Vehicle diagnosis method and device, electronic equipment and storage medium

Abstract

This invention discloses a vehicle diagnostic method, apparatus, electronic device, and storage medium. The method includes: first, acquiring a diagnostic command for a target vehicle; then, based on the diagnostic command, determining n electronic control units (ECUs) in the target vehicle that require fault diagnosis; next, determining the communication interaction mode between the diagnostic device and each of the n ECUs, obtaining n communication interaction modes; then, acquiring the data to be diagnosed corresponding to each of the n ECUs based on the n communication interaction modes, obtaining n sets of data to be diagnosed; and finally, performing fault diagnosis operations on the n ECUs based on the n sets of data to be diagnosed, obtaining the target fault diagnosis result. The implementation method of this application improves the vehicle diagnostic efficiency.

Description

Technical Field

[0001] This invention relates to the field of vehicle diagnostic technology, and in particular to a vehicle diagnostic method, apparatus, electronic device, and storage medium. Background Technology

[0002] Against the backdrop of the automotive industry's rapid development towards intelligence and connectivity, vehicle electronic control systems are becoming increasingly complex. Numerous electronic control units (ECUs) are widely used in key areas such as engine control, chassis adjustment, body electronics, and autonomous driving assistance. These ECUs interact and collaborate through different onboard bus architectures to ensure stable vehicle operation and functional fulfillment. Traditional vehicle diagnostic methods typically employ a single communication interaction method, which suffers from low diagnostic data acquisition rates, leading to inefficient vehicle diagnostics. Therefore, improving vehicle diagnostic efficiency is a pressing issue that needs to be addressed. Summary of the Invention

[0003] This application provides a vehicle diagnostic method, apparatus, electronic device, and storage medium, which improves the diagnostic efficiency of vehicles.

[0004] In a first aspect, embodiments of this application provide a vehicle diagnostic method, including: Obtain diagnostic instructions for the target vehicle; Based on the diagnostic instructions, n electronic control units in the target vehicle that require fault diagnosis are identified; n is a positive integer. Determine the communication interaction method between the diagnostic device and each of the n electronic control units to obtain n communication interaction methods; Based on the n communication interaction methods, obtain the diagnostic data corresponding to each of the n electronic control units, and obtain n sets of diagnostic data; Based on the n sets of data to be diagnosed, fault diagnosis operations are performed on the n electronic control units to obtain the target fault diagnosis result.

[0005] Secondly, embodiments of this application provide a vehicle diagnostic device, the device comprising: an acquisition unit and a processing unit; The acquisition unit is used to acquire diagnostic instructions for the target vehicle; The processing unit is used to determine, based on the diagnostic instructions, n electronic control units in the target vehicle that require fault diagnosis; n is a positive integer; Determine the communication interaction method between the diagnostic device and each of the n electronic control units to obtain n communication interaction methods; Based on the n communication interaction methods, obtain the diagnostic data corresponding to each of the n electronic control units, and obtain n sets of diagnostic data; Based on the n sets of data to be diagnosed, fault diagnosis operations are performed on the n electronic control units to obtain the target fault diagnosis result.

[0006] Thirdly, embodiments of the present invention provide an electronic device, including: a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor to cause the electronic device to perform the method as described in the first aspect.

[0007] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program that is executed by a processor to implement the method as described in the first aspect.

[0008] Fifthly, embodiments of the present invention provide a computer program product including a non-transitory computer-readable storage medium storing a computer program, such that a computer performs the method as described in the first aspect.

[0009] Implementing the embodiments of the present invention has the following beneficial effects: As can be seen, the vehicle diagnostic method described in this embodiment of the invention first obtains a diagnostic command for the target vehicle, then determines n electronic control units (ECUs) in the target vehicle that require fault diagnosis based on the diagnostic command, next determines the communication interaction method between the diagnostic device and each of the n ECUs, obtaining n communication interaction methods, then obtains the data to be diagnosed for each of the n ECUs based on the n communication interaction methods, obtaining n sets of data to be diagnosed, and finally performs fault diagnosis operations on the n ECUs based on the n sets of data to be diagnosed, obtaining the target fault diagnosis result. Using the embodiment of this application improves the vehicle diagnostic efficiency. Attached Figure Description

[0010] To more clearly illustrate the technical solutions in the embodiments of this application or the background art, the accompanying drawings used in the embodiments of this application or the background art will be described below.

[0011] Figure 1 This is a schematic diagram of the structure of a vehicle diagnostic system provided in an embodiment of this application; Figure 2 This is a flowchart of a vehicle diagnostic method provided in an embodiment of this application; Figure 3 This is a flowchart illustrating how to determine n communication interaction methods according to an embodiment of this application; Figure 4 This is a flowchart of an embodiment of the present application for determining the diagnostic complexity value corresponding to the first electronic control unit; Figure 5 This is a flowchart of a method for determining the result of a target fault diagnosis, provided in an embodiment of this application; Figure 6 This is a flowchart provided in an embodiment of the present application for determining the fault severity value corresponding to the second electronic control unit; Figure 7 This is a schematic diagram of the structure of a vehicle diagnostic device provided in an embodiment of this application; Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0012] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present application.

[0013] The terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0014] In this document, the term "implementation" means that a specific feature, structure, or characteristic described in connection with an implementation may be included in at least one implementation of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same implementation, nor is it a separate or alternative implementation mutually exclusive with other implementations. It will be explicitly and implicitly understood by those skilled in the art that the implementations described herein can be combined with other implementations.

[0015] Please see Figure 1 , Figure 1This is a schematic diagram of a vehicle diagnostic system provided in an embodiment of this application. The vehicle diagnostic system 10 includes a diagnostic device 101 and a target vehicle 102. After establishing a communication connection with the target vehicle 102, the diagnostic device 101 performs fault diagnosis operations on the target vehicle 102 to obtain the fault diagnosis results of the target vehicle 102.

[0016] In this embodiment, the diagnostic device 101 acquires a diagnostic command for the target vehicle 102, then determines n electronic control units (ECUs) in the target vehicle 102 that require fault diagnosis based on the diagnostic command, then determines the communication interaction method between the diagnostic device 101 and each of the n ECUs, obtaining n communication interaction methods, then acquires the data to be diagnosed for each of the n ECUs based on the n communication interaction methods, obtaining n sets of data to be diagnosed, and finally performs fault diagnosis operations on the n ECUs based on the n sets of data to be diagnosed, obtaining the target fault diagnosis result.

[0017] As can be seen, by establishing a communication connection between the diagnostic equipment and the target vehicle, diagnostic commands are first obtained, and then the n electronic control units to be diagnosed are determined accordingly. Next, a corresponding communication interaction method is matched for each electronic control unit and the data to be diagnosed is collected. Finally, the fault diagnosis is completed based on the collected data. The advantage of this process is that it can achieve precise definition of the diagnostic scope, avoid indiscriminate diagnosis of all electronic control units in the vehicle, and greatly improve diagnostic efficiency. At the same time, the targeted communication interaction method can ensure the stability and accuracy of data collection, provide reliable data support for subsequent fault diagnosis, effectively improve the accuracy of fault diagnosis, reduce the occurrence of misdiagnosis and missed diagnosis, and thus improve the efficiency of vehicle fault diagnosis.

