Active suspension control method, device, system, storage medium and vehicle of vehicle

Abstract

The present disclosure relates to a vehicle active suspension control method, device, system, storage medium and vehicle, wherein the method comprises: acquiring driving environment data of the vehicle; wherein the driving environment data is determined based on transmission data of an external device; and controlling the active suspension of the vehicle according to the driving environment data. Through the method, compared with acquiring driving environment data through sensors of the vehicle itself, the speed of acquiring driving environment data can be improved, the control accuracy of the active suspension can be improved, the problem of abnormal control of the active suspension caused by failure of the sensors of the vehicle itself can be avoided, and the comfort and safety of riding can be improved.

Description

Technical Field

[0001] This disclosure relates to the field of vehicle control technology, and more specifically, to an active suspension control method, apparatus, system, storage medium, and vehicle for a vehicle. Background Technology

[0002] With the development of intelligent vehicles, active suspension has attracted much attention. Among related technologies, active suspension systems use cameras to detect road undulations and then actively adjust wheel height to keep the vehicle level even on uneven roads, creating a driving experience akin to floating on a magic carpet – hence the name "magic carpet suspension." Its working principle involves the vehicle's forward-facing binocular cameras scanning the road ahead. For example, when there's a speed bump, the camera detects the increased road height. The suspension system then quickly adjusts the oil level and pressure, rapidly raising the pistons in the spring support rods to counteract the vertical movement of the vehicle body, thus greatly increasing ride comfort.

[0003] However, the distance and accuracy of sensors such as cameras are limited, which can easily increase the deviation of active suspension control and cause control lag. In addition, camera sensors are also susceptible to failure due to factors such as weather, leading to abnormal active suspension control. Summary of the Invention

[0004] One objective of this disclosure is to provide a new technical solution for active suspension control of a vehicle, thereby improving the accuracy of active suspension control.

[0005] According to a first aspect of this disclosure, an embodiment of an active suspension control method for a vehicle is provided, comprising:

[0006] Acquire the vehicle's driving environment data; wherein the driving environment data is determined based on data transmitted from external devices;

[0007] The vehicle's active suspension is controlled based on the driving environment data.

[0008] Optionally, the vehicle communicates with the external device based on a V2X system.

[0009] Optionally, the driving environment data includes at least one of the motion data of moving objects around the vehicle and the road data of the road where the vehicle is located.

[0010] Optionally, the active suspension is controlled by determining target values ​​of the control parameters of the active suspension. The target values ​​of the control parameters are determined based on the driving environment data. The target values ​​of the control parameters can be used to adjust the damping force of the active suspension so that the damping force of the active suspension reaches the target damping force corresponding to the target value.

[0011] Optionally, the target value is determined based on the sub-parameter value corresponding to at least one control index related to the control parameter and the weight value corresponding to the at least one control index, wherein the sub-parameter value corresponding to the control index is determined based on the current road parameters of the road where the vehicle is located and the current driving speed of the vehicle, and the current road parameters are determined based on the driving environment data.

[0012] Optionally, the weight value corresponding to the at least one control index is determined based on the first acceleration value of the vehicle, which is determined based on the driving environment data and the vehicle's autonomous vehicle status information.

[0013] Optionally, the weight value corresponding to the at least one control index is determined based on the ratio between the first acceleration value and the boundary acceleration value.

[0014] Optionally, when the first acceleration value is positive, the boundary acceleration value is the first boundary acceleration value; when the first acceleration value is negative, the boundary acceleration value is the second boundary acceleration value.

[0015] Optionally, when the vehicle is not in a specific operating condition, the weight corresponding to the at least one control index is determined based on the ratio between the first acceleration value and the threshold acceleration value; wherein, the specific operating condition includes the operating condition of traction control activation and the operating condition of anti-lock braking activation.

[0016] Optionally, when the vehicle is in a specific operating condition, the target value of the control parameter is determined based on the sub-parameter value corresponding to a certain control index; the specific operating condition is one of the operating condition of traction control activation and anti-lock braking activation, and the certain control index is a safety index.

[0017] Optionally, the sub-parameter values ​​corresponding to the control index can be obtained based on the current road parameters, the current driving speed, and the control parameter-driving data relationship corresponding to the control index. The control parameter-driving data relationship reflects the numerical correspondence between the corresponding sub-parameters, road parameters, and driving speed under the constraints of the corresponding control index.

[0018] Optionally, the control parameter-driving data relationship corresponding to the control index includes sub-parameter values ​​of the control parameter corresponding to each of a variety of numerical combinations, wherein the numerical combination consists of road parameters and driving speed, and the sub-parameter values ​​of the control parameter corresponding to the numerical combination are determined under the driving conditions of that numerical combination with the objective of optimizing the characterization value of the corresponding control index.

[0019] Optionally, the control indicators include comfort indicators and / or safety indicators;

[0020] The characteristic value of the comfort index includes the root mean square value of the total acceleration of the vehicle, which is the root mean square value of the vertical acceleration of the vehicle body and the root mean square value of the pitch acceleration of the vehicle body.

[0021] The safety index is characterized by the root mean square value of the total wheel dynamic load of the vehicle, which is the root mean square value of the dynamic load of the front axle wheels and the dynamic load of the rear axle wheels.

[0022] According to a second aspect of this disclosure, an embodiment of an active suspension control device for a vehicle is provided, comprising:

[0023] A data receiving module is used to acquire driving environment data of the vehicle; wherein the driving environment data is determined based on data transmitted from external devices;

[0024] The control module is used to control the vehicle's active suspension based on the driving environment data.

[0025] According to a third aspect of this disclosure, an embodiment of an active suspension control device for a vehicle is provided, comprising a processor connected to a memory; the processor invokes executable program code stored in the memory to execute an active suspension control method for a vehicle as described in the first aspect.

