Vehicle suspension adjustment method and electronic device therefor

Abstract

The embodiment of the application provides a vehicle suspension adjustment method and device, comprising: acquiring road surface data of a driving road surface where a current vehicle is located; determining a target suspension mode based on the road surface data; after the current vehicle is switched from an original suspension mode to the target suspension mode, detecting a posture of the vehicle in real time to determine posture data of the current vehicle; and based on the posture data, performing optimization adjustment on the target suspension mode. By selecting a corresponding target suspension mode according to road surface conditions, and performing parameter optimization adjustment on the target suspension mode according to the posture data of the vehicle after switching, the comfort, stability and energy consumption optimization of the vehicle under different road conditions and driving modes are ensured, and the adaptability of the vehicle to complex road conditions is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of vehicle management, and in particular to a vehicle suspension adjustment method and device, an electronic device and a storage medium thereof. BACKGROUND

[0002] When a vehicle drives in different road environments, comfort and stability are key factors affecting driving experience and safety. Driving on ordinary roads is relatively smooth, but in the case of potholes, rough terrain or high-speed driving, the vehicle is easily affected by bumps and shakes, leading to a decline in ride experience and even affecting handling performance.

[0003] In order to improve the adaptability of the vehicle in various road conditions, a way is needed to make adjustments according to the actual situation, so that the vehicle can maintain stability and smoothness in different environments. The ideal solution should be able to identify changes in driving environment and make adjustments when necessary to reduce bumps and improve comfort while maintaining the safety and handling of the vehicle. If there is still a significant discomfort or instability after adjustment, further optimization is needed to ensure that the vehicle is always in a better state. This way not only improves the driving experience, but also improves overall efficiency, making the vehicle more adaptable to various complex application scenarios. SUMMARY

[0004] The embodiments of the present application provide a vehicle suspension adjustment method to solve the problem that the existing vehicle suspension adjustment method cannot switch the suspension mode in time according to the road surface condition and analyze and adjust the corresponding parameters of the switched suspension mode.

[0005] In a first aspect, the embodiments of the present application provide a vehicle suspension adjustment method, which comprises the following steps:

[0006] Obtain road surface data of the driving road surface where the current vehicle is located;

[0007] Determine a target suspension mode based on the road surface data;

[0008] After the current vehicle is switched from the original suspension mode to the target suspension mode, the attitude of the vehicle is detected in real time to determine the attitude data of the current vehicle;

[0009] Optimize and adjust the target suspension mode based on the attitude data.

[0010] Optionally, the road surface data of the driving road surface where the current vehicle is located is obtained, comprising:

[0011] An image recognition of the road surface is performed by a camera module to determine the road surface type of the current driving road surface;

[0012] The laser radar module detects the road surface to determine profile information and distance data of the current driving road surface;

[0013] The CNN model processes the road surface type, profile information and distance data to obtain road surface data of the driving road surface where the current vehicle is located.

[0014] Optionally, the target suspension mode is determined based on the road surface data, including:

[0015] The target energy consumption ratio data and the target vehicle comfort data are determined based on the road surface data.

[0016] The target suspension mode is determined based on the target energy consumption ratio data and the target vehicle comfort data.

[0017] Optionally, the target suspension mode is determined based on the target energy consumption ratio data and the target vehicle comfort data, and the method further includes:

[0018] At least one pre-target suspension mode is determined based on the target energy consumption ratio data and the target vehicle comfort data.

[0019] Abnormal data exceeding a data threshold is calculated based on the energy consumption ratio data and the target vehicle comfort data in at least one pre-target suspension mode, in combination with the road surface data of the current driving road surface.

[0020] The target suspension mode is determined based on the abnormal data in at least one pre-target suspension mode.

[0021] Optionally, after the current vehicle is switched from the original suspension mode to the target suspension mode, the attitude of the vehicle is detected in real time to determine attitude data of the current vehicle, including:

[0022] In the target suspension mode, the attitude data of the vehicle body is monitored in real time by a vehicle body response monitoring unit to determine the attitude data of the vehicle, and the vehicle body response monitoring unit includes an accelerometer and a gyroscope.

[0023] Specifically, the vertical acceleration, longitudinal acceleration and lateral acceleration of the vehicle body are measured by the accelerometer.

[0024] The angular velocity of the vehicle body is measured by the gyroscope to obtain the pitch angle, roll angle and roll angular velocity of the vehicle body.

[0025] The attitude data of the vehicle is determined based on the vertical acceleration, longitudinal acceleration and lateral acceleration of the vehicle body, and the pitch angle, roll angle and roll angular velocity of the vehicle body.

[0026] Optionally, the optimization adjustment of the target suspension mode based on the attitude data comprises:

[0027] comparing the vertical acceleration, the longitudinal acceleration, the lateral acceleration of the vehicle body, and the pitch angle, the roll angle and the roll angular velocity of the vehicle body with the standard attitude data in the target suspension mode to determine the attitude data with abnormal values;

[0028] adjusting the corresponding suspension parameter according to the attitude data with abnormal values to obtain the optimized suspension parameter;

[0029] performing parameter optimization adjustment on the target suspension mode according to the optimized suspension parameter.

[0030] Optionally, the optimization adjustment of the target suspension mode based on the attitude data comprises:

[0031] if the attitude data cannot reach the preset standard attitude data after the adjustment of the suspension parameter, re-computing the new target suspension mode in combination with the optimized suspension parameter, the road surface data and the attitude data;

[0032] switching the original target suspension mode to the new target suspension mode to make the vehicle travel stably.

