Intelligent adjusting automobile chassis and adjusting method thereof

Abstract

The invention discloses an intelligent adjusting automobile chassis and an adjusting method thereof, relates to the field of automobile chassis, and aims to solve the balance problem of automobile stability and riding comfort under different road conditions. The chassis comprises an intelligent suspension module, a road condition sensing module, a core processing module and a separable rod group, the road condition sensing module collects road surface information and vehicle body pose parameters through a laser radar and a pose sensor, the core processing module is internally provided with a road condition recognition algorithm and a chassis adjustment algorithm and processes collected data to generate an adjustment instruction, and the intelligent suspension module responds to the instruction to adjust damping and rigidity. The separable rod set responds to the instruction to adjust the chassis rigidity. The front road condition information is collected through the laser radar, the real-time data of the attitude sensor is combined, the road condition is pre-judged, the chassis parameters are adjusted in advance, the hysteresis quality of passive adjustment of a traditional self-adaptive suspension is avoided, the chassis adjustment accuracy and response speed are improved, and the application range of the self-adaptive suspension is widened. And the driving stability and the riding comfort under complex road conditions are obviously improved.

Description

Technical Field

[0001] This invention relates to the field of automotive chassis technology, and in particular to an intelligent adjustable automotive chassis and its adjustment method. Background Technology

[0002] The chassis is a crucial component of a car, and its performance directly impacts the vehicle's stability, handling, and ride comfort. In traditional car chassis structures, the parameters of the suspension system and stabilizer bars are typically fixed, often requiring compromises between handling and comfort during the design process. For example, on smooth paved roads, a softer suspension setup provides better comfort, but at high speeds or in complex road conditions, it can lead to excessive body roll, affecting handling stability; while a stiffer suspension setup, although improving handling, reduces ride comfort.

[0003] Existing adaptive suspension technologies are mostly passive response adjustments, that is, they adjust suspension parameters after detecting changes in vehicle posture through sensors, resulting in adjustment lag; moreover, the suspension and stabilizer bar work independently and cannot achieve coordinated adaptation according to road conditions, making it difficult to meet the comprehensive performance requirements under complex road conditions. The invention patent application with publication number CN120396587A discloses an integrated electronically controlled automotive chassis suspension control system. This system judges road conditions by sensing the vehicle's motion state and road information, and then adjusts parameters such as stiffness and damping of the automotive chassis suspension. However, this system has the following shortcomings: (1) Low adjustment accuracy: It only collects road elevation data through a laser flatness meter, relies too much on the IRI index to judge flat / unflat road conditions, focuses only on the "physical characteristics of the road surface itself", and does not combine the dynamic state of the vehicle during driving. It has the problem of a single perception dimension, ignoring the dynamic matching relationship between the vehicle and the road surface, and failing to capture the real-time state of the vehicle body. It does not consider the vehicle's body posture, such as roll angle, steering angular velocity, and vibration state of the vehicle body, and cannot capture the "dynamic interaction between the vehicle and the road surface" such as body roll during sharp turns, center of gravity shift during slope driving, and vehicle stability requirements during high-speed driving. This leads to a one-sided judgment of the road surface and a lack of targeted adjustment schemes. (2) Limited stability effect: It only adjusts the stiffness and damping of the suspension to adapt to the road conditions, without setting up a special auxiliary adjustment structure for body roll and torsion, and relies heavily on suspension parameters to achieve comprehensive performance. For sharp turns, complex off-road scenarios, simply adjusting the stiffness and damping of the suspension is not enough to quickly suppress body roll, nor can it flexibly switch the overall stiffness of the chassis according to the road conditions, resulting in limited stability improvement; there is no special stability adjustment structure, no user interaction module, single function, no auxiliary adjustment structure, and it relies solely on suspension parameters, making it difficult to quickly solve stability problems such as body roll. (3) Insufficient adaptability: It only distinguishes between "flat road conditions" and "unflat road conditions". Even when unflat road conditions are further subdivided into "continuous / discontinuous", there are no special adjustment schemes for specific driving scenarios such as highways, potholes, sharp turns, and slopes. The adjustment strategies are based on "road surface smoothness" without designing differentiated solutions based on key parameters such as vehicle speed, steering status, and slope. For example, it is necessary to improve stability on highways and improve comfort on potholes. This may result in insufficient adjustment accuracy and fail to meet the balance between stability and comfort under complex working conditions. (4) Insufficient flexibility: There is no human-computer interaction module. The system only judges the road conditions and adjusts automatically. Users cannot select adjustment strategies according to their own driving needs, such as sport mode and off-road mode, which cannot adapt to the usage scenarios of different users. Summary of the Invention

