CN118004189A - Method, device, vehicle, medium and program product for determining adhesion coefficient - Google Patents
Method, device, vehicle, medium and program product for determining adhesion coefficient Download PDFInfo
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- CN118004189A CN118004189A CN202410301414.1A CN202410301414A CN118004189A CN 118004189 A CN118004189 A CN 118004189A CN 202410301414 A CN202410301414 A CN 202410301414A CN 118004189 A CN118004189 A CN 118004189A
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Abstract
The embodiment of the application provides a method, a device, a vehicle, a medium and a program product for determining an adhesion coefficient. In the method, at least one reference adhesion coefficient of the vehicle and the confidence coefficient of each reference adhesion coefficient are obtained, wherein the at least one reference adhesion coefficient comprises at least one of the following: steady state attachment coefficient, dynamic attachment coefficient, longitudinal attachment coefficient or transverse attachment coefficient; acquiring sensor states of a plurality of sensors of the vehicle, wherein the sensor states are normal states or failure states; the target adhesion coefficient of the vehicle and the confidence of the target adhesion coefficient are determined based on the at least one reference adhesion coefficient, the confidence of each reference adhesion coefficient, and the sensor states of the plurality of sensors. The accuracy of determining the adhesion coefficient of the vehicle is improved.
Description
Technical Field
The present application relates to the field of vehicle technologies, and in particular, to a method and apparatus for determining an adhesion coefficient, a vehicle, a medium, and a program product.
Background
The adhesion coefficient of the vehicle plays a key role in the longitudinal driving anti-skid control of the vehicle.
In the related art, it is common that a vehicle estimates an adhesion coefficient directly from a ratio of a longitudinal driving force and a vertical load to perform anti-skid control of the vehicle based on the adhesion coefficient.
However, in the method in the related art, the adhesion coefficient is estimated directly according to the ratio of the longitudinal driving force to the vertical load, and the adhesion coefficient is not matched with the actual condition of the vehicle, so that the anti-skid control of the vehicle is inaccurate, and the safety of passengers is affected.
Disclosure of Invention
The embodiment of the application provides a method, a device, a vehicle, a medium and a program product for determining an adhesion coefficient, which can improve the accuracy of determining the adhesion coefficient of the vehicle.
In a first aspect, an embodiment of the present application provides a method for determining an adhesion coefficient, including:
obtaining at least one reference adhesion coefficient of the vehicle and a confidence level of each reference adhesion coefficient, wherein the at least one reference adhesion coefficient comprises at least one of the following: steady state attachment coefficient, dynamic attachment coefficient, longitudinal attachment coefficient or transverse attachment coefficient;
acquiring sensor states of a plurality of sensors of the vehicle, wherein the sensor states are normal states or failure states;
the target adhesion coefficient of the vehicle and the confidence of the target adhesion coefficient are determined based on the at least one reference adhesion coefficient, the confidence of each reference adhesion coefficient, and the sensor states of the plurality of sensors.
In one implementation, determining a target adhesion coefficient of a vehicle and a confidence of the target adhesion coefficient based on at least one reference adhesion coefficient, a confidence of each reference adhesion coefficient, and a sensor state of a plurality of sensors, includes:
judging whether the sensor state of at least one sensor is a failure state according to the sensor states of the plurality of sensors;
If yes, determining the target attachment coefficient as a first preset value, and determining the confidence coefficient of the target attachment coefficient as a second preset value;
If not, determining the target adhesion coefficient of the vehicle and the confidence coefficient of the target adhesion coefficient according to at least one reference adhesion coefficient and the confidence coefficient of each reference adhesion coefficient.
In one implementation, the at least one reference attachment coefficient includes a dynamic attachment coefficient, a longitudinal attachment coefficient, and a transverse attachment coefficient; determining a target adhesion coefficient of the vehicle and a confidence level of the target adhesion coefficient based on the at least one reference adhesion coefficient and the confidence level of each reference adhesion coefficient, comprising:
If the confidence coefficient of the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient is smaller than or equal to 0, determining the target adhesion coefficient as a third preset value, and determining the confidence coefficient of the target adhesion coefficient as a fourth preset value.
In one implementation, the at least one reference attachment coefficient includes a dynamic attachment coefficient, a longitudinal attachment coefficient, and a transverse attachment coefficient; determining a target adhesion coefficient of the vehicle and a confidence level of the target adhesion coefficient based on the at least one reference adhesion coefficient and the confidence level of each reference adhesion coefficient, comprising:
determining a target number of reference attachment coefficients for which the reference attachment coefficient is greater than a first preset threshold and the corresponding confidence coefficient is greater than a second preset threshold;
and according to the target number, carrying out fusion processing on the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient to obtain the target adhesion coefficient and the confidence coefficient of the target adhesion coefficient.
In one implementation, the target number is greater than 1; according to the target number, carrying out fusion processing on the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient to obtain the target adhesion coefficient and the confidence coefficient of the target adhesion coefficient, wherein the fusion processing comprises the following steps:
obtaining the sum of the adhesion coefficients of the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient;
determining the ratio of the sum of the adhesion coefficients to the target number as a target adhesion coefficient;
And determining the confidence coefficient of the target attachment coefficient as a fifth preset value.
In one implementation, the target number is 1; according to the target number, carrying out fusion processing on the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient to obtain the target adhesion coefficient and the confidence coefficient of the target adhesion coefficient, wherein the fusion processing comprises the following steps:
According to the confidence coefficient of the dynamic adhesion coefficient, the confidence coefficient of the longitudinal adhesion coefficient and the confidence coefficient of the transverse adhesion coefficient, carrying out weighted fusion treatment on the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient to obtain a weighted adhesion coefficient;
obtaining the sum of the confidence coefficient of the dynamic adhesion coefficient, the confidence coefficient of the longitudinal adhesion coefficient and the confidence coefficient of the transverse adhesion coefficient;
Determining the ratio of the weighted attachment coefficient to the sum of the confidence coefficient as a target attachment coefficient;
and determining the confidence coefficient of the target adhesion coefficient as the mean square value of the confidence coefficient of the dynamic adhesion coefficient, the confidence coefficient of the longitudinal adhesion coefficient and the confidence coefficient of the transverse adhesion coefficient.
In one implementation, the at least one reference adhesion coefficient comprises a steady state adhesion coefficient; determining a target adhesion coefficient of the vehicle and a confidence level of the target adhesion coefficient based on the at least one reference adhesion coefficient and the confidence level of each reference adhesion coefficient, comprising:
If the confidence coefficient of the steady-state attachment coefficient is greater than or equal to 1, determining the activation duration of a stability control system of the vehicle;
acquiring a historical target attachment coefficient of the vehicle at the last moment;
And determining the target adhesion coefficient and the confidence coefficient of the target adhesion coefficient according to the steady-state adhesion coefficient, the activation time and the historical target adhesion coefficient.
