CN-116572967-B - Identification method and device for automobile pavement information, vehicle and storage medium

CN116572967BCN 116572967 BCN116572967 BCN 116572967BCN-116572967-B

Abstract

The application relates to an identification method, a device, a vehicle and a storage medium of automobile road surface information, wherein the method comprises the steps of collecting running data of the vehicle, judging the current running condition of the vehicle based on the running data of the vehicle, calculating a first parameter of a road surface according to the running data of the vehicle if the current running condition of the vehicle is a first preset condition, calculating a first attachment coefficient based on the first parameter and a first preset strategy, calculating a second parameter of the road surface according to the running data of the vehicle if the current running condition of the vehicle is a second preset condition, obtaining a second attachment coefficient based on the second parameter and the second preset strategy, filtering the first attachment coefficient or the second attachment coefficient to obtain a final attachment coefficient value, searching a relation table of preset standard road condition attachment coefficient-road condition information by taking the final attachment coefficient value as an index, and obtaining the current road condition information of the road surface.

Inventors

WU YIFENG
QI LINXING
SUN LIFEI

Assignees

奇瑞汽车股份有限公司

Dates

Publication Date: 20260505
Application Date: 20230517

Claims (9)

1. The method for identifying the automobile pavement information is characterized by comprising the following steps of: collecting running data of a vehicle, and judging the current running condition of the vehicle based on the running data of the vehicle; If the current running condition of the vehicle is a first preset condition, calculating a first parameter of a road surface according to running data of the vehicle, calculating a first attachment coefficient based on the first parameter and a first preset strategy, if the current running condition of the vehicle is a second preset condition, calculating a second parameter of the road surface according to the running data of the vehicle, obtaining a second attachment coefficient based on the second parameter and the second preset strategy, and filtering the first attachment coefficient or the second attachment coefficient to obtain a final attachment coefficient value, wherein the first preset condition is a linear running condition, the second preset condition is a nonlinear running condition, and Searching a relation table of attachment coefficients and road condition information of preset standard road conditions by taking the final attachment coefficient value as an index to obtain the current road condition information of the road surface; if the current driving condition of the vehicle is a second preset condition, calculating a second parameter of the road surface according to the driving data of the vehicle, and obtaining a second attachment coefficient based on the second parameter and a second preset strategy, wherein the method comprises the following steps: calculating a steady-state yaw rate of the vehicle according to vehicle running data, calculating a corresponding corrected yaw rate by using the steady-state yaw rate, calculating a difference between the corrected yaw rate and an actual yaw rate to obtain a yaw rate difference, and calculating an absolute value of lateral acceleration of the vehicle and an absolute value of the yaw rate difference based on the vehicle running data; carrying out fuzzification processing on the absolute value of the lateral acceleration and the absolute value of the yaw rate difference, and obtaining a second similarity coefficient according to a preset fuzzy inference table; and obtaining the second attachment coefficient according to the second similarity coefficient and a preset correction formula.
2. The method of claim 1, wherein the vehicle travel data includes at least one of a vehicle speed, a front wheel angle, a yaw rate, a side/longitudinal acceleration, an engine output torque, a gear, and a grade signal of the vehicle.
3. The method of claim 1, wherein if the current driving condition of the vehicle is a first preset condition, calculating a first parameter of a road surface according to driving data of the vehicle, and calculating a first adhesion coefficient based on the first parameter and a first preset strategy, comprises: Calculating a slip ratio and a utilization adhesion coefficient of the road surface based on the vehicle running data; Blurring the slip rate and the attachment coefficient, and obtaining six first similarity coefficients based on a preset fuzzy inference table; And calculating the first attachment coefficient according to the first similarity coefficient.
4. A method according to claim 3, wherein the first attachment coefficient is calculated as: Wherein λ opt is the first adhesion coefficient, k 1~6 is the first similarity coefficient, and λ 1~6 is the utilization adhesion coefficient.
5. The method of claim 1, wherein the predetermined correction formula is as follows: Wherein f (k) is a correction function, k is the second similarity coefficient, a, b, c, d is a correction function coefficient, μ is a road adhesion coefficient to be found, γ is a proportional coefficient to be taken as 1.19, a y is a lateral acceleration, and g is a gravitational acceleration.
6. The method according to claim 1, wherein after searching a preset standard road condition attachment coefficient-road condition information relationship table with the final attachment coefficient value as an index to obtain the current road condition information of the road surface, further comprising: generating a prompt signal and/or a feedback signal according to the road condition information; and receiving the prompting signal and/or the feedback signal, and feeding back the current road condition information of the road surface to a user in an acoustic and/or optical mode.
7. An apparatus for identifying road surface information of an automobile, comprising: The acquisition module is used for acquiring the running data of the vehicle and judging the current running condition of the vehicle based on the running data of the vehicle; The calculation module is configured to calculate a first parameter of a road surface according to driving data of the vehicle if the current driving condition of the vehicle is a first preset condition, calculate a first adhesion coefficient based on the first parameter and a first preset strategy, calculate a second parameter of the road surface according to driving data of the vehicle if the current driving condition of the vehicle is a second preset condition, obtain a second adhesion coefficient based on the second parameter and the second preset strategy, and filter the first adhesion coefficient or the second adhesion coefficient to obtain a final adhesion coefficient value, where the first preset condition is a linear driving condition, the second preset condition is a nonlinear driving condition, and The searching module is used for searching a relation table of attachment coefficients and road condition information of preset standard road conditions by taking the final attachment coefficient value as an index to obtain the current road condition information of the road surface; wherein the computing module comprises: A third calculation unit configured to calculate a steady yaw rate of the vehicle according to vehicle running data, calculate a corresponding corrected yaw rate using the steady yaw rate, and calculate a difference between the corrected yaw rate and an actual yaw rate to obtain a yaw rate difference, and calculate an absolute value of a lateral acceleration of the vehicle and an absolute value of the yaw rate difference based on the vehicle running data; The second fuzzy processing unit is used for carrying out fuzzification processing on the absolute value of the lateral acceleration and the absolute value of the yaw rate difference, and obtaining a second similarity coefficient according to a preset fuzzy inference table; And the correction unit is used for obtaining the second attachment coefficient according to the second similarity coefficient and a preset correction formula.
8. A vehicle comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor executing the program to implement the method of identifying automotive road information as claimed in any one of claims 1 to 6.
9. A computer-readable storage medium having stored thereon a computer program, characterized in that the program is executed by a processor for realizing the identification method of automotive road surface information according to any one of claims 1 to 6.