[0026] According to a fourth aspect of this disclosure, an embodiment of an active suspension system is provided, including active suspension and the active suspension control device described in the second or third aspect.

[0027] According to a fifth aspect of this disclosure, a storage medium is provided that stores computer instructions, which, when invoked, are used to execute the active suspension control method for a vehicle as described in the first aspect.

[0028] According to a sixth aspect of this disclosure, an embodiment of a vehicle is provided, including the active suspension system described in the fourth aspect, or the active suspension control device described in the second or third aspect.

[0029] One beneficial effect of this disclosure is that, according to the embodiments of this application, by acquiring the vehicle's driving environment data, wherein the driving environment data is determined based on data transmitted from an external device, the active suspension of the vehicle is controlled based on the driving environment data. This allows for the acquisition of the vehicle's driving environment data and subsequent adjustment of the active suspension based on that data. Compared to acquiring driving environment data through the vehicle's own sensors, this improves the speed of driving environment data acquisition, enhances the control accuracy of the active suspension, and avoids problems caused by the failure of the vehicle's own sensors, leading to abnormal active suspension control and improved ride comfort and safety.

[0030] Other features and advantages of the invention will become clear from the following detailed description of exemplary embodiments of the invention with reference to the accompanying drawings. Attached Figure Description

[0031] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments of the invention and, together with their description, serve to explain the principles of the invention.

[0032] Figure 1 This is a flowchart of an active suspension control method for a vehicle according to some embodiments;

[0033] Figure 2 This is a schematic diagram of a five-degree-of-freedom vehicle model based on some embodiments;

[0034] Figure 3 This is a schematic diagram of a seven-degree-of-freedom vehicle model according to other embodiments;

[0035] Figure 4 This is a schematic diagram of an active suspension control method for a vehicle according to other embodiments;

[0036] Figure 5 This is a flowchart of an active suspension control method for a vehicle according to some other embodiments;

[0037] Figure 6 This is a structural schematic diagram of an active suspension control device for a vehicle according to some embodiments;

[0038] Figure 7 This is a structural schematic diagram of an active suspension control device for a vehicle according to other embodiments;

[0039] Figure 8 This is a structural schematic diagram of an active suspension system according to some embodiments;

[0040] Figure 9 These are structural schematic diagrams of a vehicle according to some embodiments;

[0041] Figure 10This is a structural schematic diagram of a vehicle according to other embodiments. Detailed Implementation

[0042] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the invention.

[0043] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use.

[0044] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0045] In all the examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0046] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0047] This disclosure relates to a control scheme for an active suspension system of a vehicle. The active suspension system is installed at each of the four tires of the vehicle. Each active suspension includes a shock absorber, which can be a hydraulic cylinder, a magnetorheological shock absorber, an air spring, etc., and is not limited thereto. Different shock absorbers correspond to different wheels. One end of the shock absorber is connected to the control arm of the corresponding wheel, and the other end is connected to the vehicle body. The height and attitude of the vehicle body can be changed by applying different damping forces to the shock absorbers.

[0048] like Figure 1 The diagram illustrates an active suspension control method for a vehicle, which can be implemented by the vehicle's active suspension control device. The control method includes steps S1100 and S1200.

[0049] Step S1100: Obtain vehicle driving environment data.

[0050] In this embodiment, the driving environment data can be determined based on data transmitted from external devices. For example... Figure 4 As shown, external devices can be other vehicles, roadside equipment, mobile devices of vulnerable road users (pedestrians, two-wheeled vehicles, etc.), etc., without limitation here.

[0051] Data transmitted by other vehicles can include distance, speed, acceleration, etc. Data transmitted by roadside equipment can include road data, such as road classification. Data transmitted by mobile devices of vulnerable road users (pedestrians, two-wheeled vehicles, etc.) can include relative distance and relative speed, etc.

[0052] In one embodiment, the vehicle communicates with the external device based on a V2X system.

[0053] In this embodiment, each vehicle is equipped with a V2X (Vehicle to everything) system, which can acquire driving environment data during vehicle operation.

[0054] The main components of a V2X system include the Onboard Unit (OBU), the Roadside Unit (RSU), and mobile devices for vulnerable road users (pedestrians, two-wheeled vehicles, etc.).

[0055] The vehicle's active suspension control device acquires driving environment data. This driving environment data can be determined by the on-board unit (OBU) based on the analysis of data transmitted from external devices, or it can be the data transmitted from the external devices themselves. In other words, the driving environment data is the data transmitted from the external devices.

[0056] In some embodiments, the driving environment data includes motion data of moving objects around the vehicle.

[0057] In this embodiment, the moving objects around the vehicle can be other vehicles around the vehicle, or vulnerable road users (pedestrians, two-wheeled vehicles, etc.) around the vehicle. The motion data of other vehicles around the vehicle can be driving information provided by the on-board unit (OBU) of those vehicles, such as the relative distance, speed, and acceleration of other vehicles in front of or in adjacent lanes. The motion data of vulnerable road users can be information provided by their mobile devices, such as the relative distance and relative speed of vulnerable road users (pedestrians, two-wheeled vehicles, etc.) moving longitudinally or laterally in front of the vehicle.

[0058] In other embodiments, the driving environment data includes road data of the road where the vehicle is located.

[0059] In this embodiment, the road data of the road where the vehicle is located can be the road data of the road where the vehicle is located provided by the road testing unit (RSU). The road data can include road classification, etc.

[0060] Step S1200: Control the vehicle's active suspension based on driving environment data.

[0061] In this embodiment, controlling the vehicle's active suspension can be, for example, adjusting the damping force of the active suspension.

[0062] In one example, such as Figure 4 As shown, road surface unevenness displacement can be determined based on driving environment data, and then the road surface can be sensed based on this displacement. When the sensed road surface is a rough road surface, the active suspension is adjusted with an emphasis on comfort indicators.

