CN117593811A - Shimmy judging method and device, storage medium and electronic equipment - Google Patents
Shimmy judging method and device, storage medium and electronic equipment Download PDFInfo
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Abstract
The application discloses a shimmy judging method and device, a storage medium and electronic equipment. The method comprises the following steps: collecting vehicle running data, wherein the customer running data comprises steering system data, front axle data, front wheel data and speed data; establishing a vibration calculus model according to steering system data, front axle data, tire data and speed data, wherein the vibration calculus model is used for describing the vibration characteristics of a shimmy system of a vehicle; and processing the vehicle running data and the weight value of each vehicle running data by using a shimmy judging model to obtain a shimmy judging value of a shimmy system, wherein the shimmy judging model is built based on a vibration calculus model, and the weight value corresponds to the vehicle type of the vehicle. The method solves the problems of complex operation and lower accuracy of the existing shimmy judging method.
Description
Technical Field
The present invention relates to the field of vehicle engineering, and in particular, to a shimmy determination method and apparatus, a storage medium, and an electronic device.
Background
Passenger cars are a primary concern for safety as vehicles mainly used by transportation personnel. The shimmy of a passenger car generally refers to small-amplitude rapid reciprocating oscillation of a steering wheel which is visible to naked eyes when the passenger car runs straight at a medium-high speed on a well-dried road surface. On one hand, the occurrence of the shimmy of the passenger car can influence the driving of a driver, so that the driver is mental in panic; on the other hand, when the vehicle runs at a high speed, the excessive swing amplitude value can even cause the vehicle to snake, and the safety of the vehicle is seriously affected. Therefore, in order to ensure driving safety, improve handling and comfort, evaluating the shimmy of a passenger car is of great importance to passenger car manufacturers, operators and passengers.
The existing shimmy evaluation method mainly comprises an experimental measurement method, a numerical simulation method and a subjective evaluation method, however, the operation processes of the experimental measurement method and the numerical simulation method are complex, and the accuracy of the subjective evaluation method is low.
Disclosure of Invention
In view of the above, the application provides a shimmy judging method and device, a storage medium and electronic equipment, and solves the problems of complex operation and low accuracy of the existing shimmy judging method.
According to one aspect of the present application, there is provided a shimmy determination method, including:
collecting vehicle running data, wherein the vehicle running data comprises steering system data, front axle data, front wheel data and speed data;
establishing a vibration calculus model according to the steering system data, the front axle data, the tire data and the speed data, wherein the vibration calculus model is used for describing the vibration characteristics of a shimmy system of a vehicle;
and processing the vehicle running data and the weight value of each vehicle running data by using a shimmy judging model to obtain a shimmy judging value of the shimmy system, wherein the shimmy judging model is built based on the vibration calculus model, and the weight value corresponds to the vehicle type of the vehicle.
Optionally, the steering system data includes:
the moment of inertia of the steering system, the damping coefficient of the steering system, the steering system stiffness, and the caster angle.
Optionally, the front axle data includes:
damping coefficient of the front axle and front axle rigidity.
Optionally, the tire data includes:
the tire has a rotational inertia, a damping coefficient of the tire around the kingpin, a tire stiffness, a left tire lateral force, a right tire lateral force, a rotational inertia of a front axle wheel end, a tire rolling radius, a tire trailing distance, a front wheel track, a tire lateral stiffness, a kingpin offset, a rolling coefficient, and a tire camber angle.
Optionally, the speed data includes:
the first vibration acceleration of the left and right wheels, the second vibration acceleration on the front axle rigid beam, the third vibration acceleration of the plate spring system, the fourth vibration acceleration of the steering system and the vehicle speed;
the first vibration acceleration is collected by a first acceleration sensor arranged at the front wheel end, the second vibration acceleration is collected by a second acceleration sensor arranged on the front axle rigid beam, the third vibration acceleration is collected by a third acceleration sensor arranged on a rear seat of the front axle plate spring, the fourth vibration acceleration is collected by a fourth acceleration sensor arranged on the periphery of the steering wheel, and the vehicle speed is collected by a rotating speed sensor arranged on the wheel.
Optionally, before said establishing a vibration calculus equation from said steering system data, said front axle data, said tire data, and said speed data, said method further comprises:
judging whether the judging preconditions are met or not by utilizing a road spectrum data acquisition instrument, wherein the judging preconditions comprise road surface straightening conditions and tire air pressure conditions;
if yes, eliminating abnormal data in the vehicle running data;
if the information is not satisfied, generating prompt information that the shimmy cannot be judged, and ending the shimmy judgment.
