A method for active suspension control of automobiles

Abstract

This invention discloses an active suspension control method for automobiles, comprising a sensor data acquisition unit, a road condition perception unit, a mode switching control unit, an expert data calibration unit, a closed-loop control force correction unit, and an active suspension control unit. The sensor data acquisition unit collects vehicle data; the road condition perception unit determines the vehicle's driving conditions, including but not limited to bumpy roads, icy or muddy roads, sloping roads, curved roads, and level roads; the mode switching control unit adopts different perception modes according to different driving conditions, including strong perception mode, medium perception mode, and weak perception mode; the expert data calibration unit integrates an expert database through simulation, real-vehicle calibration, and empirical analysis; the closed-loop correction force correction unit constructs a closed-loop correction function to correct the active suspension control force; and the active suspension control unit controls chassis height adjustment to achieve vehicle posture adjustment.

Description

Technical Field

[0001] This invention relates to an active suspension control method for automobiles. Background Technology

[0002] Vehicles are becoming increasingly intelligent, leading to the emergence of driverless cars. In developing ADAS and AD functions for driverless cars, to ensure safety and reliability, the development of these functions has largely focused on environmental perception, path planning, and decision-making control, without considering active suspension control technology under autonomous driving conditions. Therefore, how to effectively ensure the vehicle's level under different road conditions and improve its ride comfort has become a pressing technical problem for the applicant. To address these issues, this invention proposes an active suspension control method for automobiles. Summary of the Invention

[0003] The purpose of this invention is to provide an active suspension control method for automobiles to solve the problems encountered in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: an active suspension control method for automobiles, comprising a sensor data acquisition unit, a road condition perception unit, a mode switching control unit, an expert data calibration unit, a closed-loop control force correction unit, and an active suspension control unit.

[0005] The sensor data acquisition unit includes a center of gravity sideslip angle sensor, a vehicle roll angle sensor, a vehicle vertical acceleration sensor, a vehicle pitch angle sensor, a driver's cab camera, a vehicle speed sensor, a vehicle height sensor, and a front wheel steering angle measurement system; these are used to acquire the center of gravity sideslip angle, vehicle roll angle, vehicle vertical acceleration, vehicle pitch angle, driver yaw distance, vehicle longitudinal speed, suspension height change, and front wheel steering angle, respectively; based on the acquired data, a bump factor is designed to evaluate the overall performance of the bumpiness of bumpy roads; a turning factor is introduced to evaluate the rollover risk and rollover severity when the vehicle is turning;

[0006] The road condition perception unit includes a map, navigation, camera, road condition database, and road surface condition monitor. The navigation and map are used to obtain the current vehicle position. The camera is used to acquire information about obstacles in front of, behind, and to the sides of the vehicle, road slope, and surface unevenness. The road condition database, based on the current vehicle position, obstacles, road slope, surface unevenness, and an offline road database, determines road conditions, including but not limited to bumpy roads, icy / muddy roads, sloping roads, curved roads, and level roads. The road surface condition monitor includes a front-end signal acquisition core sensor, a host acquisition system, a wireless network, and a server. It is used to monitor real-time changes in road surface water accumulation, snow thickness, rainfall / snowfall, and wet / dry conditions, and to acquire road viscosity factors and road humidity coefficients. Cluster analysis is used to analyze different icy / muddy road surface conditions, and then an environmental humidity coefficient is set.

[0007] The mode switching control unit includes a strong perception mode, a medium perception mode, and a weak perception mode. Different perception modes are adopted according to the identification of different road conditions. The number and types of vehicle state parameters acquired by different perception modes are different.

[0008] The expert data calibration unit includes simulating, calibrating, and analyzing 100 different bumpy road conditions for various custom-type vehicles to form the active suspension control force output of the vehicle at different speeds and road conditions, and integrating an expert database.

[0009] The closed-loop control force correction unit includes constructing a closed-loop correction function using the center of gravity sideslip angle, vehicle roll angle, vehicle vertical acceleration, and vehicle pitch angle obtained by the sensor data acquisition unit, to obtain the correction force for different customized vehicle models, and then correct the active suspension control force.

[0010] The active suspension control unit includes a pressure sensor, a height sensor, an air spring, a continuously adjustable damper, a solenoid valve, an air pump, an air tank, and an electronic control unit.

[0011] The road condition sensing unit determines that the road condition on which the vehicle is traveling is a bumpy road surface.

[0012] When the operating condition is a bumpy road surface, the mode switching control unit adopts a strong sensing mode, and the centroid sideslip angle sensor in the sensing data acquisition unit acquires the centroid sideslip angle β, with a weighting coefficient. The value range is from 0 to 1. A smaller value indicates less lateral deviation of the vehicle during movement and better handling stability. This indicates that the centroid side deflection angle is 0°. A larger value indicates a greater degree of lateral deviation during vehicle movement and poorer handling stability. The time indicates that the centroid side slip angle is 90°;

[0013] Calculate the root mean square value of the centroid sideslip angle using the following formula:

[0014]

[0015] Where: β t Let be the centroid sideslip angle collected at time t;

[0016] N1 is the number of samples for the centroid sideslip angle, N1 = T / ns1;

[0017] T represents the time period;

[0018] ns1 is the acquisition period of the centroid side deflection angle signal;

[0019] The vehicle roll angle sensor in the sensing data acquisition unit acquires the vehicle roll angle. Weighting coefficient The value range is from 0 to 1. A smaller value indicates less body roll during vehicle movement and a lower probability of rollover. This indicates that the vehicle body roll angle is 0°. The larger the value, the greater the degree of body roll during movement, and the higher the probability of the vehicle rolling over. The time indicates that the vehicle body roll angle is 90°;

[0020] Calculate the root mean square value of the vehicle body roll angle using the following formula:

[0021]

[0022] in: Let be the vehicle roll angle collected at time t;

[0023] N2 is the number of vehicle roll angle samples, N2 = T / ns2;

[0024] T represents the time period;

[0025] ns2 is the vehicle body roll angle signal acquisition cycle;

[0026] The vehicle vertical acceleration sensor in the sensing data acquisition unit acquires the vehicle vertical acceleration a. z Weighting coefficient The value range is from 0 to 1. A smaller value indicates less vertical vibration during vehicle movement, a lower probability of wheels leaving the ground, and better ride comfort. This indicates that the vehicle is not experiencing vertical vibration; A larger value indicates greater vertical vibration during vehicle movement, a higher probability of wheels leaving the ground, and poorer ride comfort. This indicates that the wheel has left the ground;

[0027] Calculate the root mean square value of the vehicle's vertical acceleration using the following formula:

[0028]

[0029] Where: a zt Let be the vertical acceleration of the vehicle body collected at time t;

[0030] N3 is the number of vertical acceleration samples of the vehicle body, N3 = T / ns3;

[0031] T represents the time period;

[0032] ns3 is the acquisition period for the vehicle's vertical acceleration signal;

[0033] The vehicle pitch angle sensor in the sensing data acquisition unit acquires the vehicle pitch angle θ, with weighting coefficients. The value range is from 0 to 1. A smaller value indicates less pitch during vehicle movement and a smaller difference in height between the front and rear suspensions. A time of 0 indicates that the vehicle is traveling smoothly; A larger value indicates a greater degree of pitch during vehicle movement, and a larger difference in height between the front and rear suspensions. This indicates that the vehicle has overturned, either upside down or face down.

[0034] Calculate the root mean square value of the vehicle pitch angle using the following formula:

[0035]

[0036] Where: θ t Let be the vehicle pitch angle collected at time t;

[0037] N4 is the number of vehicle pitch angle samples, N4 = T / ns4;

[0038] T represents the time period;

[0039] ns4 is the vehicle pitch angle signal acquisition cycle;

[0040] The driver's cab camera in the sensor data acquisition unit acquires the driver's circumference distance s and circumference weight coefficient. The value ranges from 0 to 1. When a driver is driving on a bumpy road, the bumps will cause the driver to sway in the front, back, left and right directions. The smaller the sway amplitude and the smaller the circumferential distance, the less the road bumps will affect the driver; the larger the sway amplitude and the larger the circumferential distance, the greater the impact of the road bumps on the driver.

[0041] The root mean square value of the driver's circumference distance is calculated using the following formula:

[0042]

[0043] Where: s t The distance of the driver's circumference collected at time t;

[0044] N5 is the number of driver's circumferential distance samples, N5 = T / ns5;

[0045] T represents the time period;

[0046] ns5 is the acquisition period for the driver's swivel distance signal;

[0047] Design a comprehensive performance index function to evaluate the degree of bumpiness on bumpy roads:

[0048] Convert it into matrix form as follows:

[0049]

[0050]

[0051] In the formula, ρ is the turbulence factor, and Q... e Here is the parameter weight correction matrix, where It is 1×1 Gaussian white noise.

[0052] Because the performance requirements for different vehicle types vary on the same road surface, vehicle types are categorized into Type A, Type B, and Type C vehicles. Type A vehicles are small cars with a wheelbase less than 2700mm, Type B vehicles are mid-size cars with a wheelbase between 2700 and 2850mm, and Type C vehicles are large cars with a wheelbase greater than 2850mm; hereinafter referred to as Type i vehicles, where i can take the values ​​A, B, or C.

