Methods and equipment for diagnosing faults in vehicle engines

Abstract

This disclosure provides a method and apparatus for diagnosing faults in a vehicle engine. The method includes: receiving test results of an engine of a vehicle to be diagnosed; identifying one or more anomalous test items in the test results; for each anomalous test item: determining a subgroup to which the anomalous test item belongs; determining one or more related subgroups of the subgroup based on a step number of the subgroup; determining the frequency of occurrence of a corresponding engine component in an engine component list corresponding to the subgroup and the group to which the one or more related subgroups belong; and determining the faulty component of the engine based on the frequency of occurrence. By utilizing the correlation between faults in the engine test results and engine components that may cause the fault, engine faults can be diagnosed efficiently.

Description

Technical Field

[0001] This disclosure generally relates to fault diagnosis of vehicle engines, and more particularly to methods and apparatus for diagnosing faults in vehicle engines. Background Technology

[0002] For vehicle engines, once an engine test fails, some test curves will inevitably deviate from the target curves. Current testing software only displays the fault curves, but there is no direct correlation between these curves and the potentially faulty components. Human involvement is necessary to diagnose engine faults and locate possible faulty parts. Furthermore, the person performing the fault diagnosis must be thoroughly familiar with engine theory, testing equipment, and testing procedures to successfully diagnose the problem.

[0003] Currently, in engine assembly plants, all fault diagnosis processes heavily rely on test experts. Therefore, the responsiveness and accuracy of fault diagnosis are bottlenecks. Fault diagnosis can help rework operators search fault history records and refer to repair guides for faulty engines, but this is only available for typical fault modes. Once a new fault mode emerges and cannot be matched against the typical fault mode database, test experts must be involved again.

[0004] Therefore, improved technologies are needed for diagnosing vehicle engine faults, thereby increasing the efficiency and accuracy of such diagnoses. Summary of the Invention

[0005] One object of this disclosure is to provide improved methods and apparatus for diagnosing faults in vehicle engines.

[0006] In one aspect of this disclosure, a method for diagnosing faults in a vehicle engine is provided, comprising: receiving test results of an engine of a vehicle to be diagnosed, the test results including test items, the test results being organized into multiple groups according to possible fault types, each group corresponding to a list of engine components that may cause the fault type corresponding to that group and including one or more subgroups, each subgroup including one or more test items and having a step number indicating a test time period for the one or more test items; identifying one or more abnormal test items in the test results; for each abnormal test item: determining the subgroup to which the abnormal test item belongs; determining one or more related subgroups of the subgroup based on the step number of the subgroup; determining the frequency of occurrence of the corresponding engine component in the engine component list corresponding to the subgroup and the group to which the one or more related subgroups belong; and determining the faulty component of the engine based on the frequency of occurrence of the corresponding engine component.

[0007] According to another aspect of this disclosure, an apparatus for diagnosing faults in a vehicle engine is provided, comprising: a memory having one or more instruction sequences stored thereon; and a processor coupled to the memory, wherein the processor is configured to cause the method described above to be performed when executing the one or more instruction sequences.

[0008] By utilizing the methods and apparatus of this disclosure, engine faults can be diagnosed efficiently by taking advantage of the correlation between faults in engine test results and engine components that may cause the faults.

[0009] According to another aspect of this disclosure, a non-transitory computer-readable storage medium is provided, comprising one or more instruction sequences that, when executed by one or more processors, cause the methods described above to be performed.

[0010] According to another aspect of this disclosure, a computer program product is provided, including program instructions for performing the methods described above. Attached Figure Description

[0011] The above and other objects, features and advantages of this disclosure will become more apparent from the more detailed description of exemplary embodiments thereof taken in conjunction with the accompanying drawings, wherein like reference numerals generally denote like parts.

[0012] Figure 1 A flowchart is shown of a method for diagnosing faults in a vehicle engine according to at least one embodiment of the present disclosure.

