Vehicle suspension adjusting method and system, vehicle and storage medium

Abstract

The invention relates to a vehicle suspension adjusting method and system, a vehicle and a storage medium. The method comprises the following steps: acquiring cabin sensor data of a vehicle; determining a driving experience demand of a user in the cabin according to the cabin sensor data; obtaining a target suspension adjustment parameter matched with the driving experience demand; and the target suspension adjusting parameters are adopted to adjust the soft and hard states of the suspension of the vehicle, so that the handling stability of the vehicle and the smoothness of the whole vehicle are correspondingly adjusted. According to the scheme provided by the invention, the control stability of the vehicle and the smoothness of the whole vehicle can be adjusted based on the driving experience requirement of the user in the cabin, so that the driving experience of the user is effectively guaranteed.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle suspension, and in particular to a vehicle suspension adjustment method, system, vehicle and storage medium. Background Art

[0002] As an important component of the vehicle, the suspension adjustment system's main function is to provide support, cushioning and stability during vehicle driving. Therefore, the performance of the suspension adjustment system is directly related to the vehicle's overall ride comfort and handling stability.

[0003] In related technologies, suspension adjustment systems mostly adjust parameters such as suspension stiffness based on road surface conditions to achieve switching between handling stability and vehicle smoothness. However, related technologies do not take user scenario requirements into consideration and therefore cannot effectively guarantee the user's driving experience. Summary of the invention

[0004] In order to solve or partially solve the problems existing in the related technology, the present application provides a vehicle suspension adjustment method, system, vehicle and storage medium, which can adjust the vehicle's handling stability and vehicle smoothness based on the driving experience requirements of users in the cockpit, thereby effectively ensuring the user's driving experience.

[0005] A first aspect of the present application provides a vehicle suspension adjustment method, comprising:

[0006] Obtain vehicle cabin sensor data;

[0007] Determining the driving experience requirements of the user in the cockpit according to the cockpit sensor data;

[0008] Obtaining target suspension adjustment parameters that match the driving experience requirements;

[0009] The target suspension adjustment parameters are used to adjust the suspension hardness and softness of the vehicle so that the handling stability and the ride comfort of the vehicle are adjusted accordingly.

[0010] In one embodiment, determining the driving experience requirements of the user in the cabin according to the cabin sensor data includes:

[0011] identifying the role type of the user in the cockpit according to the cockpit sensor data;

[0012] If the role type only includes the driver, determining the driving experience requirement of the user in the cockpit as the handling stability requirement; or,

[0013] If the role types include a driver and a passenger, the driving experience requirements of the users in the cockpit are determined to be the whole vehicle smoothness requirements.

[0014] In one embodiment, the automatic driving controller of the vehicle is configured with a plurality of preset driving experience scenarios and preset suspension adjustment parameters corresponding to the plurality of preset driving experience scenarios respectively; the obtaining of the target suspension adjustment parameters matching the driving experience requirements comprises:

[0015] When the driving experience requirement is the handling stability requirement, determining a first driving experience scenario that matches the handling stability requirement from the multiple preset driving experience scenarios, and obtaining preset suspension adjustment parameters corresponding to the first driving experience scenario as target suspension adjustment parameters; or,

[0016] When the driving experience requirement is the whole vehicle smoothness requirement, the number of passengers in the cabin is identified based on the cabin sensor data, so as to determine a second driving experience scenario that matches the whole vehicle smoothness requirement and the number of passengers from the multiple preset driving experience scenarios, and obtain preset suspension adjustment parameters corresponding to the second driving experience scenario as target suspension adjustment parameters.

[0017] In one embodiment, the chassis system of the vehicle includes a suspension assembly, and the target suspension adjustment parameters include a mixing coefficient, a simulated passive damping coefficient, and a skyhook damping coefficient; the use of the target suspension adjustment parameters to adjust the suspension hardness and softness of the vehicle so that the handling stability and the ride comfort of the vehicle are adjusted accordingly includes:

[0018] Calculating a simulated passive damping force according to the simulated passive damping coefficient, and calculating a ceiling control damping force according to the ceiling damping coefficient;

[0019] calculating a suspension damping force according to the mixing coefficient, the simulated passive damping force and the skyhook control damping force;

[0020] Generate a suspension adjustment request using the suspension damping force, and send the suspension adjustment request to the chassis system, so that the chassis system adjusts the current softness or hardness state of the suspension component to the softness or hardness state of the suspension corresponding to the suspension damping force in response to the suspension adjustment request;

[0021] Among them, the soft and hard states of the suspension include at least one of a soft state and a hard state; when the suspension component is in a hard state, the handling stability of the vehicle is improved; when the suspension component is in a soft state, the overall vehicle smoothness of the vehicle is improved.

[0022] In one embodiment, the calculating the simulated passive damping force according to the simulated passive damping coefficient includes:

[0023] Get the sprung mass speed and the unsprung mass speed;

[0024] calculating a relative speed based on the sprung mass speed and the unsprung mass speed;

[0025] A simulated passive damping force is calculated according to the simulated passive damping coefficient and the relative speed.

[0026] In one embodiment, the calculating the ceiling hook control damping force according to the ceiling hook damping coefficient includes:

[0027] determining whether the sprung mass velocity and the relative velocity are in the same direction;

[0028] If the sprung mass velocity is in the same direction as the relative velocity, a skyhook control damping force is calculated based on the skyhook damping coefficient and the sprung mass velocity.

[0029] In one embodiment, the step of obtaining the vehicle cabin sensor data includes:

[0030] Obtaining image data collected by a vehicle's cabin monitoring camera; and / or,

[0031] Obtaining radar data collected by a vehicle's cabin monitoring radar; and / or,

[0032] Obtain pressure data collected by the vehicle's cabin pressure sensor.

[0033] The second aspect of the present application provides a vehicle suspension adjustment system, comprising: a cockpit sensor and an automatic driving controller; wherein:

[0034] The cockpit sensor is used to collect cockpit sensor data of the vehicle;

[0035] The automatic driving controller is used to obtain the cockpit sensor data; determine the driving experience requirements of the user in the cockpit based on the cockpit sensor data; obtain target suspension adjustment parameters that match the driving experience requirements; and use the target suspension adjustment parameters to adjust the suspension hardness and softness of the vehicle so that the handling stability and vehicle ride comfort of the vehicle are adjusted accordingly.