[0018] Please see Figure 2 , Figure 2 This is a flowchart of a vehicle diagnostic method provided in an embodiment of this application, including but not limited to the following steps: S201: Obtain diagnostic instructions for the target vehicle.

[0019] In this embodiment, the diagnostic command for the target vehicle is the core instruction information that triggers the vehicle's intelligent diagnostic process. The diagnostic command for the target vehicle can be generated by various entities or scenarios. Specific sources include diagnostic requests for specific fault phenomena input by the user through the diagnostic device's human-machine interface, periodic diagnostic or fault warning diagnostic commands automatically triggered by the vehicle's onboard terminal based on a preset diagnostic cycle or abnormal operating conditions, and targeted diagnostic task commands issued by the cloud-based diagnostic platform based on remote vehicle monitoring data. This command must clearly define the unique identifier of the diagnostic object, i.e., the target vehicle, and may include auxiliary parameters such as diagnostic scope, diagnostic priority, and diagnostic time limit. The diagnostic scope defines the systems or components that need to be investigated, the diagnostic priority distinguishes the order of fault diagnosis, and the diagnostic time limit constrains the completion time of the diagnostic process. This information collectively provides a basis for subsequently determining the diagnostic electronic control unit that needs to be diagnosed and selecting the communication interaction method, ensuring that the diagnostic process can be carried out accurately and efficiently.

[0020] S202: Based on the diagnostic instructions, determine the n electronic control units in the target vehicle that require fault diagnosis.

[0021] In this embodiment, the acquired diagnostic command is first parsed in a structured manner to extract the core diagnostic requirement information contained in the command. The core diagnostic requirement information may include key content such as the description of the fault phenomenon, the scope of the vehicle system to be investigated, and the source of the fault alarm signal. Then, the electronic control unit (ECU) topology database of the target vehicle is retrieved. The ECU topology database stores the model, installation location, functional attributes, association with various vehicle systems, and signal interaction logic of all ECUs in the vehicle. Next, the parsed diagnostic requirements are matched with the ECU information in the database to filter out ECUs directly related to the diagnostic requirements. For example, if the diagnostic command points to a brake system fault, the brake control unit, the control module corresponding to the wheel speed sensor, the electronic parking control unit, and other related ECUs are matched and filtered. If the command is for periodic vehicle diagnostics, the engine control unit, transmission control unit, body control unit, and other core ECUs are filtered. Finally, the filtered ECUs are counted and their specific set is determined to obtain n ECUs. The specific number of ECUs depends on the scope of the diagnostic command and the ECU configuration of the target vehicle. Determining the n ECUs in the target vehicle that need to be diagnosed based on the diagnostic command ensures that subsequent diagnostic operations focus on key target modules, improving diagnostic efficiency and accuracy.

[0022] S203: Determine the communication interaction mode between the diagnostic device and each of the n electronic control units to obtain n communication interaction modes.

[0023] In this embodiment, firstly, the diagnostic complexity value is determined for each of the n electronic control units to be diagnosed, forming a set of n diagnostic complexity values. Then, these n diagnostic complexity values ​​are compared with a preset diagnostic complexity value to identify k diagnostic complexity values ​​greater than the preset value and nk diagnostic complexity values ​​less than or equal to the preset value, where k is an integer less than or equal to n. Subsequently, corresponding communication interaction methods are matched for the electronic control units corresponding to these two types of diagnostic complexity values. For the k electronic control units whose diagnostic complexity values ​​exceed the preset value, their communication interaction method with the diagnostic equipment is determined to be a service-based vehicle bus interaction method. The service-based vehicle bus interaction method uses services as the interaction carrier, and the electronic control unit realizes data interaction by sending service requests and responses. For the nk electronic control units whose diagnostic complexity values ​​do not exceed the preset value, their communication interaction method with the diagnostic equipment is determined to be a signal-based vehicle bus interaction method. The signal-based vehicle bus interaction method is a vehicle bus communication method in which the electronic control unit encapsulates operating data into signals according to preset rules and realizes data interaction by periodically or event-triggeredly sending signals through the bus. By determining the diagnostic complexity value of the electronic control unit, the communication interaction method between the diagnostic device and each of the n electronic control units is finally determined, resulting in n communication interaction methods.

[0024] S204: Based on the n communication interaction methods, obtain the diagnostic data corresponding to each of the n electronic control units, and obtain n sets of diagnostic data.

[0025] In this embodiment, the diagnostic device first retrieves a list of n predetermined communication interaction methods. According to the communication method matched to each electronic control unit (ECU) in the list, a compliant communication link is established with the corresponding ECU. For ECUs using a service-based vehicle bus interaction method, the diagnostic device sends a targeted service request command. After the ECU returns response data, the device extracts operating parameters, fault codes, status information, and other content related to fault diagnosis. For ECUs using a signal-based vehicle bus interaction method, the diagnostic device connects to the corresponding vehicle bus and receives encapsulated signals periodically or event-triggered by the ECU according to preset rules. The device then parses the signals to extract valid diagnostic data. During this process, the diagnostic device establishes an independent data set for the collected data of each ECU, ensuring that each data set is associated with its corresponding ECU. Finally, the collected data from all ECUs are integrated to form n sets of diagnostic data containing n independent data sets.

[0026] S205: Perform fault diagnosis operations on the n electronic control units based on the n sets of data to be diagnosed, and obtain the target fault diagnosis result.

[0027] In this embodiment, the historical diagnostic results of the n electronic control units within a preset historical time period are first retrieved and integrated to form n sets of historical diagnostic results. Then, based on these n sets of historical diagnostic results, the key indicators such as the historical fault occurrence frequency, fault severity, and fault recurrence rate of each electronic control unit are analyzed to determine the diagnostic priority of each electronic control unit, resulting in n priorities. The target priority order is then determined according to the priority order. Subsequently, the system calls a preset fault diagnosis algorithm model to match and analyze the n sets of data to be diagnosed with the standard operating data thresholds and fault feature databases of the corresponding electronic control units. At the same time, fault diagnosis operations are performed on the electronic control units with higher priority according to the target priority order. The diagnosis of all electronic control units is completed in sequence. Finally, the diagnostic conclusions of all electronic control units are integrated to clarify the fault status, fault type, fault location, and fault impact range of each electronic control unit, forming a comprehensive and accurate target fault diagnosis result.

[0028] It should be explained that an electronic control unit (ECU) fault feature matching library can be constructed first. This library contains typical data feature thresholds, data fluctuation patterns, and fault correlation maps of different types of ECUs under normal operation and various fault conditions. Then, n sets of data to be diagnosed are input into the fault feature matching library. By comparing the data, the deviation values ​​between the data to be diagnosed and the standard features are extracted. At the same time, the signal interaction logic and collaborative working mechanism between various ECUs are combined to analyze whether there are data anomalies in other related ECUs caused by the fault of one ECU. Then, a preset fault diagnosis algorithm is used to quantitatively analyze the deviation values ​​and related abnormal data to determine the fault probability and fault type of each ECU. Finally, the diagnostic analysis results of all ECUs are integrated to form a target fault diagnosis result covering the fault location, fault level, fault cause, and scope of impact.

