Vehicle machine system fault positioning method and device and vehicle

Abstract

The invention discloses an in-vehicle entertainment system fault positioning method and device and a vehicle, and is applied to the technical field of real vehicle testing, and the method comprises the steps: carrying out the real vehicle testing of an in-vehicle entertainment system of the vehicle, and obtaining an execution stack of each scheduling link of the in-vehicle entertainment system; wherein the different scheduling links are links for connecting different architecture layers of the vehicle-mounted infotainment system, and an execution stack of the scheduling links is used for storing a plurality of performance functions and a plurality of variable values of the scheduling links during a real vehicle test; performing anomaly detection on the vehicle-mounted information machine system to obtain an anomaly detection result which is used for representing whether the vehicle-mounted information machine system is abnormal or not during the real vehicle test period; and if the abnormal detection result is that the vehicle machine system is abnormal during the real vehicle test, determining abnormal performance functions and abnormal variable values in the vehicle machine system according to the execution stack of each scheduling link. According to the invention, the fault positioning precision of the vehicle machine system in the real vehicle test stage can be improved.

Description

Technical Field

[0001] The present application relates to the field of real vehicle testing technology, and in particular to a method, device and vehicle for locating faults in a vehicle computer system. Background Art

[0002] The vehicle computer system refers to an electronic equipment system installed on the vehicle and used to provide information display and entertainment functions. It often integrates multiple vehicle computer functions, such as navigation, audio playback, telephone communication, and vehicle status monitoring. The actual vehicle testing phase is a crucial part of the vehicle computer system debugging process. During the actual vehicle testing phase, the debugging personnel load the vehicle computer software program into the vehicle computer system and conduct a comprehensive test of the vehicle computer system to verify the stability and reliability of the vehicle computer system, and optimize the performance and repair faults of the vehicle computer system. In related technologies, manual methods are used to export and analyze log files during the actual vehicle testing phase to locate faults in the vehicle computer system. The fault location accuracy of the vehicle computer system needs to be improved. Summary of the invention

[0003] The embodiments of the present application provide a vehicle system fault location method, device and vehicle for improving the fault location accuracy of the vehicle system during the actual vehicle testing phase.

[0004] On the one hand, an embodiment of the present application provides a method for locating a fault in a vehicle system, comprising the following steps: Performing a real vehicle test on the vehicle's on-board system to obtain an execution stack of each scheduling link of the on-board system; wherein different scheduling links are links connecting different architecture layers of the on-board system, and the execution stack of the scheduling link is used to store multiple function functions and multiple variable values ​​of the scheduling link during the real vehicle test; Performing an abnormality detection on the vehicle system to obtain an abnormality detection result, wherein the abnormality detection result is used to indicate whether the vehicle system has an abnormality during the actual vehicle test; If the abnormality detection result is that the vehicle system has an abnormality during the actual vehicle test, the abnormal function and the abnormal variable value in the vehicle system are determined according to the execution stack of each scheduling link.

[0005] On the other hand, an embodiment of the present application provides a vehicle system fault location device, including: A first processing module is used to perform a real vehicle test on the vehicle system to obtain an execution stack of each scheduling link of the vehicle system; wherein different scheduling links are links connecting different architecture layers of the vehicle system, and the execution stack of the scheduling link is used to store multiple function functions and multiple variable values ​​of the scheduling link during the real vehicle test; A second processing module is used to perform an abnormality detection on the vehicle system to obtain an abnormality detection result, wherein the abnormality detection result is used to indicate whether the vehicle system has an abnormality during the actual vehicle test; The third processing module is used to determine the abnormal function and abnormal variable value in the vehicle system according to the execution stack of each scheduling link if the abnormality detection result is that the vehicle system is abnormal during the actual vehicle test.

[0006] In another aspect, an embodiment of the present application provides a vehicle, comprising: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the above-mentioned vehicle system fault locating method.

[0007] The beneficial effects of the present application are: providing a vehicle system fault location method, device and vehicle, first, performing a real vehicle test on the vehicle's vehicle system to obtain the execution stack of each scheduling link of the vehicle system, wherein different scheduling links are links connecting different architecture layers of the vehicle system, and the execution stack of the scheduling link is used to store multiple functional functions and multiple variable values ​​of the scheduling link during the real vehicle test; then, performing an abnormality detection on the vehicle system to obtain an abnormality detection result, wherein the abnormality detection result is used to characterize whether there is an abnormality in the vehicle system during the real vehicle test; finally, if the abnormality detection result is that there is an abnormality in the vehicle system during the real vehicle test, then according to the execution stack of each scheduling link, the abnormal functional function and abnormal variable value in the vehicle system are determined. The embodiment of the present application disassembles and monitors the parameters of each architecture layer of the vehicle system during the actual vehicle test, obtains multiple functional functions and multiple variable values ​​of each scheduling link and stores them in the execution stack of each scheduling link. Then, when an abnormality is detected in the vehicle system during the actual vehicle test, based on the execution stack of each scheduling link, the abnormal functional functions and abnormal variable values ​​in the vehicle system are quickly and accurately located, thereby improving the fault location accuracy and fault location efficiency of the vehicle system during the actual vehicle testing stage.

[0008] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or understood by practicing the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 is a flow chart of the vehicle system fault location method provided by the present application; Figure 2is a structural example diagram of the vehicle system provided by this application; Figure 3 is a structural example diagram of the modified first sub-stack provided by the present application; Figure 4 is a diagram showing an example structure of an execution stack provided by this application; Figure 5 It is a structural diagram of the vehicle system fault location device provided by the present application; Figure 6 is an example diagram of a vehicle provided in this application. DETAILED DESCRIPTION

[0010] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0011] The present application is further described below in conjunction with the accompanying drawings and specific embodiments. The described embodiments should not be regarded as limiting the present application, and all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present application.

[0012] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0013] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0014] The vehicle computer system refers to an electronic device system installed on the vehicle and used to provide information display and entertainment functions. It often integrates multiple vehicle computer functions, such as navigation, audio playback, telephone communication, and vehicle status monitoring. The debugging of the vehicle computer system is one of the indispensable and important links in the vehicle development process. It can be divided into two stages: cockpit bench debugging and real vehicle testing. The cockpit bench debugging stage can simulate various driving conditions of the vehicle, while the real vehicle testing stage is closer to the actual driving conditions of the vehicle.

[0015] During the cockpit bench debugging phase, the debugging personnel load the vehicle computer system's vehicle computer software program into the cockpit bench environment, and use tools such as debuggers and monitors to monitor the vehicle computer software program's execution status, variable values, vehicle computer system status, and other information in real time to verify the correctness and performance of the vehicle computer software program. In this way, the debugging personnel can discover and fix potential problems in the vehicle computer software program and ensure the stable operation of the vehicle computer software program in the actual vehicle computer system.

[0016] During the actual vehicle testing phase, the debugging personnel will load the vehicle computer software program into the vehicle computer system and conduct a comprehensive test on the vehicle computer system, such as interface interaction, data processing, response speed, etc., to verify the stability and reliability of the vehicle computer system, and optimize and adjust the performance of the vehicle computer system. In this way, the debugging personnel can find and fix problems related to vehicle hardware, environmental compatibility, etc., and further ensure the stable operation of the vehicle computer software program in the actual vehicle computer system.

[0017] In the related art, a log file is obtained during the actual vehicle testing phase. This log file usually records the operation details of the vehicle system, such as the operation record, time record, error information, etc. of the vehicle system, and then the log file is analyzed manually to locate the fault of the vehicle system. However, the implementation of the related art relies on manual methods, and the fault location accuracy and efficiency of the vehicle system need to be improved.

[0018] In view of this, the embodiments of the present application provide a vehicle system fault location method, device and vehicle, aiming to improve the fault location accuracy and fault location efficiency of the vehicle system during the actual vehicle testing phase.

[0019] The specific implementation of the embodiment of the present application is described in detail below in conjunction with the accompanying drawings. First, the implementation steps of the vehicle system fault location method provided by the embodiment of the present application are described in conjunction with the accompanying drawings.

[0020] The vehicle system fault location method provided in the embodiment of the present application can be applied to a terminal, a server, or software running in a terminal or a server. The terminal can be a tablet computer, a laptop computer, a desktop computer, etc., but is not limited to this. The server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms. In addition, the server can also be a node server in a blockchain network, but is not limited to this. Among them, blockchain is a new application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, and encryption algorithm.

[0021] Reference Figure 1 The vehicle system fault location method mainly includes the following steps S101-S103: S101, performing a real vehicle test on the vehicle system to obtain an execution stack of each scheduling link of the vehicle system; wherein different scheduling links are links connecting different architecture layers of the vehicle system, and the execution stack of the scheduling link is used to store multiple function functions and multiple variable values ​​of the scheduling link during the real vehicle test; S102, performing an abnormality detection on the vehicle system to obtain an abnormality detection result, where the abnormality detection result is used to indicate whether there is an abnormality in the vehicle system during the actual vehicle test; S103, if the abnormality detection result is that the vehicle system is abnormal during the actual vehicle test, then determine the abnormal function and the abnormal variable value in the vehicle system according to the execution stack of each scheduling link.

