Vehicle fault detection method, device and storage medium

Abstract

Embodiments of the present invention relate to the field of vehicle technology and disclose a vehicle fault detection method, device, and storage medium. The method comprises: obtaining vehicle operation data and controller execution data of a vehicle, wherein the vehicle operation data includes at least one of the vehicle's environmental parameters, the vehicle's state parameters, and operation parameters; determining the vehicle's operation scenario based on the vehicle operation data; determining abnormal data in the controller execution data based on controller standard data and the controller execution data corresponding to the operation scenario; and determining the cause of the vehicle fault corresponding to the abnormal data based on a fault database. Application of the technical solution of the present invention can improve the efficiency and convenience of detecting vehicle faults.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of vehicle technology, and in particular to a vehicle fault detection method, device, and storage medium. Background Art

[0002] Currently, after a vehicle breaks down, the user needs to send the vehicle to a 4S car sales and service store, use the vehicle manufacturer's diagnostic equipment to read the vehicle's fault information, and have technicians analyze the fault information, determine the location of the fault, and then repair the vehicle.

[0003] For users, this troubleshooting method is less convenient, and vehicle manufacturers have a limited number of diagnostic equipment, which results in vehicle repairs taking a long time and low troubleshooting efficiency. Summary of the Invention

[0004] In view of the above problems, embodiments of the present invention provide a vehicle fault detection method, device, and storage medium to solve the problem of low vehicle fault processing efficiency in the prior art.

[0005] According to one aspect of an embodiment of the present invention, a vehicle fault detection method is provided, the method comprising: acquiring vehicle operation data and controller execution data of a vehicle, the vehicle operation data comprising environmental parameters of the vehicle, state parameters of the vehicle, and operation parameters; determining an operation scenario of the vehicle based on the vehicle operation data; determining abnormal data in the controller execution data based on controller standard data and the controller execution data corresponding to the operation scenario; and determining a vehicle fault cause corresponding to the abnormal data based on a fault database.

[0006] In an optional manner, the environmental parameters include at least one of the geographical environment, ambient temperature, and atmospheric pressure of the vehicle; the operating parameters include at least one of the vehicle's driving speed, accelerator pedal opening, and brake opening; and the status parameters include at least one of the battery state of charge and charging state.

[0007] In an optional manner, determining abnormal data in the controller execution data based on the controller standard data corresponding to the operating scenario and the controller execution data includes: acquiring the controller standard data corresponding to the operating scenario; comparing the controller standard data corresponding to the operating scenario with the controller execution data, and determining abnormal control parameters in the controller execution data that are inconsistent with the controller standard data; and determining the vehicle fault cause corresponding to the abnormal data based on a fault database includes: querying the fault database, and determining the fault cause in the fault database that matches the abnormal control parameters as the vehicle fault cause.

[0008] In an optional manner, the method further includes: determining the fault degree of the vehicle according to the type of the abnormal control parameter and the deviation information between the abnormal control parameter and the controller standard data.

[0009] In an optional manner, after determining the cause of the vehicle failure corresponding to the abnormal data, the method further includes: generating fault prompt information based on the cause of the vehicle failure, the fault prompt information including the cause of the vehicle failure, the degree of the failure, and at least one of the fault repair plans corresponding to the cause of the vehicle failure; outputting the fault prompt information to send the fault prompt information to a terminal device associated with the vehicle, or to display the fault prompt information on a display screen of the vehicle.

[0010] In an optional manner, determining the operating scenario of the vehicle based on the vehicle operating data includes: using a scenario classification model to classify the environmental parameters, the state parameters and the operating parameters to determine the operating scenario of the vehicle; or, according to the priority of the environmental parameters, the state parameters and the operating parameters, matching them with parameter information corresponding to a preset operating scenario to determine the operating scenario of the vehicle.

[0011] In an optional manner, the method further includes: updating the fault database based on the vehicle operation data, the controller execution data and the vehicle fault cause.

[0012] In an optional manner, before acquiring the vehicle operation data and controller execution data of the vehicle, the method further includes: responding to a data acquisition instruction, acquiring the execution data of the controller corresponding to the data acquisition instruction to obtain the controller execution data.

[0013] According to another aspect of an embodiment of the present invention, a vehicle fault detection device is provided, which includes: an acquisition module for acquiring vehicle operation data and controller execution data of a vehicle, wherein the vehicle operation data includes environmental parameters of the vehicle, state parameters of the vehicle and operation parameters; a first determination module for determining an operation scenario of the vehicle based on the vehicle operation data; a second determination module for determining abnormal data in the controller execution data based on controller standard data corresponding to the operation scenario and the controller execution data; and a third determination module for determining the cause of the vehicle fault corresponding to the abnormal data based on a fault database.

[0014] In an optional manner, the environmental parameters include at least one of the geographical environment, ambient temperature, and atmospheric pressure of the vehicle; the operating parameters include at least one of the vehicle's driving speed, accelerator pedal opening, and brake opening; and the status parameters include at least one of the battery state of charge and charging state.

[0015] In an optional manner, the second determination module is used to obtain controller standard data corresponding to the operating scenario; compare the controller standard data corresponding to the operating scenario with the controller execution data, and determine abnormal control parameters in the controller execution data that are inconsistent with the controller standard data; and determine the vehicle fault cause corresponding to the abnormal data based on the fault database, including: querying the fault database, and determining the fault cause in the fault database that matches the abnormal control parameters as the vehicle fault cause.

[0016] In an optional manner, the third determination module is further configured to determine the fault degree of the vehicle according to the type of the abnormal control parameter and the deviation information between the abnormal control parameter and the controller standard data.

[0017] In an optional manner, after determining the cause of the vehicle failure corresponding to the abnormal data, the third determination module is further used to generate fault prompt information based on the cause of the vehicle failure, the fault prompt information including the cause of the vehicle failure, the degree of the failure, and at least one of the fault repair plans corresponding to the cause of the vehicle failure, and output the fault prompt information to send the fault prompt information to a terminal device associated with the vehicle, or to display the fault prompt information on a display screen of the vehicle.

