Vehicle body posture leveling control method and system of electric mountain transport vehicle

Abstract

The invention relates to the technical field of vehicle body posture leveling control, and provides a vehicle body posture leveling control method and system for an electric mountain transport vehicle, and the method comprises the steps: obtaining ground contact state data and a transverse shaft rotation angle in real time, and carrying out the contact terrain analysis according to the ground contact state data to obtain terrain parameter information; carrying out vehicle load distribution analysis according to the ground contact state data and the terrain inclination parameters to obtain pressure gravity center shift data; adjusting the horizontal axis rotation angle according to the pressure center-of-gravity shift data to obtain a target horizontal axis rotation angle; according to the target horizontal axis rotation angle and the terrain pressure distribution data, carrying out wheel bearing demand analysis to obtain a wheel pressure adjustment strategy; and driving the suspension system to level the posture of the vehicle body according to the wheel pressure adjusting strategy. The terrain environment change can be sensed in real time based on the wheel ground contact state change and the vehicle gravity center shift monitoring mechanism, the rotation angle of the transverse shaft and the wheel ground contact pressure are accurately adjusted, and self-adaptive leveling of the vehicle body posture is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle body posture leveling control, and in particular to a vehicle body posture leveling control method and system for an electric mountain transport vehicle. Background Art

[0002] Power projects are often constructed in remote mountainous areas, where complex road conditions such as steep slopes, side slopes, and unpaved roads can easily cause vehicles transporting power project materials to experience bumps and center of gravity shifts when traveling on mountain roads. However, power project materials (such as transformers, insulators, high-voltage switches, and cable drums) are typically large, heavy, structurally sophisticated, and require high insulation. Tilts or vibrations caused by mountainous terrain can cause internal structural displacement, insulation cracks, or seal failures, resulting in economic losses of millions or even tens of millions of yuan. Improving the stability of electric mountain transport vehicles in complex terrain is crucial to ensuring the efficient and safe transportation of power project materials.

[0003] Existing research on leveling control for electric engineering vehicles primarily focuses on designing fixed leveling methods for static conditions. It doesn't address the complex issue of vehicle center-of-gravity shifts caused by the unpredictable wheel-ground contact state when the vehicle is traveling on uneven roads. This makes it difficult to precisely control the torque used to adjust the vehicle's posture, resulting in an inability to adaptively level the vehicle during dynamic driving and difficulty responding to terrain changes in real time. This significantly reduces vehicle stability when transporting on continuously uneven mountain roads, compromising transport safety. Therefore, achieving real-time adaptive leveling of the vehicle's posture while considering the dynamic changes in wheel contact state and the impact of center-of-gravity shifts has become a pressing technical challenge in the field. Summary of the Invention

[0004] The purpose of the present invention is to provide a body posture leveling control method for an electric mountain transport vehicle. Through a monitoring mechanism based on changes in the wheel contact state and center of gravity offset, the method can sense changes in the terrain environment in real time and accurately adjust the transverse axis rotation angle and wheel ground pressure, thereby achieving real-time adaptive leveling of the body posture of the electric mountain transport vehicle, effectively improving the stability of the electric mountain transport vehicle under complex terrain conditions, and providing reliable guarantee for the efficient and safe transportation of power engineering materials.

[0005] In order to achieve the above objectives, it is necessary to provide a vehicle body posture leveling control method and system for an electric mountain transport vehicle in response to the above technical problems.

[0006] In a first aspect, an embodiment of the present invention provides a method for controlling vehicle posture leveling of an electric mountain transport vehicle equipped with an active suspension system, the method comprising:

[0007] Real-time acquisition of ground contact state data and horizontal axis rotation angle, and contact terrain analysis according to the ground contact state data to obtain corresponding terrain parameter information; the ground contact state data includes monitoring point pressure data of each wheel; the terrain parameter information includes terrain type corresponding terrain pressure distribution data;

[0008] Vehicle load distribution analysis according to the ground contact state data and the terrain inclination parameter at the corresponding sampling time to obtain pressure gravity center offset data; the pressure gravity center offset data includes the pressure mass center offset direction and the pressure mass center offset amplitude of each wheel;

[0009] Adjustment analysis of the horizontal axis rotation angle according to the pressure gravity center offset data to obtain a target horizontal axis rotation angle;

[0010] Vehicle wheel load demand analysis according to the target horizontal axis rotation angle and the terrain pressure distribution data to obtain a wheel pressure adjustment strategy; the wheel pressure adjustment strategy includes the pressure adjustment amount and the target ground pressure value of each wheel;

[0011] Driving the active suspension system to level the vehicle body posture according to the wheel pressure adjustment strategy.

[0012] Further, the monitoring point pressure data includes the pressure value of each pressure monitoring point;

[0013] The step of performing contact terrain analysis according to the ground contact state data to obtain corresponding terrain parameter information includes:

[0014] According to the preset leveling period and the sampling time corresponding to the ground contact state data, obtain the to-be-analyzed ground contact state time series data; the to-be-analyzed ground contact state time series data includes monitoring point pressure time series data of each wheel;

[0015] Map the monitoring point pressure data of each sampling time in the monitoring point pressure time series data of each wheel to a preset grid wheel contact area respectively to generate pressure distribution matrix time series data of each wheel; the preset grid wheel contact area is obtained by spatial discretization processing of the wheel surface area according to a preset grid division rule;

[0016] According to the pressure distribution matrix time series data of each wheel, perform pressure partitioning on all pressure monitoring points of each wheel based on a K-means clustering algorithm to obtain corresponding wheel pressure partitioning results;

[0017] According to the wheel pressure partitioning results of each wheel, extract corresponding wheel pressure partitioning feature vectors; the wheel pressure partitioning feature vectors include the pressure mean value and the pressure gradient mean value of each partition on each wheel;

[0018] The wheel pressure partition feature vector is matched with a preset pressure mode library to obtain the terrain parameter information; the preset pressure mode library includes wheel pressure partition standard feature vectors and terrain pressure distribution data corresponding to different terrains.

[0019] Further, the terrain inclination parameters include longitudinal slope and transverse slope.

[0020] The vehicle load distribution analysis according to the ground contact state data and the terrain inclination parameters at the corresponding sampling time is performed to obtain pressure barycenter offset data.

[0021] The wheel load data corresponding to the sampling time of the transverse axis rotation angle is corrected according to the terrain inclination parameters to obtain corrected wheel load information; the wheel load data includes vertical loads of each wheel.

[0022] Wheel pressure barycenter coordinate data corresponding to the sampling time is obtained according to the ground contact state data and the corrected wheel load information; the wheel pressure barycenter coordinate data includes pressure barycenter coordinates of each wheel.

[0023] Pressure barycenter offset information corresponding to each wheel is obtained according to the pressure barycenter coordinates of each wheel and the corresponding wheel geometric center; the pressure barycenter offset information includes transverse offset and longitudinal offset.

[0024] The pressure barycenter offset direction and the pressure barycenter offset amplitude of each wheel are obtained according to the pressure barycenter offset information of each wheel and the wheel forward direction.

[0025] The pressure barycenter offset direction and the pressure barycenter offset amplitude of each wheel are summarized to obtain the pressure barycenter offset data.

[0026] Further, the step of adjusting and analyzing the transverse axis rotation angle according to the pressure barycenter offset data to obtain a target transverse axis rotation angle includes:

[0027] According to the pressure barycenter offset data, angle compensation analysis is performed based on a pre-constructed angle compensation prediction model to obtain a corresponding rotation angle compensation coefficient.

[0028] The product of the rotation angle compensation coefficient and the transverse axis rotation angle is obtained to obtain a corresponding angle adjustment amount.

[0029] The transverse axis rotation angle is adjusted according to the angle adjustment amount to obtain an expected transverse axis rotation angle.

[0030] The expected transverse axis rotation angle is amplitude-limited according to a preset transverse axis rotation angle range to obtain the target transverse axis rotation angle.