[0022] In an embodiment of the present application, first, a real vehicle test is performed on the vehicle's on-board system to obtain execution stacks of various scheduling links of the on-board system, wherein different scheduling links are links connecting different architecture layers of the on-board system, and the execution stack of the scheduling link is used to store multiple functional functions and multiple variable values ​​of the scheduling link during the real vehicle test; then, an abnormality detection is performed on the on-board system to obtain an abnormality detection result, wherein the abnormality detection result is used to characterize whether there is an abnormality in the on-board system during the real vehicle test; finally, if the abnormality detection result is that there is an abnormality in the on-board system during the real vehicle test, then the abnormal functional functions and abnormal variable values ​​in the on-board system are determined according to the execution stacks of each scheduling link. It can be seen that the embodiment of the present application disassembles and monitors the parameters of each architecture layer of the vehicle-computer system during the actual vehicle test, obtains multiple functional functions and multiple variable values ​​of each scheduling link and stores them in the execution stack of each scheduling link, and then when it is detected that there is an abnormality in the vehicle-computer system during the actual vehicle test, based on the execution stack of each scheduling link, the abnormal functional functions and abnormal variable values ​​in the vehicle-computer system are quickly and accurately located, which facilitates the troubleshooting of the corresponding faults of the vehicle-computer system, can effectively improve the response speed of fault troubleshooting and system repair of the vehicle-computer system, and improve the fault location accuracy and efficiency of the vehicle-computer system in the actual vehicle testing stage.

[0023] In the above step S101, the vehicle's on-board system is subjected to actual vehicle testing. During the actual vehicle testing, each architecture layer of the on-board system is disassembled and parameter monitoring is performed to obtain multiple functional functions and multiple variable values ​​of each scheduling link and store them in the execution stack of each scheduling link.

[0024] The above-mentioned scheduling links are used to connect the various architecture layers of the vehicle-machine system. Different scheduling links are links connecting different architecture layers of the vehicle-machine system. All scheduling links jointly reflect the execution process of the vehicle-machine software program of the vehicle-machine system.

[0025] The architecture layer of the above-mentioned vehicle system can be set according to actual conditions, and the embodiment of the present application does not limit this. For example, the architecture layer of the above-mentioned vehicle system may include a transmission layer, a system layer and an application layer, but is not limited to this.

[0026] The execution stack of the above scheduling link may refer to a stack. A stack is a linear table that can only perform insertion or deletion operations at one end. The end where the insertion and deletion operations are located is called the top of the stack, and the other end is called the bottom of the stack. The characteristic of a stack is last in, first out, that is, the last element pushed into the stack is the first to be popped out, and the first element pushed into the stack is the last to be popped out.

[0027] The execution stack of the above-mentioned scheduling link is used to store multiple functional functions and multiple variable values ​​of the scheduling link during the actual vehicle test, wherein the functional functions and variable values ​​are used to execute the vehicle functions of the vehicle system to ensure the normal operation of the vehicle system.

[0028] The above functional functions and the above variable values ​​can be set according to actual conditions, and the embodiments of the present application do not limit this.

[0029] For example, the functional functions of the framework layer in the vehicle system may include navigation function functions, radio function functions, voice function functions, etc., among which the navigation function function is used to implement the navigation function of the vehicle system, the radio function function is used to implement the radio function of the vehicle system, and the voice function function is used to implement the voice control function of the vehicle system, and each function function can be configured with one or more variable values, and the variable value can be understood as the input value and / or output value of the function function, but is not limited to this.

[0030] The above-mentioned actual vehicle test of the vehicle's on-board system to obtain the execution stack of each scheduling link of the on-board system can include loading the on-board software program into the on-board system and testing the on-board system to obtain actual vehicle test log data, and then extracting parameters from the actual vehicle test log data to obtain multiple functional functions and multiple variable values ​​of each scheduling link during the actual vehicle test and randomly push them into the corresponding execution stack, thereby obtaining the execution stack of each scheduling link, but is not limited to this. In the above step S102, after the actual vehicle test is completed, an abnormality detection is performed on the vehicle system to detect whether there is an abnormality in the vehicle system during the actual vehicle test, and then obtain an abnormality detection result to realize abnormality detection of the vehicle system.

[0031] The above abnormality detection results are used to characterize whether there are abnormalities in the vehicle system during the actual vehicle test.

[0032] The above-mentioned abnormality detection of the vehicle system and obtaining the abnormality detection result may include obtaining the number of errors during the actual vehicle test. If the number of errors is greater than a preset error threshold, the abnormality detection result is determined to be that there is an abnormality in the vehicle system during the actual vehicle test. Otherwise, the abnormality detection result is determined to be that there is no abnormality in the vehicle system during the actual vehicle test, but is not limited to this.

[0033] The above error threshold can be set according to actual conditions, and the embodiment of the present application does not make specific limitations on this. For example, the above error threshold can be zero, but is not limited to this.

[0034] In the above step S103, after the abnormality detection is completed, if the abnormality detection result is that the vehicle-machine system is abnormal during the actual vehicle test, it means that the vehicle-machine system is abnormal during the actual vehicle test, and it is necessary to locate the problem of the vehicle-machine system. Specifically, since the functional functions and variable values ​​of each scheduling link can coordinate and cooperate to realize one or more vehicle-machine functions, if a certain functional function is abnormal and / or a certain variable value is abnormal, it may cause the vehicle-machine function to be unable to be realized, and then cause the vehicle-machine system to be abnormal. Therefore, when the vehicle-machine system is abnormal, the embodiment of the present application is based on multiple functional functions and multiple variable values ​​of each scheduling link, and quickly and accurately locates the abnormal functional functions and abnormal variable values, thereby realizing fault location processing of the vehicle-machine system.

[0035] The above-mentioned determination of abnormal functional functions and abnormal variable values ​​in the vehicle-computer system based on the execution stack of each scheduling link may include, for each scheduling link, popping the execution stack of the scheduling link to obtain multiple functional functions and multiple variable values ​​of the scheduling link, and then using a machine learning method to perform detection based on the multiple functional functions and multiple variable values ​​to obtain detection results of each functional function and each variable value, the detection results including any one of a normal result or an abnormal result, and taking the functional function with an abnormal detection result as an abnormal functional function in the vehicle-computer system, and taking the variable value with an abnormal detection result as an abnormal variable value in the vehicle-computer system, but is not limited to this.

[0036] The above-mentioned machine learning method can be set according to actual conditions, and the embodiments of the present application do not limit this. For example, the above-mentioned machine learning method can be a support vector machine; or the above-mentioned machine learning method can be a logistic regression, but is not limited thereto.

[0037] The above steps will be further described below.

[0038] In some implementations, the above vehicle system may have at least one of the following scheduling links: The first link is used to represent the link from the framework layer of the vehicle system to the system layer of the vehicle system; The second link is used to characterize the link from the system layer to the framework layer; The third link is used to represent the link from the framework layer to the application layer of the vehicle system; The fourth link is used to characterize the link from the application layer to the framework layer; Among them, the framework layer is configured with multiple service classes, each service class corresponds to at least one vehicle-machine function of the vehicle-machine system; the system layer is used to encapsulate the bus signal of each service class into a corresponding service interface and return it to the framework layer; the framework layer is used to provide the service interface of each service class to the application layer; the application layer is used to call the service class corresponding to the triggered vehicle-machine function through the service interface of the service class corresponding to the triggered vehicle-machine function when the vehicle-machine function of the vehicle-machine system is triggered; the framework layer is used to execute the service class corresponding to the triggered vehicle-machine function.

[0039] In this embodiment, the vehicle system may include a framework layer, a system layer and an application layer. Figure 2 The structure diagram of the vehicle system is shown as an example. The framework layer can be configured with multiple service classes, and each service class can correspond to one or more vehicle functions of the vehicle system. Exemplarily, the framework layer is configured with multiple service classes such as the external controller status display setting service class and the navigation entertainment service class. The external controller status display setting service class can correspond to vehicle functions such as air conditioning settings, charging settings, and vehicle settings, while the navigation entertainment service class can correspond to vehicle functions such as navigation, music, video, and radio.

[0040] When the vehicle computer system is started, the system layer receives the bus signal of each service class, encapsulates the bus signal of each service class into a corresponding service interface and returns it to the framework layer. The framework layer receives the service interface of each service class and provides it to the application layer. When the vehicle computer function of the vehicle computer system is triggered, the application layer calls the service class corresponding to the triggered vehicle computer function through the service interface of the service class corresponding to the triggered vehicle computer function, so that the framework layer executes the service class corresponding to the triggered vehicle computer function, thereby realizing the triggered vehicle computer function.

