Vehicle adaptive adjustment method, device, computer equipment and storage medium

Abstract

The present application relates to a vehicle adaptive adjustment method, device, computer equipment and storage medium, and belongs to the field of vehicle control technology. The method includes: obtaining the body vertical acceleration, suspension vertical displacement and vehicle speed of the target vehicle; pre-processing the suspension vertical displacement to determine the suspension vertical acceleration corresponding to the suspension vertical displacement; calculating and obtaining the target characteristic value based on the body vertical acceleration, suspension vertical acceleration and vehicle speed; in response to detecting that the target characteristic value is greater than a preset threshold, determining the road surface grade based on the target characteristic value; adjusting the operating parameters of the target vehicle based on the road surface grade determination result to achieve adaptive adjustment of the target vehicle. The present application calculates and determines the road surface grade based on multiple dimensions of body vertical acceleration, suspension vertical displacement and vehicle speed, and adaptively adjusts the vehicle operating parameters based on the road surface grade determination result to improve the comfort of the whole vehicle.

Description

Technical Field

[0001] The present application relates to the field of vehicle control technology, and in particular to a vehicle adaptive adjustment method, device, computer equipment and storage medium. Background Art

[0002] Road surface roughness refers to the deviation value of the longitudinal concave and convex amount of the road surface. The road surface roughness mainly reflects the flatness of the road surface longitudinal section profile curve. When the road surface longitudinal section profile curve is relatively smooth, it means that the road surface is relatively flat, or the flatness is relatively good, and the lower the road surface roughness level is, the lower the road surface roughness level is. Conversely, it means that the flatness is relatively poor, that is, the higher the road surface roughness level is. The higher the road surface roughness level will not only reduce driving comfort and increase driving operating costs, but also affect road driving safety. At present, with the increasing demand of users for the comfort and power of new energy vehicles, how to realize the adaptive adjustment of the vehicle through timely and accurate identification of the road surface level to improve the driving comfort of users is an urgent problem to be solved. Summary of the invention

[0003] Based on this, it is necessary to provide a vehicle adaptive adjustment method, device, computer equipment and storage medium that can improve user driving comfort in response to the above technical problems.

[0004] In one aspect, a vehicle adaptive adjustment method is provided, the method comprising:

[0005] Obtain the target vehicle's body vertical acceleration, suspension vertical displacement, and vehicle speed;

[0006] Preprocessing the vertical displacement of the suspension to determine the vertical acceleration of the suspension corresponding to the vertical displacement of the suspension;

[0007] Calculating and acquiring a target characteristic value based on the vehicle body vertical acceleration, the suspension vertical acceleration and the vehicle speed;

[0008] In response to detecting that the target characteristic value is greater than a preset threshold, determining a road surface grade based on the target characteristic value;

[0009] Based on the road surface grade determination result, the operating parameters of the target vehicle are adjusted to achieve adaptive adjustment of the target vehicle.

[0010] Optionally, preprocessing the vertical displacement of the suspension to determine the vertical acceleration of the suspension corresponding to the vertical displacement of the suspension includes:

[0011] Obtaining a vertical displacement of a suspension of the target vehicle;

[0012] Based on a low-pass filtering mechanism, a low-pass filtering process is performed on the vertical displacement of the suspension to obtain a target processing result;

[0013] A first-order derivative is performed on the target processing result to determine the suspension vertical acceleration corresponding to the suspension vertical displacement.

[0014] Optionally, based on the vehicle body vertical acceleration, the suspension vertical acceleration and the vehicle speed, calculating and obtaining the target characteristic value includes:

[0015] Based on the vehicle body vertical acceleration, suspension vertical acceleration and vehicle speed, the first eigenvalue and the second eigenvalue are calculated using the following formula:

[0016]

[0017]

[0018] Among them, X Body represents the first eigenvalue, a Bodyz is the vertical acceleration of the vehicle body, v x Indicates vehicle speed, X Suspension represents the second eigenvalue, a Suspension represents the vertical acceleration of the suspension;

[0019] Based on the first eigenvalue and the second eigenvalue, target eigenvalues ​​corresponding to the body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles are calculated respectively, and the target eigenvalues ​​include a root mean square value and a variance value.

[0020] Optionally, calculating the root mean square values ​​of the vehicle body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles based on the first eigenvalue and the second eigenvalue includes:

[0021] The root mean square value corresponding to the body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles is calculated using a root mean square calculation function, wherein the root mean square calculation function includes:

[0022]

[0023]

[0024] Among them, Y 1Rms Indicates the root mean square value of the vertical acceleration of the vehicle body, Y 2Rms represents the root mean square value of the vertical acceleration of the suspension, X 1k represents the first eigenvalue corresponding to the kth operation cycle, X 2k represents the second eigenvalue corresponding to the kth operating cycle, and M represents the number of operating cycles.

[0025] Optionally, calculating the variance values ​​corresponding to the vehicle body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles based on the first eigenvalue and the second eigenvalue includes:

[0026] The variance calculation function is used to calculate the variance values ​​corresponding to the body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles, and the variance calculation function includes:

[0027]

[0028]

[0029] in, It represents the variance value corresponding to the vertical acceleration of the vehicle body. represents the variance value corresponding to the vertical acceleration of the suspension, β1 represents the average value of the vertical acceleration of the vehicle body, β2 represents the average value of the vertical acceleration of the suspension, and X 1k represents the first eigenvalue corresponding to the kth operation cycle, X 2k represents the second eigenvalue corresponding to the kth operating cycle, and M represents the number of operating cycles.