[0004] The technical problem to be solved by this invention is to provide an intelligent adjustable automobile chassis and its adjustment method, which solves the problem that traditional chassis cannot balance stability and comfort under different road conditions, and achieves chassis parameter adjustment that is precise, flexible and adaptable to a wide range of scenarios.

[0005] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: an intelligent adjustable vehicle chassis, comprising an intelligent suspension module, a road condition sensing module, a core processing module, and a separable linkage; the intelligent suspension module is symmetrically arranged at the four corners of the vehicle chassis and is used to adjust the damping and stiffness of the vehicle suspension; the road condition sensing module is used to collect road surface information and vehicle position parameters in real time; the core processing module is signal-connected to the intelligent suspension module, the road condition sensing module, and the separable linkage, respectively, and is used to receive and process the data collected by the road condition sensing module to generate corresponding adjustment commands; the separable linkage is used to respond to the commands of the core processing module and adjust the stiffness of the vehicle chassis.

[0006] A further technical solution of the present invention is that the intelligent suspension module includes a magnetorheological damper and an air spring. The magnetorheological damper completes the adjustment of the damping coefficient within milliseconds. One end of the air spring is connected to the bottom of the vehicle body, and the other end is connected to an air source device, which is controlled by the core processing module.

[0007] A further technical solution of the present invention is that the air spring satisfies the polytropic gas equation P0V0. k =P e V e k and the ideal gas law P e V e =mRT e The suspension height and stiffness are adjusted by changing the inflation volume; where P0 is the absolute pressure inside the air spring in a stationary state, V0 is the volume of the air spring bladder in a stationary state, and P... e V is the absolute pressure inside the air spring at any given time. e Let T be the internal volume of the air spring airbag at any given time, and k be the gas polytropic index, which is taken as 1.0 during the positioning process; e Let be the temperature of the gas inside the airbag, m be the mass of the gas, and R be the ideal gas constant.

[0008] A further technical solution of the present invention is that the road condition sensing module includes a lidar and a pose sensor. The lidar is installed in the middle of the chassis and is used to scan the road surface in front in real time to collect information on road slope, undulation, potholes and obstacles. The pose sensor is fixed at the center of gravity of the chassis and is used to detect the vehicle body pose parameters. Both the lidar and the pose sensor are connected to the signal input terminal of the core processing module to transmit the collected data in real time.

[0009] A further technical solution of the present invention is that the separable linkage group includes a front linkage group and a rear linkage group. The front linkage group is installed laterally on both sides of the front axle and connected to the left front and right front suspensions at both ends. The rear linkage group is installed laterally on both sides of the rear axle and connected to the left rear and right rear suspensions at both ends. Both linkage groups are segmented structures, with the middle section connected by an electromagnetic clutch. The electromagnetic clutch is connected to the signal output terminal of the core processing module and is used to receive stiffness adjustment commands and control the engagement or disengagement of the linkage group.

[0010] A further technical solution of the present invention is that the core processing module is installed on the chassis crossbeam at the bottom of the vehicle body near the driver's cabin, and is wrapped with a waterproof sealed shell. Its signal input end is connected to the road condition sensing module, and its signal output end is connected to the intelligent suspension module and the detachable rod group. The core processing module adopts a high-performance microprocessor and has built-in road condition recognition algorithm and chassis adjustment algorithm.

[0011] A further technical solution of the present invention is that the intelligent adjustable car chassis also includes a human-machine interaction module, which is signal-connected to the core processing module and is used for users to independently select the chassis adjustment mode.

