Fault analysis method, system and device and electronic equipment

Abstract

The invention discloses a fault analysis method, system and device and electronic equipment, relates to the technical field of vehicles, and aims to solve the problems of relatively low analysis and processing efficiency and relatively long time consumption of a vehicle failure problem in the prior art. The method comprises the steps of obtaining message data related to a target fault in response to a condition that a user indicates that the vehicle has the target fault; determining a fault analysis time period based on the occurrence time of the feature operation corresponding to the target fault; wherein the characteristic operation is operation capable of enabling the signal to generate observable change; analyzing the message data in the fault analysis time period, and determining an abnormal signal; and determining a problem source causing the target fault based on the abnormal signal.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, specifically to a fault analysis method, system, device, and electronic equipment. Background Art

[0002] With the popularization of electric vehicles, maintenance issues are becoming increasingly prominent, especially with the high threshold for high-voltage operation, highly integrated systems and diversified functions. The diagnostic trouble codes (DTCs) and data streams of diagnostic instruments have a limited range of faults, and many functional failures or unexpected response problems rely on collected message analysis. However, the message analysis protocol is a core commercial secret and is only mastered by the OEM. The processing cycle is long, making it difficult to resolve market problems in a timely manner.

[0003] In related technologies, the power data of electric vehicles is obtained and input into a pre-trained fault diagnosis model to output fault diagnosis results. In another related technology, the original message of the electrical node is obtained from the vehicle diagnostic interface through the Controller Area Network (CAN) bus and stored in a database, and then the message is parsed in batches to obtain the parsing results of each record. It can be seen that when using the fault diagnosis model for fault diagnosis, the faults that the model can identify are relatively simple. When it comes to complex vehicle failure scenarios, multiple models may need to be involved, which is costly and inefficient. In the solution of directly parsing the original message, the amount of messages that need to be parsed is large, resulting in low parsing efficiency and long time consumption.

[0004] In summary, the analysis and processing efficiency of vehicle failure problems in related technologies is low and time-consuming. Summary of the Invention

[0005] The purpose of the embodiments of the present application is to provide a fault analysis method, system, device and electronic equipment, aiming to solve the problem of low efficiency and long time consumption in the analysis and processing of vehicle failure problems in related technologies.

[0006] In order to achieve the above objectives, the technical solutions adopted in the embodiments of the present application are as follows:

[0007] In a first aspect, an embodiment of the present application provides a fault analysis method, which includes: in response to a user indicating that a target fault occurs in a vehicle, obtaining message data related to the target fault; determining a fault analysis time period based on the occurrence time of a characteristic operation corresponding to the target fault; wherein the above-mentioned characteristic operation is an operation that can cause an observable change in the signal; analyzing the message data within the above-mentioned fault analysis time period to determine an abnormal signal; and determining the source of the problem that caused the above-mentioned target fault based on the abnormal signal.

[0008] It is understood that the present application provides a fault analysis method that can obtain the message data related to the failure function when the user specifies the target fault of the vehicle. These message data include all signals generated during the target fault process. Further, based on the occurrence time of the characteristic operation corresponding to the target fault, the fault analysis time period is determined. Here, the characteristic operation refers to the operation that can cause the signal to undergo observable changes. In this way, the fault analysis time period determined by the characteristic operation can cover the complete signal input and output process, thereby accurately locking the time window that may contain the cause of the fault, significantly improving the speed of fault analysis. By analyzing the message data within the fault time period, the signals related to the target fault can be screened out. According to the rationality of the screened target signal, the abnormal signal (such as the rationality of the value and the rationality of the response time) is determined. Based on the identified abnormal signal, the system further traces the root cause of the signal abnormality, thereby locating the specific fault point that caused the target fault. The change type of the abnormal signal can reflect the actual operating status and trend of the vehicle function, so that the fault cause and failure point can be more accurately located according to the changing trend of the actual operating status, improving the efficiency and accuracy of fault analysis. In summary, the technical solution provided in this application can improve the problem of low efficiency and long time consumption in analyzing and processing vehicle failure problems.

[0009] As a possible implementation method, the fault analysis time period is determined based on the occurrence time of the characteristic operation corresponding to the target fault, including: determining the above-mentioned fault analysis time period based on a first time period before the occurrence time of the characteristic operation, and / or a second time period after the occurrence time of the characteristic operation.

[0010] The above technical approach accurately determines the time window for fault analysis based on the occurrence time of the characteristic operation corresponding to the target fault, combined with a first time period before and / or a second time period after the characteristic operation. This approach not only covers the entire input and output process, ensuring that critical information is not missed during analysis, but also significantly narrows the scope of fault analysis and improves analysis efficiency.

[0011] As a possible implementation method, before analyzing the message data within the above-mentioned fault analysis time period, the above-mentioned method also includes: based on the fault analysis time period, time synchronization processing is performed on the message data involved in the target fault to obtain the message data within the fault analysis time period; the above-mentioned time synchronization processing is used to align the value of the message data at each moment in the fault analysis time period.

[0012] According to the above technical means, by performing time synchronization processing on the message data involved in the target fault based on the fault analysis time period, the values ​​of the message data at each moment in the fault analysis time period can be effectively aligned, avoiding analysis errors caused by asynchronous signal transmission time, thereby improving the accuracy and efficiency of fault analysis.

[0013] As a possible implementation method, the data update cycles of different signals in the above-mentioned message data are different; based on the above-mentioned fault analysis time period, the message data involved in the target fault is time-synchronized to obtain the message data within the above-mentioned fault analysis time period, including: for the target moment in the fault analysis time period, when the target moment meets the data update cycle of the target signal, the value of the target signal is updated so that the value of the target signal at the above-mentioned target moment is the updated value; when the target moment does not meet the data update cycle of the above-mentioned target signal, the value of the target signal is not updated so that the value of the target signal at the above-mentioned target moment is the value of the previous cycle; wherein the above-mentioned target moment is any moment in the fault analysis time period; the above-mentioned target signal is any signal in the message data.

[0014] Using these technical measures, the data update cycles of different signals within the message data are synchronized, ensuring the consistency of signal values ​​within the fault analysis period. When the signal update cycle is met at the target time, the signal value is updated to the actual value of the current cycle; if the update cycle is not reached at the target time, the signal value remains at the value of the previous cycle. This processing method avoids misjudgments caused by asynchronous signal cycles or differences in data update frequency, ensuring the accuracy of data analysis. It also provides reliable basic data support for subsequent analysis, significantly improving the accuracy and efficiency of fault diagnosis.