Description

Identification method and device for automobile pavement information, vehicle and storage medium Technical Field The application relates to the technical field of development of four-wheel drive systems, in particular to an identification method and device of automobile pavement information, a vehicle and a storage medium. Background As one of the important parameters of the four-wheel drive system, the road adhesion coefficient has a great influence on the torque distribution of the four-wheel drive system, the yaw stability control of ABS (AntilockBrake System, brake anti-lock system) and other systems for calculating the dynamics of the automobile, so that the road adhesion coefficient has an important meaning on the research of the recognition of the road adhesion state. With the recognition of the importance of the vehicle running state parameters to the vehicle safety active control system by domestic and foreign scholars, enterprises and universities at home and abroad are put into great efforts for vehicle running state parameter estimation. In the traditional mode, the running state parameters of the automobile are mainly measured by a sensor, and the mode of measuring by using an instrument has high accuracy and strong practicability, but the measuring cost is too high to limit the wide use of the automobile, and the automobile is not suitable for being popularized and used in business, so that the identification of some key running state parameters of the automobile by using the technology of an on-board sensor combined algorithm becomes a main research method. At present, the existing adhesion coefficient identification method is mostly limited to a specific working condition, cannot meet the requirement of updating data in real time, and is low in accuracy, so that the problem is to be solved. Disclosure of Invention The application provides an identification method, an identification device, a vehicle and a storage medium for automobile pavement information, which are used for solving the problems that the adhesion coefficient can be estimated only under specific working conditions in the prior art, the requirement for updating data in real time can not be met, the accuracy is low and the like. An embodiment of the application provides an identification method of automobile road surface information, which comprises the following steps of collecting running data of a vehicle, judging the current running condition of the vehicle based on the running data of the vehicle, calculating a first parameter of a road surface according to the running data of the vehicle if the current running condition of the vehicle is a first preset condition, calculating a first attachment coefficient based on the first parameter and a first preset strategy, calculating a second parameter of the road surface according to the running data of the vehicle if the current running condition of the vehicle is a second preset condition, obtaining a second attachment coefficient based on the second parameter and the second preset strategy, filtering the first attachment coefficient or the second attachment coefficient to obtain a final attachment coefficient value, and searching a relation table of a preset standard road condition attachment coefficient and road condition information by taking the final attachment coefficient value as an index to obtain the current road condition information of the road surface. Optionally, in one embodiment of the present application, the running data of the vehicle includes at least one of a vehicle speed, a front wheel rotation angle, a yaw rate, a side/longitudinal acceleration, an engine output torque, a gear, and a gradient signal of the vehicle. Optionally, in one embodiment of the present application, if the current driving condition of the vehicle is a first preset condition, calculating a first parameter of a road surface according to driving data of the vehicle, and calculating a first attachment coefficient based on the first parameter and a first preset policy, where the calculating includes calculating a slip rate and an attachment coefficient of the road surface based on the driving data of the vehicle, performing a blurring process on the slip rate and the attachment coefficient, and obtaining six first similarity coefficients based on a preset fuzzy inference table, and calculating the first attachment coefficient according to the first similarity coefficients. Optionally, in one embodiment of the present application, if the current driving condition of the vehicle is a second preset condition, calculating a second parameter of the road surface according to the driving data of the vehicle, and obtaining a second attachment coefficient based on the second parameter and a second preset policy, where the calculating includes calculating an absolute value of a lateral acceleration and an absolute value of a yaw rate difference of the vehicle based on the driving data of the vehicl