CN117698357A

CN117698357A - Air spring control method, system and equipment

Info

Publication number: CN117698357A
Application number: CN202410065767.6A
Authority: CN
Inventors: 陈勇; 陈佳俊; 朱江风; 杨芳燃
Original assignee: Zhejiang Gates Industrial Technology Co ltd
Current assignee: Zhejiang Gates Industrial Technology Co ltd
Priority date: 2024-01-16
Filing date: 2024-01-16
Publication date: 2024-03-15

Abstract

The application is applicable to the technical field of air spring control, and particularly relates to an air spring control method, an air spring control system and air spring control equipment, wherein the air spring control method comprises the following steps: the driving condition of the vehicle is identified, and the actual driving environment of the vehicle is known, so that the air spring can be controlled according to the actual driving environment better. Based on the recognized driving situation of the vehicle, an air spring control target is further obtained, and the air spring control target is used for reflecting the control effect to be achieved, thereby being beneficial to the actual control of the air spring. The air spring control parameter is determined according to the air spring control target, and is an actual control parameter and a parameter which directly influences the performance of the air spring. Based on the air spring control parameters, the air spring is actually regulated and controlled, so that the air spring is controlled according to different running environments, the running stability of the vehicle is improved, the riding comfort is improved, and the maintenance cost of the vehicle is reduced.

Description

Air spring control method, system and equipment

Technical Field

The application belongs to the technical field of air spring control, and particularly relates to an air spring control method, an air spring control system and air spring control equipment.

Background

An air spring is a suspension system that uses an air bag in place of a conventional metal spring. Such suspension systems use gas (typically air) to provide suspension support rather than conventional metal springs or coil springs.

In the prior art, the control of the air spring is mainly controlled by simple sensing data, the intelligent degree is low, the control cannot be performed according to different driving environments, the running stability of the vehicle is reduced, the riding comfort is affected, and the maintenance cost of the vehicle is increased.

Disclosure of Invention

The embodiment of the application provides an air spring control method, an air spring control system and an air spring control device, which can solve the problems that the air spring cannot be controlled according to different driving environments, so that the running stability of a vehicle is reduced, the riding comfort is affected, and the maintenance cost of the vehicle is increased.

In a first aspect, an embodiment of the present application provides an air spring control method, including:

identifying a driving situation of the vehicle;

based on the driving condition of the vehicle, obtaining an air spring control target; the air spring control target is used for reflecting a control effect to be achieved;

determining an air spring control parameter according to the air spring control target;

And based on the air spring control parameters, carrying out actual adjustment control on the air spring.

The technical scheme in the embodiment of the application has at least the following technical effects:

according to the air spring control method, the actual driving environment of the vehicle is known by identifying the driving condition of the vehicle, so that the air spring can be controlled better according to the actual driving environment. Based on the recognized driving situation of the vehicle, an air spring control target is further obtained, and the air spring control target is used for reflecting the control effect to be achieved, thereby being beneficial to the actual control of the air spring. The air spring control parameter is determined according to the air spring control target, and is an actual control parameter and a parameter which directly influences the performance of the air spring. Based on the air spring control parameters, the air spring is actually regulated and controlled, so that the air spring is controlled according to different running environments, the running stability of the vehicle is improved, the riding comfort is improved, and the maintenance cost of the vehicle is reduced.

In a possible implementation manner of the first aspect, the identifying a driving situation of the vehicle includes:

acquiring radar information of a vehicle;

Constructing a vehicle driving prediction road condition model based on the vehicle radar information; the vehicle driving prediction road condition model is a data model for reflecting road conditions;

and obtaining the vehicle driving prediction road condition model based on the result of constructing the vehicle driving prediction road condition model.

In a possible implementation manner of the first aspect, the constructing a vehicle driving prediction road condition model based on the vehicle radar information includes:

analyzing radar reflected signals based on the vehicle radar information;

obtaining a road surface obstacle condition based on the result of the analysis of the radar reflected signal;

calculating a road surface obstacle rate based on the road surface obstacle condition; wherein the road surface obstacle rate is used for reflecting road surface bump conditions;

obtaining the road surface obstacle rate of unit displacement based on the result of calculating the road surface obstacle rate;

and constructing a vehicle driving prediction road condition model based on the road surface obstacle rate of the unit displacement.