[0053] For type A vehicles, the preset bump factor range is [ρ Amin ,ρ Amax When ρ < ρ Amin At that time, the vehicle was deemed to be in a low-risk bumpy zone; when ρ Amin ≤ρ≤ρ Amax When the vehicle speed is below 65 km / h, it is considered to be in the low-risk bumpy zone; when the vehicle speed is above 65 km / h but below 70 km / h, it is considered to be in the medium-risk bumpy zone; and when the vehicle speed is above 70 km / h, it is considered to be in the high-risk bumpy zone. When ρ > ρ Amax At that time, the vehicle was determined to be in a high-risk, bumpy zone;

[0054] For Type B vehicles, the preset bump factor range is [ρ Bmin ,ρ Bmax When ρ < ρ BminAt that time, the vehicle was deemed to be in a low-risk bumpy zone; when ρ Bmin ≤ρ≤ρ Bmax When the vehicle speed is below 55 km / h, it is considered to be in the low-risk bumpy zone; when the vehicle speed is above 55 km / h but below 60 km / h, it is considered to be in the medium-risk bumpy zone; and when the vehicle speed is above 60 km / h, it is considered to be in the high-risk bumpy zone. When ρ > ρ Bmax At that time, the vehicle was determined to be in a high-risk, bumpy zone;

[0055] For Type C vehicles, the preset bump factor range is [ρ Cmin ,ρ Cmax When ρ < ρ Cmin At that time, the vehicle was deemed to be in a low-risk bumpy zone; when ρ Cmin ≤ρ≤ρ Cmax When the vehicle speed is below 45 km / h, it is considered to be in the low-risk bumpy zone; when the vehicle speed is above 45 km / h but below 50 km / h, it is considered to be in the medium-risk bumpy zone; and when the vehicle speed is above 50 km / h, it is considered to be in the high-risk bumpy zone. When ρ > ρ Cmax At that time, the vehicle was deemed to be in a high-risk, bumpy zone.

[0056] The expert data calibration unit includes the following steps:

[0057] Step 1: Select 100 different bumpy road conditions for different types of vehicles to conduct simulation, real vehicle calibration and experience analysis, form the active suspension control force output of the i-type vehicle under different vehicle speeds and different road conditions, and form an expert database;

[0058] Step 2: Based on the different bump risk ranges and vehicle speeds of the different vehicle models, by comparing with the expert database, the required active suspension control force for the four wheels on both sides of the i-type vehicle can be obtained as [F]. iFL F iFR F iRL F iRR ];

[0059] Among them, F iFL For the active suspension control force of the left front wheel of the i-type vehicle, F iFR For the active suspension control force of the right front wheel of the i-type vehicle, F iRL For the active suspension control force of the left rear wheel of the i-type vehicle, F iRR The active suspension control force for the right rear wheel of the i-type vehicle.

[0060] The closed-loop control force correction unit is used to correct the active suspension control forces of the four wheels in the above scheme; for the control forces based on the center of gravity sideslip angle β and the vehicle roll angle... Vertical acceleration a of the vehicle body zConstructing the closed-loop correction function for the i-type vehicle using the vehicle body pitch angle θ Calculate the closed-loop correction force F of the type i vehicle ib =k i f i , where k i The coefficients of the closed-loop correction function for type i vehicle are given, with the constraint 0 < k. i ≤1; Optimal active suspension control force output for type i vehicles:

[0061] Among them, F iZFL For the optimal active suspension output control force of the left front wheel of the i-type vehicle, F iZFR For the optimal active suspension output control force of the right front wheel of the i-type vehicle, F iZRL For the optimal active suspension output control force of the left rear wheel of the i-type vehicle, F iZRR The optimal active suspension output control force is provided for the right rear wheel of the i-type vehicle;

[0062] The electronic control unit in the active suspension control unit receives the optimal active suspension output control force for the four wheels. By adjusting the opening and closing of the solenoid valve, it realizes the inflation and deflation of the air spring and controls the damping of the continuously adjustable damper to achieve the adjustment of the vehicle body posture. The proportional-integral-derivative closed-loop feedback control is used to adjust the stiffness of the active suspension air spring and the damping of the continuously adjustable damper.

[0063] The road condition sensing unit determines that the road condition on which the vehicle is traveling is icy, snowy, or muddy.

[0064] Icy and muddy roads involve the following steps:

[0065] Step 1: When the operating condition is an icy or muddy road surface, the mode switching control unit adopts a strong sensing mode to perform cluster analysis on the relevant parameters of the icy or muddy road surface operating condition. The specific steps are as follows:

[0066] Step 1.1: Set up n sample objects, denoted as x1, x2, ..., xn. n This indicates that data is collected over multiple time periods during vehicle operation, with each sample containing m data indicators x. i1 ,x i2 ,…,x im For i = 1, 2, ..., n, parameterization of sample objects is achieved by constructing the universe of discourse U and the data matrix X:

[0067] U = {x1, x2, ..., x} n},

[0068]

[0069] In the formula, x im This represents the m types of data for the i-th sample object;

[0070] Step 1.2: Perform standard translation and range shifting on the parameterized sample objects:

[0071]

[0072]

[0073]

[0074] In the formula, s represents the average value of the k-th data type among n sample objects. k Let x′ represent the mean squared error of the k-th data type among n sample objects. ik Let x″ represent the dimensionless value of the k-th type of data in the i-th sample object. ik This represents the calculated value of the k-th data type in the i-th sample object;

[0075] Step 1.3: Calculate the similarity between sample objects, specifically the similarity r between the i-th and j-th sample objects. ij :

[0076]

[0077] Calculate the similarity between all sample objects sequentially, construct a similarity matrix R, and simplify it to a triangular matrix R. * :

[0078]

[0079] Step 1.4: Based on the triangular matrix R * The direct clustering method is used to obtain the cluster hierarchy diagram;

[0080] Step 1.5: Pre-set the initial threshold λ, find the λ with the best energy-saving effect through experimental design, and determine the driving condition classification method with the best energy-saving effect of the drive-by-wire chassis system;

[0081] Step 1.6: Add the collected data to the above domain U for processing to achieve real-time classification of driver and vehicle operating conditions;

[0082] Step 1.7: Based on the experimental design in Step 1.5, multiple different thresholds λ are used to represent the similarity of the same class, where λ∈[0,1]. The larger the value of λ, the greater the similarity.

[0083] Let λ1 = 1, for each sample object x i Construct similar classes, i.e., satisfy r ij =1 of x i and x j If they form similar classes, then merge r. ijThe sample objects with λ1 = 1 belong to one class, resulting in an equivalent classification at the λ1 = 1 level;

[0084] Taking λ² as the second largest value, we directly extract element pairs (x) with a similarity greater than or equal to λ² from R. i ,x j ), and in the equivalent classification corresponding to λ1=1, x i The class and x j The classes they belong to are merged. After merging all these classes, we get the equivalent classification for λ2.

[0085] Taking λ3 as the second largest value, we directly extract the element pairs (x) with a similarity of λ3 from R. i ,x j ), which corresponds to the equivalent classification x in λ2 i The class and x j The classes they belong to are merged. After merging all these classes, we get the equivalent classification for λ3.

[0086] And so on up to λ n =0, at this time U is merged into one class;

[0087] Step 2: Based on the cluster analysis results of the relevant parameters for the icy and muddy road conditions, sort them from largest to smallest as follows: simple icy and muddy road conditions (0%-40%), conventional icy and muddy road conditions (40%-85%), and complex icy and muddy road conditions (85%-100%); set an environmental humidity coefficient ω for different icy and muddy road conditions. wet :

[0088]

[0089] Step 3: Based on the road condition monitoring instrument in the road condition perception unit, which senses changes in road humidity and road viscosity parameters in the environment through the core sensor of the front-end acquisition signal, the host acquisition system quickly analyzes and processes the data, transmits the data to the server via wireless network, and obtains real-time data such as road viscosity and dryness / wetness conditions, i.e., road viscosity factor λ and road humidity coefficient μ. The required reduction in vehicle height for different vehicle models under different icy and muddy conditions is determined according to the following formula:

[0090]

[0091] Among them, L i This indicates the wheelbase of the i-type vehicle, and v indicates the vehicle's longitudinal speed.

[0092] Based on the above data on vehicle height reduction under different vehicle models, speeds, and icy / muddy road conditions, the active suspension control unit adjusts the opening and closing of the solenoid valve to inflate and deflate the air springs and control the damping of the continuously adjustable shock absorber, thereby adjusting the vehicle height.

[0093] The road condition sensing unit determines that the road condition on which the vehicle is traveling is a sloping road surface, which includes uphill and downhill road surfaces.

[0094] When the operating condition is an uphill road, the mode switching control unit adopts the mid-sensing mode. In the sensor data acquisition unit, the vehicle height sensor installed at the front suspension of the vehicle measures the vehicle height displacement H. uf The vehicle height sensor installed at the rear suspension of the car measures the vehicle height displacement H. ur The vehicle pitch angle sensor installed at the vehicle's center of gravity measures the actual vehicle pitch angle θ. ua The theoretical pitch angle θ of the vehicle body can be calculated using the following formula. ut :

[0095]

[0096] In the formula, L is the distance between the vehicle height sensor at the front suspension and the vehicle height sensor at the rear suspension;

[0097] When the vehicle pitch angle deviation is Δθ u =|θ ua -θ ut | Less than 0.8°, and θ ua When the angle is greater than 3°, then the data θ ua The data is transmitted to the electronic control unit, which then executes the high-slope mode, raising the rear of the vehicle chassis and lowering the front until the height difference ΔH between the front and rear of the vehicle is reached. u =|H uf -H ur If the height difference is less than 4mm, stop raising or lowering the chassis to keep the vehicle level.