[0012] Another technical solution of the present invention is an intelligent adjustment method for a car chassis. The method involves: in intelligent adjustment mode, a road condition sensing module continuously collects data; a lidar scans the road surface ahead and identifies the road type, slope, and obstacle information; a posture sensor detects the vehicle body roll angle parameters; after receiving the data, the core processing module uses a road condition recognition algorithm combined with the user-selected mode or default mode to determine whether the current road condition is smooth; if the road condition is smooth, no additional adjustment is needed; if the road condition is complex, the core processing module uses a chassis adjustment algorithm to calculate the damping coefficient of the shock absorbers and the air spring inflation volume, and controls the on / off state of the electromagnetic clutch; the intelligent suspension module and the separable linkage respond to commands to perform adjustments, while the core processing module compares the performance before and after adjustment, corrects the adjustment strategy, and continuously detects and adjusts until the vehicle is turned off.

[0013] A further technical solution of the present invention is that, in the case of complex road conditions, the core processing module calculates the damping coefficient of the shock absorber and the air spring inflation amount through a chassis adjustment algorithm, and controls the on / off state of the electromagnetic clutch, specifically including: ① High-speed adjustment: Determine whether the driving speed is >100km / h and the steering angular velocity ω is ≤3rad / s; if not, no adjustment is needed; if so, reduce the air spring inflation, increase the damping coefficient of the magnetorheological damper, and combine with the electromagnetic clutch to improve the chassis rigidity and stability. ② Adjustment for uneven road surfaces: Determine whether the wheel vibration amplitude A is 15-30mm or the vibration frequency f is 8-15Hz, and whether the density of potholes identified by the lidar is >2 potholes / m. If not, no adjustment is needed. If so, increase the air spring inflation, lower the damping coefficient of the magnetorheological shock absorber, and disengage the electromagnetic clutch to improve comfort. ③ Sharp turn adjustment: Determine whether the steering angular velocity ω is 5~15rad / s or the body roll angle φ is 3°~8°. If not, no adjustment is needed. If so, increase the damping coefficient of the inner and outer shock absorbers, and make the inner damping coefficient less than the outer one. Combine with the electromagnetic clutch to suppress body roll. ④ Slope Adjustment: Determine if the slope θ detected by the lidar is between 5° and 15°. If not, no adjustment is needed. If so, increase the air spring inflation and, in conjunction with the electromagnetic clutch, increase the damping coefficient to improve slope driving stability.

[0014] A further technical solution of the present invention is that, before the intelligent adjustment mode begins, the system performs an initialization test after startup. If the test passes, the system enters the intelligent adjustment mode; if the test fails, a fault warning is issued and the system exits the intelligent adjustment mode.

[0015] By adopting the above technical solution, the intelligent adjustable automobile chassis and its adjustment method of the present invention have the following beneficial effects compared with the prior art: 1. This invention uses lidar to collect road condition information in advance, and combines it with real-time data from attitude sensors. The core processing module can predict road conditions and adjust chassis parameters in advance, avoiding the lag of passive adjustment in traditional adaptive suspension, and greatly improving the accuracy and response speed of chassis adjustment.

[0016] 2. The intelligent suspension module of the present invention combines a magnetorheological damper and an air spring, which can simultaneously adjust damping and stiffness. The detachable rod assembly controls the stiffness switching through an electromagnetic clutch. The two work together to balance stability and comfort under different road conditions.

[0017] 3. The core processing module of this invention has a built-in dedicated algorithm to realize multi-sensor data fusion processing, with precise adjustment strategies, and adaptable to various complex road conditions such as highways, potholes, slopes, and sharp turns.

[0018] 4. This invention has human-computer interaction function, and users can select adjustment mode according to their needs, which is highly flexible and adaptable to different usage scenarios.