[0031] Further, the terrain pressure distribution data includes a ground pressure reference value of each wheel;

[0032] The step of performing wheel load demand analysis according to the target lateral axis rotation angle and the terrain pressure distribution data to obtain a wheel pressure adjustment strategy includes:

[0033] According to the target lateral axis rotation angle and the vehicle center of gravity height, a lateral offset distance of the vehicle center of gravity corresponding to the target lateral axis rotation angle is obtained;

[0034] According to the lateral offset distance of the vehicle center of gravity, the total weight of the vehicle, and the lateral wheel track of the vehicle, a lateral load transfer amount is obtained;

[0035] According to the lateral load transfer amount and the terrain pressure distribution data, wheel load demand data after load transfer is obtained based on a preset load transfer rule; the preset load transfer rule is that the ground pressure reference value of the left wheel is added by the lateral load transfer amount, and the ground pressure reference value of the right wheel is subtracted by the lateral load transfer amount; the wheel load demand data includes a target ground pressure value of each wheel;

[0036] According to the difference between the target ground pressure value of each wheel and the actual ground pressure of the corresponding wheel, a pressure adjustment amount of each wheel is obtained, and the pressure adjustment amount of each wheel and the corresponding target ground pressure value are summarized to obtain the wheel pressure adjustment strategy.

[0037] Further, the step of driving the active suspension system to adjust the body posture according to the wheel pressure adjustment strategy includes:

[0038] According to the wheel pressure adjustment strategy, a corresponding suspension system driving signal is generated; the suspension system driving signal includes a pressure control signal of each wheel;

[0039] The suspension system driving signal is sent to an actuator of the active suspension system, so that the actuator adjusts the ground pressure of each wheel according to the pressure control signal of each wheel, and corresponding adjustment process data is synchronously obtained; the adjustment process data includes a ground pressure value sequence of each wheel and a total suspension stroke change amount;

[0040] According to the adjustment process data, a leveling state analysis result is obtained; the leveling state analysis result includes a leveling result of each wheel;

[0041] When the leveling state analysis result is that the leveling result is not in the expected leveling state and has not reached the control limit, a horizontal axis rotation angle fine adjustment instruction is generated according to the terrain inclination parameter and a torque control rule table constructed in advance, and the active suspension system is driven to fine adjust the vehicle body posture according to the horizontal axis rotation angle fine adjustment instruction.

[0042] When the leveling state analysis result is that the leveling result is not in the expected leveling state and has reached the control limit, the wheel pressure adjustment strategy and the target horizontal axis rotation angle are corrected according to the collected angular velocity time series data, and the active suspension system is driven to re-level the vehicle body posture according to the corrected wheel pressure adjustment strategy and the target horizontal axis rotation angle.

[0043] Further, the step of performing leveling state analysis according to the adjustment process data to obtain a corresponding leveling state analysis result comprises:

[0044] The final stable ground pressure value in the ground pressure value sequence of each wheel and the corresponding target ground pressure value in the wheel pressure adjustment strategy are difference calculated to obtain a pressure adjustment deviation value of each wheel;

[0045] It is judged whether the pressure adjustment deviation value of each wheel is less than a preset deviation threshold value, if yes, the leveling result of the corresponding wheel is set as having reached the expected leveling state, otherwise, it is determined that the expected leveling state is not reached, and it is judged whether the total change amount of the suspension stroke reaches a preset stroke change amount threshold value;

[0046] If yes, the leveling result of the corresponding wheel is set as not reaching the expected leveling state and having reached the control limit;

[0047] If no, the leveling result of the corresponding wheel is set as not reaching the expected leveling state and not reaching the control limit.

[0048] Further, the torque control rule table comprises an angle compensation coefficient corresponding to different torque values and longitudinal slope;

[0049] The step of generating a horizontal axis rotation angle fine adjustment instruction according to the terrain inclination parameter and the torque control rule table constructed in advance comprises:

[0050] The wheel whose leveling result in the leveling state analysis result is not in the expected leveling state and has not reached the control limit is obtained as a deviation affecting wheel;

[0051] The horizontal distance between the vehicle center of gravity positions corresponding to each deviation affecting wheel is obtained, and a deviation generated additional overturning torque value is obtained according to the product sum of the pressure adjustment deviation value of each deviation affecting wheel and the horizontal distance between the vehicle center of gravity positions;

[0052] According to the deviation, an additional roll moment value and a longitudinal slope in the terrain inclination parameter are generated, a corresponding two-dimensional compensation coefficient range is obtained by querying the moment control rule table, and a target angle compensation coefficient is obtained by bilinear interpolation on the two-dimensional compensation coefficient range;

[0053] According to the ratio of the additional roll moment value to a preset vehicle roll stiffness constant, a vehicle roll resistance parameter is obtained, and a horizontal axis rotation angle fine adjustment value is obtained according to the product of the vehicle roll resistance parameter and the target angle compensation coefficient;

[0054] According to the sum of the horizontal axis rotation angle fine adjustment value and a current horizontal axis rotation angle, the target horizontal axis rotation angle is updated, and the horizontal axis rotation angle fine adjustment instruction is generated according to the updated target horizontal axis rotation angle.

[0055] Further, the step of recalculating the wheel pressure adjustment strategy and the target horizontal axis rotation angle according to the collected angular velocity time series data comprises:

[0056] An average value of absolute differences of adjacent angular velocities in the angular velocity time series data is calculated to obtain a change amplitude index;

[0057] Fast Fourier transform is performed on the angular velocity time series data to obtain a main frequency as a change frequency index;

[0058] According to the change amplitude index and the change frequency index, a preset parameter adjustment table is queried to obtain a corresponding pressure adjustment coefficient and an angle adjustment coefficient;

[0059] According to the pressure adjustment coefficient, the pressure adjustment amount of each wheel in the wheel pressure adjustment strategy is corrected to obtain a corresponding corrected pressure adjustment amount;

[0060] According to the corrected pressure adjustment amount of each wheel, the target ground pressure of the corresponding wheel is recalculated, and the wheel pressure adjustment strategy is updated according to the corrected pressure adjustment amount of each wheel and the target ground pressure;

[0061] According to the angle adjustment coefficient, the target horizontal axis rotation angle is corrected to obtain the updated target horizontal axis rotation angle.

[0062] In a second aspect, an embodiment of the present application provides a body posture leveling control system of an electric mountain transport vehicle, the electric mountain transport vehicle being equipped with an active suspension system, and the system comprising:

[0063] The terrain analysis module is used for acquiring ground contact state data and a horizontal shaft rotation angle in real time, and performing contact terrain analysis according to the ground contact state data, so as to obtain corresponding terrain parameter information; the ground contact state data comprises monitoring point pressure data of each wheel; and the terrain parameter information comprises terrain pressure distribution data corresponding to a terrain type.

[0064] The load analysis module is used for performing vehicle load distribution analysis according to the ground contact state data and a terrain inclination parameter at a corresponding sampling time, so as to obtain pressure gravity center offset data; the pressure gravity center offset data comprises pressure gravity center offset direction and pressure gravity center offset amplitude of each wheel.

[0065] The angle analysis module is used for performing adjustment analysis on the horizontal shaft rotation angle according to the pressure gravity center offset data, so as to obtain a target horizontal shaft rotation angle.

[0066] The strategy acquisition module is used for performing wheel load bearing demand analysis according to the target horizontal shaft rotation angle and the terrain pressure distribution data, so as to obtain a wheel pressure adjustment strategy; the wheel pressure adjustment strategy comprises pressure adjustment amount and target ground contact pressure value of each wheel.

[0067] The attitude leveling module is used for driving the active suspension system to perform vehicle body attitude leveling according to the wheel pressure adjustment strategy.

[0068] The application provides a vehicle body attitude leveling control method and system for an electric mountain transport vehicle, which realizes real-time acquisition of ground contact state data comprising monitoring point pressure data of each wheel and a horizontal shaft rotation angle, performs contact terrain analysis according to the ground contact state data to obtain corresponding terrain parameter information comprising terrain pressure distribution data corresponding to a terrain type, performs vehicle load distribution analysis according to the ground contact state data and a terrain inclination parameter at a corresponding sampling time to obtain pressure gravity center offset data comprising pressure gravity center offset direction and pressure gravity center offset amplitude of each wheel, performs adjustment analysis on the horizontal shaft rotation angle according to the pressure gravity center offset data to obtain a target horizontal shaft rotation angle, performs wheel load bearing demand analysis according to the target horizontal shaft rotation angle and the terrain pressure distribution data to obtain a wheel pressure adjustment strategy, and drives the active suspension system to perform vehicle body attitude leveling according to the wheel pressure adjustment strategy. BRIEF DESCRIPTION OF DRAWINGS

[0069] Figure 1 is a flowchart of the body posture leveling control method of the electric mountain transport vehicle in the embodiment of the present application;

[0070] Figure 2 is a structural diagram of the body posture leveling control system of the electric mountain transport vehicle in the embodiment of the present application;

[0071] Among them, the description of the drawings is:

[0072] 1, terrain analysis module; 2, load analysis module; 3, angle analysis module; 4, strategy acquisition module; 5, posture leveling module. DETAILED DESCRIPTION

[0073] In order to make the purpose, technical scheme and beneficial effects of the present application clearer, the present application will be further described in detail below in combination with the drawings and embodiments. Obviously, the following described embodiments are part of the embodiments of the present application, and are only used to illustrate the present application, but not to limit the scope of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of the present application.