[0063] In another example, driving environment data includes motion data of moving objects around the vehicle, which, along with the vehicle's state information, can be used to determine the vehicle's initial acceleration. When the vehicle's initial acceleration is positive and relatively large, the damping force of the active suspension is reduced.

[0064] In yet another example, driving environment data includes road surface data of the road where the vehicle is located. Road parameters, such as road classification, can be determined based on this road surface data. Higher road classifications result in increased damping force from the active suspension.

[0065] According to an embodiment of this application, by acquiring the vehicle's driving environment data, wherein the driving environment data is determined based on data transmitted from an external device, the active suspension of the vehicle is controlled based on the driving environment data. This allows for the rapid determination of the vehicle's driving environment data based on data transmitted from an external device, and then the adjustment of the active suspension based on the driving environment data. Compared to acquiring driving environment data through the vehicle's own sensors, this method improves the speed of driving environment data acquisition, enhances the control accuracy of the active suspension, and avoids problems caused by the failure of the vehicle's own sensors, leading to abnormal active suspension control and improved ride comfort and safety.

[0066] In some embodiments, the active suspension is controlled by determining target values ​​of the control parameters of the active suspension. The target values ​​of the control parameters are determined based on the driving environment data. The target values ​​of the control parameters can be used to adjust the damping force of the active suspension so that the damping force of the active suspension reaches the target damping force corresponding to the target value.

[0067] In specific implementation, step S1200 involves controlling the vehicle's active suspension based on driving environment data, including steps S2100 and S2200.

[0068] Step S2100: Determine the target values ​​of the control parameters of the active suspension based on the driving environment data.

[0069] In this embodiment, the active suspension is controlled by determining the target value of the active suspension control parameters. These control parameters can be parameters related to the damping force of the active suspension; that is, the magnitude of the active suspension damping force can be adjusted by changing the target value of the control parameters to achieve the target damping force corresponding to the target value. This target value can be determined using driving environment data.

[0070] For magnetorheological dampers, the damping force is related to the current; that is, the control parameter is the current. For other types of dampers, the control parameter can be other parameters, which are not limited here.

[0071] In some embodiments, the target value is determined based on a sub-parameter value corresponding to at least one control index related to the control parameter and a weight value corresponding to the at least one control index, wherein the sub-parameter value corresponding to the control index is determined based on the current road parameters of the road where the vehicle is located and the current driving speed of the vehicle, and the current road parameters are determined based on the driving environment data.

[0072] In this embodiment, step S2100 determines the target value of the control parameters of the active suspension based on driving environment data, including steps S2111 and S2113.

[0073] Step S2111: Determine the current road parameters of the road where the vehicle is located based on the driving environment data.

[0074] In this embodiment, the road parameter is the road grade, and the driving environment data includes the road data of the road where the vehicle is located. The vehicle's onboard unit (OBU) can determine the road roughness coefficient using the road data of the road where the vehicle is located provided by the roadside unit (RSU), and then determine the road grade based on the road roughness coefficient.

[0075] In one example, road grades are divided into eight levels: A, B, C, D, E, F, G, and H. Road grade A corresponds to Class I highways and expressways; road grades B and C correspond to common asphalt and cement roads; road grades D and E correspond to gravel roads and compacted but unpaved roads; road grade F corresponds to farmland; and road grades G and H correspond to unpaved, uneven, and damaged roads. Different road grades correspond to different road roughness coefficients. The higher the road roughness coefficient, the higher the road grade; that is, the road roughness coefficient for road grade A is lower than that for road grade B.

[0076] Step S2112: Determine at least one sub-parameter value corresponding to a control index based on the current road parameters of the road where the vehicle is located and the current driving speed of the vehicle.

[0077] In this embodiment, the control indicators can be, for example, safety, comfort, and economic indicators.

[0078] In some embodiments, the sub-parameter values ​​corresponding to the control index can be obtained based on the current road parameters, the current driving speed, and the control parameter-driving data relationship corresponding to the control index. The control parameter-driving data relationship reflects the numerical correspondence between the corresponding sub-parameters, road parameters, and driving speed under the constraints of the corresponding control index.

[0079] In specific implementation, step S2112 determines at least one sub-parameter value corresponding to a control index based on the current road parameters of the road where the vehicle is located and the current driving speed of the vehicle, including:

[0080] Based on the current road parameters, the current driving speed, and the control parameter-driving data relationship corresponding to the control index, determine the sub-parameter value corresponding to the control index.

[0081] In this embodiment, the control parameter-driving data relationship reflects the numerical correspondence between the corresponding sub-parameters, road parameters, and driving speed under the constraints of the corresponding control indicators.

[0082] In one example, taking a magnetorheological damper as the shock absorber, current as the control parameter, and comfort as the control index, the corresponding relationship between the control parameter and driving data can be shown in Table 1. The first control data is as follows:

[0083] Table 1 First Control Data

[0084]

[0085] The first control data is the relationship between the control parameters and driving data of the active suspension, primarily based on comfort indicators. Specifically, the first control data reflects the initial numerical correspondence between road grade, driving speed, and the sub-parameter values ​​of the comfort indicators.

[0086] The active suspension control device can determine the sub-parameter values ​​corresponding to the comfort index from the first control data, i.e., from Table 1, based on the current road grade and the vehicle's current driving speed.

[0087] In another example, taking a magnetorheological damper as the shock absorber and current as the control parameter, with safety as the control index, the corresponding control parameter-driving data relationship can be seen in the second control data shown in Table 2:

[0088] Table 2 Second Control Data

[0089]

[0090] The second control data is the relationship between control parameters and driving data of the active suspension, primarily based on safety indicators. Specifically, the second control data reflects the numerical correspondence between road grade, driving speed, and the sub-parameter values ​​corresponding to the safety indicators. Based on the current road parameters and vehicle speed, the sub-parameter values ​​of the safety indicators corresponding to the current road parameters and vehicle speed can be determined in the second control data, i.e., in Table 2.