[0036] A third aspect of the present application provides a vehicle, comprising:

[0037] Processor; and

[0038] The memory stores executable codes thereon, and when the executable codes are executed by the processor, the processor is caused to execute the method as described above.

[0039] A fourth aspect of the present application provides a computer-readable storage medium having executable code stored thereon. When the executable code is executed by a processor of a vehicle, the processor is caused to execute the method as described above.

[0040] The technical solution provided by this application may have the following beneficial effects:

[0041] The solution provided by the present application obtains the vehicle's cabin sensor data; determines the driving experience requirements of the users in the cabin based on the cabin sensor data; obtains the target suspension adjustment parameters that match the driving experience requirements; and uses the target suspension adjustment parameters to adjust the vehicle's suspension hardness and softness, so that the vehicle's handling stability and vehicle ride comfort are adjusted accordingly. The present application can determine the driving experience requirements of the users in the cabin through the cabin sensor data. The driving experience requirements may include at least one of the handling stability requirements and the vehicle ride comfort requirements. Therefore, based on different driving experience requirements, different suspension response effects are achieved, thereby achieving the adjustment of the handling stability and the vehicle ride comfort, thereby effectively ensuring the user's driving experience.

[0042] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The above and other objects, features and advantages of the present application will become more apparent by describing in more detail the exemplary embodiments of the present application in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same components in the exemplary embodiments of the present application.

[0044] Figure 1 is a flow chart of a vehicle suspension adjustment method shown in an embodiment of the present application;

[0045] Figure 2 is another schematic flow chart of a vehicle suspension adjustment method shown in an embodiment of the present application;

[0046] Figure 3 It is a schematic diagram of the architecture of the resnet-50 model shown in the embodiment of the present application;

[0047] Figure 4 is a schematic diagram of the architecture of the suspension control model shown in the embodiment of the present application;

[0048] Figure 5 is a structural schematic diagram of a vehicle suspension adjustment system shown in an embodiment of the present application;

[0049] Figure 6 is a structural diagram of an automatic driving controller shown in an embodiment of the present application;

[0050] Figure 7 It is a schematic diagram of the structure of a vehicle shown in an embodiment of the present application. DETAILED DESCRIPTION

[0051] The embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to make the present application more thorough and complete, and to fully convey the scope of the present application to those skilled in the art.

[0052] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0053] It should be understood that although the terms "first", "second", "third", etc. may be used in this application to describe various information, this information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of this application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of this application, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0054] In the related technologies, the suspension adjustment systems mostly adjust parameters such as suspension stiffness based on road surface conditions, so as to achieve switching between vehicle smoothness and handling stability. However, the related technologies do not take user scenario requirements into consideration, and therefore cannot well guarantee the user's driving experience.

[0055] In response to the above problems, an embodiment of the present application provides a vehicle suspension adjustment method. The driving experience requirements of users in the cabin can be determined through cabin sensor data. The driving experience requirements may include at least one of the handling stability requirements and the vehicle smoothness requirements. Therefore, based on different driving experience requirements, different suspension response effects are achieved, thereby achieving the adjustment of handling stability and vehicle smoothness, thereby effectively ensuring the user's driving experience.

[0056] The technical solution of the embodiments of the present application is described in detail below with reference to the accompanying drawings.

[0057] Figure 1 It is a flow chart of the vehicle suspension adjustment method shown in the embodiment of the present application.

[0058] See also Figure 1 The vehicle suspension adjustment method of the present application may include:

[0059] S110, obtaining cockpit sensor data of the vehicle.

[0060] Among them, the executor of the suspension adjustment of this vehicle can be an automatic driving controller mounted on the vehicle, and the automatic driving controller is respectively connected to various cockpit sensors and to the chassis system. Among them, the various cockpit sensors can include at least one of a cockpit monitoring system (OMS, Occupant Monitoring System) and a cockpit pressure sensor, wherein the cockpit monitoring system can include at least one of a cockpit monitoring camera and a cockpit monitoring radar. During the driving process of the vehicle, the automatic driving controller can obtain cockpit sensor data collected by at least one cockpit sensor, wherein the cockpit sensor data can include at least one of image data, radar data and pressure data.

[0061] S120: Determine the driving experience requirements of the user in the cabin based on the cabin sensor data.

[0062] The cabin sensor data can reflect the riding conditions of the users in the cabin. Different riding conditions of the users in the cabin will lead to different driving experience requirements of the users in the cabin. Therefore, the autonomous driving controller can identify the riding conditions of the users in the cabin based on the cabin sensor data, and then determine the driving experience requirements of the users in the cabin based on the riding conditions of the users in the cabin.

[0063] Among them, driving experience requirements refer to the various needs and expectations of users for the vehicle during driving or riding. The degree of satisfaction of driving experience requirements directly affects the user's satisfaction and loyalty to the vehicle. Among them, driving experience requirements can include at least one of the requirements for handling stability and the requirements for vehicle smoothness.

[0064] It should be noted that the in-cabin user refers to the user riding in the vehicle cabin, wherein the vehicle cabin may include a cockpit and a passenger cabin, the cockpit refers to the working area where the driver operates the vehicle, and the passenger cabin refers to the resting area for the front passenger and the rear passengers.

[0065] S130: Obtain target suspension adjustment parameters that match driving experience requirements.

[0066] The driving experience requirements of users in the cockpit are different, so the required suspension response effects will also be different. Therefore, after the automatic driving controller determines the driving experience requirements of users in the cockpit, it can obtain the target suspension adjustment parameters that match the driving experience requirements.

[0067] S140, using the target suspension adjustment parameters to adjust the suspension hardness and softness of the vehicle so that the handling stability and the ride comfort of the vehicle are adjusted accordingly.

[0068] The suspension is an integral part of the chassis system, so the automatic driving controller can use the target suspension adjustment parameters to generate a suspension adjustment request for adjusting the hardness and softness of the suspension, and then send the suspension adjustment request to the chassis system so that the suspension adjustment request can be executed by the chassis system to adjust the hardness and softness of the vehicle's suspension. The softness and hardness of the vehicle's suspension are different, and the vehicle's handling stability and vehicle ride comfort are also different. Therefore, by adjusting the vehicle's suspension hardness and softness, the vehicle's handling stability and vehicle ride comfort can be adjusted accordingly. For example, by adjusting the vehicle's suspension hardness and softness to a hard state, the vehicle's handling stability and vehicle ride comfort can be improved. For example, by adjusting the vehicle's suspension hardness and softness to a soft state, the vehicle's overall ride comfort can be improved.