[0013] Figure 2 An example of test results according to at least one embodiment of this disclosure is shown.

[0014] Figure 3 A flowchart is shown of the steps in a method for diagnosing faults in a vehicle engine according to at least one embodiment of the present disclosure.

[0015] Figure 4 A schematic diagram illustrating the logical relationships between groups according to at least one embodiment of the present disclosure is shown.

[0016] Figure 5 A block diagram of a computing device according to at least one embodiment of the present disclosure is shown. Detailed Implementation

[0017] Preferred embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While preferred embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0018] Those skilled in the art will recognize that this invention can be implemented as a system, method, or computer program product. Therefore, this disclosure can be implemented in the following forms: it can be entirely hardware, entirely software (including firmware, resident software, microcode, etc.), or a combination of hardware and software, generally referred to herein as a "circuit," "module," or "system." Furthermore, in some embodiments, the invention can also be implemented as a computer program product contained in one or more computer-readable media, which includes computer-readable program code.

[0019] Any combination of one or more computer-readable media may be used. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium can be, for example—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0020] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including—but not limited to—electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of transmitting, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0021] The program code contained on a computer-readable medium may be transmitted using any suitable medium, including—but not limited to—wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0022] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0023] The present invention will now be described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine that, when executed by a computer or other programmable data processing apparatus, creates means for implementing the functions / operations specified in the blocks of the flowchart illustrations and / or block diagrams.

[0024] These computer program instructions may also be stored in a computer-readable medium that enables a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable medium produce a manufacture that includes instruction means that implement the functions / operations specified in the boxes of a flowchart and / or block diagram.

[0025] Computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, such that the instructions that execute on the computer or other programmable apparatus can provide a process for implementing the functions / operations specified in the boxes of a flowchart and / or block diagram.

[0026] Although each operation is described in conjunction with a specific device, those skilled in the art will understand that the operations described above can be performed by different devices, and this disclosure does not limit this. Furthermore, although described as different devices, those skilled in the art will understand that the devices described above can be combined together or further divided into several devices, and this disclosure does not limit this.

[0027] As shown above, embodiments of this disclosure provide an improved method and apparatus for diagnosing faults in vehicle engines.

[0028] Figure 1 This is a flowchart illustrating a method 100 for diagnosing faults in a vehicle engine according to an embodiment of the present disclosure.

[0029] like Figure 1 As shown, method 100 includes receiving test results of the engine of the vehicle to be diagnosed in step S101.

[0030] In one example, engine test results include one or more items. For instance, engine test results could include up to 2,000 items.

[0031] The test results are organized into multiple groups according to possible fault types. Each group corresponds to a list of engine components that may cause the fault type in that group and includes one or more subgroups. Each subgroup includes one or more test items and has a step number indicating the test time period for the one or more test items. The list of engine components corresponding to each group indicates the correlation between the fault type in that group and the engine components that may cause that fault type.

[0032] exist Figure 2 The example shown is an example of test results organized by groups, subgroups, and test items. Figure 2 As shown, the test results can be organized into groups, such as groups G001, G002, G003, G004, G005, G00N, etc., and the corresponding engine component lists for these groups are, for example, LIST1, LIST2, LIST3, LIST4, LIST5, LISTN, etc. Figure 2 (Not shown in the image). For example... Figure 2As shown, group G001 contains subgroup SG001_STEP1, which includes test items ITEM1 and ITEM2. Group G002 contains subgroups SG002_STEP2 and SG003_STEP1. Subgroup SG002_STEP2 includes test items ITEM3, ITEM4, and ITEM5, while subgroup SG003_STEP1 includes test items ITEM6 and ITEM7. Group G003 contains subgroup SG004_STEP1, which includes test items ITEM8 and ITEM9. Group G004 contains subgroup SG005_STEP2, which includes test item ITEM10. Group G005 contains subgroup SG006_STEP1, which includes test item ITEM11. In the above expressions, STEPX represents the corresponding step number of the subgroup.