[0091] Step S2113: Determine the target value of the control parameter based on the sub-parameter value corresponding to at least one control index related to the control parameter and the weight value corresponding to the at least one control index.

[0092] In this embodiment, at least one control index related to the control parameters can be a safety index, or it can be a combination of a safety index and a comfort index; no limitation is made here.

[0093] In an example where at least one control indicator is a safety indicator, the sub-parameter value corresponding to the safety indicator can be determined based on the current road parameters of the road where the vehicle is located and the current driving speed of the vehicle. Then, the target value of the control parameter can be determined based on the sub-parameter value and the weight value corresponding to the safety indicator.

[0094] In one embodiment, the weight value corresponding to the at least one control index is determined based on a first acceleration value of the vehicle, which is determined based on the driving environment data and the vehicle's autonomous vehicle status information.

[0095] In this embodiment, the vehicle's onboard unit (OBU) can determine the vehicle's first acceleration value based on motion data of moving objects around the vehicle and the vehicle's own state information, serving as an estimated value for the vehicle's first acceleration value in the next stage. The first acceleration value includes a longitudinal acceleration value, which characterizes the vehicle's speed in the driving direction.

[0096] Vehicle status information can include driving speed, wheel speed, wheel cylinder pressure, active suspension damping force, accelerator / brake pedal opening, gear signal, longitudinal / lateral acceleration, yaw rate / center of gravity sideslip angle, slip ratio / slip ratio, etc. This vehicle status information can be collected by the vehicle's own sensors and transmitted to the vehicle's onboard unit (OBU) to allow the OBU to determine the driving environment data.

[0097] The moving objects around a vehicle can be other vehicles in the vicinity. During vehicle movement, there can be multiple other vehicles around the vehicle. For example, other vehicles in front of the vehicle, other vehicles behind the vehicle, other vehicles to the left of the vehicle, and other vehicles to the right of the vehicle. In this case, the most urgent other vehicle can be identified from the surrounding vehicles using the driving information provided by the other vehicles' OBUs; that is, the vehicle that has the greatest impact on the vehicle's driving, and this vehicle can be designated as the target object.

[0098] In one example, while the vehicle is in motion, the vehicle's onboard unit (OBU) can lock onto a target object by measuring the relative distance, speed, acceleration, etc., of other vehicles in front or in the three adjacent lanes. This target object can be the vehicle in front of the vehicle.

[0099] Based on the target object's first acceleration value and the vehicle's own state information, the vehicle's first acceleration value is determined. This first acceleration value includes a longitudinal acceleration value, which can be the acceleration value in the driving direction.

[0100] It should be noted that as the vehicle is in motion, the surrounding moving objects will change, and correspondingly, the target object locked on will also change.

[0101] After determining the first acceleration value of the vehicle, a weight value corresponding to at least one control index is determined based on the first acceleration value of the vehicle.

[0102] In some embodiments, the weight value corresponding to the at least one control index is determined based on the ratio between the first acceleration value and the boundary acceleration value.

[0103] In some embodiments, the control indicators include safety indicators and comfort indicators, and the first weight corresponding to the comfort indicator and the second weight corresponding to the safety indicator can be determined based on the ratio between the first acceleration value and the boundary acceleration value.

[0104] In related technologies, when controlling active suspension, only comfort requirements are considered. However, in some operating conditions where increased vehicle grip is required, safety is far more important than comfort. Therefore, the active suspension control in related technologies is relatively simple and not comprehensive enough.

[0105] In this embodiment, the control indicators include comfort indicators and safety indicators. The weight values ​​corresponding to the control indicators include a first weight corresponding to the comfort indicator and a second weight corresponding to the safety indicator. The first weight corresponding to the comfort indicator can be represented as α, and the second weight corresponding to the safety indicator can be represented as β. The sum of the first weight α and the second weight β is 1. The first weight and the second weight are between 0 and 1. The control of the active suspension comprehensively considers both the safety indicator and the comfort indicator.

[0106] The first and second weights are determined based on the vehicle's first acceleration value and the boundary acceleration value. There is a certain correspondence between the first acceleration value and the boundary acceleration value.

[0107] In some embodiments, when the first acceleration value is positive, the boundary acceleration value is the first boundary acceleration value. When the first acceleration value is negative, the boundary acceleration value is the second boundary acceleration value.

[0108] In one example, the first acceleration value is positive, that is, |a g The corresponding boundary acceleration value is the first boundary acceleration value, i.e., |a j1 |, the first acceleration value is negative, that is, -|a g The corresponding boundary acceleration value is the second boundary acceleration value, i.e., -|a|. j2 If the first acceleration is positive, the ratio between the first acceleration value and the first boundary acceleration value is: This determines the first weight α and the second weight β. If the first acceleration is negative, the ratio between the first acceleration value and the second boundary acceleration value is: Thus, the first weight α and the second weight β are determined.

[0109] In one example, the shock absorber is a magnetorheological shock absorber, and the control parameter is current, as shown in Table 1. The first control data reflects the first numerical correspondence between the sub-parameter values ​​(current) corresponding to road grade, driving speed, and comfort index, as shown in Table 2. The second control data reflects the second numerical correspondence between the sub-parameter values ​​(current) corresponding to road grade, driving speed, and safety index. Therefore, the first sub-parameter value i corresponding to the comfort index can be found in Tables 1 and 2 based on the road grade and vehicle speed. X1 and the second sub-parameter value i corresponding to the security index DX1 Then, based on the first acceleration, determine the first weight α corresponding to the comfort index and the second weight β corresponding to the safety index, and determine the target value of the control parameter: i1 = αi X1 +βi DX1 .