[0033] In a second aspect, the embodiments of the present application further provide a vehicle suspension adjustment device, which comprises:

[0034] a first acquisition module configured to acquire road surface data of a driving road surface on which a current vehicle is located;

[0035] a first determination module configured to determine a target suspension mode based on the road surface data;

[0036] a second determination module configured to detect the attitude of the vehicle in real time after the current vehicle is switched from an original suspension mode to the target suspension mode to determine attitude data of the current vehicle;

[0037] a first optimization module configured to perform optimization adjustment on the target suspension mode based on the attitude data.

[0038] In a third aspect, the embodiments of the present application provide an electronic device, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, and the processor implements the steps in the vehicle suspension adjustment method provided by the embodiments of the present application when executing the computer program.

[0039] In a fourth aspect, the embodiments of the present application provide a computer readable storage medium, and the computer readable storage medium stores a computer program. When the computer program is executed by a processor, the steps of the vehicle suspension adjustment method provided by the embodiments of the present application are implemented.

[0040] In the embodiments of the present application, road surface data of a driving road surface on which a current vehicle is located is acquired, a target suspension mode is determined based on the road surface data, after the current vehicle is switched from an original suspension mode to the target suspension mode, a posture of the vehicle is detected in real time, posture data of the current vehicle is determined, and the target suspension mode is adjusted based on the posture data. By selecting a corresponding target suspension mode according to a road surface condition, and adjusting parameters of the target suspension mode according to the posture data of the switched vehicle, the comfort, stability and energy consumption optimization of the vehicle in different road conditions and driving modes are ensured, and the adaptability of the vehicle in complex road conditions is improved. BRIEF DESCRIPTION OF DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor.

[0042] Figure 1 is a flowchart of a vehicle suspension adjustment method provided by the embodiments of the present application;

[0043] Figure 2 is a schematic diagram of a principle of an electromechanical hydraulic energy feedback suspension system provided by the embodiments of the present application;

[0044] Figure 3 is a structural schematic diagram of another vehicle suspension adjustment device provided by the embodiments of the present application;

[0045] Figure 4 is a structural schematic diagram of an electronic device provided by the embodiments of the present application.

[0046] Corresponding reference numerals in the drawings indicate corresponding parts throughout the several embodiments of the present application. DETAILED DESCRIPTION

[0047] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the present application.

[0048] As Figure 1 shown, Figure 1 is a flowchart of a vehicle suspension adjustment method provided by an embodiment of the present application, which comprises the following steps:

[0049] 101. Obtain road surface data of a driving road surface where a current vehicle is located.

[0050] In an embodiment of the present application, the vehicle suspension adjustment method described above can be applied to a vehicle suspension adjustment platform, which has functions of vehicle suspension data processing, vehicle suspension data transceiving, and noisy vehicle suspension data memory storage, and can be constructed based on a server or a server cluster, which can be an electronic device with vehicle suspension data processing capability.

[0051] The road surface data can include but is not limited to road surface types and road surface states, and the road surface states can include but are not limited to profile information and distance data of the current driving road surface. Specifically, the road surface type can be the composition type of the current driving road surface. For example, the current road surface is confirmed to be an asphalt road through scanning, which means it is a road surface suitable for high-speed driving, or it is confirmed to be a gravel road section through scanning, which means it is a road surface unsuitable for high-speed driving.

[0052] The profile information can be obtained by predicting the width and length of the road surface by the camera module, and can be used to describe the area or length of the road surface.

[0053] The distance data can be the distance data of the edge of the vehicle body from the edge of the road surface calculated in combination with the profile information and the volume of the current vehicle, or can be the maximum distance that the edge of the vehicle can approach the edge of the road surface. Whether the vehicle has a tendency to deviate from the road surface can be determined according to the degree of change in the distance between the vehicle body and the edges of the road surface. For example, if the vehicle is getting closer and closer to the left edge of the road surface during driving, it is determined that the vehicle has a left deviation or a left leaning condition.

[0054] In one possible embodiment, the CNN model can be used to extract and identify the road surface data of the current driving road surface where the current vehicle is located, to determine the road surface type, profile information, and distance data of the current driving road surface where the current vehicle is located.

[0055] 102. Determine a target suspension mode based on the road surface data.

[0056] In an embodiment of the present invention, since the suspension has different adjustment capabilities of suspension stiffness and damping, it is possible to adjust the posture data of the vehicle during driving to different degrees so that the vehicle can adapt to different road conditions. Therefore, the road surface data can be analyzed to determine the characteristics of the current driving road surface, and the suspension parameters that can adapt to the current road conditions can be dispatched, so that the vehicle can adaptively adjust the vehicle posture according to the current road conditions after using the suspension mode corresponding to the current suspension parameters.

[0057] Specifically, the above-mentioned target suspension mode may include but is not limited to passive suspension mode, semi-active suspension mode and active suspension mode. Among them, the semi-active suspension mode can also be a feed-back suspension mode, which mainly relies on the electromechanical-hydraulic feed-back system to drive the motor to generate electricity through the hydraulic motor to achieve the feed-back effect.

[0058] More specifically, according to Figure 2 The schematic diagram of the electromechanical and hydraulic energy-feeding suspension system shown in FIG. The system includes a pull arm 1, a blade damper 2, a rectifier circuit, a hydraulic motor 3, an electric motor 4, and a controller 5. The pull arm 1 is connected to the blade damper 2 via an internal spline. The blade damper 2, the rectifier circuit, the hydraulic motor 3, and the electric motor 4 are sequentially connected to form the hydraulic circuit of the electromechanical and hydraulic energy-feeding suspension system. The hydraulic motor 3 and the electric motor 4 are connected via a coupling. The bouncing of the wheels drives the pull arm 1 to reciprocate, and the pull arm 1 drives the blade shaft to reciprocate, thereby driving the flow of hydraulic oil. The hydraulic oil flows through the rectifier circuit for rectification, and after rectification, it enters the hydraulic motor 3, which drives the electric motor 4 to generate electricity, achieving the energy-feeding effect.