[0029] As can be seen, the process of first obtaining diagnostic instructions for the target vehicle, then identifying the n electronic control units (ECUs) to be diagnosed, matching a corresponding communication interaction method for each ECU, collecting n sets of diagnostic data based on the matching method, and finally performing fault diagnosis operations based on the collected data to obtain the target fault diagnosis result, can achieve precise delineation of the diagnostic scope, avoid indiscriminate diagnosis of all ECUs of the vehicle, reduce redundant diagnostic steps, and improve diagnostic efficiency. At the same time, the targeted communication interaction method can ensure the stability and accuracy of diagnostic data collection, providing reliable data support for subsequent fault analysis, effectively improving the accuracy of fault diagnosis and reducing the probability of misdiagnosis and missed diagnosis. Please see Figure 3 , Figure 3 This is a flowchart of determining n communication interaction methods according to an embodiment of this application, including but not limited to the following steps: S301: Determine the diagnostic complexity value corresponding to each of the n electronic control units to obtain n diagnostic complexity values.

[0030] In this embodiment, for any one of the n electronic control units, the number of data bytes corresponding to the electronic control unit and the number of communication interaction steps required to complete the fault diagnosis operation of the electronic control unit are first obtained. Then, based on a preset quantization mapping rule, the diagnostic complexity value corresponding to the number of data bytes is determined to obtain a first diagnostic complexity value. The diagnostic complexity value corresponding to the number of communication interaction steps is determined to obtain a second diagnostic complexity value. Finally, the first diagnostic complexity value and the second diagnostic complexity value are integrated through a preset weighted calculation model to calculate the diagnostic complexity value corresponding to the electronic control unit. The above process is performed on each of the n electronic control units one by one to finally obtain n diagnostic complexity values ​​corresponding to the n electronic control units.

[0031] S302: Determine k diagnostic complexity values ​​that are greater than the preset diagnostic complexity value and nk diagnostic complexity values ​​that are less than or equal to the preset diagnostic complexity value from among the n diagnostic complexity values.

[0032] In this embodiment, k is an integer less than or equal to n. A reasonable preset diagnostic complexity value is set as a classification threshold based on factors such as the communication processing capability of the vehicle diagnostic system, the diagnostic difficulty range adapted to different communication interaction methods, and the statistical analysis results of historical diagnostic data. Then, each of the n diagnostic complexity values ​​is compared with this preset threshold. Based on the comparison results, these n diagnostic complexity values ​​are divided into two categories: one category contains diagnostic complexity values ​​greater than the preset diagnostic complexity value, denoted as k; the other category contains diagnostic complexity values ​​less than or equal to the preset diagnostic complexity value, denoted as nk. This classification operation enables a clear grading of the diagnostic difficulty of the n electronic control units.

[0033] S303: Determine that the communication interaction mode of the k electronic control units corresponding to the k diagnostic complexity values ​​is a service-based vehicle bus interaction mode.

[0034] In this embodiment, the service-based vehicle bus interaction method is a vehicle bus communication method in which the electronic control unit uses services as the interaction carrier and achieves data interaction by sending service requests and responses.

[0035] For k electronic control units with diagnostic complexity values ​​exceeding a preset threshold, considering their characteristics of large numbers of diagnostic data bytes, cumbersome communication interaction steps, and complex diagnostic logic, a service-based vehicle bus interaction method adapted to highly complex diagnostic scenarios is matched. This method uses services as the data interaction carrier, and the diagnostic equipment and electronic control units interact by sending service request messages and receiving service response messages. This can meet the requirements of these electronic control units for the integrity of diagnostic data and the accuracy of interaction commands, ensuring that the diagnostic equipment can efficiently obtain comprehensive diagnostic data of such electronic control units.

[0036] S304: Determine that the communication interaction mode of the nk electronic control units corresponding to the nk diagnostic complexity values ​​is a signal-based vehicle bus interaction mode.

[0037] In this embodiment, the signal-based vehicle bus interaction method is a vehicle bus communication method in which the electronic control unit encapsulates the operating data into signals according to preset rules, and sends the signals periodically or event-triggered through the bus to realize data interaction.

[0038] For nk electronic control units with diagnostic complexity values ​​less than or equal to a preset threshold, based on their characteristics of small diagnostic data bytes, simple communication interaction steps, and data transmission requirements that tend to be periodic or event-triggered, a signal-based vehicle bus interaction method adapted to low-complexity diagnostic scenarios is matched. In this method, the electronic control unit encapsulates its own operating data into standardized signals according to preset rules and actively sends the signals through the vehicle bus in the form of periodic broadcasts or event triggers. The diagnostic equipment does not need to send complex service requests; it only needs to connect to the corresponding bus to directly receive and parse the signals to obtain diagnostic data. This matching method can simplify the communication process, improve the diagnostic data acquisition efficiency of low-complexity electronic control units, and reduce the communication load between the diagnostic equipment and the vehicle bus.

[0039] As can be seen, by first determining the diagnostic complexity value corresponding to each of the n electronic control units (ECUs), and then comparing these values ​​with the preset diagnostic complexity value, k ECUs with a value greater than the threshold and nk ECUs with a value less than or equal to the threshold are identified. Subsequently, a service-based vehicle bus interaction mode is matched for the k ECUs with high diagnostic complexity, and a signal-based vehicle bus interaction mode is matched for the nk ECUs with low diagnostic complexity. This enables precise adaptation of the communication interaction mode to the diagnostic difficulty of the ECUs. For high-complexity ECUs with a large number of diagnostic data bytes and cumbersome interaction steps, the service-based interaction mode can ensure the integrity and accuracy of data acquisition through the service request and response mechanism. For low-complexity ECUs with simple diagnostic data structure and single transmission requirements, the signal-based interaction mode can simplify the communication process and improve data acquisition efficiency by using a periodic or event-triggered signal sending mechanism. At the same time, this differentiated communication mode matching strategy can effectively reduce the overall communication load between the diagnostic equipment and the vehicle bus, avoid resource waste, and thus improve the efficiency and reliability of the entire vehicle fault diagnosis process.

[0040] Please see Figure 4 , Figure 4 This application provides a flowchart for determining the diagnostic complexity value corresponding to the first electronic control unit, including but not limited to the following steps: S401: Obtain the number of data bytes corresponding to the first electronic control unit and the number of communication interaction steps required to complete the fault diagnosis operation of the first electronic control unit.

[0041] In this embodiment, the first electronic control unit is any one of the n electronic control units.

[0042] The number of data bytes corresponding to the first electronic control unit (ECU) refers to the total byte capacity of all valid data related to fault diagnosis stored in the ECU. This data covers the core content used for diagnostic analysis, such as the ECU's real-time operating parameters, historical fault records, status feedback information, and software and hardware version information. The number of bytes directly reflects the scale of the diagnostic data. The number of communication interaction steps required to complete the fault diagnosis operation of the first ECU is the total number of communication command interaction links that the diagnostic equipment needs to execute from the establishment of a communication connection with the first ECU to the successful acquisition of all data to be diagnosed and the completion of data validity verification. Specifically, it may include a series of orderly interaction steps such as the diagnostic equipment sending a communication handshake command, the ECU returning a response command, the diagnostic equipment sending a data acquisition request, the ECU transmitting diagnostic data, the diagnostic equipment sending a data verification command, and the ECU returning the verification result. The number of communication interaction steps required to complete the fault diagnosis operation of the first ECU directly reflects the complexity of the target vehicle's diagnostic communication process.

