CN113433931A - Automobile CAN bus key signal analysis method based on characteristic working conditions - Google Patents
Automobile CAN bus key signal analysis method based on characteristic working conditions Download PDFInfo
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Abstract
The invention discloses an automobile CAN bus key signal analysis method based on characteristic working conditions, which comprises the following steps: screening the acquired CAN bus data, and reserving a data ID number and message data; eliminating the message data lines with message data changes in the initial segment and the final segment; eliminating the message data line with unchanged ID of the message in the process section; for the reserved change data line, removing repeated message data, acquiring data state representation, and subsequently outputting an analysis file at a corresponding time position; and outputting the file to a parsing file. By the analytical method, the corresponding signals are found to show specific change rules under the working conditions of static accelerator pedal oiling and static brake pedal braking, so that judgment and support are provided for position searching and matching of the signals.
Description
Technical Field
The invention relates to the technical field of vehicle bus signal analysis, in particular to an automobile CAN bus key signal analysis method based on characteristic working conditions.
Background
During vehicle development, the vehicle is a conventional method for mapping. When a mapping test is performed, it is often necessary to know the vehicle signal values related to the test so as to master the working state of the vehicle during the test, and it is very important to find and obtain an accurate vehicle signal.
The can (controller Area network) bus is a main communication mode of vehicle communication and is also a main channel for key signal transmission. Compared with a method for installing a sensor, the method for analyzing the key signals of the vehicle through the CAN line is a convenient and fast mode.
The key signals are signals representing the working states of the whole vehicle and the core components. The signals of the whole vehicle mainly relate to the operation of a driver, and comprise an accelerator stroke, a brake stroke, a clutch stroke, a steering wheel corner and the like, the signals of core components of the traditional vehicle mainly comprise engine rotating speed, engine torque and the like, and the signals of core components of the pure electric vehicle mainly comprise driving motor rotating speed, driving motor torque, high-voltage battery current, high-voltage battery voltage and the like. The knowledge of the key signals corresponds to the basic knowledge of the current operating state of the vehicle.
Through analysis of CAN bus key signals, the basic running state of the vehicle CAN be recorded by using data acquisition hardware in the vehicle testing process. On one hand, benchmarking and data analysis among different vehicles can be better carried out, and on the other hand, the development idea of the benchmarking vehicles can be known, so that reference learning is provided, and powerful support is provided for vehicle development. Therefore, it is necessary to provide a method for analyzing the key signals of the automobile CAN bus based on the characteristic working conditions, so as to provide judgment and support for the position search and matching of the signals.
Disclosure of Invention
In view of the above-mentioned problems, an object of the present invention is to provide a method for analyzing a key signal of a CAN bus of an automobile based on characteristic conditions, which provides a judgment and support for position search and matching of the signal.
In order to achieve the purpose, the invention adopts the following technical scheme: a key signal analysis method of an automobile CAN bus based on characteristic working conditions comprises the following specific analysis method: step 1: screening the acquired CAN bus data, and reserving a data ID number and message data; step 2: eliminating the message data lines with message data changes in the initial segment and the final segment; and step 3: eliminating the message data line with unchanged ID of the message in the process section; and 4, step 4: for the reserved variable data row, removing repeated message data, taking a message data value of a time position in an initial section and a message data maximum value in a process section from the message data, converting the message data values into 10-system values, and determining whether the value obtained by subtracting the message data value in the initial section from the message data maximum value is greater than 16, if so, representing the data value; if the judgment result is no, representing the data state; and 5: for data state representation, after a binary value is converted, an exclusive OR value of two time point positions is taken; converting the exclusive OR value into a decimal system again to obtain a position of 1 in the binary value, and subsequently outputting an analysis file at a corresponding time position, wherein 0 represents that the state does not occur, and 1 represents that the state occurs; linear judgment is firstly carried out on data value representation, a plurality of time positions are taken between a message data value at one time position in an initial segment and a message data maximum value in a process segment, and message data comparison is carried out, wherein the following conditions are met: in the process segment, the message data is more than or equal to the message data value of the initial segment, the message data of the next time position is more than the message data of the previous time position, and the message data of the last time position is the maximum value; step 6: outputting to an analysis file: and for the message data meeting the linear increase, calculating a k value, then calculating a b value, and subsequently outputting the k value and the b value to an analysis file at corresponding time positions, wherein the k value is a linear function variable coefficient, and the b value is a constant coefficient.
In the step 2, a plurality of time points are selected in the initial segment and the final segment respectively, if the obtained message data at each time point are the same, the ID message data line is judged to be unchanged, the message data line is reserved, and the message data lines in other situations are removed.