The identifying the driving situation of the vehicle further comprises:

matching a vehicle driving scene according to a preset rule based on the vehicle driving prediction road condition model;

and obtaining the driving situation of the vehicle based on the result of matching the driving scene of the vehicle according to the preset rule.

In one possible implementation manner of the first aspect, the matching the vehicle driving scenario according to the preset rule based on the vehicle driving prediction road condition model includes:

matching corresponding driving scene mapping intervals based on the numerical value of the vehicle driving prediction road condition model;

and obtaining the driving scene of the vehicle based on the result of the corresponding driving scene mapping interval.

In one possible implementation manner of the first aspect, the obtaining an air spring control target based on the driving situation of the vehicle includes:

based on the vehicle driving scene, acquiring a corresponding optimal air spring expansion control interval value;

acquiring a current air spring expansion control value;

and obtaining an air spring control target based on the optimal air spring expansion control interval value and the current air spring expansion control value.

In a possible implementation manner of the first aspect, the determining, according to the air spring control target, an air spring control parameter includes:

acquiring an air spring control relation model; the air spring control relation model is used for reflecting the association relation between an air spring control target and control parameters;

And determining the air spring control parameters according to the air spring control target and the air spring control relation model.

In a possible implementation manner of the first aspect, the acquiring an air spring control relationship model includes:

acquiring a plurality of air spring sample control parameter sets;

controlling the air springs to be tested by utilizing each air spring sample control parameter set to obtain a plurality of corresponding air spring control data sets;

obtaining different comfort quantitative scores corresponding to the air spring control data sets under different air pressure change rates;

and performing data fitting on the comfort quantitative score and the corresponding air spring sample control parameter set to obtain the air spring control relation model.

In a possible implementation manner of the first aspect, the determining the air spring control parameter according to the air spring control target and the air spring control relation model includes:

acquiring a current air spring air pressure value;

based on the current air spring air pressure value and an air spring control target, an air pressure variation interval is obtained;

obtaining an optimal air pressure change rate based on the air spring control relation model;

And determining an air spring control parameter based on the air pressure variation interval and the optimal air pressure variation rate.

In a second aspect, embodiments of the present application provide an air spring control system comprising:

the identifying unit is used for identifying the driving condition of the vehicle;

the acquisition unit is used for acquiring an air spring control target based on the driving condition of the vehicle; the air spring control target is used for reflecting a control effect to be achieved;

a confirmation unit, configured to determine an air spring control parameter according to the air spring control target;

and the control unit is used for carrying out actual adjustment control on the air spring based on the air spring control parameters.

In a third aspect, embodiments of the present application provide an air spring control apparatus comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor implementing the method according to any one of the first aspects when executing the computer program.

In a fourth aspect, embodiments of the present application provide a computer program product for, when run on a terminal device, causing the terminal device to perform the method of any one of the first aspects described above.

It will be appreciated that the advantages of the second to fourth aspects may be found in the relevant description of the first aspect and are not repeated here.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following description will briefly introduce the drawings that are needed in the embodiments or the description of the prior art, it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart of an air spring control method according to an embodiment of the present disclosure;

FIG. 2 is a flowchart of step S100 in an air spring control method according to an embodiment of the present disclosure;

FIG. 3 is a flowchart of step S120 of an air spring control method according to an embodiment of the present disclosure;

FIG. 4 is another flow chart of step S100 of an air spring control method according to an embodiment of the present application;

FIG. 5 is a flowchart of step S140 of an air spring control method according to an embodiment of the present disclosure;

FIG. 6 is a flowchart of step S200 of an air spring control method according to an embodiment of the present disclosure;

FIG. 7 is a flowchart of step S300 of an air spring control method according to an embodiment of the present disclosure;

FIG. 8 is a flowchart of step S310 of an air spring control method according to an embodiment of the present disclosure;

FIG. 9 is a flowchart of step S320 of an air spring control method according to an embodiment of the present disclosure;

FIG. 10 is a schematic diagram of an air spring control system according to one embodiment of the present application;

fig. 11 is a schematic structural view of an air spring control apparatus according to an embodiment of the present application.