Optionally, the method further comprises:
acquiring a historical shimmy discrimination value and expert scoring corresponding to the historical shimmy discrimination value, and determining a target range of the shimmy discrimination value according to the expert scoring, wherein the target range is used for evaluating shimmy intensity;
accordingly, after the obtaining the shimmy discrimination value of the shimmy system, the method further comprises:
if the shimmy discrimination value belongs to the target range, determining that the shimmy system meets the preset stability requirement, otherwise, determining that the shimmy system does not meet the preset stability requirement.
According to another aspect of the present application, there is provided a shimmy determination device, the device comprising:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring vehicle running data, and the vehicle running data comprises steering system data, front axle data, front wheel data and speed data;
the processing module is used for establishing a vibration calculus model according to the steering system data, the front axle data, the tire data and the speed data, wherein the vibration calculus model is used for describing the vibration characteristics of a shimmy system of the vehicle;
and the judging module is used for processing the vehicle running data and the weight value of each vehicle running data by utilizing a shimmy judging model to obtain a shimmy judging value of the shimmy system, wherein the shimmy judging model is established based on the vibration calculus model, and the weight value corresponds to the vehicle type of the vehicle.
Optionally, the steering system data includes:
the moment of inertia of the steering system, the damping coefficient of the steering system, the steering system stiffness, and the caster angle.
Optionally, the front axle data includes:
damping coefficient of the front axle and front axle rigidity.
Optionally, the tire data includes:
the tire has a rotational inertia, a damping coefficient of the tire around the kingpin, a tire stiffness, a left tire lateral force, a right tire lateral force, a rotational inertia of a front axle wheel end, a tire rolling radius, a tire trailing distance, a front wheel track, a tire lateral stiffness, a kingpin offset, a rolling coefficient, and a tire camber angle.
Optionally, the speed data includes:
the first vibration acceleration of the left and right wheels, the second vibration acceleration on the front axle rigid beam, the third vibration acceleration of the plate spring system, the fourth vibration acceleration of the steering system and the vehicle speed;
the first vibration acceleration is collected by a first acceleration sensor arranged at the front wheel end, the second vibration acceleration is collected by a second acceleration sensor arranged on the front axle rigid beam, the third vibration acceleration is collected by a third acceleration sensor arranged on a rear seat of the front axle plate spring, the fourth vibration acceleration is collected by a fourth acceleration sensor arranged on the periphery of the steering wheel, and the vehicle speed is collected by a rotating speed sensor arranged on the wheel.
Optionally, the apparatus further comprises a screening module for:
judging whether the judging preconditions are met or not by utilizing a road spectrum data acquisition instrument, wherein the judging preconditions comprise road surface straightening conditions and tire air pressure conditions;
if yes, eliminating abnormal data in the vehicle running data;
if the information is not satisfied, generating prompt information that the shimmy cannot be judged, and ending the shimmy judgment.
Optionally, the apparatus further comprises an evaluation module for:
acquiring a historical shimmy discrimination value and expert scoring corresponding to the historical shimmy discrimination value, and determining a target range of the shimmy discrimination value according to the expert scoring, wherein the target range is used for evaluating shimmy intensity; and if the shimmy discrimination value belongs to the target range, determining that the shimmy system meets the preset stability requirement, otherwise, determining that the shimmy system does not meet the preset stability requirement.
According to still another aspect of the present application, there is provided a storage medium having stored thereon a program or instructions which, when executed by a processor, implement the shimmy determination method described above.
According to still another aspect of the present application, there is provided an electronic device including a storage medium storing a computer program and a processor implementing the above shimmy determination method when executing the computer program.
By means of the technical scheme, the sensor is used for collecting driving data generated in the driving process of the vehicle, and the collected data are screened to remove abnormal data which can cause errors and influence judgment accuracy. And then analyzing three dimensions of a front axle and a tire from steering supply based on the screened data according to the vibration calculus model and the shimmy judgment model, and calculating by combining influence factors such as vehicle types and the like to obtain shimmy judgment values. On the basis, a target range corresponding to the shimmy discrimination value when the shimmy system is relatively stable can be further defined according to the historical data, and whether the steering system needs to be maintained or improved is further evaluated according to the target range. The judging method of the embodiment is simple and high in accuracy, and the problems that the existing shimmy judging method is complex in operation and low in accuracy are effectively solved.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
fig. 1 shows a schematic flow chart of a shimmy judging method according to an embodiment of the present application;
fig. 2 is a schematic diagram of vehicle driving data according to another shimmy determination method according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram of a judging structure of another shimmy judging method according to an embodiment of the present application;
fig. 4 is a schematic diagram illustrating a determination process of another shimmy determination method according to an embodiment of the present disclosure;
FIG. 5 is a schematic flow chart of another shimmy determination method according to an embodiment of the present disclosure;
fig. 6 shows a block diagram of a shimmy determination device according to an embodiment of the present application.