[0041] It should be noted that the functions of the framework layer, system layer and application layer of the above-mentioned vehicle system are not limited to the above contents. The functions of the framework layer, system layer and application layer can be configured according to actual conditions, and this embodiment does not make specific limitations on this.

[0042] Based on this, this implementation defines that the vehicle system may have at least one scheduling link among the first link, the second link, the third link and the fourth link. Specifically, the first link is a link from the framework layer to the system layer. The framework layer transmits the bus signal of each service class to the system layer through the first link, so that the system layer receives the bus signal of each service class and completes the interface encapsulation operation. The second link is a link from the system layer to the framework layer. The system layer transmits the encapsulated service interface to the framework layer through the second link, so that the framework layer receives the service interface of each service class. The third link is a link from the framework layer to the application layer. The framework layer provides the service interface of each service class to the application layer through the third link. The fourth link is a link from the application layer to the framework layer. In the fourth link, the application layer calls the service class corresponding to the triggered vehicle function in the framework layer through the service interface of the service class corresponding to the triggered vehicle function, and then the framework layer executes the service class corresponding to the triggered vehicle function, thereby realizing the triggered vehicle function.

[0043] Among them, the first link, the second link and the third link jointly reflect the service interface processing status of each service class. If the service interface encapsulation of the service class is abnormal, or the service interface of the service class cannot be passed to the framework layer or the application layer, it will affect the application layer's call to the service class, thereby failing to implement the corresponding vehicle-computer function, resulting in an abnormality in the vehicle-computer system; the fourth link reflects the implementation of the vehicle-computer function. If the service interface call is abnormal, or the service class execution is abnormal, it will affect the normal implementation of the vehicle-computer function, resulting in an abnormality in the vehicle-computer system.

[0044] It can be seen that this implementation method introduces the idea of ​​layered architecture, and utilizes the hierarchical relationship of each architecture layer of the vehicle-computer system to disassemble the vehicle-computer system into the first link, the second link, the third link and the fourth link. The first link, the second link and the third link reflect the service interface processing status of the vehicle-computer system, and the fourth link reflects the implementation status of the vehicle-computer function. This is conducive to parameter monitoring of scheduling links at different levels during actual vehicle testing, and is conducive to fault location processing of the vehicle-computer system through the parameters of scheduling links at different levels after the actual vehicle testing.

[0045] The types of the above service classes can be set according to actual conditions, and this embodiment does not specifically limit this. For example, the types of the above service classes can be external controller status display setting service classes, navigation entertainment service classes, and controller proxy service classes, among which the external controller status display setting service class is mainly used to implement vehicle functions such as air conditioning settings, charging settings, vehicle settings, and digital video recording of the vehicle system, the navigation entertainment service class is mainly used to implement vehicle functions such as navigation, music, video, and radio of the vehicle system, and the controller proxy service class is mainly used to implement vehicle functions such as rearview mirror control and power amplifier control of the vehicle system, but is not limited thereto.

[0046] The type of the service interface can be set according to actual conditions, and this embodiment does not specifically limit this. For example, the service interface can be an application programming interface (Application Programming Interface, API), but is not limited thereto.

[0047] In some implementations, the above-mentioned actual vehicle test of the vehicle system to obtain the execution stack of each scheduling link of the vehicle system may include: Load the preset vehicle computer software program into the vehicle computer system; Conduct real vehicle testing on the vehicle system loaded with the vehicle software program; For each scheduling link in the vehicle system, an execution stack of the scheduling link is obtained according to multiple functional functions and multiple variable values ​​of the scheduling link during the actual vehicle test.

[0048] In this implementation, first, a vehicle computer software program is loaded into the vehicle computer system. This vehicle computer software program is a pre-set software program, which is mainly used to implement various vehicle computer functions of the vehicle computer system; then, the vehicle computer system loaded with the vehicle computer software program is subjected to actual vehicle testing; during the actual vehicle testing, for each scheduling link in the vehicle computer system, multiple functional functions and multiple variable values ​​of the scheduling link are obtained, and based on these functional functions and these variable values, an execution stack of the scheduling link is constructed, so that when an abnormality is detected in the vehicle computer system during the actual vehicle testing, the execution stack of each scheduling link can be used to quickly and accurately locate the abnormal functional functions and abnormal variable values ​​in the vehicle computer system.

[0049] The above-mentioned vehicle computer software program can be set according to actual conditions, and this embodiment does not make any specific limitation to this.

[0050] The above-mentioned method obtains the execution stack of the scheduling link based on multiple function functions and multiple variable values ​​of the scheduling link during the actual vehicle test, which can include pushing the called function function mark into the stack when the function function of the scheduling link is called, and pushing the triggered variable value mark into the stack when the variable value of the scheduling link is triggered, thereby obtaining the execution stack of the scheduling link, wherein the stacking order of the function functions and the stacking order of the variable values ​​are positively correlated with the time value, that is, the earlier the time value when the function function is called or the time value when the variable value is triggered, the earlier the stacking order of the function function or the stacking order of the variable value, but it is not limited to this.

[0051] In some implementations, obtaining the execution stack of the scheduling link according to the multiple functional functions and multiple variable values ​​of the scheduling link during the actual vehicle test may include: Pushing multiple function functions of the scheduling link into the first sub-stack of the scheduling link; Pushing multiple variable values ​​of the scheduling link into a second sub-stack associated with the scheduling link; An execution stack of the scheduling link is obtained according to the first sub-stack and the second sub-stack.

[0052] In this embodiment, during the actual vehicle test, for each scheduling link in the vehicle system, multiple function functions of the scheduling link are pushed into the first sub-stack corresponding to the scheduling link, and multiple variable values ​​of the scheduling link are pushed into the second sub-stack corresponding to the scheduling link, and then the first sub-stack and the second sub-stack are used to build an execution stack of the scheduling link. In this way, the corresponding function functions are stored in the first sub-stack and the corresponding variable values ​​are stored in the second sub-stack, which is conducive to quickly traversing each function function and each variable value when performing fault location processing on the vehicle system, thereby quickly and accurately locating abnormal function functions and abnormal variable values ​​in the vehicle system.

[0053] The first sub-stack of the scheduling link is used to store multiple functional functions of the scheduling link.

[0054] The above-mentioned pushing multiple function functions of the scheduling link into the first sub-stack of the scheduling link may include pushing the multiple function functions of the scheduling link into the first sub-stack of the scheduling link in sequence according to the scheduling time value of the function function, wherein the stacking order of the function functions is positively correlated with the scheduling time value, that is, the earlier the scheduling time value of the function function, the earlier the stacking order of the function function in the first sub-stack.

[0055] Alternatively, the above-mentioned pushing multiple function functions of the scheduling link into the first sub-stack of the scheduling link may include pushing the multiple function functions of the scheduling link into the first sub-stack of the scheduling link in sequence according to the scheduling time value of the function function, wherein the order in which the function functions are pushed into the stack is negatively correlated with the scheduling time value, that is, the earlier the scheduling time value of the function function, the later the order in which the function functions are pushed into the first sub-stack.

[0056] It should be understood that if multiple function functions are pushed into the stack at the same scheduling time value, the order in which the multiple function functions at the same scheduling time value are pushed into the stack may be random.

[0057] The second sub-stack of the scheduling link is used to store multiple variable values ​​of the scheduling link.

[0058] The above-mentioned pushing multiple variable values ​​of the scheduling link into the second sub-stack of the scheduling link may include pushing multiple variable values ​​of the scheduling link into the second sub-stack of the scheduling link in sequence according to the trigger time value of the variable value, wherein the stacking order of the variable values ​​is positively correlated with the trigger time value, that is, the earlier the trigger time value of the variable value, the earlier the stacking order of the variable value in the second sub-stack.

[0059] Alternatively, the above-mentioned pushing multiple variable values ​​of the scheduling link into the second sub-stack of the scheduling link may include pushing multiple variable values ​​of the scheduling link into the second sub-stack of the scheduling link in sequence according to the trigger time value of the variable value, wherein the stacking order of the variable values ​​is negatively correlated with the trigger time value, that is, the earlier the trigger time value of the variable value, the later the stacking order of the variable value in the second sub-stack.

[0060] Optionally, if multiple variable values ​​are pushed into the stack at the same trigger time value, the order in which the multiple variable values ​​at the same trigger time value are pushed into the stack may be random.

[0061] The execution stack may include a first sub-stack and a second sub-stack, but is not limited thereto.

[0062] Obtaining the execution stack of the scheduling link according to the first substack and the second substack may include connecting the first substack and the second substack into the execution stack of the scheduling link. In the execution stack, the first substack and the second substack are independent of each other, but is not limited thereto.