[0033] For different vehicle models or engines, the test results are in the same groups and subgroups, but the test items included in the corresponding subgroups may be different.

[0034] In one example, the list of engine parts is identified by codes, and the engine parts in the engine list are also identified by codes to reduce problems that may be caused by typos.

[0035] Method 100 further includes, in step S103, identifying one or more abnormal test items in the test results.

[0036] In one example, test items have corresponding test curves, and identifying one or more abnormal test items in the test results involves comparing the test curve of the test item with the normal test curve of the test item. The test curves represent the test values ​​of the test items in a curved form to provide a more intuitive representation.

[0037] exist Figure 2 The document also highlights abnormal test items, such as test items ITEM1, ITEM5, ITEM6, and ITEM11.

[0038] Method 100 further includes, in step S105, determining the subgroup to which the abnormal test item belongs for each abnormal test item. Taking the abnormal item ITEM1 as an example, the subgroup determined in this step is SG001_STEP1.

[0039] In step S107, based on the step number of the subgroup, one or more related subgroups of the subgroup are determined.

[0040] As described with respect to step S101, the step number indicates the time period of the test item (or the subgroup to which the test item belongs). Multiple tests may be performed within the same time period, and the test items corresponding to these tests will be assigned the same step number. For example, all test items (and their respective subgroups) performed between 0 and 200 seconds will have the step number STEP1, while all test items (and their respective subgroups) performed between 201 and 400 seconds will have the step number STEP2, and so on. The above figures are merely examples, and this disclosure does not limit the specific length of the test period or the encoding method of the step numbers. Multiple tests performed within the same time period will be divided into different subgroups according to the components involved.

[0041] In one example, step S107 may include, for example, identifying one or more subgroups that have the same step number as the subgroup as the one or more related subgroups.

[0042] Continuing with the example above, according to this step, the subgroups with the same step number as subgroup SG001_STEP1, namely subgroups SG003_STEP1, SG004_STEP1, and SG006_STEP1, will be identified as the related subgroups of the subgroup.

[0043] In another example, step S107 may include, for example, identifying one or more subgroups that have the same step number as the subgroup; and determining one or more of the identified subgroups that contain an anomalous test item as the one or more related subgroups.

[0044] Continuing with the example above, at this step, the subgroups with the same step number as subgroup SG001_STEP1 are SG003_STEP1, SG004_STEP1, and SG006_STEP1. However, only subgroups SG003_STEP1 and SG006_STEP1 are identified as relevant subgroups because they contain abnormal test items, while subgroup SG004_STEP1 is not identified as a relevant subgroup because it does not contain abnormal test items.

[0045] According to this example, only the subgroups that have the same step number as the subgroup and contain anomalies are identified as the related subgroups of the subgroup.

[0046] When identifying one or more relevant subgroups, for the anomalous test item ITEM5 (see also...), Figure 2The subgroup with the same step number as subgroup SG002_STEP2 is SG005_STEP2; however, since this subgroup does not contain any abnormal test items, it will not be identified as a relevant subgroup according to the example above. Step S107 also includes the operation in this case. See below for further details. Figure 3 To describe the operation of step S107 in this case.

[0047] In step S301, the test results of one or more previously manufactured engines are obtained.

[0048] As described above regarding step S101, the engine test results include one or more items. For example, the engine test results may include up to 2000 items.

[0049] The test results are organized into multiple groups according to possible fault types. Each group corresponds to a list of engine components that may cause the fault type in that group and includes one or more subgroups. Each subgroup includes one or more test items and has a step number indicating the test time period for the one or more test items. The list of engine components corresponding to each group indicates the correlation between the fault type in that group and the engine components that may cause that fault type.

[0050] At this step, test results for a predetermined number of previously produced engines can be obtained. The predetermined number can be specified by the user as needed, and this disclosure does not impose any restrictions on it.