[0074] In one embodiment, as shown in Figure 1 A body posture leveling control method of an electric mountain transport vehicle is provided, and the electric mountain transport vehicle is equipped with an active suspension system. The electric mountain transport vehicle can be understood as an existing electric vehicle used for transporting goods or personnel in complex terrain environments such as rugged, uneven, and large-slope mountainous, hilly, and forested areas, and driven by electricity. The corresponding active suspension system can be understood as one of the existing hydraulic control suspension system, air suspension system, and electromagnetic induction suspension system that can support the control of the vehicle's lateral axis rotation angle and wheel ground pressure. In actual leveling control, the execution mechanism of the active suspension system can be driven based on the real-time analysis of the wheel pressure adjustment strategy and the target lateral axis rotation angle to level the body posture. The specific body posture leveling control method based on the active suspension system includes the following steps:

[0075] S11, real-time acquisition of ground contact state data and lateral axis rotation angle, and contact terrain analysis according to the ground contact state data to obtain corresponding terrain parameter information; wherein the ground contact state data can be understood as the wheel ground pressure monitoring data collected by the flexible piezoresistive / piezocapacitive film sensor array arranged in each tire inner liner or rim surface according to the actual application requirements in advance, that is, the ground contact state data includes the monitoring point pressure data of each wheel, and in actual application, the monitoring point pressure data collected by the sensor array includes the pressure value of the pressure monitoring point corresponding to each sensor in the sensor array. The terrain parameter information can be understood as the ground type of the current vehicle driving and the ground pressure parameter data of each wheel under the terrain type obtained based on the wheel ground state analysis of the ground contact state data, that is, the terrain parameter information includes the terrain pressure distribution data corresponding to the terrain type.

[0076] Specifically, the step of analyzing the contact terrain according to the ground contact state data to obtain corresponding terrain parameter information includes:

[0077] According to the preset leveling period and the sampling time corresponding to the ground contact state data, the ground contact state time series data to be analyzed is obtained; wherein the preset leveling period can be understood as the maximum allowed time window for sensing terrain environment changes based on the actual vehicle body posture leveling and balance calculation and analysis efficiency requirements, and the specific duration is not limited here. Correspondingly, the ground contact state time series data to be analyzed can be understood as the ground contact state data corresponding to the preset leveling period duration obtained by counting back from the sampling time of the ground contact state data to improve the terrain sensing accuracy, that is, the ground contact state time series data to be analyzed includes the monitoring point pressure time series data of each wheel, and the monitoring point pressure time series data includes the monitoring point pressure data of multiple sampling times.

[0078] The monitoring point pressure data of each sampling time in the monitoring point pressure time series data of each wheel is respectively mapped to a preset grid wheel contact area to generate pressure distribution matrix time series data of each wheel; the preset grid wheel contact area is obtained by spatial discretization processing of the wheel surface area according to a preset grid division rule; wherein the preset grid division rule can set the grid size (for example, 10mm) based on the sensor layout position relationship in the sensor array collecting ground contact state data, so as to ensure that each grid unit corresponds to a sensor, and facilitate capturing the pressure detail changes of each surface position of the wheel; the corresponding preset grid wheel contact area can be understood as the area that the entire wheel can contact with the ground, and the implementation process of spatial discretization processing of the wheel surface area based on the preset grid division rule can be realized by referring to the related existing grid method, which is not described in detail here. The corresponding pressure distribution matrix time series data includes a pressure distribution matrix generated by mapping the monitoring point pressure data of each sampling time to the preset grid wheel contact area, and the elements of each position in the matrix are determined according to the positions and corresponding pressure values of each pressure monitoring point, which is not described in detail here.

[0079] According to the pressure distribution matrix time series data of each wheel, the pressure of all pressure monitoring points of each wheel is divided based on the K-means clustering algorithm to obtain the corresponding wheel pressure partition result; wherein the wheel pressure partition result can be understood as a plurality of pressure regions obtained by clustering and grouping all pressure monitoring points on the same wheel according to the pressure value size, for example, in actual application, three initial cluster centers representing high pressure region, medium pressure region (which can be understood as pressure transition zone) and low pressure region can be randomly selected, then the distance of each pressure monitoring point to each cluster center is calculated, each pressure monitoring point is classified into the category of the nearest cluster center, and the cluster center position is optimized through multiple iterations, finally forming a stable partition result, that is, the required wheel pressure partition result is obtained.

[0080] According to the wheel pressure partition result of each wheel, a corresponding wheel pressure partition feature vector is extracted; the wheel pressure partition feature vector includes the pressure mean value and the pressure gradient mean value of each type of partition on each wheel; in actual application, the acquisition process of the wheel pressure partition feature vector can be understood as follows: first, a corresponding wheel pressure partition distribution map is generated according to the wheel pressure partition result of each wheel; the pressure mean value and the pressure gradient mean value of each pressure region in the wheel pressure partition distribution map are calculated based on the pressure value (the pressure gradient amplitude in each region is calculated first, and then the mean value is calculated); the pressure mean value and the pressure gradient mean value of each pressure region corresponding to each wheel pressure partition distribution map are encoded and spliced in order to obtain the wheel pressure partition encoding vector of a single wheel, and then the wheel pressure partition encoding vectors of each wheel are spliced in a preset order (for example, front left-rear left-front right-rear right) to obtain the required wheel pressure partition feature vector.

[0081] The wheel pressure partition feature vector is matched with a preset pressure pattern library to obtain the terrain parameter information; wherein the preset pressure pattern library can be understood as a database constructed based on the wheel pressure partition and wheel reference ground contact pressure value analysis of a data set including ground contact state data of various terrains, and the wheel pressure partition and wheel ground contact pressure can be obtained by referring to related prior art analysis, which will not be described in detail here. The preset pressure pattern library includes a plurality of terrain types and corresponding wheel pressure partition feature vectors and terrain pressure distribution data; that is, the preset pressure pattern library includes wheel pressure partition standard feature vectors and terrain pressure distribution data corresponding to different terrains, and the terrain pressure distribution data includes the ground contact pressure reference value of each wheel. In actual application, the wheel pressure partition feature vector obtained at present can be sequentially analyzed for similarity (such as calculating the Euclidean distance) with the wheel pressure partition standard feature vectors in the preset pressure pattern library, and the terrain type and terrain pressure distribution data corresponding to the wheel pressure partition standard feature vector with the highest similarity are taken as the required terrain parameter information.

[0082] The method provided in the embodiment based on ground contact state data for wheel pressure partition feature extraction and based on wheel pressure partition feature for terrain recognition facilitates real-time, efficient and accurate perception of the current driving road surface environment of the vehicle, and obtains reliable terrain information, which provides an effective reference basis for subsequent vehicle body posture leveling control.

[0083] S12, vehicle load distribution analysis is performed according to the ground contact state data and the terrain inclination parameter at the corresponding sampling time to obtain pressure barycenter offset data; the pressure barycenter offset data includes the pressure centroid offset direction and the pressure centroid offset amplitude of each wheel; wherein the terrain inclination parameter includes the longitudinal slope and the transverse slope of the road surface, which can correspond to the vehicle longitudinal inclination and the vehicle transverse inclination collected by the inclination sensor arranged on the vehicle, respectively.