[0043] S402: Determine the diagnostic complexity value corresponding to the number of data bytes to obtain the first diagnostic complexity value.

[0044] In this embodiment, it can be a first mapping relationship between a preset number of data bytes and a diagnostic complexity value. Based on this first mapping relationship, the diagnostic complexity value corresponding to the number of data bytes can be determined, and the first diagnostic complexity value can be obtained.

[0045] S403: Determine the diagnostic complexity value corresponding to the number of communication interaction steps to obtain the second diagnostic complexity value.

[0046] In this embodiment, it can be a second mapping relationship between a preset number of communication interaction steps and a diagnostic complexity value. Based on this second mapping relationship, the diagnostic complexity value corresponding to the number of communication interaction steps can be determined, and a second diagnostic complexity value can be obtained.

[0047] S404: Determine the diagnostic complexity value corresponding to the first electronic control unit based on the first diagnostic complexity value and the second diagnostic complexity value.

[0048] In this embodiment, a first weight corresponding to the first diagnostic complexity value and a second weight corresponding to the second diagnostic complexity value can be set in advance according to the influence weight of the number of data bytes and the number of communication interaction steps on the diagnostic complexity. The sum of the two weights is 1. Then, the first diagnostic complexity value is multiplied by the first weight to obtain the first weighted value, and the second diagnostic complexity value is multiplied by the second weight to obtain the second weighted value. Finally, the first weighted value and the second weighted value are summed. The result is the diagnostic complexity value corresponding to the first electronic control unit that can comprehensively reflect the data volume and the complexity of the process.

[0049] For example, a first weight corresponding to the first diagnostic complexity value and a second weight corresponding to the second diagnostic complexity value are determined, and the sum of the first weight and the second weight is 1. Specifically, the influence of the number of data bytes and the number of communication interaction steps on the diagnostic complexity of the electronic control unit is first analyzed. If the size of the data bytes has a more significant impact on the diagnostic difficulty in historical diagnostics, for example, large data transmission is prone to packet loss, verification failure, etc., which directly leads to the diagnostic process being stuck or failing, then a higher first weight is assigned to the first diagnostic complexity value. If the number of communication interaction steps has a more critical impact on diagnostic efficiency, for example, too many steps will significantly increase communication time and the probability of command interaction errors, then a higher second weight is assigned to the second diagnostic complexity value. Subsequently, the weight is fine-tuned by referring to the weight setting standards of similar diagnostic systems in the industry, combined with factors such as the type of electronic control unit of the target vehicle and the communication processing capability of the diagnostic equipment. Finally, the sum of the first weight and the second weight is calculated to ensure that it equals 1, thereby achieving a reasonable weight ratio of the two indicators in the diagnostic complexity value calculation, so as to ensure that the final diagnostic complexity value can truly reflect the diagnostic difficulty of the electronic control unit.

[0050] For example, a reference diagnostic complexity value is determined based on the first diagnostic complexity value, the first weight, the second diagnostic complexity value, and the second weight. Specifically, the reference diagnostic complexity value is calculated according to the following formula: Reference diagnostic complexity value = First diagnostic complexity value × First weight + Second diagnostic complexity value × Second weight; According to the above formula, a reference diagnostic complexity value can be determined based on the first diagnostic complexity value, the first weight, the second diagnostic complexity value, and the second weight.

[0051] For example, the failure function impact coefficient corresponding to the first electronic control unit is obtained. The failure function impact coefficient is the degree of impact on the driving safety of the target vehicle when the first electronic control unit malfunctions. Specifically, the failure function impact coefficient corresponding to the first electronic control unit characterizes the degree of impact of the failure of the first electronic control unit on the driving safety, overall vehicle stability, and core function realization of the target vehicle. In the process of determining the diagnostic complexity value, the failure function impact coefficient corresponding to the first electronic control unit is used as a key correction basis and integrated into the calculation system based on the first and second diagnostic complexity values. If the first electronic control unit belongs to core safety-related modules such as the vehicle power system, braking system, and steering system, the failure function impact coefficient corresponding to the first electronic control unit is higher, which will correspondingly increase the diagnostic complexity value of the electronic control unit, thereby highlighting the importance and urgency of the diagnostic work of electronic control units of the same type as the first electronic control unit. If the first electronic control unit belongs to non-core comfort modules such as window control and interior lighting, the failure function impact coefficient corresponding to the first electronic control unit is lower, and the improvement effect on the diagnostic complexity value is relatively limited. Therefore, it is necessary to obtain the failure function impact coefficient corresponding to the first electronic control unit.

[0052] For example, the adjustment parameter corresponding to the failure function impact coefficient is determined. Specifically, it can be a preset mapping relationship between the failure function impact coefficient and the adjustment parameter. Based on this mapping relationship, the adjustment parameter corresponding to the failure function impact coefficient can be determined.

[0053] For example, the reference diagnostic complexity value is adjusted based on the adjustment parameters to obtain the diagnostic complexity value corresponding to the first electronic control unit. Specifically, the diagnostic complexity value corresponding to the first electronic control unit is calculated according to the following formula: The diagnostic complexity value corresponding to the first electronic control unit = reference diagnostic complexity value × (1 + adjustment parameter). Based on the above formula, the reference diagnostic complexity value can be adjusted according to the adjustment parameters to obtain the diagnostic complexity value corresponding to the first electronic control unit.

[0054] It should be explained that, since the first electronic control unit is any one of the n electronic control units, the diagnostic complexity value corresponding to each of the n electronic control units can be determined according to the method for determining the diagnostic complexity value corresponding to the first electronic control unit, thus obtaining n diagnostic complexity values.

[0055] Please see Figure 5 , Figure 5This is a flowchart of a method for determining a target fault diagnosis result provided in an embodiment of this application, including but not limited to the following steps: S501: Obtain the historical diagnostic results of each of the n electronic control units within a preset historical time period to obtain n sets of historical diagnostic results.

[0056] In this embodiment, the historical diagnostic results of each of the n electronic control units within a preset historical time period refer to the collection of all historical records formed by fault diagnosis for each electronic control unit within a predefined time range. These records cover the time node of each diagnosis of the electronic control unit within that time period, the reason for triggering the diagnosis (e.g., proactive periodic diagnosis, diagnosis triggered by abnormal operating conditions), the characteristics of the operating data collected during the diagnosis process, the detected fault type, fault code, specific operating conditions of the fault occurrence, the severity level of the fault (e.g., minor fault, moderate fault, severe fault), the frequency of fault recurrence, and the corresponding maintenance measures, the results of the re-inspection after maintenance, and whether the fault has been completely resolved. The n sets of historical diagnostic results can reflect the fault occurrence pattern, fault evolution trend, and the effectiveness of past diagnosis and maintenance of the electronic control unit.

[0057] S502: Based on the n sets of historical diagnostic results, determine the priority of each of the n electronic control units to obtain n priorities.