[0015] As a possible implementation method, the above method is applied to a fault analysis system; analyzing the message data within the fault analysis time period to determine the abnormal signal, including: calling a communication protocol, analyzing the message data within the fault analysis time period, and determining the abnormal signal; wherein the communication protocol is configured in the fault analysis system.

[0016] Using these technical measures, by invoking the communication protocol configured within the fault analysis system, the system can automatically parse message data and filter out signals related to the target fault, reducing manual intervention and reliance on core commercial secrets. Furthermore, by analyzing message data within the fault analysis timeframe, it can accurately locate abnormal signals, significantly improving the efficiency and accuracy of fault diagnosis.

[0017] As a possible implementation method, analyzing the message data within the above-mentioned fault analysis time period to determine abnormal signals includes: analyzing the message data within the fault analysis time period according to the system simulation model involved in the target fault to determine abnormal signals.

[0018] By analyzing the message data within the fault analysis period and combining it with the system simulation model corresponding to the target fault, the aforementioned technical approach can accurately locate abnormal signals, significantly improving the efficiency and accuracy of fault diagnosis. This approach utilizes the system simulation model to verify the input-output relationship and logic of the signal, ensuring more reliable analysis results while reducing manual intervention and technical barriers, thereby enhancing the automation level of fault diagnosis.

[0019] On the second aspect, the present application provides a fault analysis system, comprising: an interaction layer and a processing layer, wherein the processing layer and the interaction layer are communicatively connected; the interaction layer is used to receive a user's failure instruction and message data input by the user; wherein the above-mentioned failure instruction is used to indicate that a target fault has occurred in the vehicle; the processing layer is used to obtain message data related to the above-mentioned target fault in response to the failure instruction; based on the occurrence time of the characteristic operation corresponding to the target fault, the fault analysis time period is determined; wherein the above-mentioned characteristic operation is an operation that can cause observable changes in the signal; the message data within the above-mentioned fault analysis time period is analyzed to determine the abnormal signal; based on the above-mentioned abnormal signal, the root cause of the problem causing the above-mentioned target fault is determined.

[0020] As a possible implementation method, the above-mentioned fault analysis system also includes: a protocol layer and a solution layer; wherein the above-mentioned processing layer is respectively communicated with the above-mentioned protocol layer and the above-mentioned solution layer; the above-mentioned protocol layer is configured with at least one communication protocol for message parsing; the above-mentioned solution layer is configured with at least one fault analysis solution for analyzing message data and identifying abnormal signals in the message data.

[0021] As another possible implementation, the method further includes: the processing layer is specifically configured to call the protocol layer and the solution layer to analyze the message data within the fault analysis time period and determine abnormal signals.

[0022] As another possible implementation, the method further includes: a processing layer, specifically used to determine a fault analysis time period based on a first time period before the occurrence time of the characteristic operation, and / or a second time period after the occurrence time of the characteristic operation.

[0023] On the third aspect, the present application provides a fault analysis device, which includes a communication module and an analysis module; the communication module is used to obtain message data related to the target fault in response to a user's indication that a target fault occurs in the vehicle; the analysis module is used to determine the fault analysis time period based on the occurrence time of the characteristic operation corresponding to the target fault; wherein the above-mentioned characteristic operation is an operation that can cause observable changes in the signal; the message data within the above-mentioned fault analysis time period is analyzed to determine the abnormal signal; based on the above-mentioned abnormal signal, the problem source causing the target fault is determined.

[0024] As a possible implementation manner, the analysis module is specifically configured to determine the fault analysis time period based on a first time period before the occurrence time of the characteristic operation and / or a second time period after the occurrence time of the characteristic operation.

[0025] As another possible implementation method, the analysis module is also used to perform time synchronization processing on the message data involved in the target fault based on the fault analysis time period to obtain the message data within the fault analysis time period; the above-mentioned time synchronization processing is used to align the values ​​of the message data at each moment in the fault analysis time period.

[0026] As another possible implementation method, the data update cycles of different signals in the above-mentioned message data are different; the analysis module is specifically used to perform time synchronization processing on the message data involved in the above-mentioned target fault based on the different data update cycles of different signals in the message data; based on the fault analysis time period, obtain the message data in the above-mentioned fault analysis time period, for the target moment in the above-mentioned fault analysis time period, when the data update cycle of the target signal is met at the target moment, update the value of the target signal so that the value of the above-mentioned target signal at the target moment is the updated value; when the data update cycle of the target signal is not met at the above-mentioned target moment, do not update the value of the above-mentioned target signal so that the value of the above-mentioned target signal at the target moment is the value of the previous cycle; wherein the above-mentioned target moment is any moment in the fault analysis time period; the above-mentioned target signal is any signal in the message data.

[0027] As another possible implementation, an analysis module is specifically used to apply the above method to a fault analysis system; analyzing the message data within the fault analysis time period to determine the abnormal signal, including: calling a communication protocol, analyzing the message data within the fault analysis time period, and determining the abnormal signal; wherein the above communication protocol is configured in the fault analysis system.

[0028] As another possible implementation method, the analysis module is specifically used to analyze the message data within the above-mentioned fault analysis time period and determine the abnormal signal, including: analyzing the message data within the above-mentioned fault analysis time period according to the system simulation model involved in the target fault and determining the abnormal signal.

[0029] In a fourth aspect, the present application provides an electronic device comprising: a processor and a memory; wherein the memory is used to store instructions executable by the processor; and the processor is configured to execute instructions to implement any one of the fault analysis methods provided in the first aspect above.

[0030] In a fifth aspect, the present application provides a computer-readable storage medium, comprising: software instructions; when the software instructions are executed in an electronic device, the electronic device implements the fault analysis method provided in the first aspect and any possible implementation thereof.

[0031] In a sixth aspect, the present application provides a computer program product, comprising: computer instructions, which, when executed on a computer device, enable the computer device to execute the fault analysis method provided in the first aspect and any possible implementation thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application, and do not constitute an improper limitation on the present application.

