocity and estimated mass.

[0048] The theoretical yaw rate of the vehicle is calculated based on the estimated longitudinal velocity, estimated mass, and steering wheel angle. The theoretical yaw rate is calculated as follows:

[0049]

[0050] in, is the theoretical yaw angular velocity, To estimate the longitudinal velocity, is the vehicle's wheelbase, 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.

[0051] in, The stability factor is calculated as follows:

[0052]

[0053] 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 wheels, is the front axle cornering stiffness of the vehicle, is the rear axle cornering stiffness of the vehicle, is the wheelbase of the vehicle.

[0054] 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.

[0055] See also Figure 3 , is a flow chart of a vehicle control method provided by a third embodiment of the present invention. Step S102 of calculating the target yaw rate of the vehicle in a preset motion mode includes:

[0056] S301: Determine an adjustment coefficient of the vehicle based on a preset motion pattern and an estimated longitudinal speed;

[0057] S302: Calculate the target yaw rate according to the adjustment coefficient and the theoretical yaw rate.

[0058] In this embodiment, the vehicle's adjustment coefficient is determined based on the preset motion pattern and estimated longitudinal velocity. The adjustment coefficient corresponds to the motion pattern and longitudinal velocity. Therefore, the corresponding adjustment coefficient can be determined by looking up the table. The target yaw rate is calculated based on the adjustment coefficient and the theoretical yaw rate.

[0059] It should be noted that the preset sports modes may include comfort mode and sport mode, among others. Comfort mode is a mode where the vehicle's steering is relatively slow and smooth, i.e., it corresponds to a low rate of change of the steering wheel angle. Sport mode is a mode where the vehicle's steering is relatively sensitive and aggressive, i.e., it corresponds to a high rate of change of the steering wheel angle. In this embodiment, a mode where the rate of change of the steering wheel angle is less than a preset rate may be defined as comfort mode, while a mode where the rate of change of the steering wheel angle is not less than the preset rate may be defined as sport mode.

[0060] In this embodiment, when determining the vehicle's adjustment coefficient based on the preset motion mode and the estimated longitudinal velocity, 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:

[0061]

[0062] in, is the target yaw rate, is the theoretical yaw angular velocity, is the adjustment coefficient.

[0063] In this embodiment, the corresponding adjustment coefficient is determined according to the preset motion mode, so that personalized vehicle steady-state operating characteristics in different motion modes can be achieved.

[0064] S103: 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.

[0065] In step S103, a preset motion scene of the vehicle is obtained, and 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 cornering motion scene and a cornering motion scene, and the additional yaw moment is the sum of the lateral moments of each vehicle.

[0066] In this embodiment, an additional yaw moment is calculated based on the target yaw angular velocity for a preset motion scenario. The preset motion scenarios include a cornering motion scenario and a cornering exit motion scenario. The cornering motion scenario and the cornering exit motion scenario can be determined based on the steering wheel angle and the rate of change of the steering wheel angle. For example, if the steering wheel angle is negative and the rate of change of the steering wheel angle is less than zero, or if the steering wheel angle is positive and the rate of change of the steering wheel angle is greater than zero, the motion scenario is determined to be a cornering motion scenario. If the steering wheel angle is negative and the rate of change of the steering wheel angle is greater than zero, or if the steering wheel angle is positive and the rate of change of the steering wheel angle is less than zero, the motion scenario is determined to be a cornering motion scenario.

[0067] It should be noted that when calculating the additional yaw moment under a preset motion scenario based on the target yaw angular velocity, different preset motion scenarios correspond to different additional yaw moment feedforward values, that is, different transient characteristic responses of the vehicle, thereby increasing the vehicle's stability when entering and exiting corners.

[0068] See also Figure 4 , is a flow chart of a vehicle control method provided by a fourth embodiment of the present invention. Step S103 calculates an additional yaw moment under a preset motion scenario based on a target yaw angular velocity, including:

[0069] S401: Calculating a yaw rate deviation based on the target yaw rate and the actual yaw rate information;

[0070] S402: Calculate an additional yaw moment of the vehicle according to a preset motion scenario and a yaw angular velocity deviation.

[0071] In this embodiment, the motion state parameter information also includes actual yaw rate information, that is, the yaw rate collected and acquired in real time during vehicle driving. The yaw rate deviation is calculated based on the target yaw rate and the actual yaw rate information. The calculation formula for the yaw rate deviation is as follows:

[0072]

[0073] in, is the yaw rate deviation, is the actual yaw angular velocity, is the target yaw rate.