In one implementation, determining a target attachment coefficient, and a confidence level for the target attachment coefficient, based on a steady state attachment coefficient, an activation duration, and a historical target attachment coefficient, includes:
Obtaining a coefficient difference value between the steady-state attachment coefficient and the historical target attachment coefficient;
determining an adjustment coefficient according to the activation time length, and determining the product of the adjustment coefficient and the coefficient difference value as a coefficient adjustment quantity;
Determining the sum of the historical target attachment coefficient and the coefficient adjustment amount as a target attachment coefficient;
And determining the confidence of the target attachment coefficient as a sixth preset value.
In a second aspect, an embodiment of the present application provides an apparatus for determining an adhesion coefficient, including:
The system comprises an acquisition module for acquiring at least one reference adhesion coefficient of the vehicle and confidence of each reference adhesion coefficient, wherein the at least one reference adhesion coefficient comprises at least one of the following: steady state attachment coefficient, dynamic attachment coefficient, longitudinal attachment coefficient or transverse attachment coefficient;
The acquisition module is also used for acquiring sensor states of a plurality of sensors of the vehicle, wherein the sensor states are normal states or failure states;
the processing module is further used for determining a target adhesion coefficient of the vehicle and the confidence coefficient of the target adhesion coefficient according to the at least one reference adhesion coefficient, the confidence coefficient of each reference adhesion coefficient and the sensor states of the plurality of sensors.
In one implementation, the processing module is specifically configured to:
judging whether the sensor state of at least one sensor is a failure state according to the sensor states of the plurality of sensors;
If yes, determining the target attachment coefficient as a first preset value, and determining the confidence coefficient of the target attachment coefficient as a second preset value;
If not, determining the target adhesion coefficient of the vehicle and the confidence coefficient of the target adhesion coefficient according to at least one reference adhesion coefficient and the confidence coefficient of each reference adhesion coefficient.
In one implementation, the at least one reference attachment coefficient includes a dynamic attachment coefficient, a longitudinal attachment coefficient, and a transverse attachment coefficient; the processing module is specifically used for:
If the confidence coefficient of the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient is smaller than or equal to 0, determining the target adhesion coefficient as a third preset value, and determining the confidence coefficient of the target adhesion coefficient as a fourth preset value.
In one implementation, the at least one reference attachment coefficient includes a dynamic attachment coefficient, a longitudinal attachment coefficient, and a transverse attachment coefficient; the processing module is specifically used for:
determining a target number of reference attachment coefficients for which the reference attachment coefficient is greater than a first preset threshold and the corresponding confidence coefficient is greater than a second preset threshold;
and according to the target number, carrying out fusion processing on the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient to obtain the target adhesion coefficient and the confidence coefficient of the target adhesion coefficient.
In one implementation, the target number is greater than 1; the processing module is specifically used for:
obtaining the sum of the adhesion coefficients of the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient;
determining the ratio of the sum of the adhesion coefficients to the target number as a target adhesion coefficient;
And determining the confidence coefficient of the target attachment coefficient as a fifth preset value.
In one implementation, the target number is 1; the processing module is specifically used for:
According to the confidence coefficient of the dynamic adhesion coefficient, the confidence coefficient of the longitudinal adhesion coefficient and the confidence coefficient of the transverse adhesion coefficient, carrying out weighted fusion treatment on the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient to obtain a weighted adhesion coefficient;
obtaining the sum of the confidence coefficient of the dynamic adhesion coefficient, the confidence coefficient of the longitudinal adhesion coefficient and the confidence coefficient of the transverse adhesion coefficient;
Determining the ratio of the weighted attachment coefficient to the sum of the confidence coefficient as a target attachment coefficient;
and determining the confidence coefficient of the target adhesion coefficient as the mean square value of the confidence coefficient of the dynamic adhesion coefficient, the confidence coefficient of the longitudinal adhesion coefficient and the confidence coefficient of the transverse adhesion coefficient.
In one implementation, the at least one reference adhesion coefficient comprises a steady state adhesion coefficient; the processing module is specifically used for:
If the confidence coefficient of the steady-state attachment coefficient is greater than or equal to 1, determining the activation duration of a stability control system of the vehicle;
acquiring a historical target attachment coefficient of the vehicle at the last moment;
And determining the target adhesion coefficient and the confidence coefficient of the target adhesion coefficient according to the steady-state adhesion coefficient, the activation time and the historical target adhesion coefficient.
In one implementation, the processing module is specifically configured to:
Obtaining a coefficient difference value between the steady-state attachment coefficient and the historical target attachment coefficient;
determining an adjustment coefficient according to the activation time length, and determining the product of the adjustment coefficient and the coefficient difference value as a coefficient adjustment quantity;
Determining the sum of the historical target attachment coefficient and the coefficient adjustment amount as a target attachment coefficient;
And determining the confidence of the target attachment coefficient as a sixth preset value.
In a third aspect, an embodiment of the present application provides a vehicle including:
A processor, a memory communicatively coupled to the processor;
A memory for storing computer-executable instructions;
a processor for executing computer-executable instructions stored in a memory to implement the method of determining the attachment coefficient of the first aspect.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having stored therein computer-executable instructions for implementing the method for determining the attachment coefficient of the first aspect when the computer-executable instructions are executed by a processor.
In a fifth aspect, embodiments of the present application provide a computer program product comprising a computer program for implementing a method of determining an attachment coefficient as in the first aspect when the computer program is executed by a processor.
The embodiment of the application provides a method, a device, a vehicle, a medium and a program product for determining an adhesion coefficient. In the method, the vehicle may obtain at least one reference adhesion coefficient of the vehicle and a confidence level of each reference adhesion coefficient. Wherein the at least one reference adhesion coefficient comprises at least one of: steady state attachment coefficient, dynamic attachment coefficient, longitudinal attachment coefficient, or transverse attachment coefficient. The vehicle may also acquire sensor states of a plurality of sensors of the vehicle, the sensor states being either normal states or failure states. The vehicle may determine a target adhesion coefficient of the vehicle and a confidence level of the target adhesion coefficient based on the at least one reference adhesion coefficient, the confidence level of each reference adhesion coefficient, and the sensor states of the plurality of sensors. Through the mode, the target attachment coefficient and the confidence coefficient of the target attachment coefficient can be accurately determined, the accuracy of determining the attachment coefficient is improved, the anti-skid control capability of the vehicle is further improved, and the safety of passengers is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the related art, the drawings that are required to be used in the embodiments or the related technical descriptions will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to the drawings without inventive effort to those skilled in the art.