[0033] Figure 1 is a block diagram of a fault analysis system according to an exemplary embodiment;

[0034] Figure 2 is a flow chart showing a fault analysis method according to an exemplary embodiment;

[0035] Figure 3 is a flow chart showing another fault analysis method according to an exemplary embodiment;

[0036] Figure 4 is a flow chart showing another fault analysis method according to an exemplary embodiment;

[0037] Figure 5 is a flow chart showing another fault analysis method according to an exemplary embodiment;

[0038] Figure 6 is a block diagram of a fault analysis device according to an exemplary embodiment;

[0039] Figure 7 The figure is a schematic structural diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0041] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of such features. Throughout this application, unless otherwise specified, "plurality" means two or more.

[0042] In the description of this application, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," "connected," and "connected" should be understood broadly. For example, they may refer to fixed connections, detachable connections, or integral connections. They may be directly connected, indirectly connected through an intermediary, or internally connected between two components. Those skilled in the art will understand the specific meanings of these terms in this application based on the specific circumstances.

[0043] In the embodiments of the present application, the terms "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, article, or device comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of other identical elements in the process, article, or device comprising the element.

[0044] In the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be interpreted as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0045] In the description of this specification, specific features, structures, materials or characteristics may be combined in an appropriate manner in any one or more embodiments or examples.

[0046] The specific implementation of the embodiment of the present application is described in detail below with reference to the accompanying drawings.

[0047] Figure 1FIG. 1 is a block diagram of a fault analysis system according to an exemplary embodiment. Figure 1 As shown, the fault analysis system 100 includes: an interaction layer 101, a processing layer 102, a protocol layer 103 and a solution layer 104, wherein the processing layer 102 is communicatively connected to the interaction layer 101, and the processing layer 102 is communicatively connected to the protocol layer 103 and the solution layer 104 respectively.

[0048] For example, the deployment form of the interaction layer 101 can be any of the following: a desktop World Wide Web (web) application, a mobile H5 page, a tablet-adapted client, or a micro-application integrated into an enterprise, etc. The embodiment of the present application does not impose any special restrictions on the specific deployment form of the interaction layer 101.

[0049] In some embodiments, the above-mentioned interaction layer 101 is used to display a user interface, receive user operations on the above-mentioned user interface, send the user's operation instructions (such as selecting a failure function, uploading an American Standard Code for Information Interchange format message, etc.) to the processing layer 102, and at the same time display the fault analysis results or abnormal signal information returned by the processing layer 102, so as to provide the user with intuitive operation feedback and diagnostic conclusions.

[0050] In some embodiments, the interaction layer 101 is configured to receive a user's failure instruction and message data input by the user, wherein the failure instruction is used to indicate that a target fault has occurred in the vehicle.

[0051] For example, the processing layer 102 may be a data processing module implemented based on a high-computing chip or a cloud computing platform, supporting parsing, analysis, and logical judgment of message data. The present embodiment of the application does not impose any particular restrictions on the specific implementation of the processing layer 102.

[0052] In some embodiments, the processing layer 102 is used to receive operation instructions transmitted by the interaction layer 101, call the communication protocol parsing rules provided by the protocol layer 103, and the fault analysis scheme and system simulation model maintained in the scheme layer 104, perform time synchronization processing, feature operation estimation, frame-by-frame analysis and fault result estimation on the message data of the target fault, and feed back the analysis results to the interaction layer 101.

[0053] In some embodiments, the processing layer 102 is used to obtain message data related to the target fault in response to the failure instruction; determine the fault analysis time period based on the occurrence time of the characteristic operation corresponding to the target fault; wherein the above-mentioned characteristic operation is an operation that can cause observable changes in the signal; analyze the message data within the above-mentioned fault analysis time period to determine the abnormal signal; and determine the root cause of the problem that caused the target fault based on the above-mentioned abnormal signal.

[0054] For example, the protocol layer 103 may be a signal parsing module implemented based on a controller area network (DBC) file, a CAN communication protocol, or other custom protocols, for maintaining the communication protocol. The embodiment of the present application does not impose any particular restrictions on the specific implementation of the protocol layer 103.

[0055] In some embodiments, the protocol layer 103 is used to maintain the communication protocol and provide message parsing rules and signal screening support according to the requirements of the processing layer 102 to ensure that the message data can be correctly parsed into readable signals.

[0056] In some embodiments, the protocol layer 103 is configured with at least one communication protocol for performing message parsing.

[0057] Exemplarily, the solution layer 104 may be a storage and invocation module for fault analysis solutions implemented based on flowchart modeling, a rule engine, or scripted logic, and used to maintain input and output values, judgment conditions, and execution order. The embodiments of this application do not impose any particular limitations on the specific implementation of the solution layer 104.

[0058] In some embodiments, the solution layer 104 is used to store and manage fault analysis solutions and system simulation models, maintain input and output values ​​and judgment conditions in a fixed format, and provide the processing layer 102 with the ability to call to achieve fault scenario prediction and fault result estimation.

[0059] In some embodiments, the solution layer 104 is configured with at least one fault analysis solution for analyzing message data and identifying abnormal signals in the message data.

[0060] Exemplarily, the processing layer 102 is specifically configured to call the protocol layer 103 and the solution layer 104 to analyze the message data within the above-mentioned fault analysis time period and determine abnormal signals.

[0061] It should be noted that the system architecture described in the embodiments of the present application is intended to more clearly illustrate the technical solutions of the embodiments of the present application, and does not constitute a limitation on the technical solutions provided in the embodiments of the present application. A person skilled in the art will know that with the evolution of the system architecture, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0062] The fault analysis method provided in the embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0063] like Figure 2 As shown, the fault analysis method provided in the embodiment of the present application may include the following steps:

[0064] S201 : In response to a user indicating that a target fault occurs in a vehicle, obtain message data related to the target fault.

[0065] The target fault can be any of the following: a functional failure fault, a fault in which the vehicle does not perform as expected by the driver.

[0066] Functional failure refers to a failure during vehicle operation where one or more components or systems malfunction or fail, preventing the vehicle from functioning properly. Examples of functional failures include engine starting failure, brake system failure, steering system failure, lighting system failure, and air conditioning system failure.