[0018] In an optional manner, the first determination module is used to use a scenario classification model to classify the environmental parameters, the state parameters and the operating parameters to determine the operating scenario of the vehicle; or, according to the priority of the environmental parameters, the state parameters and the operating parameters, match them with the parameter information corresponding to the preset operating scenario to determine the operating scenario of the vehicle.

[0019] In an optional manner, the third determination module is further configured to update the fault database based on the vehicle operation data, the controller execution data and the vehicle fault cause.

[0020] In an optional manner, the acquisition module is further configured to respond to a data acquisition instruction and acquire execution data of the controller corresponding to the data acquisition instruction to obtain the controller execution data.

[0021] According to another aspect of an embodiment of the present invention, an electronic device is provided, comprising: a processor; and a memory for storing at least one executable instruction; the executable instruction enables the processor to perform the operation of any of the above vehicle fault detection methods.

[0022] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided, wherein the storage medium stores at least one executable instruction. When the executable instruction is executed on an electronic device, the electronic device performs the operation of the vehicle fault detection method as described in any one of the above items.

[0023] The embodiment of the present invention can obtain the vehicle operation data and controller execution data of the vehicle, and determine the vehicle operation scenario based on the vehicle operation data, determine the abnormal data in the controller execution data based on the controller standard data and controller execution data corresponding to the operation scenario, and then determine the vehicle fault cause corresponding to the abnormal data based on the fault database, thereby realizing the automatic monitoring of vehicle operation and the automatic identification of vehicle faults, improving the efficiency and convenience of vehicle fault detection, and being able to provide users with timely understanding of the vehicle condition and guidance and assistance for vehicle repair.

[0024] The above description is only an overview of the technical solutions of the embodiments of the present invention. In order to more clearly understand the technical means of the embodiments of the present invention, they can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the embodiments of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The accompanying drawings are only used to illustrate the embodiments and are not to be considered as limiting the present invention. In addition, the same reference symbols are used to represent the same components throughout the drawings. In the drawings:

[0026] Figure 1 A flow chart of a vehicle fault detection method provided by the present invention is shown;

[0027] Figure 2 A flow chart of another vehicle fault detection method provided by the present invention is shown;

[0028] Figure 3 A flow chart of another vehicle fault detection method provided by the present invention is shown;

[0029] Figure 4 A flow chart of another vehicle fault detection method provided by the present invention is shown;

[0030] Figure 5 A flow chart of another vehicle fault detection method provided by the present invention is shown;

[0031] Figure 6A flow chart of another vehicle fault detection method provided by the present invention is shown;

[0032] Figure 7 An interactive diagram illustrating a vehicle fault detection method provided by the present invention;

[0033] Figure 8 A flow chart of another vehicle fault detection method provided by the present invention is shown;

[0034] Figure 9 A schematic structural diagram of a vehicle fault detection device provided by the present invention is shown;

[0035] Figure 10 A schematic structural diagram of an electronic device provided by the present invention is shown. DETAILED DESCRIPTION

[0036] The exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0037] Figure 1 A flowchart of a vehicle fault detection method provided by an embodiment of the present invention is shown. The method can be executed by an electronic device, and can obtain vehicle operation data and controller execution data of the vehicle in a recent period of time, and detect whether the vehicle has a fault and the cause of the vehicle fault based on the vehicle operation data and controller execution data, thereby realizing automatic identification of vehicle faults and improving the efficiency and convenience of vehicle fault detection.

[0038] The electronic device may be a central console with data processing capabilities on a vehicle, or a vehicle-related backend server or service cluster, or a cloud server that provides vehicle data processing, which is not specifically limited in this embodiment. Figure 1 As shown, the vehicle fault detection method provided by the embodiment of the present invention may include the following steps:

[0039] Step 110: Acquire vehicle operation data and controller execution data of the vehicle.

[0040] Vehicle operation data refers to a series of data collected during the operation of the vehicle, and may include at least one of the vehicle's environmental parameters, vehicle status parameters, and operating parameters. For example, vehicle operation data may include terrain data and temperature data of the vehicle's geographical location, as well as data related to the vehicle's power unit, such as the time when the engine starts and shuts down, the degree of opening of the brake and accelerator pedals, and other data. It may also include vehicle driving data, such as driving trajectory, driving speed, and driving time. Controller execution data refers to the execution data of the control components that control the operation of the vehicle. According to their functional classification, the vehicle's control components can include five functional domains: the power domain, the chassis domain, the infotainment domain, the autonomous driving domain, and the body domain.

[0041] The powertrain domain may include the engine, transmission, battery, and controllers for emissions, fuel economy, and power saving. The chassis domain may include the braking system, transmission, driving system, steering system, vehicle speed sensor, and body posture sensor. The infotainment domain may include audio, seats, and more; the autonomous driving domain may include image acquisition sensors and image processors. The body domain may include headlights, taillights, interior lights, door locks, windows, sunroof, wipers, trunk, air conditioning, smart key, antenna, and more.

[0042] In this embodiment, the electronic device can receive communication messages sent by the vehicle or actively send detection instructions to obtain vehicle operation data and controller execution data. For example, the electronic device can obtain vehicle operation data and controller execution data through sensors, control devices, data recording instruments, and data systems installed on the vehicle.

[0043] For example, environmental parameters in vehicle operation data, such as geographic location, can be collected through sensors installed on the vehicle, such as Global Positioning System (GPS) sensors, and the engine start and shutdown time, brake and accelerator pedal openings, etc. can be recorded and obtained through event data recorders (EDR) and on-board diagnostic systems (OBD) installed on the vehicle.

[0044] Controller execution data can be obtained through domain controllers in each area. Specifically, in each functional domain divided by the vehicle according to function, each area has a corresponding domain controller. The domain controller can transmit the acquired control device data to the vehicle's center console or host it to a cloud server through communication methods such as the Controller Area Network (CAN) or Local Interconnect Network (LIN) or Ethernet.