[0098] When the vehicle pitch angle deviation is Δθ u =|θ ua -θ ut | Less than 0.8°, and θ a When the angle is less than 3°, then the data θ ua The data is transmitted to the electronic control unit, which then executes the low-slope mode, raising only the rear of the vehicle chassis until the height difference ΔH between the front and rear of the vehicle is reached. u =|H uf -H ur If the height difference is less than 4mm, stop raising or lowering the chassis to keep the vehicle level.

[0099] When the vehicle pitch angle deviation is Δθ u =|θ ua -θ ut If the pitch angle is greater than or equal to 0.8°, the electronic control unit will determine that the pitch angle measurement deviation is too large and it is necessary to re-collect the data from the front and rear vehicle height sensors and then compare the vehicle pitch angle deviation.

[0100] When the driving condition is a downhill road, the mode switching control unit adopts the mid-sensing mode. In the sensor data acquisition unit, the vehicle height sensor installed at the front suspension of the vehicle measures the vehicle height displacement H. df The vehicle height sensor installed at the rear suspension of the car measures the vehicle height displacement H. dr The vehicle pitch angle sensor installed at the vehicle's center of gravity measures the actual vehicle pitch angle θ. da The theoretical pitch angle θ of the vehicle body can be calculated using the following formula. dt :

[0101]

[0102] In the formula, L is the distance between the vehicle height sensor at the front suspension and the vehicle height sensor at the rear suspension;

[0103] When the vehicle pitch angle deviation is Δθ d =|θ da -θ dt | Less than 0.8°, and θ da When the angle is greater than 3°, then the data θ da The data is transmitted to the electronic control unit, which then executes the high-slope mode, raising the height of the front of the vehicle chassis and lowering the height of the rear until the height difference ΔH between the front and rear of the vehicle is reached. d =|H df -H dr If the height difference is less than 4mm, stop raising or lowering the chassis to keep the vehicle level.

[0104] When the vehicle pitch angle deviation is Δθ d =|θ da -θ dt | Less than 0.8°, and θ da When the angle is less than 3°, then the data θ da The data is transmitted to the electronic control unit, which then executes the low-slope mode, raising only the front of the vehicle chassis until the height difference ΔH between the front and rear of the vehicle is reached. d =|H df -H dr If the height difference is less than 4mm, stop raising or lowering the chassis to keep the vehicle level.

[0105] When the vehicle pitch angle deviation is Δθ d =|θda -θ dt If the pitch angle is greater than or equal to 0.8°, the electronic control unit will determine that the pitch angle measurement deviation is too large and it is necessary to re-collect the data from the front and rear vehicle height sensors and then compare the vehicle pitch angle deviation.

[0106] The road condition sensing unit determines that the road condition on which the vehicle is traveling is a turning surface.

[0107] The following steps are involved in turning on the road:

[0108] Step 1: When the operating condition is a turning road surface, the mode switching control unit adopts the mid-sensing mode, and in the sensor data acquisition unit, the front wheel steering angle measurement system acquires the vehicle's front wheel steering angle δ. r The vehicle speed sensor obtains the vehicle's turning speed v. r When a car is driving normally, and the lateral acceleration does not exceed 0.4g and the sideslip angle does not exceed 5°, the wheel lateral force can be determined according to the following formula:

[0109]

[0110]

[0111] Among them, F C1 ,F C2 ,F C3 ,F C4 This indicates the lateral force exerted on each wheel by the ground during a turn; k f ,k r Indicates the lateral stiffness of the front and rear axle tires; β represents the slip angle at the center of gravity; L f ,L r ω represents the distance from the center of mass to the front and rear axles; z This represents the angular velocity of the car as it rotates around the Z-axis;

[0112] Considering the dynamics of a car turning in the Z and Y directions, we have:

[0113] I z ω=L f (F C1 +F C2 cosδ r -L r (F C3 +F C4 ),

[0114] mv r (β+ω z )=(F C1 +F C2 cosδ r +(F C3 +F C4 ),

[0115] Where m represents the total vehicle mass; I z β represents the angular velocity of the car as it rotates around the Z-axis; β represents the sideslip angle of the car's center of mass as it rotates.

[0116] When a car turns, the load on the inner tire is transferred to the outer wheel. The lateral load transfer rate can be calculated using the following formula:

[0117]

[0118] Among them, F zl ,F zr This represents the vertical load on the left and right wheels. When LTR = 0, the sprung mass of the vehicle does not move laterally. When LTR = ±1, one wheel of the vehicle has already left the ground.

[0119] Step 2: To evaluate the risk and severity of rollover when a car is turning, a turning factor ζ is introduced, whose expression is as follows:

[0120]

[0121] Among them, Q a Q b Q c ,P a ,P b For weighting coefficients, 0 < P a ,P b <1, and P a +P b =1, 0 < Q a Q b Q c <1; θ is the vehicle body roll angle. a is the vehicle body roll rate; y For lateral acceleration, a yl LTR is the critical lateral acceleration; LTR is the lateral load transfer rate. l The critical lateral load transfer rate;

[0122] Step 3: Preset the turning factor ζ for the i-type vehicle i The active suspension control unit executes the following strategy:

[0123] When the vehicle turns right, i.e., δ r >0, if the turning factor ζ is greater than the preset turning factor ζ of type i vehicle iWhen the vehicle is level, the active suspension control unit controls the left front and left rear continuously adjustable dampers of the i-type vehicle to extend, the right front and right rear continuously adjustable dampers to compress, the left front and left rear air springs to inflate, and the right front and right rear air springs to deflate until the vehicle body is level. If the turning factor ζ is less than or equal to the i-type vehicle's preset turning factor ζ... i When the vehicle is level, the active suspension control unit controls the left front and left rear continuously adjustable damping shock absorbers of the i-type vehicle to perform a stretching motion, and the left front and left rear air springs to inflate until the vehicle body is level.

[0124] When the vehicle turns left, i.e., δ r <0, if the turning factor ζ is greater than the preset turning factor ζ of type i vehicle i When the vehicle is level, the active suspension control unit controls the left front and left rear continuously adjustable dampers of the i-type vehicle to compress, the right front and right rear continuously adjustable dampers to extend, the left front and left rear air springs to deflate, and the right front and right rear air springs to inflate until the vehicle body is level; if the turning factor ζ is less than or equal to the i-type vehicle's preset turning factor ζ i When the vehicle is in a horizontal position, the active suspension control unit controls the right front and right rear continuously adjustable dampers of the i-type vehicle to extend, and the right front and right rear air springs to inflate until the vehicle body is level.

[0125] The road condition sensing unit determines that the road condition on which the vehicle is traveling is a level and good road surface.

[0126] When the operating condition is a level and good road surface, the mode switching control unit adopts a weak perception mode, which obtains the vehicle's longitudinal speed through the vehicle speed sensor in the sensing data acquisition unit, and adjusts the vehicle height through the active suspension control unit for different vehicle models, including the following steps:

[0127] Step 1: Determine the required reduction in vehicle height for different vehicle models at different speeds using the following formula:

[0128]

[0129] Among them, H i The i model represents a lower body height, L i The wheelbase of model i is represented by v. i η represents the longitudinal speed of vehicle type i. i η represents the chassis protection coefficient of vehicle model i, where 0.2 ≤ η i ≤0.3;

[0130] Step 2: Based on the above data on vehicle height reduction under different vehicle models and speeds, the active suspension control unit adjusts the opening and closing of the solenoid valve to charge and deflate the air springs and control the damping of the continuously adjustable shock absorber, thereby adjusting the vehicle height.

[0131] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0132] 1. An active suspension control method for automobiles can actively collect data and actively identify road conditions, thereby performing active suspension control to ensure chassis level and improve vehicle ride smoothness and comfort.

[0133] 2. This invention actively identifies five road conditions: bumpy road surface, icy and muddy road surface, sloping road surface, turning road surface, and level road surface. It also classifies vehicles in a custom way and adopts different control methods for active suspension for different road conditions and different vehicle models, ensuring the uniqueness of the control method under different conditions.

[0134] 3. To accommodate different road conditions, the perception mode switching unit is divided into strong perception mode, medium perception mode and weak perception mode, so that the number and types of vehicle state parameters acquired by different perception modes are different, thereby making the vehicle drive smoother, more stable and safer. Attached Figure Description

[0135] The present invention will be further described below with reference to the accompanying drawings:

[0136] Figure 1 This is a control framework diagram of an active suspension control method for automobiles proposed in this invention;

[0137] Figure 2 A flowchart illustrating the workflow when the vehicle is traveling on a bumpy road surface.

[0138] Figure 3 A flowchart illustrating the workflow when vehicles are traveling on icy, snowy, or muddy roads.

[0139] Figure 4 A flowchart illustrating the workflow when the vehicle is traveling on a sloping road surface.

[0140] Figure 5 A flowchart illustrating the workflow when the vehicle is traveling on a turning road surface.