Detailed Description
The present application will be described in detail hereinafter with reference to the accompanying drawings in conjunction with embodiments. It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other.
In this embodiment, a shimmy judging method is provided, as shown in fig. 1, and the method includes the following steps:
step 101, collecting vehicle running data, wherein the vehicle running data comprises steering system data, front axle data, front wheel data and speed data;
102, establishing a vibration calculus model according to steering system data, front axle data, tire data and speed data, wherein the vibration calculus model is used for describing the vibration characteristics of a shimmy system of a vehicle;
and 103, processing the vehicle running data and the weight value of each vehicle running data by using a shimmy judging model to obtain a shimmy judging value of a shimmy system, wherein the shimmy judging model is built based on a vibration calculus model, and the weight value corresponds to the vehicle type of the vehicle.
The shimmy judging method is used for evaluating vehicle shimmy according to the running state of the vehicle. The swing and vibration fault of the passenger car refers to the phenomenon that the passenger car swings, jolts or shakes in the running process. In general, a passenger car should be kept in a stable and stable state during driving, but the shimmy fault can cause instability of the car, and influence on comfort and safety of a driver and passengers. Based on the method, the shimmy of the passenger car can be judged, so that maintenance or whole car optimization can be carried out according to the shimmy judgment result of the passenger car.
In this embodiment, during the running of the vehicle, vehicle running data is collected, a vibration calculus model is built according to the vehicle running data, and finally the intensity of the vehicle shimmy is judged according to the vibration calculus model. In particular, since vehicle shimmy may be caused by a variety of factors, for example, tire imbalance, uneven wear, or tire breakage may all result in shimmy failure; loosening or wearing of the steering gear, steering mechanism or knuckle can also cause the vehicle to deviate from the track and shimmy. Based on this, various factors can be comprehensively analyzed from these aspects, a vibration calculus model can be established, and the motion and vibration characteristics in a shimmy system formed by a vehicle can be described by using the vibration calculus model, wherein the shimmy system of the vehicle refers to the whole system transmitted from a tire to a steering wheel, and is used for relieving the influence of uneven road surfaces or external impacts suffered by the vehicle during the running process, and is not limited to the steering system. The motion rule of the shimmy system can be obtained by solving the vibration calculus model, further, the vibration characteristics of the shimmy system are analyzed and researched, the vibration calculus model is integrated to obtain a shimmy judgment model, vehicle running data are used as independent variables to be input into the shimmy judgment model, corresponding weights are respectively given to each vehicle running data, the shimmy judgment value of the shimmy system is calculated by using the shimmy judgment model, and the shimmy intensity is estimated. Wherein the weight is closely related to the vehicle model.
In the embodiment, the sensor is used for collecting the driving data generated in the driving process of the vehicle, and the collected data is screened to remove abnormal data which possibly cause errors and influence the judgment accuracy. And then analyzing three dimensions of a front axle and a tire from steering supply based on the screened data according to the vibration calculus model and the shimmy judgment model, and calculating by combining influence factors such as vehicle types and the like to obtain shimmy judgment values. On the basis, a target range corresponding to the shimmy discrimination value when the shimmy system is relatively stable can be further defined according to the historical data, and whether the steering system needs to be maintained or improved is further evaluated according to the target range. The judging method of the embodiment is simple and high in accuracy, and the problems that the existing shimmy judging method is complex in operation and low in accuracy are effectively solved.
Further, in step 102, the steering system data includes: the moment of inertia of the steering system, the damping coefficient of the steering system, the steering system stiffness, and the caster angle.
It will be appreciated that the steering system is a factor that may affect vibration and thus steering system data may be incorporated into the vibration calculus equation. In particular, the steering system data may include the moment of inertia of the steering system, the damping coefficient of the steering system, the steering system stiffness, and the caster angle, among others. The moment of inertia of the system refers to the inertia of the whole steering system when rotating around the axis of the system, and the larger the moment of inertia is, the slower the response speed of the steering system to steering input is. The damping coefficient of the steering system refers to the damping effect of the steering system on steering input and is used for measuring the damping capacity of the steering system on shimmy. The larger damping coefficient can slow down the vibration speed of the steering system, so proper damping can provide stable and smooth steering response and reduce shimmy. Steering system stiffness refers to the degree of deformation of the steering system under the force applied. The higher the steering system stiffness, the more difficult the steering system is to compress or twist, and the faster the response to steering inputs is. The caster angle of the kingpin refers to an included angle between the kingpin and a vertical line, and affects the geometric layout of a steering system, thereby affecting steering stability.
Further, in step 102, the front axle data includes: damping coefficient of the front axle and front axle rigidity.