[0067] A failure in which the vehicle fails to perform as intended by the driver occurs when the vehicle's actual response deviates from the driver's intended operation, resulting in the vehicle being unable to operate normally as intended. For example, the driver performs a specific operation (such as pressing the accelerator or turning the steering wheel), but the vehicle's actual response is inconsistent with the driver's expectations (such as slow acceleration or understeer). Examples of failures in which the vehicle fails to perform as intended by the driver include delayed acceleration response, weak or ineffective braking, steering system failure, and confusing shifting logic.

[0068] In some embodiments, the above-mentioned step S201 can be implemented as follows: based on the identification of the target fault indicated by the user and the preset correspondence, the message data related to the target fault is obtained from the message data input by the user; wherein the above-mentioned preset correspondence is used to indicate the correspondence between the vehicle fault identification and the identification (Identity, ID) of the message data related to the vehicle fault.

[0069] Exemplarily, the user inputs the vehicle's message data through the interaction layer and indicates that the vehicle has a target fault. Furthermore, the interaction layer sends the message data input by the user and the identifier of the target fault to the processing layer. Then, the processing layer determines the ID of the message data involved in the target fault based on the identifier of the target fault and a preset correspondence, and then obtains the message data involved in the target fault from the vehicle's message data according to the ID of the message data involved in the target fault.

[0070] S202: Determine a fault analysis time period based on the occurrence time of the characteristic operation corresponding to the target fault.

[0071] The above-mentioned characteristic operation is an operation that can cause observable changes in the signal.

[0072] For example, the characteristic operation may be a triggering operation for a vehicle function, such as an engine start triggering operation, a lighting system turning on triggering operation, an air conditioning system turning on triggering operation, etc. The characteristic operation may be a driver's control operation of the vehicle, such as stepping on the accelerator, stepping on the brake, turning the steering wheel, shifting gears, etc.

[0073] In some embodiments, the method further includes: determining a characteristic operation corresponding to the target fault based on the target fault and a characteristic operation library, wherein the characteristic operation library is used to indicate the characteristic operation corresponding to each vehicle fault.

[0074] In some embodiments, the above step S202 can be implemented as: determining the fault analysis time period based on a first time period before the occurrence time of the above characteristic operation and / or a second time period after the occurrence time of the above characteristic operation.

[0075] For example, the lengths of the first and second time periods can be flexibly adjusted based on the specific characteristics of the target fault and the requirements of the fault scenario. For example, for functional failures, the data from 10 seconds before (first time period) and 10 seconds after (second time period) the characteristic operation occurs can be used as the fault analysis time period to cover the complete causal chain. For faults where the vehicle does not perform as the driver expected, the time period range can be dynamically adjusted based on the time point when the characteristic operation signal is triggered to ensure that all key signal changes related to the fault are captured.

[0076] S203: Analyze the message data within the fault analysis time period to determine abnormal signals.

[0077] As a possible implementation method, the above method is applied to a fault analysis system (for example, a processing layer in a fault analysis system), and the above step S203 can be implemented as follows: calling the communication protocol, analyzing the message data within the fault analysis time period, and filtering out abnormal signals based on the analysis results combined with the input-output relationship, logical conditions and execution order defined in the fault analysis plan.

[0078] The communication protocol is configured in the fault analysis system, for example, in the protocol layer of the fault analysis system.

[0079] The above-mentioned fault analysis solution is configured in the above-mentioned fault analysis system, for example, the solution layer in the fault analysis system.

[0080] As another possible implementation, the above step S203 may be implemented as follows: analyzing the message data within the fault analysis time period according to the system simulation model involved in the above target fault, and determining an abnormal signal.

[0081] The system simulation model is a mathematical model or simulation model of the vehicle's system functions. The above model can be developed and implemented using tools such as MATLAB / Simulink.

[0082] Exemplarily, the above-mentioned analysis of message data within the fault analysis time period using the system simulation model involved in the target fault can be implemented as follows: based on the time when the characteristic operation corresponding to the target fault occurs, the fault analysis time period is determined, and the relevant message data within this time period is extracted. Based on the system simulation model involved in the target fault (such as a MATLAB / Simulink model), the message data is parsed into readable signals, and signals related to the model input and output are screened. Utilizing the logical relationships, calibration quantities, and error thresholds defined in the model, the deviation between the requested signal and the actual signal is compared frame by frame to determine whether the signal deviation is within a reasonable range and identify abnormal signals.

[0083] The request signal is a user-desired signal value (e.g., a user-set signal value). For example, for an air conditioning cooling function, the request signal may be the temperature value set by the user on the air conditioning control panel. Alternatively, the request signal may be a signal value calculated based on a system simulation model associated with the target fault.

[0084] The actual signal is the actual signal value collected during vehicle operation. For example, for the air conditioning cooling function, the actual signal is the actual air temperature blown out by the air conditioning system.

[0085] In some embodiments, by invoking the communication protocol in the protocol layer, the message data is parsed frame by frame, converting the original message into a readable signal value. The signal rationality is further analyzed based on the fault analysis plan or system simulation model involved in the target fault. If a signal value is found to be outside the normal range, does not respond as expected, or the error exceeds the threshold allowed by the model, it is marked as an abnormal signal. For calibration-related faults, the system also comprehensively considers other factors marked in the model that may affect the signal to avoid misjudgment.

[0086] S204: Based on the abnormal signal, determine the source of the problem causing the target failure.

[0087] In some embodiments, the above step S204 may be implemented as follows: the system analyzes the abnormal signal according to the characteristics of the abnormal signal and in combination with a fault analysis solution or simulation model corresponding to the target fault.

[0088] Exemplarily, the system calls the fault analysis plan or simulation model related to the target fault based on the changing characteristics of the abnormal signal during the fault analysis time period, and confirms the source of the target fault by tracing back to the source. For example, for process-related faults, the system traces the root cause of the abnormal signal according to the input and output, judgment conditions and execution sequence declared in the fault analysis plan; for calibration-related faults, the system analyzes the difference between the request signal and the actual signal by comparing the XY axis values ​​of the system simulation model (the X axis represents time, and the Y axis represents the actual output signal), and further locates the source of the problem by combining the possible influencing factors marked in the model. At the same time, the system will make rationality judgments on fault-related signals (such as the rationality of the value and the rationality of the response time), and trace the abnormal signal upwards, and finally output the source of the problem that caused the target fault.