[0069] It should be noted that handling stability and vehicle ride comfort are two important indicators for evaluating vehicle performance, which respectively involve the vehicle's operating characteristics and driving experience under different conditions. For example, handling stability includes two main aspects: maneuverability and stability. Good maneuverability means that the vehicle can operate according to the driver's requirements, while good stability means that the vehicle can resist external interference and maintain stable driving. Vehicle ride comfort (MPV, Multi-Purpose Vehicles) is closely related to the vertical movement of the vehicle, mainly involving the dynamic response of the vehicle in different directions. Vehicle ride comfort requires the vehicle to be able to cope with high-frequency vibrations and impacts from the road surface and provide a comfortable ride experience.

[0070] It can be seen that compared with the related art that adjusts the vehicle's handling stability and vehicle smoothness based on road surface conditions, the embodiment of the present application adjusts the vehicle's handling stability and vehicle smoothness based on the driving experience needs of users in the cockpit, thereby fully considering user scenario needs and effectively ensuring user driving experience.

[0071] In addition, the related technologies rely on high-precision road condition collection devices (such as laser radar, ultrasonic radar, surround view camera, etc.), which have high implementation costs and cannot guarantee the implementation effect. For example, during vehicle driving, the related technologies need to collect road condition information in real time through road condition collection devices, and then adjust the vehicle's handling stability and vehicle ride comfort in real time based on the road condition information. However, the vehicle's driving speed is generally fast, so it is easy to have untimely road condition information collection or untimely processing, resulting in failure to adjust the vehicle's handling stability and vehicle ride comfort in time. Therefore, the implementation effect cannot be guaranteed, and the user's driving experience cannot be guaranteed. In this regard, the embodiment of the present application utilizes the original equipment of the existing vehicle model, without the need to add new sensors or equipment, and can implement the suspension adjustment strategy based on the cabin sensor data through software updates. While ensuring the user's driving experience, the implementation cost of this strategy is low and the implementation effect is good.

[0072] As can be seen from this example, the solution provided by this application obtains the vehicle's cabin sensor data; determines the driving experience requirements of users in the cabin based on the cabin sensor data; obtains target suspension adjustment parameters that match the driving experience requirements; and uses the target suspension adjustment parameters to adjust the vehicle's suspension hardness and softness to adjust the vehicle's handling stability and vehicle ride comfort accordingly. This application can determine the driving experience requirements of users in the cabin through cabin sensor data. The driving experience requirements may include at least one of the handling stability requirements and the vehicle ride comfort requirements. Therefore, based on different driving experience requirements, different suspension response effects are achieved, thereby achieving the adjustment of handling stability and vehicle ride comfort, thereby effectively ensuring the user's driving experience.

[0073] Figure 2 It is another flow chart of the vehicle suspension adjustment method shown in the present application.

[0074] See also Figure 2 The vehicle suspension adjustment method of the present application may include:

[0075] S210, obtaining cockpit sensor data of the vehicle.

[0076] For this step, please refer to the description in S110 and will not be repeated here.

[0077] In one implementation, obtaining cabin sensor data of a vehicle may include:

[0078] Acquire image data collected by a vehicle's cabin monitoring camera; and / or, acquire radar data collected by a vehicle's cabin monitoring radar; and / or, acquire pressure data collected by a vehicle's cabin pressure sensor.

[0079] The vehicle is equipped with various cabin sensors, which may include at least one of a cabin monitoring camera, a cabin monitoring radar, and a cabin pressure sensor.

[0080] During vehicle driving, the automatic driving controller can obtain image data collected by the cabin monitoring camera; or, the automatic driving controller can obtain radar data collected by the cabin monitoring radar; or, the automatic driving controller can obtain pressure data collected by the cabin pressure sensor; or, the automatic driving controller can separately obtain image data collected by the cabin monitoring camera and radar data collected by the cabin monitoring radar; or, the automatic driving controller can separately obtain image data collected by the cabin monitoring camera and pressure data collected by the cabin pressure sensor; or, the automatic driving controller can separately obtain radar data collected by the cabin monitoring radar and pressure data collected by the cabin pressure sensor; or, the automatic driving controller can separately obtain image data collected by the cabin monitoring camera, radar data collected by the cabin monitoring radar and pressure data collected by the cabin pressure sensor, so the cabin sensor data can include at least one of image data, radar data and pressure data.

[0081] S220: Identify the role type of the user in the cockpit according to the cockpit sensor data.

[0082] The cabin sensor data can reflect the riding conditions of the users in the cabin. The riding conditions of the users in the cabin may include the role types of the users in the cabin. The role types of the users in the cabin refer to the role types played by the users in the cabin during the driving of the vehicle. Generally speaking, the role types of the users in the cabin may include at least one of the driver and the passenger. The driver is responsible for driving and controlling the vehicle, while the passenger is the service object of the vehicle operation.

[0083] In a specific implementation, the cockpit sensor data may include cockpit sensor data of the two areas of the cockpit and the passenger compartment. Since the driver is responsible for driving and controlling the vehicle, the driver is an indispensable role type during the driving of the vehicle. Therefore, the automatic driving controller may not need to identify whether there is anyone in the cockpit, but directly identify whether there is anyone in the passenger compartment, where the passenger compartment may include the front passenger compartment and the rear passenger compartment. If it is identified that there is no one in the front passenger compartment and the rear passenger compartment, the automatic driving controller can identify that the role type of the user in the cockpit only includes the driver, but not the passenger, so it can enter step S231; if it is identified that there are people in the front passenger compartment and / or the rear passenger compartment, the automatic driving controller can identify that the role type of the user in the cockpit includes the driver and the passenger, so it can enter step S232.

[0084] S231: If the role type only includes the driver, determining the driving experience requirement of the user in the cockpit as the handling stability requirement.

[0085] If the role type only includes the driver, it means that there are no passengers in the vehicle cabin. Therefore, the embodiment of the present application can focus on the driver's driving experience requirements, wherein the driver's driving experience requirements are handling stability requirements, so step S241 can be entered.

[0086] S232: If the role types include a driver and a passenger, determining the driving experience requirements of the users in the cockpit as the whole vehicle smoothness requirements.