[0030] Optionally, in response to detecting that the target characteristic value is greater than a preset threshold, determining the road surface grade based on the target characteristic value includes:

[0031] In response to detecting that the root mean square value corresponding to the vertical acceleration of the vehicle body is greater than a first preset value within M operating cycles, and / or the root mean square value corresponding to the vertical acceleration of the suspension is greater than a second preset value, and / or the variance value corresponding to the vertical acceleration of the vehicle body is greater than a third preset value, and / or the variance value corresponding to the vertical acceleration of the suspension is greater than a fourth preset value, a first target road surface grade is determined based on a first objective function, wherein the first objective function includes:

[0032]

[0033]

[0034] Wherein, d1 represents the first output value, b1 and c1 represent the weight coefficients of the root mean square value, d2 represents the second output value, b2 and c2 represent the weight coefficients of the variance value;

[0035] Based on a first preset mapping table, determining a first road surface grade and a second road surface grade corresponding to the first output value and the second output value respectively;

[0036] A second target road surface grade is determined based on the first road surface grade and the second road surface grade, and a second objective function, wherein the second objective function includes:

[0037]

[0038] Wherein, F represents the third output value, and γ represents the target weight coefficient;

[0039] Based on the second preset mapping table, a second target road surface grade corresponding to the third output value is determined, which is the final road surface grade.

[0040] Optionally, adjusting the operating parameters of the target vehicle based on the road surface grade determination result includes:

[0041] In response to detecting that the road surface grade is greater than a fifth preset value, determining the damping coefficient adjustment value corresponding to the road surface grade based on a mapping relationship table between the road surface grade and the damping coefficient adjustment value;

[0042] Based on the damping coefficient adjustment value, the current damping coefficient of the target vehicle is adjusted upward.

[0043] On the other hand, a vehicle adaptive adjustment device is provided, the device comprising:

[0044] A data acquisition module is used to obtain the vertical acceleration of the target vehicle, the vertical displacement of the suspension, and the vehicle speed;

[0045] A preprocessing module, used for preprocessing the vertical displacement of the suspension to determine the vertical acceleration of the suspension corresponding to the vertical displacement of the suspension;

[0046] A calculation module, used for calculating and obtaining a target characteristic value based on the vehicle body vertical acceleration, the suspension vertical acceleration and the vehicle speed;

[0047] A road surface grade determination module, configured to determine a road surface grade based on the target characteristic value when detecting that the target characteristic value is greater than a preset threshold;

[0048] The adjustment module is used to adjust the operating parameters of the target vehicle based on the road surface grade determination result to achieve adaptive adjustment of the target vehicle.

[0049] In another aspect, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the following steps are implemented:

[0050] Obtain the target vehicle's body vertical acceleration, suspension vertical displacement, and vehicle speed;

[0051] Preprocessing the vertical displacement of the suspension to determine the vertical acceleration of the suspension corresponding to the vertical displacement of the suspension;

[0052] Calculating and acquiring a target characteristic value based on the vehicle body vertical acceleration, the suspension vertical acceleration and the vehicle speed;

[0053] In response to detecting that the target characteristic value is greater than a preset threshold, determining a road surface grade based on the target characteristic value;

[0054] Based on the road surface grade determination result, the operating parameters of the target vehicle are adjusted to achieve adaptive adjustment of the target vehicle.

[0055] In another aspect, a computer-readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0056] Obtain the target vehicle's body vertical acceleration, suspension vertical displacement, and vehicle speed;

[0057] Preprocessing the vertical displacement of the suspension to determine the vertical acceleration of the suspension corresponding to the vertical displacement of the suspension;

[0058] Calculating and acquiring a target characteristic value based on the vehicle body vertical acceleration, the suspension vertical acceleration and the vehicle speed;

[0059] In response to detecting that the target characteristic value is greater than a preset threshold, determining a road surface grade based on the target characteristic value;

[0060] Based on the road surface grade determination result, the operating parameters of the target vehicle are adjusted to achieve adaptive adjustment of the target vehicle.

[0061] The above-mentioned vehicle adaptive adjustment method, device, computer equipment and storage medium, the method includes: obtaining the body vertical acceleration, suspension vertical displacement and vehicle speed of the target vehicle; preprocessing the suspension vertical displacement to determine the suspension vertical acceleration corresponding to the suspension vertical displacement; calculating and obtaining the target characteristic value based on the body vertical acceleration, suspension vertical acceleration and vehicle speed; in response to detecting that the target characteristic value is greater than a preset threshold, determining the road surface grade based on the target characteristic value; based on the road surface grade determination result, adjusting the operating parameters of the target vehicle to achieve adaptive adjustment of the target vehicle. The present application calculates and determines the road surface grade based on multiple dimensions of body vertical acceleration, suspension vertical displacement and vehicle speed, and adaptively adjusts the vehicle operating parameters according to the road surface grade determination result to improve the comfort of the entire vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 A diagram showing an application environment of a vehicle adaptive adjustment method in an embodiment;

[0063] Figure 2 A schematic diagram of a process flow of a vehicle adaptive adjustment method in one embodiment;

[0064] Figure 3is a structural block diagram of a vehicle adaptive adjustment device in one embodiment;

[0065] Figure 4 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0066] In order to make the purpose, technical solutions and advantages of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0067] It should be understood that in the description of the present application, unless the context clearly requires otherwise, words such as "include", "comprises", and the like throughout the specification should be interpreted as including rather than being exclusive or exhaustive; that is, as including but not limited to.

[0068] It should also be understood that the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of this application, unless otherwise specified, "plurality" means two or more.

[0069] It should be noted that the terms "S1", "S2", etc. are only used for the purpose of describing the steps, and do not specifically refer to the order or sequence, nor are they used to limit the present application. They are only for the convenience of describing the method of the present application, and cannot be understood as indicating the order of the steps. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in this field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection required by the present application.