[0084] Specifically, the step of performing vehicle load distribution analysis according to the ground contact state data and the terrain inclination parameter at the corresponding sampling time to obtain pressure barycenter offset data comprises:

[0085] According to the terrain inclination parameter, the wheel load data at the corresponding sampling time of the horizontal axis rotation angle is corrected to obtain corrected wheel load information; the wheel load data comprises vertical loads of each wheel; wherein the vertical load can be understood as data obtained by performing attitude transformation (the attitude transformation matrix is determined based on the wheel force sensor installation angle) on the load data collected by the wheel force sensor pre-installed on each wheel. Considering that when the vehicle travels on a road surface with different inclination parameters, the gravity component will be decomposed along the slope direction, causing the vertical load of each wheel to shift, the embodiment preferably corrects the wheel load data based on the actual terrain inclination parameter before using it for analysis. The specific correction can be understood as correcting the vertical load of each wheel according to the following formula to obtain corrected wheel load information comprising the vertical load of each wheel, so as to ensure the accuracy of subsequent wheel pressure barycenter coordinate calculation, while considering the longitudinal slope, the transverse slope and the wheel camber angle (which can be obtained by the camber angle sensor arranged on the wheel):

[0086]

[0087] In the formula, F m,z and F m,z_vehicle respectively represent the vertical load and the vertical load of the mth wheel; θ, φ and γ respectively represent the longitudinal slope, the transverse slope and the wheel camber angle.

[0088] According to the ground contact state data and the corrected wheel load information, wheel pressure barycenter coordinate data at the corresponding sampling time is obtained; the wheel pressure barycenter coordinate data comprises pressure barycenter coordinates of each wheel, and the pressure barycenter coordinates are represented as:

[0089]

[0090] In the formula, X m and Y m respectively represent the X-axis coordinate and the Y-axis coordinate of the pressure barycenter of the mth wheel, m = 1, 2, 3, 4; p m,i represents the pressure value of the i th pressure monitoring point of the mth wheel; x m,i and y m,i respectively represent the X-axis coordinate and the Y-axis coordinate of the position coordinate of the i th pressure monitoring point of the mth wheel in the wheel coordinate system with the wheel geometric center ground projection point as the origin; F m,zrepresents the vertical load of the mth wheel; n represents the total number of pressure monitoring points on the wheel.

[0091] According to the pressure centroid coordinates of each wheel and the corresponding wheel geometric center, the pressure centroid offset information corresponding to each wheel is obtained; the pressure centroid offset information includes a lateral offset and a longitudinal offset; wherein the lateral offset can be understood as the offset of the X-axis coordinate of the pressure centroid coordinate relative to the X-axis coordinate of the wheel geometric center, and the longitudinal offset can be understood as the offset of the Y-axis coordinate of the pressure centroid coordinate relative to the Y-axis coordinate of the wheel geometric center, and the specific calculation process is not described here.

[0092] According to the pressure centroid offset information of each wheel and the wheel forward direction, the pressure centroid offset direction and the pressure centroid offset amplitude of each wheel are obtained; wherein the pressure centroid offset direction can be understood as the included angle between the vector direction from the wheel geometric center to the pressure centroid and the wheel forward direction; the pressure centroid offset amplitude can be understood as a value calculated based on the Pythagorean theorem according to the lateral offset and the longitudinal offset, i.e. the square root of the sum of the squares of the lateral offset and the longitudinal offset, to truly reflect the stress state of the wheel, and a larger offset amplitude often indicates that the vehicle may slip or roll over, providing a reliable basis for subsequent reasonable adjustment of the horizontal axis rotation angle.

[0093] The pressure centroid offset direction and the pressure centroid offset amplitude of each wheel are summarized to obtain the pressure gravity center offset data.

[0094] The method for analyzing the pressure centroid offset of each wheel based on the real-time collected ground contact state data and the terrain inclination parameter can accurately reflect the gravity center offset caused by the change of the wheel ground contact pressure under different terrain conditions, and provides reliable support for the accuracy of the subsequent adjustment of the horizontal axis rotation angle considering the influence of the gravity center offset.

[0095] S13, adjusting and analyzing the horizontal axis rotation angle according to the pressure gravity center offset data to obtain a target horizontal axis rotation angle.

[0096] Specifically, the step of adjusting and analyzing the horizontal axis rotation angle according to the pressure gravity center offset data to obtain a target horizontal axis rotation angle includes:

[0097] According to the pressure center of gravity offset data, angle compensation analysis is performed based on a pre-constructed angle compensation prediction model to obtain a corresponding rotation angle compensation coefficient; wherein, the angle compensation prediction model can be understood as a data set including pressure center of gravity offset data and corresponding transverse axis rotation angle adjustment coefficients constructed based on vehicle leveling stability, which is obtained by training a neural network model and can perform predictive analysis based on the input pressure center of gravity offset data to obtain the required rotation angle compensation coefficient; it should be noted that the type selection of the neural network model and the implementation of the model training method can refer to the relevant existing technology implementation.

[0098] The corresponding angle adjustment amount is obtained according to the product of the rotation angle compensation coefficient and the horizontal axis rotation angle; in actual application, the rotation angle compensation coefficient is a positive value. Since the horizontal axis rotation angle can be positive or negative, the corresponding angle adjustment amount can also be positive or negative.

[0099] The transverse axis rotation angle is adjusted according to the angle adjustment amount to obtain a desired transverse axis rotation angle; wherein, the acquisition of the desired transverse axis rotation angle can be understood as adjusting the transverse axis rotation angle based on the angle adjustment amount on the principle of reducing the degree of vehicle tilt; for example, if the current transverse axis rotation angle is a positive value, it means that the vehicle is tilted to the right, and the calculated angle adjustment amount is also a positive value, then it means that the degree of tilt needs to be reduced, and the desired transverse axis rotation angle is equal to the current transverse axis rotation angle minus the angle adjustment amount.

[0100] According to a preset transverse axis rotation angle range, the desired transverse axis rotation angle is limited to obtain the target transverse axis rotation angle; wherein, the preset transverse axis rotation angle range can be a transverse axis rotation angle adjustable range pre-set based on actual vehicle driving safety requirements; in actual application, if the desired transverse axis rotation angle obtained by adjusting the transverse axis rotation angle according to the angle adjustment amount is not within the preset transverse axis rotation angle range, then the transverse axis rotation angle upper limit or lower limit closest to it is directly used as the final target transverse axis rotation angle to prevent the risk of vehicle loss of control due to excessive adjustment.

[0101] In this embodiment, while taking into account the influence of the center of gravity offset, a rotation angle compensation coefficient of the lateral axis rotation angle is generated based on a neural network model for adjusting the lateral axis rotation angle. This method can effectively ensure the accuracy and efficiency of the lateral axis rotation angle adjustment, ensure timely and accurate control of the vehicle posture, and significantly improve the vehicle's driving stability and safety under complex road conditions.

[0102] S14, performing wheel load demand analysis according to the target lateral axis rotation angle and the terrain pressure distribution data, to obtain a wheel pressure adjustment strategy; wherein the wheel pressure adjustment strategy can be understood as a ground pressure redistribution strategy of each wheel, so as to reestablish the balance between the gravity moment generated by the total weight of the vehicle and the counter moment generated by the ground support force.

[0103] Specifically, the step of performing wheel load demand analysis according to the target lateral axis rotation angle and the terrain pressure distribution data to obtain a wheel pressure adjustment strategy comprises:

[0104] According to the target lateral axis rotation angle and the vehicle gravity center height, a vehicle gravity center lateral offset distance corresponding to the target lateral axis rotation angle is obtained; that is, the vehicle gravity center lateral offset distance can be expressed as the product of the vehicle gravity center height and the tangent value of the target lateral axis rotation angle.

[0105] According to the vehicle gravity center lateral offset distance, the total weight of the vehicle and the vehicle lateral wheel track, a lateral load transfer amount is obtained; wherein the lateral load transfer amount can be expressed as:

[0106]

[0107] In the formula, m represents the total weight of the vehicle; D1 and L represent the vehicle gravity center lateral offset distance and the vehicle lateral wheel track respectively; C represents the lateral load transfer amount.

[0108] According to the lateral load transfer amount and the terrain pressure distribution data, a wheel load demand data after load transfer is obtained based on a preset load transfer rule; the preset load transfer rule is that the ground pressure reference value of the left side wheel is added by the lateral load transfer amount, and the ground pressure reference value of the right side wheel is subtracted by the lateral load transfer amount, so as to ensure that the total load is redistributed among the wheels while the total load remains unchanged; the wheel load demand data includes target ground pressure values of each wheel; that is, the target ground pressure values of each wheel are the expected ground pressure values after pressure redistribution obtained by adding / subtracting the lateral load transfer amount to / from the corresponding ground pressure reference value in the terrain pressure distribution data.