[0059] Furthermore, the above-mentioned blade damper also includes: a shell, a blade shaft, a partition and other components, wherein the blade shaft and the partition divide the shell into four chambers, and when the blade shaft rotates, the four chambers form two high-pressure chambers and two low-pressure chambers. The above-mentioned rectification circuit can include eight one-way valves, wherein four one-way valves are arranged in the radial direction of the partition, two by two arranged back to back, and each partition is provided with an oil outlet channel hole in the axial direction, and the one-way valve is correspondingly connected to the oil outlet channel port; the other four one-way valves are arranged at the rear end of the shell, respectively connecting the four chambers, and the hydraulic oil flowing through the hydraulic motor 3 flows back to the four chambers through the four one-way valves arranged at the rear end of the shell.

[0060] In a possible embodiment, after analyzing and identifying the road surface data on which the vehicle is currently traveling, the vehicle suspension adjustment platform selects suspension parameters corresponding to the current road conditions, matches the corresponding suspension mode based on the suspension parameters, and switches after using the suspension mode as the target suspension mode.

[0061] 103. After the current vehicle is changed from the original suspension mode to the target suspension mode, the vehicle posture is detected in real time to determine the current vehicle posture data.

[0062] In the embodiment of the present application, the attitude data can include but is not limited to acceleration data and angular velocity data of the vehicle. Specifically, the current attitude data of the vehicle can be acquired by the vehicle-mounted gyroscope and accelerometer. Generally, the vehicle suspension adjustment platform can acquire and analyze the current attitude data of the vehicle in real time through the vehicle-mounted gyroscope and accelerometer.

[0063] It can be understood that when the acceleration and angular velocity of the vehicle have abnormal data, it indicates that the current attitude data of the vehicle is abnormal, i.e., the current attitude of the vehicle is unstable and is not suitable for driving or other actions, and thus the suspension parameters of the target suspension mode of the vehicle need to be adjusted and optimized according to the abnormal attitude data.

[0064] In a possible embodiment, after the vehicle is switched from the original suspension mode to the target suspension mode, the vehicle suspension adjustment platform monitors the attitude data of the vehicle in real time through the vehicle-mounted accelerometer and gyroscope to determine whether the vehicle has abnormal attitude data.

[0065] 104. Adjust and optimize the target suspension mode based on the attitude data.

[0066] In the embodiment of the present application, after the vehicle is switched from the original suspension mode to the target suspension mode during driving, the suspension system is dynamically adjusted and optimized in real time according to the vehicle attitude data to adapt to different road conditions and improve the stability, comfort and passability of the vehicle.

[0067] For example, when the vehicle enters a gravel road from a normal road, the vehicle suspension adjustment platform switches the suspension mode of the vehicle from the original passive suspension mode to the semi-active suspension mode to balance the comfort and energy recovery after recognizing that the road becomes rough. However, after the mode is switched, it is detected in real time that there is still a large body vibration in the vehicle attitude data, which leads to a decrease in comfort, and thus the suspension stiffness is further adjusted to reduce the body vibration and improve the comfort of the vehicle.

[0068] In the embodiment of the present application, the road surface data of the driving road where the current vehicle is located is acquired, the target suspension mode is determined based on the road surface data, the attitude of the vehicle is detected in real time after the current vehicle is switched from the original suspension mode to the target suspension mode, the attitude data of the current vehicle is determined, and the target suspension mode is adjusted and optimized based on the attitude data. By selecting the corresponding target suspension mode according to the road conditions and adjusting and optimizing the parameters of the target suspension mode according to the vehicle attitude data after switching, the comfort, stability and energy consumption optimization of the vehicle in different road conditions and driving modes are ensured, and the adaptability of the vehicle in complex road conditions is improved.

[0069] Optionally, in the step of acquiring the road surface data of the driving road surface where the current vehicle is located, the image recognition of the road surface can be performed by the camera module to determine the road surface type of the current driving road surface; the laser radar module can be used to detect the road surface to determine the contour information and distance data of the current driving road surface; and the CNN model can be used to process the road surface type, contour information and distance data to obtain the road surface data of the driving road surface where the current vehicle is located.

[0070] In the embodiment of the present application, the camera module described above can be a device composed of an image sensor, a lens and a control circuit, mainly used for capturing environmental images and videos and performing subsequent analysis and processing. It can be understood that the camera module described above can be used to capture and recognize the road surface, and the pictures can be input into the vehicle suspension adjustment platform for subsequent analysis to determine the road surface type of the current road surface. For example, when it is recognized that the road surface is relatively flat, has no debris and has the color characteristics of asphalt road, it is indicated that the current driving road surface is an ordinary highway suitable for high-speed driving.

[0071] The laser radar described above can be a sensing device based on laser ranging, which can be used to obtain three-dimensional environmental information and detect the position and contour of an object. Generally, it can be used to measure the distance from the vehicle body to the edge of the road surface, and to detect whether the vehicle deviates or has an abnormal posture.