[0087] If the role types include the driver and the passengers, it means that there are passengers in the vehicle cabin, such as the front passenger and / or the rear passengers. Therefore, the embodiment of the present application can focus on the driving experience requirements of the passengers, wherein the driving experience requirements of the passengers are the smoothness requirements of the entire vehicle, and therefore step S242 can be entered.

[0088] S241, obtaining target suspension adjustment parameters that match the handling stability requirements.

[0089] The handling stability requirement is used to characterize the vehicle's need for better handling stability. The handling stability mainly focuses on how the vehicle responds to the driver's control and resists external interference. Therefore, the automatic driving controller can obtain the target suspension adjustment parameters that match the handling stability requirement. The target suspension adjustment parameters that match the handling stability requirement can be used to improve the vehicle's handling stability, thereby effectively guaranteeing the driver's driving experience requirements.

[0090] In one embodiment, the vehicle's automatic driving controller is configured with a plurality of preset driving experience scenarios and preset suspension adjustment parameters corresponding to the plurality of preset driving experience scenarios.

[0091] In order to improve the efficiency of suspension adjustment, the automatic driving controller can pre-configure a variety of preset driving experience scenarios, wherein each preset driving experience scenario has corresponding preset suspension adjustment parameters.

[0092] In one example, the preset driving experience scenario is as follows:

[0093] Preset driving experience scenario 1: Only the driver is in the vehicle cabin;

[0094] Preset driving experience scenario 2: There are two users in the vehicle cabin;

[0095] Preset driving experience scenario 3: There are three users in the vehicle cabin;

[0096] ……;

[0097] Preset driving experience scenario i: there are i users in the vehicle cabin.

[0098] Wherein, i is a positive integer, and when i≥2, the i-th user includes the driver and the passenger.

[0099] In one example, the preset suspension adjustment parameters are as follows:

[0100] Under the preset driving experience scenario 1, the corresponding preset suspension adjustment parameters are: α1, C sky1 , C f1 ;

[0101] Under the preset driving experience scenario 2, the corresponding preset suspension adjustment parameters are: α2, C sky2 , C f2 ;

[0102] Under the preset driving experience scenario 3, the corresponding preset suspension adjustment parameters are: α3, C sky3 , C f3 ;

[0103] ……;

[0104] Under the preset driving experience scenario i, the corresponding preset suspension adjustment parameters are: α i , C skyi , C fi ;

[0105] Among them, α represents the mixing coefficient, C sky represents the ceiling damping coefficient, C f represents the simulated passive damping coefficient.

[0106] It should be noted that the preset suspension adjustment parameters corresponding to different preset driving experience scenarios are determined through actual vehicle parameter calibration tests.

[0107] In one embodiment, obtaining target suspension adjustment parameters that match the handling stability requirement may include:

[0108] When the driving experience requirement is a handling stability requirement, a first driving experience scenario matching the handling stability requirement is determined from a plurality of preset driving experience scenarios, and preset suspension adjustment parameters corresponding to the first driving experience scenario are obtained as target suspension adjustment parameters.

[0109] When the driving experience requirement is a handling stability requirement, the automatic driving controller can determine the first driving experience scenario that matches the handling stability requirement from the preset driving experience scenarios 1 to the preset driving experience scenarios i as the preset driving experience scenario 1, thereby obtaining the preset suspension adjustment parameters (α1, C sky1 , C f1 ), the preset suspension adjustment parameters (α1, C sky1 , C f1) can be used to improve the vehicle's handling stability, thereby effectively ensuring the driver's driving experience needs.

[0110] S242, obtaining target suspension adjustment parameters that match the vehicle's smoothness requirements.

[0111] The vehicle ride comfort requirement is used to characterize the need for a better vehicle ride comfort. The vehicle ride comfort focuses on how the vehicle provides a comfortable ride experience and copes with vibrations caused by uneven road surfaces. Therefore, the autonomous driving controller can obtain target suspension adjustment parameters that match the vehicle ride comfort requirement. The target suspension adjustment parameters that match the vehicle ride comfort requirement can be used to improve the vehicle ride comfort, thereby effectively ensuring the occupants' driving experience requirements.

[0112] In one embodiment, obtaining target suspension adjustment parameters that match the vehicle ride comfort requirements may include:

[0113] When the driving experience requirement is the smoothness requirement of the entire vehicle, the number of passengers in the cabin is identified based on the cabin sensor data, so as to determine a second driving experience scenario that matches the smoothness requirement of the entire vehicle and the number of passengers from a variety of preset driving experience scenarios, and obtain the preset suspension adjustment parameters corresponding to the second driving experience scenario as the target suspension adjustment parameters.

[0114] When there are passengers in the vehicle cabin, the embodiments of the present application need to focus on the passengers' vehicle smoothness requirements, where different numbers of passengers have corresponding vehicle smoothness requirements. For example, the more passengers there are, the heavier the vehicle body weight is, and thus the greater the improvement in the vehicle smoothness is. Therefore, the embodiments of the present application can further identify the number of passengers in the cabin based on the cabin sensor data, where the number of passengers is the total number of drivers and passengers.

[0115] In one example, assuming that the cabin sensor data is image data collected by a cabin monitoring camera, the autonomous driving controller can pre-train a resnet-50 (deep residual network) model, and then input the image data into the trained resnet-50 model. The architecture diagram of the resnet-50 model is shown in FIG. Figure 3As shown, the image data is an RGB image of 244*244 pixels with 3 channels. The image data is input into the first layer of the resnet-50 model. The first layer may include CONV (convolution layer), batch norm (batch normalization layer), ReLU (Rectified Linear Unit, non-linear activation function layer) and Max pool (maximum pooling layer). The image data can be feature extracted through CONV, the image data can be normalized through batch norm, nonlinearity can be introduced through ReLU, and the feature map size of the image data can be reduced through Max pool. After processing the first layer, the image data can enter the second layer of the resnet-50 model. The second layer may include four residual blocks, each of which may include CONV (convolution layer) and ID block (identification block). The image data can be feature extracted through CONV, and the input and output dimensions of the image data can be ensured to be consistent through ID block. After processing the second layer, the image data can enter the third layer of the resnet-50 model, and the third layer may include Avg pool (Average pool, average pooling layer), Flattening (compression layer) and FC (Fully Connected layer). Avg pool can generate the feature vector of image data, Flattening can compress the spatial dimension of image data, and FC can map the feature vector of image data to the category array to output the number of people in the cabin, that is, the number of passengers in the cabin.