[0109] According to the difference between the target ground pressure value of each wheel and the actual ground pressure of the corresponding wheel, the pressure adjustment amount of each wheel is obtained, and the pressure adjustment amount of each wheel and the target ground pressure value are summarized to obtain the wheel pressure adjustment strategy; the wheel pressure adjustment strategy includes the pressure adjustment amount and the target ground pressure value of each wheel; wherein the actual ground pressure of the wheel can be understood as the ratio of the actual vertical load collected by the wheel force sensor to the wheel ground contact area; if the actual pressure adjustment amount is negative, it is considered that the wheel needs to reduce the pressure, and the pressure reduction operation can be performed through the control principle of the actual active suspension system (reducing the suspension stiffness or adjusting the air spring pressure); if the actual pressure adjustment amount is positive, it is considered that the wheel needs to increase the pressure, and the corresponding pressure increasing operation can be performed through the control principle of the actual active suspension system.

[0110] The embodiment realizes the differentiated allocation of the left and right wheel load requirements under the condition that the total load remains unchanged by analyzing the wheel load requirements based on the target horizontal axis rotation angle and the wheel pressure reference value under the corresponding terrain type, ensures the accuracy of the contact pressure value control of each wheel, and effectively prevents the vehicle from bouncing too much and the risk of rollover.

[0111] S15, according to the wheel pressure adjustment strategy, driving the active suspension system to level the vehicle body posture.

[0112] Specifically, the step of driving the active suspension system to level the vehicle body posture according to the wheel pressure adjustment strategy comprises:

[0113] According to the wheel pressure adjustment strategy, a corresponding suspension system driving signal is generated; the suspension system driving signal includes a pressure control signal of each wheel, and each pressure control signal can be understood as a digital driving signal that can be recognized and executed by the corresponding actuator of the active suspension system, such as if the active suspension system is an air suspension system, the target ground pressure value of each wheel is converted into a corresponding digital driving signal through PID (Proportional Integral Derivative) control or other closed-loop control, and then the digital driving signal is converted into a voltage or current signal by a digital-to-analog converter and input to a corresponding electromagnetic valve driver, the electromagnetic valve driver amplifies the signal to a sufficient current to drive the electromagnetic valve coil to act (open / close / adjust), thereby realizing the inflation or deflation of the air spring, and finally making the wheel reach the target ground pressure value.

[0114] The suspension system driving signal is sent to the actuator of the active suspension system to control the wheel ground pressure according to the wheel pressure control signal of each wheel, and the corresponding adjustment process data is obtained synchronously; wherein the specific process of wheel ground pressure control varies with the actual control principle of the active suspension system, which is not described in detail here. In order to facilitate effective monitoring of the actual execution effect of the wheel pressure adjustment strategy, the embodiment preferably continuously collects the actual ground pressure values (pressure sensor) and suspension stroke change amounts (collected by displacement sensor, which can reflect the vertical displacement of the wheel relative to the vehicle body) of each wheel during the adjustment process through the corresponding sensors arranged during the ground pressure adjustment process of each wheel by the execution mechanism, to obtain the corresponding adjustment process data for subsequent leveling state analysis; that is, the adjustment process data includes the ground pressure value sequence of each wheel and the total change amount of the suspension stroke.

[0115] The leveling state analysis is performed according to the adjustment process data to obtain the corresponding leveling state analysis result; the leveling state analysis result includes the leveling result of each wheel, and the corresponding leveling result is any one of reaching the expected leveling state, not reaching the expected leveling state and not reaching the control limit, and not reaching the expected leveling state and reaching the control limit. Specifically, the step of performing leveling state analysis according to the adjustment process data to obtain the corresponding leveling state analysis result includes:

[0116] The final stable ground pressure value in the ground pressure value sequence of each wheel and the corresponding target ground pressure value in the wheel pressure adjustment strategy are calculated to obtain the pressure adjustment deviation value of each wheel; wherein the final stable ground pressure value can be understood as the actual ground pressure value at the last sampling time in the ground pressure value sequence.

[0117] It is judged whether the pressure adjustment deviation value of each wheel is less than a preset deviation threshold value, if yes, the leveling result of the corresponding wheel is set as having reached the expected leveling state, otherwise, it is determined that the expected leveling state has not been reached, and it is judged whether the corresponding total change amount of the suspension stroke reaches a preset stroke change amount threshold value; wherein the preset deviation threshold value can be understood as a deviation upper limit for judging whether the wheel ground pressure value control reaches the expected adjustment, which facilitates rapid identification of potential instability risk and provides a trigger signal for subsequent compensation control; the preset stroke change amount threshold value can be understood as a stroke change amount upper limit in the control process, if the value is reached, it means that the corresponding pressure adjustment deviation cannot be reduced by continuing to adjust based on the current adjustment, that is, the wheel ground pressure control has reached the control limit. It should be noted that the preset deviation threshold value and the preset stroke change amount threshold value can be set according to actual application requirements, which are not specifically limited here.

[0118] If yes, the leveling result of the corresponding wheel is set as not reaching the expected leveling state and reaching the regulation limit; that is, if the pressure adjustment deviation value of a certain wheel is greater than or equal to the preset deviation threshold value and the total change amount of the suspension stroke has reached the preset stroke change amount threshold value, the leveling result of the wheel is not reaching the expected leveling state but reaching the regulation limit.

[0119] If no, the leveling result of the corresponding wheel is set as not reaching the expected leveling state and not reaching the regulation limit; that is, if the pressure adjustment deviation value of a certain wheel is greater than or equal to the preset deviation threshold value and the total change amount of the suspension stroke is less than the preset stroke change amount threshold value, the leveling result of the wheel is not reaching the expected leveling state and not reaching the regulation limit.

[0120] The embodiment can effectively improve the comprehensiveness and accuracy of the leveling state analysis by comprehensively analyzing the wheel leveling state based on the ground pressure adjustment deviation value and the total change amount of the suspension stroke, thereby providing a reliable analysis basis for whether to perform secondary adjustment or adopt other compensation measures.

[0121] When the leveling result of not reaching the expected leveling state and not reaching the regulation limit exists in the leveling state analysis result, a horizontal shaft rotation angle fine adjustment instruction is generated according to the terrain inclination parameter and the pre-constructed torque control rule table, and the main suspension system is driven to perform body posture fine adjustment according to the horizontal shaft rotation angle fine adjustment instruction; wherein the torque control rule table includes angle compensation coefficients corresponding to different torque values and longitudinal slopes, which can be constructed based on a large amount of historical experimental data, and the specific construction process is not described here; the corresponding horizontal shaft rotation angle fine adjustment instruction can be understood as a horizontal shaft rotation angle regulation instruction generated by fine adjusting the current horizontal shaft rotation angle based on the angle compensation coefficient obtained by querying the torque control rule table based on the terrain inclination parameter. Specifically, the step of generating a horizontal shaft rotation angle fine adjustment instruction according to the terrain inclination parameter and the pre-constructed torque control rule table includes:

[0122] The wheel with the leveling result of not reaching the expected leveling state and not reaching the regulation limit in the leveling state analysis result is obtained as a deviation-affected wheel; wherein the deviation-affected wheel can be understood as a wheel that increases the risk of additional overturning torque, and there can be one or more, which is determined according to the actual leveling state analysis result.

[0123] The horizontal distance between the vehicle center of gravity and each of the deviation-affected wheels is obtained, and the product of the pressure adjustment deviation value of each of the deviation-affected wheels and the horizontal distance between the vehicle center of gravity is accumulated to obtain an additional overturning moment value caused by the deviation; wherein the horizontal distance between the vehicle center of gravity and each of the deviation-affected wheels can be understood as the horizontal distance between the wheel and the vehicle center of gravity. First, the vehicle center of gravity is estimated based on IMU (Inertial Measurement Unit) sensor data, wheel speed sensor data, suspension force sensor data, and a pre-set vehicle dynamics model (such as a three-degree-of-freedom model). Then, the coordinate position of each of the deviation-affected wheels is determined based on the vehicle coordinate system, the wheel track, and the wheelbase. Finally, the absolute difference between the X-axis coordinate of each of the deviation-affected wheels and the X-axis coordinate of the vehicle center of gravity is obtained to determine the corresponding horizontal distance between the vehicle center of gravity. The calculation process of the additional overturning moment value caused by the deviation is based on the principle of mechanical equilibrium. Considering that each of the deviation-affected wheels has a pressure adjustment deviation value that will generate a large additional moment relative to the vehicle center of gravity, the product of the pressure adjustment deviation value of each of the deviation-affected wheels and the corresponding horizontal distance between the vehicle center of gravity is obtained to determine the corresponding additional overturning moment. The algebraic sum of each of the additional overturning moments is calculated to obtain the required additional overturning moment value caused by the deviation. It should be noted that when calculating the algebraic sum of the additional moments generated by each of the deviation-affected wheels, the directionality needs to be considered, with the moment being positive when the vehicle tilts to the right and negative when the vehicle tilts to the left. This calculation method can accurately quantify the impact of pressure deviation on the vehicle attitude.