[0063] In some implementations, obtaining the execution stack of the scheduling link according to the first sub-stack and the second sub-stack may include: For each function of the first sub-stack, at least one variable value corresponding to the function in the second sub-stack is determined as the target variable value of the function according to the sub-stack mapping data, and a mapping identifier of the function function relative to each target variable value is obtained as an element of a mapping set of the function function according to the arrangement position of the function function in the first sub-stack and the arrangement position of each target variable value in the second sub-stack; wherein the sub-stack mapping data includes a plurality of preset function functions and at least one variable value corresponding to each preset function function; Modifying the first sub-stack by using the mapping set of each function of the first sub-stack to obtain a modified first sub-stack; An execution stack of the scheduling link is constructed according to the second sub-stack and the modified first sub-stack.

[0064] In this implementation, for each scheduling link, when a function is scheduled, one or more variable values ​​corresponding to the function will be triggered synchronously, that is, the function corresponds to one or more variable values, and the variable values ​​can be understood as the input value and output value of the function. Based on this, this implementation maps each function in the first sub-stack and each variable value in the second sub-stack to obtain the execution stack of the scheduling link. By constructing a mapping relationship between the first sub-stack and the second sub-stack, each function in the vehicle system is strongly correlated with the corresponding variable value, which is conducive to quickly traversing each function and each variable value when locating the fault of the vehicle system, so as to quickly and accurately locate the abnormal function and the abnormal variable value.

[0065] Specifically, first, for each function of the first sub-stack, according to the sub-stack mapping data, at least one variable value corresponding to the function is determined in the second sub-stack as the target variable value of the function, and according to the arrangement position of the function in the first sub-stack and the arrangement position of each target variable value in the second sub-stack, the mapping identifier of the function relative to each target variable value is determined as an element of the mapping set of the function, and each mapping identifier can reflect the relationship between the function function and each variable value. It can be understood that each element together constitutes the mapping set of the function function. By traversing each function of the first sub-stack, the mapping set of each function function of the first sub-stack can be obtained. Afterwards, the first sub-stack is modified using the mapping set of each function function of the first sub-stack to obtain the modified first sub-stack. The modification here can be understood as assigning the mapping set of each function function to each function function, so that each function function carries the corresponding mapping set when the stack is popped, so that it is convenient to find the corresponding variable value through the mapping set of each function function. Finally, according to the second sub-stack and the modified first sub-stack, the execution stack of the scheduling link is constructed.

[0066] The sub-stack mapping data may include a plurality of preset function functions and at least one variable value corresponding to each preset function function.

[0067] The data format of the sub-stack mapping data can be set according to actual conditions, and this embodiment does not limit this. For example, the sub-stack mapping data can be chart data or table data, but is not limited thereto.

[0068] The mapping relationship between the above functional functions and the above variable values ​​can be set according to actual conditions, and this embodiment does not limit this.

[0069] The above-mentioned method of obtaining a mapping identifier of the function function relative to each target variable value based on the arrangement position of the function function in the first sub-stack and the arrangement position of each target variable value in the second sub-stack may include, for each target variable value, associating the arrangement position of the function function in the first sub-stack with the arrangement position of the target variable value in the second sub-stack to obtain a mapping identifier of the function function relative to the target variable value; wherein, The first substack of the scheduling link The function is relative to the The first The mapping identifier of the target variable value can be expressed as (the arrangement position of the function in the first sub-stack , the position of the target variable value in the second substack ).

[0070] Alternatively, the above-mentioned obtaining a mapping identifier of the function function relative to each target variable value based on the arrangement position of the function function in the first sub-stack and the arrangement position of each target variable value in the second sub-stack may include, for each target variable value, associating the arrangement position of the function function in the first sub-stack with the arrangement position of the target variable value in the second sub-stack to obtain a mapping identifier of the function function relative to the target variable value; wherein, The first substack of the scheduling link The function is relative to the The first The mapping identifier of the target variable value can be expressed as (the arrangement position of the target variable value in the second sub-stack , the arrangement position of the function in the first sub-stack ).

[0071] The mapping set of the above function may include multiple elements, where an element refers to a mapping identifier of the function relative to the target variable value.

[0072] The above-mentioned modification of the first sub-stack by using the mapping set of each function function of the first sub-stack may be to assign the mapping set of the function function to each function function of the first sub-stack, so that the function function carries the corresponding mapping set during the popping process.

[0073] The above-mentioned construction of the execution stack of the scheduling link based on the second sub-stack and the modified first sub-stack can be to connect the second sub-stack and the modified first sub-stack into the execution stack of the scheduling link. In the execution stack, the first sub-stack and the second sub-stack are associated with each other through a mapping set of each function.

[0074] In an example, the first substack of a certain scheduling link has function function A, function function B, function function C, function function D, ..., function function Y pushed into the stack in sequence. Since function function A is pushed into the stack first, the bottom pointer of the first substack points to function function A. Since function function Y is pushed into the stack last, the top pointer of the first substack points to function function Y. Similarly, the second substack has variable value A, variable value B, variable value C, variable value D, ..., variable value X pushed into the stack in sequence. Since variable value A is pushed into the stack first, the bottom pointer of the second substack points to variable value A. Since variable value X is pushed into the stack last, the bottom pointer of the second substack points to variable value X.

[0075] Taking function A, function B, function C, function D and function Y as examples, assuming that it can be known through the sub-stack mapping data that function A is associated with variable value A and variable value B respectively, function B is associated with variable value C, function C is associated with variable value B, function D is associated with variable value D, and function Y is associated with variable value X. On this basis, determine the mapping identifier of function function A relative to variable value A and the mapping identifier of function function A relative to variable value B as elements of mapping set 1 of function function A, thereby constructing mapping set 1 of function function A; determine function function B The mapping identifier relative to the variable value C is used as an element of mapping set 2 of function function B, thereby constructing mapping set 2 of function function B; the mapping identifier of function function C relative to the variable value B is determined as an element of mapping set 3 of function function C, thereby constructing mapping set 3 of function function C; the mapping identifier of function function D relative to the variable value D is determined as an element of mapping set 4 of function function D, thereby constructing mapping set 4 of function function D; the mapping identifier of function function Y relative to the variable value X is determined as an element of mapping set N of function function Y, thereby constructing mapping set N of function function Y.

[0076] After obtaining the mapping sets of each function, mapping set 1 is assigned to function A, mapping set 2 is assigned to function B, mapping set 3 is assigned to function C, mapping set 4 is assigned to function D, and mapping set N is assigned to function Y, so as to obtain the modified first sub-stack, as shown in FIG. Figure 3 Finally, the second substack and the modified first substack are connected to form an execution stack of the scheduling link. In the execution stack, the first substack and the second substack are associated with each other through the mapping set of each function, as shown in FIG. Figure 4 shown.

[0077] In some implementations, the above-mentioned abnormality detection on the vehicle system to obtain the abnormality detection result may include: Obtain the actual vehicle test log data of the vehicle system; According to the actual vehicle test log data, each dispatch link is detected for abnormalities; If an abnormality is detected in at least one scheduling link, the abnormality detection result is determined to be an abnormality in the vehicle system during the actual vehicle test.

[0078] In this implementation, after the actual vehicle test is completed, it is necessary to perform an abnormality detection on the vehicle system, that is, to detect whether the vehicle system has an abnormality during the actual vehicle test. Specifically, firstly, the actual vehicle test log data of the vehicle system is obtained, and the actual vehicle test log data is used to characterize the scheduling status of each scheduling link during the actual vehicle test. Then, according to the actual vehicle test log data, it is detected whether each scheduling link has an abnormality. If at least one scheduling link is detected to have an abnormality, it means that the vehicle system has an abnormality during the actual vehicle test. At this time, it is determined that the abnormality detection result is that the vehicle system has an abnormality during the actual vehicle test, thereby improving the abnormality detection efficiency of the vehicle system.

[0079] The above-mentioned acquisition of the actual vehicle test log data of the vehicle system may include capturing the actual vehicle test log data of the vehicle system through a preset log management tool, but is not limited thereto.

[0080] The log management tool can be set according to actual conditions, and this embodiment does not limit this. For example, the log management tool can be the Logcat tool of Android Studio; or the log management tool can be a third-party tool such as Bugfender, ACRA, etc., but is not limited thereto.

[0081] The above-mentioned abnormality detection of each scheduling link based on the actual vehicle test log data may include using natural language technology to process the actual vehicle test log data to obtain log events of each scheduling link, and then using machine learning methods to perform abnormality detection on each scheduling link based on the log events of each scheduling link, but is not limited to this.

[0082] The above-mentioned machine learning method can be set according to actual conditions, and the embodiments of the present application are not limited to this.

[0083] For example, the above-mentioned machine learning method may be a support vector machine; or, the above-mentioned machine learning method may be a logistic regression, but is not limited thereto.