[0116] In another example, assuming that the cabin sensor data is radar data collected by a cabin monitoring radar, the autonomous driving controller can pre-train a classifier that includes multiple scenarios. The autonomous driving controller decomposes the radar data into multiple received signal components, and inputs the multiple received signal components into the trained classifier. The classifier identifies one of the training scenarios based on the multiple received signal components and generates an output signal indicating the identified scene. The output signal is used to characterize the number of users in the cabin.

[0117] In another example, assuming that the cabin sensor data is pressure data collected by a cabin pressure sensor, the automatic driving controller may pre-set a preset pressure threshold, and compare the pressure data of each seat in each cabin with the preset pressure threshold. If the pressure data of a certain seat is greater than or equal to the preset pressure threshold, it is determined that the seat is occupied; if the pressure data of a certain seat is less than the preset pressure threshold, it is determined that the seat is unoccupied, and the number of users in the cabin is obtained by counting the number of occupied seats.

[0118] In another example, in order to improve the recognition accuracy, the autonomous driving controller can identify the number of passengers in the cabin through image data to obtain a first recognition result, and can identify the number of passengers in the cabin through radar data to obtain a second recognition result, and can identify the number of passengers in the cabin through pressure data to obtain a third recognition result. The autonomous driving controller can comprehensively determine the number of passengers in the cabin based on at least two recognition results.

[0119] After identifying the number of passengers in the cabin, the automatic driving controller can determine a second driving experience scenario that matches the vehicle's smoothness requirements and the number of passengers from the above-mentioned preset driving experience scenarios 1 to i. As an example, assuming that the number of passengers is 2, the second driving experience scenario is the preset driving experience scenario 2, so that the preset suspension adjustment parameters (α2, C sky2 , C f2 ), the preset suspension adjustment parameters (α2, C sky2 , C f2 ) can be used to improve the vehicle's overall ride comfort, and the improved overall ride comfort can be adapted to the driving experience requirements of two users (a driver and a passenger) in the vehicle cabin. As another example, assuming that there are four passengers, the second driving experience scenario is the preset driving experience scenario 4, so that the preset suspension adjustment parameters (α4, C sky4 , C f4 ), the preset suspension adjustment parameters (α4, C sky4 , C f4 ) can be used to improve the vehicle's overall smoothness, and the improved vehicle smoothness can adapt to the driving experience needs of 4 users (1 driver and 3 passengers) in the vehicle cabin.

[0120] S250 uses target suspension adjustment parameters to adjust the vehicle's suspension hardness and softness so that the vehicle's handling stability and vehicle ride comfort can be adjusted accordingly.

[0121] For this step, please refer to the description in S140 and will not be repeated here.

[0122] In one embodiment, the chassis system of the vehicle includes a suspension assembly, and the target suspension adjustment parameters include a mixing coefficient, a simulated passive damping coefficient, and a skyhook damping coefficient; using the target suspension adjustment parameters to adjust the suspension hardness and softness of the vehicle so that the handling stability and the ride comfort of the vehicle are adjusted accordingly may include:

[0123] The simulated passive damping force is calculated according to the simulated passive damping coefficient, and the ceiling control damping force is calculated according to the ceiling damping coefficient; the suspension damping force is calculated according to the mixing coefficient, the simulated passive damping force and the ceiling control damping force; the suspension damping force is used to generate a suspension adjustment request, and the suspension adjustment request is sent to the chassis system, so that the chassis system responds to the suspension adjustment request and adjusts the current soft and hard state of the suspension component to the suspension soft and hard state corresponding to the suspension damping force; wherein the suspension soft and hard state includes at least one of a soft state and a hard state; when the suspension component is in a hard state, the handling stability of the vehicle is improved; when the suspension component is in a soft state, the overall vehicle smoothness of the vehicle is improved.

[0124] The chassis system of a vehicle may include a suspension assembly, wherein the suspension assembly is a support device consisting of springs and shock absorbers connected to the vehicle body and wheels.

[0125] The target suspension adjustment parameters may include the mixing coefficient α, the simulated passive damping coefficient C f and the ceiling damping coefficient C sky .

[0126] The automatic driving controller can obtain the simulated passive damping coefficient C f , calculate and simulate the passive damping force F fsd , and the ceiling damping coefficient C can be obtained sky , calculate the ceiling control damping force F skyhook Among them, the simulated passive damping force F fsd In physics and engineering, it refers to a damping force that is proportional to the vibration speed and opposite in direction to the vibration speed of the simulated vibration system. skyhook Refers to the damping force in a vehicle suspension assembly by simulating a damper installed between the vehicle body and a hypothetical "ceiling".

[0127] The autopilot controller can simulate the passive damping force F according to the mixing coefficient α fsd and ceiling control damping force F skyhook , calculate the suspension damping force F acting on the suspension components h , suspension damping force F h The calculation formula is as follows:

[0128] F h =α·F skyhook +(1-α)·F fsd Formula 1

[0129] Figure 4 is the suspension control model, which uses the architecture of a 1 / 4 vehicle model. Figure 4In the above equation, Sky represents the sky (i.e., the hypothetical “ceiling”), m1 represents the unsprung mass, and m2 represents the sprung mass. The sprung mass m1 may refer to the total weight of the vehicle body, the unsprung mass m2 may refer to the mass of the wheels, Z1 represents the unsprung mass displacement, Z2 represents the sprung mass displacement, and Z r represents the road displacement, v1 represents the unsprung mass velocity, v2 represents the sprung mass velocity, K s represents the spring stiffness of the suspension component, Kf represents the elastic stiffness of the wheel, and α·F skyhook and (1-α)·F fsd The suspension damping force F acting on the suspension component can be obtained by superposition of h .

[0130] The autopilot controller can use the suspension damping force F h Generate a suspension adjustment request, and then send the suspension adjustment request F h The chassis system executes the suspension adjustment request from the autonomous driving controller. The adjustment of the current hard and soft state of the suspension component can be achieved by adjusting the damping force of the shock absorber in the suspension component. When the damping force of the shock absorber is adjusted to the suspension damping force F in the suspension adjustment request, h When the current hardness or softness of the suspension component is adjusted to the hardness or softness of the suspension corresponding to the suspension damping force.

