Vehicle bus signal filtering method and system
By constructing filtering algorithms and models and self-adjusting filter parameters, the problem of low sensitivity and unstable filtering effect in the prior art is solved, and more efficient and stable filtering processing is achieved.
Patent Information
- Application Number
- CN202411008602.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-07-26
- Publication Date
- 2024-12-17
AI Technical Summary
In the prior art, the filter coefficient is adjusted by threshold values, resulting in low sensitivity of the filtering effect of the vehicle bus signal and unstable results.
By obtaining the input data of the historical vehicle bus signal, the filter data outputted by the last time and the filter data outputted by the current time, a filter algorithm and filter coefficient model are constructed, and iterative filtering processing is performed, the filter parameters are updated according to the difference value, and the filter coefficient is adjusted by itself to improve the The robustness and efficiency of the filtering algorithm.
It effectively improves the sensitivity and stability of the filtering process, avoids the problems of unstable results or low sensitivity caused by inappropriate filter coefficients, and achieves a more accurate and stable filtering effect.
Smart Images
Figure CN119149883A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of data processing, and in particular to a filtering method and system for vehicle bus signals. Background Art
[0002] When the vehicle sensor receives the vehicle bus signal, it generally needs to be processed by the chassis electronic control software and then filtered before the application layer software is called to avoid vehicle working environment such as vibration, road bumps, etc., which may cause vehicle bus signal fluctuations. When the vehicle bus signal is transmitted to the application layer software, the fluctuation is too large, causing the application layer function to exit abnormally.
[0003] At present, the filtering of vehicle bus signals generally adopts a first-order low-pass filtering algorithm. Through the linear system differential equation, the filtering performance is adjusted by adjusting the filtering coefficient. When the input signal fluctuates greatly and reaches the threshold, the filtering coefficient is reduced to reduce the signal fluctuation. However, adjusting the filtering coefficient through the threshold will result in low filtering sensitivity and unstable filtering results. Summary of the invention
[0004] In view of this, the purpose of the present invention is to provide a vehicle bus signal filtering method and system, aiming to solve the problem in the prior art that adjusting the filtering coefficient by threshold value will lead to low filtering sensitivity and unstable filtering results.
[0005] A first aspect of the present invention is to provide a method for filtering a vehicle bus signal, the method comprising:
[0006] Obtain historical input data of historical vehicle bus signals, corresponding filtering data of the previous historical output, and corresponding filtering data of the current historical output, construct a filtering algorithm, and obtain corresponding historical filtering coefficients;
[0007] Calculating a historical difference between the historical input data and the corresponding filtered data outputted last time in history, and constructing a filter coefficient model based on the historical difference and the historical filter coefficient;
[0008] Performing n iterative filtering processes on the vehicle bus signal, wherein the filtering parameters used in each iterative filtering process are updated based on the filter coefficient model output according to the difference between the input data of the current vehicle bus signal and the output data obtained after the previous iterative filtering process;
[0009] According to the filtering parameters, the filtering algorithm is input and the current filtering data of the current vehicle bus signal is output.
[0010] Compared with the prior art, the beneficial effects of the present invention are as follows: the filtering method for vehicle bus signals provided by the present invention can effectively improve the sensitivity and stability of the filtering process, specifically, by obtaining the historical input data of the historical vehicle bus signal, the corresponding filtering data outputted last time in history, and the corresponding filtering data outputted at that time in history, constructing a filtering algorithm, and obtaining the corresponding historical filtering coefficient, which can effectively perform filtering processing and improve the accuracy of the output filtered signal; calculating the historical difference between the historical input data and the corresponding filtering data outputted last time in history, constructing a filtering coefficient model based on the historical difference and the historical filtering coefficient, constructing the filtering coefficient model through the historical difference and the historical filtering coefficient, which can be adjusted according to the specific situation of the vehicle, can effectively self-adjust the filtering coefficient, improve the robustness and efficiency of the filtering algorithm, and improve the stability and Sensitivity and stability, avoiding the phenomenon that the filtering result is unstable or the sensitivity is too low due to inappropriate filtering coefficients; the vehicle bus signal is iterated and filtered n times, and the filtering parameters used in each iterative filtering process are based on the difference between the input data of the current vehicle bus signal and the output data obtained after the previous iterative filtering process, and the filtering parameters are updated based on the filtering coefficient model output, and the filtering parameters are adjusted and updated based on the filtering coefficient model according to the difference, so that the filtering process is more accurate, sensitive and stable, avoiding the phenomenon that the filtering effect sensitivity is low and the filtering result is unstable due to the filtering coefficient adjusted by the threshold; according to the filtering parameters, the filtering algorithm is input, and the current filtering data of the current vehicle bus signal is output, thereby solving the technical problem that the filtering effect sensitivity is low and the filtering result is unstable due to the filtering coefficient adjusted by the threshold.