[0084] In some implementations, the above-mentioned abnormality detection of each scheduling link based on the actual vehicle test log data may include: According to the actual vehicle test log data, the link parameters are obtained; The link parameters include a first interface parameter, a second interface parameter, a third interface parameter, an interface scheduling parameter, a service class execution status, a packet loss rate of the first link, a packet loss rate of the second link, and a packet loss rate of the third link. The first interface parameter is a parameter of the service interface encapsulated by the system layer, the second interface parameter is a parameter of the service interface received by the framework layer, the third interface parameter is a parameter of the service interface received by the application layer, the interface scheduling parameter is a parameter of the service interface called by the application layer, and the service class execution status includes any one of a success status or a failure status. The above-mentioned abnormality detection of each scheduling link based on the actual vehicle test log data may also include at least one of the following: Performing anomaly detection on the first link according to the packet loss rate of the first link; Performing abnormality detection on the second link according to the first interface parameter, the second interface parameter and the packet loss rate of the second link; Performing abnormality detection on the third link according to the second interface parameter, the third interface parameter and the packet loss rate of the third link; According to the interface scheduling parameters and the service class execution status, an abnormality detection is performed on the fourth link.

[0085] In this implementation, after obtaining the actual vehicle test log data, the actual vehicle test log data is first processed to obtain link parameters, which may include first interface parameters, second interface parameters, third interface parameters, interface scheduling parameters, service class execution status, packet loss rate of the first link, packet loss rate of the second link, and packet loss rate of the third link; then, based on one or more data in the link parameters and combined with the characteristics of each scheduling link, anomaly detection is performed on each scheduling link, which can effectively improve the anomaly detection accuracy of each scheduling link.

[0086] Specifically, the framework layer transmits the bus signals of each service class to the system layer through the first link, so that the system layer receives the bus signals of each service class and performs interface encapsulation. If the bus signals of some service classes are lost during the transmission of the first link, the system layer cannot perform interface encapsulation processing on the service class whose bus signal is lost, resulting in abnormality of the vehicle system. It can be seen that the transmission integrity of the bus signals of each service class is crucial to the stable operation of the vehicle system. Therefore, the first link can be detected for abnormality through the packet loss rate of the first link to detect whether the bus signals of each service class in the first link are lost.

[0087] The system layer transmits the encapsulated service interface to the framework layer through the second link. If the service interface encapsulated by the system layer is abnormal, or the service interface of some service classes is lost during the transmission process of the second link, it will affect the subsequent application layer's call to the service interface and the realization of the vehicle-machine function, thereby causing the vehicle-machine system to be abnormal; wherein, the abnormality of the service interface encapsulated by the system layer can be understood as the system layer encapsulating the bus signal of the service class as an incorrect service interface. It can be seen that the accuracy of the interface encapsulation of the system layer and the transmission integrity of the service interfaces of each service class are crucial to the stable operation of the vehicle-machine system. Therefore, the second link can be detected for abnormality through the parameters of the service interface encapsulated by the system layer, the parameters of the service interface received by the framework layer, and the packet loss rate of the second link, so as to detect whether the interface encapsulation operation of the system layer is abnormal and whether the service interfaces of each service class are lost in the second link.

[0088] The framework layer provides the service interface of each service class to the application layer through the third link. If the service interface of some service classes is lost during the transmission process of the third link, it will affect the subsequent application layer's call to the service interface and the realization of the vehicle-computer function, thereby causing the vehicle-computer system to be abnormal. It can be seen that the transmission integrity of the service interface of each service class is crucial to the stable operation of the vehicle-computer system. Therefore, the second link can be detected for abnormality through the parameters of the service interface received by the framework layer, the parameters of the service interface received by the application layer, and the packet loss rate of the third link to detect whether the service interface of each service class is lost in the third link.

[0089] In the fourth link, the application layer calls the service class corresponding to the triggered vehicle function in the framework layer through the service interface of the service class corresponding to the triggered vehicle function, and the framework layer executes the service class corresponding to the triggered vehicle function. If the service interface call is abnormal, or the service interface call is normal but the service class execution is abnormal, it may cause the vehicle function to fail to be implemented, thereby causing the vehicle system to be abnormal; wherein, the service interface call abnormality can be understood as the application layer calling the service interface that does not correspond to the triggered vehicle function. It can be seen that the correctness of the call of the service interface of each service class and the correctness of the execution of each service class are crucial to the stable operation of the vehicle system. Therefore, the fourth link can be detected for abnormality through the parameters of the service interface called by the application layer and the status of the service class corresponding to the triggered vehicle function to detect whether the service interface is called normally and whether the service class is executed normally.

[0090] The above-mentioned packet loss rate can be the ratio of the difference in message volume between the receiving end and the sending end to the message volume received by the receiving end, and the difference in message volume between the receiving end and the sending end can be the absolute value of the difference in message volume received by the receiving end to the message volume sent by the sending end.

[0091] The performing anomaly detection on the first link according to the packet loss rate of the first link may include performing anomaly detection on the first link according to the packet loss rate of the first link in combination with a machine learning method to obtain an anomaly detection result of the first link.

[0092] Alternatively, the above-mentioned performing abnormality detection on the first link according to the packet loss rate of the first link may include determining that the first link is abnormal if the packet loss rate of the first link is greater than a preset first packet loss threshold, and otherwise determining that the first link is not abnormal.

[0093] The first packet loss threshold may be set according to actual conditions, and this embodiment does not impose any specific limitation on this.

[0094] The above-mentioned first interface parameter refers to the parameter of the service interface encapsulated by the system layer, such as the type of the service interface encapsulated by the system layer and the vehicle machine function identifier, etc., wherein the vehicle machine function identifier can be a specific value, but is not limited to this.

[0095] The above-mentioned second interface parameters refer to the parameters of the service interface received by the framework layer, such as the type of the service interface received by the framework layer and the vehicle machine function identifier, but are not limited to this.

[0096] The above-mentioned performing anomaly detection on the second link according to the first interface parameters, the second interface parameters and the packet loss rate of the second link may include performing anomaly detection on the second link according to the first interface parameters, the second interface parameters and the packet loss rate of the second link in combination with a machine learning method to obtain anomaly detection results of the second link.

[0097] Alternatively, the above-mentioned abnormality detection on the second link based on the first interface parameters, the second interface parameters and the packet loss rate of the second link may include determining that there is an abnormality in the second link if at least one of the following is satisfied: the first interface parameters are inconsistent with the preset encapsulation interface parameters, the first interface parameters are inconsistent with the second interface parameters, or the packet loss rate of the second link is greater than a preset second packet loss threshold; otherwise, determining that there is no abnormality in the second link.

[0098] The second packet loss threshold and the encapsulation interface parameters can be set according to actual conditions, and this embodiment does not specifically limit this. For example, the encapsulation interface parameters may include a preset type and a preset function identifier of the service interface, wherein the preset function identifier may be a specific value, but is not limited thereto.

[0099] The inconsistency between the above-mentioned first interface parameters and the preset encapsulation interface parameters may mean that the type of the service interface encapsulated at the system layer is different from the preset type of the service interface encapsulated at the system layer, and / or the vehicle-machine function identifier of the service interface encapsulated at the system layer is different from the preset function identifier of the service interface encapsulated at the system layer.

[0100] The inconsistency between the first interface parameters and the second interface parameters may mean that the type of service interface encapsulated by the system layer is different from the type of service interface received by the framework layer, and / or the vehicle function identifier of the service interface encapsulated by the system layer is different from the preset function identifier of the service interface received by the framework layer.

[0101] The third interface parameter mentioned above refers to the parameter of the service interface received by the application layer, such as the type of the service interface received by the application layer and the vehicle machine function identifier, but is not limited thereto.

[0102] The above-mentioned performing anomaly detection on the third link according to the second interface parameters, the third interface parameters and the packet loss rate of the third link may include performing anomaly detection on the third link according to the second interface parameters, the third interface parameters and the packet loss rate of the third link in combination with a machine learning method to obtain anomaly detection result of the third link.

[0103] Alternatively, the above-mentioned abnormality detection on the third link based on the second interface parameters, the third interface parameters and the packet loss rate of the third link may include determining that there is an abnormality in the third link if the second interface parameters are inconsistent with the third interface parameters and / or the packet loss rate of the third link is greater than a preset third packet loss threshold, otherwise determining that there is no abnormality in the third link.

[0104] The third packet loss threshold may be set according to actual conditions, and this embodiment does not specifically limit this.

[0105] The inconsistency between the above-mentioned second interface parameters and the third interface parameters may mean that the type of service interface received by the framework layer is different from the type of service interface received by the application layer, and / or the vehicle-machine function identifier of the service interface received by the framework layer is different from the vehicle-machine function identifier of the service interface received by the application layer.

[0106] The above-mentioned interface scheduling parameters refer to the parameters of the service interface called by the application layer, such as the type of the service interface called by the application layer and the vehicle computer function identifier, but are not limited thereto.