[0019] The technical features of an intelligent adjustable automobile chassis and its adjustment method according to the present invention will be further described below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0020] Figure 1A schematic diagram of the module connections for intelligent adjustment of the car chassis; Figure 2 A schematic diagram showing the installation position of the intelligent adjustable car chassis; Figure 3 This is a flowchart of the intelligent adjustment method for the automobile chassis described in Example 2; Figures 4-7 Example 2: Flowcharts for adjusting various complex road conditions, wherein: Figure 4 High-speed adjustment flowchart; Figure 5 Flowchart for adjusting potholes in road surfaces; Figure 6 : Flowchart of sharp turn adjustment; Figure 7 Flowchart of ramp adjustment; In the diagram, 1-intelligent suspension module, 2-LiDAR, 3-pose sensor, 4-detachable linkage. 5 - Core processing module, 6 - Front axle. Detailed Implementation Example 1

[0021] An intelligent adjustable car chassis includes an intelligent suspension module 1, a road condition sensing module, a core processing module 5, a detachable linkage 4, and a human-machine interaction module; wherein: The intelligent suspension module 1 is symmetrically positioned at the four corners of the vehicle chassis, above the left front, left rear, right front, and right rear wheels, and is used to adjust the damping and stiffness of the vehicle suspension. This intelligent suspension module includes a magnetorheological damper and an air spring. The magnetorheological damper adjusts the damping coefficient within milliseconds, exhibiting fast response and a wide adjustment range. One end of the air spring is connected to the bottom of the vehicle body, and the other end is connected to an air source device controlled by the core processing module. The air spring satisfies the polytropic gas equation P0V0. k =P e V e k and the ideal gas law P e V e =mRT e The suspension height and stiffness are adjusted by changing the inflation volume; where P0 is the absolute pressure inside the air spring in a stationary state, V0 is the volume of the air spring bladder in a stationary state, and P... e V is the absolute pressure inside the air spring at any given time. e Let T be the internal volume of the air spring airbag at any given time, and k be the gas polytropic index, which is taken as 1.0 during the positioning process; e Let be the temperature of the gas inside the airbag, m be the mass of the gas, and R be the ideal gas constant.

[0022] The road condition sensing module is used to collect road surface information and vehicle posture parameters in real time. The module includes a lidar 2 and a posture sensor 3. The lidar 2 is installed in the center of the chassis and is used to scan the road surface in real time, collecting information on road slope, undulations, potholes, and obstacles. The posture sensor 3 is fixed at the center of gravity of the chassis and is used to detect the vehicle's posture parameters. Both the lidar and the posture sensor are connected to the signal input terminal of the core processing module via signal wires to transmit the collected data in real time. The center of gravity of the vehicle chassis can be determined with reference to the following formula: Let a represent the distance from the center of gravity to the front axle and b represent the distance from the center of gravity to the rear axle, and let a + b = L. The distance 'a' from the center of gravity to the front axle can be calculated using the following formula: a=(W r .L) / W in: W r L represents the rear axle load (the load on the rear bearing), and L represents the wheelbase (the distance from the center of the front axle to the center of the rear axle). W represents the weight of the entire vehicle (whether it is unloaded, half-loaded, or fully loaded). Ensure a + b = L, where b = (W f .L) / W W f This is the front axle load.

[0023] The core processing module 5 is connected to the intelligent suspension module, the road condition sensing module, and the detachable linkage, respectively. It receives and processes data collected by the road condition sensing module to generate corresponding adjustment commands. The detachable linkage responds to the commands from the core processing module to adjust the stiffness of the vehicle chassis. The core processing module is mounted on the chassis crossbeam near the driver's cabin at the bottom of the vehicle body, encased in a waterproof sealed shell. Its signal input is connected to the road condition sensing module, and its signal output is connected to the intelligent suspension module and the detachable linkage. The core processing module uses a high-performance microprocessor with built-in road condition recognition and chassis adjustment algorithms. Both the road condition recognition and chassis adjustment algorithms are existing technologies. The road condition recognition algorithm primarily achieves accurate classification of flat road conditions, highway conditions, potholes, sharp turns, and slopes through multi-sensor data fusion, providing a basis for subsequent adjustment strategies.