[0058] In this embodiment, firstly, for any one of the n electronic control units, the corresponding historical diagnostic results from n sets of historical diagnostic results are retrieved. Then, based on the historical diagnostic results, the vehicle downtime loss value and vehicle repair time corresponding to the electronic control unit when a fault occurs within a preset historical time period are analyzed and determined. Subsequently, a quantitative mapping relationship between the vehicle downtime loss value, vehicle repair time and fault severity value is established. Based on the mapping relationship, a first fault severity value corresponding to the vehicle downtime loss value and a second fault severity value corresponding to the vehicle repair time are determined. Then, the first fault severity value and the second fault severity value are integrated through a preset weighted fusion algorithm to obtain the fault severity value corresponding to the electronic control unit. Following this process, n fault severity values ​​corresponding to each of the n electronic control units are calculated sequentially. Finally, following the rule that the larger the fault severity value corresponding to the electronic control unit, the higher the priority, a corresponding diagnostic priority is matched for each electronic control unit, ultimately obtaining n priorities corresponding to the n electronic control units one-to-one.

[0059] For example, based on the n sets of historical diagnostic results, the severity value of each of the n electronic control units (ECUs) when it malfunctions within the preset historical time period is determined, resulting in n severity values. Specifically, for any one of the n ECUs, the corresponding historical diagnostic result from the n sets of historical diagnostic results is first retrieved, and then key data is extracted from the historical diagnostic result to determine the vehicle downtime loss value corresponding to the ECU malfunction, i.e., the quantitative value of operational losses and time losses caused by the vehicle's inability to drive normally due to the malfunction, and the vehicle repair time, i.e., the time required for professional repair personnel to complete the fault detection, disassembly, and repair. The total working time required for the entire process, including inspection and re-inspection, is calculated. Then, quantitative mapping rules are established between vehicle downtime loss value, vehicle repair time, and fault severity value. Based on these rules, the vehicle downtime loss value is converted into a corresponding first fault severity value, and the vehicle repair time is converted into a corresponding second fault severity value. Then, the first and second fault severity values ​​are integrated through a preset weighted calculation model to obtain the fault severity value corresponding to the electronic control unit when it malfunctions within a preset historical time period. Finally, the above process is followed to calculate each of the n electronic control units one by one, and n fault severity values ​​corresponding to each of the n electronic control units are obtained.

[0060] For example, based on the n fault severity values, the priority of each of the n electronic control units is determined, resulting in the n priorities. The higher the fault severity value of an electronic control unit, the higher its priority. Specifically, a correspondence mechanism between fault severity values ​​and diagnostic priorities is pre-established. This mechanism can define different priority levels according to the distribution range of fault severity values. Then, the n fault severity values, which correspond one-to-one with the n electronic control units, are substituted into this mechanism to perform priority matching for each electronic control unit. Electronic control units with fault severity values ​​in the higher range are assigned high priority, those in the middle range are assigned medium priority, and those in the lower range are assigned low priority. If multiple electronic control units have the same fault severity value, the priority can be fine-tuned based on the core functional attributes of the electronic control units. Finally, the n priorities corresponding one-to-one with the n electronic control units are obtained, thereby clarifying the order of subsequent fault diagnosis operations.

[0061] S503: Determine the target priority order based on the n priorities.

[0062] In this embodiment, the n priorities corresponding to the n electronic control units are sorted in descending order of priority value. If multiple electronic control units have the same priority value, they can be further sorted by auxiliary indicators such as the fault recurrence rate of the corresponding electronic control unit and its correlation with the core safety functions of the vehicle. Finally, a target priority order is formed that clarifies the order of diagnosis of all electronic control units to be diagnosed, providing a clear execution order for subsequent fault diagnosis operations.

[0063] S504: Based on the n sets of data to be diagnosed, perform fault diagnosis operations on the n electronic control units according to the target priority order to obtain the target fault diagnosis result.

[0064] In this embodiment, the diagnostic system first retrieves n sets of diagnostic data corresponding to n electronic control units (ECUs). Simultaneously, it retrieves data in a predetermined priority order, strictly adhering to the principle of prioritizing ECUs with higher priority for diagnosis. During diagnosis, the system first selects the diagnostic data corresponding to the highest priority ECU. This data is then compared and analyzed in multiple dimensions with standard data thresholds, typical fault feature maps, and historical fault data models under normal operating conditions for that type of ECU. Parameters deviating from standard thresholds in the diagnostic data are extracted, abnormal patterns in data fluctuations are identified, and it is determined whether these anomalies correspond to specific fault types. Next, the diagnostic system combines the signal interaction logic between the ECU and other vehicle systems to analyze whether abnormal data will trigger a chain reaction in related modules, thereby determining the scope of the fault's impact. After diagnosing the highest priority ECU, the system sequentially performs the same data analysis, anomaly identification, fault matching, and impact scope determination operations on the next lower priority ECUs according to the target priority order. After the diagnostic work for all ECUs is completed, the system integrates the diagnostic conclusions of all ECUs, summarizing the fault status, fault level, fault cause, and corresponding repair suggestions for each unit, ultimately forming a comprehensive, systematic, and accurate target fault diagnosis result.

[0065] As can be seen, by first acquiring n sets of historical diagnostic results for n electronic control units within a preset historical time period, then determining the priority of each electronic control unit based on these historical diagnostic results and forming a target priority order, and finally performing fault diagnosis operations according to this order in conjunction with n sets of data to be diagnosed to obtain the target fault diagnosis result, the advantages of this approach are that it can rely on the reference value of historical fault data to allow the diagnostic work to focus on core electronic control units with high fault severity and high recurrence frequency, avoiding the inefficiency caused by indiscriminate diagnosis. At the same time, the priority-based diagnostic process can quickly locate key fault points, reduce redundant diagnostic steps, improve overall diagnostic efficiency, and more accurately identify abnormal features in the data to be diagnosed by combining historical fault patterns, reducing the probability of false positives and false negatives. In addition, this process can clarify the order of diagnostic work and optimize the allocation of diagnostic resources.

[0066] Please see Figure 6 , Figure 6 This application provides a flowchart for determining the fault severity value corresponding to the second electronic control unit, including but not limited to the following steps: S601: Determine the first historical diagnostic result corresponding to the second electronic control unit.

[0067] In this embodiment, the second electronic control unit is any one of the n electronic control units, and the first historical diagnostic result is the historical diagnostic result corresponding to the second electronic control unit among the n sets of historical diagnostic results.

[0068] The first historical diagnostic result is the historical diagnostic result corresponding to the second electronic control unit among the n sets of historical diagnostic results. It means that among the n sets of historical diagnostic results that have been acquired and correspond one-to-one with the n electronic control units, the set of historical diagnostic records that completely matches any one of the n electronic control units is accurately located and extracted based on the unique identification information of the electronic control unit, such as hardware number, module name, etc. These historical diagnostic records contain all fault diagnosis-related information of the electronic control unit within a preset historical time period, such as fault occurrence time, fault type, fault code, fault handling measures, and re-inspection results. This operation enables the accurate association between historical diagnostic data and target electronic control units, providing data support for the subsequent extraction of key indicators such as vehicle fault downtime loss value and vehicle fault repair time from historical data.

[0069] S602: Based on the first historical diagnostic results, determine the vehicle downtime loss value and vehicle repair time corresponding to the second electronic control unit.

[0070] In this embodiment, regarding the vehicle downtime loss value, the duration of the vehicle's inability to operate normally due to the failure of the second electronic control unit can be calculated based on the first historical diagnostic results. This is combined with the vehicle's usage attributes, such as the average daily revenue of operating vehicles and the backup travel costs of non-operating vehicles, and further supplemented with direct expenses such as towing fees and temporary parking fees incurred during the failure period, to calculate the comprehensive vehicle downtime loss value. Regarding the vehicle repair time, the entire repair record of the second electronic control unit failure can be compiled based on the second historical diagnostic results. This record covers all operational steps from vehicle reception and inspection, fault location, disassembly of faulty components, replacement or repair of damaged parts, to assembly and debugging, functional retesting, and confirmation of fault elimination. The actual working time consumed in each step is accumulated to obtain the vehicle repair time corresponding to the second electronic control unit.