Description of the embodiments

In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system configurations, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

It should also be understood that the term "and/or" as used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.

As used in this specification and the appended claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]".

In addition, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used merely to distinguish between descriptions and are not to be construed as indicating or implying relative importance.

Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.

In order to solve the above problems, embodiments of the present application provide a method, a system, and an apparatus for controlling an air spring. In the method, the actual driving environment of the vehicle is known by identifying the driving condition of the vehicle, so that the air spring is better controlled according to the actual driving environment. Based on the recognized driving situation of the vehicle, an air spring control target is further obtained, and the air spring control target is used for reflecting the control effect to be achieved, thereby being beneficial to the actual control of the air spring. The air spring control parameter is determined according to the air spring control target, and is an actual control parameter and a parameter which directly influences the performance of the air spring. Based on the air spring control parameters, the air spring is actually regulated and controlled, so that the air spring is controlled according to different running environments, the running stability of the vehicle is improved, the riding comfort is improved, and the maintenance cost of the vehicle is reduced.

The air spring control method provided by the embodiment of the application can be applied to terminal equipment, and the terminal equipment is the execution main body of the air spring control method provided by the embodiment of the application, and the embodiment of the application does not limit the specific type of the terminal equipment.

For example, the terminal device may be an automobile control system (which may include an onboard controller of an automobile), an onboard device, an augmented reality (augmented reality, AR)/Virtual Reality (VR) device, a computing device or other processing device connected to a wireless modem, an internet of vehicles terminal, a computer, or the like. The air spring may be a variety of types of vehicle-mounted controllable air springs, and may include, for example, an air spring assembly, a sensor, an Electronic Control Unit (ECU), a valve, an air pump, and the like.

In order to better understand the air spring control method provided by the embodiment of the present application, the following exemplary description is provided for a specific implementation procedure of the air spring control method provided by the embodiment of the present application.

Fig. 1 shows a schematic flowchart of an air spring control method provided in an embodiment of the present application, where the air spring control method includes:

s100, identifying the driving condition of the vehicle.

It will be appreciated that vehicle driving conditions refer to the external environment and conditions surrounding the vehicle, which factors affect driving versus air spring control data and are important indicators directly affecting air spring control parameters. The recognition of the driving situation of the vehicle may use various sensors and cameras to capture the environment around the vehicle and analyze and process these data through preset algorithms.

In one possible implementation, referring to fig. 2, S100, identifying a driving situation of a vehicle includes:

s110, acquiring vehicle radar information.

It is understood that radar sensors are commonly used to detect objects in the surrounding environment, including other vehicles, pedestrians, obstacles, etc., and to provide such information for use by the vehicle system. The radar sensor is typically connected to a control system of the vehicle, transmitting detected object information to the vehicle control unit. By accessing the Electronic Control Unit (ECU) of the vehicle, raw data or processed information of the radar sensor may be acquired, which acquired data will be used for subsequent analysis.

S120, constructing a vehicle driving prediction road condition model based on vehicle radar information; the vehicle driving prediction road condition model is a data model for reflecting road conditions.

It can be understood that the obtained radar data can be used for carrying out corresponding processing on the actual driving environment of the vehicle according to a preset rule or algorithm, so as to construct a data model capable of reflecting road conditions, namely a vehicle driving prediction road condition model. This model is the key for the terminal equipment to recognize the driving environment.

Optionally, referring to fig. 3, S120, constructing a vehicle driving prediction road condition model based on the vehicle radar information includes:

s121, analyzing radar reflection signals based on vehicle radar information.