It will be appreciated that the front axle of the vehicle is also a factor that may affect vibration, and thus the front axle data may be incorporated into the vibration calculus equation. Specifically, the front axle data may include a damping coefficient of the front axle and a front axle stiffness. The damping coefficient of the front axle refers to the damping effect of the front axle (comprising a suspension system and the like) on steering input, and is used for measuring the damping capacity of the front axle on vehicle shimmy. The damping coefficient can slow down the vibration speed of the front axle, thus reducing shimmy. Front axle stiffness refers to the degree of deformation of the front axle portion under the force applied. The higher the front axle stiffness, the more difficult the front axle is to compress or twist, and the faster the response to steering inputs. Thus, the higher the front axle rigidity, the higher the steering accuracy and steering stability.
Further, in step 102, the tire data includes: the tire has a rotational inertia, a damping coefficient of the tire around the kingpin, a tire stiffness, a left tire lateral force, a right tire lateral force, a rotational inertia of a front axle wheel end, a tire rolling radius, a tire trailing distance, a front wheel track, a tire lateral stiffness, a kingpin offset, a rolling coefficient, and a tire camber angle.
It will be appreciated that the tire is also a factor that may affect vibration and that tire data may be incorporated into the vibration calculus equation. Specifically, the tire data includes the moment of inertia of the tire, the damping coefficient of the tire around the kingpin, the tire stiffness, the left tire lateral force, the right tire lateral force, the moment of inertia of the front axle wheel end, the tire rolling radius, the tire trailing distance, the front wheel tread, the tire lateral stiffness, the kingpin offset, the rolling coefficient, and the tire camber angle. Where the moment of inertia of the tire refers to the inertia that the tire has when rotating about its own axis. The greater the moment of inertia, the slower the tire's response to steering inputs. A larger moment of inertia may increase the inertia of the tire, which in turn slows the shimmy response of the steering system. The damping coefficient of the tire around the kingpin refers to the damping effect of the tire when rotating around the kingpin of the steering system, and is used to measure the damping capacity of the steering system to the shimmy of the tire. The greater the damping coefficient, the more the tire vibration velocity is relatively full. The rigidity of the tire refers to the deformation degree of the tire caused by stress. The higher the tire stiffness, the harder the tire is to compress or twist and the faster the response to steering inputs, and therefore the tire stiffness contributes to improving the response speed of the suspension system and steering accuracy. The left tire side force and the right tire side force refer to the side force generated by the left tire and the right tire of the vehicle during steering respectively, and are used for controlling the vehicle and realizing steering, and the unbalanced side force of different tires can cause the vehicle to swing. The moment of inertia of the front axle wheel end refers to the inertia that the front axle portion has when rotating about the front axle axis. The greater the moment of inertia, the slower the front axle response to steering input, thus increasing vehicle shimmy. The tire rolling radius refers to the size of the tire radius during rolling, and has an effect on the vehicle speed and steering flexibility. The larger the tire rolling radius, the higher the stability and controllability of the vehicle. Tire towing distance refers to the horizontal distance between the front and rear tire ground contact points of a vehicle, affecting vehicle stability and handling. . The wheel track of the front wheels refers to the horizontal distance between the front wheels, so that the control stability and the steering flexibility of the vehicle can be influenced, and the larger the wheel track of the front wheels is, the higher the control stability is. The lateral rigidity of the tire refers to the lateral rigidity of the tire under the action of lateral load, and influences the response and steering control performance of a suspension system of the vehicle. The greater the lateral stiffness of the tire, the greater the steering accuracy and steering stability. Kingpin offset refers to the horizontal distance between the kingpin and the vertical line of the tire, which is used to define the geometry of the steering system. The rolling coefficient refers to a ratio between the lateral force and lateral displacement of the tire in a rolling state, affecting the lateral force response when the vehicle turns. The tire side inclination refers to the inclination angle of the vehicle body caused by centrifugal force when the vehicle turns, and has an influence on the steering performance and steering stability of the vehicle.
FIG. 2 is a schematic diagram of vehicle driving data according to one embodiment of the present application, where θ is a rotation angle value; i S 、K S And C S Is a steering system related parameter, wherein I S K being moment of inertia of the steering system S For steering system stiffness, C S Is the damping coefficient of the steering system; k (K) A And C A Is a front axle related parameter, wherein K A For front axle stiffness, C A Is the damping coefficient of the front axle; i A 、I t 、K t C t Is a tire related parameter, wherein I A Is the rotational inertia of the front axle wheel end, I t K being the moment of inertia of the tyre t For tyre rigidity, C t Is the damping coefficient of the tire around the kingpin. These parameters can be obtained through experiments, corresponding experiments need other instruments and equipment to help, the shimmy system of the whole vehicle can be evaluated through the parameters, and if the evaluation shows that the stability is poor, the improvement and the optimization can be carried out in a targeted manner.