[0141] Figure 6 This is a flowchart illustrating the workflow when the road conditions for vehicle operation are a level and well-maintained surface. Detailed Implementation

[0142] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0143] like Figure 1 As shown, the present invention is an active suspension control method for automobiles, including a sensor data acquisition unit, a road condition perception unit, a mode switching control unit, an expert data calibration unit, a closed-loop control force correction unit, and an active suspension control unit.

[0144] The sensor data acquisition unit includes a center of gravity sideslip angle sensor, a vehicle roll angle sensor, a vehicle vertical acceleration sensor, a vehicle pitch angle sensor, a driver's cab camera, a vehicle speed sensor, a vehicle height sensor, and a front wheel steering angle measurement system; these are used to acquire the center of gravity sideslip angle, vehicle roll angle, vehicle vertical acceleration, vehicle pitch angle, driver yaw distance, vehicle longitudinal speed, suspension height change, and front wheel steering angle, respectively; based on the acquired data, a bump factor is designed to evaluate the overall performance of the bumpiness of bumpy roads; a turning factor is introduced to evaluate the rollover risk and rollover severity when the vehicle is turning;

[0145] The road condition perception unit includes a map, navigation, camera, road condition database, and road surface condition monitor. The navigation and map are used to obtain the current vehicle position. The camera is used to acquire information about obstacles in front of, behind, and to the sides of the vehicle, road slope, and surface unevenness. The road condition database, based on the current vehicle position, obstacles, road slope, surface unevenness, and an offline road database, determines road conditions, including but not limited to bumpy roads, icy / muddy roads, sloping roads, curved roads, and level roads. The road surface condition monitor includes a front-end signal acquisition core sensor, a host acquisition system, a wireless network, and a server. It is used to monitor real-time changes in road surface water accumulation, snow thickness, rainfall / snowfall, and wet / dry conditions, and to acquire road viscosity factors and road humidity coefficients. Cluster analysis is used to analyze different icy / muddy road surface conditions, and then an environmental humidity coefficient is set.

[0146] The mode switching control unit includes a strong perception mode, a medium perception mode, and a weak perception mode. Different perception modes are adopted according to the identification of different road conditions. The number and types of vehicle state parameters acquired by different perception modes are different.

[0147] The expert data calibration unit includes simulation, real vehicle calibration and experience analysis of 100 different bumpy road conditions selected from various custom types of vehicles to form the active suspension control force output of different types of vehicles at different speeds and road conditions, and integrates an expert database.

[0148] The closed-loop control force correction unit includes constructing a closed-loop correction function using the center of gravity sideslip angle, vehicle roll angle, vehicle vertical acceleration, and vehicle pitch angle obtained by the sensor data acquisition unit, to obtain the correction force for different customized vehicle models, and then correct the active suspension control force.

[0149] The active suspension control unit includes a pressure sensor, a height sensor, an air spring, a continuously adjustable damper, a solenoid valve, an air pump, an air tank, and an electronic control unit.

[0150] like Figure 2As shown, the road condition sensing unit determines that the road condition on which the vehicle is traveling is a bumpy road surface.

[0151] When the operating condition is a bumpy road surface, the mode switching control unit adopts a strong sensing mode, and the centroid sideslip angle sensor in the sensing data acquisition unit acquires the centroid sideslip angle β, with a weighting coefficient. The value range is from 0 to 1. A smaller value indicates less lateral deviation of the vehicle during movement and better handling stability. This indicates that the centroid side deflection angle is 0°. A larger value indicates a greater degree of lateral deviation during vehicle movement and poorer handling stability. The time indicates that the centroid side slip angle is 90°;

[0152] Calculate the root mean square value of the centroid sideslip angle using the following formula:

[0153]

[0154] Where: β t Let be the centroid sideslip angle collected at time t;

[0155] N1 is the number of samples for the centroid sideslip angle, N1 = T / ns1;

[0156] T represents the time period;

[0157] ns1 is the acquisition period of the centroid side deflection angle signal;

[0158] The vehicle roll angle sensor in the sensing data acquisition unit acquires the vehicle roll angle. Weighting coefficient The value range is from 0 to 1. A smaller value indicates less body roll during vehicle movement and a lower probability of rollover. This indicates that the vehicle body roll angle is 0°. The larger the value, the greater the degree of body roll during movement, and the higher the probability of the vehicle rolling over. The time indicates that the vehicle body roll angle is 90°;

[0159] Calculate the root mean square value of the vehicle body roll angle using the following formula:

[0160]

[0161] in: Let be the vehicle roll angle collected at time t;

[0162] N2 is the number of vehicle roll angle samples, N2 = T / ns2;

[0163] T represents the time period;

[0164] ns2 is the vehicle body roll angle signal acquisition cycle;

[0165] The vehicle vertical acceleration sensor in the sensing data acquisition unit acquires the vehicle vertical acceleration a. z Weighting coefficient The value range is from 0 to 1. A smaller value indicates less vertical vibration during vehicle movement, a lower probability of wheels leaving the ground, and better ride comfort. This indicates that the vehicle is not experiencing vertical vibration; A larger value indicates greater vertical vibration during vehicle movement, a higher probability of wheels leaving the ground, and poorer ride comfort. This indicates that the wheel has left the ground;

[0166] Calculate the root mean square value of the vehicle's vertical acceleration using the following formula:

[0167]

[0168] Where: a zt Let be the vertical acceleration of the vehicle body collected at time t;

[0169] N3 is the number of vertical acceleration samples of the vehicle body, N3 = T / ns3;

[0170] T represents the time period;

[0171] ns3 is the acquisition period for the vehicle's vertical acceleration signal;

[0172] The vehicle pitch angle sensor in the sensing data acquisition unit acquires the vehicle pitch angle θ, with weighting coefficients. The value range is from 0 to 1. A smaller value indicates less pitch during vehicle movement and a smaller difference in height between the front and rear suspensions. This indicates that the vehicle is traveling smoothly; A larger value indicates a greater degree of pitch during vehicle movement, and a larger difference in height between the front and rear suspensions. This indicates that the vehicle has overturned, either upside down or face down.

[0173] Calculate the root mean square value of the vehicle pitch angle using the following formula:

[0174]

[0175] Where: θ t Let be the vehicle pitch angle collected at time t;

[0176] N4 is the number of vehicle pitch angle samples, N4 = T / ns4;

[0177] T represents the time period;

[0178] ns4 is the vehicle pitch angle signal acquisition cycle;

[0179] The driver's cab camera in the sensor data acquisition unit acquires the driver's circumference distance s and circumference weight coefficient. The value ranges from 0 to 1. When a driver is driving on a bumpy road, the bumps will cause the driver to sway in the front, back, left and right directions. The smaller the sway amplitude and the smaller the circumferential distance, the less the road bumps will affect the driver; the larger the sway amplitude and the larger the circumferential distance, the greater the impact of the road bumps on the driver.

[0180] The root mean square value of the driver's circumference distance is calculated using the following formula:

[0181]

[0182] Where: s t The distance of the driver's circumference collected at time t;

[0183] N5 is the number of driver's circumferential distance samples, N5 = T / ns5;

[0184] T represents the time period;

[0185] ns5 is the acquisition period for the driver's swivel distance signal;

[0186] Design a comprehensive performance index function to evaluate the degree of bumpiness on bumpy roads:

[0187] Convert it into matrix form as follows:

[0188]

[0189]

[0190] In the formula, ρ is the turbulence factor, and Q... e Here is the parameter weight correction matrix, where It is 1×1 Gaussian white noise.

[0191] Because the performance requirements for different vehicle types vary on the same road surface, vehicle types are categorized into Type A, Type B, and Type C vehicles. Type A vehicles are small cars with a wheelbase less than 2700mm, Type B vehicles are mid-size cars with a wheelbase between 2700 and 2850mm, and Type C vehicles are large cars with a wheelbase greater than 2850mm; hereinafter referred to as Type i vehicles, where i can take the values ​​A, B, or C.

[0192] For type A vehicles, the preset bump factor range is [ρ Amin ,ρ Amax When ρ < ρAmin At that time, the vehicle was deemed to be in a low-risk bumpy zone; when ρ Amin ≤ρ≤ρ Amax When the vehicle speed is below 65 km / h, it is considered to be in the low-risk bumpy zone; when the vehicle speed is above 65 km / h but below 70 km / h, it is considered to be in the medium-risk bumpy zone; and when the vehicle speed is above 70 km / h, it is considered to be in the high-risk bumpy zone. When ρ > ρ Amax At that time, the vehicle was determined to be in a high-risk, bumpy zone;

[0193] For Type B vehicles, the preset bump factor range is [ρ Bmin ,ρ Bmax When ρ < ρ Bmin At that time, the vehicle was deemed to be in a low-risk bumpy zone; when ρ Bmin ≤ρ≤ρ Bmax When the vehicle speed is below 55 km / h, it is considered to be in the low-risk bumpy zone; when the vehicle speed is above 55 km / h but below 60 km / h, it is considered to be in the medium-risk bumpy zone; and when the vehicle speed is above 60 km / h, it is considered to be in the high-risk bumpy zone. When ρ > ρ Bmax At that time, the vehicle was determined to be in a high-risk, bumpy zone;

[0194] For Type C vehicles, the preset bump factor range is [ρ Cmin ,ρ Cmax When ρ < ρ Cmin At that time, the vehicle was deemed to be in a low-risk bumpy zone; when ρ Cmin ≤ρ≤ρ Cmax When the vehicle speed is below 45 km / h, it is considered to be in the low-risk bumpy zone; when the vehicle speed is above 45 km / h but below 50 km / h, it is considered to be in the medium-risk bumpy zone; and when the vehicle speed is above 50 km / h, it is considered to be in the high-risk bumpy zone. When ρ > ρ Cmax At that time, the vehicle was deemed to be in a high-risk, bumpy zone.