[0045] It should be noted that the domain controller can also transmit the acquired controller data to the vehicle's center console or cloud server through other communication methods, such as CAN With Flexible Data-Rate (CAN FD) communication method. This embodiment does not specifically limit this.

[0046] In one optional embodiment, environmental parameters refer to parameters of the vehicle's environment, and may include at least one of the vehicle's geographical environment, ambient temperature, and atmospheric pressure. The geographical environment refers to the natural environment of the vehicle's location, and may include information such as its geographic location and topography. The ambient temperature and atmospheric pressure refer to the temperature and atmospheric pressure of the vehicle's external environment, respectively.

[0047] Operating parameters refer to parameters during vehicle operation and may include at least one of the vehicle's speed, accelerator pedal position, and brake pedal position. Accelerator pedal position and brake pedal position represent the pedal travel from the initial position of the accelerator and brake pedals, respectively, to the bottom. A higher pedal position indicates a longer pedal travel and a closer pedal position to the bottom.

[0048] State parameters refer to parameters related to the vehicle's power state and may include at least one of the vehicle's battery state of charge (SOC) and charging state. Battery SOC refers to the remaining charge in the battery, and charging state includes both "charging" and "not charging."

[0049] By acquiring the vehicle's operation data and controller execution data, it is possible to realize digital monitoring of vehicle operation and provide data support for analyzing the vehicle's operation status.

[0050] Step 120: Determine the vehicle's operating scenario based on the vehicle operating data.

[0051] The vehicle's operating scenario may indicate the vehicle's driving conditions at a given time, the type of environment it is in, and the driver's driving conditions, etc. Each operating scenario corresponds to a specific vehicle operating state.

[0052] For example, the vehicle's operating scenario can be set according to the season, city, road type, speed, charging status, driving time, etc. For example, the parameters corresponding to operating scenario 1 can be: {winter; Beijing; urban highway; low speed; not charged; 20 minutes}, and the parameters corresponding to operating scenario 2 can be: {summer; Beijing; highway; high speed; not charged; 1 hour}.

[0053] It should be understood that the above-mentioned operating scenarios are only for illustrative purposes. According to actual needs, the operating scenarios can be combined with other operating parameters to set up as more detailed scenarios, and parameters such as the vehicle speed can also be specific values. This embodiment does not impose any special restrictions on this.

[0054] After obtaining the vehicle's operating data, corresponding scenario feature data can be extracted from it, such as the seasonal characteristics, city characteristics, road type characteristics, speed characteristics, driving duration characteristics, and other data in the parameter examples of the operating scenarios described above. The vehicle's operating scenario at the corresponding time can then be determined based on the feature values of this scenario feature data. For example, assuming the vehicle operating data is the vehicle's operating data for the last 15 minutes, and based on the vehicle operating data, it can be determined that the scenario feature data in this data is the same as the parameter values corresponding to operating scenario 1, then by analyzing the vehicle operating data, it can be determined that the vehicle's operating scenario during the aforementioned time period was operating scenario 1.

[0055] By determining the vehicle's operating scenario, the external environment and internal operating conditions of the vehicle can be determined, and a preliminary detection of the vehicle's operating conditions can be completed.

[0056] Step 130: Determine abnormal data in the controller execution data based on the controller standard data and the controller execution data corresponding to the operation scenario.

[0057] The controller standard data corresponding to an operating scenario can be control data when the vehicle operates normally under that operating scenario, or it can be control data when the vehicle experiences an abnormality under that operating scenario. By comparing the controller standard data corresponding to the operating scenario with the controller execution data, abnormal data in the controller execution data can be identified.

[0058] For example, by comparing the controller standard data corresponding to the operating scenario with the data of the corresponding items in the controller execution data, such as tire pressure data, it can be determined whether the data of each item in the controller execution data is within the normal range, thereby identifying abnormal data in the controller execution data.

[0059] Through the above method, abnormal data of the controller execution data can be identified, and data positioning of vehicle fault detection can be achieved.

[0060] Step 140: Based on the fault database, determine the vehicle fault cause corresponding to the abnormal data.

[0061] A fault database is generated using vehicle operation data, controller execution data, and vehicle fault conditions from one or more vehicles. It records the vehicle operation data and controller execution data when a specific fault occurs. For example, the fault database may record that when a vehicle's tire pressure is too high (a tire pressure range greater than 250 kPa), tire wear increases.

[0062] In order to improve the completeness of the fault database, when establishing the fault database, professional technicians can analyze the above-mentioned vehicle operation data and controller execution data based on their own vehicle maintenance experience to generate a fault database with higher reliability.

[0063] After determining the abnormal data in the controller execution data, the fault database can be used to determine the cause of the vehicle fault corresponding to the abnormal data. For example, if the abnormal data is the battery level, based on the normal range of battery level in the fault database, the cause of the vehicle fault can be determined to be low battery level.

[0064] According to the vehicle fault detection method provided in this embodiment, the vehicle operation data and controller execution data of the vehicle can be obtained, and the vehicle operation scenario can be determined based on the vehicle operation data. The abnormal data in the controller execution data can be determined based on the controller standard data and controller execution data corresponding to the operation scenario. Then, based on the fault database, the cause of the vehicle fault corresponding to the abnormal data is determined, thereby realizing automated monitoring of vehicle operation and automatic identification of vehicle faults, improving the efficiency and convenience of vehicle fault detection, and being able to provide users with timely understanding of the vehicle condition and guidance and assistance for vehicle repair.

[0065] As mentioned above, in an optional manner, the vehicle operation data may include the vehicle's environmental parameters, vehicle status parameters and operation parameters. In order to determine the cause of the vehicle's failure, Figure 2 FIG. 1 shows a flow chart of another vehicle fault detection method provided by this embodiment. Figure 2 As shown, the vehicle fault detection method may include the following steps 210 to 240:

[0066] Step 210: Acquire vehicle operation data and controller execution data of the vehicle.

[0067] The vehicle operation data includes at least one of the vehicle's environmental parameters, vehicle status parameters, and operation parameters.