[0074] The additional yaw moment of the vehicle is calculated based on the preset motion scenario and the yaw rate deviation. The calculation formula for the additional yaw moment is as follows:

[0075]

[0076] 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.

[0077] It should be noted that the feedforward value of the additional yaw moment is mapped to the motion scenario, road adhesion coefficient, and vehicle longitudinal velocity. The corresponding feedforward value of the additional yaw moment is obtained by looking up a table based on the corresponding preset motion scenario, estimated longitudinal velocity, and estimated road adhesion coefficient. The estimated longitudinal velocity and estimated road adhesion coefficient can be estimated based on the motion state parameters and driving state parameters.

[0078] See also Figure 5 , is a flow chart of a vehicle control method provided in a fifth embodiment of the present invention. Step S402 calculates an additional yaw moment of the vehicle based on a preset motion scene and a yaw rate deviation, including:

[0079] S501: estimating the road adhesion coefficient of the vehicle based on the wheel speed information, lateral acceleration information, and longitudinal acceleration information of each wheel to obtain an estimated road adhesion coefficient;

[0080] S502: Determining a feedforward value of an additional yaw moment based on the estimated road adhesion coefficient, the estimated longitudinal speed, and a preset motion scenario;

[0081] S503: Calculate the additional yaw moment of the vehicle according to the feedforward value of the additional yaw moment and the yaw rate deviation.

[0082] In this embodiment, the vehicle's road adhesion coefficient is estimated based on the wheel speed, lateral acceleration, and longitudinal acceleration information of each wheel to obtain an estimated road adhesion coefficient. This estimation is performed based on a preset second vehicle control reference model. Specifically, the wheel speed, lateral acceleration, and longitudinal acceleration information of each wheel are input into the preset second vehicle control reference model, which outputs the estimated road adhesion coefficient. A feedforward value for the additional yaw moment is determined by looking up the estimated road adhesion coefficient, the estimated longitudinal velocity, and a preset motion scenario in a table. The feedforward value for the additional yaw moment is mapped to the motion scenario, the road adhesion coefficient, and the vehicle's longitudinal velocity.

[0083] It should be noted that the motion scenarios include cornering and exiting motion scenarios. 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 motion 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 exit stability.

[0084] See also Figure 6 , which is a flow chart of a vehicle control method provided by a sixth embodiment of the present invention, before step S103 calculates the additional yaw moment under a preset motion scenario according to the target yaw angular velocity, the method further includes:

[0085] S601: Estimate the vehicle's center of mass slip angle based on the wheel speed information, lateral acceleration information, and longitudinal acceleration information of each wheel to obtain an estimated center of mass slip angle;

[0086] S602: When the estimated sideslip angle of the center of mass and the estimated road adhesion coefficient meet preset conditions, calculate an additional yaw moment under a preset motion scenario.

[0087] In this embodiment, the vehicle's center of mass slip angle is estimated based on the wheel speed information, lateral acceleration information, and longitudinal acceleration information of each wheel to obtain an estimated center of mass slip 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 slip angle is output.

[0088] The additional yaw moment is constrained based on the estimated center of mass slip angle and the estimated road adhesion coefficient. Specifically, when calculating the additional yaw moment, the estimated road adhesion coefficient must be less than a preset maximum road adhesion coefficient, and the estimated center of mass slip angle must be less than a preset eccentricity angle. If the estimated road adhesion coefficient is not less than the preset maximum road adhesion coefficient, or the estimated center of mass slip angle is not less than a preset eccentricity angle, the additional yaw moment is recalculated to ensure that the estimated center of mass slip angle and the estimated road adhesion coefficient meet the preset conditions when calculating the additional yaw moment. Specifically, the estimated road adhesion coefficient must be less than the preset maximum road adhesion coefficient, and the estimated center of mass slip angle must be less than the preset eccentricity angle.

[0089] S104: Calculate the longitudinal moment of the vehicle based on the driving state parameter information, calculate the driving torque of each wheel in the vehicle based on the additional yaw moment and the longitudinal moment, and control the driving of the corresponding wheel based on the driving torque of each wheel.

[0090] In step S104, the vehicle's longitudinal torque is calculated based on the driving state parameter information. The longitudinal torque is the torque in the vehicle's longitudinal direction, i.e., the sum of the torques in the longitudinal direction of each wheel. The driving torque for each wheel is calculated based on the additional yaw moment and the longitudinal torque. Specifically, the additional yaw moment is distributed to each wheel in the lateral direction, and the longitudinal torque is distributed to each wheel in the longitudinal direction. Based on the driving torque of each wheel, the corresponding wheel is controlled and driven.