[0195] The expert data calibration unit includes the following steps:

[0196] Step 1: Select 100 different bumpy road conditions for different types of vehicles to conduct simulation, real vehicle calibration and experience analysis, form the active suspension control force output of the i-type vehicle under different vehicle speeds and different road conditions, and form an expert database;

[0197] Step 2: Based on the different bump risk ranges and vehicle speeds of the different vehicle models, by comparing with the expert database, the required active suspension control force for the four wheels on both sides of the i-type vehicle can be obtained as [F]. iFL F iFR FiRL F iRR ];

[0198] Among them, F iFL For the active suspension control force of the left front wheel of the i-type vehicle, F iFR For the active suspension control force of the right front wheel of the i-type vehicle, F iRL For the active suspension control force of the left rear wheel of the i-type vehicle, F iRR The active suspension control force for the right rear wheel of the i-type vehicle.

[0199] The closed-loop control force correction unit is used to correct the active suspension control forces of the four wheels in the above scheme; for the control forces based on the center of gravity sideslip angle β and the vehicle roll angle... Vertical acceleration a of the vehicle body z Constructing the closed-loop correction function for the i-type vehicle using the vehicle body pitch angle θ Calculate the closed-loop correction force F of the type i vehicle ib =k i f i , where k i The coefficients of the closed-loop correction function for type i vehicle are given, with the constraint 0 < k. i ≤1; Optimal active suspension control force output for type i vehicles:

[0200] Among them, F iZFL For the optimal active suspension output control force of the left front wheel of the i-type vehicle, F iZFR For the optimal active suspension output control force of the right front wheel of the i-type vehicle, F iZRL For the optimal active suspension output control force of the left rear wheel of the i-type vehicle, F iZRR The optimal active suspension output control force is provided for the right rear wheel of the i-type vehicle;

[0201] The electronic control unit in the active suspension control unit receives the optimal active suspension output control force for the four wheels. By adjusting the opening and closing of the solenoid valve, it realizes the inflation and deflation of the air spring and controls the damping of the continuously adjustable damper to achieve the adjustment of the vehicle body posture. The proportional-integral-derivative closed-loop feedback control is used to adjust the stiffness of the active suspension air spring and the damping of the continuously adjustable damper.

[0202] like Figure 3 As shown, the road condition perception unit determines that the road condition on which the vehicle is traveling is an icy, snowy, or muddy road surface.

[0203] Icy and muddy roads involve the following steps:

[0204] Step 1: When the operating condition is an icy or muddy road surface, the mode switching control unit adopts a strong sensing mode to perform cluster analysis on the relevant parameters of the icy or muddy road surface operating condition. The specific steps are as follows:

[0205] Step 1.1: Set up n sample objects, denoted as x1, x2, ..., xn. n This indicates that data is collected over multiple time periods during vehicle operation, with each sample containing m data indicators x. i1 ,x i2 ,…,x im For i = 1, 2, ..., n, parameterization of sample objects is achieved by constructing the universe of discourse U and the data matrix X:

[0206] U = {x1, x2, ..., x} n},

[0207]

[0208] In the formula, x im This represents the m types of data for the i-th sample object;

[0209] Step 1.2: Perform standard translation and range shifting on the parameterized sample objects:

[0210]

[0211]

[0212]

[0213] In the formula, s represents the average value of the k-th data type among n sample objects. k This represents the mean squared error of the k-th data type among n sample objects. This represents the dimensionless value of the k-th type of data in the i-th sample object. This represents the calculated value of the k-th data type in the i-th sample object;

[0214] Step 1.3: Calculate the similarity between sample objects, specifically the similarity r between the i-th and j-th sample objects. ij :

[0215]

[0216] Calculate the similarity between all sample objects sequentially, construct a similarity matrix R, and simplify it to a triangular matrix R. * :

[0217]

[0218] Step 1.4: Based on the triangular matrix R * The direct clustering method is used to obtain the cluster hierarchy diagram;

[0219] Step 1.5: Pre-set the initial threshold λ, find the λ with the best energy-saving effect through experimental design, and determine the driving condition classification method with the best energy-saving effect of the drive-by-wire chassis system;

[0220] Step 1.6: Add the collected data to the above domain U for processing to achieve real-time classification of driver and vehicle operating conditions;

[0221] Step 1.7: Based on the experimental design in Step 1.5, multiple different thresholds λ are used to represent the similarity of the same class, where λ∈[0,1]. The larger the value of λ, the greater the similarity.

[0222] Let λ1 = 1, for each sample object x i Construct similar classes, i.e., satisfy r ij =1 of x i and x j If they form similar classes, then merge r. ij The sample objects with λ1 = 1 belong to one class, resulting in an equivalent classification at the λ1 = 1 level;

[0223] Taking λ² as the second largest value, we directly extract element pairs (x) with a similarity greater than or equal to λ² from R. i ,x j ), and in the equivalent classification corresponding to λ1=1, x i The class and x j The classes they belong to are merged. After merging all these classes, we get the equivalent classification for λ2.

[0224] Taking λ3 as the second largest value, we directly extract the element pairs (x) with a similarity of λ3 from R. i ,x j ), which corresponds to the equivalent classification x in λ2 i The class and x j The classes they belong to are merged. After merging all these classes, we get the equivalent classification for λ3.

[0225] And so on up to λ n =0, at this time U is merged into one class;

[0226] Step 2: Based on the cluster analysis results of the relevant parameters for the icy and muddy road conditions, sort them from largest to smallest as follows: simple icy and muddy road conditions (0%-40%), conventional icy and muddy road conditions (40%-85%), and complex icy and muddy road conditions (85%-100%); set an environmental humidity coefficient ω for different icy and muddy road conditions. wet :

[0227]

[0228] Step 3: Based on the road condition monitoring instrument in the road condition perception unit, which senses changes in road humidity and road viscosity parameters in the environment through the core sensor of the front-end acquisition signal, the host acquisition system quickly analyzes and processes the data, transmits the data to the server via wireless network, and obtains real-time data such as road viscosity and dryness / wetness conditions, i.e., road viscosity factor λ and road humidity coefficient μ. The required reduction in vehicle height for different vehicle models under different icy and muddy conditions is determined according to the following formula:

[0229]

[0230] Among them, L i This indicates the wheelbase of the i-type vehicle, and v indicates the vehicle's longitudinal speed.

[0231] Based on the above data on vehicle height reduction under different vehicle models, speeds, and icy / muddy road conditions, the active suspension control unit adjusts the opening and closing of the solenoid valve to inflate and deflate the air springs and control the damping of the continuously adjustable shock absorber, thereby adjusting the vehicle height.

[0232] like Figure 4 As shown, the road condition perception unit determines that the road condition on which the vehicle is traveling is a sloping road surface, which includes uphill and downhill road surfaces.

[0233] When the operating condition is an uphill road, the mode switching control unit adopts the mid-sensing mode. In the sensor data acquisition unit, the vehicle height sensor installed at the front suspension of the vehicle measures the vehicle height displacement H. uf The vehicle height sensor installed at the rear suspension of the car measures the vehicle height displacement H. ur The vehicle pitch angle sensor installed at the vehicle's center of gravity measures the actual vehicle pitch angle θ. ua The theoretical pitch angle θ of the vehicle body can be calculated using the following formula. ut :

[0234]

[0235] In the formula, L is the distance between the vehicle height sensor at the front suspension and the vehicle height sensor at the rear suspension;

[0236] When the vehicle pitch angle deviation is Δθ u =|θ ua -θ ut | Less than 0.8°, and θ ua When the angle is greater than 3°, then the data θ ua The data is transmitted to the electronic control unit, which then executes the high-slope mode, raising the rear of the vehicle chassis and lowering the front until the height difference ΔH between the front and rear of the vehicle is reached. u =|H uf -Hur If the height difference is less than 4mm, stop raising or lowering the chassis to keep the vehicle level.

[0237] When the vehicle pitch angle deviation is Δθ u =|θ ua -θ ut | Less than 0.8°, and θ a When the angle is less than 3°, then the data θ ua The data is transmitted to the electronic control unit, which then executes the low-slope mode, raising only the rear of the vehicle chassis until the height difference ΔH between the front and rear of the vehicle is reached. u =|H uf -H ur If the height difference is less than 4mm, stop raising or lowering the chassis to keep the vehicle level.

[0238] When the vehicle pitch angle deviation is Δθ u =|θ ua -θ ut If the pitch angle is greater than or equal to 0.8°, the electronic control unit will determine that the pitch angle measurement deviation is too large and it is necessary to re-collect the data from the front and rear vehicle height sensors and then compare the vehicle pitch angle deviation.