Further, in step 102, the speed data includes: the first vibration acceleration of the left and right wheels, the second vibration acceleration on the front axle rigid beam, the third vibration acceleration of the leaf spring system, the fourth vibration acceleration of the steering system, and the vehicle speed.
It will be appreciated that speed is also a factor that may affect vibration, and thus speed data may be incorporated into the vibration calculus equation. Specifically, the speed data includes: the first vibration acceleration of the left and right wheels, the second vibration acceleration on the front axle rigid beam, the third vibration acceleration of the leaf spring system, the fourth vibration acceleration of the steering system and the vehicle speed. The speed data can be acquired by using a sensor, specifically, the first vibration acceleration is acquired by a first acceleration sensor arranged at the front wheel end, the second vibration acceleration is acquired by a second acceleration sensor arranged on the front axle rigid beam, the third vibration acceleration is acquired by a third acceleration sensor arranged on the rear seat of the front axle plate spring, the fourth vibration acceleration is acquired by a fourth acceleration sensor arranged at the periphery of the steering wheel, and the vehicle speed is acquired by a rotating speed sensor arranged at the wheel.
In this embodiment, the vehicle is tested on a straight section, regardless of the system clearance, steering trapezoidal difference, manufacturing error, and the like, the vibration calculus model is specifically as follows:
wherein I is t For moment of inertia of tyre, C t For damping coefficient, K, of tyre around kingpin t For tyre rigidity, F y1 For left tyre side force, F y2 For right tire lateral force, I A Is the rotational inertia of the front axle wheel end, C A K is the damping coefficient of the front axle A For front axle stiffness, I S For moment of inertia of steering system, C S K being the damping coefficient of the steering system S For steering system rigidity, R is caster angle of kingpin, R is tire rolling radius, e is tire trailing distance, B is front wheel track, ρ is tire lateral rigidity, L is kingpin offset, f is rolling coefficient,is the tire roll angle.
And integrating five formulas in the model to obtain a shimmy judging model:
A＝f(I t ,C t ,K t ,I A ,C A ,K A ,I S ,C S ,K S ,r,ρ,L)
wherein the input of the shimmy discrimination model comprises I t ,C t ,K t ,I A ,C A ,K A ,I S ,C S ,K S R, ρ, L, the shimmy discrimination value A is a sum, where formula f is only a general function, where weight assignment is involved and the weights are closely related to the vehicle model.
FIG. 3 is a schematic diagram showing a judging structure of an embodiment of the present application, in which an automobile is uniformly driven on a straight road section as much as possible, and an engine should be flatAnd the operation is stable. The front wheel end of the vehicle is respectively provided with a left wheel sensor (corresponding to one first acceleration sensor) and a right wheel sensor (corresponding to the other first acceleration sensor) for collecting the vibration angular acceleration values a of the wheels at the left side and the right side in the running process of the vehicle t The method comprises the steps of carrying out a first treatment on the surface of the A front axle sensor (corresponding to a second acceleration sensor) is arranged on the front axle rigid beam and used for collecting the vibration acceleration value a of the front axle rigid beam in the running process of the vehicle A The method comprises the steps of carrying out a first treatment on the surface of the The plate spring rear seat of the front axle plate spring is provided with a plate spring rear seat sensor (corresponding to a third acceleration sensor) for collecting the vibration acceleration value a of the plate spring system during the running process of the vehicle S The method comprises the steps of carrying out a first treatment on the surface of the A steering wheel sensor (equivalent to a fourth acceleration sensor) is arranged on the periphery of the steering wheel, and the vibration angular acceleration value a of the steering system in the running process of the vehicle is collected g . Wherein the directions of all the sensors are arranged according to an automobile coordinate system. The V-BOX road spectrum data acquisition instrument is placed at the center of mass of the whole vehicle, positioning coordinate data, air pressure data, altitude data and vehicle speed data V in the running process of the vehicle are acquired, and whether the standard air pressure of a straight road surface and a tire is met is judged according to the acquired data. The computer stores and calculates the acquired data to obtain the shimmy discrimination value and displays the shimmy discrimination value in a visual form through the display device. If the shimmy discrimination value is within the target range, the stability of the shimmy system is considered to be good, otherwise, the stability of the shimmy system is considered to be poor, so that the shimmy system is optimized.
Further, as a refinement and extension of the specific implementation of the foregoing embodiment, for fully explaining the specific implementation process of the embodiment, another shimmy determination method is provided, and as shown in fig. 4, the method includes four steps of data acquisition, data screening, data processing, and shimmy determination value outputting.
The data acquisition specifically comprises the following steps:
in step 201, vehicle travel data is collected, wherein the customer travel data includes steering system data, front axle data, front wheel data, and speed data.