[0068] Step 220: Use the scenario classification model to classify the environmental parameters, state parameters, and operating parameters to determine the vehicle's operating scenario; or, according to the priority of the environmental parameters, state parameters, and operating parameters, match them with the parameter information corresponding to the preset operating scenario to determine the vehicle's operating scenario.

[0069] That is, in this step, the vehicle's operating scenario can be determined in either of the following two ways:

[0070] (1) Using the scene classification model, the environmental parameters, state parameters and operating parameters are classified and processed to determine the vehicle's operating scene.

[0071] The scene classification model may be a pre-trained classification model, such as a decision tree, random forest, or other model.

[0072] Taking the decision tree model as an example, environmental parameters, state parameters, and operating parameters can be used as input data for a pre-trained decision tree model. Each feature of the input data is a node in the decision tree model. Different branches can be divided according to its value. The generated tree structure can represent the classification of the input data. Each node at the end of the tree structure corresponds to an operating scenario.

[0073] When training a decision tree model, the root node and leaf nodes corresponding to each operating scenario are constructed based on the type of operating scenario. The root node represents the judgment of a feature in the vehicle operating data, and the leaf node represents the output of the judgment result. The root and leaf nodes can include multiple levels. For example, a root node can be divided into multiple leaf nodes, and each of these leaf nodes can be further divided into multiple sub-nodes based on the characteristics, which serve as leaf nodes of another level.

[0074] After building the decision tree model, training data can be input into the built decision tree model for training to generate a pre-trained decision tree classification model. The training data can be vehicle operation data obtained from one or more vehicles, which can also include environmental parameters of the vehicle, vehicle state parameters, and operating parameters.

[0075] Since the scene classification model can be generated through training of a large amount of vehicle operation data, and its processing speed and efficiency are relatively high, using the scene classification model to divide the vehicle operation data to determine the vehicle operation scene can improve the efficiency and accuracy of determining the operation scene.

[0076] (2) According to the priority of environmental parameters, state parameters and operating parameters, the parameter information corresponding to the preset operating scenario is matched to determine the vehicle's operating scenario.

[0077] The priorities of environmental parameters, state parameters, and operating parameters can be used to indicate their importance in assessing vehicle operation. A higher priority indicates a greater impact on vehicle operation. The priority of each parameter can be set by the operator based on actual needs. For example, because the normal operating range of a vehicle's control components may vary under different environmental conditions, environmental parameters can be prioritized first, while state parameters and operating parameters can be prioritized second and third, respectively.

[0078] A preset operating scenario refers to a possible operating scenario for the vehicle. The parameter information corresponding to a preset operating scenario refers to information such as the type and value range of the parameter when the vehicle is in that preset operating scenario. Generally speaking, the preset operating scenario and its parameter information can be pre-set by the operator based on the vehicle's actual operating scenario type and operating data.

[0079] According to the priority of environmental parameters, state parameters and operating parameters, the environmental parameters, state parameters and operating parameters can be matched in turn with parameter information corresponding to preset operating scenarios, such as environmental parameter information, state parameter information and operating parameter information, to determine the operating scenario of the vehicle.

[0080] For example, the first-priority environmental parameters can be first matched with the environmental parameter information corresponding to each preset operating scenario to filter out candidate operating scenarios, and then the state parameters can be matched with the state parameters corresponding to each candidate operating scenario to determine the target operating scenario in the candidate operating scenario. Finally, the operating parameter information can be matched with the operating parameter information corresponding to the target operating scenario to determine the vehicle's operating scenario.

[0081] In an optional manner, when a parameter among the environment parameter, the state parameter and the operation parameter includes multiple data contents, the priority of the environment parameter, the state parameter and the operation parameter can be further set according to the data content in each parameter.

[0082] For example, when the environmental parameters include ambient temperature and atmospheric pressure, and the status parameters include the battery state of charge and charging state, the priority of the environmental parameters and the status parameters can be set according to the specific data content in each parameter. For example, according to the importance of each data content, the priority of the environmental parameters and the status parameters can be set from high to low to ambient temperature, battery state of charge, atmospheric pressure and charging state.

[0083] By matching the various parameters in the vehicle operation data with the parameter information of the preset operation scenario according to the parameter priority in the vehicle operation data, the vehicle operation scenario can be determined. This can optimize the parameter matching path and improve the efficiency of determining the vehicle operation scenario.

[0084] Step 230: Determine abnormal data in the controller execution data based on the controller standard data and the controller execution data corresponding to the operation scenario.

[0085] Step 240: Based on the fault database, determine the vehicle fault cause corresponding to the abnormal data.

[0086] Through the above steps 210 to 240, the environmental parameters, state parameters and operating parameters in the vehicle operation data can be analyzed to determine the vehicle operation scenario, and the cause of the vehicle failure can be determined based on the operation scenario, thereby realizing automatic detection of vehicle failures and helping users understand the vehicle operation status.

[0087] It should be noted that the specific implementation of the above step 210 and steps 230 to 240 can refer to the specific implementation of step 110 and steps 130 to 140 in the above embodiment, which will not be repeated here.

[0088] Figure 3 A flow chart of another vehicle fault detection method provided by an embodiment of the present invention is shown. Figure 3 As shown, the following steps may be included:

[0089] Step 310: Obtain vehicle operation data and controller execution data of the vehicle.

[0090] The vehicle operation data includes at least one of the vehicle's environmental parameters, vehicle status parameters, and operation parameters.

[0091] Step 320: Determine the vehicle's operating scenario based on the vehicle operating data.

[0092] Step 330: Obtain controller standard data corresponding to the operating scenario.

[0093] The controller standard data corresponding to the operation scenario may be execution data of the controller for normal operation of the vehicle under the operation scenario.

[0094] Specifically, the electronic device may search for controller standard data that matches the vehicle's operating scenario in a corresponding controller standard database according to the determined vehicle's operating scenario.

[0095] Step 340: Compare the controller standard data corresponding to the running scenario with the controller execution data to determine abnormal control parameters in the controller execution data that are inconsistent with the controller standard data.