[0239] When the driving condition is a downhill road, the mode switching control unit adopts the mid-sensing mode. In the sensor data acquisition unit, the vehicle height sensor installed at the front suspension of the vehicle measures the vehicle height displacement H. df The vehicle height sensor installed at the rear suspension of the car measures the vehicle height displacement H. dr The vehicle pitch angle sensor installed at the vehicle's center of gravity measures the actual vehicle pitch angle θ. da The theoretical pitch angle θ of the vehicle body can be calculated using the following formula. dt :

[0240]

[0241] In the formula, L is the distance between the vehicle height sensor at the front suspension and the vehicle height sensor at the rear suspension;

[0242] When the vehicle pitch angle deviation is Δθ d =|θ da -θ dt | Less than 0.8°, and θ da When the angle is greater than 3°, then the data θ da The data is transmitted to the electronic control unit, which then executes the high-slope mode, raising the height of the front of the vehicle chassis and lowering the height of the rear until the height difference ΔH between the front and rear of the vehicle is reached. d =|H df -H dr If the height difference is less than 4mm, stop raising or lowering the chassis to keep the vehicle level.

[0243] When the vehicle pitch angle deviation is Δθ d =|θ da -θ dt | Less than 0.8°, and θ da When the angle is less than 3°, then the data θ da The data is transmitted to the electronic control unit, which then executes the low-slope mode, raising only the front of the vehicle chassis until the height difference ΔH between the front and rear of the vehicle is reached. d =|H df -H dr If the height difference is less than 4mm, stop raising or lowering the chassis to keep the vehicle level.

[0244] When the vehicle pitch angle deviation is Δθ d =|θ da -θ dt If the pitch angle is greater than or equal to 0.8°, the electronic control unit will determine that the pitch angle measurement deviation is too large and it is necessary to re-collect the data from the front and rear vehicle height sensors and then compare the vehicle pitch angle deviation.

[0245] like Figure 5 As shown, the road condition sensing unit determines that the road condition on which the vehicle is traveling is a turning road surface;

[0246] The following steps are involved in turning on the road:

[0247] Step 1: When the operating condition is a turning road surface, the mode switching control unit adopts the mid-sensing mode, and in the sensor data acquisition unit, the front wheel steering angle measurement system acquires the vehicle's front wheel steering angle δ. r The vehicle speed sensor obtains the vehicle's turning speed v. r When a car is driving normally, and the lateral acceleration does not exceed 0.4g and the sideslip angle does not exceed 5°, the wheel lateral force can be determined according to the following formula:

[0248]

[0249]

[0250] Among them, F C1 ,F C2 ,F C3 ,F C4 This indicates the lateral force exerted on each wheel by the ground during a turn; k f ,k r Indicates the lateral stiffness of the front and rear axle tires; β represents the slip angle at the center of gravity; L f ,L r ω represents the distance from the center of mass to the front and rear axles; z This represents the angular velocity of the car as it rotates around the Z-axis;

[0251] Considering the dynamics of a car turning in the Z and Y directions, we have:

[0252] I z ω=L f (F C1 +F C2 cosδ r -L r (F C3 +F C4 ),

[0253] mv r (β+ω z )=(F C1 +F C2 cosδ r +(F C3 +F C4 ),

[0254] Where m represents the total vehicle mass; I z β represents the angular velocity of the car as it rotates around the Z-axis; β represents the sideslip angle of the car's center of mass as it rotates.

[0255] When a car turns, the load on the inner tire is transferred to the outer wheel. The lateral load transfer rate can be calculated using the following formula:

[0256]

[0257] Among them, F zl ,F zr This represents the vertical load on the left and right wheels. When LTR = 0, the sprung mass of the vehicle does not move laterally. When LTR = ±1, one wheel of the vehicle has already left the ground.

[0258] Step 2: To evaluate the risk and severity of rollover when a car is turning, a turning factor ζ is introduced, whose expression is as follows:

[0259]

[0260] Among them, Q a Q b Q c ,P a ,P b For weighting coefficients, 0 < P a ,P b <1, and P a +P b =1, 0 < Q a Q b Q c <1; θ is the vehicle body roll angle. a is the vehicle body roll rate; y For lateral acceleration, ayl LTR is the critical lateral acceleration; LTR is the lateral load transfer rate. l The critical lateral load transfer rate;

[0261] Step 3: Preset the turning factor ζ for the i-type vehicle i The active suspension control unit executes the following strategy:

[0262] When the vehicle turns right, i.e., δ r >0, if the turning factor ζ is greater than the preset turning factor ζ of type i vehicle i When the vehicle is level, the active suspension control unit controls the left front and left rear continuously adjustable dampers of the i-type vehicle to extend, the right front and right rear continuously adjustable dampers to compress, the left front and left rear air springs to inflate, and the right front and right rear air springs to deflate until the vehicle body is level. If the turning factor ζ is less than or equal to the i-type vehicle's preset turning factor ζ... i When the vehicle is level, the active suspension control unit controls the left front and left rear continuously adjustable damping shock absorbers of the i-type vehicle to perform a stretching motion, and the left front and left rear air springs to inflate until the vehicle body is level.

[0263] When the vehicle turns left, i.e., δ r <0, if the turning factor ζ is greater than the preset turning factor ζ of type i vehicle i When the vehicle is level, the active suspension control unit controls the left front and left rear continuously adjustable dampers of the i-type vehicle to compress, the right front and right rear continuously adjustable dampers to extend, the left front and left rear air springs to deflate, and the right front and right rear air springs to inflate until the vehicle body is level; if the turning factor ζ is less than or equal to the i-type vehicle's preset turning factor ζ i When the vehicle is in a horizontal position, the active suspension control unit controls the right front and right rear continuously adjustable dampers of the i-type vehicle to extend, and the right front and right rear air springs to inflate until the vehicle body is level.

[0264] like Figure 6 As shown, the road condition sensing unit determines that the road condition on which the vehicle is traveling is a level and good road surface.

[0265] When the operating condition is a level and good road surface, the mode switching control unit adopts a weak perception mode, which obtains the vehicle's longitudinal speed through the vehicle speed sensor in the sensing data acquisition unit, and adjusts the vehicle height through the active suspension control unit for different vehicle models, including the following steps:

[0266] Step 1: Determine the required reduction in vehicle height for different vehicle models at different speeds using the following formula:

[0267]

[0268] Among them, H i The i model represents a lower body height, Li The wheelbase of model i is represented by v. i η represents the longitudinal speed of vehicle type i. i η represents the chassis protection coefficient of vehicle model i, where 0.2 ≤ η i ≤0.3;

[0269] Step 2: Based on the above data on vehicle height reduction under different vehicle models and speeds, the active suspension control unit adjusts the opening and closing of the solenoid valve to charge and deflate the air springs and control the damping of the continuously adjustable shock absorber, thereby adjusting the vehicle height.