[0072] The CNN model described above can be any deep learning model capable of analyzing and processing the road surface data such as the road surface type, contour information and distance data to determine the state relationship between the vehicle and the current driving road surface. Generally, the CNN model can analyze whether the current driving road surface of the vehicle is winding or bumpy by processing the road surface type, contour information and distance data and combining the posture data of the current vehicle.

[0073] In a possible embodiment, the image collected by the camera and the point cloud data obtained by the laser radar are processed by a convolutional neural network (CNN) to identify the road surface type and the degree of unevenness in real time.

[0074] Optionally, in the step of determining the target suspension mode based on the road surface data, the target energy consumption ratio data and the target vehicle comfort data are determined based on the road surface data; and the target suspension mode is determined based on the target energy consumption ratio data and the target vehicle comfort data.

[0075] In the embodiment of the present application, the target energy consumption ratio data described above can be the calculation result of the energy distribution and consumption of the vehicle suspension adjustment platform under different road conditions and suspension modes, which can be used to optimize the energy consumption control, energy recovery and vehicle dynamic performance of the suspension system.

[0076] Specifically, the core indicators of the target energy consumption ratio data can include, but are not limited to, suspension system damping adjustment energy consumption, suspension stiffness adjustment energy consumption, energy recovery ratio, and vehicle energy consumption influence, etc. for evaluating energy consumption ratio.

[0077] More specifically, the suspension system damping adjustment energy consumption can be the energy required for adjusting the damping; the suspension stiffness adjustment energy consumption can be the consumption of electric energy or hydraulic energy affecting the adjustment of the suspension spring stiffness; and the energy recovery ratio can be the proportion of the energy recovered by the energy feedback suspension system through the hydraulic motor + motor or the magneto-rheological damper in the suspension movement. The target energy consumption ratio data can be used to balance the stability, comfort and energy consumption of the suspension system, and to ensure that the suspension system meets the driving requirements while achieving the lowest energy consumption or the best energy utilization rate.

[0078] The target vehicle comfort data can be a parameter for measuring the comfort of the vehicle in the current suspension mode, which is used to determine whether the suspension adjustment meets the passenger comfort standard and whether further optimization is needed.

[0079] Specifically, the target vehicle comfort data can be confirmed by the acceleration data and angular velocity data of the current vehicle. Generally, if the vertical acceleration of the vehicle body is too high, it means that the suspension is too hard and the damping needs to be adjusted; if the pitch angular velocity of the vehicle body is too large, it means that the suspension is not balanced front and rear and the stiffness needs to be optimized; and if the roll angular velocity of the vehicle body is abnormal, it means that the vehicle body is unstable during steering and the lateral damping needs to be adjusted.

[0080] In one possible embodiment, the vehicle suspension adjustment platform determines the target energy consumption ratio data and the target vehicle comfort data of the vehicle under the current road conditions after analyzing the road data, and selects a corresponding suspension model for switching as the target suspension model according to the corresponding suspension parameters after determining the target energy consumption ratio data and the target vehicle comfort data.

[0081] Optionally, in the step of determining the target suspension mode based on the target energy consumption ratio data and the target vehicle comfort data, the step further includes determining at least one pre-target suspension mode based on the target energy consumption ratio data and the target vehicle comfort data; calculating abnormal data exceeding a data threshold based on the energy consumption ratio data and the target vehicle comfort data in the at least one pre-target suspension mode, in combination with the road data of the current driving road; and determining the target suspension mode based on the abnormal data in the at least one pre-target suspension mode.

[0082] In the embodiments of the present application, the pre-target suspension mode can be any one of the suspension modes meeting the suspension parameters corresponding to the multiple current road conditions. Generally, different suspension modes are set for different road conditions, but among the different suspension modes, there can be multiple same suspension parameters, so the target suspension mode required can be accurately determined according to the analysis after the specific refinement of the suspension parameters.

[0083] Specifically, the indicators in the suspension mode can be confirmed according to the following evaluation function:

[0084]

[0085] Among them, is the weight of each indicator in the driving mode, which is adjusted according to the suspension switching strategy in the mode. is the mean value of the body acceleration, is the standard deviation of the body acceleration; is the mean value of the pitch angular velocity, is the standard deviation of the pitch angular velocity; is the mean value of the roll angular velocity, is the standard deviation of the roll angular velocity; is the minimum value of the vibration frequency, is the maximum value of the vibration frequency; is the shortest vibration duration, is the longest vibration duration; is the average value of the road power spectral density, is the standard deviation of the road power spectral density; is the average value of the vehicle driving speed, is the standard deviation of the vehicle driving speed; is the average value of the regenerative efficiency, is the maximum value of the regenerative efficiency, which can be obtained by analyzing the indicators of the vehicle in the driving process, i.e. the body vertical acceleration a, the pitch and roll angular velocities and , the vibration frequency , the vibration duration t, the road power spectral density Gq, the vehicle driving speed v, and the regenerative efficiency .

[0086] More specifically, an evaluation indicator threshold group can also be set: When , it indicates that the evaluation indicator is low at this time, the body stability is good, and the comfort is high; when , it indicates that the evaluation indicator is medium at this time, the body stability is general, and the comfort is general; when , the evaluation indicator is high at this time, the body stability is poor, and the comfort is poor.