[0070] The vehicle adaptive adjustment method provided in this application can be applied to Figure 1 In the vehicle 100 shown, the vehicle 100 may include an onboard terminal 120. The onboard terminal 120 includes at least one memory and at least one processor, wherein a computer program is stored in the at least one memory, and when the computer program is executed by the at least one processor, the vehicle adaptive adjustment method according to the exemplary embodiment of the present disclosure is executed. Here, the onboard terminal 120 is not necessarily a single electronic device, but may also be any collection of devices or circuits that can execute the above-mentioned computer program alone or in combination.

[0071] In the vehicle terminal 120, the processor may include a central processing unit (CPU), a graphics processing unit (GPU), a programmable logic device, a dedicated processor system, a microcontroller or a microprocessor. As an example and not a limitation, the processor may also include an analog processor, a digital processor, a microprocessor, a multi-core processor, a processor array, a network processor, etc.; in the vehicle terminal 120, the processor may run a computer program stored in a memory, which may be divided into one or more modules / units (such as computer program 1, computer program 2, ...), and the one or more modules / units are stored in the memory and executed by the processor to complete the present invention. The one or more modules / units may be a series of computer program instruction segments capable of completing a specific function, which are used to describe the execution process of the computer program in the terminal device. The memory may be integrated with the processor, for example, RAM or flash memory is arranged within an integrated circuit microprocessor, etc. In addition, the memory may include an independent device, such as an external disk drive, a storage array, or any other storage device that can be used by any database system. The memory and the processor may be coupled in operation, or may communicate with each other, for example, through an I / O port, a network connection, etc., so that the processor can read files stored in the memory.

[0072] In addition, the vehicle terminal 120 may also include a display device (such as a liquid crystal display, etc.) and a user interaction interface (such as a keyboard, a mouse, a touch input device, etc.), and all components of the vehicle terminal 120 may be connected to each other via a bus and / or a network.

[0073] In one embodiment, Figure 2 As shown, a vehicle adaptive adjustment method is provided, and the method is applied to Figure 1 The terminal in is used as an example to illustrate, including the following steps:

[0074] S1: Obtain the target vehicle's body vertical acceleration, suspension vertical displacement, and vehicle speed.

[0075] It should be noted that the vertical acceleration of the target vehicle, the vertical displacement of the suspension, and the vehicle speed can be obtained through the vehicle-mounted sensors. The vertical acceleration of the target vehicle refers to the acceleration of the vehicle in the vertical direction, which is usually expressed in meters per second squared (m / s 2 ), which is affected by many factors, such as vehicle weight, speed, road conditions, etc. Under normal driving conditions, the vertical acceleration of a vehicle is usually small, about 0.1 to 0.3 m / s 2 However, during driving, if you encounter bumpy roads or sudden braking, the vertical acceleration of the vehicle will increase instantly and may even exceed 1m / s 2, which will have an impact on the safety of the vehicle and the driver and passengers. Therefore, the application needs to consider the influence of vertical acceleration when performing adaptive adjustment; the suspension is a general term for all force transmission connection devices between the vehicle body and the wheel. It is mainly composed of springs (such as leaf springs, coil springs, torsion bar springs, etc.), shock absorbers and guide mechanisms. The shock absorber mainly balances the vertical displacement of the wheel through the extension and contraction of the guide rod as the vehicle tire shakes, and cooperates with the damper (usually liquid damper, gas damper and electromagnetic damper) to reduce vibration and improve driving experience. The damper and the guide rod are both installed inside the shock-absorbing shell. When the car is driving on different roads, the suspension system realizes elastic support between the vehicle body and the wheel, which effectively reduces the vibration of the vehicle body and the wheel to ensure the normal driving of the car. The driving comfort of the vehicle is closely related to the displacement of the vehicle suspension system. The displacement of the vehicle suspension in the vertical direction is the vertical displacement of the suspension, which shows the up and down displacement amplitude of the vehicle and the vehicle body on complex roads. Therefore, the application needs to consider the influence of the vertical displacement of the suspension when performing adaptive adjustment.

[0076] S2: Preprocessing the suspension vertical displacement to determine the suspension vertical acceleration corresponding to the suspension vertical displacement.

[0077] It should be noted that this step specifically includes:

[0078] Obtaining a vertical displacement of a suspension of the target vehicle;

[0079] Based on the low-pass filtering mechanism, the suspension vertical displacement is subjected to low-pass filtering to obtain the target processing result. At the same time, the vehicle body vertical acceleration is also subjected to low-pass filtering, that is, useless high-frequency components in the collected suspension vertical displacement and vehicle body vertical acceleration data sets are eliminated by low-pass filtering to ensure the accuracy of subsequent vehicle adaptive adjustment. The target characteristic value refers to the suspension vertical displacement and vehicle body vertical acceleration obtained after low-pass filtering.

[0080] A first-order derivative is performed on the target processing result to determine the suspension vertical acceleration corresponding to the suspension vertical displacement, wherein the data to be derived here is the suspension vertical displacement.

[0081] In the above implementation, the accuracy of subsequent vehicle adaptive adjustment can be improved by preprocessing the collected suspension vertical displacement and vehicle body vertical acceleration.

[0082] S3: Calculate and obtain a target characteristic value based on the vehicle body vertical acceleration, suspension vertical acceleration and vehicle speed.

[0083] It should be noted that the target characteristic value includes a root mean square value and a variance value.