[0131] The suspension soft and hard state may include at least one of a soft state and a hard state. When the damping force of the shock absorber is adjusted to a smaller suspension damping force F h When the current hardness and softness of the suspension components are adjusted to the soft state, the vehicle can better absorb the vibration and bumps of the road during driving, so that the vehicle's overall ride comfort can be improved, but the vehicle's handling stability will be reduced. When the damping force of the shock absorber is adjusted to a larger suspension damping force F h When the current soft and hard state of the suspension component is adjusted to the hard state, the vehicle can better filter the vibration and bumps of the road during driving, so that the vehicle's handling stability can be improved, but the vehicle's overall smoothness will be reduced.

[0132] Among them, different degrees of soft state correspond to different improvements in vehicle smoothness. For example, the softer the suspension component, the greater the improvement in the vehicle's overall smoothness. However, an overly soft suspension component will affect driving safety. Therefore, the minimum degree of soft state needs to be greater than the driving safety threshold. Therefore, the embodiment of the present application can improve the vehicle's overall smoothness accordingly while ensuring driving safety, thereby effectively ensuring the vehicle smoothness needs of the occupants.

[0133] In one embodiment, calculating the simulated passive damping force according to the simulated passive damping coefficient may include:

[0134] The sprung mass velocity and the unsprung mass velocity are obtained; the relative velocity is calculated according to the sprung mass velocity and the unsprung mass velocity; and the simulated passive damping force is calculated according to the simulated passive damping coefficient and the relative velocity.

[0135] The embodiment of the present application can simulate the passive damping force F fsd For relative speed v rel Specifically, the automatic driving controller can obtain the sprung mass speed v2 and the unsprung mass speed v1, and then calculate the difference between the sprung mass speed v2 and the unsprung mass speed v1 to obtain the relative speed v rel , and then calculate the simulated passive damping coefficient C f and relative velocity v rel The product value of the simulated passive damping force F fsd .

[0136] Among them, the relative speed v rel The calculation formula is shown in the following formula 2:

[0137] v rel =v2-v1 Formula 2

[0138] Among them, the simulated passive damping force F fsd The calculation formula is shown in the following formula 3:

[0139] F fsd =-C f ·v rel Formula 3

[0140] In one embodiment, calculating the ceiling hook control damping force according to the ceiling hook damping coefficient may include:

[0141] Determine whether the sprung mass velocity and the relative velocity are in the same direction; if the sprung mass velocity and the relative velocity are in the same direction, calculate the ceiling control damping force based on the ceiling damping coefficient and the sprung mass velocity.

[0142] The core idea of ​​the skyhook control strategy is to suppress the vibration of the sprung mass of the 1 / 4 vehicle model. Due to its simple structure and good vehicle ride comfort control effect, it can be used in the control of vehicle suspension components. The algorithm of the skyhook control strategy can be expressed as follows:

[0143]

[0144] Among them, from formula 2, we can know that (v2-v1) is the relative speed v rel , the autopilot controller can determine the sprung mass velocity v2 and the relative velocity v relWhether they are in the same direction, when v2·(v2-v1)≥0, the autopilot controller can determine that the sprung mass velocity and the relative velocity are in the same direction, indicating that a suitable ceiling control damping force F can be applied to the suspension control model skyhook For example, the autopilot controller can calculate the ceiling damping coefficient C by using Equation 4 sky The product of the sprung mass velocity v2 gives the appropriate skyhook control damping force F skyhook ; When v2·(v2-v1)<0, the autopilot controller can determine that the sprung mass velocity and the relative velocity are out of direction, indicating that the minimum ceiling control damping force F can be applied to the suspension control model skyhook For example, the autopilot controller can determine the minimum ceiling control damping force F by using Equation 4: skyhook is zero.

[0145] It can be seen from this example that the solution provided in the present application can determine the driving experience requirements of users in the cabin through cabin sensor data. The driving experience requirements may include at least one of the handling stability requirements and the vehicle smoothness requirements. Therefore, based on different driving experience requirements, different suspension response effects are achieved, thereby achieving the adjustment of handling stability and vehicle smoothness, thereby effectively ensuring the user's driving experience.

[0146] Furthermore, the present application can identify the role type and the number of passengers in the cockpit through cockpit sensor data; if the role type only includes the driver, the driver's driving experience needs can be focused on, wherein the driver's driving experience needs are handling stability needs, and therefore the target suspension adjustment parameters that match the handling stability needs can be used to adjust the vehicle's suspension soft and hard state to a hard state, so that the vehicle's handling stability needs can be improved, thereby effectively ensuring the driver's handling stability needs; if the role type includes the driver and passengers, the passengers' driving experience needs can be focused on, wherein the passengers' driving experience needs are the vehicle's smoothness needs, and therefore the target suspension adjustment parameters that match the vehicle's smoothness needs and the number of passengers can be used to adjust the vehicle's suspension soft and hard state to a soft state, so that the vehicle's smoothness can be improved, thereby effectively ensuring the passengers' vehicle's smoothness needs.

[0147] Furthermore, the present application pre-configures multiple preset driving experience scenarios and preset suspension adjustment parameters corresponding to each preset driving experience scenario, so that in actual applications, target suspension adjustment parameters that match the handling stability requirements can be quickly obtained, or target suspension adjustment parameters that match the vehicle smoothness requirements and the number of passengers can be quickly obtained, thereby improving the suspension adjustment efficiency.

[0148] Furthermore, the present application utilizes existing equipment of existing vehicle models, without the need for new sensors or equipment, and can implement intelligent suspension adjustment strategies based on cockpit sensor data through software updates. While ensuring the user's driving experience, the implementation cost of this strategy is low and the implementation effect is good.

[0149] Corresponding to the aforementioned application function implementation method embodiment, the present application also provides a vehicle suspension adjustment system, a vehicle, a computer-readable storage medium and corresponding embodiments.

[0150] Figure 5 It is a schematic diagram of the structure of a vehicle suspension adjustment system shown in an embodiment of the present application.

[0151] See also Figure 5 The present application provides a vehicle suspension adjustment system 500, which may include: a cabin sensor 510 and an automatic driving controller 520; wherein,

[0152] A cockpit sensor 510, used to collect cockpit sensor data of the vehicle;

[0153] The automatic driving controller 520 is used to obtain cockpit sensor data; determine the driving experience requirements of users in the cockpit based on the cockpit sensor data; obtain target suspension adjustment parameters that match the driving experience requirements; and use the target suspension adjustment parameters to adjust the suspension hardness and softness of the vehicle so that the vehicle's handling stability and overall vehicle ride comfort can be adjusted accordingly.