[0089] In summary, it can be seen that the solution provided by the embodiment of the present application can automatically parse the message according to the scheme and protocol corresponding to the target message when receiving the target message uploaded by the user, and generate fault analysis data. In this way, according to the fault analysis scheme and communication protocol maintained in advance, the message can be quickly parsed and the problem can be located, which improves the efficiency of fault analysis. Different types of failure problems correspond to different fault analysis schemes and protocols, which enhances the flexibility of fault analysis. Further, in the process of analyzing the message frame by frame based on the estimated fault time period, the system can perform a variety of analysis operations, wherein the operation type of fault analysis can be flexibly adjusted according to demand, such as process fault analysis, calibration fault analysis, etc. Different analysis operations correspond to different service interfaces. When the system receives the analysis request from the user, it can call the corresponding service interface to perform specific operations. In this way, it can be seen that the analysis logic and judgment conditions corresponding to different failure problems in the present application may be different. There are more selectivities and richer operations that can be executed at different analysis stages, which effectively improves the flexibility of fault analysis. In summary, based on the technical solution provided by the present application, the flexibility and processing efficiency of fault analysis can be improved.

[0090] In some embodiments, before step S203, the method further includes:

[0091] S301 : Based on the fault analysis time period, perform time synchronization processing on the message data involved in the target fault to obtain the message data within the fault analysis time period.

[0092] The time synchronization process is used to align the values ​​of the message data at each moment in the fault analysis time period.

[0093] In some embodiments, the above step S301 can be implemented as follows: for the target moment in the above fault analysis time period, when the data update cycle of the target signal is met at the target moment, the value of the target signal is updated so that the value of the above target signal at the target moment is the updated value; when the data update cycle of the above target signal is not met at the above target moment, the value of the target signal is not updated, so that the value of the above target signal at the target moment is the value of the previous cycle.

[0094] The target moment is any moment in the fault analysis time period; the target signal is any signal in the message data.

[0095] It is understandable that time synchronization processing can ensure the consistency of static values ​​in data processing. The specific method is to use the cycle time of the shortest period signal as a reference. For signals with longer cycles or asynchronous signals, the value at the reference time point is the value of the previous cycle. For example, in the time analysis of Table 1, the battery management system (BMS) signal cycle is 10ms, which is used as the reference time; at A+10ms, the BMS signal is updated to 10, while the vehicle control unit (VCU) and motor control unit (MCU) signals still maintain the value of the previous cycle because their update cycle has not yet arrived.

[0096] Table 1: Time analysis

[0097]

[0098] It is understandable that after time synchronization, the processing layer will filter out the message corresponding to the target fault indicated by the user according to the message ID, and parse the message into a signal according to the communication protocol maintained by the protocol layer.

[0099] In some embodiments, before the above step S203, the above method further includes: maintaining the scheme and protocol in a fixed format in the development system.

[0100] For example, the above method can be implemented by maintaining the signals and conditions for changing states corresponding to a vehicle fault analysis solution in a standardized format, with input and output values ​​and judgment conditions clearly defined to facilitate interface calls and automatic code generation. After maintenance, the system automatically analyzes each frame within the estimated fault time period using the solution's logic and outputs any unreasonable signals (i.e., abnormal signals).

[0101] For example, the fixed format can be in the form of a flow chart. For example, when maintaining the solution, Figure 3The fault analysis method shown in FIG. 1 includes constructing a flowchart similar to system simulation modeling. Specifically, the flowchart can be represented as follows: When condition 1 is met, system initialization begins. After system initialization, if condition 2 is met, system inspection begins. After system initialization, if condition 3 is met, the system enters the subsequent operation state. After the system inspection, if condition 5 is met, the system enters the subsequent operation state. When the subsequent operation state meets condition 4, the system returns to system initialization.

[0102] It can be understood that the above conditions 1, 2, 3, 4, and 5 are intended to more clearly illustrate the technical solutions of the embodiments of the present application, and do not constitute a limitation on the technical conditions provided by the embodiments of the present application. A person skilled in the art can know that the technical conditions provided by the embodiments of the present application are different depending on the type of fault, so no specific limitation is made to the above conditions.

[0103] In some embodiments, the above step S202 may be implemented as follows: determining the type of characteristic operation according to the type of the target fault, and then determining the fault analysis time period according to the occurrence time of the characteristic operation corresponding to the target fault.

[0104] Exemplarily, if the target fault type is a functional failure fault, the operation that causes the state of the failure function to change (for example, the operation that causes the input of the usage scenario signal of the failure function to change) is classified as the first type of characteristic operation. In the case where the characteristic operation is the first type of characteristic operation, the first time period before the occurrence time of the characteristic operation and the second time period after the occurrence time of the characteristic operation are determined as the fault analysis time period. Exemplarily, with the occurrence time of the first type of characteristic operation as the time center, the data before and after 10S (time adjustable) is obtained for frame-by-frame analysis.

[0105] For example, if no characteristic operation is detected throughout the entire process, the system will report that no corresponding characteristic signal input is present. For example, if an air conditioner is turned on and an air conditioning panel (ACP) request is received, this time is used as the fault analysis node. If no such request is received throughout the entire process, the system will report that no ACP request is received, thus guiding maintenance personnel to check the input signal.

[0106] For example, if the target fault type is a vehicle failure that failed to perform as expected by the driver, the driver's operation is classified as a second-category characteristic operation. If the characteristic operation is a second-category characteristic operation, the second time period following the occurrence of the characteristic operation is determined as the fault analysis time period. For example, starting with the occurrence of the second-category characteristic operation, the processing layer analyzes the data frame by frame according to the scheme / model, dynamically adjusting the time period to ensure that all key signal changes related to the fault are captured.

[0107] For example, when the vehicle has no acceleration capability, the data during the period when the accelerator pedal signal is valid should be automatically analyzed.