[0110] In one embodiment, the control parameter-driving data relationship corresponding to the control index includes sub-parameter values ​​of the control parameter corresponding to each of a plurality of numerical combinations, wherein the numerical combinations consist of road parameters and driving speed, and the sub-parameter values ​​of the control parameter corresponding to the numerical combinations are determined under the driving conditions of the numerical combinations with the objective of optimizing the characterization value of the corresponding control index.

[0111] In practice, the relationship between the control parameters and driving data corresponding to the comfort index can be constructed in the following steps S3100 and S3200.

[0112] Step S3100: For each of the various combinations of road parameters and driving speed, determine the sub-parameter values ​​of the control parameters corresponding to the combination of values ​​with the goal of optimizing the characterization value of the comfort index.

[0113] In this embodiment, the road parameter can be the road grade.

[0114] In one example, the road grades include eight levels: A, B, C, D, E, F, G, and H. Driving speeds range from 0 to 120 km / h, divided into 25 groups of speeds in 5 km / h increments: 0, 5, 10...110, 115, and 120 km / h. A numerical combination can be created by randomly selecting one road grade and one driving speed value, resulting in 200 possible combinations. For each numerical combination, a comfort index is calculated.

[0115] In one embodiment, the characteristic value of the comfort index includes the root mean square value of the total acceleration of the vehicle, which is the root mean square value of the vertical acceleration of the vehicle body and the root mean square value of the pitch acceleration of the vehicle body.

[0116] In some examples, a five-degree-of-freedom vehicle model can be built, such as... Figure 2 As shown, the vertical motion of the vehicle body, the longitudinal motion of the vehicle body, the pitch motion of the vehicle body, the vertical motion of the front wheels, and the vertical motion of the rear wheels are substituted into the control model of the active suspension.

[0117] Based on the five-degree-of-freedom vehicle model, the root mean square value of the vertical acceleration a of the vehicle body can be calculated using formula (1). ZC :

[0118]

[0119] Among them, X s This represents the longitudinal displacement of the vehicle body, which is related to the damping force of the active suspension shock absorbers.

[0120] The root mean square value of the vehicle pitch acceleration a is calculated using formula (2). FY :

[0121]

[0122] Where θ is the pitch angle of the vehicle body, which is related to the damping force of the shock absorbers in the active suspension.

[0123] The root mean square value of total acceleration a HZ The calculation formula (3) is as follows:

[0124]

[0125] As can be seen from formulas (1), (2) and (3), the root mean square value of total acceleration is a value related to the damping force of the active suspension shock absorber. For each combination of values, the first damping force of the optimized shock absorber is obtained by reducing the root mean square value of the vehicle's total acceleration.

[0126] In these examples, the formula for calculating the damping force of the shock absorber in the active suspension model is as follows:

[0127]

[0128] Among them, F c For the damping force of the shock absorber, z c For the displacement of the shock absorber piston, A is the piston speed of the damper, a1 is the shear force coefficient, a2 is the damping correlation coefficient of the damper before yielding, a3 is the damping correlation coefficient of the damper after yielding, and a4 is the critical coefficient. a1, a2, a3, and a4 are all related to the input current of the damper.

[0129] By using the calculation formula of the damper's damping force in the active suspension model, the correspondence between the damper's damping force and the damper's input current can be obtained. Based on this correspondence and the optimized first damping force, the first value of the current corresponding to the optimized first damping force is determined, that is, the sub-parameter value of the control parameter.

[0130] In other examples, it is possible to establish, such as Figure 3 The seven-degree-of-freedom model is shown. The seven-degree-of-freedom model includes the vertical motion of the vehicle body, the longitudinal motion of the vehicle body, the pitch motion of the vehicle body, the vertical motion of the front wheels, the vertical motion of the rear wheels, the rotation of the front wheels, and the rotation of the rear wheels. Substituting the seven-degree-of-freedom model into the control model of the active suspension, the expression for the root mean square of the total acceleration is solved.

[0131] Step S3200: Based on the sub-parameter values ​​of the control parameters corresponding to each numerical combination, obtain the control parameter-driving data relationship corresponding to the comfort index.

[0132] Continuing with the example above, after obtaining the sub-parameter values ​​of the current corresponding to 200 numerical combinations, the first control data is obtained, as shown in Table 1 above.

[0133] The relationship between control parameters and driving data corresponding to safety indicators can be constructed in the following steps S4100 and S4200.

[0134] Step S4100: For each of the various combinations of road parameters and driving speed, with the goal of optimizing the characterization value of the safety index, determine the sub-parameter value of the control parameter corresponding to the combination of values.

[0135] In this embodiment, the multiple combinations of road parameters and driving speed in the second control data are the same as the multiple combinations of values ​​in the first control data. That is, when the first control data includes 200 combinations of values, the second control data also includes 200 combinations of values.

[0136] In one embodiment, the characteristic value of the safety index includes the root mean square value of the total wheel dynamic load of the vehicle, wherein the root mean square value of the total wheel dynamic load is the root mean square value of the dynamic load of the front axle wheels and the dynamic load of the rear axle wheels.

[0137] In one example, the root mean square value of the dynamic load Z on the front axle wheel is calculated using formula (4). m :

[0138]

[0139] Among them, Z t1 Vertical displacement of unsprung mass on the front axle, Z r1 The front axle ground displacement is related to the damping force of the active suspension shock absorbers.

[0140] The root mean square value of the dynamic load Z of the rear axle wheel is calculated using formula (5). n :

[0141]

[0142] Among them, Z t2 Vertical displacement of unsprung mass on rear axle, Z r2 The rear axle ground displacement is related to the damping force of the active suspension shock absorber.

[0143] The root mean square value of the total wheel dynamic load can be expressed as:

[0144]

[0145] According to formulas (4), (5) and (6), for each combination of values, the optimized second damping force is obtained by taking the root mean square value of the total wheel dynamic load of the vehicle as the optimization objective.