[0011] According to one aspect of the above technical solution, the formula of the filtering algorithm is:
[0012] Y(n)=k×X(n)+(1-k)×Y(n-1),
[0013] Among them, Y(n) is the filtered data output for the nth time, X(n) is the input data input for the nth time, Y(n-1) is the filtered data output for the n-1th time, and k is the filter coefficient.
[0014] According to one aspect of the above technical solution, the construction formula of the filter coefficient model is:
[0015] Use the difference |X(n)-Y(n-1)| as the function input x to build the filter coefficient model.
[0016]
[0017] Among them, a, b, c, d are constraint coefficients according to vehicle tests, k is a filter coefficient, and x is |X(n)-Y(n-1)|.
[0018] According to one aspect of the above technical solution, the method further includes:
[0019] collecting in real time the current filtering data updated by the filtering coefficient model and the input data of the vehicle bus signal;
[0020] Calculating a deviation rate between the current filtered data and the input data;
[0021] Determining whether the deviation rate is greater than a preset deviation value;
[0022] If yes, stop outputting the current filtered data;
[0023] If not, output the current filtered data.
[0024] According to one aspect of the above technical solution, the steps after stopping outputting the current filtered data specifically include:
[0025] Calculating preset filtering data according to the preset deviation value and input data;
[0026] Obtaining a preset filter coefficient based on the filtering algorithm according to the preset filter data, the output data obtained after the previous iterative filtering process, and the input data;
[0027] The preset filter coefficient is used to modify the filter coefficient model, and then the preset filter data is updated to be the current filter data output.
[0028] According to one aspect of the above technical solution, the method further includes:
[0029] The historical filter coefficients may also be obtained by testing the vehicle bus signal by adjusting interference signals of different vehicle environments.
[0030] According to one aspect of the above technical solution, the historical filter coefficient can also be obtained by adjusting the interference signals of different vehicle environments to test the vehicle bus signal, specifically including:
[0031] Acquire a preset bus signal of the vehicle, a preset bus signal processed by the previous iterative filtering, and a real bus signal interfered by an interference signal;
[0032] Based on the filtering algorithm, the historical filtering coefficient is obtained.
[0033] A second aspect of the present invention is to provide a vehicle bus signal filtering system, which is used to perform any one of the vehicle bus signal filtering methods described above, and the system comprises:
[0034] A filtering algorithm building module is used to obtain historical input data of historical vehicle bus signals, corresponding filtering data of the previous historical output, and corresponding filtering data of the current historical output, build a filtering algorithm, and obtain corresponding historical filtering coefficients;
[0035] A model building module, used for calculating the historical difference between the historical input data and the corresponding filtering data outputted in the past, and building a filtering coefficient model based on the historical difference and the historical filtering coefficient;
[0036] A filter parameter updating module, used for performing n iterative filtering processes on the vehicle bus signal, wherein the filter parameters used in each iterative filtering process are updated based on the filter coefficient model output according to the difference between the input data of the current vehicle bus signal and the output data obtained after the previous iterative filtering process;
[0037] The filter data processing module is used to input the filter algorithm according to the filter parameters and output the current filter data of the current vehicle bus signal.
[0038] A third aspect of the present invention is to provide a readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the steps of any one of the methods described above.
[0039] A fourth aspect of the present invention is to provide an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any one of the methods described above when executing the program. BRIEF DESCRIPTION OF THE DRAWINGS
[0040] Figure 1 is a flow chart of a method for filtering a vehicle bus signal in a first embodiment of the present invention;
[0041] Figure 2 A structural block diagram of filtering of a vehicle bus signal in a second embodiment of the present invention;
[0042] Component symbol description:
[0043] Filter algorithm construction module 100, model construction module 200, filter parameter update module 300, filter data processing module 400.
[0044] The following specific implementation manner will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION
[0045] In order to facilitate the understanding of the present invention, the present invention will be described more fully below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, the purpose of providing these embodiments is to make the disclosure of the present invention more thorough and comprehensive.
[0046] It should be noted that when an element is referred to as being "fixed to" another element, it may be directly on the other element or there may be a central element. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be a central element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.