Fig. 1 is a schematic diagram of an application scenario to which an embodiment of the present application is applicable;
fig. 2 is a schematic flow chart of a first embodiment of a method for determining an adhesion coefficient according to an embodiment of the present application;
Fig. 3 is a schematic flow chart of a second embodiment of a method for determining an adhesion coefficient according to an embodiment of the present application;
Fig. 4 is a schematic flow chart of a third embodiment of a method for determining an adhesion coefficient according to an embodiment of the present application;
fig. 5 is a schematic flow chart of a fourth embodiment of a method for determining an adhesion coefficient according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an adhesion coefficient determining device according to an embodiment of the present application;
Fig. 7 is a block diagram of a vehicle according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which are made by a person skilled in the art based on the embodiments of the application in light of the present disclosure, are intended to be within the scope of the application.
The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements that are expressly listed or inherent to such process, method, article, or apparatus.
The adhesion coefficient of the vehicle plays a key role in the longitudinal driving anti-skid control of the vehicle. In the related art, it is common that a vehicle estimates an adhesion coefficient directly from a ratio of a longitudinal driving force and a vertical load to perform anti-skid control of the vehicle based on the adhesion coefficient. However, in the method in the related art, the adhesion coefficient is estimated directly according to the ratio of the longitudinal driving force to the vertical load, and the adhesion coefficient is not matched with the actual condition of the vehicle, so that the anti-skid control of the vehicle is inaccurate, and the safety of passengers is affected.
Based on the above technical problems, the embodiments of the present application provide a method for determining an adhesion coefficient, where a vehicle may obtain at least one reference adhesion coefficient of the vehicle and a confidence coefficient of each reference adhesion coefficient. Wherein the at least one reference adhesion coefficient comprises at least one of: steady state attachment coefficient, dynamic attachment coefficient, longitudinal attachment coefficient, or transverse attachment coefficient. The vehicle may also acquire sensor states of a plurality of sensors of the vehicle, the sensor states being either normal states or failure states. The vehicle may determine a target adhesion coefficient of the vehicle and a confidence level of the target adhesion coefficient based on the at least one reference adhesion coefficient, the confidence level of each reference adhesion coefficient, and the sensor states of the plurality of sensors. By the method, the target attachment coefficient and the confidence coefficient of the target attachment coefficient can be accurately determined, so that the matching degree of the attachment coefficient and the actual condition of the vehicle is improved, and the anti-skid control capability of the vehicle is further improved.
The principles and features of embodiments of the present application are described below with reference to the drawings, the examples are provided for the purpose of illustrating the embodiments of the present application and are not intended to limit the scope of the embodiments of the present application.
Fig. 1 is a schematic diagram of an application scenario to which the embodiment of the present application is applicable. The application scenario includes a vehicle 10, the vehicle 10 including a plurality of wheels. Illustratively, fig. 1 shows four wheels, a left front wheel 101, a right front wheel 102, a left rear wheel 103 and a right rear wheel 104, respectively. In addition, a plurality of sensors (not shown in FIG. 1) may also be mounted on the vehicle 10. It should be noted that the plurality of sensors may include a wheel speed sensor, may include an inertial measurement unit (inertial measurement unit, abbreviated as IMU) motion sensor, and may include a steering wheel angle sensor.
In this application scenario, the vehicle 10 may acquire at least one reference adhesion coefficient of the vehicle 10, and a confidence level of each reference adhesion coefficient. Wherein the at least one reference adhesion coefficient comprises at least one of: steady state attachment coefficient, dynamic attachment coefficient, longitudinal attachment coefficient, or transverse attachment coefficient. The vehicle 10 may also acquire sensor states of a plurality of sensors of the vehicle 10, the sensor states being either normal states or failure states. The vehicle 10 may determine the target adhesion coefficient of the vehicle 10, and the confidence of the target adhesion coefficient, based on the at least one reference adhesion coefficient, the confidence of each reference adhesion coefficient, and the sensor states of the plurality of sensors.
The embodiment of the present application is not limited to the actual form of the vehicle shown in fig. 1, and in the application of the solution, the embodiment may be set according to the actual requirement.
The technical scheme of the application is described in detail through specific embodiments. It should be noted that the following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.
Fig. 2 is a flowchart of an embodiment of a method for determining an adhesion coefficient according to an embodiment of the present application. Referring to fig. 2, the method specifically includes the steps of:
s201: at least one reference adhesion coefficient of the vehicle, and a confidence level of each reference adhesion coefficient are obtained.
In this embodiment, the vehicle may acquire at least one reference adhesion coefficient of the vehicle, and a confidence level of each reference adhesion coefficient.
Wherein the at least one reference adhesion coefficient comprises at least one of: steady state attachment coefficient, dynamic attachment coefficient, longitudinal attachment coefficient, or transverse attachment coefficient.
The process of the vehicle to acquire at least one reference adhesion coefficient is explained below.
Steady state adhesion coefficient: under the condition that the stability control system is activated, the steady-state attachment coefficient is determined according to the instantaneous attachment coefficients at a plurality of moments and the activation intervention duration.
Transverse adhesion coefficient: the vehicle determines a lateral attachment coefficient using a least square method based on the plurality of rack forces and the plurality of front axle lateral forces at the plurality of historical moments.
Longitudinal adhesion coefficient: and fitting the vehicle according to the longitudinal rigidity and the slip ratio by utilizing a hyperbolic tangent function to obtain the longitudinal attachment coefficient and the variance of the attachment coefficient of each wheel. The vehicle calculates the longitudinal adhesion coefficient of the vehicle under the high adhesion condition and the low adhesion condition according to the longitudinal adhesion coefficient of each wheel. The vehicle determines the longitudinal adhesion coefficient from the longitudinal adhesion coefficient of the vehicle in the case of high adhesion and the longitudinal adhesion coefficient of the vehicle in the case of low adhesion according to the variance of the adhesion coefficient of each wheel.
Dynamic adhesion coefficient: the slip ratio of a plurality of wheels of the vehicle, the longitudinal rigidity of the wheels and the longitudinal force of the tires are used for obtaining the longitudinal/transverse stability factors of the vehicle. And determining the dynamic adhesion coefficient under the condition of high adhesion according to the longitudinal/transverse stability factors of the vehicle and the instantaneous adhesion coefficient, and determining the dynamic adhesion coefficient under the condition of low adhesion. And the vehicle determines the dynamic attachment coefficient of the vehicle according to the dynamic attachment coefficient under the high attachment condition and the dynamic attachment coefficient under the low attachment condition.
In addition, the process of obtaining the instantaneous attachment coefficient includes:
The vehicle may acquire tire information for each tire (wheel) of the vehicle, the tire information including tire longitudinal force, tire lateral force, and tire vertical load of the tire. The vehicle may determine a first adhesion coefficient of the vehicle based on the tire information for each tire. The vehicle may determine the gain factor based on the first attachment factor and the tire information for each tire. The vehicle may determine the second attachment coefficient based on the gain coefficient, and an acceleration of the vehicle. The vehicle may determine an instantaneous adhesion coefficient of the vehicle based on the first adhesion coefficient and the second adhesion coefficient.