[0108] It is understandable that the accuracy and efficiency of fault analysis are significantly improved by classifying fault scenarios into different characteristic operation types and then determining the fault analysis time period based on different types of characteristic operations. For functional failure faults, by identifying the signal input changes (characteristic operations) that are bound to occur in specific function usage scenarios, the moment of occurrence of the characteristic operation is taken as the center, and frame-by-frame analysis is extended 10 seconds before and after (adjustable) to ensure coverage of the complete cause-effect chain. If no characteristic operation is detected throughout the process, the feedback will be that there is no relevant characteristic signal input, guiding maintenance personnel to quickly locate the source of the problem. For faults in which the vehicle does not perform as the driver expects, the driver's operation is used as the characteristic operation. When the characteristic operation signal is triggered, the system analyzes the data frame by frame based on the fault analysis plan or model to quickly locate the abnormal signal or root cause. This method reduces the reliance on core commercial secrets and significantly shortens the fault handling cycle.

[0109] In some embodiments, the method provided in the present application further includes: estimating the fault results, and dividing the fault results into process-related faults and calibration-related faults.

[0110] For example, process-based failures involve following the inputs and outputs, judgment conditions, and execution sequence specified in the fault analysis plan. The system then determines the rationality of signals within the timeline (value rationality and response time rationality) and outputs abnormalities and generates fault estimates for any unreasonable signals. For example, during a power-on failure, the key unlock feature is triggered, but the corresponding signal value is abnormal, causing the BMS to operate abnormally and output an abnormal signal.

[0111] For example, calibration faults are detected by comparing the difference between the requested signal and the actual signal based on the XY axis values ​​of the system simulation MATLAB model to see if the error is within the threshold range allowed by the model, taking into account other signals marked in the model that may affect the Y value. For example, when the vehicle is shaking, the torque tracking model should be called to check the consistency of the pedal and torque. If there is an abnormality, the cause of the abnormality can be output, such as: Microcontroller Unit_Insulated Gate Bipolar Transistor (MCU_IGBT) overtemperature. However, normal signals such as the Anti-lock Braking System (ABS) also need to be monitored. No error processing is performed, only a prompt is given.

[0112] It is understandable that the efficiency and accuracy of fault diagnosis have been significantly improved through the dual analysis of process-related faults and calibration-related faults. For process-related faults, the system analyzes the rationality of the signal frame by frame according to the input and output, judgment conditions and execution order declared in the fault analysis plan, quickly locates abnormal signals and outputs fault estimates, thereby effectively reducing the workload of manual troubleshooting. For calibration-related faults, the system compares the difference between the request signal and the actual signal based on the XY axis values ​​of the system simulation MATLAB model, and combines the error range allowed by the model and other signals that may affect the Y value to accurately determine the cause of the fault and prompt the abnormality to avoid false alarms. In addition, through frame-by-frame analysis triggered by characteristic operation signals, the system can flexibly respond to different types of fault scenarios, enhance the applicability and flexibility of fault diagnosis, and reduce dependence on core commercial secrets, providing a convenient and efficient solution for after-sales technical support and repair stations.

[0113] In some embodiments, the method provided by the present application also includes: according to the schemes and protocols maintained in the system by the above method, an encrypted calling interface is set for calling. It can be understood that the present application produces a software that can automatically analyze the message frame by frame. The logic of the data processing inside the software is that the horizontal axis is time, and the vertical axis is the signal screened out in the scheme selected by the customer, and the signal is analyzed frame by frame, and abnormal values ​​or feedback results are output. For the user's after-sales technical support and maintenance station, there is no need to master the core commercial secrets such as fault analysis schemes, models and protocols. In the packaged software, the customer enters the name of the failed scheme (such as the air conditioner does not cool), collects and uploads ASC format messages to the software, and automatically outputs the failure problem points of the fault analysis scheme based on high-computing power chips or cloud computing.

[0114] It is understandable that by maintaining standardized schemes and protocols within the system and setting up encrypted calling interfaces, a software that can automatically analyze messages frame by frame was created. The data processing logic within the software is based on the timeline and filtered signals, and can accurately output abnormal values ​​or fault feedback results. For after-sales technical support and repair stations, there is no need to master core commercial secrets (such as fault analysis schemes, models, and protocols). You only need to enter the failure scheme name through the packaged software and upload the message, and you can use high-computing power chips or cloud computing to quickly locate the problem point. This method improves the efficiency of fault analysis, lowers the technical threshold, and at the same time ensures the security of core commercial secrets.

[0115] For ease of understanding, the fault analysis method provided in the embodiments of the present application is described below in combination with different application scenarios.

[0116] Scenario 1: Functional failure scenario prediction and fault estimation.

[0117] For example, Figure 4As shown, the above-mentioned functional failure scenario prediction and fault estimation may include the following steps:

[0118] Sa1. Receive an operation instruction from a user indicating that the vehicle has an air conditioning failure.

[0119] Sa2. Determine the characteristic operation corresponding to the air conditioner failure.

[0120] For example, a characteristic operation corresponding to the air conditioning failure fault is determined based on the air conditioning failure fault and a characteristic operation library, wherein the characteristic operation library is used to indicate the characteristic operation corresponding to each vehicle fault.

[0121] Exemplarily, the characteristic operation corresponding to the air conditioning failure is an air conditioning (AC) request issued by a user.

[0122] Sa3. Parse the message and check whether there is a time point at which the AC request changes from 0 to 1.

[0123] If yes, execute the following step Sa5; if no, execute the following step Sa4.

[0124] Sa4, output the time point when no AC request changes from 0 to 1, guiding the user to find the input signal to confirm whether an AC request is issued.

[0125] Sa5. Determine the fault analysis period based on the time point when the AC request changes from 0 to 1, and automatically analyze the message data within the fault analysis period according to the maintenance plan to determine the abnormal signal.

[0126] Sa6, output abnormal signal.

[0127] Scenario 2: The vehicle fails to perform the fault scenario prediction and fault estimation as expected.

[0128] For example, Figure 5 As shown, the above-mentioned vehicle failure to perform fault scenario prediction and fault estimation as expected can be implemented as follows:

[0129] Sc1. Receive an operation instruction from a user indicating that the vehicle has an acceleration failure.

[0130] Sc2. Determine that the system simulation model corresponding to the vehicle acceleration failure is a torque following model.

[0131] Sc3. Analyze the message to determine whether there is an abnormal signal that limits the torque.

[0132] If yes, execute the following step Sc4; if no, execute the following step Sc5.

[0133] Sc4. Output abnormal signal.

[0134] Sc5. Analyze the message based on the torque following model.