[0071] S603: Determine the severity value of the fault corresponding to the vehicle downtime loss value, and obtain the first fault severity value.

[0072] In this embodiment, it can be a third mapping relationship between a preset vehicle downtime loss value and a fault severity value. Based on this third mapping relationship, the fault severity value corresponding to the vehicle downtime loss value can be determined to obtain a first fault severity value.

[0073] S604: Determine the severity value of the fault corresponding to the vehicle fault repair time, and obtain the second fault severity value.

[0074] In this embodiment, it can be a fourth mapping relationship between a preset vehicle fault repair time and a fault severity value. Based on this fourth mapping relationship, the fault severity value corresponding to the vehicle fault repair time can be determined, and a second fault severity value can be obtained.

[0075] S605: Determine the fault severity value corresponding to the second electronic control unit based on the first fault severity value and the second fault severity value.

[0076] In this embodiment, a third weight corresponding to the first fault severity value and a fourth weight corresponding to the second fault severity value can be determined first. Then, based on the third weight, the fourth weight, the first fault severity value, and the second fault severity value, the fault severity value corresponding to the second electronic control unit can be determined. Specifically, the fault severity value corresponding to the second electronic control unit can be calculated according to the following formula: The severity value of the fault corresponding to the second electronic control unit = the severity value of the first fault × the third weight + the severity value of the second fault × the fourth weight; According to the above formula, the fault severity value corresponding to the second electronic control unit can be determined based on the third weight, the fourth weight, the first fault severity value, and the second fault severity value.

[0077] It should be explained that, since the second electronic control unit is any one of the n electronic control units, the fault severity value corresponding to each of the n electronic control units when a fault occurs within the preset historical time period can be determined according to the method for determining the fault severity value corresponding to the second electronic control unit, thereby obtaining n fault severity values.

[0078] As can be seen, by first determining the historical diagnostic results for any one of the n electronic control units, and then extracting two core quantitative indicators—vehicle downtime loss and vehicle repair time—based on these historical diagnostic results, and then converting these two indicators into corresponding first and second fault severity values, and finally integrating the severity values ​​of the two dimensions to obtain the final fault severity value of the electronic control unit, the severity of the electronic control unit fault can be quantitatively assessed from two key dimensions: economic loss and repair difficulty. This avoids the one-sidedness of assessment caused by a single indicator, and by relying on real data from historical diagnostic results, the objectivity and accuracy of the assessment results are ensured, thereby improving the efficiency of vehicle intelligent diagnosis.

[0079] In summary, implementing the embodiments of the present invention has the following beneficial effects: As can be seen, the vehicle diagnostic method described in this embodiment of the invention first obtains a diagnostic command for the target vehicle, then determines n electronic control units (ECUs) in the target vehicle that require fault diagnosis based on the diagnostic command, next determines the communication interaction method between the diagnostic device and each of the n ECUs, obtaining n communication interaction methods, then obtains the data to be diagnosed for each of the n ECUs based on the n communication interaction methods, obtaining n sets of data to be diagnosed, and finally performs fault diagnosis operations on the n ECUs based on the n sets of data to be diagnosed, obtaining the target fault diagnosis result. Using the embodiment of this application improves the vehicle diagnostic efficiency.

[0080] Please see Figure 7 , Figure 7 This is a schematic diagram of the structure of a vehicle diagnostic device provided in an embodiment of this application. The vehicle diagnostic device 700 includes: an acquisition unit 701 and a processing unit 702. The acquisition unit 701 is used to acquire diagnostic instructions for the target vehicle; The processing unit 702 is used to determine, based on the diagnostic instructions, n electronic control units in the target vehicle that require fault diagnosis; n is a positive integer; Determine the communication interaction method between the diagnostic device and each of the n electronic control units to obtain n communication interaction methods; Based on the n communication interaction methods, obtain the diagnostic data corresponding to each of the n electronic control units, and obtain n sets of diagnostic data; Based on the n sets of data to be diagnosed, fault diagnosis operations are performed on the n electronic control units to obtain the target fault diagnosis result.

[0081] In some possible implementations, in determining the communication interaction mode corresponding to each of the n electronic control units among the diagnostic device and obtaining n communication interaction modes, the processing unit 702 is specifically used for: Determine the diagnostic complexity value corresponding to each of the n electronic control units to obtain n diagnostic complexity values; Determine k diagnostic complexity values ​​that are greater than a preset diagnostic complexity value and nk diagnostic complexity values ​​that are less than or equal to the preset diagnostic complexity value from among the n diagnostic complexity values; k is an integer less than or equal to n; The communication interaction mode of the k electronic control units corresponding to the k diagnostic complexity values ​​is determined to be a service-based vehicle bus interaction mode; the service-based vehicle bus interaction mode is a vehicle bus communication mode in which the electronic control units use services as the interaction carrier and realize data interaction by sending service requests and responses. The communication interaction mode of the nk electronic control units corresponding to the nk diagnostic complexity values ​​is determined to be a signal-based vehicle bus interaction mode; the signal-based vehicle bus interaction mode is a vehicle bus communication mode in which the electronic control unit encapsulates the operating data into signals according to preset rules, and sends the signals periodically or event-triggered through the bus to realize data interaction.

[0082] In some possible implementations, in determining the diagnostic complexity value corresponding to each of the n electronic control units to obtain n diagnostic complexity values, the processing unit 702 is specifically used for: The number of data bytes corresponding to the first electronic control unit and the number of communication interaction steps required to complete the fault diagnosis operation of the first electronic control unit are obtained; the first electronic control unit is any one of the n electronic control units; Determine the diagnostic complexity value corresponding to the number of data bytes to obtain the first diagnostic complexity value; Determine the diagnostic complexity value corresponding to the number of communication interaction steps to obtain the second diagnostic complexity value; The diagnostic complexity value corresponding to the first electronic control unit is determined based on the first diagnostic complexity value and the second diagnostic complexity value.

[0083] In some possible implementations, in determining the diagnostic complexity value corresponding to the first electronic control unit based on the first diagnostic complexity value and the second diagnostic complexity value, the processing unit 702 is specifically configured to: Determine a first weight corresponding to the first diagnostic complexity value and a second weight corresponding to the second diagnostic complexity value; the sum of the first weight and the second weight is 1; A reference diagnostic complexity value is determined based on the first diagnostic complexity value, the first weight, the second diagnostic complexity value, and the second weight; Obtain the fault function failure impact coefficient corresponding to the first electronic control unit; the fault function failure impact coefficient is the degree of impact on the driving safety of the target vehicle when the first electronic control unit malfunctions. Determine the adjustment parameters corresponding to the failure impact coefficient of the aforementioned fault function; The reference diagnostic complexity value is adjusted based on the adjustment parameters to obtain the diagnostic complexity value corresponding to the first electronic control unit.