[0124] According to the additional overturning moment value caused by the deviation and the longitudinal slope in the terrain inclination parameter, a corresponding two-dimensional compensation coefficient range is obtained by querying the moment control rule table, and a target angle compensation coefficient is obtained by bilinear interpolation of the two-dimensional compensation coefficient range; wherein the two-dimensional compensation coefficient range can be understood as the compensation coefficient range corresponding to the four angle compensation coefficients obtained by querying the moment control rule table based on the upper and lower limit values of the moment value range corresponding to the additional overturning moment value caused by the deviation and the upper and lower limit values of the longitudinal slope value range corresponding to the longitudinal slope in the terrain inclination parameter. In actual application, the moment value range of the additional overturning moment value caused by the deviation and the longitudinal slope value range of the longitudinal slope in the terrain inclination parameter are determined in the moment control rule table, and the corresponding four angle compensation coefficients are obtained based on the upper and lower limit values of the moment value range and the longitudinal slope value range in the moment control rule table. Then, based on the obtained two-dimensional compensation coefficient range defined by the four angle compensation coefficients, the bilinear interpolation method is used to interpolate the angle compensation coefficient in the moment dimension first, and then in the slope dimension, and finally an accurate compensation coefficient is obtained as the required target angle compensation coefficient.

[0125] The method for obtaining the target angle compensation coefficient based on the bilinear interpolation technology can effectively avoid the error risk caused by directly adopting the value closest to the angle compensation coefficient in the moment control rule table when the deviation produces an additional overturning moment value and a longitudinal slope that cannot exactly match a certain moment value and longitudinal slope in the moment control rule table, avoid the step change of control, improve the smoothness of adjustment, effectively guarantee the accuracy of the subsequent generated horizontal axis rotation angle fine tuning instruction, and further provide reliable protection for improving the final leveling effect.

[0126] The vehicle anti-roll ability parameter is obtained according to the ratio of the additional overturning moment value generated by the deviation to a preset vehicle anti-overturning stiffness constant, and the horizontal axis rotation angle fine tuning value is obtained according to the product of the vehicle anti-roll ability parameter and the target angle compensation coefficient. The preset vehicle anti-overturning stiffness constant can be understood as a parameter of vehicle design and configuration, which is different for specific vehicles and is not limited here.

[0127] The target horizontal axis rotation angle is updated according to the sum of the horizontal axis rotation angle fine tuning value and the current horizontal axis rotation angle, and the horizontal axis rotation angle fine tuning instruction is generated according to the updated target horizontal axis rotation angle. The horizontal axis rotation angle fine tuning instruction can be understood as a suspension system driving signal for driving the actuator of the active suspension system based on the updated target horizontal axis rotation angle, and the specific generation process is different for the driving principle of the active suspension system, which is not described here. It should be noted that in order to ensure the safety of regulation and control, the sum of the horizontal axis rotation angle fine tuning value and the current horizontal axis rotation angle needs to be limited in amplitude before obtaining the updated target horizontal axis rotation angle.

[0128] When the vehicle body posture leveling processing based on the wheel pressure adjustment strategy does not reach the expected leveling state but still has a regulation and control space, the generation of the horizontal axis rotation angle fine tuning instruction for secondary fine tuning based on the terrain inclination parameter and the moment control rule table can realize rapid and accurate vehicle body posture leveling control.

[0129] When the leveling results in the leveling state analysis result are all not in the expected leveling state and the regulation limit has been reached, the wheel pressure adjustment strategy and the target lateral axis rotation angle are corrected according to the collected angular velocity time series data, and the active suspension system is driven to re-level the vehicle body posture according to the corrected wheel pressure adjustment strategy and the target lateral axis rotation angle. The angular velocity time series data can be understood as angular velocity data of a certain time length obtained by continuous sampling of a gyroscope during the regulation process based on the wheel pressure adjustment strategy. When the expected leveling state cannot be reached after the regulation based on the wheel pressure adjustment strategy, and the ground pressure regulation gap cannot be adjusted by the lateral axis rotation angle fine adjustment, the current leveling strategy needs to be deeply optimized and adjusted based on the wheel pressure adjustment strategy and the target lateral axis rotation angle.

[0130] Specifically, the step of recalculating the wheel pressure adjustment strategy and the target lateral axis rotation angle according to the collected angular velocity time series data includes:

[0131] The average value of the absolute difference between adjacent angular velocities in the angular velocity time series data is calculated to obtain a change amplitude index. In actual application, if there are 100 continuous sampling points in the angular velocity time series data, the difference between adjacent sampling points (if the first point is 5 degrees per second and the second point is 5.3 degrees per second, the difference is 0.3 degrees per second) can be calculated, and the average of the absolute values of all differences can be obtained to obtain the change amplitude index reflecting the fluctuation degree of the signal.

[0132] The angular velocity time series data is subjected to fast Fourier transform to obtain a main frequency as a change frequency index. The change frequency index is obtained by first converting the angular velocity time series data from the time domain to the frequency domain through fast Fourier transform, and then identifying the main frequency component as the change frequency index, which is used to reflect that the vehicle is currently experiencing periodic disturbance of this frequency.

[0133] According to the change amplitude index and the change frequency index, a preset parameter adjustment table is queried to obtain corresponding pressure adjustment coefficients and angle adjustment coefficients. The preset parameter adjustment table can be understood as a data table with the lateral axis as the interval range of the change amplitude index and the vertical axis as the interval range of the change frequency index, which is constructed based on empirical knowledge in advance. The table includes pressure adjustment coefficients and angle adjustment coefficients corresponding to different change amplitude indexes and change frequency indexes obtained through a large number of road tests and optimization.

[0134] According to the pressure adjustment coefficient, the pressure adjustment amount of each wheel in the wheel pressure adjustment strategy is corrected to obtain a corresponding corrected pressure adjustment amount; wherein the corrected pressure adjustment amount of each wheel can be expressed as the product of the pressure adjustment amount of each wheel in the wheel pressure adjustment strategy and the pressure adjustment coefficient; for example, the current pressure adjustment amount of a certain wheel is 20 kPa, and the obtained pressure coefficient is 0.85, then the optimized corrected pressure adjustment amount is 17 kPa, which can reflect the more conservative pressure adjustment strategy needed in the current dynamic environment to avoid excessive adjustment caused by rapid changes in the environment.

[0135] According to the corrected pressure adjustment amount of each wheel, the target ground pressure of the corresponding wheel is recalculated, and the wheel pressure adjustment strategy is updated according to the corrected pressure adjustment amount of each wheel and the target ground pressure; wherein the recalculated target ground pressure of the wheel can be understood as the algebraic sum of the corrected pressure adjustment amount of each wheel and the current actual ground pressure of the wheel.

[0136] According to the angle adjustment coefficient, the target lateral axis rotation angle is corrected to obtain an updated target lateral axis rotation angle; wherein the process of updating the target lateral axis rotation angle can be understood as obtaining an angle adjustment amount based on the product of the angle adjustment coefficient and the current lateral axis rotation angle, adjusting the current lateral axis rotation angle based on the angle adjustment amount, and then limiting the amplitude of the expected lateral axis rotation angle value obtained after adjustment to obtain the updated target lateral axis rotation angle.

[0137] After obtaining the corrected wheel pressure adjustment strategy and the target lateral axis rotation angle through the above method steps, the wheel pressure adjustment strategy and the target lateral axis rotation angle can be converted into corresponding control driving signals at the same time and sent to the actuator of the active suspension system to drive the active suspension system to re-level the vehicle body posture. The specific control process of the specific actuator varies depending on the design of the actual active suspension system, which is not described in detail here.

[0138] When the vehicle body posture leveling process based on the wheel pressure adjustment strategy does not reach the expected leveling state and has reached the control limit, the joint control method of the target ground pressure value and the target lateral axis rotation angle of the wheel based on the angular velocity time series data can quickly level the vehicle body posture, maintain the optimal leveling posture in complex dynamic environments, and significantly improve the vehicle driving stability and transportation safety.