[0096] Compare the controller standard data corresponding to the running scenario with the controller execution data, that is, compare the controller standard data with the corresponding data of the controller execution data, such as comparing the standard brake pedal opening in the controller standard data with the brake pedal opening in the controller execution data, to determine the data in the controller execution data that is inconsistent with the controller standard data, and obtain abnormal control parameters.

[0097] Correspondingly, the data in the controller execution data that is consistent with the controller standard data is the normal control parameter.

[0098] Step 350: query the fault database, and determine the fault cause in the fault database that matches the abnormal control parameter as the vehicle fault cause.

[0099] For example, the corresponding fault database can be queried according to the type and model of the vehicle, and then the fault cause that matches the parameter type and value range of the abnormal control parameter can be found in the fault database to obtain the vehicle fault cause.

[0100] Through the above steps 310 to 350 , abnormal control parameters in the controller execution data can be identified, and the cause of the vehicle failure can be determined based on the abnormal control parameters.

[0101] It should be noted that the specific implementation of the above steps 310 to 320 can refer to the specific implementation of steps 110 to 120 in the above embodiment, which will not be repeated here.

[0102] In order to facilitate users to understand the impact of the vehicle's operating conditions on driving the vehicle, in an optional manner, the degree of the vehicle's failure can be further determined after the cause of the vehicle failure is determined. Figure 4 Another vehicle fault detection method provided by an embodiment of the present invention is shown. Figure 4 As shown, the following steps may be included:

[0103] Step 410: Obtain vehicle operation data and controller execution data of the vehicle.

[0104] The vehicle operation data includes at least one of the vehicle's environmental parameters, vehicle status parameters, and operation parameters.

[0105] Step 420: Determine the vehicle's operating scenario based on the vehicle operating data.

[0106] Step 430: Compare the controller standard data corresponding to the running scenario with the controller execution data to determine abnormal control parameters in the controller execution data.

[0107] Step 440: Determine the fault cause that matches the abnormal control parameter in the fault database as the vehicle fault cause.

[0108] Step 450: Determine the fault degree of the vehicle based on the type of abnormal control parameter and the deviation information between the abnormal control parameter and the controller standard data.

[0109] The deviation information between the abnormal control parameter and the controller standard data may include a difference or ratio between the abnormal control parameter and the controller standard data.

[0110] For numerical control parameters, the severity of the vehicle's fault can be determined based on the abnormal control parameter's type and the deviation between the abnormal control parameter and the controller's standard data. For example, if the abnormal control parameter is tire pressure, the controller's standard data range is 240-250 kPa. The difference between the abnormal control parameter's value and the endpoints of this range can be calculated to determine the severity of the vehicle's tire fault.

[0111] Through the above method, after determining the cause of the vehicle failure, the degree of the vehicle failure can be further determined, which makes it easier to determine whether the vehicle can continue to drive and how long it can continue to drive, thereby improving the convenience of users using the vehicle.

[0112] It should be noted that the specific implementation of the above steps 410 to 440 can refer to the specific implementation of steps 310 to 340 in the above embodiment, which will not be repeated here.

[0113] After determining the cause of the vehicle failure corresponding to the abnormal data, in order to make the user understand the vehicle failure situation, Figure 5 A flow chart of another vehicle fault detection method provided by an embodiment of the present invention is shown. Figure 5 As shown, the following steps may be included:

[0114] Step 510: Obtain vehicle operation data and controller execution data of the vehicle.

[0115] The vehicle operation data includes at least one of the vehicle's environmental parameters, vehicle status parameters, and operation parameters.

[0116] Step 520: Determine the vehicle's operating scenario based on the vehicle operating data.

[0117] Step 530: Determine abnormal data in the controller execution data based on the controller standard data and the controller execution data corresponding to the operation scenario.

[0118] Step 540: Based on the fault database, determine the vehicle fault cause corresponding to the abnormal data.

[0119] Step 550: Generate fault prompt information based on the cause of the vehicle fault.

[0120] The fault prompt information includes at least one of the cause of the vehicle fault, the degree of the fault, and a fault repair plan corresponding to the cause of the vehicle fault.

[0121] Fault prompt information can be prompt information composed of at least one of text and pictures, which may include the cause of the vehicle fault and the degree of the fault. The degree of the fault may specifically include the degree of impact of the fault cause on the operation of the device on the vehicle and the degree of impact on the driving of the vehicle, etc. It may also include a fault repair plan corresponding to the cause of the vehicle fault. The fault repair plan can be specifically set according to the fault situation of the vehicle, and may include the vehicle maintenance method, information about the repair station closest to the current location of the vehicle, etc.

[0122] Step 560: Output fault prompt information, used to send the fault prompt information to a terminal device associated with the vehicle, or used to display the fault prompt information on a display screen of the vehicle.

[0123] Among them, the terminal device associated with the vehicle can be a client used by a user that is bound or connected to the vehicle, such as a mobile phone, computer, etc.

[0124] After the fault prompt information is generated, the fault prompt information can be output, for example, the fault prompt information can be synchronized to the terminal device and the vehicle's center console, and the fault prompt information can be displayed on the terminal device and the vehicle's display screens, so that the user can understand the vehicle's fault condition and fault handling method, and then repair the vehicle according to the fault repair plan in the fault prompt information, or drive the vehicle to the nearest repair station for repair.

[0125] In an optional manner, the terminal device and the vehicle's center console can also choose whether to display or play fault prompt information in audio form according to the user's use of the terminal device and the center console, so as to ensure the user's driving safety and provide convenience for the user.

[0126] Through the above method, users can understand the vehicle's fault level and situation, as well as the repair plan for the fault, and provide guidance for users to choose whether to repair the vehicle and how to repair the vehicle. It can greatly improve the efficiency of detecting vehicle faults and provide convenience for vehicle maintenance.

[0127] It should be noted that the specific implementation of the above steps 510 to 540 can refer to the specific implementation of steps 110 to 140 in the above embodiment, which will not be repeated here.