It will be appreciated that the acquired radar data may be used to analyze obstructions on the road surface. The radar sensor is capable of detecting objects around the vehicle, including small obstacles on the road surface, by emitting radio waves and receiving the reflections thereof. The reflected signal strength of the obstruction may provide information about the material and shape of the object. A higher reflected signal may represent a small obstruction of a relatively hard or metallic material. The obstacle on the road surface can be distinguished by different threshold intervals based on the radar reflection signal by setting a threshold rule. The obstacle is classified into various categories, such as a group I obstacle, a group II obstacle, a large object, a small object, a soft obstacle, and a hard obstacle. Different types of obstacles reflect different road surface condition effects. For example, when the shape size information of a certain object is recognized to be greater than a certain threshold value, it is regarded as a class I obstacle, and when it is recognized to be greater than a larger threshold value, it is regarded as a class II obstacle, and based on this, the number information of the types of obstacles is determined.

S122, obtaining the road surface obstacle condition based on the result of analyzing the radar reflection signals.

It can be understood that various types of obstacles and the quantity information thereof in the range of the radar detection area can be obtained through analysis of radar data, and the data represent road obstacle conditions. The accurate interpretation of the data is helpful for the terminal equipment to make timely response according to the actual road condition, so that the driving safety and the driving comfort are improved.

S123, calculating a road surface obstacle rate based on the road surface obstacle condition; wherein the road surface obstacle rate is used for reflecting the road surface bumping condition.

It is understood that the road surface Obstacle Rate (Obstacle Rate) is the proportion of road surface obstacles detected during running of the vehicle. The road obstruction rate reflects the probability or strength of road jolt under certain conditions. The road surface obstacle condition obtained by radar analysis can be used for counting the number of obstacles and the type of the obstacles detected in front of or around the vehicle. The obstacles are classified into different categories, such as a class I obstacle, a class II obstacle, a large object, a small object, a soft obstacle, a hard obstacle, and the like. Different types of obstacles may have different degrees of impact on road jolts.

S124, obtaining the road surface obstacle rate of unit displacement based on the result of calculating the road surface obstacle rate.

It will be appreciated that the method for calculating the road surface obstruction rate may be designed in advance by an algorithm, for example, the algorithm formula for calculating the road surface obstruction rate may be: y=n/D, Y is the road surface obstacle rate per unit displacement, N is the total number of obstacles within the radar detection range distance, and D is the radar detection range distance. This formula represents the average number of obstacles detected per unit radar detection distance. Since the vehicle running and the radar can be regarded as a whole, the unit road surface obstacle rate calculated based on the radar detection range can be regarded as a unit displacement road surface obstacle rate displacement in which the vehicle is running. The road surface obstacle rate of unit displacement is a relative index, and the specific value of the road surface obstacle rate may be affected by a plurality of factors such as road conditions, sensor accuracy, obstacle properties and the like. Thus, in different applications, a scaling parameter K may be set for the formula for tuning and optimization according to different situations. For example y=k×n/D. The resulting road surface obstruction rate is data reflecting road surface jolt conditions.

S125, constructing a vehicle driving prediction road condition model based on the road surface obstacle rate of the unit displacement.

It can be understood that the road obstacle rate of unit displacement is considered to be the number of road obstacles per unit displacement, according to this data, the average change condition in the continuous interval period of the road obstacles in the vehicle driving process can be constructed, and a set of prediction models can be preset based on mathematical statistical rules to construct the vehicle driving prediction road condition model, i.e. the actual model. For example, the actual model for constructing the predicted road condition of the vehicle driving can be a linear regression model, a Bayesian regression, a ridge regression, a lasso regression, etc.

S130, obtaining a vehicle driving prediction road condition model based on the result of constructing the vehicle driving prediction road condition model.

It can be understood that the prediction model based on the preset rule can input the road obstacle rate of unit displacement into the model, and obtain the data condition of average change in the continuous interval time period of the road obstacle in the vehicle driving process according to the rule of the model, so as to obtain the vehicle driving prediction road condition model, wherein the model is embodied by a mathematical model and finally embodied in a series of dynamic numerical forms. It reflects the average change in road surface jolt conditions, with a larger value indicating a road surface jolt and a smaller value indicating a road surface flatter.

In one possible implementation, referring to fig. 4, S100, identifying a driving situation of the vehicle further includes:

and S140, matching the driving scene of the vehicle according to a preset rule based on the driving prediction road condition model of the vehicle.