[0107] The above-mentioned service class execution status is mainly used to characterize the status of the service class corresponding to the triggered vehicle computer function. The service class execution status includes any one of a success status or a failure status, where the success status indicates that the service class is executed successfully and the vehicle computer function is successfully implemented; the failure status indicates that the service class execution fails and the vehicle computer function is not successfully implemented.

[0108] The above-mentioned performing anomaly detection on the fourth link according to the interface scheduling parameters and the service class execution status may include performing anomaly detection on the fourth link according to the interface scheduling parameters and the service class execution status in combination with a machine learning method to obtain anomaly detection results of the fourth link.

[0109] Alternatively, the above-mentioned abnormality detection on the fourth link based on the interface scheduling parameters and the service class execution status may include determining that there is an abnormality in the fourth link if the interface scheduling parameters are inconsistent with the preset interface parameters of the triggered vehicle function, and / or the service class execution status is a failure state, otherwise determining that there is no abnormality in the fourth link.

[0110] The preset interface parameters of the above-mentioned triggered vehicle function can be set according to actual conditions, and this embodiment does not limit this. For example, the preset interface parameters of the above-mentioned triggered vehicle function can be the type of preset interface of the triggered vehicle function and the vehicle function identifier, but is not limited thereto.

[0111] The inconsistency between the above-mentioned interface scheduling parameters and the preset interface parameters of the triggered vehicle-computer function may mean that the type of the service interface called by the application layer is inconsistent with the type of the preset interface of the triggered vehicle-computer function, and / or the vehicle-computer function identifier of the service interface called by the application layer is inconsistent with the vehicle-computer function identifier of the preset interface of the triggered vehicle-computer function.

[0112] In some implementations, determining the abnormal function and the abnormal variable value in the vehicle system according to the execution stack of each scheduling link may include: Acquire the scheduling link with the abnormality as the abnormal link; Popping the first substack in the execution stack of the exception link to obtain multiple functional functions of the exception link; According to a plurality of preset functions of the abnormal link, at least one function function having an abnormality is determined among a plurality of function functions of the abnormal link.

[0113] In this embodiment, first, the abnormal scheduling link can be obtained as an abnormal link through the abnormal detection in the above steps; then, for a single abnormal link, the execution stack of the abnormal link is obtained, and the first substack in the execution stack of the abnormal link is popped to obtain multiple functional functions of the abnormal link, and then at least one abnormal functional function is determined from the multiple functional functions of the abnormal link according to the multiple preset functions of the abnormal link. In this way, the functional functions stored in the first substack can be quickly and accurately located in the vehicle system, thereby improving the fault location efficiency and fault location accuracy of the vehicle system.

[0114] The above-mentioned abnormal function refers to the function that causes the vehicle system to be abnormal, which can be understood as an abnormal function.

[0115] The method for determining the above-mentioned abnormal functional function can be set according to actual conditions, and this embodiment does not make any specific limitation to this.

[0116] Exemplarily, in some embodiments, the above-mentioned determining at least one abnormal function among the multiple function functions of the abnormal link according to the multiple preset functions of the abnormal link may include comparing the function functions and the preset functions located at the same arrangement position according to the arrangement position of each function function and the arrangement position of each preset function; for the first A function, if The pseudo code of the first function is the same as the If the pseudocode of the preset function is different, The first function is determined to be an abnormal function, otherwise the The function functions are normal; by traversing the function functions of the abnormal link, at least one function with an abnormality is obtained.

[0117] Exemplarily, in some embodiments, the above-mentioned determining at least one abnormal function among the multiple function functions of the abnormal link according to the multiple preset functions of the abnormal link may include comparing the function functions and the preset functions located at the same arrangement position according to the arrangement position of each function function and the arrangement position of each preset function; for the first A function, if The car function of the first function is the same as the If the car computer function of the first preset function is different, The first function is determined to be an abnormal function, otherwise the The function functions are normal; by traversing the function functions of the abnormal link, at least one function with an abnormality is obtained.

[0118] Exemplarily, in some embodiments, the above-mentioned determining at least one abnormal function among the multiple function functions of the abnormal link according to the multiple preset functions of the abnormal link may include comparing the function functions and the preset functions located at the same arrangement position according to the arrangement position of each function function and the arrangement position of each preset function; for the first A function, if The car function of the first function is the same as the The car computer functions differently for the preset functions and / or The pseudo code of the first function is the same as the If the pseudocode of the preset function is different, The first function is determined to be an abnormal function, otherwise the The function functions are normal; by traversing the function functions of the abnormal link, at least one function with an abnormality is obtained.

[0119] It can be understood that when there are at least two abnormal links, this implementation is performed on each abnormal link sequentially or simultaneously.

[0120] In some implementations, the above-mentioned determining the abnormal function and the abnormal variable value in the vehicle system according to the execution stack of each scheduling link may also include: Popping the second substack in the execution stack of the exception link to obtain multiple variable values ​​of the exception link; For each abnormal function of the abnormal link, according to the mapping set of the abnormal function, among the multiple variable values ​​of the abnormal link, at least one variable value corresponding to the abnormal function is determined as a candidate variable value, and according to the multiple preset variable values ​​of the abnormal function, at least one abnormal variable value is determined among the multiple candidate variable values.

[0121] In this implementation, the abnormality of the function is often caused by the incorrect application of the variable value of the function. Therefore, after determining the abnormal function, the abnormal function can be used in combination with the second sub-stack to determine the abnormal variable value in the vehicle system. Specifically, for ease of understanding, the arrangement position of the function function with an exception in the first sub-stack is defined as a pointer position, and the arrangement position of the variable value in the second sub-stack is defined as a candidate position. The function functions popped out of the first sub-stack all carry a corresponding mapping set. According to the mapping set, it can be seen that the pointer position is strongly correlated with some candidate positions. Therefore, for a single abnormal link, the second sub-stack in the execution stack of the abnormal link is first popped to obtain multiple variable values ​​of the abnormal link, and then for each function function with an exception in the abnormal link, there are: among the multiple variable values ​​of the abnormal link, the candidate position corresponding to the pointer position is determined as the target position, and the variable value located at the target position is determined as the variable value corresponding to the function function with the exception, that is, the candidate variable value. In this way, through the mapping relationship between the function function and the variable value, the variable value of the function function with the exception can be quickly and accurately traversed to obtain, and then through the multiple preset variable values ​​of the function function with the exception, at least one variable value with an exception is determined from the multiple candidate variable values. By traversing all the abnormal function functions in the abnormal link, at least one abnormal variable value in the vehicle system can be found, so that the abnormal variable value in the vehicle system can be further located quickly and accurately, thereby improving the fault location efficiency and fault location accuracy of the vehicle system.

[0122] The method for determining the abnormal variable value can be set according to the actual situation, and this embodiment does not make any specific limitation to this.

[0123] Exemplarily, in some embodiments, the above-mentioned multiple preset variable values ​​of the functional function with the exception, determining at least one variable value with an exception among multiple candidate variable values, may include, for each candidate variable value, if the data type of the candidate variable value is different from the numerical type of the preset variable value corresponding to the candidate variable value, then determining the candidate variable value as a variable value with an exception.

[0124] The above data types can be set according to actual conditions, and this embodiment does not specifically limit this. For example, the above data types can include numerical types, string types, Boolean types, etc., but are not limited thereto.

[0125] Exemplarily, in some embodiments, the above-mentioned multiple preset variable values ​​of the functional function with the abnormality, determining at least one variable value with the abnormality among multiple candidate variable values, may include, for each candidate variable value, if the numerical value of the candidate variable value is different from the numerical value of the preset variable value corresponding to the candidate variable value, then determining the candidate variable value as a variable value with the abnormality.

[0126] Exemplarily, in some embodiments, the above-mentioned multiple preset variable values ​​of the functional function with the abnormality, determining at least one variable value with an abnormality among multiple candidate variable values, may include, for each candidate variable value, if the data type of the candidate variable value is different from the numerical type of the preset variable value corresponding to the candidate variable value, or the data type of the candidate variable value is the same as the numerical type of the preset variable value corresponding to the candidate variable value, but the numerical value of the candidate variable value is different from the numerical value of the preset variable value corresponding to the candidate variable value, then determining the candidate variable value as a variable value with an abnormality.

[0127] It can be understood that when there are at least two abnormal links, this implementation is performed on each abnormal link sequentially or simultaneously.

[0128] To facilitate the understanding of the above-mentioned vehicle system fault locating method of the present application, the actual application scenario of the above-mentioned vehicle system fault locating method of the present application is illustrated here by way of example.