In the step 3, the message data of a plurality of time points of the process segment data are selected as comparison data, a data point is taken from the initial segment and the final segment as reference data, if the comparison data is not equal to the reference data, the data is judged to be a change line, the data is reserved, and the data lines in other situations are removed.
Compared with the prior art, the method for analyzing the key signals of the automobile CAN bus based on the characteristic working conditions has the advantages that the analysis method enables the corresponding signals to show specific change rules under the working conditions of static accelerator pedal oiling and static brake pedal braking, so that judgment and support are provided for position searching and matching of the signals.
DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION
The technical solutions in the embodiments of the present invention are clearly and completely described below through the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention discloses an automobile CAN bus key signal analysis method based on characteristic working conditions, which confirms a target automobile CAN line, tests the characteristic working conditions, collects CAN bus data in real time, provides signal characteristics under each working condition according to a signal database in each established characteristic working condition, inputs test data of a target automobile, corresponds the data in the working conditions, calculates signal matching and outputs an analysis file.
The characteristic working condition evaluation comprises static accelerator pedal evaluation and static brake pedal evaluation, wherein the static accelerator pedal evaluation is realized by slowly stepping the accelerator pedal from an original state to a maximum position through a low-power state on a vehicle, then quickly releasing the accelerator pedal to the original position, and acquiring a key signal of the accelerator opening;
the evaluation mode of the static brake pedal is that the brake pedal is slowly stepped from an original state to a maximum position through a low-power state on the vehicle, then the pedal is quickly released to the original position, and a key signal of the brake opening degree is obtained;
wherein the working condition evaluation process is divided into three sections: the method comprises an initial section, a process section and an end section, wherein the initial section and the end section are both set with a preset time (5s) and do not need to be operated, and the intermediate process between the initial section and the end section is defined as the process section.
The process section comprises the following specific operations: in a low-power state on a vehicle, firstly, the accelerator pedal is slowly stepped to the maximum position from the original state, the preset time (5s) is set, then the maximum position is kept for the designated time (3s), and finally, the pedal is quickly released to the original position for about 0.5-1 s. The corresponding steps can be divided into three parts, namely, stepping down the pedal section, keeping the maximum value section and loosening the pedal section.
The signal characteristics of the static accelerator pedal evaluation and the static brake pedal evaluation are as follows: an initial stage: an invariant value; a process section: linearly increasing to a maximum value and rapidly decreasing after stabilizing for a period of time; and an ending section: the data is equal to its real value. The key signals of the static accelerator pedal are the accelerator opening and the brake opening of the static brake pedal.
For the recorded CAN bus data, the specific analysis method is as follows:
step 1: and screening the acquired CAN bus data, and reserving the data ID number and the message data.
Step 2: and (3) rejecting a message data line with message data change in the initial segment and the end segment (the message data is composed of B1-B8 data, the message data line is composed of a line position of the data, an ID number and message data), selecting a plurality of time points in the initial segment and the end segment respectively, and judging that the ID message data line is unchanged, the message data line is reserved and the message data lines in other situations are rejected when the message data obtained at each time point are the same (when the initial segment and the end segment respectively select 3 time points and satisfy the following formula (1)).
DataBi，start1＝DataBi，start2＝DataBi，start3＝DataBi，end1＝DataBi，end2＝DataBi，end3 (1)
Wherein DataBi， start The message data at a certain time point in the initial period; dataBi，endIs the message data at a certain time point of the ending segment. As shown in the following table,
| Line | Arb ID | B1 | B2 | B3 | B4 | B5 | B6 | B7 | B8 |
| 379 | 3B7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
| 761 | 3B7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
| 1130 | 3B7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
| 1512 | 3B7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
| 1886 | 3B7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
| 2263 | 3B7 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 8 |
line represents a time point position; ArbID represents the ID number of the message data at the time point; the combination of B1-B8 represents the specific message data, and as shown in the above table, when the message data composed of B1-B8 in the six columns are identical, the condition is satisfied, so that the data can be retained.
And step 3: eliminating the message data line with unchanged ID of the message in the process segment: selecting message data of a plurality of time points of process section data as comparison data, taking a data point from the initial section and the final section as reference data, if the comparison data is not equal to the reference data, judging that the line data is a change line, reserving the data, and removing the data lines in other situations.