[0139] The embodiment of the present application provides the technical scheme that the ground contact state data including the monitoring point pressure data of each wheel and the horizontal shaft rotation angle are acquired in real time, the contact terrain analysis is performed according to the ground contact state data, the terrain parameter information corresponding to the terrain pressure distribution data including the terrain type is obtained, the vehicle load distribution analysis is performed according to the ground contact state data and the terrain inclination parameter at the corresponding sampling time, the pressure barycenter offset data including the pressure barycenter offset direction and the pressure barycenter offset amplitude of each wheel is obtained, the horizontal shaft rotation angle is adjusted and analyzed according to the pressure barycenter offset data, the target horizontal shaft rotation angle is obtained, the wheel load bearing demand analysis is performed according to the target horizontal shaft rotation angle and the terrain pressure distribution data, the wheel pressure adjustment strategy is obtained, and the active suspension system is driven according to the wheel pressure adjustment strategy to perform the vehicle body posture leveling, the terrain environment change is perceived in real time through the monitoring mechanism based on the wheel contact ground state change and the barycenter offset, and the horizontal shaft rotation angle and the wheel grounding pressure are accurately adjusted, the real-time self-adaptive leveling of the vehicle body posture of the electric mountain transport vehicle is realized, the stability of the electric mountain transport vehicle under complex terrain conditions is effectively improved, and reliable protection is provided for the efficient and safe transportation of electric power engineering materials.

[0140] It should be noted that although each step in the above flowchart is displayed in sequence according to the arrow indication, these steps are not necessarily executed in the order indicated by the arrow. Unless otherwise specified herein, the execution of these steps has no strict order limitation, and these steps can be executed in other orders.

[0141] In one embodiment, as shown in Figure 2 A vehicle body posture leveling control system of an electric mountain transport vehicle is provided, the electric mountain transport vehicle is equipped with an active suspension system, and the system comprises:

[0142] A terrain analysis module 1 is configured to acquire ground contact state data and a horizontal shaft rotation angle in real time, and perform contact terrain analysis according to the ground contact state data to obtain corresponding terrain parameter information; the ground contact state data includes monitoring point pressure data of each wheel; and the terrain parameter information includes terrain pressure distribution data corresponding to a terrain type.

[0143] A load analysis module 2 is configured to perform vehicle load distribution analysis according to the ground contact state data and a terrain inclination parameter at a corresponding sampling time to obtain pressure barycenter offset data; the pressure barycenter offset data includes a pressure barycenter offset direction and a pressure barycenter offset amplitude of each wheel.

[0144] An angle analysis module 3 is configured to adjust and analyze the horizontal shaft rotation angle according to the pressure barycenter offset data to obtain a target horizontal shaft rotation angle.

[0145] a strategy acquisition module 4 for analyzing wheel load requirements based on the target transverse axis rotation angle and the terrain pressure distribution data to obtain a wheel pressure adjustment strategy; the wheel pressure adjustment strategy includes a pressure adjustment amount for each wheel and a target ground contact pressure value;

[0146] The posture leveling module 5 is used to drive the active suspension system to level the vehicle body posture according to the wheel pressure adjustment strategy.

[0147] Regarding the specific definition of the vehicle body posture leveling control system of the electric mountain transport vehicle, please refer to the definition of the vehicle body posture leveling control method of the electric mountain transport vehicle above. The corresponding technical effects can also be obtained equivalently, which will not be repeated here. The various modules in the above-mentioned vehicle body posture leveling control system of the electric mountain transport vehicle can be implemented in whole or in part by software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0148] In summary, the embodiment of the present invention provides a body posture leveling control method and system for an electric mountain transport vehicle. This method senses terrain environment changes in real time and accurately adjusts the transverse axis rotation angle and wheel ground pressure through a monitoring mechanism based on changes in wheel contact with the ground and center of gravity offset, thereby achieving real-time adaptive leveling of the body posture of the electric mountain transport vehicle, effectively improving the stability of the electric mountain transport vehicle under complex terrain conditions, and providing reliable guarantee for the efficient and safe transportation of power engineering materials.

[0149] Each embodiment in this specification is described in a progressive manner, and the same or similar parts of each embodiment can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. It should be noted that the various technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the various technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0150] The above-described embodiments merely represent several preferred implementations of the present invention, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the patent. It should be noted that a person skilled in the art can make several improvements and substitutions without departing from the technical principles of the present invention, and such improvements and substitutions should also be considered within the scope of protection of the present invention. Therefore, the scope of protection of the patent for this invention shall be based on the scope of protection of the claims.

Claims

1. A method for controlling the body posture leveling of an electric mountain transport vehicle, characterized in that: An electric mountain transport vehicle is equipped with an active suspension system, and the method includes: Acquiring ground contact state data and a horizontal axis rotation angle in real time, and performing contact terrain analysis based on the ground contact state data to obtain corresponding terrain parameter information; the ground contact state data includes pressure data at monitoring points of each wheel; and the terrain parameter information includes terrain pressure distribution data corresponding to the terrain type; Performing vehicle load distribution analysis based on the ground contact state data and the terrain inclination parameter at the corresponding sampling moment to obtain pressure center of mass offset data; the pressure center of mass offset data includes the pressure center of mass offset direction and pressure center of mass offset amplitude of each wheel; Adjusting and analyzing the horizontal axis rotation angle according to the pressure center of gravity offset data to obtain a target horizontal axis rotation angle; performing a wheel load demand analysis based on the target transverse axis rotation angle and the terrain pressure distribution data to obtain a wheel pressure adjustment strategy; the wheel pressure adjustment strategy includes a pressure adjustment amount for each wheel and a target ground contact pressure value; According to the wheel pressure adjustment strategy, the active suspension system is driven to level the vehicle body posture.

2. The method for controlling the body posture leveling of an electric mountain transport vehicle according to claim 1, wherein: The monitoring point pressure data includes the pressure value of each pressure monitoring point; The step of performing contact terrain analysis based on the ground contact state data to obtain corresponding terrain parameter information includes: Acquire the ground contact state time series data to be analyzed according to the preset leveling cycle and the sampling time corresponding to the ground contact state data; the ground contact state time series data to be analyzed includes the pressure time series data of the monitoring points of each wheel; Mapping the monitoring point pressure data at each sampling moment in the monitoring point pressure time series data of each wheel to a preset gridded wheel contact area to generate pressure distribution matrix time series data for each wheel; the preset gridded wheel contact area is obtained by spatially discretizing the wheel surface area according to a preset grid division rule; According to the pressure distribution matrix time series data of each wheel, all pressure monitoring points of each wheel are pressure zoned based on the K-means clustering algorithm to obtain corresponding wheel pressure zone results; Extracting corresponding wheel pressure partition feature vectors based on the wheel pressure partition results of each wheel; the wheel pressure partition feature vectors include the pressure mean and pressure gradient mean of each partition on each wheel; The wheel pressure partition feature vector is matched with a preset pressure pattern library to obtain the terrain parameter information; the preset pressure pattern library includes wheel pressure partition standard feature vectors and terrain pressure distribution data corresponding to different terrains.

3. The method for controlling the body posture leveling of an electric mountain transport vehicle according to claim 1, wherein: The terrain inclination parameters include longitudinal slope and transverse slope; The step of performing vehicle load distribution analysis based on the ground contact state data and the terrain inclination parameter at the corresponding sampling moment to obtain pressure center of gravity offset data includes: According to the terrain inclination parameter, the wheel load data at the sampling moment corresponding to the horizontal axis rotation angle is corrected to obtain corrected wheel load information; the wheel load data includes the vertical load of each wheel; Obtaining wheel pressure centroid coordinate data corresponding to a sampling moment based on the ground contact state data and the corrected wheel load information; the wheel pressure centroid coordinate data includes the pressure centroid coordinates of each wheel; Obtaining pressure center of mass offset information corresponding to each wheel based on the pressure center of mass coordinates of each wheel and the corresponding wheel geometric center; the pressure center of mass offset information includes a lateral offset and a longitudinal offset; Obtaining the pressure center of mass offset direction and pressure center of mass offset amplitude of each wheel according to the pressure center of mass offset information of each wheel and the wheel forward direction; The pressure center of mass offset direction and the pressure center of mass offset amplitude of each wheel are summarized to obtain the pressure center of mass offset data.