[0091] 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.

[0092] Optionally, the driving torque of each wheel in the vehicle is calculated based on the additional yaw moment and the longitudinal moment, including:

[0093] Based on the pedal information, the longitudinal moment of the vehicle is calculated. Based on the additional yaw moment and longitudinal moment, the driving torque of each wheel is calculated with the goal of maximizing the vehicle's driving efficiency and the vehicle's road adhesion.

[0094] In this embodiment, the driving parameter information also includes pedal information. Specifically, the vehicle's longitudinal torque is calculated based on the accelerator pedal parameter information and the brake pedal parameter information. The driving torque for each wheel is calculated based on the additional yaw moment and the longitudinal torque, with the goal of maximizing the vehicle's driving efficiency and road adhesion. Specifically, after distributing the longitudinal torque and the additional yaw moment to each wheel, the vehicle's driving efficiency and road adhesion are calculated to determine whether the vehicle's driving efficiency and road adhesion have reached their maximum values. If the vehicle's driving efficiency and road adhesion have reached their maximum values, the driving torque for each wheel is determined as the final driving torque, and the drive motor on each wheel is driven according to the corresponding driving torque. If the vehicle's driving efficiency or road adhesion has not reached its maximum value, the driving torque to each wheel is redistributed until the vehicle's driving efficiency and road adhesion are maximized.

[0095] It should be noted that if the vehicle's driving efficiency and road adhesion cannot reach their maximum values ​​simultaneously, the driving torque of each wheel may be calculated with the vehicle's driving efficiency as the target. Alternatively, the driving torque of each wheel may be calculated with the vehicle's road adhesion as the target. This is not limited in this embodiment.

[0096] The system obtains motion state parameter information and driving state parameter information for each wheel of the vehicle in real time, combines the motion state parameter information and driving state information to determine the theoretical yaw rate value of the vehicle, calculates the target yaw rate of the vehicle in a preset motion mode, obtains a preset motion scenario for the vehicle, calculates the additional yaw moment in the preset motion scenario based on the target yaw rate, calculates the longitudinal torque of the vehicle based on the driving state parameter information, calculates the driving torque of each wheel in the vehicle based on the additional yaw moment and the longitudinal torque, and controls the driving of the corresponding wheel based on the driving torque of each wheel. In this application, the additional yaw moment is calculated based on the vehicle's operating mode and operating scenario, so that the vehicle can adaptively match different operating characteristics according to different operating modes and operating scenarios, and controls the vehicle's performance in different operating modes and operating scenarios, thereby achieving a more personalized handling feel and a better driving experience.

[0097] See also Figure 7 , Figure 7 This is a structural block diagram of a vehicle control system provided by the seventh embodiment of the present invention. For ease of explanation, 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 .

[0098] 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.

[0099] The first calculation module 72 is used to 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.

[0100] The second calculation module 73 is configured to obtain a preset motion scene of the vehicle and calculate an additional yaw moment under the preset motion scene according to a target yaw angular velocity.

[0101] The third calculation module 74 is used to calculate the longitudinal torque of the vehicle based on the driving state parameter information, calculate the driving torque of each wheel in the vehicle based on the additional yaw torque and the longitudinal torque, and control the driving of the corresponding wheel based on the driving torque of each wheel.

[0102] Optionally, the first calculation module 72 includes:

[0103] 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.

[0104] The first calculation unit is configured to calculate a theoretical yaw rate value of the vehicle according to the estimated longitudinal velocity, the estimated mass, and the steering wheel angle.

[0105] Optionally, the first calculation module 72 includes:

[0106] The determining unit is configured to determine an adjustment coefficient of the vehicle according to a preset motion pattern and an estimated longitudinal speed.

[0107] The second calculation unit is used to calculate the target yaw rate according to the adjustment coefficient and the theoretical yaw rate.

[0108] Optionally, the second calculation module 73 includes:

[0109] The third calculation unit is configured to calculate a yaw rate deviation according to the target yaw rate and the actual yaw rate information.

[0110] 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.

[0111] Optionally, the fourth calculation unit includes:

[0112] The estimation subunit is used to estimate the road adhesion coefficient of the vehicle based on the wheel speed information, lateral acceleration information, and longitudinal acceleration information of each wheel to obtain an estimated road adhesion coefficient.

[0113] 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.

[0114] 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.

[0115] Optionally, the vehicle control system 70 further includes:

[0116] The estimation module is used to estimate the vehicle's center of mass sideslip angle based on the wheel speed information, lateral acceleration information, and longitudinal acceleration information of each wheel to obtain an estimated center of mass sideslip angle.