S202: sensor states of a plurality of sensors of the vehicle are acquired.
In the present embodiment, the vehicle may acquire the sensor states of a plurality of sensors. Wherein the sensor state is a normal state or a failure state.
In one implementation, the vehicle determines that the sensor state is a failure state upon determining that the sensor signal transmitted by the sensor includes a failure signal.
In one implementation, the vehicle determines that the sensor state is a failure state upon determining that the sensor signal sent by the sensor is not received.
S203: the target adhesion coefficient of the vehicle and the confidence of the target adhesion coefficient are determined based on the at least one reference adhesion coefficient, the confidence of each reference adhesion coefficient, and the sensor states of the plurality of sensors.
In the present embodiment, the vehicle may determine the target adhesion coefficient of the vehicle and the confidence of the target adhesion coefficient based on at least one reference adhesion coefficient, the confidence of each reference adhesion coefficient, and the sensor states of the plurality of sensors.
Specifically, the vehicle may determine whether the sensor state of at least one sensor is a failure state based on the sensor states of the plurality of sensors.
If yes, the vehicle determines that the target adhesion coefficient is a first preset value, and determines that the confidence coefficient of the target adhesion coefficient is a second preset value. Illustratively, the first preset value may be 1 and the second preset value may be 0.
If not, the vehicle may determine the target adhesion coefficient of the vehicle and the confidence level of the target adhesion coefficient based on the at least one reference adhesion coefficient and the confidence level of each reference adhesion coefficient.
In one implementation, the vehicle may also acquire a tire mode for each wheel, where the tire mode may be a spare tire mode or a non-spare tire mode. The vehicle may determine that the target adhesion coefficient is a first preset value and determine that the confidence of the target adhesion coefficient is a second preset value, if it is determined that the sensor state of the at least one sensor is a failure state and/or if the tire mode of the at least one wheel is a spare tire mode.
It should be noted that the vehicle may calculate the rolling radius of each wheel on a per-wheel basis. For each wheel, the vehicle determines that the tire mode of the wheel is a spare tire mode if it is determined that the rolling radius of the wheel is less than a radius threshold.
The beneficial effects of this embodiment are: the vehicle may obtain at least one reference adhesion coefficient of the vehicle, and a confidence level for each reference adhesion coefficient. Wherein the at least one reference adhesion coefficient comprises at least one of: steady state attachment coefficient, dynamic attachment coefficient, longitudinal attachment coefficient, or transverse attachment coefficient. The vehicle may also acquire sensor states of a plurality of sensors of the vehicle, the sensor states being either normal states or failure states. The vehicle may determine a target adhesion coefficient of the vehicle and a confidence level of the target adhesion coefficient based on the at least one reference adhesion coefficient, the confidence level of each reference adhesion coefficient, and the sensor states of the plurality of sensors. Through the mode, the target attachment coefficient and the confidence coefficient of the target attachment coefficient can be accurately determined, the accuracy of determining the attachment coefficient is improved, the anti-skid control capability of the vehicle is further improved, and the safety of passengers is improved.
Fig. 3 is a schematic flow chart of a second embodiment of a method for determining an adhesion coefficient according to an embodiment of the present application. Referring to fig. 3, the method specifically includes the steps of:
s301: at least one reference adhesion coefficient of the vehicle, and a confidence level of each reference adhesion coefficient are obtained.
In this embodiment, the vehicle may acquire at least one reference adhesion coefficient of the vehicle, and a confidence level of each reference adhesion coefficient.
Wherein the at least one reference attachment coefficient comprises a dynamic attachment coefficient, a longitudinal attachment coefficient, and a transverse attachment coefficient.
Accordingly, the confidence of each reference adhesion coefficient includes the confidence of the dynamic adhesion coefficient, the confidence of the longitudinal adhesion coefficient, and the confidence of the transverse adhesion coefficient.
S302: sensor states of a plurality of sensors of the vehicle are acquired.
In the present embodiment, the vehicle may acquire sensor states of a plurality of sensors of the vehicle, wherein the sensor states are a normal state or a failure state.
S303: and judging whether the sensor state of at least one sensor is a failure state according to the sensor states of the plurality of sensors.
In this embodiment, the vehicle may determine whether or not the sensor state of at least one sensor is a failure state based on the sensor states of the plurality of sensors.
If yes, executing S304;
if not, S305 is performed.
S304: determining the target adhesion coefficient as a first preset value and determining the confidence coefficient of the target adhesion coefficient as a second preset value.
In this embodiment, when the vehicle determines that the sensor state in which at least one sensor exists is the failure state, the vehicle determines that the target attachment coefficient is a first preset value, and determines that the confidence coefficient of the target attachment coefficient is a second preset value.
In addition, the vehicle may determine that the confidence Level is Level zero (Level 0) in the event that it is determined that the sensor state of the at least one sensor is a failure state.
S305: if the confidence coefficient of the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient is smaller than or equal to 0, determining the target adhesion coefficient as a third preset value, and determining the confidence coefficient of the target adhesion coefficient as a fourth preset value.
In this embodiment, when the vehicle determines that the sensor state in which at least one sensor is not present is the failure state, it may be determined whether the confidence of the dynamic adhesion coefficient, the longitudinal adhesion coefficient, and the lateral adhesion coefficient is less than or equal to 0.
If the confidence coefficients of the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient are all smaller than or equal to 0, the vehicle can determine that the target adhesion coefficient is a third preset value, and determine that the confidence coefficient of the target adhesion coefficient is a fourth preset value. Illustratively, the third preset value may be 1 and the fourth preset value may be 1.
In addition, the vehicle may determine the confidence Level to be Level one (Level 1) in the case where the confidence levels of the dynamic adhesion coefficient, the longitudinal adhesion coefficient, and the lateral adhesion coefficient are all less than or equal to 0.
The beneficial effects of this embodiment are: in this embodiment, when the vehicle determines that the sensor state in which at least one sensor exists is the failure state, the vehicle determines that the target attachment coefficient is a first preset value, and determines that the confidence coefficient of the target attachment coefficient is a second preset value. When the vehicle determines that the sensor state in which at least one sensor is not present is the failure state, the vehicle may determine that the target adhesion coefficient is a third preset value and determine that the confidence of the target adhesion coefficient is a fourth preset value, in the case where the confidence of the dynamic adhesion coefficient, the longitudinal adhesion coefficient, and the lateral adhesion coefficient are all less than or equal to 0. By the method, the target attachment coefficient and the confidence coefficient thereof can be accurately determined based on the sensor state and the confidence coefficient of each reference attachment coefficient, the accuracy of determining the attachment coefficient and the confidence coefficient thereof is improved, the anti-skid control capability of the vehicle is further improved, and the safety of passengers is improved.