[0024] The lidar system collects three-dimensional road surface data, such as slope, pothole density, and obstacle distance. It uses a set scanning frequency of 50-500Hz and a laser emission frequency of 5000-2000000Hz to collect three-dimensional point cloud data of the road surface, obtaining the three-dimensional coordinates (X, Y, Z), acquisition time (T), and reflection intensity (I) for each laser point. The three-dimensional coordinates (X, Y, Z) represent the spatial position of each scan point, the acquisition time (T) records the time it takes for the laser pulse to return to the system, and the reflection intensity (I) is the sensor's output value of the received laser reflection energy. The lidar is installed in the center of the chassis, and its scanning plane covers the road surface within 100m in front, with a scanning angle range of [-90º, 90º] to ensure coverage of the wheel trajectory area. A two-dimensional index Tgrid sequential structure is constructed to organize the point cloud, assigning a two-dimensional index G(i,j) to each laser point, corresponding to the j-th point on the i-th scan line, to quickly establish the adjacency relationship of the point cloud.

[0025] Slope detection algorithm: i = (h / B) × 100%, Where i is the cross slope, h is the elevation difference between the two boundaries on the cross section, and B is the road width, which can be calculated from the planar coordinates of the two endpoints.

[0026] i p =(△Z / △L)×100% Where i p The slope is denoted as ΔZ and ΔL, which represent the elevation difference and distance between two endpoints on the same road segment, respectively. The basic steps are: (1) extract the road surface point cloud and fit the local plane; (2) generate the longitudinal profile along the driving direction and the cross profile in the vertical direction; (3) use the least squares method to fit the cross-sectional line and calculate the slope value.

[0027] Pothole / uneven road surface algorithm:

[0028] h(i,j) represents the height difference, -h d Represents the maximum possible depth of cracks and potholes, and gradf(i,j) represents the average slope value with (i,j) as the center node. th δ represents the minimum gradient change requirement for candidate points. R51 Let be the height variance, k be the number of neighboring points in the neighborhood of the node centered at (i,j), and gradient(i,j,m) be the slope from the m-th neighboring point to the center point (i,j). ΔI represents the intensity contrast, and F... BThe maximum proportion of cracks and potholes. The process is as follows: (1) Calculate the local road surface plane based on the Tgrid structure and fit it with robust least squares; (2) Calculate the height difference h between each point cloud and the local plane; (3) Extract the point cloud with the height difference less than the pothole depth threshold of -0.02m; (4) Calculate the pothole density.

[0029] Main tests: (1) below the low point of the road surface; (2) not higher than the low intensity point of the road surface.

[0030] Road surface smoothness algorithm:

[0031] n is the number of sampling points within the reference length, h i The International Roughness Index (IRI) formula is used to calculate the elevation deviation:

[0032] Where L is the length of the scanned road segment, N is the number of measurement points, and Z... i The elevation of the i-th measurement point is obtained by discretization. The process is as follows: (1) Extract the wheel track point cloud from the lidar point cloud; (2) Resample the longitudinal profile elevation at a sampling interval of 0.25m; (3) Calculate σ and IRI values ​​to quantify the degree of road surface undulation.

[0033] Road obstacle detection algorithm: Distinguish between the reflection intensity of obstacles, such as metal and stone with a reflection intensity I>200 and the road surface intensity (I=50-150).

[0034] The chassis adjustment algorithm calculates the optimal damping coefficient of the magnetorheological dampers and the air spring inflation based on road condition recognition results and the user-selected adjustment mode, and controls the on / off state of the electromagnetic clutch to achieve a dynamic balance between stability and comfort. Parameters such as steering angular velocity ω, body roll angle φ, wheel vibration amplitude A, and vibration frequency f are extracted from position sensors around the vehicle.