4. The method for controlling the body posture leveling of an electric mountain transport vehicle according to claim 1, wherein: The step of adjusting and analyzing the horizontal axis rotation angle according to the pressure center of gravity offset data to obtain a target horizontal axis rotation angle includes: According to the pressure center of gravity offset data, an angle compensation analysis is performed based on a pre-built angle compensation prediction model to obtain a corresponding rotation angle compensation coefficient; Obtaining a corresponding angle adjustment amount according to the product of the rotation angle compensation coefficient and the horizontal axis rotation angle; Adjusting the horizontal axis rotation angle according to the angle adjustment amount to obtain a desired horizontal axis rotation angle; According to a preset horizontal axis rotation angle range, the desired horizontal axis rotation angle is limited to obtain the target horizontal axis rotation angle.

5. The vehicle body posture leveling control method of the electric mountain transport vehicle according to claim 1, characterized in that: The terrain pressure distribution data includes a ground contact pressure reference value of each wheel; The step of performing wheel load demand analysis based on the target transverse axis rotation angle and the terrain pressure distribution data to obtain a wheel pressure adjustment strategy includes: Obtaining a lateral offset distance of the vehicle's center of gravity corresponding to the target lateral axis rotation angle according to the target lateral axis rotation angle and the vehicle's center of gravity height; Obtaining a lateral load transfer amount based on the lateral offset distance of the vehicle's center of gravity, the vehicle's gross weight, and the vehicle's lateral wheelbase; Determining wheel load requirement data after load transfer based on the lateral load transfer amount and the terrain pressure distribution data according to a preset load transfer rule; the preset load transfer rule being a ground contact pressure reference value of a left wheel plus the lateral load transfer amount, and a ground contact pressure reference value of a right wheel minus the lateral load transfer amount; the wheel load requirement data including a target ground contact pressure value for each wheel; A pressure adjustment amount for each wheel is obtained based on a difference between the target ground contact pressure value of each wheel and the actual ground contact pressure of the corresponding wheel. The pressure adjustment amount for each wheel and the corresponding target ground contact pressure value are summed to obtain the wheel pressure adjustment strategy.

6. The method for controlling the body posture leveling of an electric mountain transport vehicle according to claim 1, wherein: The step of driving the active suspension system to perform vehicle body posture leveling according to the wheel pressure adjustment strategy includes: generating a corresponding suspension system drive signal according to the wheel pressure adjustment strategy; the suspension system drive signal includes a pressure control signal of each wheel; sending the suspension system drive signal to the actuator of the active suspension system so that the actuator regulates the wheel ground contact pressure according to the pressure control signal of each wheel and simultaneously obtains corresponding adjustment process data; the adjustment process data includes a numerical sequence of the ground contact pressure of each wheel and a total change in suspension travel; Performing a leveling state analysis based on the adjustment process data to obtain a corresponding leveling state analysis result; the leveling state analysis result includes a leveling result of each wheel; When the leveling state analysis results show that the expected leveling state and the control limit have not been reached, a lateral axis rotation angle fine-tuning instruction is generated based on the terrain inclination parameter and a pre-established torque control rule table, and the active suspension system is driven to perform vehicle body posture fine-tuning according to the lateral axis rotation angle fine-tuning instruction; When the leveling results in the leveling state analysis results all fail to reach the expected leveling state and have reached the control limit, the wheel pressure adjustment strategy and the target lateral axis rotation angle are corrected according to the collected angular velocity time series data, and the active suspension system is driven to re-level the vehicle body posture according to the corrected wheel pressure adjustment strategy and the target lateral axis rotation angle.

7. The method for controlling the body posture leveling of an electric mountain transport vehicle according to claim 6, wherein: The step of performing leveling state analysis according to the adjustment process data to obtain corresponding leveling state analysis results includes: Calculating the difference between a final stable ground contact pressure value in the ground contact pressure value sequence of each wheel and a corresponding target ground contact pressure value in the wheel pressure adjustment strategy to obtain a pressure adjustment deviation value for each wheel; determining whether the pressure adjustment deviation value of each wheel is less than a preset deviation threshold; if so, setting the leveling result of the corresponding wheel as having reached the expected leveling state; otherwise, determining that the expected leveling state has not been reached, and determining whether the corresponding total suspension travel change has reached a preset travel change threshold; If yes, the leveling result of the corresponding wheel is set to not reaching the expected leveling state and reaching the control limit; If not, the leveling result of the corresponding wheel is set to not reaching the expected leveling state and not reaching the control limit.

8. The method for controlling the body posture leveling of an electric mountain transport vehicle according to claim 6, wherein: The torque control rule table includes angle compensation coefficients corresponding to different torque values ​​and longitudinal slopes; The step of generating a lateral axis rotation angle fine-tuning instruction according to the terrain inclination parameter and the pre-established torque control rule table includes: obtaining, from the leveling state analysis result, a wheel whose leveling result shows that the wheel has not reached the expected leveling state and has not reached the control limit as a deviation-affecting wheel; Obtaining the horizontal spacing between the center of gravity of the vehicle corresponding to each of the deviation-affecting wheels, and accumulating the product of the pressure-adjusted deviation value of each of the deviation-affecting wheels and the horizontal spacing between the center of gravity of the vehicle to obtain an additional overturning moment value generated by the deviation; generating an additional overturning moment value according to the deviation and the longitudinal slope in the terrain inclination parameter, querying the moment control rule table to obtain a corresponding two-dimensional compensation coefficient range, and performing bilinear interpolation on the two-dimensional compensation coefficient range to obtain a target angle compensation coefficient; Obtaining a vehicle anti-roll capability parameter based on a ratio of an additional overturning moment value generated according to the deviation to a preset vehicle anti-rolling stiffness constant, and obtaining a transverse axis rotation angle fine-tuning value based on a product of the vehicle anti-roll capability parameter and the target angle compensation coefficient; The target horizontal axis rotation angle is updated according to the sum of the horizontal axis rotation angle fine adjustment value and the current horizontal axis rotation angle, and the horizontal axis rotation angle fine adjustment instruction is generated according to the updated target horizontal axis rotation angle.

9. The method for controlling the body posture leveling of an electric mountain transport vehicle according to claim 6, wherein: The step of recalculating the wheel pressure adjustment strategy and the target transverse axis rotation angle according to the collected angular velocity time series data includes: Calculating an average of absolute differences between adjacent angular velocities in the angular velocity time series data to obtain a variation index; Performing a fast Fourier transform on the angular velocity time series data to obtain a main frequency as a change frequency indicator; According to the change amplitude index and the change frequency index, query the preset parameter adjustment table to obtain the corresponding pressure adjustment coefficient and angle adjustment coefficient; Correcting the pressure adjustment amount of each wheel in the wheel pressure adjustment strategy according to the pressure adjustment coefficient to obtain a corresponding corrected pressure adjustment amount; recalculating a target ground contact pressure of each wheel according to the corrected pressure adjustment amount of each wheel, and updating the wheel pressure adjustment strategy according to the corrected pressure adjustment amount and the target ground contact pressure of each wheel; The target horizontal axis rotation angle is corrected according to the angle adjustment coefficient to obtain the updated target horizontal axis rotation angle.

10. A vehicle posture leveling control system for an electric mountain transport vehicle, characterized in that: The electric mountain transport vehicle is equipped with an active suspension system, which includes: A terrain analysis module is configured to acquire ground contact state data and a horizontal axis rotation angle in real time, and perform contact terrain analysis based on the ground contact state data to obtain corresponding terrain parameter information; the ground contact state data includes pressure data at monitoring points of each wheel; and the terrain parameter information includes terrain pressure distribution data corresponding to the terrain type; a load analysis module configured to perform vehicle load distribution analysis based on the ground contact state data and the terrain inclination parameter at the corresponding sampling moment to obtain pressure center of gravity offset data; the pressure center of gravity offset data including the pressure center of gravity offset direction and pressure center of gravity offset amplitude of each wheel; An angle analysis module, configured to adjust and analyze the horizontal axis rotation angle according to the pressure center of gravity offset data to obtain a target horizontal axis rotation angle; a strategy acquisition module, configured to analyze wheel load requirements based on the target transverse axis rotation angle and the terrain pressure distribution data to obtain a wheel pressure adjustment strategy; the wheel pressure adjustment strategy includes a pressure adjustment amount for each wheel and a target ground contact pressure value; The posture leveling module is used to drive the active suspension system to level the vehicle body posture according to the wheel pressure adjustment strategy.

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