[0129] Reference Figure 2 , the vehicle system of this example has a first link, a second link, a third link and a fourth link. Specifically, the first link is a link from the framework layer to the system layer. The framework layer transmits the bus signal of each service class to the system layer through the first link, so that the system layer receives the bus signal of each service class and completes the interface encapsulation operation. The second link is a link from the system layer to the framework layer. The system layer transmits the encapsulated service interface to the framework layer through the second link, so that the framework layer receives the service interface of each service class. The third link is a link from the framework layer to the application layer. The framework layer provides the service interface of each service class to the application layer through the third link. The fourth link is a link from the application layer to the framework layer. In the fourth link, the application layer calls the service class corresponding to the triggered vehicle function in the framework layer through the service interface of the service class corresponding to the triggered vehicle function, and then the framework layer executes the service class corresponding to the triggered vehicle function, thereby realizing the triggered vehicle function.

[0130] Based on this, the fault location process of the vehicle system implemented in this example specifically includes the following steps S201-S204.

[0131] S201, loading the vehicle computer software program into the vehicle computer system, and performing a real vehicle test on the vehicle computer system loaded with the vehicle computer software program.

[0132] S202, during the actual vehicle test, multiple functional functions and multiple variable values ​​of each scheduling link are obtained and pushed into a stack.

[0133] Specifically, for each scheduling link, there are: First, according to the scheduling time value of the function function, multiple function functions of the scheduling link are pushed into the first sub-stack of the scheduling link in sequence, wherein the stacking order of the function functions is positively correlated with the scheduling time value, that is, the earlier the scheduling time value of the function function, the earlier the stacking order of the function function in the first sub-stack; and, according to the triggering time value of the variable value, multiple variable values ​​of the scheduling link are pushed into the second sub-stack of the scheduling link in sequence, wherein the stacking order of the variable values ​​is positively correlated with the triggering time value, that is, the earlier the triggering time value of the variable value, the earlier the stacking order of the variable value in the second sub-stack.

[0134] Then, for each function of the first sub-stack, according to the sub-stack mapping data, at least one variable value corresponding to the function function is determined in the second sub-stack as the target variable value of the function function, and according to the arrangement position of the function function in the first sub-stack and the arrangement position of each target variable value in the second sub-stack, the mapping identifier of the function function relative to each target variable value is determined as the mapping set of the function function, and each mapping identifier can reflect the relationship between the function function and each variable value; by traversing each function function of the first sub-stack, the mapping set of each function function of the first sub-stack can be obtained.

[0135] Finally, the first sub-stack is modified using the mapping set of each function function of the first sub-stack, that is, the mapping set of each function function is assigned to each function function, so that each function function carries the corresponding mapping set during the pop-up processing, thereby obtaining the modified first sub-stack, and based on the second sub-stack and the modified first sub-stack, construct the execution stack of the scheduling link.

[0136] S203, after the actual vehicle test is completed, an abnormality detection is performed on the vehicle system to detect whether there is an abnormality in the vehicle system during the actual vehicle test, and then obtain an abnormality detection result to realize abnormality detection of the vehicle system.

[0137] Specifically, firstly, the actual vehicle test log data of the vehicle system is captured through the preset log management tool, and the link parameters are extracted according to the actual vehicle test log data, wherein the link parameters include the first interface parameter, the second interface parameter, the third interface parameter, the interface scheduling parameter, the service class execution status, the packet loss rate of the first link, the packet loss rate of the second link and the packet loss rate of the third link. The first interface parameter is the parameter of the service interface encapsulated by the system layer, the second interface parameter is the parameter of the service interface received by the framework layer, the third interface parameter is the parameter of the service interface received by the application layer, the interface scheduling parameter is the parameter of the service interface called by the application layer, and the service class execution status includes any one of a success status or a failure status.

[0138] Then, according to the packet loss rate of the first link, an abnormality detection is performed on the first link. More specifically, if the packet loss rate of the first link is greater than a preset first packet loss threshold, it is determined that the first link is abnormal, otherwise it is determined that the first link is not abnormal.

[0139] At the same time, according to the first interface parameter, the second interface parameter and the packet loss rate of the second link, the second link is detected for abnormality. More specifically, if at least one of the first interface parameter and the preset encapsulation interface parameter are inconsistent, the first interface parameter and the second interface parameter are inconsistent, or the packet loss rate of the second link is greater than the preset second packet loss threshold, it is determined that the second link is abnormal, otherwise it is determined that the second link is not abnormal.

[0140] At the same time, according to the second interface parameter, the third interface parameter and the packet loss rate of the third link, the third link is detected for abnormality. More specifically, if the second interface parameter is inconsistent with the third interface parameter, and / or the packet loss rate of the third link is greater than a preset third packet loss threshold, it is determined that the third link is abnormal, otherwise it is determined that the third link is not abnormal.

[0141] At the same time, according to the interface scheduling parameters and the service class execution status, the fourth link is detected for abnormality. More specifically, if the interface scheduling parameters are inconsistent with the preset interface parameters of the triggered vehicle function, and / or the service class execution status is a failure state, it is determined that the fourth link is abnormal, otherwise it is determined that the fourth link is not abnormal.

[0142] Through the above-mentioned abnormality detection, if it is detected that at least one scheduling link has an abnormality, it is determined that the abnormality detection result is that there is an abnormality in the vehicle system during the actual vehicle test.

[0143] S204, after the abnormality detection is completed, if the abnormality detection result is that the vehicle system is abnormal during the actual vehicle test, it means that the vehicle system is abnormal during the actual vehicle test, and it is necessary to locate the problem of the vehicle system. The location processing is divided into two stages, the first stage is to locate the function with abnormality, and the second stage is to locate the variable value with abnormality.

[0144] Specifically, in the first stage, first, a scheduling link with an exception is obtained as an abnormal link; then, for a single abnormal link, the first substack in the execution stack of the abnormal link is popped to obtain multiple function functions of the abnormal link, and according to the arrangement position of each function function and the arrangement position of each preset function, the function function and the preset function at the same arrangement position are compared; for the first substack in the execution stack of the abnormal link, the function function and the preset function at the same arrangement position are popped to obtain multiple function functions of the abnormal link. A function, if The car function of the first function is the same as the The car computer functions differently for the preset functions and / or The pseudo code of the first function is the same as the If the pseudocode of the preset function is different, The first function is determined to be an abnormal function, otherwise the In this way, by traversing the functional functions of the abnormal link, at least one abnormal functional function in the vehicle system is obtained.

[0145] In the second stage, the abnormality of the function is often caused by the incorrect application of the variable value of the function. Therefore, after determining the abnormal function, the abnormal function can be used in combination with the second sub-stack to determine the abnormal variable value in the vehicle system.

[0146] More specifically, the arrangement position of the abnormal function in the first sub-stack is defined as the pointer position, and the arrangement position of the variable value in the second sub-stack is defined as the candidate position. The function functions popped out of the first sub-stack all carry a corresponding mapping set. According to the mapping set, it can be seen that the pointer position is strongly correlated with some candidate positions. Therefore, for a single abnormal link, the second sub-stack in the execution stack of the abnormal link is first popped to obtain multiple variable values ​​of the abnormal link, and then for each abnormal function in the abnormal link: among the multiple variable values ​​of the abnormal link, the candidate position corresponding to the pointer position is determined as the target position, and the variable value at the target position is determined as the variable value corresponding to the abnormal function, that is, the candidate variable value. In this way, through the mapping relationship between the function function and the variable value, the variable value of the abnormal function can be quickly and accurately traversed to obtain the variable value of the abnormal function, and then through the multiple preset variable values ​​of the abnormal function, at least one abnormal variable value is determined from the multiple candidate variable values. By traversing all the abnormal function functions in the abnormal link, at least one abnormal variable value in the vehicle system can be found, so that the abnormal variable value in the vehicle system can be further located quickly and accurately, thereby improving the fault location efficiency and fault location accuracy of the vehicle system.

[0147] Next, the implementation of the vehicle system fault location device provided by the embodiment of the present application is described in conjunction with the accompanying drawings. Figure 5 The vehicle system fault location device provided in the embodiment of the present application may include: The first processing module 301 is used to perform a real vehicle test on the vehicle system to obtain an execution stack of each scheduling link of the vehicle system; wherein different scheduling links are links connecting different architecture layers of the vehicle system, and the execution stack of the scheduling link is used to store multiple function functions and multiple variable values ​​of the scheduling link during the real vehicle test; The second processing module 302 is used to perform an abnormality detection on the vehicle system to obtain an abnormality detection result, and the abnormality detection result is used to indicate whether there is an abnormality in the vehicle system during the actual vehicle test; The third processing module 303 is used to determine the abnormal function and abnormal variable value in the vehicle system according to the execution stack of each scheduling link if the abnormality detection result is that the vehicle system is abnormal during the actual vehicle test.

[0148] The contents of the above method embodiments are all applicable to the present device embodiments. The functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0149] Finally, refer to Figure 6 , the embodiment of the present application further provides a vehicle, which may include: at least one processor 401; At least one memory 402, used to store at least one program; When at least one program is executed by at least one processor 401, the at least one processor 401 implements the above-mentioned vehicle system fault locating method.