[0087] According to the above evaluation index threshold group, the vehicle speed can be set with a threshold When , it is low speed, when , it is medium speed, when , it is high speed, and the road surface power spectral density Gq is set with a threshold, when the road surface is A and B grade road surface, the road surface power spectral density Gq is low; when the road surface grade is C grade road surface, the road surface power spectral density Gq is medium; when the road surface grade is D grade and below, the road surface power spectral density Gq is high. When , wherein when the vehicle speed is low and the road surface power spectral density is low, the passive suspension is switched, when the road surface power spectral density is medium, the regenerative suspension is switched, and when the road surface power spectral density is high, the regenerative suspension is switched; when the vehicle speed is medium and the road surface power spectral density is low, the passive suspension is switched, when the road surface power spectral density is medium, the regenerative suspension is switched, and when the road surface power spectral density is high, the regenerative suspension is switched; when the vehicle speed is high and the road surface power spectral density is low, the regenerative suspension is switched, when the road surface power spectral density is medium, the regenerative suspension is switched, and when the road surface power spectral density is high, the active suspension is switched. When , wherein when the vehicle speed is low and the road surface power spectral density is low, the passive suspension is switched, when the road surface power spectral density is medium, the passive suspension is switched, and when the road surface power spectral density is high, the regenerative suspension is switched; when the vehicle speed is medium and the road surface power spectral density is low, the regenerative suspension is switched, when the road surface power spectral density is medium, the regenerative suspension is switched, and when the road surface power spectral density is high, the active suspension is switched; when the vehicle speed is high and the road surface power spectral density is low, the regenerative suspension is switched, when the road surface power spectral density is medium, the regenerative suspension is switched, and when the road surface power spectral density is high, the active suspension is switched. When , wherein when the vehicle speed is low, the regenerative suspension is switched; when the vehicle speed is medium and the road surface power spectral density is low and medium, the regenerative suspension is switched; when the vehicle speed is high and the road surface power spectral density is low, the regenerative suspension is switched, and when the road surface power spectral density is medium and high, the active suspension is switched.

[0088] The above abnormal data can be the parameter value corresponding to the threshold value calculated by the evaluation function of the vehicle suspension adjustment platform.

[0089] More specifically, the evaluation function can also adjust the parameters according to the working mode of the vehicle, for example, when the vehicle is in driving mode, the mean pitch angle velocity, vibration duration and other parameters can be appropriately reduced to meet the comfort evaluation, when the vehicle is in combat mode, the vibration frequency and other parameters can be appropriately increased to meet the adaptability to all terrain.

[0090] Optionally, after the current vehicle is switched from the original suspension mode to the target suspension mode, the step of detecting the attitude of the vehicle in real time to determine the attitude data of the current vehicle further comprises: in the target suspension mode, monitoring the attitude data of the vehicle body in real time by the vehicle body response monitoring unit to determine the attitude data of the vehicle; specifically, the vertical acceleration, longitudinal acceleration and lateral acceleration of the vehicle body are measured by the accelerometer to obtain the vertical acceleration, longitudinal acceleration and lateral acceleration of the vehicle body; the angular velocity of the vehicle body is measured by the gyroscope to obtain the pitch angle, roll angle and roll angular velocity of the vehicle body; and the attitude data of the vehicle is determined based on the vertical acceleration, longitudinal acceleration and lateral acceleration of the vehicle body and the pitch angle, roll angle and roll angular velocity of the vehicle body.

[0091] In the embodiment of the present application, the vehicle body response monitoring unit can be used to monitor the dynamic performance of the vehicle body in real time, especially after the suspension mode is switched, to ensure that the stability and comfort of the vehicle are not affected, and the abnormal vehicle body response after the mode is switched can be prevented by monitoring the vehicle body response.

[0092] Specifically, the vehicle body response monitoring unit can be composed of an accelerometer and a gyroscope.

[0093] In a possible embodiment, to ensure that the target suspension mode adapts to different road conditions and provides optimal driving stability, the vehicle suspension adjustment platform monitors the attitude data of the vehicle in real time to dynamically optimize the suspension parameters. For example, the multi-axis acceleration and angular velocity data of the vehicle body are obtained by the accelerometer and the gyroscope, which are used to evaluate the stability of the vehicle in the target suspension mode and to make intelligent adjustments.

[0094] For example, assuming that an intelligent SUV drives from an urban road into a mountainous road, the vehicle suspension adjustment platform automatically switches to the target suspension mode (semi-active suspension), and when the vehicle body leans too much, the pitch changes significantly, or the vertical vibration is frequent in the curve, the vehicle suspension adjustment platform needs to monitor the vehicle attitude in real time and optimize the suspension parameters to ensure driving stability and comfort.

[0095] Optionally, in the step of optimizing and adjusting the target suspension mode based on the attitude data, the vertical acceleration, longitudinal acceleration and lateral acceleration of the vehicle body and the pitch angle, roll angle and roll angular velocity of the vehicle body are compared with the standard attitude data in the target suspension mode to determine the attitude data with abnormal values; the corresponding suspension parameters are adjusted according to the attitude data with abnormal values to obtain the optimized suspension parameters; and the target suspension mode is parameter-optimized and adjusted according to the optimized suspension parameters.

[0096] In the embodiment of the present application, the vehicle suspension adjustment platform optimizes the selected target suspension mode to ensure the stability, comfort and safety of the vehicle under different road conditions.

[0097] Specifically, after the suspension mode is switched, the vehicle suspension adjustment platform collects real-time vehicle body posture data, including but not limited to vertical acceleration, longitudinal acceleration, lateral acceleration, pitch angle, roll angle and roll angular velocity, and compares the data with standard posture data in the target suspension mode to determine whether there is an abnormal value.

[0098] When abnormal posture data is detected, the platform performs targeted optimization based on the type of abnormality:

[0099] If the vertical acceleration is excessive, it indicates that the vehicle body is bouncing too much, and the damping parameter is adjusted to enhance the cushioning effect.