[0051] At step S303, the deviation between the test items contained in the subgroup to which the abnormal test item belongs (such as the subgroup determined in step S105) and the test items contained in one or more subgroups with the same step number as the subgroup, and the corresponding test items contained in the subgroup corresponding to the test results of one or more previously produced engines obtained at step S301 is calculated.

[0052] For example, for the abnormal test item ITEM5, calculate the deviation between the test items (i.e., ITEM3, ITEM4, and ITEM5) included in its subgroup SG002_STEP and the test item (i.e., ITEM10) included in the subgroup SG005_STEP2 with the same step number as this subgroup, and the corresponding test items (i.e., test items ITEM3, ITEM4, ITEM5, and ITEM10) of previously produced engines. This may include, for example, calculating the rank of the test value corresponding to the aforementioned test item of the engine among all data and the normal distribution parameters of the aforementioned data, etc.

[0053] In step S305, a predetermined number of test items are selected based on the calculated deviation, and the subgroup to which the selected test items belong is determined as one or more relevant subgroups. Those skilled in the art will understand that the predetermined number can be selected by the user according to needs and corresponding criteria. For example, the user can select the test item with the largest standard deviation (indicating that the test item deviates the most from the corresponding test item of a previously produced engine), or the lowest-ranked test item (indicating that the test item has the largest deviation), etc., and this disclosure does not limit this selection.

[0054] According to this example, if none of the subgroups with the same step number as the subgroup contain abnormal test items, the relevant subgroups can be identified by utilizing data from previously produced engines (specifically, data from their corresponding test items).

[0055] Method 100 further includes, in step S109, determining the number of occurrences of the corresponding engine component in the engine component list corresponding to the subgroup and the group to which the one or more related subgroups belong, and determining the faulty component of the engine based on the number of occurrences of the corresponding engine component.

[0056] As described above regarding step S101, each group and its corresponding engine component list indicate the correlation between the fault type corresponding to that group and the engine components that may cause that fault type. Therefore, based on the frequency of occurrence of engine components, the engine component most likely to fail can be determined.

[0057] According to this step, the engine component that appears most frequently can be identified as the faulty part of the engine, so that the engine component can be inspected and dealt with first during rework.

[0058] By utilizing the method of this disclosure, engine faults can be diagnosed efficiently by taking advantage of the correlation between faults in engine test results and engine components that may cause the faults.

[0059] In one example, the multiple groups have logical relationships established based on causality, including parent-child relationships and peer relationships.

[0060] Figure 4An example of a logical relationship between groups is shown. For instance, suppose that a failure in group G002 (specifically, a failure of a test item in one of its subgroups) causes a failure in group G001, and a failure in group G003 (specifically, a failure of a test item in one of its subgroups) also causes a failure in group G001. Then, there is a causal relationship between group G001 and groups G002 and G003, establishing a parent-child relationship between them. Conversely, suppose that failures in groups G004, G005, and G00N do not cause a failure in group G001; that is, there is no causal relationship between failures in groups G004, G005, and G00N and failures in group G001. Then, there is an equivalent (or equal) relationship between groups G004, G005, and G00N and group G001. Logical relationships between other groups can be established similarly, but will not be described in detail here.

[0061] In one example, determining the number of occurrences of the corresponding engine component in the engine component list corresponding to the subgroup and the group to which the one or more related subgroups belong also includes excluding groups that are not child groups of the group to which the subgroup belongs.

[0062] Continuing the previous example, for test item ITEM1, its subgroup is SG001_STEP1, and the group to which subgroup SG001_STEP1 belongs is group G001. Subgroups with the same step number as subgroup SG001_STEP1 are subgroups SG003_STEP1, SG004_STEP1, and SG006_STEP1, and these subgroups correspond to groups G002, G003, and G005, respectively. According to this step, group G005, to which subgroup SG006_STEP1 belongs, is excluded because it is not a child group of group G001. Therefore, when calculating the occurrence count of engine parts, the list of engine parts corresponding to group G005 is excluded.