Namely, the following formula (2) is satisfied,
DataBi，processi≠DataBi，start＝DataBi，end (2)；
wherein DataBi，processIs the message data at a certain time point in the process segment;
and 4, step 4: and for the reserved variable data lines, removing repeated message data, taking a message data value of a time position in the initial section and a message data maximum value in the process section from the message data, converting the message data value into a 10-system value, and judging whether the value obtained by subtracting the message data value in the initial section from the message data maximum value is greater than 16 or not, if so, representing the data value. And if the judgment result is no, representing the data state. Namely, the comparison of the formula (3),
HEX2DE(DataBi，max)-HEX2DE(DataBi，start)＞16 (3)；
HEX2DE is a conversion of hexadecimal to decimal;
and 5: for data state characterization, after converting the binary value, taking the exclusive OR value of the two time point positions. The xor value is converted back to decimal and the position of 1 in the binary value is determined (recorded from right to left). And then, outputting the data to an analysis file at a corresponding position, wherein 0 represents that the state does not occur, and 1 represents that the state occurs. As shown in the following formula (4),
HEX2BIN(DataBi，max)xor HEX2BIN(DataBi，start) (4)
HEX2BIN is the conversion of a hexadecimal number to a binary number;
linear judgment is firstly carried out on data value representation, a plurality of time positions (10 points) are taken between a message data value at one time position in an initial section and a message data maximum value in a process section, each point is separated by 0.3s from the 1 st s in the process section, and comparison is carried out, wherein the following conditions are met: in the process segment, the message data is greater than or equal to the message data value of the initial segment, in the process segment, the message data of the next time position is greater than the message data of the previous time position, and the message data of the last time position is the maximum value. That is, equation 5 should be satisfied:
HEX2DE(DataBi，start)≤···＜HEX2DE(DataBi，processi)＜···≤HEX2DE(DataBi，max) (5)
step 6: outputting to an analysis file: for the message data meeting the linear increase, the k value is obtained according to the following formula, then the b value is obtained, and the k value is output to an analysis file at the corresponding time position, wherein the k value is a linear function variable coefficient, and the b value is a constant coefficient.
b＝-k*HEX2DE(DataBi，start) (7)
And obtaining a signal characteristic schematic diagram of the automobile through the obtained k and b values, and knowing the information of an accelerator pedal and a brake pedal of the automobile. And judging the position and the form of the signal by judging the data change in the process. By the analysis method, the corresponding signals are found to show a specific change rule under the working conditions of static accelerator pedal oiling and static brake pedal braking, so that judgment and support are provided for position searching and matching of the signals.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims.
Claims (3)
1. A method for analyzing key signals of an automobile CAN bus based on characteristic working conditions is characterized by comprising the following steps:
step 1: screening the acquired CAN bus data, and reserving a data ID number and message data;
step 2: eliminating the message data lines with message data changes in the initial segment and the final segment;
and step 3: eliminating the message data line with unchanged ID of the message in the process section;
and 4, step 4: for the reserved variable data row, removing repeated message data, taking a message data value of a time position in an initial section and a message data maximum value in a process section from the message data, converting the message data values into 10-system values, and determining whether the value obtained by subtracting the message data value in the initial section from the message data maximum value is greater than 16, if so, representing the data value; if the judgment result is no, representing the data state;
and 5: for data state representation, after a binary value is converted, an exclusive OR value of two time point positions is taken; converting the exclusive OR value into a decimal system again to obtain a position of 1 in the binary value, and subsequently outputting an analysis file at a corresponding time position, wherein 0 represents that the state does not occur, and 1 represents that the state occurs;
linear judgment is firstly carried out on data value representation, a plurality of time positions are taken between a message data value at one time position in an initial segment and a message data maximum value in a process segment, and message data comparison is carried out, wherein the following conditions are met: in the process segment, the message data is more than or equal to the message data value of the initial segment, the message data of the next time position is more than the message data of the previous time position, and the message data of the last time position is the maximum value;
step 6: outputting to an analysis file: and for the message data meeting the linear increase, calculating a k value, then calculating a b value, and subsequently outputting the k value and the b value to an analysis file at corresponding time positions, wherein the k value is a linear function variable coefficient, and the b value is a constant coefficient.
2. The method for analyzing the key signals of the CAN bus of the automobile based on the characteristic working conditions as claimed in claim 1, wherein: in the step 2, a plurality of time points are selected in the initial segment and the final segment respectively, if the obtained message data at each time point are the same, the ID message data line is judged to be unchanged, the message data line is reserved, and the message data lines in other situations are removed.
3. The method for analyzing the key signals of the CAN bus of the automobile based on the characteristic working conditions as claimed in claim 1, wherein: in the step 3, the message data of a plurality of time points of the process section data are selected as comparison data, a data point is respectively selected from the initial section and the final section as reference data, if the comparison data is not equal to the reference data, the data in the line is judged to be a change line, the data is reserved, and the data in other situations are removed.
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