[0154] See also Figure 6 The automatic driving controller 520 may include: a cockpit sensor data acquisition module 610, a driving experience requirement determination module 620, a target suspension adjustment parameter acquisition module 630 and a suspension hard and soft state adjustment module 640.

[0155] A cockpit sensor data acquisition module 610, used to acquire cockpit sensor data;

[0156] A driving experience requirement determination module 620, for determining the driving experience requirement of the user in the cabin according to the cabin sensor data;

[0157] A target suspension adjustment parameter acquisition module 630 is used to acquire target suspension adjustment parameters that match driving experience requirements;

[0158] The suspension hardness and softness state adjustment module 640 is used to adjust the suspension hardness and softness state of the vehicle by using the target suspension adjustment parameters, so that the handling stability and the ride comfort of the vehicle can be adjusted accordingly.

[0159] In one embodiment, the driving experience requirement determination module 620 may include:

[0160] A role type identification submodule is used to identify the role type of the user in the cockpit based on the cockpit sensor data;

[0161] A handling stability requirement determination submodule is used to determine the driving experience requirement of the user in the cockpit as the handling stability requirement if the role type only includes the driver; or

[0162] The vehicle smoothness requirement determination submodule is used to determine the driving experience requirements of the users in the cabin as the vehicle smoothness requirements if the role types include the driver and the passenger.

[0163] In one embodiment, the automatic driving controller of the vehicle is configured with a plurality of preset driving experience scenarios and preset suspension adjustment parameters corresponding to the plurality of preset driving experience scenarios respectively; the target suspension adjustment parameter acquisition module 630 may include:

[0164] a submodule for obtaining target suspension adjustment parameters for handling stability requirements, for determining a first driving experience scenario that matches the handling stability requirement from a plurality of preset driving experience scenarios when the driving experience requirement is the handling stability requirement, and obtaining preset suspension adjustment parameters corresponding to the first driving experience scenario as target suspension adjustment parameters; or

[0165] The submodule for acquiring the target suspension adjustment parameters for the vehicle smoothness requirement is used to identify the number of passengers in the cabin based on the cabin sensor data when the driving experience requirement is the vehicle smoothness requirement, so as to determine a second driving experience scenario that matches the vehicle smoothness requirement and the number of passengers from a variety of preset driving experience scenarios, and acquire the preset suspension adjustment parameters corresponding to the second driving experience scenario as the target suspension adjustment parameters.

[0166] In one embodiment, see Figure 5 The suspension adjustment system may further include: a chassis system 530, wherein the chassis system 530 includes a suspension component.

[0167] In one embodiment, the target suspension adjustment parameters include a mixing coefficient, a simulated passive damping coefficient, and a skyhook damping coefficient; the suspension soft and hard state adjustment module 640 may include:

[0168] A simulated passive damping force calculation submodule is used to calculate the simulated passive damping force according to the simulated passive damping coefficient;

[0169] A ceiling control damping force calculation submodule is used to calculate the ceiling control damping force according to the ceiling damping coefficient;

[0170] A suspension damping force calculation submodule is used to calculate the suspension damping force according to the mixing coefficient, the simulated passive damping force and the ceiling control damping force;

[0171] The suspension adjustment request sending submodule is used to generate a suspension adjustment request using the suspension damping force and send the suspension adjustment request to the chassis system.

[0172] The chassis system 530 is used to adjust the current hardness or softness state of the suspension component to the hardness or softness state of the suspension corresponding to the suspension damping force in response to the suspension adjustment request.

[0173] Among them, the soft and hard states of the suspension include at least one of a soft state and a hard state; when the suspension component is in a hard state, the handling stability of the vehicle is improved; when the suspension component is in a soft state, the overall vehicle smoothness is improved.

[0174] In one embodiment, the simulated passive damping force calculation submodule may include:

[0175] A speed acquisition unit, used for acquiring a sprung mass speed and an unsprung mass speed;

[0176] a relative speed calculation unit, configured to calculate a relative speed according to the sprung mass speed and the unsprung mass speed;

[0177] The simulated passive damping force calculation unit is used to calculate the simulated passive damping force according to the simulated passive damping coefficient and the relative speed.

[0178] In one embodiment, the skyhook control damping force calculation submodule may include:

[0179] A direction consistency judgment unit is used to judge whether the sprung mass speed and the relative speed are in the same direction;

[0180] The skyhook control damping force calculation unit is used to calculate the skyhook control damping force according to the skyhook damping coefficient and the sprung mass velocity if the sprung mass velocity is in the same direction as the relative velocity.

[0181] In one embodiment, the cabin sensor data acquisition module 610 may include:

[0182] An image data acquisition submodule, used to acquire image data collected by a vehicle's cabin monitoring camera; and / or,

[0183] A radar data acquisition submodule, used to acquire radar data collected by a vehicle's cabin monitoring radar; and / or,

[0184] The pressure data acquisition submodule is used to acquire the pressure data collected by the vehicle's cabin pressure sensor.

[0185] As can be seen from this example, the solution provided by this application obtains the vehicle's cabin sensor data; determines the driving experience requirements of users in the cabin based on the cabin sensor data; obtains target suspension adjustment parameters that match the driving experience requirements; and uses the target suspension adjustment parameters to adjust the vehicle's suspension hardness and softness to adjust the vehicle's handling stability and vehicle ride comfort accordingly. This application can determine the driving experience requirements of users in the cabin through cabin sensor data. The driving experience requirements may include at least one of the handling stability requirements and the vehicle ride comfort requirements. Therefore, based on different driving experience requirements, different suspension response effects are achieved, thereby achieving the adjustment of handling stability and vehicle ride comfort, thereby effectively ensuring the user's driving experience.

[0186] Regarding the system in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated again here.

[0187] Figure 7 It is a schematic diagram of the structure of a vehicle shown in an embodiment of the present application.

[0188] See also Figure 7 , the vehicle 700 includes a memory 710 and a processor 720 .