[0128] Figure 6 A flow chart of another vehicle fault detection method provided by an embodiment of the present invention is shown. Figure 6 As shown, the following steps may be included:

[0129] Step 610: Obtain vehicle operation data and controller execution data of the vehicle.

[0130] The vehicle operation data includes at least one of the vehicle's environmental parameters, vehicle status parameters, and operation parameters.

[0131] Step 620: Determine the vehicle's operating scenario based on the vehicle operating data.

[0132] Step 630: Determine abnormal data in the controller execution data based on the controller standard data and the controller execution data corresponding to the operation scenario.

[0133] Step 640: Based on the fault database, determine the vehicle fault cause corresponding to the abnormal data.

[0134] Step 650: Update the fault database based on the vehicle operation data, controller execution data and vehicle fault causes.

[0135] Since the fault database records the vehicle operation data and controller execution data when a certain specific fault occurs, in order to improve the fault database, after determining the cause of the vehicle fault, the fault parameters in the fault database can be automatically modified according to the vehicle operation data, controller execution data and the cause of the vehicle fault to complete the update of the fault database.

[0136] As the fault database is continuously updated, it can combine the vehicle maintenance experience of professional technicians and the analysis results of a large amount of vehicle data. Therefore, the cause of vehicle failure determined by relying on the fault database can avoid the misjudgment of vehicle failure due to differences in personal professional knowledge, and has higher reliability and accuracy.

[0137] It should be noted that the specific implementation of the above steps 610 to 640 can refer to the specific implementation of steps 110 to 140 in the above embodiment, which will not be repeated here.

[0138] Figure 7 An interactive diagram of a vehicle fault detection method provided by an embodiment of the present invention is shown, Figure 7 As shown, the method includes a vehicle 710, a cloud server 720 and a terminal device 730, and specifically includes the following steps:

[0139] Step 701: Establish a fault database in the cloud server 720.

[0140] A fault database can be generated by an operator based on vehicle operation data and controller execution data from one or more vehicles, as well as the causes of vehicle faults. When establishing the fault database, the vehicle maintenance experience of professional technicians and analysis of vehicle data can be combined to form a database containing vehicle operation data, controller execution data, and fault conditions.

[0141] Step 702 : The vehicle 710 obtains vehicle operation data and controller execution data.

[0142] The vehicle operation data may include at least one of the vehicle's environmental parameters, vehicle status parameters, and operation parameters, and the controller execution data may include data of various control devices in the vehicle.

[0143] Step 703 : The vehicle 710 sends the acquired vehicle operation data and controller execution data to the cloud server 720 .

[0144] Step 704: The cloud server 720 determines the vehicle's operating scenario based on the vehicle operating data.

[0145] After receiving the vehicle operation data and controller execution data, the cloud server 720 may analyze the vehicle operation data to determine the vehicle's operation scenario at the corresponding time. For example, the cloud server 720 may determine the vehicle's operation scenario by matching the environmental parameters, state parameters, and operation parameters in the vehicle operation data with parameter information corresponding to a preset operation scenario based on their priority.

[0146] Among them, the preset operating scenarios and their corresponding parameter information can be set in advance by the operator according to the actual operating scenario type and operating data of the vehicle, and stored in the cloud server 720.

[0147] Step 705: The cloud server 720 determines abnormal data in the controller execution data based on the controller standard data and the controller execution data corresponding to the operation scenario.

[0148] For example, the cloud server 720 may compare the controller standard data corresponding to the operating scenario with the controller execution data to determine abnormal control parameters in the controller execution data, that is, to obtain abnormal data.

[0149] Step 706: The cloud server 720 determines the cause of the vehicle failure corresponding to the abnormal data based on the failure database.

[0150] After determining the abnormal data, the cloud server 720 can search the fault database for a fault cause that matches the abnormal data, such as the abnormal control parameters, as the cause of the vehicle fault.

[0151] After determining the cause of the vehicle failure, the cloud server 720 can further determine the degree of the vehicle failure based on the type of abnormal control parameters and the deviation information between the abnormal control parameters and the controller standard data.

[0152] Step 707: The cloud server 720 generates fault prompt information.

[0153] The fault prompt information may include at least one of the cause of the vehicle fault, the degree of the fault, and a fault repair plan corresponding to the cause of the vehicle fault.

[0154] Step 708 : The cloud server 720 sends the fault prompt information to the terminal device 730 .

[0155] After receiving the fault prompt information, the terminal device 730 can display or play the fault prompt information, so that the user can determine the fault condition of the vehicle according to the fault prompt information, as well as determine when to deal with the vehicle fault, the method of dealing with the vehicle fault, etc.

[0156] During vehicle use, since users use different components at different frequencies and the service lives of various vehicle components also vary, when obtaining controller execution data, if the controller execution data includes the execution data of all controllers, then there may be a situation where the execution data of some controllers remains unchanged for a long period of time.

[0157] Therefore, in order to reduce the amount of data executed by the controller and improve the efficiency of fault detection, Figure 8 A flow chart of another vehicle fault detection method provided by an embodiment of the present invention is shown. Figure 8 As shown, the following steps may be included:

[0158] Step 810: In response to the data acquisition instruction, the execution data of the controller corresponding to the data acquisition instruction is acquired to obtain the controller execution data.

[0159] Among them, the data acquisition instruction is an instruction for the acquisition controller to execute data. It can be automatically triggered by the electronic device according to a certain time period, or it can be automatically triggered by the electronic device according to the vehicle's operating conditions. For example, when the electronic device determines that a certain component of the vehicle has an abnormality, it can automatically generate a data acquisition instruction, and the data acquisition instruction can include parameter information of the controller corresponding to the abnormal component.

[0160] In some cases, the data collection instruction may also be an instruction manually triggered by a user on a terminal device or a vehicle's center console, etc. In this case, the user may select corresponding controllers so that the generated data collection instruction includes parameter information of these controllers.