[0035] For the high-speed adjustment algorithm (speed > 100 km / h, ω ≤ 3 rad / s), it is achieved by adjusting the damping coefficient of the magnetorheological damper and the air volume of the air spring:

[0036] Pothole adjustment algorithm (A=15-30mm or f=8-15Hz, D>2 potholes / m):

[0037] Where r k It is the stiffness ratio, r mλ is the mass ratio, Ψ is the frequency ratio, Ψ is the ratio of inertia coefficient to spring stiffness, ξ is the suspension system damping ratio, ω is the natural angular frequency of the vehicle body, and j is a complex variable. H(jω) is the displacement frequency response function of the vehicle body to the road surface, representing the adjustment relationship between vehicle vibration and suspension damping.

[0038] Sharp turn adjustment algorithm (ω=5-15rad / s or φ=3-8°):

[0039] Where β is the sideslip angle, θ is the turning angle, V is the vehicle speed, and G... y ω is the lateral acceleration, ω is the actual yaw rate, and x and y are the displacement components of the vehicle along the x and y axes, respectively.

[0040] Slope adjustment algorithm (slope θ = 5°-15°):

[0041] Where k is the adjustment stiffness, S is the safety factor, m is the total mass of the vehicle under full load, and Z... 均 Let g be the average elevation, and g be the acceleration due to gravity, taken as g = 9.8 m / s². 2 sinθ is the vertical component of gravity.

[0042] The car's suspension model is as follows: M1ẍ1 + c1(ẋ1-ẋ2) + k1(x1-x2) = 0 M2ẍ2 + c1(ẋ2-ẋ1) + k1(x2-x1) + k2x2 = k2q In the formula, M1 is the spring mass, M2 is the non-spring mass, x1 is the spring displacement, x2 is the non-spring displacement, k1 is the suspension stiffness, k2 is the tire stiffness, c1 is the suspension damping, and q is the road surface unevenness input.

[0043] Combining the air spring model with the ideal gas law and applying the first law of thermodynamics, we get:

[0044] T e q represents the temperature of the gas inside the airbag. m Let R be the mass flow rate, and R be the ideal gas constant, R = 8.314 Pa·L·mol. -1 K -1 ,

[0045] A e Z represents the effective bearing area of ​​the air spring, and z1 and z2 represent the displacements of the sprung mass and unsprung mass, respectively.

[0046] The damping coefficient adjustment model for magnetorheological dampers is as follows:

[0047] F is the output damping force, Fy is the Coulomb damping force, which is related to the magnetic field strength, c is the damping coefficient, v is the speed of the damper piston or cylinder, sgn(x) is the sign function, and f is the force generated by the compensator, which can be ignored.

[0048] The separable linkage 4 includes a front linkage and a rear linkage. The front linkage is installed laterally on both sides of the front axle, connecting to the left front and right front suspensions at both ends. The rear linkage is installed laterally on both sides of the rear axle, connecting to the left rear and right rear suspensions at both ends. Both the front and rear linkages are segmented structures. The two segments of the front linkage are connected by an electromagnetic clutch, and similarly, the two segments of the rear linkage are also connected by an electromagnetic clutch. The electromagnetic clutch is connected to the signal output terminal of the core processing module to receive stiffness adjustment commands. It is disengaged when the road surface is flat to reduce stiffness and improve comfort, and engaged when the road conditions are complex to increase stiffness and enhance stability.

[0049] The human-machine interaction module is connected to the core processing module. Users can select chassis adjustment modes such as sport mode and off-road mode through the vehicle display screen or steering wheel buttons. The core processing module adjusts the adjustment strategy according to the mode selected by the user.

[0050] Example 2

[0051] An adjustment method for intelligently adjusting a car chassis as described in Embodiment 1: After the system is started, an initialization test is performed first. If the test passes, the system enters the intelligent adjustment mode; if the test fails, a fault warning is issued and the system exits the intelligent adjustment mode.

[0052] In intelligent adjustment mode, the road condition sensing module continuously collects data: the lidar scans the road surface ahead and identifies the road type, slope, and obstacle information; the posture sensor detects the vehicle body roll angle parameters. After receiving the data, the core processing module uses a road condition recognition algorithm combined with the user-selected mode or the default mode to determine whether the current road condition is smooth. If the road condition is smooth, no additional adjustment is required. If the road condition is complex, the core processing module uses a chassis adjustment algorithm to calculate the damping coefficient of the shock absorbers and the air spring inflation volume, and controls the on / off state of the electromagnetic clutch. The intelligent suspension module and the separable linkage respond to commands to execute adjustments. At the same time, the core processing module compares the performance before and after adjustment, corrects the adjustment strategy, and continuously detects and adjusts until the vehicle is turned off.