[0189] The processor 720 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0190] The memory 710 may include various types of storage units, such as system memory, read-only memory (ROM), and permanent storage. Among them, ROM may store static data or instructions required by the processor 720 or other modules of the computer. The permanent storage may be a readable and writable storage device. The permanent storage may be a non-volatile storage device that does not lose the stored instructions and data even after the computer is powered off. In some embodiments, the permanent storage device uses a large-capacity storage device (such as a magnetic or optical disk, flash memory) as a permanent storage device. In other embodiments, the permanent storage device may be a removable storage device (such as a floppy disk, optical drive). The system memory may be a readable and writable storage device or a volatile readable and writable storage device, such as a dynamic random access memory. The system memory may store some or all instructions and data required by the processor at run time. In addition, the memory 710 may include any combination of computer-readable storage media, including various types of semiconductor memory chips (such as DRAM, SRAM, SDRAM, flash memory, programmable read-only memory), and disks and / or optical disks may also be used. In some embodiments, the memory 710 may include a readable and / or writable removable storage device, such as a laser disc (CD), a read-only digital versatile disc (such as a DVD-ROM, a double-layer DVD-ROM), a read-only Blu-ray disc, an ultra-density optical disc, a flash memory card (such as an SD card, a mini SD card, a Micro-SD card, etc.), a magnetic floppy disk, etc. The computer-readable storage medium does not include carrier waves and transient electronic signals transmitted wirelessly or wired.

[0191] The memory 710 stores executable codes, and when the executable codes are processed by the processor 720 , the processor 720 can execute part or all of the methods described above.

[0192] In addition, the method according to the present application may also be implemented as a computer program or a computer program product, which includes computer program code instructions for executing some or all of the steps in the above method of the present application.

[0193] Alternatively, the present application can also be implemented as a computer-readable storage medium (or non-temporary machine-readable storage medium or machine-readable storage medium) on which executable code (or computer program or computer instruction code) is stored. When the executable code (or computer program or computer instruction code) is executed by the vehicle's processor, the processor executes part or all of the steps of the above-mentioned method according to the present application.

[0194] The embodiments of the present application have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or improvements to the technology in the market, or to enable other persons of ordinary skill in the art to understand the embodiments disclosed herein.

Claims

1. A vehicle suspension adjustment method, characterized in that: include: Obtain vehicle cabin sensor data; Determining the driving experience requirements of the user in the cockpit according to the cockpit sensor data; Obtaining target suspension adjustment parameters that match the driving experience requirements; The target suspension adjustment parameters are used to adjust the suspension hardness and softness of the vehicle so that the handling stability and the ride comfort of the vehicle are adjusted accordingly.

2. The method according to claim 1, characterized in that Determining the driving experience requirements of the user in the cockpit according to the cockpit sensor data includes: identifying the role type of the user in the cockpit according to the cockpit sensor data; If the role type only includes the driver, determining the driving experience requirement of the user in the cockpit as the handling stability requirement; or, If the role types include a driver and a passenger, the driving experience requirements of the users in the cockpit are determined to be the whole vehicle smoothness requirements.

3. The method according to claim 2, characterized in that The automatic driving controller of the vehicle is configured with a plurality of preset driving experience scenarios and preset suspension adjustment parameters respectively corresponding to the plurality of preset driving experience scenarios; the obtaining of the target suspension adjustment parameters matching the driving experience requirements comprises: When the driving experience requirement is the handling stability requirement, determining a first driving experience scenario that matches the handling stability requirement from the multiple preset driving experience scenarios, and obtaining preset suspension adjustment parameters corresponding to the first driving experience scenario as target suspension adjustment parameters; or, When the driving experience requirement is the whole vehicle smoothness requirement, the number of passengers in the cabin is identified based on the cabin sensor data, so as to determine a second driving experience scenario that matches the whole vehicle smoothness requirement and the number of passengers from the multiple preset driving experience scenarios, and obtain preset suspension adjustment parameters corresponding to the second driving experience scenario as target suspension adjustment parameters.

4. The method according to claim 1, characterized in that: The chassis system of the vehicle includes a suspension component, and the target suspension adjustment parameters include a mixing coefficient, a simulated passive damping coefficient, and a skyhook damping coefficient; The adopting of the target suspension adjustment parameter to adjust the suspension hardness and softness of the vehicle so as to adjust the handling stability and the ride comfort of the vehicle accordingly includes: Calculating a simulated passive damping force according to the simulated passive damping coefficient, and calculating a ceiling control damping force according to the ceiling damping coefficient; calculating a suspension damping force according to the mixing coefficient, the simulated passive damping force and the skyhook control damping force; Generate a suspension adjustment request using the suspension damping force, and send the suspension adjustment request to the chassis system, so that the chassis system adjusts the current softness or hardness state of the suspension component to the softness or hardness state of the suspension corresponding to the suspension damping force in response to the suspension adjustment request; Among them, the soft and hard states of the suspension include at least one of a soft state and a hard state; when the suspension component is in a hard state, the handling stability of the vehicle is improved; when the suspension component is in a soft state, the overall vehicle smoothness of the vehicle is improved.

5. The method according to claim 4, characterized in that The calculating of the simulated passive damping force according to the simulated passive damping coefficient comprises: Get the sprung mass speed and the unsprung mass speed; calculating a relative speed based on the sprung mass speed and the unsprung mass speed; A simulated passive damping force is calculated according to the simulated passive damping coefficient and the relative speed.

6. The method according to claim 5, characterized in that The calculating the ceiling control damping force according to the ceiling damping coefficient comprises: determining whether the sprung mass velocity and the relative velocity are in the same direction; If the sprung mass velocity is in the same direction as the relative velocity, a skyhook control damping force is calculated based on the skyhook damping coefficient and the sprung mass velocity.

7. The method according to claim 1, characterized in that The step of obtaining the vehicle's cabin sensor data includes: Obtaining image data collected by a vehicle's cabin monitoring camera; and / or, Obtaining radar data collected by a vehicle's cabin monitoring radar; and / or, Obtain pressure data collected by the vehicle's cabin pressure sensor.

8. A vehicle suspension adjustment system, characterized in that: include: Cockpit sensors and autopilot controllers; among them, The cockpit sensor is used to collect cockpit sensor data of the vehicle; The automatic driving controller is used to obtain the cockpit sensor data; determine the driving experience requirements of the user in the cockpit based on the cockpit sensor data; obtain target suspension adjustment parameters that match the driving experience requirements; and use the target suspension adjustment parameters to adjust the suspension hardness and softness of the vehicle so that the handling stability and vehicle ride comfort of the vehicle are adjusted accordingly.

9. A vehicle, characterized in that: include: processor; as well as A memory having executable codes stored thereon, which, when executed by the processor, causes the processor to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having executable codes stored thereon, which, when executed by a processor of a vehicle, causes the processor to execute the method according to any one of claims 1 to 7.

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