Claims

1. A method of controlling an active suspension of a vehicle, characterized by, The application relates to a vehicle active suspension control system, which comprises a sensing data acquisition unit, a road condition state sensing unit, a mode switching control unit, an expert data calibration unit, a closed-loop control force correction unit and an active suspension control unit. The sensing data acquisition unit comprises a mass center side slip angle sensor, a vehicle body roll angle sensor, a vehicle body vertical acceleration sensor, a vehicle body pitch angle sensor, a driver's cab camera, a vehicle speed sensor, a vehicle body height sensor and a front wheel rotation angle measuring system, which are respectively used for acquiring a mass center side slip angle, a vehicle body roll angle, a vehicle body vertical acceleration, a vehicle body pitch angle, a driver's swing distance, a vehicle longitudinal speed, a suspension height change and a front wheel rotation angle; according to the above-mentioned collected data, a bumping factor is designed for evaluating the comprehensive performance of the bumping degree of a bumping road; a turning factor is introduced for evaluating the rollover risk and rollover degree of the automobile during turning; The road condition state sensing unit comprises a map, a navigation, a camera, a road working condition database and a road surface condition monitor; the navigation and the map are used for acquiring the current vehicle position; the camera is used for acquiring the obstacles on the front and rear sides of the vehicle, the road slope size and the ground concave-convex degree; the road working condition database is used for judging the road working condition according to the current vehicle position, the obstacles, the road slope, the ground concave-convex degree and the offline road library, and the road working condition includes but is not limited to a bumping road, a snow and slush road, a slope road, a turning road and a horizontal good road; the road surface condition monitor comprises a front-end acquisition signal core sensor, a host acquisition system, a wireless network and a server, and is used for monitoring the real-time data changes of road water, snow thickness, snowfall amount, dry and wet conditions and the like, acquiring a road viscosity factor and a road humidity coefficient; different snow and slush road working conditions are analyzed through a clustering analysis method, and then an environmental humidity coefficient is set; The mode switching control unit comprises a strong sensing mode, a medium sensing mode and a weak sensing mode, different sensing modes are adopted according to the identification of different road conditions, and the number and types of vehicle state parameters acquired by different sensing modes are different; The expert data calibration unit comprises simulation, real vehicle calibration and experience analysis of 100 different bumping road conditions of multiple self-defined types of vehicles, and the active suspension control force output of the vehicle under different speeds and different road conditions is formed, and an expert database is integrated; The closed-loop control force correction unit comprises a mass center side slip angle, a vehicle body roll angle, a vehicle body vertical acceleration and a vehicle body pitch angle acquired through the sensing data acquisition unit, a closed-loop correction function is constructed, a correction force of different self-defined vehicle types is obtained, and the active suspension control force is corrected; The active suspension control unit comprises a pressure sensor, a height sensor, an air spring, a continuously adjustable damper, an electromagnetic valve, an air pump, a gas tank and an electronic control unit. The road condition state sensing unit judges that the vehicle driving road working condition is a bumping road; 2. The method of claim 1, wherein The mass center side slip angle root mean square value is calculated according to the following formula: When the working condition is a bumpy road, the mode switching control unit adopts a strong sensing mode, and a center of mass side slip angle sensor in the sensing data acquisition unit acquires a center of mass side slip angle , the weight coefficient , is in the range of 0 to 1, The smaller the value, the smaller the degree of side slip of the vehicle during movement, and the better the steering stability, = 0 indicates that the center of mass side slip angle is 0°; The larger the value, the greater the degree of side slip of the vehicle during movement, and the worse the steering stability, = 1 indicates that the center of mass side slip angle is 90°; The vehicle body roll angle root mean square value is calculated according to the following formula: ， wherein: is the center of mass lateral angle collected at the moment for the centroid side slip angle, ; T is the time period; is the centroid lateral angle signal acquisition period; The vehicle body side inclination angle sensor in the sensing data acquisition unit acquires a vehicle body side inclination angle , the weight coefficient , is in the range of 0 to 1, The smaller the value, the smaller the degree of vehicle inclination during movement, and the lower the probability of vehicle rollover, = 0 indicates that the vehicle body side inclination angle is 0°; The larger the value, the greater the degree of vehicle inclination during movement, and the higher the probability of vehicle rollover, = 1 indicates that the vehicle body side inclination angle is 90°; The vehicle body vertical acceleration root mean square value is calculated according to the following formula: ， wherein: is the body roll angle collected at the moment the number of body roll angle samples, ; T is the time period; is the body roll angle signal acquisition period; The vehicle body vertical acceleration sensor in the sensing data collection unit acquires vehicle body vertical acceleration , the weight coefficient , is in the range of 0 to 1, The smaller the value, the smaller the vertical vibration of the vehicle during movement, the lower the probability of the wheel leaving the ground, and the better the ride comfort, = 0 indicates that the vehicle has no vertical vibration; The larger the value, the greater the vertical vibration of the vehicle during movement, the higher the probability of the wheel leaving the ground, and the worse the ride comfort, = 1 indicates that the wheel leaves the ground; The vehicle body pitch angle root mean square value is calculated according to the following formula: ， wherein: is the vertical acceleration of the vehicle body collected at the moment the number of samples of the vehicle body vertical acceleration, ; is a time period; The vehicle body vertical acceleration signal acquisition period; The vehicle body pitch angle sensor in the sensing data acquisition unit acquires a vehicle body pitch angle , the weight coefficient , is in the range of 0 to 1, The smaller the value, the smaller the degree of pitch of the vehicle during movement, and the smaller the height difference between the front and rear suspensions of the vehicle, = 0 indicates that the vehicle is running smoothly. The larger the value, the greater the degree of pitch of the vehicle during movement, and the greater the height difference between the front and rear suspensions of the vehicle, = 1 indicates that the vehicle is overturned or rolled over. The driver's swing distance root mean square value is calculated according to the following formula: ， wherein: is the body pitch angle collected at the moment; the number of samples for the vehicle body pitch angle, ; is a time period; The body pitch angle signal acquisition period; The cab camera in the sensing data collection unit acquires a driver's swing distance s, a swing weight coefficient , The value range is 0 to 1. When the driver drives on a bumpy road, the driver will sway in the front, rear, left and right directions due to the road bumping. The smaller the sway amplitude, the smaller the swing distance, and the smaller the influence of the road bumping on the driver. The larger the sway amplitude, the larger the swing distance, and the larger the influence of the road bumping on the driver. A comprehensive performance index function for evaluating the bumping degree of a bumping road is designed ， wherein: is the driver's current steering wheel angle; to sample the number of turns, ; is a time period; to collect the distance signal of the driver's circle; ​ = , which is converted into matrix form as follows: = ， ， wherein is the jerk factor, Q e is a parameter weight correction matrix, where , is a Gaussian white noise.

3. The method of claim 2, wherein The performance requirements of different vehicle types are different under the same road surface, and the vehicle types are divided into A-type vehicles, B-type vehicles and C-type vehicles according to different vehicle types, wherein the A-type vehicle is a small vehicle with an axle distance less than 2700mm, the B-type vehicle is a medium vehicle with an axle distance between 2700mm and 2850mm, and the C-type vehicle is a large vehicle with an axle distance greater than 2850mm; hereinafter, i is referred to as A, B and C; For A-type vehicles, the preset jounce factor range is when , the vehicle is judged to be in a low-risk jounce interval; when , if the vehicle speed is lower than 65 km / h, the vehicle is judged to be in a low-risk jounce interval, if the vehicle speed is greater than 65 km / h and lower than 70 km / h, the vehicle is judged to be in a medium-risk jounce interval, if the vehicle speed is higher than 70 km / h, the vehicle is judged to be in a high-risk jounce interval; when , the vehicle is judged to be in a high-risk jounce interval; For B-type vehicles, the preset jounce factor range is When , the vehicle is judged to be in a low-risk jounce interval; when , if the vehicle speed is lower than 55 km / h, the vehicle is judged to be in a low-risk jounce interval, if the vehicle speed is greater than 55 km / h and less than 60 km / h, the vehicle is judged to be in a medium-risk jounce interval, and if the vehicle speed is higher than 60 km / h, the vehicle is judged to be in a high-risk jounce interval; when , the vehicle is judged to be in a high-risk jounce interval; For C-type vehicles, the preset jounce factor range is When , the vehicle is judged to be in a low jounce risk interval; when , if the vehicle speed is lower than 45 km / h, the vehicle is judged to be in a low jounce risk interval, if the vehicle speed is greater than 45 km / h and lower than 50 km / h, the vehicle is judged to be in a medium jounce risk interval, if the vehicle speed is higher than 50 km / h, the vehicle is judged to be in a high jounce risk interval; when , the vehicle is judged to be in a high jounce risk interval.

4. The method of claim 3, wherein The expert data calibration unit comprises the following steps: Step 1: 100 different bump road conditions are selected for different types of vehicles for simulation, real vehicle calibration and experience analysis, forming the active suspension control force output of i-type vehicles under different vehicle speeds and different road conditions, forming an expert database; Step 2: According to the different vehicle types, the vehicles are in different jolt risk intervals and different vehicle speeds, the required active suspension control forces of the four wheels on the left and right sides of the type i vehicle are compared with the expert database ; wherein, is the i-type car left front wheel active suspension control force, is the i-type car right front wheel active suspension control force, is the i-type car left rear wheel active suspension control force, is the i-type car right rear wheel active suspension control force.

5. The method of claim 4, wherein The closed-loop control force correction unit is used to correct the four-wheel active suspension control force; for the center of mass side slip angle , the body roll angle , the body vertical acceleration , the body pitch angle Constructing the closed-loop correction function of the i-type vehicle , calculating the closed-loop correction force of the i-type vehicle , wherein The i-type vehicle closed-loop correction function coefficient is constrained by ; The optimal active suspension control force output of the i-type vehicle is , wherein, is the optimal active suspension output control force for the left front wheel of the i-type vehicle, is the optimal active suspension output control force for the right front wheel of the i-type vehicle, is the optimal active suspension output control force for the left rear wheel of the i-type vehicle, is the optimal active suspension output control force for the right rear wheel of the i-type vehicle; The electronic control unit in the active suspension control unit receives the optimal active suspension output control force of the four wheels, adjusts the opening and closing of the electromagnetic valve to realize the air spring charging and discharging and controls the damping of the continuously adjustable shock absorber to realize the body posture adjustment, and uses proportional-integral-derivative closed-loop feedback control to adjust the stiffness of the active suspension air spring and the damping of the continuously adjustable shock absorber.