[0084] In some possible implementations, in order to perform fault diagnosis operations on the n electronic control units based on the n sets of data to be diagnosed and obtain the target fault diagnosis result, the processing unit 702 is specifically used for: Obtain the historical diagnostic results of each of the n electronic control units within a preset historical time period to obtain n sets of historical diagnostic results; Based on the n sets of historical diagnostic results, the priority of each of the n electronic control units is determined, resulting in n priorities. The target priority order is determined based on the n priorities; Based on the n sets of data to be diagnosed, fault diagnosis operations are performed on the n electronic control units in accordance with the target priority order to obtain the target fault diagnosis result.

[0085] In some possible implementations, in determining the priority of each of the n electronic control units based on the n sets of historical diagnostic results, and obtaining n priorities, the processing unit 702 is specifically used for: Based on the n sets of historical diagnostic results, determine the fault severity value corresponding to the fault of each of the n electronic control units when a fault occurs within the preset historical time period, and obtain n fault severity values; The priority of each of the n electronic control units is determined based on the n fault severity values, thus obtaining the n priorities; the higher the fault severity value of the electronic control unit, the higher the priority of the electronic control unit.

[0086] In some possible implementations, in determining the fault severity value corresponding to the fault of each of the n electronic control units within the preset historical time period based on the n sets of historical diagnostic results, and obtaining n fault severity values, the processing unit 702 is specifically used for: Determine the first historical diagnostic result corresponding to the second electronic control unit; the second electronic control unit is any one of the n electronic control units, and the first historical diagnostic result is the historical diagnostic result corresponding to the second electronic control unit in the n sets of historical diagnostic results; Based on the first historical diagnostic results, determine the vehicle downtime loss value and vehicle repair time corresponding to the second electronic control unit; Determine the severity value of the fault corresponding to the vehicle downtime loss value to obtain the first fault severity value; Determine the severity value of the fault corresponding to the vehicle fault repair time to obtain the second fault severity value; The fault severity value corresponding to the second electronic control unit is determined based on the first fault severity value and the second fault severity value.

[0087] Please see Figure 8 , Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. For example... Figure 8 As shown, the electronic device 800 includes a transceiver 801, a processor 802, and a memory 803. These are connected via a bus 804. The memory 803 stores computer programs and data, and the transceiver 801 can transmit data stored in the memory 803 to the processor 802. The program includes instructions for performing the following steps: Obtain diagnostic instructions for the target vehicle; Based on the diagnostic instructions, n electronic control units in the target vehicle that require fault diagnosis are identified; n is a positive integer. Determine the communication interaction method between the diagnostic device and each of the n electronic control units to obtain n communication interaction methods; Based on the n communication interaction methods, obtain the diagnostic data corresponding to each of the n electronic control units, and obtain n sets of diagnostic data; Based on the n sets of data to be diagnosed, fault diagnosis operations are performed on the n electronic control units to obtain the target fault diagnosis result.

[0088] In some possible implementations, the above procedure includes instructions for performing the following steps in determining the communication interaction mode corresponding to each of the n electronic control units among the diagnostic device and obtaining the n communication interaction modes: Determine the diagnostic complexity value corresponding to each of the n electronic control units to obtain n diagnostic complexity values; Determine k diagnostic complexity values ​​that are greater than a preset diagnostic complexity value and nk diagnostic complexity values ​​that are less than or equal to the preset diagnostic complexity value from among the n diagnostic complexity values; k is an integer less than or equal to n; The communication interaction mode of the k electronic control units corresponding to the k diagnostic complexity values ​​is determined to be a service-based vehicle bus interaction mode; the service-based vehicle bus interaction mode is a vehicle bus communication mode in which the electronic control units use services as the interaction carrier and realize data interaction by sending service requests and responses. The communication interaction mode of the nk electronic control units corresponding to the nk diagnostic complexity values ​​is determined to be a signal-based vehicle bus interaction mode; the signal-based vehicle bus interaction mode is a vehicle bus communication mode in which the electronic control unit encapsulates the operating data into signals according to preset rules, and sends the signals periodically or event-triggered through the bus to realize data interaction.

[0089] In some possible implementations, in determining the diagnostic complexity value corresponding to each of the n electronic control units to obtain n diagnostic complexity values, the above procedure includes instructions for performing the following steps: The number of data bytes corresponding to the first electronic control unit and the number of communication interaction steps required to complete the fault diagnosis operation of the first electronic control unit are obtained; the first electronic control unit is any one of the n electronic control units; Determine the diagnostic complexity value corresponding to the number of data bytes to obtain the first diagnostic complexity value; Determine the diagnostic complexity value corresponding to the number of communication interaction steps to obtain the second diagnostic complexity value; The diagnostic complexity value corresponding to the first electronic control unit is determined based on the first diagnostic complexity value and the second diagnostic complexity value.

[0090] In some possible implementations, in determining the diagnostic complexity value corresponding to the first electronic control unit based on the first diagnostic complexity value and the second diagnostic complexity value, the above procedure includes instructions for performing the following steps: Determine a first weight corresponding to the first diagnostic complexity value and a second weight corresponding to the second diagnostic complexity value; the sum of the first weight and the second weight is 1; A reference diagnostic complexity value is determined based on the first diagnostic complexity value, the first weight, the second diagnostic complexity value, and the second weight; Obtain the fault function failure impact coefficient corresponding to the first electronic control unit; the fault function failure impact coefficient is the degree of impact on the driving safety of the target vehicle when the first electronic control unit malfunctions. Determine the adjustment parameters corresponding to the failure impact coefficient of the aforementioned fault function; The reference diagnostic complexity value is adjusted based on the adjustment parameters to obtain the diagnostic complexity value corresponding to the first electronic control unit.

[0091] In some possible implementations, in order to perform fault diagnosis operations on the n electronic control units based on the n sets of data to be diagnosed and obtain a target fault diagnosis result, the above procedure includes instructions for performing the following steps: Obtain the historical diagnostic results of each of the n electronic control units within a preset historical time period to obtain n sets of historical diagnostic results; Based on the n sets of historical diagnostic results, the priority of each of the n electronic control units is determined, resulting in n priorities. The target priority order is determined based on the n priorities; Based on the n sets of data to be diagnosed, fault diagnosis operations are performed on the n electronic control units in accordance with the target priority order to obtain the target fault diagnosis result.

[0092] In some possible implementations, in determining the priority of each of the n electronic control units based on the n sets of historical diagnostic results, to obtain n priorities, the above procedure includes instructions for performing the following steps: Based on the n sets of historical diagnostic results, determine the fault severity value corresponding to the fault of each of the n electronic control units when a fault occurs within the preset historical time period, and obtain n fault severity values; The priority of each of the n electronic control units is determined based on the n fault severity values, thus obtaining the n priorities; the higher the fault severity value of the electronic control unit, the higher the priority of the electronic control unit.

[0093] In some possible implementations, in determining the fault severity value corresponding to the fault that occurred in each of the n electronic control units within the preset historical time period based on the n sets of historical diagnostic results, and obtaining n fault severity values, the above procedure includes instructions for performing the following steps: Determine the first historical diagnostic result corresponding to the second electronic control unit; the second electronic control unit is any one of the n electronic control units, and the first historical diagnostic result is the historical diagnostic result corresponding to the second electronic control unit in the n sets of historical diagnostic results; Based on the first historical diagnostic results, determine the vehicle downtime loss value and vehicle repair time corresponding to the second electronic control unit; Determine the severity value of the fault corresponding to the vehicle downtime loss value to obtain the first fault severity value; Determine the severity value of the fault corresponding to the vehicle fault repair time to obtain the second fault severity value; The fault severity value corresponding to the second electronic control unit is determined based on the first fault severity value and the second fault severity value.