Fig. 4 is a schematic flow chart of a third embodiment of a method for determining an adhesion coefficient according to an embodiment of the present application. Referring to fig. 4, the method specifically includes the steps of:
S401: at least one reference adhesion coefficient of the vehicle, and a confidence level of each reference adhesion coefficient are obtained.
In this embodiment, the vehicle may acquire at least one reference adhesion coefficient of the vehicle, and a confidence level of each reference adhesion coefficient.
Wherein the at least one reference attachment coefficient comprises a dynamic attachment coefficient, a longitudinal attachment coefficient, and a transverse attachment coefficient. Accordingly, the confidence of each reference adhesion coefficient includes the confidence of the dynamic adhesion coefficient, the confidence of the longitudinal adhesion coefficient, and the confidence of the transverse adhesion coefficient.
S402: sensor states of a plurality of sensors of the vehicle are acquired.
In the present embodiment, the vehicle may acquire sensor states of a plurality of sensors of the vehicle, wherein the sensor states are a normal state or a failure state.
S403: and judging whether the sensor state of at least one sensor is a failure state according to the sensor states of the plurality of sensors.
In this embodiment, the vehicle may determine whether or not the sensor state of at least one sensor is a failure state based on the sensor states of the plurality of sensors.
If yes, executing S404;
If not, then S405 is performed.
S404: determining the target adhesion coefficient as a first preset value and determining the confidence coefficient of the target adhesion coefficient as a second preset value.
In this embodiment, when the vehicle determines that the sensor state in which at least one sensor exists is the failure state, the vehicle may determine that the target adhesion coefficient is a first preset value and determine that the confidence of the target adhesion coefficient is a second preset value.
In addition, the vehicle may determine that the confidence Level is Level zero (Level 0) in the event that it is determined that the sensor state of the at least one sensor is a failure state.
S405: and determining the target number of the reference adhesion coefficients, of which the reference adhesion coefficients are larger than a first preset threshold value and the corresponding confidence coefficient is larger than a second preset threshold value.
In this embodiment, in the case where the vehicle determines that the sensor state in which at least one sensor is not present is the failure state, it may be determined that the reference adhesion coefficient is greater than the first preset threshold value, and the corresponding confidence coefficient is greater than the target number of reference adhesion coefficients of the second preset threshold value.
In addition, the vehicle may also determine a confidence level based on each reference adhesion coefficient having a confidence level greater than a second predetermined threshold.
For example, the vehicle may determine that the confidence Level is Level two (Level 2) in the case where the confidence of the determination of the lateral adhesion coefficient is greater than the second preset threshold.
The vehicle may determine that the confidence Level is Level three (Level 3) in the event that the confidence of the longitudinal attachment coefficient is determined to be greater than the second preset threshold.
The vehicle may determine that the confidence Level is Level four (Level 4) if the confidence of the dynamic attachment coefficient is determined to be greater than the second preset threshold.
The vehicle may determine that the confidence Level is Level five (Level 5) in the case where it is determined that the confidence that there are two reference attachment coefficients is greater than the second preset threshold.
The vehicle may determine that the confidence Level is Level six (Level 6) in the case where the confidence levels of the three reference attachment coefficients are determined to be all greater than the second preset threshold.
In one implementation, in determining the target number:
the vehicle may attribute each reference adhesion coefficient, according to the magnitude of the value, to the corresponding adhesion coefficient value level. The vehicle may attribute the confidence level of each reference attachment coefficient to the corresponding confidence value level according to the value size.
For example, the vehicle may attribute the reference adhesion coefficient to a high adhesion coefficient value level upon determining that the reference adhesion coefficient is greater than a first preset threshold. The vehicle may attribute the reference adhesion coefficient to a low adhesion coefficient value level upon determining that the reference adhesion coefficient is less than or equal to the first preset threshold.
For example, the vehicle may attribute the confidence of the reference adhesion coefficient to a high confidence value level upon determining that the confidence of the reference adhesion coefficient is greater than a second preset threshold. The vehicle may attribute the confidence of the reference adhesion coefficient to a high confidence value level upon determining that the confidence of the reference adhesion coefficient is less than or equal to a second preset threshold.
The vehicle may determine that the reference adhesion coefficient is assigned to a high adhesion coefficient value level and the corresponding confidence is assigned to the target number of reference adhesion coefficients for the high confidence value level.
S406: and according to the target number, carrying out fusion processing on the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient to obtain the target adhesion coefficient and the confidence coefficient of the target adhesion coefficient.
In this embodiment, the vehicle may perform fusion processing on the dynamic adhesion coefficient, the longitudinal adhesion coefficient, and the transverse adhesion coefficient according to the target number, to obtain the target adhesion coefficient and the confidence coefficient of the target adhesion coefficient.
Specifically, in the case where the target number is greater than 1, the vehicle may acquire the sum of the adhesion coefficients of the dynamic adhesion coefficient, the longitudinal adhesion coefficient, and the lateral adhesion coefficient. The vehicle may determine a ratio of the sum of the adhesion coefficients to the target number as the target adhesion coefficient. The vehicle may determine the confidence level of the target attachment coefficient as a fifth preset value. Illustratively, the fifth preset value may be 0.01.
Specifically, the vehicle may determine the target attachment coefficient based on the following formula:
Wherein fusion mue (t) is a target adhesion coefficient, latrfeMue (t) is a transverse adhesion coefficient, longrfeMue (t) is a longitudinal adhesion coefficient, mueFromVehDyn (t) is a dynamic adhesion coefficient, and MaxConfdIdx _B (i) is a target number.
Under the condition that the target number is 1, the vehicle can perform weighted fusion processing on the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient according to the confidence coefficient of the dynamic adhesion coefficient, the confidence coefficient of the longitudinal adhesion coefficient and the confidence coefficient of the transverse adhesion coefficient to obtain the weighted adhesion coefficient. The vehicle may obtain the sum of the confidence of the dynamic adhesion coefficient, the confidence of the longitudinal adhesion coefficient, and the confidence of the transverse adhesion coefficient. The vehicle may determine a ratio of the weighted attachment coefficient to the sum of the confidence coefficients as the target attachment coefficient. The vehicle may determine the confidence of the target adhesion coefficient as the mean square of the confidence of the dynamic adhesion coefficient, the confidence of the longitudinal adhesion coefficient, and the confidence of the transverse adhesion coefficient.
Specifically, the vehicle may determine the target attachment coefficient based on the following formula:
Wherein fusion mue (t) is a target adhesion coefficient, latrfeMue (t) is a transverse adhesion coefficient, latConfd (t) is a confidence coefficient of the transverse adhesion coefficient, longrfeMue (t) is a longitudinal adhesion coefficient, longConfd (t) is a confidence coefficient of the longitudinal adhesion coefficient, mueFromVehDyn (t) is a dynamic adhesion coefficient, vehDynConfd (t) is a confidence coefficient of the dynamic adhesion coefficient, and MaxConfdIdx _B (i) is a target number.