It can be appreciated that the threshold interval of the road condition model predicted by the driving of the vehicle may be preset to divide different driving scenarios. For example, the driving scene may be a highway, a city street, a mountain road, or the like. Each scene has different road condition characteristics and driving requirements, and can be embodied through a threshold interval of a vehicle driving prediction road condition model.

Optionally, referring to fig. 5, S140, based on a vehicle driving prediction road condition model, matching a vehicle driving scene according to a preset rule includes:

s141, matching corresponding driving scene mapping intervals based on the numerical value of the vehicle driving prediction road condition model.

It can be appreciated that, based on the values of the vehicle driving prediction road condition model, a set of mapping rules can be designed in advance to map the output of the model to the corresponding driving scene interval. The rules of this mapping may be based on the values of the vehicle driving prediction road condition model, e.g. assigning different driving scenarios to different scenario mapping intervals. Different driving scenario mapping intervals are divided, for example:

Section 1 is mountain road.

Section 2, urban road.

Section 3, expressway.

The set rules map the output of the model to different driving scenario intervals. This may be based on a set threshold for a vehicle driving prediction road condition model, such as:

if the model number is between 0 and 10, it is mapped to the "highway" interval.

If the model output probability is between 10 and 60, mapping to an "urban road" section.

If the model output probability is between 60 and 100, mapping to a "mountain road" interval.

And S142, obtaining a vehicle driving scene based on the result of matching the corresponding driving scene mapping interval.

It can be understood that according to the set mapping rule, the numerical value of the vehicle driving prediction road condition model is mapped to the corresponding driving scene, and the mapped driving scene result is output. According to the mapped driving scene, the driving strategy is adjusted correspondingly, so that the driving strategy is suitable for different road conditions. This contributes to improvement in safety and efficiency of driving.

And S150, obtaining the driving situation of the vehicle based on the result of matching the driving scene of the vehicle according to the preset rule.

It can be understood that the numerical value of the vehicle driving prediction road condition model can be mapped to a corresponding driving scene to serve as a vehicle driving condition, so that a basis is provided for subsequent parameter control. The advantage of mapping is its simplicity and interpretability. According to the range of the model output values, the driving scene of the vehicle can be intuitively known.

S200, obtaining an air spring control target based on the driving condition of the vehicle; the air spring control target is used for reflecting the control effect to be achieved.

It will be appreciated that different driving scenarios may require different suspension settings. For example, on highways, it may be desirable for the vehicle suspension to be more stable; while traveling over rough mountains, comfort and suspension adjustability may be more important. Therefore, different air spring control targets can be designated in advance for different driving scenes, so as to achieve the purpose of adapting the suspension to environmental changes.

In one possible implementation, referring to fig. 6, S200, obtaining an air spring control target based on a driving situation of a vehicle includes:

s210, acquiring a corresponding optimal air spring expansion control interval value based on a vehicle driving scene.

It will be appreciated that the optimum air spring extension control interval value refers to a range of values that provide optimum drivability and comfort through air spring extension parameters under given driving conditions. This optimal interval value is data that depends on different driving scenarios, road conditions and other driving factors and that has been tested before the air suspension installation. A set of mapping rules can be formulated in advance, the optimal air spring expansion control interval values corresponding to different driving scenes are associated, and when the current driving scene is determined, the corresponding optimal air spring expansion control interval values can be obtained through the mapping rules.

S220, acquiring a current air spring expansion control value.

It will be appreciated that the current telescoping control value may be obtained by a control unit connected to the vehicle's Electronic Control Unit (ECU) or to the suspension system. The current air spring expansion control value is obtained, so that the vehicle performance is optimized, the driving comfort and the driving safety are improved, and the vehicle can be better adapted to different driving environments and the requirements of drivers.

And S230, obtaining an air spring control target based on the optimal air spring expansion control interval value and the current air spring expansion control value.