6. The method of claim 1, wherein The road condition state perception unit judges that the vehicle is running on an icy and muddy road surface; The icy and muddy road surface comprises the following steps: Step 1: When the working condition is an icy and muddy road surface, the mode switching control unit adopts a strong perception mode, and the parameters related to the icy and muddy road surface working condition are analyzed by clustering method, and the specific steps are as follows: Step 1.1: Setting up a sample object, denoted as ; multi-period data acquisition is performed during vehicle driving, each sample object contains a data index , and sample object parameterization is achieved by constructing a domain and a data matrix : ， ， In the formula, represents the first sample object kind of data; Step 1.2: Standard translation and translation range processing is performed on the parameterized sample object: ， ， ， In the formula, represents the average value of the first kind of data in the sample objects, represents the mean square error of the first kind of data in the sample objects, represents the dimensionless value of the first kind of data in the sample objects, represents the calculated value of the first kind of data in the sample objects, represents the calculated value of the first kind of data in the sample objects.​​​​​​​ Step 1.3: Calculate the similarity between the sample objects, the similarity between the first sample object and the second sample object :​​ ， The similarity degrees between all sample objects are calculated in sequence to form a similarity matrix , and simplified to a triangular matrix : ， Step 1.4: According to the triangular matrix , the direct clustering method is used to obtain the clustering phylogenetic tree; Step 1.5: Setting the initial threshold value , find the best energy-saving effect of , determine the best energy-saving effect of the drive mode classification method of the drive-by-wire chassis system Step 1.6: The collected data is added to the above domain of discourse and processed to achieve real-time classification of the driver and vehicle operating conditions; Step 1.7: Take multiple different thresholds for the test design in step 1.5 represents the degree of similarity, ∈ [0, 1], The larger the value, the greater the degree of similarity: Take = 1 for each sample object Similar class, that is, meet = 1 And Make up a similar class, at this time, merge = 1 sample object into a class, get = 1 level of equivalent classification; Pick The second largest value, from Directly extract those with similarity greater than or equal to element pairs ( , ), which will correspond to In the equivalent classification of =1 The class it belongs to and Merging the classes they belong to, and merging all these classes together, yields the result for... Equivalent classification; Pick The second largest value, from Directly extract the similarity score. element pairs ( , ), which will correspond to In the equivalent classification The class it belongs to and Merging the classes they belong to, and merging all these classes together, yields the result for... Equivalent classification; and so on until = 0, in which case are grouped together; Step 2: According to the clustering analysis results of the ice and snow muddy road working condition related parameters, the order from large to small includes: simple ice and snow muddy road working condition 0%-40% interval, conventional ice and snow muddy road working condition 40%-85% interval and complex ice and snow muddy road working condition 85%-100% interval; the environmental humidity coefficient is set for different ice and snow muddy road working conditions : Step 3: According to the road condition monitoring instrument in the road condition state sensing unit, the change of the road humidity and the road adhesion degree parameter in the environment is sensed through the front end acquisition signal core sensor, the rapid analysis and processing are carried out through the host acquisition system, the data are transmitted to the server through the wireless network, and the real-time data such as the road adhesion and the dry and wet conditions, i.e. the road adhesion factor , the road humidity coefficient , according to the following formula, the height of the vehicle body that needs to be reduced under different ice and snow and muddy working conditions of different vehicle types is determined: ， wherein represents the wheelbase of a car of type represents the longitudinal vehicle speed of the car According to the above vehicle body height reduction data of different vehicle types, different speeds and different icy and muddy road conditions, the active suspension control unit adjusts the opening and closing of the electromagnetic valve to realize the air spring charging and discharging and controls the damping of the continuously adjustable shock absorber, so as to adjust the vehicle body height.

7. The method of claim 1, wherein The road condition state perception unit judges that the vehicle is running on a slope road surface, which includes an uphill road surface and a downhill road surface; When the working condition is uphill, the mode switching control unit adopts the middle sensing mode, in the sensing data collection unit, the vehicle height sensor installed at the front suspension of the vehicle measures the vehicle height displacement , the vehicle height sensor installed at the rear suspension of the vehicle measures the vehicle height displacement , the vehicle pitch angle sensor installed at the vehicle mass center measures the actual vehicle pitch angle , the theoretical vehicle pitch angle can be calculated according to the following formula : ， In the formula, is the distance between the front suspension body height sensor and the rear suspension body height sensor; When the vehicle body pitch angle deviation is less than 0.8°, and is greater than 3°, the data is transmitted to the electronic control unit, the active suspension control unit executes the high slope mode, raises the height of the rear side of the vehicle chassis, and lowers the height of the front side of the vehicle chassis until the front and rear height displacement difference of the vehicle body is less than 4mm, and the lifting of the chassis is stopped to maintain the vehicle body level. When the vehicle body pitch angle deviation is less than 0.8°, and is less than 3°, the data is transmitted to the electronic control unit, and the active suspension control unit executes the low gradient mode, only raising the height of the rear side of the vehicle chassis until the front and rear height displacement of the vehicle body is less than 4mm, the lifting of the chassis is stopped to maintain the vehicle body level; When the vehicle body pitch angle deviation is greater than or equal to 0.8° If the vehicle body pitch angle deviation is greater than or equal to 0.8°, the electronic control unit determines that the pitch angle measurement deviation is large, and the front and rear vehicle body height sensor data need to be collected again for comparison of the vehicle body pitch angle deviation. When the working condition is downhill road, the mode switching control unit adopts the middle sensing mode, in the sensing data collection unit, the vehicle height sensor installed at the front suspension of the vehicle measures the vehicle height displacement , the vehicle height sensor installed at the rear suspension of the vehicle measures the vehicle height displacement , the vehicle pitch angle sensor installed at the vehicle mass center measures the actual vehicle pitch angle , the following formula can be used to calculate the theoretical vehicle pitch angle : ， In the formula, is the distance between the front suspension body height sensor and the rear suspension body height sensor; When the vehicle body pitch angle deviation is less than 0.8°, and is greater than 3°, the data is transmitted to the electronic control unit, the active suspension control unit executes the high slope mode, raises the height of the front side of the vehicle chassis, and lowers the height of the rear side of the vehicle chassis until the front and rear height displacement difference of the vehicle body is less than 4mm, the lifting of the chassis is stopped to maintain the vehicle body level; When the vehicle body pitch angle deviation is less than 0.8°, and is less than 3°, the data is transmitted to the electronic control unit, and the active suspension control unit executes the low gradient mode, only raising the height of the front side of the vehicle chassis until the front and rear height displacement of the vehicle body is less than 4mm, and the lifting of the chassis is stopped to maintain the vehicle body level. When the vehicle body pitch angle deviation is greater than or equal to 0.8° If the vehicle body pitch angle deviation is greater than or equal to 0.8°, the electronic control unit determines that the pitch angle measurement deviation is large, and the front and rear vehicle body height sensor data need to be collected again for comparison of the vehicle body pitch angle deviation.

8. The method of claim 1, wherein The road condition state perception unit judges that the vehicle is running on a turning road surface; The turning road surface comprises the following steps: Step 1: When the working condition is a turning road, the mode switching control unit adopts a middle perception mode, in the sensing data acquisition unit, the front wheel turning angle measurement system obtains the front wheel turning angle of the vehicle , the vehicle speed sensor obtains the turning speed of the vehicle , when the lateral acceleration is not more than 0.4g and the side slip angle is not more than 5° during normal driving of the vehicle, the wheel side slip force can be determined according to the following formula: ， ， wherein, represents the side slip force of the ground on each wheel when turning; represents the side slip stiffness of the front and rear axle tires; represents the side slip angle of the center of mass; represents the distance of the center of mass to the front and rear axles; represents the angular velocity of the car when turning around the Z axis; Considering the dynamics of Z direction and Y direction when the vehicle turns, there are: ， ， wherein, represents the total vehicle mass; represents the angular velocity of the vehicle when it is turning around the Z axis; represents the side slip angle of the center of mass when the vehicle is turning; When the vehicle turns, the load of the inner tire is transferred to the outer tire, and the lateral load transfer rate can be calculated according to the following formula: ， wherein, represents the vertical load of the left and right wheels, when the sprung mass of the vehicle does not move laterally, when one side wheel of the vehicle has lifted off the ground; Step 2: To evaluate the risk and degree of rollover when the car turns, a turning factor is introduced whose expression is as follows: ， wherein is a weighting factor, , and , ; is a body roll angle, is a body roll angular velocity; is a lateral acceleration, is a critical lateral acceleration; is a lateral load transfer rate, is a critical lateral load transfer rate; Step 3: Presetting cornering factor for i-type vehicle The active suspension control unit executes the strategy as follows: When the vehicle turns right, i.e. , if the turning factor is greater than the preset turning factor of the i-type vehicle , the active suspension control unit controls the left front and left rear continuously adjustable dampers of the i-type vehicle to perform extension, the right front and right rear continuously adjustable dampers to perform compression, the left front and left rear air springs to inflate, and the right front and right rear air springs to deflate until the vehicle body is horizontal; if the turning factor is less than or equal to the preset turning factor of the i-type vehicle , the active suspension control unit controls the left front and left rear continuously adjustable dampers of the i-type vehicle to perform extension, and the left front and left rear air springs to inflate until the vehicle body is horizontal; When the vehicle turns left, i.e. , if the turning factor is greater than the preset turning factor of the type i vehicle , the active suspension control unit controls the left front and left rear continuously adjustable shock absorbers of the type i vehicle to do compression movement, the right front and right rear continuously adjustable shock absorbers to do stretching movement, the left front and left rear air springs to deflate, and the right front and right rear air springs to inflate until the vehicle body is horizontal; if the turning factor is less than or equal to the preset turning factor of the type i vehicle , the active suspension control unit controls the right front and right rear continuously adjustable shock absorbers of the type i vehicle to do stretching movement, and the right front and right rear air springs to inflate until the vehicle body is horizontal.

9. The method of claim 1, wherein The road condition state perception unit judges that the vehicle is running on a horizontal good road surface; When the working condition is a horizontal good road surface, the mode switching control unit adopts a weak perception mode, the vehicle longitudinal speed is obtained through the speed sensor in the sensing data acquisition unit, and the vehicle body height is adjusted through the active suspension control unit for different vehicle types, comprising the following steps: Step 1: Determine the vehicle body height to be reduced for different vehicle types at different speeds according to the following formula: ， wherein, a body lowering height of the i-th vehicle type, a wheelbase of the i-th vehicle type, a longitudinal vehicle speed of the i-th vehicle type, a chassis protection coefficient of the i-th vehicle type, wherein ; Step 2: According to the above vehicle body height reduction data of different vehicle types and different speeds, the active suspension control unit adjusts the opening and closing of the electromagnetic valve to realize the air spring charging and discharging and controls the damping of the continuously adjustable shock absorber, so as to adjust the vehicle body height.

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