[0146] Based on the optimized second damping force and the correspondence between damping force and current in the active suspension model, the second value of the current corresponding to the numerical combination is determined.

[0147] Step S4200: Based on the sub-parameter values ​​of the control parameters corresponding to each numerical combination, obtain the control parameter-driving data relationship corresponding to the safety index.

[0148] Continuing with the example above, after obtaining the second value of the current corresponding to the 200 numerical combinations, the second control data is obtained, as shown in Table 2 above.

[0149] It should be noted that in the process of optimizing the root mean square value of total acceleration and the root mean square value of total wheel dynamic load, the following constraints must also be met: a. The control current must be within the actual allowable current range of the shock absorber; b. The suspension dynamic travel must not exceed the maximum value of the system; c. The wheel dynamic load must not exceed the wheel static load.

[0150] In some embodiments, when the vehicle is not in a specific operating condition, the weight corresponding to the at least one control index is determined based on the ratio between the first acceleration value and the boundary acceleration value.

[0151] In this embodiment, the vehicle's operating conditions include rapid acceleration, gradual acceleration, rapid deceleration, gradual deceleration, traction control, and anti-lock braking. Specific operating conditions include traction control activation and anti-lock braking activation. Rapid acceleration is defined as a situation where the target object's first acceleration is positive and greater than a first threshold acceleration. Gradual acceleration is defined as a situation where the target object's first acceleration is positive and less than or equal to the first threshold acceleration. Gradual deceleration is defined as a situation where the target object's first acceleration is negative and greater than a second threshold acceleration. Rapid deceleration is defined as a situation where the target object's first acceleration is negative and less than or equal to the second threshold acceleration. Specific operating conditions can be initiated based on user control or by the vehicle's automatic activation; this is not limited here.

[0152] When the vehicle is not under specific operating conditions, i.e., under any of the following conditions: rapid acceleration, gradual acceleration, rapid deceleration, and gradual deceleration, at least one control indicator includes a safety indicator and a comfort indicator. In this case, a first weight corresponding to the comfort indicator and a second weight corresponding to the safety indicator are determined based on the first acceleration value and the threshold acceleration value.

[0153] It should be noted that when the vehicle is in rapid acceleration, gradual acceleration, or traction control mode, the drive system outputs the target driving force to propel the vehicle. When the vehicle is in rapid deceleration, gradual deceleration, or anti-lock braking mode, the braking system outputs the target braking force to brake the vehicle.

[0154] According to an embodiment of this application, by determining the weight of the at least one control index based on the ratio between the first acceleration value and the boundary acceleration value when the vehicle is not under specific operating conditions, the accuracy of active suspension control can be further improved.

[0155] In some embodiments, when the vehicle is in a specific operating condition, the target value of the control parameter is determined based on the sub-parameter value corresponding to a certain control index; the specific operating condition is one of the operating condition of traction control activation and anti-lock braking activation, and the certain control index is a safety index.

[0156] In this embodiment, the specific operating condition is one of the conditions for activating traction control and activating anti-lock braking. The specific operating condition can be triggered automatically by the vehicle or actively by the driver. When the vehicle is in the specific operating condition, the second weight is 1, and the control of the active suspension is primarily based on safety indicators. That is, according to the road parameters, vehicle speed, and the control parameter-driving data relationship corresponding to the safety indicators (i.e., the second control data shown in Table 2), the sub-parameter values ​​of the control parameters corresponding to the current road parameters and current driving speed are determined. The control parameter-driving data relationship corresponding to the safety indicators reflects the numerical correspondence between the corresponding sub-parameters (current) and the road parameters and driving speed under the constraints of the safety indicators.

[0157] When the vehicle is under specific operating conditions, and comfort is disregarded while safety is the primary concern, the target value of the control parameter is: i2 = i DX2 .

[0158] Figure 5 An active suspension control method for a vehicle according to other embodiments is shown, which can also be implemented by the vehicle's active suspension control device. For example... Figure 5 As shown, the control method may include steps S1 to S9.

[0159] Step S1: Obtain vehicle driving environment data. The driving environment data is determined based on the transmission data of external devices, and the vehicle communicates with external devices based on the V2X system.

[0160] In this example, the driving environment data includes either the motion data of moving objects around the vehicle or the road data of the road where the vehicle is located.

[0161] Step S2: Is the vehicle under a specific operating condition? If yes, proceed to step S3; otherwise, proceed to step S7.

[0162] In this example, the specific operating condition is one of the conditions for activating traction control and activating anti-lock braking.

[0163] Step S3: Determine the first weight corresponding to the comfort index and the second weight corresponding to the safety index based on the ratio between the longitudinal acceleration value and the boundary acceleration value; wherein the longitudinal acceleration value is obtained based on the vehicle's self-state information and driving environment data.

[0164] In some examples, when the longitudinal acceleration value is positive, the boundary acceleration value is the first boundary acceleration value. When the longitudinal acceleration value is negative, the boundary acceleration value is the second boundary acceleration value.

[0165] Step S4: Based on the road parameters, vehicle speed values, and first control data corresponding to comfort indicators, determine the first target value of the control parameters corresponding to the road parameters and speed values.

[0166] In this example, the first control data can characterize the relationship between control parameters and driving data corresponding to the comfort index, as shown in Table 1 above. The first control data reflects the numerical correspondence between the corresponding sub-parameters, road parameters, and driving speed under the constraints of the comfort index.

[0167] In some examples, the step of obtaining the first control data includes: for each of a variety of numerical combinations of road parameters and driving speed values, determining a first value of the control parameter corresponding to the numerical combination, with the optimization objective of reducing the root mean square value of the vehicle's total acceleration. Here, the root mean square value of the total acceleration is the root mean square value of the vehicle's vertical acceleration and the root mean square value of the vehicle's pitch acceleration. Based on the first value of the control parameter corresponding to each numerical combination, the first control data is obtained.