[0084] In some specific implementations, based on the vehicle body vertical acceleration, the suspension vertical acceleration and the vehicle speed, calculating and obtaining the target characteristic value includes:

[0085] Based on the vehicle body vertical acceleration, suspension vertical acceleration and vehicle speed, the first eigenvalue and the second eigenvalue are calculated using the following formula:

[0086]

[0087]

[0088] Among them, X Body represents the first eigenvalue, a Bodyz is the vertical acceleration of the vehicle body, v x Indicates vehicle speed, X Suspension represents the second eigenvalue, a Suspension represents the vertical acceleration of the suspension;

[0089] Based on the first eigenvalue and the second eigenvalue, target eigenvalues ​​corresponding to the vehicle body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles are calculated respectively, including:

[0090] Calculating the root mean square values ​​of the vehicle body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles based on the first eigenvalue and the second eigenvalue includes:

[0091] The root mean square value corresponding to the body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles is calculated using a root mean square calculation function, wherein the root mean square calculation function includes:

[0092]

[0093]

[0094] Among them, Y 1Rms Indicates the root mean square value of the vertical acceleration of the vehicle body, Y 2Rms represents the root mean square value of the vertical acceleration of the suspension, X 1k represents the first eigenvalue corresponding to the kth operation cycle, X 2k represents the second eigenvalue corresponding to the kth operation cycle, and M represents the number of operation cycles;

[0095] Further, based on the first eigenvalue and the second eigenvalue, calculating the variance values ​​corresponding to the vehicle body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles includes:

[0096] The variance calculation function is used to calculate the variance values ​​corresponding to the body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles, and the variance calculation function includes:

[0097]

[0098]

[0099] in, It represents the variance value corresponding to the vertical acceleration of the vehicle body. represents the variance value corresponding to the vertical acceleration of the suspension, β1 represents the average value of the vertical acceleration of the vehicle body, β2 represents the average value of the vertical acceleration of the suspension, and X 1k represents the first eigenvalue corresponding to the kth operation cycle, X 2k represents the second eigenvalue corresponding to the kth operating cycle, and M represents the number of operating cycles.

[0100] In the above-mentioned implementation, the target characteristic value is calculated based on the collected data of multiple dimensions, so as to subsequently determine the road surface grade according to the target characteristic value, thereby performing adaptive adjustment of the vehicle.

[0101] S4: In response to detecting that the target characteristic value is greater than a preset threshold, determining a road surface grade based on the target characteristic value.

[0102] It should be noted that the preset thresholds include a first preset value, a second preset value, a third preset value and a fourth preset value, all of which can be set according to actual needs.

[0103] In some specific embodiments, in response to detecting that the target characteristic value is greater than a preset threshold, determining the road surface grade based on the target characteristic value includes:

[0104] In response to detecting that the root mean square value corresponding to the vertical acceleration of the vehicle body is greater than a first preset value within M operating cycles, and / or the root mean square value corresponding to the vertical acceleration of the suspension is greater than a second preset value, and / or the variance value corresponding to the vertical acceleration of the vehicle body is greater than a third preset value, and / or the variance value corresponding to the vertical acceleration of the suspension is greater than a fourth preset value, it indicates that the road surface is uneven, and at this time, the corresponding road surface grade needs to be calculated for the subsequent target vehicle to adaptively adjust relevant operating parameters according to the road surface grade. Specifically: based on the first objective function, a first target road surface grade is determined, and the first objective function includes:

[0105]

[0106]

[0107] Wherein, d1 represents the first output value, b1 and c1 represent the weight coefficients of the root mean square value, d2 represents the second output value, b2 and c2 represent the weight coefficients of the variance value, wherein b1 represents the weight coefficient of the root mean square value corresponding to the vertical acceleration of the vehicle body, c1 represents the weight coefficient of the root mean square value corresponding to the vertical acceleration of the suspension, b1 represents the weight coefficient of the variance value corresponding to the vertical acceleration of the vehicle body, and c1 represents the weight coefficient of the variance value corresponding to the vertical acceleration of the suspension;

[0108] Based on a first preset mapping table, determining a first road surface grade and a second road surface grade corresponding to the first output value and the second output value, respectively, wherein the first target road surface grade includes a first road surface grade and a second road surface grade, and the first preset mapping table includes at least one mapping relationship generated between the first output value and the first road surface grade, and a mapping relationship generated between the second output value and the second road surface grade, and the first road surface grade and the second road surface grade are values ​​obtained through multiple tests and combined with expert scoring;

[0109] Further, based on the first road surface grade and the second road surface grade, and a second objective function, a second target road surface grade is determined, and the second objective function includes:

[0110]

[0111] Wherein, F represents the third output value, and γ represents the target weight coefficient;

[0112] Based on the second preset mapping table, the second target road surface grade corresponding to the third output value is determined, that is, the final road surface grade, wherein the second preset mapping table includes a mapping relationship generated by at least one third output value and a second target road surface grade, and the second target road surface grade is a value obtained through multiple tests and combined with expert scores.

[0113] In the above embodiment, the accuracy of the adaptive adjustment of the vehicle operating parameters can be improved by performing a secondary evaluation based on the road surface grade.

[0114] S5: Based on the road surface grade determination result, the operating parameters of the target vehicle are adjusted to achieve adaptive adjustment of the target vehicle.

[0115] It should be noted that the operating parameters of the target vehicle include the vehicle damping coefficient.

[0116] In some specific embodiments, adjusting the operating parameters of the target vehicle based on the road grade determination result includes:

[0117] In response to detecting that the road surface grade is greater than a fifth preset value, determining the damping coefficient adjustment value corresponding to the road surface grade based on a mapping relationship table between the road surface grade and the damping coefficient adjustment value, wherein the fifth preset value can be set according to actual needs, and the mapping relationship table includes at least one mapping relationship generated between the road surface grade and the damping coefficient adjustment value, and the damping coefficient adjustment value is a value obtained through multiple tests and combined with expert scoring;

[0118] Based on the damping coefficient adjustment value, the current damping coefficient of the target vehicle is adjusted downward. For example, the current damping coefficient is X, and the damping coefficient adjustment value is Y. Because the larger the road surface grade, the more uneven the road surface is, the value obtained by XY needs to be used as the target damping coefficient to improve the comfort of the entire vehicle.