The data screening specifically comprises the following steps:
and 202, judging whether the judging preconditions are met or not by utilizing road spectrum data acquisition, wherein the judging preconditions comprise road surface flatness conditions and tire air pressure conditions.
And 203, if the judgment result is met, eliminating abnormal data in the vehicle running data, and if the judgment result is not met, generating prompt information for judging shimmy, and ending shimmy judgment.
In step 202-step 203, the V-BOX spectrum data acquisition instrument is used to acquire positioning coordinate data, air pressure data, altitude data, vehicle speed data and the like, and then whether the precondition of the calculus equation can be satisfied is judged according to the acquired data. Specifically, experiments require a flat road surface and standard tire air pressure, which would otherwise affect the accuracy of the evaluation index. Therefore, if the road surface flatness condition and the tire air pressure condition are not met, the current experiment environment is considered not to be met, so that shimmy judgment is not carried out, and corresponding prompt information is generated; and otherwise, normally performing shimmy judgment.
Before shimmy judgment, the V-BOX path spectrum data acquisition instrument can be used for data cleaning, and abnormal data caused by equipment faults, improper testing conditions and the like can be removed. It can be understood that the V-BOX road spectrum data acquisition instrument is a common vehicle running data acquisition device, is commonly used in the fields of vehicle performance evaluation, test, research and development and the like, is composed of a group of high-precision sensors and data recorders, and can acquire various vehicle parameter data including position, speed, acceleration, gesture, angular speed and the like. In addition, the V-BOX road spectrum data acquisition instrument can also acquire positioning coordinate data, air pressure data, altitude data and the like in the running process of the vehicle.
In the embodiment, the V-BOX path spectrum data acquisition instrument is used for judging whether the precondition of the calculus equation is met, so that the accuracy of a judging result is guaranteed. On the basis, the V-BOX road spectrum data acquisition instrument is used for analyzing the vehicle driving data, and identifying and eliminating abnormal data such as abrupt change, fluctuation abnormality, data exceeding a set threshold value and the like so as to ensure the accuracy of the data. Further, after abnormal data are removed, data correction and reconstruction can be performed through interpolation algorithm, curve fitting and the like, so that the gap of the removed data points is filled, and the integrity of driving data is ensured.
The data processing specifically comprises the following steps:
and 204, establishing a vibration calculus model according to the steering system data, the front axle data, the tire data and the speed data, wherein the vibration calculus model is used for describing the vibration characteristics of a shimmy system of the vehicle.
The method for outputting the shimmy discrimination value specifically comprises the following steps:
and 205, processing the vehicle running data and the weight value of each vehicle running data by using a shimmy distinguishing model to obtain a shimmy distinguishing value of a shimmy system, wherein the shimmy distinguishing model is built based on a vibration calculus model, and the weight value corresponds to the vehicle type of the vehicle.
And 206, acquiring the historical shimmy discrimination value and expert scoring corresponding to the historical shimmy discrimination value, and determining a target range of the shimmy discrimination value according to the expert scoring, wherein the target range is used for evaluating shimmy intensity.
Step 207, if the shimmy discrimination value belongs to the target range, determining that the shimmy system meets the preset stability requirement, otherwise determining that the shimmy system does not meet the preset stability requirement.
In step 206-step 207, a large number of real vehicles are tested to obtain historical shimmy discrimination values, shimmy is subjectively felt, the historical shimmy discrimination values are scored, overall treatment is carried out on the scoring condition, and a target range of the historical shimmy discrimination values is manually specified. If the shimmy discrimination value is in the target range, the shimmy degree is considered to be weaker, the stability of a shimmy system of the vehicle is high, and the requirement of the preset stability is met; otherwise, the shimmy is considered to be stronger, the stability of the shimmy system is low, and the requirement of the preset stability is not met, so that the stability of the shimmy system is optimized.
In the embodiment shown in fig. 5, the sensor is used to collect the driving data generated during the driving process of the vehicle, the V-BOX road spectrum data collector is used to determine whether the precondition of the calculus equation is satisfied, and the collected data is screened to remove the abnormal data that may cause errors and affect the accuracy of the determination on the premise that the precondition is satisfied. And then analyzing three dimensions of the steering system, the front axle and the tire based on the screened data according to the vibration calculus model and the shimmy discrimination equation, and calculating to obtain a shimmy discrimination value. On the basis, a target range corresponding to the shimmy discrimination value when the steering system is stable can be further defined according to the historical data, and whether the vehicle needs to be maintained or improved is further evaluated according to the target range. The judging method of the embodiment is simple and high in accuracy, and the problems that the existing shimmy judging method is complex in operation and low in accuracy are effectively solved.
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, and should not limit the implementation process of the embodiment of the present invention.