[0168] Step S5: Based on the road parameters, vehicle speed values, and the second control data corresponding to the safety indicators, determine the second target value of the control parameters corresponding to the road parameters and speed values.

[0169] In this example, the second control data can characterize the relationship between control parameters and driving data corresponding to the safety index. It reflects the numerical correspondence between the corresponding sub-parameters, road parameters, and driving speed under the constraints of the safety index.

[0170] In some examples, the steps for obtaining the second control data include: for each of a variety of combinations of road parameters and driving speed values, determining a second value for the control parameter corresponding to the combination of values, with the optimization objective of reducing the root mean square value of the total wheel dynamic load of the vehicle. Here, the root mean square value of the total wheel dynamic load is the root mean square value of the root mean square values ​​of the front axle wheel dynamic load and the rear axle wheel dynamic load. The second control data is obtained based on the second value of the control parameter corresponding to each combination of values.

[0171] Step S6: Determine the target value of the control parameter based on the first target value, the second target value, the first weight, and the second weight. Then, proceed to step S9.

[0172] Step S7: Based on the road parameters, vehicle speed values, and the second control data corresponding to the safety indicators, determine the second target value of the control parameters corresponding to the road parameters and speed values. Then, proceed to step S8.

[0173] Step S8: Set the second target value as the target value of the control parameter, and then execute step S9.

[0174] Step S9: Adjust the damping force of the active suspension based on the target value of the control parameters to obtain the target damping force corresponding to the target value.

[0175] In some embodiments, such as Figure 6 As shown, an active suspension control device 6000 for the vehicle is also provided, which includes a data receiving module 6100 and a control module 6200.

[0176] The data receiving module 6100 is used to acquire the driving environment data of the vehicle, wherein the driving environment data is determined based on the transmission data of the external device.

[0177] The control module 6200 is used to control the active suspension of the vehicle based on the driving environment data.

[0178] In one embodiment, the vehicle communicates with the external device based on a V2X system.

[0179] In one embodiment, the driving environment data includes at least one of the motion data of moving objects around the vehicle and the road data of the road where the vehicle is located.

[0180] In one embodiment, the active suspension is controlled by a target value of a control parameter of the active suspension, the target value of which is determined based on the driving environment data. The target value of the control parameter can be used to adjust the damping force of the active suspension so that the damping force of the active suspension reaches the target damping force corresponding to the target value.

[0181] In one embodiment, the target value is determined based on the sub-parameter value corresponding to at least one control index related to the control parameter and the weight value corresponding to the at least one control index, wherein the sub-parameter value corresponding to the control index is determined based on the current road parameters of the road where the vehicle is located and the current driving speed of the vehicle, and the current road parameters are determined based on the driving environment data.

[0182] In one embodiment, the weight value corresponding to the at least one control index is determined based on a first acceleration value of the vehicle, which is determined based on the driving environment data and the vehicle's autonomous vehicle status information.

[0183] In one embodiment, the weight value corresponding to the at least one control index is determined based on the ratio between the first acceleration value and the boundary acceleration value.

[0184] In one embodiment, when the first acceleration value is positive, the boundary acceleration value is a first boundary acceleration value; when the first acceleration value is negative, the boundary acceleration value is a second boundary acceleration value.

[0185] In one embodiment, when the vehicle is not in a specific operating condition, the weight corresponding to the at least one control index is determined based on the ratio between the first acceleration value and the boundary acceleration value;

[0186] The specific operating conditions include the conditions for activating traction control and the conditions for activating anti-lock braking.

[0187] In one embodiment, when the vehicle is under a specific operating condition, the target value of the control parameter is determined based on the sub-parameter value corresponding to a certain control index; the specific operating condition is one of the operating condition of traction control activation and anti-lock braking activation, and the certain control index is a safety index.

[0188] In one embodiment, the sub-parameter value corresponding to the control index can be obtained based on the current road parameters, the current driving speed, and the control parameter-driving data relationship corresponding to the control index. The control parameter-driving data relationship reflects the numerical correspondence between the corresponding sub-parameter, the road parameters, and the driving speed under the constraints of the corresponding control index.

[0189] In one embodiment, the control parameter-driving data relationship corresponding to the control index includes sub-parameter values ​​of the control parameter corresponding to each of a plurality of numerical combinations, wherein the numerical combinations consist of road parameters and driving speed, and the sub-parameter values ​​of the control parameter corresponding to the numerical combinations are determined under the driving conditions of the numerical combinations with the objective of optimizing the characterization value of the corresponding control index.

[0190] In one embodiment, the control indicators include comfort indicators and / or safety indicators;

[0191] The characteristic value of the comfort index includes the root mean square value of the total acceleration of the vehicle, which is the root mean square value of the vertical acceleration of the vehicle body and the root mean square value of the pitch acceleration of the vehicle body.

[0192] The safety index is characterized by the root mean square value of the total wheel dynamic load of the vehicle, which is the root mean square value of the dynamic load of the front axle wheels and the dynamic load of the rear axle wheels.

[0193] In some embodiments, such as Figure 7 As shown, an active suspension control device 7000 for a vehicle is also provided. The device 7000 includes a processor connected to a memory. The processor calls the executable program code stored in the memory to execute the active suspension control method for a vehicle as described in the embodiments of this application.

[0194] In some embodiments, an active suspension system 800 is also provided, such as Figure 8 As shown, it includes an active suspension 810 and an active suspension control device 820.

[0195] The active suspension control device 820 can be as follows: Figure 6 The active suspension control device shown can also be as follows: Figure 7 The active suspension control device shown.

[0196] In some of the dead foxes, a storage medium is also provided, which stores computer instructions that, when invoked, are used to execute the active suspension control method for the vehicle described in any of the above method embodiments.