[0100] If the roll angle is too large, it indicates that the vehicle is rolling too much when turning, and the lateral stiffness is increased to enhance stability.

[0101] If the pitch angle is abnormal, it indicates that the vehicle body is swaying too much when accelerating / braking, and the front and rear suspension damping ratio is optimized to reduce the inclination of the vehicle body.

[0102] After optimization, the vehicle suspension adjustment platform updates the suspension parameters and applies the adjusted parameters to the target suspension mode to ensure that the vehicle's posture under the current road conditions returns to the best state.

[0103] Optionally, in the step of optimizing and adjusting the target suspension mode based on the posture data, if the posture data still cannot meet the preset standard posture data after the suspension parameter adjustment, the suspension parameters, road data and posture data are recalculated to determine a new target suspension mode; the original target suspension mode is switched to the new target suspension mode to ensure stable vehicle driving.

[0104] In the embodiment of the present application, the preset standard posture data can be the posture data obtained by testing the most comfortable and most driving performance of the current vehicle model under different road conditions. It can be understood that the preset standard posture data can also be set according to the suspension parameters of the current vehicle model under different road conditions.

[0105] In a possible embodiment, after the vehicle suspension adjustment platform switches the suspension mode of the vehicle under the current road data, multiple suspension parameters or vehicle posture data still do not meet the requirements, the recalculated suspension parameters, road data and posture data are used to increase the number of corresponding suspension parameters or the number of posture data in the pre-target suspension mode, calculate a new target suspension mode that meets the number of corresponding suspension parameters or the number of posture data, and switch it as the new target suspension mode.

[0106] For example, Figure 3As shown, the embodiment of the present application also provides a vehicle suspension adjustment device 300, which comprises:

[0107] A first acquisition module 301 is configured to acquire road surface data of a driving road surface where a current vehicle is located;

[0108] A first determination module 302 is configured to determine a target suspension mode based on the road surface data;

[0109] A second determination module 303 is configured to detect a posture of the vehicle in real time after the current vehicle is switched from an original suspension mode to the target suspension mode, and determine posture data of the current vehicle;

[0110] A first optimization module 304 is configured to optimize and adjust the target suspension mode based on the posture data.

[0111] Optionally, the first acquisition module 301 comprises:

[0112] A first determination sub-module is configured to identify a road surface type of a current driving road surface by image recognition of the road surface through a camera module;

[0113] A second determination sub-module is configured to detect the current driving road surface by a laser radar module, and determine profile information and distance data of the current driving road surface;

[0114] A third determination sub-module is configured to process the road surface type, the profile information and the distance data through a CNN model, and obtain the road surface data of the current driving road surface where the vehicle is located.

[0115] Optionally, the first determination module 303 comprises:

[0116] A fourth determination sub-module is configured to determine target energy consumption ratio data and target vehicle comfort data based on the road surface data;

[0117] A fifth determination sub-module is configured to determine the target suspension mode based on the target energy consumption ratio data and the target vehicle comfort data.

[0118] Optionally, the fifth determination sub-module comprises:

[0119] A first determination unit is configured to determine at least one pre-target suspension mode based on the target energy consumption ratio data and the target vehicle comfort data;

[0120] A first calculation unit is configured to calculate abnormal data exceeding a data threshold based on energy consumption ratio data and target vehicle comfort data in at least one pre-target suspension mode, and in combination with the road surface data of the current driving road surface;

[0121] The second determining unit is configured to determine a target suspension mode from the at least one pre-target suspension mode based on the abnormal data.

[0122] Optionally, the second determining module 302 includes:

[0123] The sixth determining sub-module is configured to determine the attitude data of the vehicle by monitoring the attitude data of the vehicle body in real time through a vehicle body response monitoring unit in the target suspension mode, wherein the vehicle body response monitoring unit includes an accelerometer and a gyroscope.

[0124] The seventh determining sub-module is configured to specifically measure the acceleration of the vehicle body in different axial directions through the accelerometer to obtain the vertical acceleration, longitudinal acceleration and lateral acceleration of the vehicle body.

[0125] The eighth determining sub-module is configured to measure the angular velocity of the vehicle body through the gyroscope to obtain the pitch angle, roll angle and roll angular velocity of the vehicle body.

[0126] The ninth determining sub-module is configured to determine the attitude data of the vehicle based on the vertical acceleration, longitudinal acceleration and lateral acceleration of the vehicle body and the pitch angle, roll angle and roll angular velocity of the vehicle body.

[0127] Optionally, the first optimization module 304 includes:

[0128] The tenth determining sub-module is configured to compare the vertical acceleration, longitudinal acceleration and lateral acceleration of the vehicle body and the pitch angle, roll angle and roll angular velocity of the vehicle body with the standard attitude data in the target suspension mode to determine the attitude data with abnormal values.

[0129] The adjusting sub-module is configured to adjust the corresponding suspension parameter according to the attitude data with abnormal values to obtain the optimized suspension parameter.

[0130] The optimization sub-module is configured to perform parameter optimization adjustment on the target suspension mode according to the optimized suspension parameter.

[0131] Optionally, the device further includes:

[0132] The recalculation module is configured to recalculate the new target suspension mode by combining the optimized suspension parameter, road surface data and attitude data if the attitude data cannot reach the preset standard attitude data after the adjustment of the suspension parameter.

[0133] The switching module is configured to switch the original target suspension mode to the new target suspension mode to stabilize the driving of the vehicle.

[0134] As Figure 4As shown, the embodiment of the present application further provides an electronic device 400, comprising a processor, wherein the processor can execute any one of the above vehicle suspension adjustment methods.