[0119] In some specific embodiments, when the constraints that the root mean square value corresponding to the vehicle body vertical acceleration is less than or equal to the first preset value, the root mean square value corresponding to the suspension vertical acceleration is less than or equal to the second preset value, the variance value corresponding to the vehicle body vertical acceleration is less than or equal to the third preset value, and the variance value corresponding to the suspension vertical acceleration is less than or equal to the fourth preset value are satisfied simultaneously within the target time period, the road surface tends to be flat and the adaptive adjustment of the vehicle is stopped. Among them, the target time period can be set according to actual needs, and its start time node maintains a time interval with the time node when the vehicle starts adaptive adjustment, which is related to the road surface grade. If the road surface grade is higher, the target time period is longer.

[0120] In the above-mentioned embodiment, the corresponding damping coefficient adjustment value is determined based on the road surface grade to adjust the vehicle operating parameters, thereby improving the comfort of the vehicle on uneven roads. Furthermore, when the vehicle is on a flat road, the adaptive adjustment of the vehicle is stopped, thereby realizing intelligent control of the vehicle comfort and improving the user's car experience.

[0121] In the above-mentioned vehicle adaptive adjustment method, the method includes: obtaining the body vertical acceleration, suspension vertical displacement, and vehicle speed of the target vehicle; preprocessing the suspension vertical displacement to determine the suspension vertical acceleration corresponding to the suspension vertical displacement; calculating and obtaining a target characteristic value based on the body vertical acceleration, suspension vertical acceleration and vehicle speed; in response to detecting that the target characteristic value is greater than a preset threshold, determining a road surface grade based on the target characteristic value; based on the road surface grade determination result, adjusting the operating parameters of the target vehicle to achieve adaptive adjustment of the target vehicle. The present application calculates and determines the road surface grade based on multiple dimensions of body vertical acceleration, suspension vertical displacement and vehicle speed, and adaptively adjusts the vehicle operating parameters according to the road surface grade determination result to improve the comfort of the entire vehicle.

[0122] It should be understood that although Figure 2 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 2 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0123] In one embodiment, Figure 3 As shown, a vehicle adaptive adjustment device is provided, comprising: a data acquisition module, a preprocessing module, a calculation module, a road surface grade determination module and an adjustment module, wherein:

[0124] A data acquisition module is used to obtain the vertical acceleration of the target vehicle, the vertical displacement of the suspension, and the vehicle speed;

[0125] A preprocessing module, used for preprocessing the vertical displacement of the suspension to determine the vertical acceleration of the suspension corresponding to the vertical displacement of the suspension;

[0126] A calculation module, used for calculating and obtaining a target characteristic value based on the vehicle body vertical acceleration, the suspension vertical acceleration and the vehicle speed;

[0127] A road surface grade determination module, configured to determine a road surface grade based on the target characteristic value when detecting that the target characteristic value is greater than a preset threshold;

[0128] The adjustment module is used to adjust the operating parameters of the target vehicle based on the road surface grade determination result to achieve adaptive adjustment of the target vehicle.

[0129] As a preferred implementation, in the embodiment of the present invention, the preprocessing module is specifically used for:

[0130] Obtaining a vertical displacement of a suspension of the target vehicle;

[0131] Based on a low-pass filtering mechanism, a low-pass filtering process is performed on the vertical displacement of the suspension to obtain a target processing result;

[0132] A first-order derivative is performed on the target processing result to determine the suspension vertical acceleration corresponding to the suspension vertical displacement.

[0133] As a preferred implementation, in the embodiment of the present invention, the calculation module is specifically used for:

[0134] Based on the vehicle body vertical acceleration, suspension vertical acceleration and vehicle speed, the first eigenvalue and the second eigenvalue are calculated using the following formula:

[0135]

[0136]

[0137] Among them, X Body represents the first eigenvalue, a Bodyz is the vertical acceleration of the vehicle body, v x Indicates vehicle speed, X Suspension represents the second eigenvalue, a Suspension represents the vertical acceleration of the suspension;

[0138] Based on the first eigenvalue and the second eigenvalue, target eigenvalues ​​corresponding to the body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles are calculated respectively, and the target eigenvalues ​​include a root mean square value and a variance value.

[0139] As a preferred implementation, in the embodiment of the present invention, the calculation module is further used for:

[0140] The root mean square value corresponding to the body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles is calculated using a root mean square calculation function, wherein the root mean square calculation function includes:

[0141]

[0142]

[0143] Among them, Y 1Rms Indicates the root mean square value of the vertical acceleration of the vehicle body, Y 2Rms represents the root mean square value of the vertical acceleration of the suspension, X 1k represents the first eigenvalue corresponding to the kth operation cycle, X 2k represents the second eigenvalue corresponding to the kth operating cycle, and M represents the number of operating cycles.

[0144] As a preferred implementation, in the embodiment of the present invention, the calculation module is further used for:

[0145] The variance calculation function is used to calculate the variance values ​​corresponding to the body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles, and the variance calculation function includes:

[0146]

[0147]

[0148] in, It represents the variance value corresponding to the vertical acceleration of the vehicle body. represents the variance value corresponding to the vertical acceleration of the suspension, β1 represents the average value of the vertical acceleration of the vehicle body, β2 represents the average value of the vertical acceleration of the suspension, and X 1k represents the first eigenvalue corresponding to the kth operation cycle, X 2k represents the second eigenvalue corresponding to the kth operating cycle, and M represents the number of operating cycles.