[0063] Based on this example, the logical relationships between groups can be used to exclude groups that do not have a causal relationship (i.e., exclude the list of engine parts corresponding to that group), and further filter the identified groups and their corresponding list of engine parts, thereby improving the efficiency and accuracy of fault diagnosis.

[0064] Figure 5 The illustration shows a block diagram of a computing device according to one or more embodiments of the present disclosure, which is an example of a hardware device that can be applied to various aspects of the present disclosure.

[0065] Now refer to Figure 5The description of computing device 500 is an example of a hardware device that can be applied to various aspects of this disclosure. Computing device 500 can be any machine configured to perform processing and / or computation, and can be, but is not limited to, a workstation, server, desktop computer, laptop computer, tablet computer, personal data assistant, smartphone, in-vehicle computer, or any combination thereof. The various devices / server / client devices mentioned above can be implemented wholly or at least partially by computing device 500 or similar devices or systems.

[0066] The computing device 500 may include elements that may be connected to or communicate with the bus 502 via one or more interfaces. For example, the computing device 500 may include the bus 502, one or more processors 504, one or more input devices 506, and one or more output devices 508. The one or more processors 504 may be any type of processor and may include, but are not limited to, one or more general-purpose processors and / or one or more dedicated processors (such as dedicated processing chips). The input devices 506 may be any type of device capable of inputting information to the computing device and may include, but are not limited to, a mouse, keyboard, touchscreen, microphone, and / or remote control. The output devices 508 may be any type of device capable of presenting information and may include, but are not limited to, a monitor, speaker, video / audio output terminal, vibrator, and / or printer. The computing device 500 may also include or be connected to a non-transient storage device 510, which may be any non-transient storage device capable of storing data, and may include, but is not limited to, disk drives, optical storage devices, solid-state storage devices, floppy disks, flexible disks, hard disks, magnetic tapes or any other magnetic media, optical discs or any other optical media, ROM (read-only memory), RAM (random access memory), cache memory and / or any other memory chips or cassettes, and / or any other media from which a computer may read data, instructions and / or code. The non-transient storage device 510 may be detachable from an interface. The non-transient storage device 510 may have data / instructions / code for implementing the methods and steps described above. The computing device 500 may also include a communication device 512. The communication device 512 may be any type of device or system capable of communicating with external devices and / or with a network, and may include, but is not limited to, modems, network interface cards, infrared communication devices, wireless communication devices and / or chipsets, such as Bluetooth™ devices, 1302.11 devices, Wi-Fi devices, WiMAX devices, cellular communication facilities, etc.

[0067] Furthermore, the non-transient storage device 510 may contain map information and software elements, enabling the processor 504 to perform route guidance processing. Additionally, the output device 506 may include a display for showing maps, vehicle location markers, and images indicating vehicle movement. The output device 506 may also include a speaker or an interface to headphones for audio guidance.

[0068] Bus 502 may include, but is not limited to, Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus. In particular, for automotive devices, bus 502 may also include Controller Area Network (CAN) bus or other architectures designed for automotive applications.

[0069] The computing device 500 may also include working memory 514, which may be any kind of working memory that can store instructions and / or data useful for the operation of the processor 504, and may include, but is not limited to, random access memory and / or read-only memory devices.

[0070] Software elements may reside in working memory 514, including but not limited to operating system 516, one or more application programs 518, drivers, and / or other data and code. Instructions for performing the methods and steps described above may be included in one or more application programs 518, and components / units / elements of the various devices / servers / clients mentioned above may be implemented by processor 504 reading and executing the instructions of one or more application programs 518.

[0071] It should also be recognized that variations are possible depending on specific requirements. For example, custom hardware may be used, and / or specific elements may be implemented in hardware, software, firmware, middleware, microcode, hardware description languages, or any combination thereof. Additionally, connections to other computing devices (such as network input / output devices) may be employed. For instance, some or all of the disclosed methods and apparatus may be implemented by programming hardware (e.g., programmable logic circuit systems including field-programmable gate arrays (FPGAs) and / or programmable logic arrays (PLAs)) using the logic and algorithms according to this disclosure in assembly language or hardware programming languages ​​(such as Verilog, VHDL, C++).