[0053] In the case of complex road conditions, the core processing module calculates the damping coefficient of the shock absorbers and the air spring inflation amount through a chassis adjustment algorithm, and controls the on / off state of the electromagnetic clutch, specifically including: ① High-speed adjustment: Determine whether the driving speed is >100km / h and the steering angular velocity ω is ≤3rad / s; if not, no adjustment is needed; if so, reduce the air spring inflation, increase the damping coefficient of the magnetorheological damper, and combine with the electromagnetic clutch to improve the chassis rigidity and stability. ② Adjustment for uneven road surfaces: Determine whether the wheel vibration amplitude A is 15-30mm or the vibration frequency f is 8-15Hz, and whether the density of potholes identified by the lidar is >2 potholes / m. If not, no adjustment is needed. If so, increase the air spring inflation, lower the damping coefficient of the magnetorheological shock absorber, and disengage the electromagnetic clutch to improve comfort. ③ Sharp turn adjustment: Determine whether the steering angular velocity ω is 5~15rad / s or the body roll angle φ is 3°~8°. If not, no adjustment is needed. If so, increase the damping coefficient of the inner and outer shock absorbers, and make the inner damping coefficient less than the outer one. Combine with the electromagnetic clutch to suppress body roll. ④ Slope Adjustment: Determine if the slope θ detected by the lidar is between 5° and 15°. If not, no adjustment is needed. If so, increase the air spring inflation and, in conjunction with the electromagnetic clutch, increase the damping coefficient to improve slope driving stability.

Claims

1. An intelligent adjustable automobile chassis, characterized in that, The system includes an intelligent suspension module, a road condition sensing module, a core processing module, and a detachable linkage. The intelligent suspension module is symmetrically positioned at the four corners of the vehicle chassis and is used to adjust the damping and stiffness of the vehicle suspension. The road condition sensing module is used to collect road surface information and vehicle position parameters in real time. The core processing module is connected to the intelligent suspension module, the road condition sensing module, and the detachable linkage, respectively, and is used to receive and process the data collected by the road condition sensing module to generate corresponding adjustment commands. The detachable linkage is used to respond to the commands of the core processing module and adjust the stiffness of the vehicle chassis.

2. The intelligent adjustable automobile chassis according to claim 1, characterized in that, The intelligent suspension module includes a magnetorheological damper and an air spring. The magnetorheological damper adjusts the damping coefficient in milliseconds. One end of the air spring is connected to the bottom of the vehicle body, and the other end is connected to an air source device, which is controlled by the core processing module.

3. The intelligent adjustable automobile chassis according to claim 2, characterized in that, The air spring satisfies the polytropic equation P0V0. k =P e V e k and the ideal gas law P e V e =mRT e The height and stiffness of the suspension can be adjusted by changing the inflation volume; Where P0 is the absolute pressure inside the air spring in a stationary state, V0 is the volume of the air spring bladder when stationary, and P e V is the absolute pressure inside the air spring at any given time. e Let T be the internal volume of the air spring airbag at any given time, and k be the gas polytropic index, which is taken as 1.0 during the positioning process; e Let be the temperature of the gas inside the airbag, m be the mass of the gas, and R be the ideal gas constant.

4. The intelligent adjustable automobile chassis according to claim 1, characterized in that, The road condition sensing module includes a lidar and a pose sensor. The lidar is installed in the middle of the chassis and is used to scan the road surface in real time to collect information on road slope, undulation, potholes and obstacles. The pose sensor is fixed at the center of gravity of the chassis and is used to detect the vehicle's pose parameters. Both the lidar and the pose sensor are connected to the signal input terminal of the core processing module to transmit the collected data in real time.