[0135] Sc6. Determine whether the abnormal data stream includes a data stream corresponding to a normal torque limiting operation (eg, an Advanced Emergency Braking System (AEBS)).

[0136] If yes, execute the following step Sc7; if no, execute the following step Sc8.

[0137] Sc7. Determine that the source of the problem is torque limitation caused by normal user operation, output the conclusion, and confirm that there are no abnormal signals.

[0138] Sc8. Output abnormal data stream.

[0139] In summary, the present invention proposes a fault analysis method, system, device and electronic equipment, which can accurately locate the root cause of vehicle functional failure through automatic message parsing and intelligent fault analysis technology. In complex fault scenarios, for functional failure and non-expected execution problems, the system can flexibly extract key signals through time window analysis of feature operations, and judge the rationality of the signal frame by frame in combination with the fault analysis solution and the system simulation model, focusing on outputting abnormal signals and their possible causes. Through time synchronization processing and standardized protocol calls, the accuracy of data causality is ensured, and real-time analysis and result feedback are achieved with the help of high-computing power chips or cloud computing. Through encapsulated software and encrypted interface design, the technical threshold of after-sales technical support is lowered, and the security of core commercial secrets is guaranteed, providing strong support for rapid response and efficient resolution of market problems, and significantly improving fault handling efficiency and reliability.

[0140] The above mainly introduces the solution provided by the embodiment of the present application from the perspective of the method. In order to realize the above functions, the fault analysis device or electronic device includes a hardware structure and / or software module corresponding to the execution of each function. It should be easy for those skilled in the art to realize that, in combination with the units and algorithm steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0141] The embodiment of the present application can, according to the above method, exemplarily divide the functional modules of the fault analysis device or electronic device. For example, the fault analysis device or electronic device can include various functional modules corresponding to the various functional divisions, or two or more functions can be integrated into one processing module. The above-mentioned integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiment of the present application is schematic and is only a logical functional division. There may be other division methods in actual implementation.

[0142] Figure 6 FIG. 1 is a block diagram of a fault analysis device according to an exemplary embodiment. Figure 6 As shown, the fault analysis device 600 includes: a communication module 601 and an analysis module 602.

[0143] The communication module 601 is configured to obtain message data related to a target fault in response to a user indicating a target fault of the vehicle.

[0144] Analysis module 602 is used to determine the fault analysis time period based on the occurrence time of the characteristic operation corresponding to the target fault; wherein the above-mentioned characteristic operation is an operation that can cause observable changes in the signal corresponding to the target fault; analyze the message data within the above-mentioned fault analysis time period to determine the abnormal signal; based on the above-mentioned abnormal signal, determine the problem source that caused the target fault.

[0145] As a possible implementation manner, the analysis module 602 is specifically configured to determine the fault analysis time period based on a first time period before the occurrence time of the characteristic operation and / or a second time period after the occurrence time of the characteristic operation.

[0146] As another possible implementation method, the analysis module 602 is also used to perform time synchronization processing on the message data involved in the target fault based on the fault analysis time period to obtain the message data within the fault analysis time period; the above-mentioned time synchronization processing is used to align the values ​​of the message data at each moment in the fault analysis time period.

[0147] As another possible implementation, the data update cycles of different signals in the message data are different; the analysis module 602 is specifically used to perform time synchronization processing on the message data involved in the target fault based on the fault analysis time period, and obtain the message data in the fault analysis time period. For the target moment in the fault analysis time period, when the target moment meets the data update cycle of the target signal, the value of the target signal is updated so that the value of the target signal at the target moment is the updated value; when the target moment does not meet the data update cycle of the target signal, the value of the target signal is not updated so that the value of the target signal at the target moment is the value of the previous cycle; wherein the target moment is any moment in the fault analysis time period; and the target signal is any signal in the message data.

[0148] As another possible implementation, the analysis module 602 is specifically used to apply the above method to a fault analysis system; analyzing the message data within the fault analysis time period to determine the abnormal signal, including: calling a communication protocol, analyzing the message data within the fault analysis time period, and determining the abnormal signal; wherein the above communication protocol is configured in the fault analysis system.

[0149] As another possible implementation method, the analysis module 602 is specifically used to analyze the message data within the above-mentioned fault analysis time period and determine the abnormal signal, including: analyzing the message data within the above-mentioned fault analysis time period according to the system simulation model corresponding to the above-mentioned target fault and determining the abnormal signal.

[0150] In the case of implementing the functions of the above-mentioned integrated modules in the form of hardware, the embodiments of the present disclosure provide a possible structure of the electronic device involved in the above-mentioned embodiments. Figure 7 As shown, the electronic device 700 includes: a processor 702 and a bus 704. Optionally, the electronic device 700 may further include a memory 701; and optionally, the electronic device 700 may further include a communication interface 703.

[0151] The processor 702 may implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the embodiments of the present application. The processor 702 may be a central processing unit, a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array, or other programmable logic device, a transistor logic device, a hardware component, or any combination thereof. It may implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the embodiments of the present disclosure. The processor 702 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a digital signal processor (DSP) and a microprocessor, and the like.

[0152] The communication interface 703 is used to connect to other devices via a communication network, such as Ethernet, wireless access network, wireless local area network (WLAN), etc.

[0153] The memory 701 may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0154] As a possible implementation, the memory 701 can exist independently of the processor 702. The memory 701 can be connected to the processor 702 via a bus 704 and used to store instructions or program codes. When the processor 702 calls and executes the instructions or program codes stored in the memory 701, it can implement the functions involved in the management method of the approval process provided in the embodiment of the present application. In another possible implementation, the memory 701 can also be integrated with the processor 702.

[0155] The bus 704 may be an extended industry standard architecture (EISA) bus, etc. The bus 704 may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 7 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0156] In an exemplary embodiment, the present application also provides a readable storage medium having program instructions stored thereon; when the program instructions are executed by an electronic device, the electronic device implements the method described in the aforementioned embodiment. The readable storage medium can be a non-transitory readable storage medium, for example, a ROM, a random access memory (RAM), a compact disc read-only memory (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, etc.

[0157] In an exemplary embodiment, the embodiment of the present application further provides a computer program product, which, when executed on an electronic device, enables the electronic device to execute the above-mentioned related method steps to implement the functions involved in the management method of the approval process in the above-mentioned embodiment.