[0072] This disclosure also provides an apparatus for diagnosing faults in a vehicle engine, comprising: a memory storing one or more instruction sequences thereon; and a processor coupled to the memory, wherein the processor is configured to cause the methods described above to be performed when executing the one or more instruction sequences.

[0073] This disclosure also provides a non-transitory computer-readable storage medium including one or more instruction sequences that, when executed by one or more processors, cause the methods described above to be performed.

[0074] This disclosure also provides a computer program product including program instructions for performing the methods described above.

[0075] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0076] Various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical applications, or technical improvements to technologies in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for diagnosing a vehicle engine fault, comprising: Receive test results of the engine of the vehicle to be diagnosed. The test results include test items and are organized into multiple groups according to possible fault types. Each group corresponds to a list of engine components that may cause the fault type corresponding to that group and includes one or more subgroups. Each subgroup includes one or more test items and has a step number indicating the test time period of the one or more test items. Identify one or more abnormal test items in the test results; For each abnormal test item: Determine the subgroup to which the abnormal test item belongs; Based on the step number of the subgroup, determine one or more related subgroups of the subgroup; as well as Determine the frequency of occurrence of the corresponding engine component in the engine component list corresponding to the subgroup and the group to which the one or more related subgroups belong, and determine the faulty component of the engine based on the frequency of occurrence.

2. The method of claim 1, wherein determining one or more related subgroups of the subgroup based on the step number of the subgroup comprises: One or more subgroups that have the same step number as the subgroup are identified as the one or more related subgroups.

3. The method of claim 1, wherein determining one or more related subgroups of the subgroup based on the step number of the subgroup comprises: Identify one or more subgroups that have the same step number as the subgroup; as well as One or more of the test items that contain anomalies in the identified one or more subgroups are identified as the one or more relevant subgroups.

4. The method of claim 1, wherein determining one or more related subgroups of the subgroup based on the step number of the subgroup comprises: Identify one or more subgroups that have the same step number as the subgroup; as well as In response to determining that the one or more subgroups do not contain any abnormal test items: Obtain test results for one or more previously manufactured engines; Calculate the deviation between the test items contained in the subgroup and the test items contained in one or more subgroups with the same step number as the subgroup, and the corresponding test items contained in the subgroup corresponding to the test results of the one or more previously produced engines; as well as Based on the calculated deviation, a predetermined number of test items are selected, and the subgroup to which the selected test items belong is determined as one or more related subgroups.

5. The method according to claim 1, wherein the test items have corresponding test curves, and identifying one or more abnormal test items in the test results includes: Compare the test curve of the test item with the normal test curve of the test item.

6. The method according to claim 1, further comprising: The multiple groups have logical relationships established based on causal relationships, including father-child relationships and peer relationships.

7. The method of claim 6, wherein determining the occurrence count of the corresponding engine component in the engine component list corresponding to the subgroup and the group to which the one or more related subgroups belong includes: Exclude groups that are not child groups of the group to which the one or more related subgroups belong.

8. The method of claim 1, wherein the list of engine components is identified by a code, and the engine components in the list of engines are identified by a code.

9. An apparatus for diagnosing faults in a vehicle engine, comprising: A memory on which one or more instruction sequences are stored; as well as A processor coupled to the memory, wherein the processor is configured to, when executing the one or more instruction sequences, cause the method of any one of claims 1-8 to be performed.

10. A non-transitory computer-readable storage medium comprising one or more instruction sequences, said one or more instruction sequences causing the method of any one of claims 1-8 to be performed when executed by one or more processors.

11. A computer program product comprising program instructions for performing the method of any one of claims 1-8.

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