It will be appreciated that the optimal air spring extension control interval value may be compared to the current air spring extension control value. The difference between these two values can be used to determine the degree of deviation of the current state of the suspension system from the optimal state. And formulating an adjustment strategy according to the comparison result. And if the current control value deviates from the optimal value, obtaining a corresponding control target. If the current value is less than the optimum value, it may be necessary to gradually increase the control value to increase the suspension stiffness. If the current value is greater than the optimum value, it may be necessary to gradually decrease the control value to decrease the suspension stiffness.

S300, determining air spring control parameters according to the air spring control targets.

It will be appreciated that different air spring control parameters may be preset under different driving modes to accommodate varying demands of different environments. And (3) air pressure adjustment: the control target may include a desired air pressure range. By adjusting the air pressure of the air spring, the stiffness of the suspension can be directly influenced. In general, increasing the air pressure will make the suspension stiffer and decreasing the air pressure will make the suspension softer. And (3) adjusting the degree of expansion: the degree of expansion of the air spring is also an important control parameter. By adjusting the degree of telescoping, the height of the suspension can be changed, thereby affecting the ground clearance and attitude of the vehicle.

In one possible implementation, referring to fig. 7, S300, determining an air spring control parameter according to an air spring control target includes:

s310, acquiring an air spring control relation model; the air spring control relation model is used for reflecting the association relation between an air spring control target and control parameters.

It will be appreciated that the air spring control relationship model is a mathematical model that is used to represent and analyze the relationship between air spring control targets and control parameters. The air spring control relationship model is used to express the interaction relationship between an air spring control target (e.g., performance index of the suspension system) and a control parameter (e.g., air pressure, spring height, etc.). This model is validated by data testing and pre-established.

Optionally, referring to fig. 8, S310, acquiring an air spring control relationship model includes:

s311, a plurality of air spring sample control parameter sets are acquired.

It will be appreciated that the air spring sample control parameter set is a different sample set of air spring control parameter tests. For example, the control parameter may be Air Pressure (Air Pressure): the air pressure of the charge or exhaust is typically expressed in pascals (Pa) or other units of pressure. Spring Height (Spring Height): the actual length or degree of expansion of an air spring is typically in meters (m) or millimeters (mm).

S312, controlling the air springs by using each air spring sample control parameter set to perform testing, and obtaining a plurality of corresponding air spring control data sets.

It will be appreciated that the initial control parameters, such as air pressure, spring height, etc., may be set using the selected air spring sample. Using the test apparatus and the control system, a test program is executed to perform various control operations on the air spring. Real-time data during the test, including air pressure changes, spring height changes, etc., are recorded. The test is repeated for each air spring sample to obtain a plurality of corresponding reliable air spring control data sets. Multiple tests are performed under different conditions and control parameters to cover potential usage scenarios.

S313, different comfort quantitative scores corresponding to the air spring control data sets under different air pressure change rates are obtained.

It will be appreciated that specific indicators of comfort may be predefined, which may include vibration level, stability of the suspension system, feedback response of the suspension system, etc. And acquiring the comfort index values of the combination of different air pressure change rates and other control parameters corresponding to the air spring control data set, and obtaining different corresponding comfort quantization scores of the air spring control data according to the comfort index values and the calculation rules or the mapping relation of the comfort index values and the comfort quantization scores.

And S314, performing data fitting on the comfort quantitative scores and the corresponding air spring sample control parameter sets to obtain an air spring control relation model.

It can be appreciated that a set of fitting rules or statistical algorithms can be set to statistically fit the comfort quantization scores and the corresponding air spring sample control parameter sets to obtain an air spring control relationship model. Suitable fitting methods, such as linear regression, polynomial regression, support vector regression, etc., fit the comfort quantization scores to the control parameter set. The fitting algorithm can be formulated as a combination of variables and model structures to find a best fit air spring control relationship model.

S320, determining air spring control parameters according to the air spring control target and the air spring control relation model.

It will be appreciated that the air spring control parameters may be determined based on the air spring control target and an air spring control relationship model (interrelationship) between the air spring control target and the control parameters. By carefully adjusting and optimizing the control parameters of the air spring, a higher level of performance, comfort, and adaptability can be achieved, while also enabling an increase in energy efficiency and a reduction in maintenance costs in some respects.