[0161] Upon receiving a data collection instruction, the electronic device can parse the controller parameter information in the instruction, identify one or more controllers indicated by the instruction, and then obtain the execution data of the controller on the vehicle over a period of time to obtain the controller execution data. In this way, the purpose of collecting controller execution data on demand can be achieved.

[0162] Step 820: Obtain vehicle operation data and controller execution data of the vehicle.

[0163] The vehicle operation data includes at least one of the vehicle's environmental parameters, vehicle status parameters, and operation parameters.

[0164] Step 830: Determine the vehicle's operating scenario based on the vehicle operating data.

[0165] Step 840: Determine abnormal data in the controller execution data based on the controller standard data and the controller execution data corresponding to the operation scenario.

[0166] Step 850: Based on the fault database, determine the vehicle fault cause corresponding to the abnormal data.

[0167] After the cause of the vehicle failure is determined, the cause of the vehicle failure can be synchronously sent to the terminal device associated with the vehicle or the vehicle's central console, so that the user can refer to the cause of the vehicle failure in time and handle the vehicle failure.

[0168] Through the above method, the electronic device can be controlled to obtain the execution data of the corresponding controller according to the controller indicated by the data acquisition instruction, and the controller execution data is obtained without collecting the execution data of all controllers on the vehicle. Therefore, the amount of controller execution data can be reduced, and the data acquisition efficiency and vehicle fault detection efficiency can be improved.

[0169] It should be noted that the specific implementation of the above steps 820 to 850 can refer to the specific implementation of steps 110 to 140 in the above embodiment, which will not be repeated here.

[0170] In summary, according to the vehicle fault detection method in this embodiment, the vehicle operation scenario can be determined based on the vehicle operation data of the vehicle, and the abnormal data in the controller execution data can be determined based on the controller standard data and controller execution data corresponding to the operation scenario. Then, the fault database can be used to determine the cause of the vehicle fault corresponding to the abnormal data, and fault prompt information can be generated and sent to the terminal device or the vehicle's center console, so that the user can timely understand the vehicle's operation status and fault status, as well as the vehicle fault handling plan, which improves the timeliness and reliability of vehicle fault detection and provides convenience for users to repair vehicles.

[0171] Figure 9FIG. 1 shows a schematic diagram of the structure of a vehicle fault detection device provided by an embodiment of the present invention. Figure 9 As shown, the vehicle fault detection device 900 may include: an acquisition module 910, which can be used to acquire vehicle operation data and controller execution data of the vehicle, and the vehicle operation data may include the environmental parameters of the vehicle, the state parameters of the vehicle and the operation parameters; a first determination module 920, which can be used to determine the operation scenario of the vehicle based on the vehicle operation data; a second determination module 930, which can be used to determine abnormal data in the controller execution data based on the controller standard data and the controller execution data corresponding to the operation scenario; a third determination module 940, which can be used to determine the cause of the vehicle fault corresponding to the abnormal data based on the fault database.

[0172] In an optional manner, the environmental parameters include at least one of the vehicle's geographical environment, ambient temperature, and atmospheric pressure; the operating parameters include at least one of the vehicle's driving speed, accelerator pedal opening, and brake opening; and the status parameters include at least one of the battery state of charge and charging state.

[0173] In an optional manner, the second determination module 930 can be used to obtain controller standard data corresponding to the operating scenario; compare the controller standard data corresponding to the operating scenario with the controller execution data to determine abnormal control parameters in the controller execution data that are inconsistent with the controller standard data; the third determination module 940 can be used to query the fault database and determine the fault cause in the fault database that matches the abnormal control parameters as the vehicle fault cause.

[0174] In an optional manner, the third determination module 940 may also be configured to determine the fault degree of the vehicle according to the type of abnormal control parameter and the deviation information between the abnormal control parameter and the controller standard data.

[0175] In an optional manner, after determining the cause of the vehicle failure corresponding to the abnormal data, the third determination module 940 can also be used to generate fault prompt information based on the cause of the vehicle failure, the fault prompt information including the cause of the vehicle failure, the degree of the failure, and at least one of the fault repair plans corresponding to the cause of the vehicle failure, and output the fault prompt information to send the fault prompt information to a terminal device associated with the vehicle, or to display the fault prompt information on the vehicle's display screen.

[0176] In an optional manner, the first determination module 920 can be used to utilize a scenario classification model to classify and process environmental parameters, state parameters, and operating parameters to determine the operating scenario of the vehicle; or, according to the priority of environmental parameters, state parameters, and operating parameters, match the parameter information corresponding to the preset operating scenario to determine the operating scenario of the vehicle.

[0177] In an optional manner, the third determination module 940 may also be configured to update the fault database based on vehicle operation data, controller execution data, and vehicle fault causes.

[0178] In an optional manner, the acquisition module 910 may also be configured to respond to a data acquisition instruction and acquire execution data of the controller corresponding to the data acquisition instruction to obtain controller execution data.

[0179] The specific details of each module in the above device have been described in detail in the implementation method part. The details of the undisclosed scheme can be found in the implementation method part, so they will not be repeated here.

[0180] Figure 10 A schematic structural diagram of an electronic device provided by an embodiment of the present invention is shown. The specific embodiment of the present invention does not limit the specific implementation of the electronic device.

[0181] like Figure 10 As shown, the electronic device may include: a processor (processor) 1002 , a communication interface (Communications Interface) 1004 , a memory (memory) 1006 , and a communication bus 1008 .

[0182] Processor 1002, communication interface 1004, and memory 1006 communicate with each other via communication bus 1008. Communication interface 1004 is used to communicate with other devices, such as client devices or other server network elements. Processor 1002 is used to execute program 1010, which may specifically perform the steps described in the above-mentioned embodiment of the vehicle fault detection method.

[0183] Specifically, the program 1010 may include program code, which includes computer-executable instructions.

[0184] Processor 1002 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included in an electronic device may be processors of the same type, such as one or more CPUs, or processors of different types, such as one or more CPUs and one or more ASICs.