The beneficial effects of this embodiment are: in this embodiment, when the vehicle determines that the sensor state in which at least one sensor is not present is the failure state, it may be determined that the reference adhesion coefficient is greater than the first preset threshold value, and the corresponding confidence coefficient is greater than the target number of reference adhesion coefficients of the second preset threshold value. The vehicle can perform fusion processing on the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient according to the target quantity to obtain the target adhesion coefficient and the confidence coefficient of the target adhesion coefficient. By means of the method for fusing the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient, the target adhesion coefficient and the confidence coefficient thereof are accurately determined, the accuracy of determining the adhesion coefficient and the confidence coefficient thereof is improved, the anti-skid control capability of a vehicle is further improved, and the safety of passengers is improved.
Fig. 5 is a flowchart of a fourth embodiment of a method for determining an adhesion coefficient according to an embodiment of the present application. Referring to fig. 5, the method specifically includes the steps of:
s501: at least one reference adhesion coefficient of the vehicle, and a confidence level of each reference adhesion coefficient are obtained.
In this embodiment, the vehicle may acquire at least one reference adhesion coefficient of the vehicle, and a confidence level of each reference adhesion coefficient.
Wherein the at least one reference adhesion coefficient comprises a steady state adhesion coefficient. Accordingly, the confidence of each reference adhesion coefficient includes the confidence of the steady state adhesion coefficient.
S502: sensor states of a plurality of sensors of the vehicle are acquired.
In the present embodiment, the vehicle may acquire sensor states of a plurality of sensors of the vehicle, wherein the sensor states are a normal state or a failure state.
S503: and judging whether the sensor state of at least one sensor is a failure state according to the sensor states of the plurality of sensors.
In this embodiment, the vehicle may determine whether or not the sensor state of at least one sensor is a failure state based on the sensor states of the plurality of sensors.
If yes, executing S504;
if not, S505 is executed.
S504: determining the target adhesion coefficient as a first preset value and determining the confidence coefficient of the target adhesion coefficient as a second preset value.
In this embodiment, when the vehicle determines that the sensor state in which at least one sensor exists is the failure state, the vehicle may determine that the target adhesion coefficient is a first preset value and determine that the confidence of the target adhesion coefficient is a second preset value.
S505: and if the confidence coefficient of the steady-state attachment coefficient is greater than or equal to 1, determining the activation duration of the stability control system of the vehicle.
In this embodiment, the vehicle determines whether the confidence of the steady-state adhesion coefficient is greater than or equal to 1 in the case where it is determined that the sensor state in which at least one sensor is not present is the failure state.
The activation duration of the stability control system of the vehicle may be determined if the confidence level of the steady state attachment coefficient is greater than or equal to 1. In addition, the vehicle may also determine that the confidence Level is Level seven (Level 7) in the case where the confidence of determining the steady-state adhesion coefficient is greater than or equal to 1.
It should be noted that, the vehicle may start timing when the stability control system is activated, so as to obtain the activation duration of the stability control system.
It should also be noted that the vehicle may determine that the vehicle activates the stability control system if it is recognized that there is a tire (wheel) with a brake flag set and the tire (wheel) braking torque is greater than zero. The vehicle may also determine that the vehicle activates the stability control system if it is recognized that there is a control flag of the antilock braking system of one tire (wheel) set and the braking torque of the tire (wheel) is greater than zero. The vehicle may also determine that the vehicle activates the stability control system if it is identified that there is one tire (wheel) corresponding to the identity of the tire (wheel) in the lift-torsion request and the slip rate of the tire (wheel) is greater than zero.
S506: and acquiring a historical target attachment coefficient of the vehicle at the last moment.
In this embodiment, the vehicle may also acquire the historical target attachment coefficient of the vehicle at the last time. The last time point refers to the last time point when the target attachment coefficient is determined.
S507: and determining the target adhesion coefficient and the confidence coefficient of the target adhesion coefficient according to the steady-state adhesion coefficient, the activation time and the historical target adhesion coefficient.
In this embodiment, the vehicle may determine the target adhesion coefficient, and the confidence level of the target adhesion coefficient, based on the steady state adhesion coefficient, the activation time period, and the historical target adhesion coefficient.
Specifically, the vehicle may obtain a coefficient difference of the steady state adhesion coefficient from the historical target adhesion coefficient. The vehicle may determine the adjustment coefficient according to the activation time period, and determine the product of the adjustment coefficient and the coefficient difference value as the coefficient adjustment amount. The vehicle may determine the sum of the historical target adhesion coefficient and the coefficient adjustment amount as the target adhesion coefficient.
In addition, the vehicle may also determine the confidence of the target attachment coefficient as a sixth preset value. Illustratively, the sixth preset threshold may be 7.
Specifically, the vehicle may determine the target attachment coefficient based on the following formula:
Wherein fusion Mue (t) is a target adhesion coefficient, mueFromStabCtrl (t) is a steady state adhesion coefficient, fusionMue (t-1) is a historical target adhesion coefficient, For the adjustment of the coefficients, TS is the value corresponding to the activation duration, TC is the time constant.
The beneficial effects of this embodiment are: in this embodiment, when the vehicle determines that the sensor state in which at least one sensor is not present is the failure state and the confidence coefficient of the steady-state adhesion coefficient is greater than or equal to 1, the target adhesion coefficient and the confidence coefficient of the target adhesion coefficient are determined according to the steady-state adhesion coefficient, the activation duration of the vehicle for activating the stability control system, and the historical target adhesion coefficient. By the method, the target attachment coefficient and the confidence coefficient thereof can be accurately determined, the accuracy of determining the attachment coefficient and the confidence coefficient thereof is improved, the anti-skid control capability of the vehicle is further improved, and the safety of passengers is improved.
The following are examples of the apparatus of the present application that may be used to perform the method embodiments of the present application. For details not disclosed in the embodiments of the apparatus of the present application, please refer to the embodiments of the method of the present application.
Fig. 6 is a schematic structural diagram of an adhesion coefficient determining device according to an embodiment of the present application. As shown in fig. 6, the adhesion coefficient determining means 60 includes an acquisition module 61 and a processing module 62. Wherein,
An acquisition module 61, configured to acquire at least one reference adhesion coefficient of the vehicle, and a confidence level of each reference adhesion coefficient, where the at least one reference adhesion coefficient includes at least one of: steady state attachment coefficient, dynamic attachment coefficient, longitudinal attachment coefficient or transverse attachment coefficient;
The acquiring module 61 is further configured to acquire sensor states of a plurality of sensors of the vehicle, where the sensor states are a normal state or a failure state;
the processing module 62 is further configured to determine a target adhesion coefficient of the vehicle and a confidence level of the target adhesion coefficient based on the at least one reference adhesion coefficient, the confidence level of each reference adhesion coefficient, and the sensor states of the plurality of sensors.