Optionally, referring to fig. 9, S320, determining an air spring control parameter according to an air spring control target and an air spring control relationship model includes:

s321, acquiring the current air spring air pressure value.

It will be appreciated that the current air spring air pressure value may be obtained from an Electronic Control Unit (ECU) of the vehicle or a control unit of the suspension system. The method for acquiring the current air spring air pressure value in real time has important significance for ensuring normal operation of the vehicle, improving performance and ensuring safety and comfort.

S322, obtaining an air pressure variation interval based on the current air spring air pressure value and the air spring control target.

It can be understood that the current air spring air pressure value and the set control target can be subjected to differential algorithm operation to calculate the air pressure variation. Air pressure change amount = current air pressure value-control target air pressure value. According to the calculated air pressure variation, a section representing the difference section of the current air pressure value relative to the control target can be determined. By calculating the air pressure variation interval, useful information can be provided for the control, maintenance and optimization of the air spring, and the reliability, performance and safety of the system can be improved.

S323, obtaining the optimal air pressure change rate based on the air spring control relation model.

It can be appreciated that the relationship between comfort or other performance metrics and air pressure change rate can be predicted by an air spring control relationship model, based on which the optimal air pressure change rate with the highest comfort quantization score during air pressure change can be obtained. And constructing an optimized objective function based on the established air spring control relation model. This function relates comfort or other performance metrics to the rate of change of air pressure.

S324, determining an air spring control parameter based on the air pressure variation interval and the optimal air pressure variation rate.

It can be understood that the adjustment parameters of the air spring air pressure change device, namely the air spring inflation and deflation parameters, can be determined according to the optimal air pressure change rate and the air pressure change amount interval. This may be to adjust the inflation rate, deflation rate, inflation starting pressure, deflation starting pressure, etc. These parameters are actual control parameters that control the air spring air pressure variation, i.e., adjust the amount of air spring expansion and contraction. The optimal air pressure change rate is the change rate of air pressure and can be used for determining the air charging rate and the air discharging rate. The air pressure change amount interval is the amount by which the air pressure needs to be changed, and can be used for determining the time corresponding to the inflation and deflation rate under the optimal air pressure change rate.

S400, performing actual adjustment control on the air spring based on the air spring control parameters.

It can be understood that the air spring air pressure changing device can be controlled to adjust air pressure according to the determined adjusting parameters of the air spring air pressure changing device, so that the air spring is actually adjusted and controlled.

In one possible implementation, S400, performing actual adjustment control on the air spring based on the air spring control parameter, includes:

s410, controlling the air pressure change in the air spring based on the air spring control parameter to actually adjust the air spring.

It will be appreciated that the parameters of the inflation and deflation of the air spring air pressure varying device may be adjusted based on the previously determined air spring control parameters to achieve the set air pressure target. This may include adjusting the inflation rate, deflation rate, inflation starting pressure, deflation starting pressure, inflation time, deflation time, etc. In the adjusting process, the air pressure value in the air spring is monitored in real time, and the air pressure value is determined to be gradually close to or maintained in a set target range, so that the air spring is controlled according to different driving environments, the running stability of the vehicle is improved, the riding comfort is improved, and the maintenance cost of the vehicle is reduced.

It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic of each process, and should not limit the implementation process of the embodiment of the present application in any way.

Corresponding to the air spring control method described in the above embodiments, the embodiments of the present application further provide an air spring control system, where each unit of the system may implement each step of the air spring control method. Fig. 10 shows a block diagram of an air spring control system provided in an embodiment of the present application, and only a portion relevant to the embodiment of the present application is shown for convenience of explanation.

Referring to fig. 10, the air spring control system includes:

It should be noted that, because the content of information interaction and execution process between the above systems/units is based on the same concept as the method embodiment of the present application, specific functions and technical effects thereof may be referred to in the method embodiment section, and will not be described herein again.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit module may exist alone physically, or two or more unit modules may be integrated in one unit, where the integrated unit may be implemented in a form of hardware or a form of a software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.