[0158] The above are only specific embodiments of the present application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A fault analysis method, characterized in that: The method comprises: In response to a user indicating that a target fault occurs in the vehicle, obtaining message data related to the target fault; Determining a fault analysis time period based on the occurrence time of a characteristic operation corresponding to the target fault; wherein the characteristic operation is an operation that can cause an observable change in the signal; The determining of the fault analysis time period based on the occurrence time of the characteristic operation corresponding to the target fault includes: The fault analysis time period is determined based on a first time period before the occurrence time of the characteristic operation and / or a second time period after the occurrence time of the characteristic operation; wherein, in a case where the type of the target fault is a functional failure type fault, the characteristic operation corresponding to the target fault is a first type characteristic operation, the first type characteristic operation is an operation that causes a change in the state of the failure function, and the first time period before the occurrence time of the first type characteristic operation and the second time period after the occurrence time of the characteristic operation are determined as the fault analysis time period; in a case where the type of the target fault is a fault in which the vehicle does not perform as expected by the driver, the characteristic operation corresponding to the target fault is a second type characteristic operation, the second type characteristic operation is an operation by the driver, and the second time period after the occurrence time of the characteristic operation is determined as the fault analysis time period; Analyze the message data within the fault analysis time period to determine abnormal signals; Based on the abnormal signal, a problem source causing the target fault is determined.

2. The fault analysis method according to claim 1, characterized in that: Before analyzing the message data within the fault analysis time period, the method further includes: Based on the fault analysis time period, time synchronization processing is performed on the message data involved in the target fault to obtain the message data within the fault analysis time period; the time synchronization processing is used to align the value of the message data at each moment in the fault analysis time period.

3. The fault analysis method according to claim 2, characterized in that: Different signals in the message data have different data update periods; performing time synchronization processing on the message data involved in the target fault based on the fault analysis time period to obtain the message data within the fault analysis time period includes: For the target moment in the fault analysis time period, when the target moment meets the data update cycle of the target signal, the value of the target signal is updated so that the value of the target signal at the target moment is the updated value; when the target moment does not meet the data update cycle of the target signal, the value of the target signal is not updated so that the value of the target signal at the target moment is the value of the previous cycle; wherein, the target moment is any moment in the fault analysis time period; and the target signal is any signal in the message data.

4. The fault analysis method according to claim 1, characterized in that: The method is applied to a fault analysis system; Analyzing the message data within the fault analysis time period to determine abnormal signals includes: A communication protocol is called to analyze the message data within the fault analysis time period to determine abnormal signals; wherein the communication protocol is configured in the fault analysis system.

5. The fault analysis method according to claim 1, characterized in that: Analyzing the message data within the fault analysis time period to determine abnormal signals includes: According to the system simulation model involved in the target fault, the message data within the fault analysis time period is analyzed to determine the abnormal signal.

6. A fault analysis system, characterized in that: The system comprises: an interaction layer and a processing layer; wherein the processing layer and the interaction layer are communicatively connected; The interaction layer is used to receive a user's failure instruction and message data input by the user; wherein the failure instruction is used to indicate that a target fault occurs in the vehicle; The processing layer is configured to, in response to the failure instruction, obtain message data related to the target fault; determine a fault analysis time period based on the occurrence time of a characteristic operation corresponding to the target fault; wherein the characteristic operation is an operation that can cause an observable change in a signal; analyze the message data within the fault analysis time period to determine an abnormal signal; and determine a root cause of the problem causing the target fault based on the abnormal signal; The processing layer is specifically used to determine the fault analysis time period based on a first time period before the occurrence time of the characteristic operation and / or a second time period after the occurrence time of the characteristic operation; wherein, when the type of the target fault is a functional failure type fault, the characteristic operation corresponding to the target fault is a first type characteristic operation, and the first type characteristic operation is an operation that causes the state of the failure function to change, and the first time period before the occurrence time of the first type characteristic operation and the second time period after the occurrence time of the characteristic operation are determined as the fault analysis time period; when the type of the target fault is a fault in which the vehicle does not perform as expected by the driver, the characteristic operation corresponding to the target fault is a second type characteristic operation, and the second type characteristic operation is the driver's operation, and the second time period after the occurrence time of the characteristic operation is determined as the fault analysis time period.

7. The fault analysis system according to claim 6, characterized in that: The fault analysis system further comprises: a protocol layer and a solution layer; wherein the processing layer is communicatively connected to the protocol layer and the solution layer respectively; The protocol layer is configured with at least one communication protocol for performing message parsing; At least one fault analysis scheme is configured in the scheme layer, which is used to analyze message data and identify abnormal signals in the message data.

8. The fault analysis system according to claim 7, characterized in that: The processing layer is specifically configured to call the protocol layer and the solution layer to analyze the message data within the fault analysis time period and determine abnormal signals.

9. A fault analysis device, characterized in that: The fault analysis device includes a communication module and an analysis module; The communication module is configured to obtain message data related to a target fault in response to a user indicating that the vehicle has a target fault; The analysis module is configured to determine the fault analysis time period based on the occurrence time of a characteristic operation corresponding to the target fault; wherein the characteristic operation is an operation that can cause an observable change in a signal; analyze the message data within the fault analysis time period to determine an abnormal signal; and determine the source of the problem causing the target fault based on the abnormal signal; The analysis module is specifically used to determine the fault analysis time period based on a first time period before the occurrence time of the characteristic operation and / or a second time period after the occurrence time of the characteristic operation; wherein, when the type of the target fault is a functional failure type fault, the characteristic operation corresponding to the target fault is a first type characteristic operation, and the first type characteristic operation is an operation that causes the state of the failure function to change. The first time period before the occurrence time of the first type characteristic operation and the second time period after the occurrence time of the characteristic operation are determined as the fault analysis time period; when the type of the target fault is a fault in which the vehicle does not perform as expected by the driver, the characteristic operation corresponding to the target fault is a second type characteristic operation, and the second type characteristic operation is the driver's operation. The second time period after the occurrence time of the characteristic operation is determined as the fault analysis time period.

10. An electronic device, characterized in that: The electronic device includes: a processor and a memory; The memory is used to store instructions executable by the processor; The processor is configured to execute the instructions to implement the fault analysis method according to any one of claims 1 to 5.

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