[0117] The judgment module is used to calculate the additional yaw moment under a preset motion scenario when the estimated sideslip angle of the center of mass and the estimated road adhesion coefficient meet preset conditions.

[0118] Optionally, the third calculation module 74 includes:

[0119] The fifth calculation unit is used to calculate the longitudinal moment of the vehicle based on the pedal information, and calculate the driving torque of each wheel 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.

[0120] It should be noted that the information interaction, execution process and other contents between the above modules are based on the same concept as the method embodiment of this application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0121] Figure 8 This is a schematic diagram of the structure of a computer device provided by the eighth embodiment 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), 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 of any of the above-mentioned vehicle control method embodiments are implemented.

[0122] The computer device may include, but is not limited to, a processor and a memory. It will be understood by those skilled in the art that Figure 8 The above 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 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.

[0123] The processor may be a CPU, other general-purpose processors, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), 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.

[0124] Memory includes readable storage media, internal memory, and the like. Internal memory can be the internal memory of a computer device, providing an environment for the operation of the operating system and computer-readable instructions stored in the readable storage medium. The readable storage medium can be the computer device's hard drive. In other embodiments, it can also be an external storage device, such as a plug-in hard drive, a Smart Media Card (SMC), a Secure Digital (SD) card, or a flash memory card. Furthermore, memory can include both the computer device's internal storage unit and external storage devices. Memory is used to store the operating system, application programs, boot loaders, data, and other programs, such as the program code of computer programs. Memory can also be used to temporarily store data that has been output or is about to be output.

[0125] Those skilled in the art 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 for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be 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 alone, 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 a software functional unit. 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 aforementioned 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 process steps in the above-described method embodiments by instructing the relevant hardware through a computer program. The computer program may be stored in a computer-readable storage medium. When executed by a processor, the computer program implements the steps of the above-described method embodiments. The computer program includes computer program code, which may be in source code form, object code form, executable file, or some intermediate form. Computer-readable media may include at least: any entity or device capable of carrying computer program code, recording media, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunications signals, and software distribution media. Examples include USB flash drives, removable hard drives, magnetic disks, or optical disks. In some jurisdictions, based on legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunications signals.

[0126] The present application implements all or part of the processes in the above-mentioned embodiment method, and can 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 it.

[0127] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0128] Those skilled 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 beyond the scope of this application.

[0129] In the embodiments provided in this application, it should be understood that the disclosed apparatus / computer equipment and methods can be implemented in other ways. For example, the apparatus / computer equipment embodiments described above are merely schematic. For example, the division of modules or units is merely a logical function division. In actual implementation, there may be other division methods, 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 the apparatus or unit, which can be electrical, mechanical or other forms.

[0130] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0131] 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 various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A vehicle control method, characterized in that: include: Real-time acquisition of motion state parameter information and driving state parameter information of each wheel of the vehicle; Determining a theoretical yaw rate value of the vehicle by combining the motion state parameter information and the driving state parameter information, and calculating a target yaw rate of the vehicle in a preset motion mode; Obtaining 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 based on the driving state parameter information, the driving torque of each wheel in the vehicle is calculated based on the additional yaw moment and the longitudinal moment, and the corresponding wheel is controlled to be driven based on the driving torque of each wheel.

2. The vehicle control method according to claim 1, wherein: The motion state parameter information includes wheel speed information, lateral acceleration information and longitudinal acceleration information of each wheel, and the driving state parameter information includes steering wheel angle; Determining a theoretical yaw rate value of the vehicle by combining the motion state parameter information and the driving state parameter information includes: estimating the longitudinal speed and mass of the vehicle based on 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 velocity, the estimated mass, and the steering wheel angle.

3. The vehicle control method according to claim 2, wherein: 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, wherein: The motion state parameter information also includes actual yaw rate information; Calculating the additional yaw moment in the preset motion scenario according to the target yaw angular velocity includes: 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, wherein: The calculating the additional yaw moment of the vehicle according to the preset motion scene and the yaw angular velocity deviation includes: estimating a road adhesion coefficient of the vehicle based on 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, wherein: 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 vehicle's center of mass based on the wheel speed information of each wheel, the lateral acceleration information, and the longitudinal acceleration information to obtain an estimated sideslip angle of the vehicle's 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, wherein: The driving state parameter information also includes pedal information; Calculating the driving torque of each wheel of the vehicle according to the additional yaw moment and the longitudinal moment includes: 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 driving efficiency of the vehicle and the road adhesion of the vehicle.

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