[0150] The above-mentioned vehicles can be private cars, such as sedans, sport utility vehicles (SUV), multi-purpose vehicles (MPV) or pickup trucks, etc., or they can be commercial vehicles, such as vans, buses, small trucks or large trailers, etc. They can also be gasoline vehicles or new energy vehicles such as hybrid vehicles and pure electric vehicles.

[0151] The above-mentioned memory 402, as a non-transient network system, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory 402 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory 402 may optionally include a memory 402 remotely arranged relative to the processor 401, and these remote memories 402 may be connected to the processor 401 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0152] The above-mentioned memory 402 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device or a random access memory (RAM). The memory 402 can store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 402, and the processor 401 is called to execute the method of the embodiment of this application.

[0153] The processor 401 may be implemented by a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solution provided in the embodiments of the present application.

[0154] In some embodiments, the vehicle may further include: Input / output interface, used to realize information input and output; Communication interface, used to realize communication interaction between this device and other devices. Communication can be realized through wired methods (such as USB, network cable, etc.) or wireless methods (such as mobile network, WIFI, Bluetooth, etc.); A bus that transmits information between various components of the device (e.g., processor 401, memory 402, input / output interfaces, and communication interfaces); The processor 401 , the memory 402 , the input / output interface and the communication interface can be connected to each other in communication within the device via a bus.

[0155] The contents of the above method embodiments are all applicable to the present vehicle embodiment. The functions specifically implemented by the present vehicle embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0156] In some optional embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the application is provided by way of example, for the purpose of providing a more comprehensive understanding of technology. The disclosed method is not limited to the operation and logic flow presented herein. Optional embodiments are expected, wherein the order of various operations is changed and the sub-operation described as a part of a larger operation is performed independently.

[0157] In addition, although the present application is described in the context of functional modules, it should be understood that, unless otherwise specified, one or more of the functions and / or features can be integrated into a single physical device and / or software module, or one or more functions and / or features can be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the present application. More specifically, in view of the properties, functions, and internal relationships of the various functional modules in the device disclosed herein, the actual implementation of the module will be understood within the conventional techniques of the engineer. Therefore, those skilled in the art can implement the present application set forth in the claims without excessive experimentation using ordinary techniques. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present application, which is determined by the full scope of the attached claims and their equivalents.

[0158] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several programs to enable a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.

[0159] The logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable programs for implementing logical functions, and may be embodied in any computer-readable medium for use by a program execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch and execute a program from a program execution system, device or apparatus), or in conjunction with such program execution system, device or apparatus. 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 a program execution system, device or apparatus, or in conjunction with such program execution system, device or apparatus.

[0160] 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.

[0161] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable program 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 their combination: 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.

[0162] In the above description of this specification, the description with reference to the terms "one embodiment / example", "another embodiment / example" or "certain embodiments / examples" etc. 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 application. 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.

[0163] Although the embodiments of the present application have been shown and described, those skilled in the art will appreciate that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the claims and their equivalents.

[0164] The above is a specific description of the preferred implementation of the present application, but the present application is not limited to the described embodiments. Technical personnel familiar with the field may make various equivalent modifications or substitutions without violating the spirit of the present application. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present application.

Claims

1. A method for locating a fault in a vehicle system, characterized in that: The following steps are involved: Performing a real vehicle test on the vehicle's on-board system to obtain an execution stack of each scheduling link of the on-board system; wherein different scheduling links are links connecting different architecture layers of the on-board system, and the execution stack of the scheduling link is used to store multiple function functions and multiple variable values ​​of the scheduling link during the real vehicle test; Performing an abnormality detection on the vehicle system to obtain an abnormality detection result, wherein the abnormality detection result is used to indicate whether the vehicle system has an abnormality during the actual vehicle test; If the abnormality detection result is that the vehicle system has an abnormality during the actual vehicle test, the abnormal function and the abnormal variable value in the vehicle system are determined according to the execution stack of each scheduling link.

2. The vehicle system fault location method according to claim 1, characterized in that: The actual vehicle test is performed on the vehicle system to obtain the execution stack of each scheduling link of the vehicle system, including: Loading a preset vehicle computer software program into the vehicle computer system; Conducting a real vehicle test on the vehicle system loaded with the vehicle software program; For each of the scheduling links in the vehicle system, an execution stack of the scheduling link is obtained according to a plurality of functional functions and a plurality of variable values ​​of the scheduling link during the actual vehicle test.

3. The vehicle system fault location method according to claim 2, characterized in that: The step of obtaining the execution stack of the scheduling link according to the multiple functional functions and multiple variable values ​​of the scheduling link during the actual vehicle test includes: Pushing a plurality of function functions of the scheduling link into a first sub-stack associated with the scheduling link; Pushing a plurality of variable values ​​of the scheduling link into a second sub-stack associated with the scheduling link; An execution stack of the scheduling link is obtained according to the first sub-stack and the second sub-stack.

4. The vehicle system fault location method according to claim 3, characterized in that: The obtaining, according to the first sub-stack and the second sub-stack, an execution stack of the scheduling link includes: For each of the function functions of the first sub-stack, according to the sub-stack mapping data, at least one variable value corresponding to the function function in the second sub-stack is determined as the target variable value of the function function, and according to the arrangement position of the function function in the first sub-stack and the arrangement position of each of the target variable values ​​in the second sub-stack, a mapping identifier of the function function relative to each of the target variable values ​​is obtained as an element of the mapping set of the function function; wherein the sub-stack mapping data includes a plurality of preset function functions and at least one variable value corresponding to each of the preset function functions; Modifying the first sub-stack by using the mapping set of each of the functional functions of the first sub-stack to obtain a modified first sub-stack; An execution stack of the scheduling link is constructed according to the second sub-stack and the modified first sub-stack.

5. The vehicle system fault location method according to claim 1, characterized in that: The performing abnormality detection on the vehicle system to obtain an abnormality detection result includes: Obtaining real vehicle test log data of the vehicle system; According to the actual vehicle test log data, performing anomaly detection on each of the scheduling links; If an abnormality is detected in at least one of the scheduling links, it is determined that the abnormality detection result is that an abnormality exists in the vehicle system during the actual vehicle test.

6. The vehicle system fault location method according to claim 1, characterized in that: The determining, according to the execution stack of each of the scheduling links, the abnormal function and the abnormal variable value in the vehicle system includes: Acquire the scheduling link with the abnormality as the abnormal link; Popping the first substack in the execution stack of the abnormal link to obtain multiple functional functions of the abnormal link; According to the multiple preset functions of the abnormal link, at least one functional function with the abnormality is determined from the multiple functional functions of the abnormal link.

7. The vehicle system fault location method according to claim 6, characterized in that: The determining, according to the execution stack of each of the scheduling links, the abnormal function and the abnormal variable value in the vehicle system further includes: Popping the second substack in the execution stack of the abnormal link to obtain multiple variable values ​​of the abnormal link; For each of the abnormal function functions of the abnormal link, according to the mapping set of the abnormal function functions, among the multiple variable values ​​of the abnormal link, at least one variable value corresponding to the abnormal function is determined as a candidate variable value, and according to the multiple preset variable values ​​of the abnormal function, at least one abnormal variable value is determined among the multiple candidate variable values.

8. The vehicle system fault location method according to any one of claims 1 to 7, characterized in that: The vehicle system has at least one of the following scheduling links: A first link, used to represent a link from the framework layer of the vehicle system to the system layer of the vehicle system; A second link, used to represent a link from the system layer to the framework layer; A third link, used to represent a link from the framework layer to the application layer of the vehicle system; a fourth link, used to characterize a link from the application layer to the framework layer; The framework layer is configured with a plurality of service classes, each of which corresponds to at least one vehicle function of the vehicle system; the system layer is used to encapsulate the bus signal of each service class into a corresponding service interface and return it to the framework layer; the framework layer is used to provide the service interface of each service class to the application layer; The application layer is used to call the service class corresponding to the triggered vehicle function through the service interface of the service class corresponding to the triggered vehicle function when the vehicle function of the vehicle system is triggered; the framework layer is used to execute the service class corresponding to the triggered vehicle function.

9. A vehicle system fault location device, characterized in that: include: A first processing module is used to perform a real vehicle test on the vehicle system to obtain an execution stack of each scheduling link of the vehicle system; wherein different scheduling links are links connecting different architecture layers of the vehicle system, and the execution stack of the scheduling link is used to store multiple function functions and multiple variable values ​​of the scheduling link during the real vehicle test; A second processing module is used to perform an abnormality detection on the vehicle system to obtain an abnormality detection result, wherein the abnormality detection result is used to indicate whether the vehicle system has an abnormality during the actual vehicle test; The third processing module is used to determine the abnormal function and abnormal variable value in the vehicle system according to the execution stack of each scheduling link if the abnormality detection result is that the vehicle system is abnormal during the actual vehicle test.

10. A vehicle, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the vehicle system fault locating method as described in any one of claims 1-8.

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