The device for determining the adhesion coefficient provided by the embodiment of the application can execute the technical scheme shown in the embodiment of the method, and the implementation principle and the beneficial effects are similar, and are not repeated here.
In one implementation, the processing module 62 is specifically configured to:
judging whether the sensor state of at least one sensor is a failure state according to the sensor states of the plurality of sensors;
If yes, determining the target attachment coefficient as a first preset value, and determining the confidence coefficient of the target attachment coefficient as a second preset value;
If not, determining the target adhesion coefficient of the vehicle and the confidence coefficient of the target adhesion coefficient according to at least one reference adhesion coefficient and the confidence coefficient of each reference adhesion coefficient.
The device for determining the adhesion coefficient provided by the embodiment of the application can execute the technical scheme shown in the embodiment of the method, and the implementation principle and the beneficial effects are similar, and are not repeated here.
In one implementation, the at least one reference attachment coefficient includes a dynamic attachment coefficient, a longitudinal attachment coefficient, and a transverse attachment coefficient; the processing module 62 is specifically configured to:
If the confidence coefficient of the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient is smaller than or equal to 0, determining the target adhesion coefficient as a third preset value, and determining the confidence coefficient of the target adhesion coefficient as a fourth preset value.
The device for determining the adhesion coefficient provided by the embodiment of the application can execute the technical scheme shown in the embodiment of the method, and the implementation principle and the beneficial effects are similar, and are not repeated here.
In one implementation, the at least one reference attachment coefficient includes a dynamic attachment coefficient, a longitudinal attachment coefficient, and a transverse attachment coefficient; the processing module 62 is specifically configured to:
determining a target number of reference attachment coefficients for which the reference attachment coefficient is greater than a first preset threshold and the corresponding confidence coefficient is greater than a second preset threshold;
and according to the target number, carrying out fusion processing on the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient to obtain the target adhesion coefficient and the confidence coefficient of the target adhesion coefficient.
The device for determining the adhesion coefficient provided by the embodiment of the application can execute the technical scheme shown in the embodiment of the method, and the implementation principle and the beneficial effects are similar, and are not repeated here.
In one implementation, the target number is greater than 1; the processing module 62 is specifically configured to:
obtaining the sum of the adhesion coefficients of the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient;
determining the ratio of the sum of the adhesion coefficients to the target number as a target adhesion coefficient;
And determining the confidence coefficient of the target attachment coefficient as a fifth preset value.
The device for determining the adhesion coefficient provided by the embodiment of the application can execute the technical scheme shown in the embodiment of the method, and the implementation principle and the beneficial effects are similar, and are not repeated here.
In one implementation, the target number is 1; the processing module 62 is specifically configured to:
According to the confidence coefficient of the dynamic adhesion coefficient, the confidence coefficient of the longitudinal adhesion coefficient and the confidence coefficient of the transverse adhesion coefficient, carrying out weighted fusion treatment on the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient to obtain a weighted adhesion coefficient;
obtaining the sum of the confidence coefficient of the dynamic adhesion coefficient, the confidence coefficient of the longitudinal adhesion coefficient and the confidence coefficient of the transverse adhesion coefficient;
Determining the ratio of the weighted attachment coefficient to the sum of the confidence coefficient as a target attachment coefficient;
and determining the confidence coefficient of the target adhesion coefficient as the mean square value of the confidence coefficient of the dynamic adhesion coefficient, the confidence coefficient of the longitudinal adhesion coefficient and the confidence coefficient of the transverse adhesion coefficient.
The device for determining the adhesion coefficient provided by the embodiment of the application can execute the technical scheme shown in the embodiment of the method, and the implementation principle and the beneficial effects are similar, and are not repeated here.
In one implementation, the at least one reference adhesion coefficient comprises a steady state adhesion coefficient; the processing module 62 is specifically configured to:
If the confidence coefficient of the steady-state attachment coefficient is greater than or equal to 1, determining the activation duration of a stability control system of the vehicle;
acquiring a historical target attachment coefficient of the vehicle at the last moment;
And determining the target adhesion coefficient and the confidence coefficient of the target adhesion coefficient according to the steady-state adhesion coefficient, the activation time and the historical target adhesion coefficient.
The device for determining the adhesion coefficient provided by the embodiment of the application can execute the technical scheme shown in the embodiment of the method, and the implementation principle and the beneficial effects are similar, and are not repeated here.
In one implementation, the processing module 62 is specifically configured to:
Obtaining a coefficient difference value between the steady-state attachment coefficient and the historical target attachment coefficient;
determining an adjustment coefficient according to the activation time length, and determining the product of the adjustment coefficient and the coefficient difference value as a coefficient adjustment quantity;
Determining the sum of the historical target attachment coefficient and the coefficient adjustment amount as a target attachment coefficient;
And determining the confidence of the target attachment coefficient as a sixth preset value.
The device for determining the adhesion coefficient provided by the embodiment of the application can execute the technical scheme shown in the embodiment of the method, and the implementation principle and the beneficial effects are similar, and are not repeated here.
Fig. 7 is a block diagram of a vehicle according to an embodiment of the present application. As shown in fig. 7, the vehicle 70 includes a processor 71 and a memory 72. Wherein the processor 71 is communicatively coupled to a memory 72, the memory 72 for storing computer-executable instructions; the processor 71 is configured to execute the technical solutions of any of the method embodiments described above via computer-executable instructions stored in the execution memory 72.
Alternatively, the memory 72 may be separate or integrated with the processor 71. Alternatively, when the memory 72 is a device separate from the processor 71, the vehicle 70 may further include: and a bus for connecting the devices.
The technical scheme of the vehicle for executing any of the foregoing method embodiments has similar implementation principles and technical effects, and is not described herein.
The embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores computer execution instructions, and the computer execution instructions are used for realizing the technical scheme provided by any one of the method embodiments when being executed by a processor.
The embodiment of the application also provides a computer program product, which comprises a computer program, and the computer program is used for realizing the technical scheme provided by the embodiment of the method when being executed by a processor.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the method embodiments described above may be performed by hardware associated with program instructions. The foregoing program may be stored in a computer readable storage medium. The program, when executed, performs steps including the method embodiments described above; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features can be replaced equivalently; such modifications and substitutions do not depart from the spirit of the application.