[0185] The memory 1006 is used to store the program 1010. The memory 1006 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0186] Program 1010 can be specifically called by processor 1002 to enable the electronic device to execute the operating steps of the above-mentioned vehicle fault detection method.

[0187] An embodiment of the present invention provides a computer-readable storage medium storing at least one executable instruction. When the executable instruction is executed on an electronic device, the electronic device executes the vehicle fault detection method in any of the above method embodiments.

[0188] The executable instructions can be specifically used to enable the electronic device to execute the operating steps of the above-mentioned vehicle fault detection method.

[0189] The algorithms or displays provided herein are not inherently related to any particular computer, virtual system or other device. In addition, the embodiments of the present invention are not directed to any particular programming language.

[0190] In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the present invention may be practiced without these specific details. Similarly, in order to streamline the present invention and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the present invention, various features of embodiments of the present invention are sometimes grouped together into a single embodiment, figure, or description thereof. The claims that follow the detailed description are hereby expressly incorporated into that detailed description, with each claim itself serving as a separate embodiment of the present invention.

[0191] Those skilled in the art will appreciate that the modules in the devices of the embodiments can be adaptively changed and installed in one or more devices different from the embodiments. The modules, units, or components in the embodiments can be combined into one module, unit, or component, and furthermore, they can be divided into multiple submodules, subunits, or subcomponents. Except that at least some of such features and / or processes or units are mutually exclusive.

[0192] It should be noted that the above embodiments illustrate rather than limit the invention, and that alternative embodiments may be devised by a person skilled in the art without departing from the scope of the appended claims. In the claims, any reference signs placed between brackets should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The present invention may be implemented by means of hardware comprising several different elements and by means of appropriately programmed computers. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third etc. does not indicate any order. These words may be interpreted as names. The steps in the above embodiments should not be understood as limiting the order of execution unless otherwise specified.

Claims

1. A vehicle fault detection method, characterized in that: The method comprises: Acquiring vehicle operation data and controller execution data of the vehicle, wherein the vehicle operation data includes environmental parameters of the vehicle, state parameters of the vehicle, and operation parameters; determining an operating scenario of the vehicle according to the vehicle operating data; determining abnormal data in the controller execution data based on the controller standard data corresponding to the operation scenario and the controller execution data; Determining the cause of the vehicle failure corresponding to the abnormal data based on the failure database; The step of determining the vehicle operation scenario based on the vehicle operation data includes: Using a scenario classification model, environmental parameters, state parameters, and operating parameters are classified and processed to determine the vehicle's operating scenario; or, according to the priority of environmental parameters, state parameters, and operating parameters, the parameter information corresponding to the preset operating scenario is matched to determine the vehicle's operating scenario; The determining abnormal data in the controller execution data according to the controller standard data corresponding to the operation scenario and the controller execution data includes: Obtain controller standard data corresponding to the operating scenario; Comparing the controller standard data corresponding to the operating scenario with the controller execution data to determine abnormal control parameters in the controller execution data that are inconsistent with the controller standard data; The determining, based on the fault database, the vehicle fault cause corresponding to the abnormal data includes: querying the fault database and determining a fault cause in the fault database that matches the abnormal control parameter as the vehicle fault cause; The fault degree of the vehicle is determined according to the type of the abnormal control parameter and the deviation information between the abnormal control parameter and the controller standard data.

2. The method according to claim 1, characterized in that The environmental parameters include at least one of the geographical environment, ambient temperature, and atmospheric pressure of the vehicle; the operating parameters include at least one of the vehicle's driving speed, accelerator pedal opening, and brake opening; and the status parameters include at least one of the battery state of charge and charging state.

3. The method according to any one of claims 1 to 2, characterized in that After determining the vehicle fault cause corresponding to the abnormal data, the method further includes: generating fault prompt information according to the cause of the vehicle fault, the fault prompt information including at least one of the cause of the vehicle fault, the degree of the fault, and a fault repair plan corresponding to the cause of the vehicle fault; The fault prompt information is outputted to send the fault prompt information to a terminal device associated with the vehicle, or to display the fault prompt information on a display screen of the vehicle.

4. The method according to any one of claims 1 to 2, characterized in that The method further comprises: The fault database is updated according to the vehicle operation data, the controller execution data and the vehicle fault cause.

5. The method according to any one of claims 1 to 2, characterized in that Before acquiring the vehicle operation data and the controller execution data of the vehicle, the method further includes: In response to a data acquisition instruction, execution data of the controller corresponding to the data acquisition instruction is acquired to obtain the controller execution data.

6. A vehicle fault detection device, characterized in that: The device comprises: an acquisition module, configured to acquire vehicle operation data and controller execution data of the vehicle, wherein the vehicle operation data includes environmental parameters of the vehicle, state parameters of the vehicle, and operation parameters; A first determining module, configured to determine an operating scenario of the vehicle based on the vehicle operating data; a second determining module, configured to determine abnormal data in the controller execution data based on the controller standard data corresponding to the operation scenario and the controller execution data; a third determining module, configured to determine a vehicle fault cause corresponding to the abnormal data based on a fault database; The first determination module is specifically configured to classify and process environmental parameters, state parameters, and operating parameters using a scenario classification model to determine the vehicle's operating scenario; or to match the environmental parameters, state parameters, and operating parameters with parameter information corresponding to a preset operating scenario according to their priorities to determine the vehicle's operating scenario; A second determination module is specifically used to obtain controller standard data corresponding to the operation scenario; Comparing the controller standard data corresponding to the operating scenario with the controller execution data to determine abnormal control parameters in the controller execution data that are inconsistent with the controller standard data; a third determining module, specifically configured to query the fault database and determine a fault cause in the fault database that matches the abnormal control parameter as the vehicle fault cause; The fault degree of the vehicle is determined according to the type of the abnormal control parameter and the deviation information between the abnormal control parameter and the controller standard data.

7. A computer-readable storage medium, characterized in that The storage medium stores at least one executable instruction. When the executable instruction is executed on the electronic device, the electronic device executes the operation of the vehicle fault detection method according to any one of claims 1 to 5.

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