[0135] Specifically, the electronic device 400 comprises a processor 401 and a memory 402, and a computer program for executing the vehicle suspension adjustment method stored in the memory 402 and capable of running on the processor 401.

[0136] The processor 401 runs the computer program of the vehicle suspension adjustment method stored in the memory 402, and executes the following steps:

[0137] Obtain road surface data of a driving road surface where the current vehicle is located;

[0138] Determine a target suspension mode based on the road surface data;

[0139] After the current vehicle is switched from the original suspension mode to the target suspension mode, the attitude of the vehicle is detected in real time to determine attitude data of the current vehicle;

[0140] Optimize and adjust the target suspension mode based on the attitude data.

[0141] Optionally, the processor 401 executes the obtaining of the road surface data of the driving road surface where the current vehicle is located, comprising:

[0142] Identify the road surface type of the current driving road surface through image recognition of the road surface by a camera module;

[0143] Detect the current driving road surface through a laser radar module to determine contour information and distance data of the current driving road surface;

[0144] Process the road surface type, contour information and distance data through a CNN model to obtain the road surface data of the driving road surface where the current vehicle is located.

[0145] Optionally, the processor 401 executes the determining of the target suspension mode based on the road surface data, comprising:

[0146] Determine target energy consumption ratio data and target vehicle comfort data based on the road surface data;

[0147] Determine the target suspension mode based on the target energy consumption ratio data and the target vehicle comfort data.

[0148] Optionally, the processor 401 executes the determining of the target suspension mode based on the target energy consumption ratio data and the target vehicle comfort data, and the method further comprises:

[0149] Determine at least one pre-target suspension mode based on the target energy consumption ratio data and the target vehicle comfort data.

[0150] Based on the energy consumption ratio data and the target vehicle comfort data in at least one of the pre-target suspension modes, and in combination with the road surface data of the current driving road, abnormal data exceeding a data threshold is calculated;

[0151] Based on the abnormal data, a target suspension mode is determined in at least one of the pre-target suspension modes.

[0152] Optionally, after the processor 401 performs the conversion of the current vehicle from the original suspension mode to the target suspension mode, the attitude of the vehicle is detected in real time, and attitude data of the current vehicle is determined, including:

[0153] In the target suspension mode, the attitude data of the vehicle is determined by monitoring the attitude data of the vehicle body in real time through a vehicle body response monitoring unit, and the vehicle body response monitoring unit includes an accelerometer and a gyroscope.

[0154] Specifically, the vertical acceleration, longitudinal acceleration and lateral acceleration of the vehicle body are measured by the accelerometer.

[0155] The angular velocity of the vehicle body is measured by the gyroscope to obtain the pitch angle, roll angle and roll angular velocity of the vehicle body.

[0156] Based on the vertical acceleration, longitudinal acceleration and lateral acceleration of the vehicle body, and the pitch angle, roll angle and roll angular velocity of the vehicle body, the attitude data of the vehicle is determined.

[0157] Optionally, the processor 401 also performs the optimization adjustment of the target suspension mode based on the attitude data, including:

[0158] The vertical acceleration, longitudinal acceleration and lateral acceleration of the vehicle body, and the pitch angle, roll angle and roll angular velocity of the vehicle body are compared with the standard attitude data in the target suspension mode to determine attitude data with abnormal values.

[0159] According to the attitude data with abnormal values, the corresponding suspension parameters are adjusted to obtain optimized suspension parameters.

[0160] According to the optimized suspension parameters, the target suspension mode is adjusted in terms of parameters.

[0161] Optionally, the processor 401 also performs the optimization adjustment of the target suspension mode based on the attitude data, and the method further includes:

[0162] If the attitude data cannot reach the preset standard attitude data after the suspension parameter adjustment, the new target suspension mode is determined by recalculating in combination with the optimized suspension parameter, the road surface data and the attitude data.

[0163] The original target suspension mode is switched to the new target suspension mode, so that the vehicle runs stably.

[0164] The embodiment of the present application further provides a computer readable storage medium, and the computer readable storage medium stores a computer program, the computer program is executed by a processor to realize each process of the vehicle suspension adjustment method or the application end vehicle suspension adjustment method provided by the embodiment of the present application, and the same technical effects can be achieved, to avoid repetition, which will not be repeated here.

[0165] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment method can be completed by a computer program instructing related hardware, and can be stored in a computer readable storage medium. The program can include the processes of the above-mentioned embodiment method when executed. The storage medium can be a magnetic disc, an optical disc, a read-only memory (ROM) or a random access memory (RAM).

[0166] The above only discloses the preferred embodiments of the present application, and of course cannot limit the scope of the right of the present application, so the equivalent changes made according to the claims of the present application still belong to the scope covered by the present application.