[0149] As a preferred implementation, in the embodiment of the present invention, the road surface grade determination module is specifically used for:

[0150] In response to detecting that the root mean square value corresponding to the vertical acceleration of the vehicle body is greater than a first preset value within M operating cycles, and / or the root mean square value corresponding to the vertical acceleration of the suspension is greater than a second preset value, and / or the variance value corresponding to the vertical acceleration of the vehicle body is greater than a third preset value, and / or the variance value corresponding to the vertical acceleration of the suspension is greater than a fourth preset value, a first target road surface grade is determined based on a first objective function, wherein the first objective function includes:

[0151]

[0152]

[0153] Wherein, d1 represents the first output value, b1 and c1 represent the weight coefficients of the root mean square value, d2 represents the second output value, b2 and c2 represent the weight coefficients of the variance value;

[0154] Based on a first preset mapping table, determining a first road surface grade and a second road surface grade corresponding to the first output value and the second output value respectively;

[0155] A second target road surface grade is determined based on the first road surface grade and the second road surface grade, and a second objective function, wherein the second objective function includes:

[0156]

[0157] Wherein, F represents the third output value, and γ represents the target weight coefficient;

[0158] Based on the second preset mapping table, a second target road surface grade corresponding to the third output value is determined, which is the final road surface grade.

[0159] As a preferred implementation, in the embodiment of the present invention, the adjustment module is specifically used for:

[0160] In response to detecting that the road surface grade is greater than a fifth preset value, determining the damping coefficient adjustment value corresponding to the road surface grade based on a mapping relationship table between the road surface grade and the damping coefficient adjustment value;

[0161] Based on the damping coefficient adjustment value, the current damping coefficient of the target vehicle is adjusted upward.

[0162] For the specific definition of the vehicle adaptive adjustment device, please refer to the definition of the vehicle adaptive adjustment method above, which will not be repeated here. Each module in the above-mentioned vehicle adaptive adjustment device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0163] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a vehicle adaptive adjustment method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0164] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0165] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0166] S1: Obtain the vertical acceleration of the target vehicle, the vertical displacement of the suspension, and the vehicle speed;

[0167] S2: preprocessing the vertical displacement of the suspension to determine the vertical acceleration of the suspension corresponding to the vertical displacement of the suspension;

[0168] S3: Calculating and obtaining a target characteristic value based on the vehicle body vertical acceleration, the suspension vertical acceleration and the vehicle speed;

[0169] S4: in response to detecting that the target characteristic value is greater than a preset threshold, determining a road surface grade based on the target characteristic value;

[0170] S5: Based on the road surface grade determination result, the operating parameters of the target vehicle are adjusted to achieve adaptive adjustment of the target vehicle.

[0171] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0172] Obtaining a vertical displacement of a suspension of the target vehicle;

[0173] Based on a low-pass filtering mechanism, a low-pass filtering process is performed on the vertical displacement of the suspension to obtain a target processing result;

[0174] A first-order derivative is performed on the target processing result to determine the suspension vertical acceleration corresponding to the suspension vertical displacement.

[0175] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0176] Based on the vehicle body vertical acceleration, suspension vertical acceleration and vehicle speed, the first eigenvalue and the second eigenvalue are calculated using the following formula:

[0177]

[0178]

[0179] Among them, X Body represents the first eigenvalue, a Bodyz is the vertical acceleration of the vehicle body, v x Indicates vehicle speed, X Suspension represents the second eigenvalue, a Suspension represents the vertical acceleration of the suspension;

[0180] Based on the first eigenvalue and the second eigenvalue, target eigenvalues ​​corresponding to the body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles are calculated respectively, and the target eigenvalues ​​include a root mean square value and a variance value.

[0181] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0182] The root mean square value corresponding to the body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles is calculated using a root mean square calculation function, wherein the root mean square calculation function includes:

[0183]

[0184]

[0185] Among them, Y 1Rms Indicates the root mean square value of the vertical acceleration of the vehicle body, Y 2Rms represents the root mean square value of the vertical acceleration of the suspension, X 1k represents the first eigenvalue corresponding to the kth operation cycle, X 2k represents the second eigenvalue corresponding to the kth operating cycle, and M represents the number of operating cycles.

[0186] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0187] The variance calculation function is used to calculate the variance values ​​corresponding to the body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles, and the variance calculation function includes:

[0188]

[0189]

[0190] in, It represents the variance value corresponding to the vertical acceleration of the vehicle body. represents the variance value corresponding to the vertical acceleration of the suspension, β1 represents the average value of the vertical acceleration of the vehicle body, β2 represents the average value of the vertical acceleration of the suspension, and X 1k represents the first eigenvalue corresponding to the kth operation cycle, X 2k represents the second eigenvalue corresponding to the kth operating cycle, and M represents the number of operating cycles.

[0191] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0192] In response to detecting that the root mean square value corresponding to the vertical acceleration of the vehicle body is greater than a first preset value within M operating cycles, and / or the root mean square value corresponding to the vertical acceleration of the suspension is greater than a second preset value, and / or the variance value corresponding to the vertical acceleration of the vehicle body is greater than a third preset value, and / or the variance value corresponding to the vertical acceleration of the suspension is greater than a fourth preset value, a first target road surface grade is determined based on a first objective function, wherein the first objective function includes:

[0193]

[0194]

[0195] Wherein, d1 represents the first output value, b1 and c1 represent the weight coefficients of the root mean square value, d2 represents the second output value, b2 and c2 represent the weight coefficients of the variance value;

[0196] Based on a first preset mapping table, determining a first road surface grade and a second road surface grade corresponding to the first output value and the second output value respectively;

[0197] A second target road surface grade is determined based on the first road surface grade and the second road surface grade, and a second objective function, wherein the second objective function includes:

[0198]

[0199] Wherein, F represents the third output value, and γ represents the target weight coefficient;

[0200] Based on the second preset mapping table, a second target road surface grade corresponding to the third output value is determined, which is the final road surface grade.