[0197] In some embodiments, a vehicle 900 is also provided, such as Figure 9 As shown, the vehicle 900 includes, for example... Figure 8 The active suspension system 800 shown, or, as... Figure 10 As shown, the vehicle 900 includes, for example Figure 6 or Figure 7 The active suspension control device shown.

[0198] This invention can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of the invention.

[0199] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination thereof. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0200] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0201] The computer program instructions used to perform the operations of this invention may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing state information from the computer-readable program instructions. This electronic circuitry can execute the computer-readable program instructions to implement various aspects of the invention.

[0202] Various aspects of the present invention are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0203] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0204] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0205] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions. It will be known to those skilled in the art that implementation in hardware, implementation in software, and implementation using a combination of software and hardware are equivalent.

[0206] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, and are not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or technical improvements to the technology in the market, or to enable others skilled in the art to understand the embodiments disclosed herein. The scope of the invention is defined by the appended claims.

Claims

1. A method for active suspension control of a vehicle, characterized in that, include: Acquire the vehicle's driving environment data; wherein the driving environment data is determined based on data transmitted from external devices; The vehicle's active suspension is controlled based on the driving environment data; The driving environment data includes motion data of moving objects around the vehicle; The active suspension is controlled according to the target value of the active suspension control parameters; wherein, based on the driving environment data and the vehicle's self-state information, a first acceleration value of the vehicle is determined, the first acceleration value includes a longitudinal acceleration value in the driving direction, the first acceleration value is used as an estimated value of the first acceleration value of the vehicle in the next stage, a weight value corresponding to at least one control index related to the control parameters is determined based on the first acceleration value, and the target value is determined based on the weight value and the sub-parameter value corresponding to the at least one control index; the at least one control index includes a safety index and a comfort index.

2. The active suspension control method according to claim 1, characterized in that, The vehicle communicates with the external devices based on a V2X system.

3. The method according to claim 1, characterized in that, The driving environment data also includes road data of the road where the vehicle is located.

4. The method according to claim 1, characterized in that, The target value of the control parameter can be used to adjust the damping force of the active suspension so that the damping force of the active suspension reaches the target damping force corresponding to the target value.

5. The method according to claim 4, characterized in that, The sub-parameter values ​​corresponding to the control index are determined based on the current road parameters of the road where the vehicle is located and the current driving speed of the vehicle. The current road parameters are determined based on the driving environment data.

6. The method according to claim 5, characterized in that, The weight value corresponding to the at least one control index is determined based on the ratio between the first acceleration value and the boundary acceleration value.

7. The method according to claim 6, characterized in that, When the first acceleration value is positive, the boundary acceleration value is the first boundary acceleration value; when the first acceleration value is negative, the boundary acceleration value is the second boundary acceleration value.

8. The method according to claim 6, characterized in that, When the vehicle is not under a specific operating condition, the weight value corresponding to the at least one control index is determined based on the ratio between the first acceleration value and the boundary acceleration value; The specific operating conditions include the conditions for activating traction control and the conditions for activating anti-lock braking.

9. The method according to claim 5, characterized in that, When the vehicle is under a specific operating condition, the target value of the control parameter is determined based on the sub-parameter value corresponding to a certain control index; the specific operating condition is one of the operating conditions of traction control activation and anti-lock braking activation, and the certain control index is a safety index.

10. The method according to any one of claims 5-9, characterized in that, The sub-parameter values ​​corresponding to the control index can be obtained based on the current road parameters, the current driving speed, and the control parameter-driving data relationship corresponding to the control index. The control parameter-driving data relationship reflects the numerical correspondence between the corresponding sub-parameters, road parameters, and driving speed under the constraints of the corresponding control index.

11. The method according to claim 10, characterized in that, The control parameter-driving data relationship corresponding to the control index includes sub-parameter values ​​of the control parameter corresponding to each of a variety of numerical combinations, wherein the numerical combination consists of road parameters and driving speed, and the sub-parameter values ​​of the control parameter corresponding to the numerical combination are determined under the driving conditions of that numerical combination with the goal of optimizing the characterization value of the corresponding control index.

12. The method according to claim 11, characterized in that, The characteristic value of the comfort index includes the root mean square value of the total acceleration of the vehicle, which is the root mean square value of the vertical acceleration of the vehicle body and the root mean square value of the pitch acceleration of the vehicle body. The safety index is characterized by the root mean square value of the total wheel dynamic load of the vehicle, which is the root mean square value of the dynamic load of the front axle wheels and the dynamic load of the rear axle wheels.

13. An active suspension control device for a vehicle, characterized in that, include: A data receiving module is used to acquire driving environment data of the vehicle; wherein the driving environment data is determined based on data transmitted from external devices; The control module is used to control the vehicle's active suspension based on the driving environment data. The driving environment data includes motion data of moving objects around the vehicle; The active suspension is controlled according to the target value of the active suspension control parameters; wherein, based on the driving environment data and the vehicle's self-state information, a first acceleration value of the vehicle is determined, the first acceleration value includes a longitudinal acceleration value in the driving direction, the first acceleration value is used as an estimated value of the first acceleration value of the vehicle in the next stage, a weight value corresponding to at least one control index related to the control parameters is determined based on the first acceleration value, and the target value is determined based on the weight value and the sub-parameter value corresponding to the at least one control index; the at least one control index includes a safety index and a comfort index.

14. An active suspension control device for a vehicle, characterized in that, The system includes a processor connected to a memory; the processor calls executable program code stored in the memory to execute the active suspension control method for a vehicle according to any one of claims 1 to 12.

15. An active suspension system, characterized in that, The system includes the apparatus of claim 13 or 14, and the system further includes an active suspension.

16. A storage medium, characterized in that, The storage medium stores computer instructions, which, when invoked, are used to execute the active suspension control method for the vehicle as described in any one of claims 1-12.

17. A vehicle, characterized in that, Includes the device as described in claim 13 or 14, or the active suspension system as described in claim 15.

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