Further, as a specific implementation of the shimmy determination method, an embodiment of the present application provides a shimmy determination device, as shown in fig. 6, where the device includes: the device comprises an acquisition module, a processing module and a judging module.
The system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring vehicle running data, and the vehicle running data comprises steering system data, front axle data, front wheel data and speed data;
the processing module is used for establishing a vibration calculus model according to steering system data, front axle data, tire data and speed data, wherein the vibration calculus model is used for describing the vibration characteristics of a shimmy system of the vehicle;
and the judging module is used for processing the vehicle running data and the weight value of each vehicle running data by utilizing a shimmy judging model to obtain a shimmy judging value of the shimmy system, wherein the shimmy judging model is established based on a vibration calculus model, and the weight value corresponds to the vehicle type of the vehicle.
In a specific application scenario, optionally, the steering system data includes:
the moment of inertia of the steering system, the damping coefficient of the steering system, the steering system stiffness, and the caster angle.
In a specific application scenario, optionally, the front axle data includes:
damping coefficient of the front axle and front axle rigidity.
In a specific application scenario, optionally, the tire data includes:
the tire has a rotational inertia, a damping coefficient of the tire around the kingpin, a tire stiffness, a left tire lateral force, a right tire lateral force, a rotational inertia of a front axle wheel end, a tire rolling radius, a tire trailing distance, a front wheel track, a tire lateral stiffness, a kingpin offset, a rolling coefficient, and a tire camber angle.
In a specific application scenario, optionally, the speed data includes:
the first vibration acceleration of the left and right wheels, the second vibration acceleration on the front axle rigid beam, the third vibration acceleration of the plate spring system, the fourth vibration acceleration of the steering system and the vehicle speed;
the first vibration acceleration is collected by the first acceleration sensor that sets up at the front wheel end, and the second vibration acceleration is collected by the second acceleration sensor that sets up on the front axle rigid beam, and the third vibration acceleration is collected by the third acceleration sensor that sets up at the rear seat of front axle leaf spring, and the fourth vibration acceleration is collected by the fourth acceleration sensor that sets up at the steering wheel periphery, and the speed of a motor vehicle is collected by the rotational speed sensor that sets up at the wheel.
In a specific application scenario, optionally, the apparatus further includes a screening module, configured to:
judging whether the judging preconditions are met or not by utilizing a road spectrum data acquisition instrument, wherein the judging preconditions comprise road surface straightening conditions and tire air pressure conditions;
if yes, eliminating abnormal data in the vehicle running data;
if the information is not satisfied, generating prompt information that the shimmy cannot be judged, and ending the shimmy judgment.
In a specific application scenario, optionally, the apparatus further includes an evaluation module, configured to:
acquiring a historical shimmy discrimination value and expert scoring corresponding to the historical shimmy discrimination value, and determining a target range of the shimmy discrimination value according to the expert scoring, wherein the target range is used for evaluating shimmy intensity; and if the shimmy discrimination value belongs to the target range, determining that the shimmy system meets the preset stability requirement, otherwise, determining that the shimmy system does not meet the preset stability requirement.
It should be noted that, other corresponding descriptions of each functional module related to the shimmy judging device provided in the embodiment of the present application may refer to corresponding descriptions in the above method, and are not repeated herein.
Based on the above method, correspondingly, the embodiment of the application also provides a storage medium, on which a computer program is stored, which when executed by a processor, implements the shimmy judging method.
Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.), and includes several instructions for causing an electronic device (may be a personal computer, a server, or a network device, etc.) to perform the methods described in various implementation scenarios of the present application.
Based on the method shown in fig. 1 to fig. 4 and the virtual device embodiment shown in fig. 5, in order to achieve the above object, the embodiment of the present application further provides an electronic device, which may specifically be a personal computer, a server, a network device, or the like, where the electronic device includes a storage medium and a processor; a storage medium storing a computer program; and a processor for executing a computer program to implement the shimmy determination method as shown in fig. 1 to 4.
Optionally, the electronic device may also include a user interface, a network interface, a camera, radio Frequency (RF) circuitry, sensors, audio circuitry, WI-FI modules, and the like. The user interface may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), etc., and the optional user interface may also include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (e.g., bluetooth interface, WI-FI interface), etc.
It will be appreciated by those skilled in the art that the structure of the electronic device provided in this embodiment is not limited to the electronic device, and may include more or fewer components, or may be combined with certain components, or may be arranged with different components.
The storage medium may also include an operating system, a network communication module. An operating system is a program that manages and saves electronic device hardware and software resources, supporting the execution of information handling programs, as well as other software and/or programs. The network communication module is used for realizing communication among all the controls in the storage medium and communication with other hardware and software in the entity equipment.
From the above description of the embodiments, it will be apparent to those skilled in the art that the present application may be implemented by means of software plus necessary general hardware platforms, or may be implemented by hardware.