[0201] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0202] In response to detecting that the road surface grade is greater than a fifth preset value, determining the damping coefficient adjustment value corresponding to the road surface grade based on a mapping relationship table between the road surface grade and the damping coefficient adjustment value;

[0203] Based on the damping coefficient adjustment value, the current damping coefficient of the target vehicle is adjusted upward.

[0204] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0205] S1: Obtain the vertical acceleration of the target vehicle, the vertical displacement of the suspension, and the vehicle speed;

[0206] S2: preprocessing the vertical displacement of the suspension to determine the vertical acceleration of the suspension corresponding to the vertical displacement of the suspension;

[0207] S3: Calculating and obtaining a target characteristic value based on the vehicle body vertical acceleration, the suspension vertical acceleration and the vehicle speed;

[0208] S4: in response to detecting that the target characteristic value is greater than a preset threshold, determining a road surface grade based on the target characteristic value;

[0209] S5: Based on the road surface grade determination result, the operating parameters of the target vehicle are adjusted to achieve adaptive adjustment of the target vehicle.

[0210] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0211] Obtaining a vertical displacement of a suspension of the target vehicle;

[0212] Based on a low-pass filtering mechanism, a low-pass filtering process is performed on the vertical displacement of the suspension to obtain a target processing result;

[0213] A first-order derivative is performed on the target processing result to determine the suspension vertical acceleration corresponding to the suspension vertical displacement.

[0214] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0215] Based on the vehicle body vertical acceleration, suspension vertical acceleration and vehicle speed, the first eigenvalue and the second eigenvalue are calculated using the following formula:

[0216]

[0217]

[0218] Among them, X Body represents the first eigenvalue, a Bodyz is the vertical acceleration of the vehicle body, v x Indicates vehicle speed, X Suspension represents the second eigenvalue, a Suspension represents the vertical acceleration of the suspension;

[0219] Based on the first eigenvalue and the second eigenvalue, target eigenvalues ​​corresponding to the body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles are calculated respectively, and the target eigenvalues ​​include a root mean square value and a variance value.

[0220] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0221] The root mean square value corresponding to the body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles is calculated using a root mean square calculation function, wherein the root mean square calculation function includes:

[0222]

[0223]

[0224] Among them, Y 1Rms Indicates the root mean square value of the vertical acceleration of the vehicle body, Y 2Rms represents the root mean square value of the vertical acceleration of the suspension, X 1krepresents the first eigenvalue corresponding to the kth operation cycle, X 2k represents the second eigenvalue corresponding to the kth operating cycle, and M represents the number of operating cycles.

[0225] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0226] The variance calculation function is used to calculate the variance values ​​corresponding to the body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles, and the variance calculation function includes:

[0227]

[0228]

[0229] in, It represents the variance value corresponding to the vertical acceleration of the vehicle body. represents the variance value corresponding to the vertical acceleration of the suspension, β1 represents the average value of the vertical acceleration of the vehicle body, β2 represents the average value of the vertical acceleration of the suspension, and X 1k represents the first eigenvalue corresponding to the kth operation cycle, X 2k represents the second eigenvalue corresponding to the kth operating cycle, and M represents the number of operating cycles.

[0230] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0231] In response to detecting that the root mean square value corresponding to the vertical acceleration of the vehicle body is greater than a first preset value within M operating cycles, and / or the root mean square value corresponding to the vertical acceleration of the suspension is greater than a second preset value, and / or the variance value corresponding to the vertical acceleration of the vehicle body is greater than a third preset value, and / or the variance value corresponding to the vertical acceleration of the suspension is greater than a fourth preset value, a first target road surface grade is determined based on a first objective function, wherein the first objective function includes:

[0232]

[0233]

[0234] Wherein, d1 represents the first output value, b1 and c1 represent the weight coefficients of the root mean square value, d2 represents the second output value, b2 and c2 represent the weight coefficients of the variance value;

[0235] Based on a first preset mapping table, determining a first road surface grade and a second road surface grade corresponding to the first output value and the second output value respectively;

[0236] A second target road surface grade is determined based on the first road surface grade and the second road surface grade, and a second objective function, wherein the second objective function includes:

[0237]

[0238] Wherein, F represents the third output value, and γ represents the target weight coefficient;

[0239] Based on the second preset mapping table, a second target road surface grade corresponding to the third output value is determined, which is the final road surface grade.

[0240] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0241] In response to detecting that the road surface grade is greater than a fifth preset value, determining the damping coefficient adjustment value corresponding to the road surface grade based on a mapping relationship table between the road surface grade and the damping coefficient adjustment value;

[0242] Based on the damping coefficient adjustment value, the current damping coefficient of the target vehicle is adjusted upward.