[0094] It should be understood that the electronic devices mentioned in this application may include smartphones (such as Android phones, iOS phones, Windows Phones, etc.), tablets, PDAs, laptops, mobile internet devices (MIDs) or wearable devices, servers, edge computing nodes, etc. The above-mentioned electronic devices are merely examples and not exhaustive, and include, but are not limited to, the electronic devices described above.

[0095] This application also provides a computer-readable storage medium storing a computer program that is executed by a processor to implement some or all of the steps of any of the methods described in the above method embodiments.

[0096] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods described in the above method embodiments.

[0097] It should be noted that, for the sake of simplicity, the aforementioned methods are described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are optional, and the actions and modules involved are not necessarily essential to this application.

[0098] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0099] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0100] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0101] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software program module.

[0102] If the integrated unit is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0103] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage device, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0104] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The above description of the embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A vehicle diagnostic method, characterized in that, include: Obtain diagnostic instructions for the target vehicle; Based on the diagnostic instructions, n electronic control units in the target vehicle that require fault diagnosis are identified; n is a positive integer. Determine the communication interaction method between the diagnostic device and each of the n electronic control units to obtain n communication interaction methods; Based on the n communication interaction methods, obtain the diagnostic data corresponding to each of the n electronic control units, and obtain n sets of diagnostic data; Based on the n sets of data to be diagnosed, fault diagnosis operations are performed on the n electronic control units to obtain the target fault diagnosis result.

2. The method as described in claim 1, characterized in that, The communication interaction method between the diagnostic device and each of the n electronic control units is determined, resulting in n communication interaction methods, including: Determine the diagnostic complexity value corresponding to each of the n electronic control units to obtain n diagnostic complexity values; Determine k diagnostic complexity values ​​that are greater than a preset diagnostic complexity value and nk diagnostic complexity values ​​that are less than or equal to the preset diagnostic complexity value from among the n diagnostic complexity values; k is an integer less than or equal to n; The communication interaction mode of the k electronic control units corresponding to the k diagnostic complexity values ​​is determined to be a service-based vehicle bus interaction mode; the service-based vehicle bus interaction mode is a vehicle bus communication mode in which the electronic control units use services as the interaction carrier and realize data interaction by sending service requests and responses. The communication interaction mode of the nk electronic control units corresponding to the nk diagnostic complexity values ​​is determined to be a signal-based vehicle bus interaction mode; the signal-based vehicle bus interaction mode is a vehicle bus communication mode in which the electronic control unit encapsulates the operating data into signals according to preset rules, and sends the signals periodically or event-triggered through the bus to realize data interaction.

3. The method as described in claim 2, characterized in that, The process of determining the diagnostic complexity value corresponding to each of the n electronic control units to obtain n diagnostic complexity values ​​includes: The number of data bytes corresponding to the first electronic control unit and the number of communication interaction steps required to complete the fault diagnosis operation of the first electronic control unit are obtained; the first electronic control unit is any one of the n electronic control units; Determine the diagnostic complexity value corresponding to the number of data bytes to obtain the first diagnostic complexity value; Determine the diagnostic complexity value corresponding to the number of communication interaction steps to obtain the second diagnostic complexity value; The diagnostic complexity value corresponding to the first electronic control unit is determined based on the first diagnostic complexity value and the second diagnostic complexity value.

4. The method as described in claim 3, characterized in that, Determining the diagnostic complexity value corresponding to the first electronic control unit based on the first diagnostic complexity value and the second diagnostic complexity value includes: Determine a first weight corresponding to the first diagnostic complexity value and a second weight corresponding to the second diagnostic complexity value; the sum of the first weight and the second weight is 1; A reference diagnostic complexity value is determined based on the first diagnostic complexity value, the first weight, the second diagnostic complexity value, and the second weight; Obtain the fault function failure impact coefficient corresponding to the first electronic control unit; the fault function failure impact coefficient is the degree of impact on the driving safety of the target vehicle when the first electronic control unit malfunctions. Determine the adjustment parameters corresponding to the failure impact coefficient of the aforementioned fault function; The reference diagnostic complexity value is adjusted based on the adjustment parameters to obtain the diagnostic complexity value corresponding to the first electronic control unit.

5. The method as described in claim 4, characterized in that, The step of performing fault diagnosis operations on the n electronic control units based on the n sets of data to be diagnosed, and obtaining the target fault diagnosis result, includes: Obtain the historical diagnostic results of each of the n electronic control units within a preset historical time period to obtain n sets of historical diagnostic results; Based on the n sets of historical diagnostic results, the priority of each of the n electronic control units is determined, resulting in n priorities. The target priority order is determined based on the n priorities; Based on the n sets of data to be diagnosed, fault diagnosis operations are performed on the n electronic control units in accordance with the target priority order to obtain the target fault diagnosis result.

6. The method as described in claim 5, characterized in that, The priority of each of the n electronic control units is determined based on the n sets of historical diagnostic results, resulting in n priorities, including: Based on the n sets of historical diagnostic results, determine the fault severity value corresponding to the fault of each of the n electronic control units when a fault occurs within the preset historical time period, and obtain n fault severity values; The priority of each of the n electronic control units is determined based on the n fault severity values, thus obtaining the n priorities; the higher the fault severity value of the electronic control unit, the higher the priority of the electronic control unit.

7. The method as described in claim 6, characterized in that, The method involves determining the severity value of each of the n electronic control units (ECUs) when a fault occurs within the preset historical time period based on the n sets of historical diagnostic results, resulting in n severity values, including: Determine the first historical diagnostic result corresponding to the second electronic control unit; the second electronic control unit is any one of the n electronic control units, and the first historical diagnostic result is the historical diagnostic result corresponding to the second electronic control unit in the n sets of historical diagnostic results; Based on the first historical diagnostic results, determine the vehicle downtime loss value and vehicle repair time corresponding to the second electronic control unit; Determine the severity value of the fault corresponding to the vehicle downtime loss value to obtain the first fault severity value; Determine the severity value of the fault corresponding to the vehicle fault repair time to obtain the second fault severity value; The fault severity value corresponding to the second electronic control unit is determined based on the first fault severity value and the second fault severity value.

8. A vehicle diagnostic device, characterized in that, The device includes: an acquisition unit and a processing unit; The acquisition unit is used to acquire diagnostic instructions for the target vehicle; The processing unit is used to determine, based on the diagnostic instructions, n electronic control units in the target vehicle that require fault diagnosis; n is a positive integer; Determine the communication interaction method between the diagnostic device and each of the n electronic control units to obtain n communication interaction methods; Based on the n communication interaction methods, obtain the diagnostic data corresponding to each of the n electronic control units, and obtain n sets of diagnostic data; Based on the n sets of data to be diagnosed, fault diagnosis operations are performed on the n electronic control units to obtain the target fault diagnosis result.

9. An electronic device, characterized in that, The method includes a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the one or more programs include instructions for performing the steps of the method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that is executed by a processor to implement the method as described in any one of claims 1-7.

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