Those skilled in the art will appreciate that the drawings are merely schematic illustrations of one preferred implementation scenario, and that the elements or processes in the drawings are not necessarily required to practice the present application. Those skilled in the art will appreciate that elements of an apparatus in an implementation may be distributed throughout the apparatus in an implementation as described in the implementation, or that corresponding variations may be located in one or more apparatuses other than the present implementation. The units of the implementation scenario may be combined into one unit, or may be further split into a plurality of sub-units.
The foregoing application serial numbers are merely for description, and do not represent advantages or disadvantages of the implementation scenario. The foregoing disclosure is merely a few specific implementations of the present application, but the present application is not limited thereto and any variations that can be considered by a person skilled in the art shall fall within the protection scope of the present application.
Claims (10)
1. A shimmy determination method, the method comprising:
collecting vehicle running data, wherein the vehicle running data comprises steering system data, front axle data, front wheel data and speed data;
establishing a vibration calculus model according to the steering system data, the front axle data, the tire data and the speed data, wherein the vibration calculus model is used for describing the vibration characteristics of a shimmy system of a vehicle;
and processing the vehicle running data and the weight value of each vehicle running data by using a shimmy judging model to obtain a shimmy judging value of the shimmy system, wherein the shimmy judging model is built based on the vibration calculus model, and the weight value corresponds to the vehicle type of the vehicle.
2. The method of claim 1, wherein the steering system data comprises:
the moment of inertia of the steering system, the damping coefficient of the steering system, the steering system stiffness, and the caster angle.
3. The method of claim 1, wherein the front axle data comprises:
damping coefficient of the front axle and front axle rigidity.
4. The method of claim 1, wherein the tire data comprises:
the tire has a rotational inertia, a damping coefficient of the tire around the kingpin, a tire stiffness, a left tire lateral force, a right tire lateral force, a rotational inertia of a front axle wheel end, a tire rolling radius, a tire trailing distance, a front wheel track, a tire lateral stiffness, a kingpin offset, a rolling coefficient, and a tire camber angle.
5. The method of claim 1, wherein the speed data comprises:
the first vibration acceleration of the left and right wheels, the second vibration acceleration on the front axle rigid beam, the third vibration acceleration of the plate spring system, the fourth vibration acceleration of the steering system and the vehicle speed;
the first vibration acceleration is collected by a first acceleration sensor arranged at the front wheel end, the second vibration acceleration is collected by a second acceleration sensor arranged on the front axle rigid beam, the third vibration acceleration is collected by a third acceleration sensor arranged on a rear seat of the front axle plate spring, the fourth vibration acceleration is collected by a fourth acceleration sensor arranged on the periphery of the steering wheel, and the vehicle speed is collected by a rotating speed sensor arranged on the wheel.
6. The method of claim 5, wherein prior to said establishing a vibratory calculus equation based on said steering system data, said front axle data, said tire data, and said speed data, said method further comprises:
judging whether the judging preconditions are met or not by utilizing a road spectrum data acquisition instrument, wherein the judging preconditions comprise road surface straightening conditions and tire air pressure conditions;
if yes, eliminating abnormal data in the vehicle running data;
if the information is not satisfied, generating prompt information that the shimmy cannot be judged, and ending the shimmy judgment.
7. The method according to claim 1, wherein the method further comprises:
acquiring a historical shimmy discrimination value and expert scoring corresponding to the historical shimmy discrimination value, and determining a target range of the shimmy discrimination value according to the expert scoring, wherein the target range is used for evaluating shimmy intensity;
accordingly, after the obtaining the shimmy discrimination value of the shimmy system, the method further comprises:
if the shimmy discrimination value belongs to the target range, determining that the shimmy system meets the preset stability requirement, otherwise, determining that the shimmy system does not meet the preset stability requirement.
8. A shimmy determination device, the device comprising:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring vehicle running data, and the vehicle running data comprises steering system data, front axle data, front wheel data and speed data;
the processing module is used for establishing a vibration calculus model according to the steering system data, the front axle data, the tire data and the speed data, wherein the vibration calculus model is used for describing the vibration characteristics of a shimmy system of the vehicle;
and the judging module is used for processing the vehicle running data and the weight value of each vehicle running data by utilizing a shimmy judging model to obtain a shimmy judging value of the shimmy system, wherein the shimmy judging model is established based on the vibration calculus model, and the weight value corresponds to the vehicle type of the vehicle.
9. A storage medium having stored thereon a program or instructions which, when executed by a processor, implement the method of any of claims 1 to 7.
10. An electronic device comprising a storage medium, a processor and a computer program stored on the storage medium and executable on the processor, characterized in that the processor implements the method of any one of claims 1 to 7 when executing the program.
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