The embodiment of the application also provides air spring control equipment, and fig. 11 is a schematic structural diagram of the air spring control equipment provided by the embodiment of the application. As shown in fig. 11, the air spring control apparatus 6 of this embodiment includes: at least one processor 60 (only one is shown in fig. 11), at least one memory 61 (only one is shown in fig. 11), and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60, which processor 60, when executing the computer program 62, causes the air spring control apparatus 6 to perform the steps of any of the respective air spring control method embodiments described above, or causes the air spring control apparatus 6 to perform the functions of the respective units of the respective system embodiments described above.

Illustratively, the computer program 62 may be partitioned into one or more units that are stored in the memory 61 and executed by the processor 60 to complete the present application. The one or more units may be a series of computer program instruction segments capable of performing a specific function for describing the execution of the computer program 62 in the air spring control device 6.

The air spring control device 6 may be a vehicle control system (may include a controller of a vehicle), an on-board device, a cloud server, and other computing devices. The air spring control device may include, but is not limited to, a processor 60, a memory 61. It will be appreciated by those skilled in the art that fig. 11 is merely an example of the air spring control apparatus 6 and is not meant to be limiting of the air spring control apparatus 6, and may include more or fewer components than shown, or may combine certain components, or may include different components, such as input-output devices, network access devices, buses, etc.

The processor 60 may be a central processing unit (Central Processing Unit, CPU), the processor 60 may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

The memory 61 may in some embodiments be an internal storage unit of the air spring control device 6, such as a hard disk or a memory of the air spring control device 6. The memory 61 may in other embodiments also be an external storage device of the air spring control device 6, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like, which is provided on the air spring control device 6. Further, the memory 61 may also include both an internal memory unit and an external memory device of the air spring control apparatus 6. The memory 61 is used for storing an operating system, application programs, boot loader (BootLoader), data, other programs, etc., such as program codes of the computer program. The memory 61 may also be used for temporarily storing data that has been output or is to be output.

Embodiments of the present application also provide a computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of any of the various method embodiments described above.

Embodiments of the present application provide a computer program product for causing an air spring control apparatus to carry out the steps of any of the various method embodiments described above when the computer program product is run on the air spring control apparatus.

The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application implements all or part of the flow of the method of the above embodiments, and may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, where the computer program, when executed by a processor, may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a terminal device, a recording medium, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Such as a U-disk, removable hard disk, magnetic or optical disk, etc. In some jurisdictions, computer readable media may not be electrical carrier signals and telecommunications signals in accordance with legislation and patent practice.

In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiments provided herein, it should be understood that the disclosed air spring control system/air spring control apparatus and method may be implemented in other ways. For example, the air spring control system/air spring control apparatus embodiments described above are merely illustrative, e.g., the division of the elements is merely a logical functional division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.

Claims

1. An air spring control method, comprising:

identifying a driving situation of the vehicle;

2. The air spring control method according to claim 1, wherein the identifying a driving situation of the vehicle includes:

acquiring radar information of a vehicle;

3. The air spring control method according to claim 2, wherein the constructing a vehicle driving prediction road condition model based on the vehicle radar information includes:

analyzing radar reflected signals based on the vehicle radar information;

Constructing a vehicle driving prediction road condition model based on the road surface obstacle rate of the unit displacement;

the identifying the driving situation of the vehicle further comprises:

4. The air spring control method according to claim 3, wherein said matching the driving scene of the vehicle according to a preset rule based on the predicted road condition model of the driving of the vehicle comprises:

5. The air spring control method according to claim 4, wherein the obtaining an air spring control target based on the vehicle driving situation includes:

acquiring a current air spring expansion control value;

6. The air spring control method according to any one of claims 1 to 5, wherein the determining an air spring control parameter according to the air spring control target includes:

7. The air spring control method of claim 6, wherein said obtaining an air spring control relationship model comprises:

acquiring a plurality of air spring sample control parameter sets;

8. The air spring control method of claim 6 wherein said determining said air spring control parameter based on said air spring control target and said air spring control relationship model comprises:

Acquiring a current air spring air pressure value;

9. An air spring control system, comprising:

10. An air spring control device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the method of any one of claims 1 to 8 when executing the computer program.