[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed types.
[0048] The analysis will be described in detail below with reference to specific embodiments and drawings.
[0049] Embodiment 1
[0050] See also Figure 1 , which shows a method for filtering a vehicle bus signal in a first embodiment of the present invention, and the method includes steps S10 to S13.
[0051] Step S10, obtaining historical input data of historical vehicle bus signals, corresponding filtering data of the previous historical output, and corresponding filtering data of the current historical output, constructing a filtering algorithm, and obtaining corresponding historical filtering coefficients;
[0052] The formula of the filtering algorithm is:
[0053] Y(n)=k×X(n)+(1-k)×Y(n-1),
[0054] Among them, Y(n) is the filtered data output for the nth time, X(n) is the input data input for the nth time, Y(n-1) is the filtered data output for the n-1th time, and k is the filter coefficient.
[0055] It should be noted that by performing calculation and analysis on the input data, the last output filtered data, and the current output filtered data, a filtering algorithm can be constructed, which can effectively perform filtering processing and improve the accuracy of the output filtered signal.
[0056] Step S11, calculating the historical difference between the historical input data and the corresponding historical output filter data, and constructing a filter coefficient model based on the historical difference and the historical filter coefficient;
[0057] Among them, the construction formula of the filter coefficient model is:
[0058] Use the difference |X(n)-Y(n-1)| as the function input x to build the filter coefficient model.
[0059]
[0060] Among them, a, b, c, d are constraint coefficients according to vehicle tests, k is a filter coefficient, and x is |X(n)-Y(n-1)|.
[0061] Specifically, [0, a] is a small fluctuation segment, the filter coefficient k is small, and the filtering is stable; (a, b) is a large fluctuation segment, the filter coefficient k is large, and the sensitivity is high. The selection of a and b should be based on the signal type and the corresponding range, so that the signal small fluctuation range is [0, a]; b should select the maximum value of the reasonable change of the signal physical quantity. When the difference is greater than b, the signal sampling value can be considered abnormal and treated as 0. The constraints of c and d parameters can be adjusted according to the specific test results of the vehicle.
[0062] Furthermore, by constructing a filter coefficient model through historical differences and historical filter coefficients, it can be adjusted according to the specific conditions of the vehicle, and can effectively self-adjust the filter coefficients, thereby improving the robustness and efficiency of the filtering algorithm, improving the stability and sensitivity of the filtering process, and avoiding the phenomenon of unstable filtering results or too low sensitivity due to inappropriate filter coefficients.
[0063] In addition, the method further comprises:
[0064] The historical filter coefficients may also be obtained by testing the vehicle bus signal by adjusting interference signals of different vehicle environments.
[0065] Specifically, a preset bus signal of the vehicle, a preset bus signal processed by the previous iterative filtering, and a real bus signal interfered by the interference signal are obtained;
[0066] Based on the filtering algorithm, the historical filtering coefficient is obtained.
[0067] Therefore, by testing the impact of interference signals in different vehicle environments on vehicle bus signals, the filter coefficients can be adjusted and regulated. Adjustments can be made according to the specific conditions of the vehicle, which can effectively self-regulate the filter coefficients, improve the robustness and efficiency of the filtering algorithm, and improve the stability, sensitivity and stability of the filtering process.
[0068] Step S12, performing n iterative filtering processes on the vehicle bus signal, wherein the filtering parameters used in each iterative filtering process are updated based on the filter coefficient model output according to the difference between the input data of the current vehicle bus signal and the output data obtained after the previous iterative filtering process;
[0069] According to the difference, the filter parameters are adjusted and updated based on the filter coefficient model to make the filtering process more accurate, sensitive and stable, and avoid adjusting the filter coefficient through the threshold, which will lead to low sensitivity of the filtering effect and unstable filtering results.
[0070] Furthermore, the method further comprises:
[0071] collecting in real time the current filtering data updated by the filtering coefficient model and the input data of the vehicle bus signal;
[0072] Calculating a deviation rate between the current filtered data and the input data;
[0073] Determining whether the deviation rate is greater than a preset deviation value;
[0074] If yes, stop outputting the current filtered data;
[0075] If not, output the current filtered data.
[0076] The steps after stopping outputting the current filtered data specifically include:
[0077] Calculating preset filtering data according to the preset deviation value and input data;
[0078] Obtaining a preset filter coefficient based on the filtering algorithm according to the preset filter data, the output data obtained after the previous iterative filtering process, and the input data;
[0079] The preset filter coefficient is used to modify the filter coefficient model, and then the preset filter data is updated to be the current filter data output.