Claims

1. A vehicle suspension adjustment method, characterized in that: include: Obtain the road surface data of the current vehicle driving road; Determining target energy consumption ratio data and target vehicle comfort data based on the road surface data; determining at least one pre-target suspension mode based on the target energy consumption ratio data and the target vehicle comfort data; Based on at least one of the energy consumption ratio data and the target vehicle comfort data under the pre-target suspension mode, combined with the road surface data of the current driving road, abnormal data exceeding the data threshold is calculated, and the index under the pre-target suspension mode is confirmed according to the following evaluation function: in, is the weight of each indicator in the driving mode, and is adjusted according to the suspension switching strategy in this mode. is the mean vehicle acceleration, is the standard deviation of vehicle body acceleration; is the mean pitch angular velocity, is the standard deviation of pitch angular velocity; is the mean roll angular velocity, is the standard deviation of the roll angular velocity; is the minimum vibration frequency, is the maximum vibration frequency; is the shortest vibration duration, is the maximum vibration duration; is the average power spectrum density of the road surface, is the standard deviation of the pavement power spectrum density; is the average vehicle speed, is the standard deviation of vehicle speed; is the average value of energy feeding efficiency, The maximum energy feeding efficiency can be obtained based on the vehicle's indicators during driving, namely the vertical acceleration a, pitch and roll angular velocity of the vehicle body. and , vibration frequency , vibration duration t, road surface power spectrum density Gq, vehicle speed v, energy feedback efficiency After a period of collection and analysis, the corresponding evaluation value S1 is obtained. The abnormal data is the parameter value corresponding to the threshold value exceeded after calculation by the evaluation function; determining a target suspension mode in at least one of the pre-target suspension modes based on the abnormal data; After the current vehicle is switched from the original suspension mode to the target suspension mode, the vehicle posture is detected in real time to determine the current vehicle posture data; Based on the posture data, the target suspension mode is optimized and adjusted.

2. The vehicle suspension adjustment method according to claim 1, wherein: The obtaining of road surface data of the current vehicle driving road comprises: The camera module performs image recognition on the road surface to determine the road type of the current driving road; The road surface is detected by the LiDAR module to determine the contour information and distance data of the current road surface; The road surface type, contour information and distance data are processed by the CNN model to obtain the road surface data of the current vehicle driving on.

3. The vehicle suspension adjustment method according to claim 1, wherein: After the current vehicle is changed from the original suspension mode to the target suspension mode, the posture of the vehicle is detected in real time to determine the posture data of the current vehicle, including: In the target suspension mode, the vehicle body posture data is monitored in real time by a vehicle body response monitoring unit to determine the vehicle posture data. The vehicle body response monitoring unit includes an accelerometer and a gyroscope. Specifically, the acceleration of the vehicle body in different axes is measured by an accelerometer to obtain the vertical acceleration, longitudinal acceleration, and lateral acceleration of the vehicle body; The angular velocity of the vehicle body is measured by a gyroscope to obtain the pitch angle, roll angle and rolling angular velocity of the vehicle body; The vehicle posture data is determined based on the vertical acceleration, longitudinal acceleration, lateral acceleration of the vehicle body and the pitch angle, roll angle and rolling angular velocity of the vehicle body.

4. The vehicle suspension adjustment method according to claim 3, wherein: The optimizing and adjusting the target suspension mode based on the posture data includes: comparing the vertical acceleration, longitudinal acceleration, lateral acceleration of the vehicle body, and the pitch angle, roll angle, and roll angular velocity of the vehicle body with standard posture data under the target suspension mode to determine posture data having abnormal values; According to the posture data having abnormal values, corresponding suspension parameters are adjusted to obtain optimized suspension parameters; According to the optimized suspension parameters, the target suspension mode is subjected to parameter optimization adjustment.

5. The vehicle suspension adjustment method according to claim 1, wherein: The method further comprises optimizing and adjusting the target suspension mode based on the posture data: If the posture data still cannot reach the preset standard posture data after the suspension parameters are adjusted, recalculation is performed in combination with the optimized suspension parameters, road surface data, and posture data to determine a new target suspension mode; Switch the original target suspension mode to a new target suspension mode to make the vehicle run stably.

6. A vehicle suspension adjustment device, characterized in that: include: The first acquisition module is used to obtain road surface data of the road on which the vehicle is currently traveling; a first determining module, configured to determine a target suspension mode based on the road surface data; a second determination module, configured to detect the posture of the vehicle in real time and determine the posture data of the current vehicle after the current vehicle is changed from the original suspension mode to the target suspension mode; A first optimization module, configured to optimize and adjust the target suspension mode based on the posture data; The first determination module is further configured to determine target energy consumption ratio data and target vehicle comfort data; determine at least one pre-target suspension mode based on the target energy consumption ratio data and the target vehicle comfort data; calculate abnormal data exceeding a data threshold based on the energy consumption ratio data and the target vehicle comfort data under the at least one pre-target suspension mode, combined with road surface data of the current driving road surface, and confirm the indicators under the pre-target suspension mode according to the following evaluation function: in, is the weight of each indicator in the driving mode, and is adjusted according to the suspension switching strategy in this mode. is the mean vehicle acceleration, is the standard deviation of vehicle body acceleration; is the mean pitch angular velocity, is the standard deviation of pitch angular velocity; is the mean roll angular velocity, is the standard deviation of the roll angular velocity; is the minimum vibration frequency, is the maximum vibration frequency; is the shortest vibration duration, is the maximum vibration duration; is the average power spectrum density of the road surface, is the standard deviation of the pavement power spectrum density; is the average vehicle speed, is the standard deviation of vehicle speed; is the average value of energy feeding efficiency, The maximum energy feeding efficiency can be obtained based on the vehicle's indicators during driving, namely the vertical acceleration a, pitch and roll angular velocity of the vehicle body. and , vibration frequency , vibration duration t, road surface power spectrum density Gq, vehicle speed v, energy feedback efficiency After a period of collection and analysis, a corresponding evaluation value S1 is obtained. The abnormal data is a parameter value that exceeds the threshold value after calculation by the evaluation function; Based on the abnormal data, a target suspension mode is determined in at least one of the pre-target suspension modes.

7. An electronic device, characterized in that: include: 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 steps of the vehicle suspension adjustment method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the vehicle suspension adjustment method according to any one of claims 1 to 5.

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