5. The intelligent adjustable automobile chassis according to claim 1, characterized in that, The separable linkage assembly includes a front linkage assembly and a rear linkage assembly. The front linkage assembly is installed laterally on both sides of the front axle, with its two ends connected to the left front and right front suspensions. The rear linkage assembly is installed laterally on both sides of the rear axle, with its two ends connected to the left rear and right rear suspensions. Both linkage assemblies are segmented structures, with the middle section connected by an electromagnetic clutch. The electromagnetic clutch is connected to the signal output terminal of the core processing module and is used to receive stiffness adjustment commands and control the engagement or disengagement of the linkage assembly.

6. The intelligent adjustable automobile chassis according to claim 1, characterized in that, The core processing module is installed on the chassis crossbeam at the bottom of the vehicle body near the driver's cabin, and is encased in a waterproof and sealed shell. Its signal input end is connected to the road condition sensing module, and its signal output end is connected to the intelligent suspension module and the detachable linkage. The core processing module uses a high-performance microprocessor and has built-in road condition recognition algorithm and chassis adjustment algorithm.

7. The intelligent adjustable automobile chassis according to claim 1, characterized in that, The intelligent adjustable car chassis also includes a human-machine interaction module, which is signal-connected to the core processing module and is used by the user to independently select the chassis adjustment mode.

8. A method for adjusting an intelligent vehicle chassis according to any one of claims 1 to 7, characterized in that, The method is as follows: In intelligent adjustment mode, the road condition sensing module continuously collects data: the lidar scans the road surface ahead and identifies the road surface type, slope, and obstacle information, and the posture sensor detects the vehicle body tilt angle parameters; after receiving the data, the core processing module uses the road condition recognition algorithm combined with the user-selected mode or the default mode to determine whether the current road condition is smooth; if the road condition is smooth, no additional adjustment is required. In the case of complex road conditions, the core processing module calculates the damping coefficient of the shock absorber and the air volume of the air spring through the chassis adjustment algorithm, and controls the on and off of the electromagnetic clutch. The intelligent suspension module and detachable linkage respond to commands and perform adjustments. Meanwhile, the core processing module compares the performance before and after adjustment, corrects the adjustment strategy, and continuously detects and adjusts until the vehicle is turned off.

9. The method for adjusting an intelligent vehicle chassis according to claim 8, characterized in that, In the case of complex road conditions, the core processing module calculates the damping coefficient of the shock absorbers and the air spring inflation amount through a chassis adjustment algorithm, and controls the on / off state of the electromagnetic clutch, specifically including: ① High-speed adjustment: Determine whether the driving speed is >100km / h and the steering angular velocity ω is ≤3rad / s; if not, no adjustment is needed; if so, reduce the air spring inflation, increase the damping coefficient of the magnetorheological damper, and combine with the electromagnetic clutch to improve the chassis rigidity and stability. ② Adjustment for uneven road surfaces: Determine whether the wheel vibration amplitude A is 15-30mm or the vibration frequency f is 8-15Hz, and whether the density of potholes identified by the lidar is >2 potholes / m. If not, no adjustment is needed. If so, increase the air spring inflation, lower the damping coefficient of the magnetorheological shock absorber, and disengage the electromagnetic clutch to improve comfort. ③ Sharp turn adjustment: Determine whether the steering angular velocity ω is 5~15rad / s or the body roll angle φ is 3°~8°. If not, no adjustment is needed. If so, increase the damping coefficient of the inner and outer shock absorbers, and make the inner damping coefficient less than the outer one. Combine with the electromagnetic clutch to suppress body roll. ④ Slope Adjustment: Determine if the slope θ detected by the lidar is between 5° and 15°. If not, no adjustment is needed. If so, increase the air spring inflation and, in conjunction with the electromagnetic clutch, increase the damping coefficient to improve slope driving stability.

10. The intelligent adjustment method for a car chassis according to claim 9, characterized in that, Before starting the intelligent adjustment mode, the system performs an initialization test after startup. If the test passes, it enters the intelligent adjustment mode; if the test fails, a fault warning is issued and the system exits the intelligent adjustment mode.

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