[0080] In order to further improve the accuracy and sensitivity of the filtering process, the deviation rate is calculated by comparing the input data with the current filtering data, and the current filtering data is outputted according to the size of the deviation rate, thereby improving the accuracy of the filtering process.
[0081] Step S13, according to the filtering parameters, input the filtering algorithm, and output the current filtering data of the current vehicle bus signal.
[0082] In summary, the filtering method of the vehicle bus signal in the above-mentioned embodiment of the present invention can effectively improve the sensitivity and stability of the filtering process. Specifically, the historical input data of the historical vehicle bus signal, the corresponding filtering data outputted in the past, and the corresponding filtering data outputted at that time in the past are obtained, a filtering algorithm is constructed, and the corresponding historical filtering coefficient is obtained, which can effectively perform filtering processing and improve the accuracy of the output filtered signal; the historical difference between the historical input data and the corresponding filtering data outputted in the past is calculated, and a filtering coefficient model is constructed based on the historical difference and the historical filtering coefficient. The filtering coefficient model is constructed by the historical difference and the historical filtering coefficient, which can be adjusted according to the specific situation of the vehicle, and the filtering coefficient can be effectively self-adjusted, thereby improving the robustness and efficiency of the filtering algorithm, and improving the stability and sensitivity of the filtering process and the stability. The invention can improve the filtering efficiency and the filtering effect of the vehicle bus signal, and avoid the phenomenon that the filtering result is unstable or the sensitivity is too low due to the inappropriate filtering coefficient; the vehicle bus signal is iterated and filtered for n times, and the filtering parameters used in each iterative filtering process are updated based on the difference between the input data of the current vehicle bus signal and the output data obtained after the previous iterative filtering process, and the filtering parameters are updated based on the filtering coefficient model output, and the filtering parameters are adjusted and updated based on the filtering coefficient model according to the difference, so that the filtering process is more accurate, sensitive and stable, and avoid the phenomenon that the filtering effect sensitivity is low and the filtering result is unstable due to the filtering coefficient being adjusted by the threshold; according to the filtering parameters, the filtering algorithm is input, and the current filtering data of the current vehicle bus signal is output, thereby solving the technical problem that the filtering effect sensitivity is low and the filtering result is unstable due to the filtering coefficient being adjusted by the threshold.
[0083] Embodiment 2
[0084] See also Figure 2 , which is a filtering system for vehicle bus signals proposed in a second embodiment of the present invention, the system comprises:
[0085] The filtering algorithm building module 100 is used to obtain the historical input data of the historical vehicle bus signal, the corresponding filtering data of the previous historical output, and the corresponding filtering data of the current historical output, build a filtering algorithm, and obtain the corresponding historical filtering coefficient;
[0086] A model building module 200 is used to calculate the historical difference between the historical input data and the corresponding historical output filter data, and to build a filter coefficient model based on the historical difference and the historical filter coefficient;
[0087] A filter parameter updating module 300 is used to perform n iterative filtering processes on the vehicle bus signal, wherein the filter parameters used in each iterative filtering process are updated based on the filter coefficient model output according to the difference between the input data of the current vehicle bus signal and the output data obtained after the previous iterative filtering process;
[0088] The filter data processing module 400 is used to input the filter algorithm according to the filter parameters and output the current filter data of the current vehicle bus signal.
[0089] In summary, the filtering system of the vehicle bus signal in the above-mentioned embodiment of the present invention can effectively improve the sensitivity and stability of the filtering process. Specifically, the filtering algorithm construction module can effectively perform filtering processing and improve the accuracy of the output filtered signal; the model construction module uses historical differences and historical filtering coefficients to construct a filtering coefficient model, which can be adjusted according to the specific conditions of the vehicle, and can effectively self-adjust the filtering coefficient, thereby improving the robustness and efficiency of the filtering algorithm, improving the stability and sensitivity of the filtering process, and avoiding the phenomenon that the filtering result is unstable or the sensitivity is too low due to inappropriate filtering coefficients; the filtering parameter updating module adjusts and updates the filtering parameters based on the filtering coefficient model according to the difference, so that the filtering process is more accurate, sensitive and stable, and avoids the phenomenon that the filtering effect sensitivity is low and the filtering result is unstable due to the adjustment of the filtering coefficient through the threshold, thereby solving the technical problem that the filtering effect sensitivity is low and the filtering result is unstable due to the adjustment of the filtering coefficient through the threshold.