Claims (12)
1. A method of determining an adhesion coefficient, comprising:
Obtaining at least one reference adhesion coefficient of the vehicle, and a confidence level of each reference adhesion coefficient, wherein the at least one reference adhesion coefficient comprises at least one of the following: steady state attachment coefficient, dynamic attachment coefficient, longitudinal attachment coefficient or transverse attachment coefficient;
acquiring sensor states of a plurality of sensors of the vehicle, wherein the sensor states are normal states or failure states;
Determining a target adhesion coefficient of the vehicle and a confidence of the target adhesion coefficient based on the at least one reference adhesion coefficient, the confidence of each reference adhesion coefficient, and the sensor states of the plurality of sensors.
2. The method of claim 1, wherein determining the target adhesion coefficient of the vehicle and the confidence of the target adhesion coefficient based on the at least one reference adhesion coefficient, the confidence of each reference adhesion coefficient, and the sensor states of the plurality of sensors comprises:
Judging whether the sensor state of at least one sensor is a failure state according to the sensor states of the plurality of sensors;
if yes, determining the target adhesion coefficient as a first preset value, and determining the confidence coefficient of the target adhesion coefficient as a second preset value;
If not, determining the target adhesion coefficient of the vehicle and the confidence coefficient of the target adhesion coefficient according to the at least one reference adhesion coefficient and the confidence coefficient of each reference adhesion coefficient.
3. The method of claim 2, wherein the at least one reference attachment coefficient comprises the dynamic attachment coefficient, the longitudinal attachment coefficient, and the transverse attachment coefficient; determining a target adhesion coefficient of the vehicle and a confidence level of the target adhesion coefficient according to the at least one reference adhesion coefficient and the confidence level of each reference adhesion coefficient, comprising:
If the confidence coefficient of the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient is smaller than or equal to 0, determining the target adhesion coefficient as a third preset value, and determining the confidence coefficient of the target adhesion coefficient as a fourth preset value.
4. The method of claim 2, wherein the at least one reference attachment coefficient comprises the dynamic attachment coefficient, the longitudinal attachment coefficient, and the transverse attachment coefficient; determining a target adhesion coefficient of the vehicle and a confidence level of the target adhesion coefficient according to the at least one reference adhesion coefficient and the confidence level of each reference adhesion coefficient, comprising:
determining a target number of reference attachment coefficients for which the reference attachment coefficient is greater than a first preset threshold and the corresponding confidence coefficient is greater than a second preset threshold;
And according to the target quantity, carrying out fusion processing on the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient to obtain the target adhesion coefficient and the confidence coefficient of the target adhesion coefficient.
5. The method of claim 4, wherein the target number is greater than 1; according to the target number, carrying out fusion processing on the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient to obtain the target adhesion coefficient and the confidence coefficient of the target adhesion coefficient, wherein the fusion processing comprises the following steps:
acquiring the sum of the adhesion coefficients of the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient;
determining a ratio of the sum of the attachment coefficients to the target number as the target attachment coefficient;
and determining the confidence coefficient of the target attachment coefficient as a fifth preset value.
6. The method of claim 4, wherein the target number is 1; according to the target number, carrying out fusion processing on the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient to obtain the target adhesion coefficient and the confidence coefficient of the target adhesion coefficient, wherein the fusion processing comprises the following steps:
according to the confidence coefficient of the dynamic adhesion coefficient, the confidence coefficient of the longitudinal adhesion coefficient and the confidence coefficient of the transverse adhesion coefficient, carrying out weighted fusion treatment on the dynamic adhesion coefficient, the longitudinal adhesion coefficient and the transverse adhesion coefficient to obtain a weighted adhesion coefficient;
acquiring the sum of the confidence coefficient of the dynamic attachment coefficient, the confidence coefficient of the longitudinal attachment coefficient and the confidence coefficient of the transverse attachment coefficient;
determining the ratio of the weighted attachment coefficient to the sum of the confidence coefficients as the target attachment coefficient;
and determining the confidence coefficient of the target adhesion coefficient as the mean square value of the confidence coefficient of the dynamic adhesion coefficient, the confidence coefficient of the longitudinal adhesion coefficient and the confidence coefficient of the transverse adhesion coefficient.
7. The method of claim 2, wherein the at least one reference adhesion coefficient comprises the steady state adhesion coefficient; determining a target adhesion coefficient of the vehicle and a confidence level of the target adhesion coefficient according to the at least one reference adhesion coefficient and the confidence level of each reference adhesion coefficient, comprising:
if the confidence coefficient of the steady-state attachment coefficient is greater than or equal to 1, determining the activation duration of the stability control system of the vehicle;
acquiring a historical target attachment coefficient of the vehicle at the last moment;
And determining the target adhesion coefficient and the confidence coefficient of the target adhesion coefficient according to the steady-state adhesion coefficient, the activation duration and the historical target adhesion coefficient.
8. The method of claim 7, wherein determining the target adhesion coefficient, and a confidence level for the target adhesion coefficient, based on the steady state adhesion coefficient, the activation duration, and the historical target adhesion coefficient, comprises:
obtaining a coefficient difference value between the steady-state attachment coefficient and the historical target attachment coefficient;
Determining an adjustment coefficient according to the activation time length, and determining the product of the adjustment coefficient and the coefficient difference value as a coefficient adjustment quantity;
Determining the sum of the historical target attachment coefficient and the coefficient adjustment amount as the target attachment coefficient;
and determining the confidence coefficient of the target attachment coefficient as a sixth preset value.
9. An adhesion coefficient determining apparatus, comprising:
An acquisition module for acquiring at least one reference adhesion coefficient of the vehicle, and a confidence level of each reference adhesion coefficient, the at least one reference adhesion coefficient including at least one of: steady state attachment coefficient, dynamic attachment coefficient, longitudinal attachment coefficient or transverse attachment coefficient;
The acquisition module is further used for acquiring sensor states of a plurality of sensors of the vehicle, wherein the sensor states are normal states or failure states;
The processing module is further configured to determine a target adhesion coefficient of the vehicle and a confidence level of the target adhesion coefficient according to the at least one reference adhesion coefficient, the confidence level of each reference adhesion coefficient, and the sensor states of the plurality of sensors.
10. A vehicle, characterized by comprising:
A processor, and a memory communicatively coupled to the processor;
the memory is used for storing computer execution instructions;
The processor is configured to execute computer-executable instructions stored in the memory to implement the method for determining an adhesion coefficient according to any one of claims 1 to 8.
11. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein computer executable instructions for implementing the method of determining the adhesion coefficient according to any of claims 1-8 when executed by a processor.
12. A computer program product comprising a computer program which, when executed by a processor, implements the method of determining an attachment coefficient according to any of claims 1-8.
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| CN202410301414.1A CN118004189A (en) | 2024-03-15 | 2024-03-15 | Method, device, vehicle, medium and program product for determining adhesion coefficient |
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| CN202410301414.1A CN118004189A (en) | 2024-03-15 | 2024-03-15 | Method, device, vehicle, medium and program product for determining adhesion coefficient |
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