[0243] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0244] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0245] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A vehicle adaptive adjustment method, characterized in that: The method comprises: Obtain the target vehicle's body vertical acceleration, suspension vertical displacement, and vehicle speed; Preprocessing the vertical displacement of the suspension to determine the vertical acceleration of the suspension corresponding to the vertical displacement of the suspension; Calculating and acquiring a target characteristic value based on the vehicle body vertical acceleration, the suspension vertical acceleration and the vehicle speed; In response to detecting that the target characteristic value is greater than a preset threshold, determining a road surface grade based on the target characteristic value; Based on the road surface grade determination result, the operating parameters of the target vehicle are adjusted to achieve adaptive adjustment of the target vehicle; The calculating and obtaining the target characteristic value based on the vehicle body vertical acceleration, the suspension vertical acceleration and the vehicle speed includes: Based on the vehicle body vertical acceleration, the suspension vertical acceleration and the vehicle speed, a first eigenvalue and a second eigenvalue are calculated using the following calculation formula: Among them, X Body represents the first eigenvalue, a Bodyz represents the vertical acceleration of the vehicle body, v x represents the vehicle speed, X Suspension represents the second eigenvalue, a Suspension represents the vertical acceleration of the suspension; Based on the first eigenvalue and the second eigenvalue, target eigenvalues ​​corresponding to the body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles are calculated respectively, and the target eigenvalues ​​include a root mean square value and a variance value.

2. The vehicle adaptive adjustment method according to claim 1, characterized in that: Preprocessing the vertical displacement of the suspension to determine the vertical acceleration of the suspension corresponding to the vertical displacement of the suspension includes: Obtaining a vertical displacement of a suspension of the target vehicle; Based on a low-pass filtering mechanism, a low-pass filtering process is performed on the vertical displacement of the suspension to obtain a target processing result; A first-order derivative is performed on the target processing result to determine the suspension vertical acceleration corresponding to the suspension vertical displacement.

3. The vehicle adaptive adjustment method according to claim 1, characterized in that: Calculating the root mean square values ​​of the vehicle body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles based on the first eigenvalue and the second eigenvalue includes: The root mean square value corresponding to the body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles is calculated using a root mean square calculation function, wherein the root mean square calculation function includes: Among them, Y 1Rms Indicates the root mean square value of the vertical acceleration of the vehicle body, Y 2Rms represents the root mean square value of the vertical acceleration of the suspension, X 1k represents the first eigenvalue corresponding to the kth operation cycle, X 2k represents the second eigenvalue corresponding to the kth operating cycle, and M represents the number of operating cycles.

4. The vehicle adaptive adjustment method according to claim 1, characterized in that: Calculating the variance values ​​corresponding to the vehicle body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles based on the first eigenvalue and the second eigenvalue includes: The variance calculation function is used to calculate the variance values ​​corresponding to the body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles, and the variance calculation function includes: in, Indicates the variance value corresponding to the vertical acceleration of the vehicle body, represents the variance value corresponding to the vertical acceleration of the suspension, β1 represents the average value of the vertical acceleration of the vehicle body, β2 represents the average value of the vertical acceleration of the suspension, and X 1k represents the first eigenvalue corresponding to the kth operation cycle, X 2k represents the second eigenvalue corresponding to the kth operating cycle, and M represents the number of operating cycles.

5. The vehicle adaptive adjustment method according to claim 1, characterized in that: In response to detecting that the target characteristic value is greater than a preset threshold, determining the road surface grade based on the target characteristic value includes: In response to detecting that the root mean square value corresponding to the vertical acceleration of the vehicle body is greater than a first preset value within M operating cycles, and / or the root mean square value corresponding to the vertical acceleration of the suspension is greater than a second preset value, and / or the variance value corresponding to the vertical acceleration of the vehicle body is greater than a third preset value, and / or the variance value corresponding to the vertical acceleration of the suspension is greater than a fourth preset value, a first target road surface grade is determined based on a first objective function, wherein the first objective function includes: Wherein, d1 represents the first output value, b1 and c1 represent the weight coefficients of the root mean square value, d2 represents the second output value, b2 and c2 represent the weight coefficients of the variance value; Based on a first preset mapping table, determining a first road surface grade and a second road surface grade corresponding to the first output value and the second output value respectively; A second target road surface grade is determined based on the first road surface grade and the second road surface grade, and a second objective function, wherein the second objective function includes: Wherein, F represents the third output value, and γ represents the target weight coefficient; Based on the second preset mapping table, a second target road surface grade corresponding to the third output value is determined, which is the final road surface grade.

6. The vehicle adaptive adjustment method according to claim 1, characterized in that: Based on the road surface grade determination result, adjusting the operating parameters of the target vehicle includes: In response to detecting that the road surface grade is greater than a fifth preset value, determining the damping coefficient adjustment value corresponding to the road surface grade based on a mapping relationship table between the road surface grade and the damping coefficient adjustment value; Based on the damping coefficient adjustment value, the current damping coefficient of the target vehicle is adjusted upward.

7. A vehicle adaptive adjustment device, characterized in that: The device comprises: A data acquisition module is used to obtain the vertical acceleration of the target vehicle, the vertical displacement of the suspension, and the vehicle speed; A preprocessing module, used for preprocessing the vertical displacement of the suspension to determine the vertical acceleration of the suspension corresponding to the vertical displacement of the suspension; A calculation module is used to calculate a first eigenvalue and a second eigenvalue based on the vehicle body vertical acceleration, the suspension vertical acceleration and the vehicle speed, and based on the first eigenvalue and the second eigenvalue, respectively calculate target eigenvalues ​​corresponding to the vehicle body vertical acceleration and the suspension vertical acceleration of the target vehicle in M ​​operating cycles, wherein the target eigenvalues ​​include a root mean square value and a variance value; the calculation formula is: Among them, X Body represents the first eigenvalue, a Bodyz represents the vertical acceleration of the vehicle body, v x represents the vehicle speed, X Suspension represents the second eigenvalue, a Suspension represents the vertical acceleration of the suspension; A road surface grade determination module, configured to determine a road surface grade based on the target characteristic value when detecting that the target characteristic value is greater than a preset threshold; The adjustment module is used to adjust the operating parameters of the target vehicle based on the road surface grade determination result to achieve adaptive adjustment of the target vehicle.

8. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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