[0090] Embodiment 3
[0091] The third embodiment of the present invention further provides a readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of the method described in the first embodiment are implemented.
[0092] Embodiment 4
[0093] The fourth embodiment of the present invention further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method described in the first embodiment when executing the program.
[0094] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.
[0095] Those skilled in the art will appreciate that the logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable instructions for implementing logical functions, and may be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For purposes of this specification, a "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.
[0096] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.
[0097] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or a combination thereof: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.
[0098] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.
[0099] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.
Claims
1. A method for filtering a vehicle bus signal, characterized in that: The method comprises: Obtain historical input data of historical vehicle bus signals, corresponding filtering data of the previous historical output, and corresponding filtering data of the current historical output, construct a filtering algorithm, and obtain corresponding historical filtering coefficients; Calculating a historical difference between the historical input data and the corresponding filtered data outputted last time in history, and constructing a filter coefficient model based on the historical difference and the historical filter coefficient; Performing n iterative filtering processes on the vehicle bus signal, wherein the filtering parameters used in each iterative filtering process are updated based on the filter coefficient model output according to the difference between the input data of the current vehicle bus signal and the output data obtained after the previous iterative filtering process; According to the filtering parameters, the filtering algorithm is input and the current filtering data of the current vehicle bus signal is output.
2. The vehicle bus signal filtering method according to claim 1, characterized in that: The formula of the filtering algorithm is: Y(n)=k×X(n)+(1-k)×Y(n-1), Among them, Y(n) is the filtered data output for the nth time, X(n) is the input data input for the nth time, Y(n-1) is the filtered data output for the n-1th time, and k is the filter coefficient.
3. The vehicle bus signal filtering method according to claim 2, characterized in that: The construction formula of the filter coefficient model is: Use the difference |X(n)-Y(n-1)| as the function input x to build the filter coefficient model. Among them, a, b, c, d are constraint coefficients according to vehicle tests, k is a filter coefficient, and x is |X(n)-Y(n-1)|.
4. The vehicle bus signal filtering method according to claim 3, characterized in that: The method further comprises: collecting in real time the current filtering data updated by the filtering coefficient model and the input data of the vehicle bus signal; Calculating a deviation rate between the current filtered data and the input data; Determining whether the deviation rate is greater than a preset deviation value; If yes, stop outputting the current filtered data; If not, output the current filtered data.
5. The method for filtering a vehicle bus signal according to claim 34, characterized in that: The steps after stopping outputting the current filtered data specifically include: Calculating preset filtering data according to the preset deviation value and input data; Obtaining a preset filter coefficient based on the filtering algorithm according to the preset filter data, the output data obtained after the previous iterative filtering process, and the input data; The preset filter coefficient is used to modify the filter coefficient model, and then the preset filter data is updated to be the current filter data output.
6. The vehicle bus signal filtering method according to claim 1, characterized in that: The method further comprises: The historical filter coefficients may also be obtained by testing the vehicle bus signal by adjusting interference signals of different vehicle environments.
7. The vehicle bus signal filtering method according to claim 6, characterized in that: The historical filter coefficients may also be obtained by adjusting interference signals of different vehicle environments to test the vehicle bus signal, specifically including: Acquire a preset bus signal of the vehicle, a preset bus signal processed by the previous iterative filtering, and a real bus signal interfered by an interference signal; Based on the filtering algorithm, the historical filtering coefficient is obtained.
8. A vehicle bus signal filtering system, characterized in that: A method for filtering a vehicle bus signal according to any one of claims 1 to 7, the system comprising: A filtering algorithm building module is used to obtain historical input data of historical vehicle bus signals, corresponding filtering data of the previous historical output, and corresponding filtering data of the current historical output, build a filtering algorithm, and obtain corresponding historical filtering coefficients; A model building module, used for calculating the historical difference between the historical input data and the corresponding filtering data outputted in the past, and building a filtering coefficient model based on the historical difference and the historical filtering coefficient; A filter parameter updating module, used for performing n iterative filtering processes on the vehicle bus signal, wherein the filter parameters used in each iterative filtering process are updated based on the filter coefficient model output according to the difference between the input data of the current vehicle bus signal and the output data obtained after the previous iterative filtering process; The filter data processing module is used to input the filter algorithm according to the filter parameters and output the current filter data of the current vehicle bus signal.
9. A readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.
10. An electronic device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 7 when executing the program.