Vehicle fault diagnosis methods, devices, electronic equipment and storage media

Abstract

A vehicle fault diagnosis method, device, electronic equipment, and storage medium are disclosed, relating to the field of vehicle fault diagnosis technology. The method includes: when a vehicle malfunctions, quickly identifying the fault code and the fault code information indicated by the fault code based on a fault code list; storing the fault code information at high frequency at the control unit's underlying layer; transmitting the fault code information at low frequency to the CAN network; then transmitting it sequentially through a gateway and a cloud platform to a big data platform; and finally, acquiring, analyzing, and pinpointing the problem through the big data platform, and quickly guiding repairs. This method enables remote fault diagnosis without upgrading the CAN network architecture, increasing the CAN load rate, or requiring repair personnel to go to the site to reproduce the fault, thereby quickly identifying the problem and guiding repairs.

Description

Technical Field

[0001] This application relates to the field of vehicle fault diagnosis technology, and more specifically, to a vehicle fault diagnosis method, apparatus, electronic device and storage medium. Background Technology

[0002] With the rapid development of the automotive industry and the continuous improvement of people's living standards, the number of cars on the road is increasing. Moreover, the types of malfunctions in various powertrain models are becoming more numerous and complex. This necessitates both timely and safe problem-solving, making the rapid identification and resolution of problems increasingly urgent.

[0003] Therefore, how to efficiently identify faults and guide repairs without requiring maintenance personnel to go to the site has become an urgent problem to be solved. Summary of the Invention

[0004] In view of this, embodiments of this application propose a vehicle fault diagnosis method, device, electronic device and storage medium, which can obtain key signals before and after the fault occurs without upgrading the CAN network architecture, increasing the CAN load rate, and without requiring maintenance personnel to go to the site to reproduce the fault, so as to analyze the problem, locate the problem and quickly guide the repair.

[0005] The following technical solution is adopted in this application.

[0006] According to a first aspect of the embodiments of this application, a vehicle fault diagnosis method is provided, applied to a vehicle control unit, wherein the control unit transmits data with a big data platform via a CAN network, the method comprising:

[0007] Based on the fault occurring in the vehicle, a target fault code and target fault information indicated by the target fault code are obtained; the target fault code is a fault code from a list of reproducible fault codes; the target fault information includes at least the fault enabling conditions, fault confirmation conditions, fault confirmation time, or operating parameters at the time of the fault; the target fault information is uploaded to the CAN network at a first time interval greater than or equal to a time threshold; the vehicle is diagnosed based on the diagnostic results obtained from the CAN network; the diagnostic results include at least the fault status, fault location, and fault handling method.

[0008] In some embodiments, the method for obtaining the target fault code of the fault includes: The fault occurring in the vehicle is detected, and the corresponding fault code is determined; if the fault code matches the fault code in the fault code list, the fault code is determined to be the target fault code.

[0009] In some embodiments, after obtaining the target fault code of the fault and the target fault information indicated by the target fault code, the method further includes: The target fault information is stored according to a set second time interval; wherein the second time interval for storing the target fault information is less than the first time interval for uploading the target fault information.

[0010] In some embodiments, the method of storing the target fault information according to a set second time interval includes: The storage duration of the fault is determined; the storage duration is used to indicate the time period before and after the vehicle experiences the fault; the storage space occupied by the fault is determined based on the storage duration and the second time interval; the target fault information is written into the storage space according to the second time interval.

[0011] In some embodiments, before obtaining the target fault code of the fault and the target fault information indicated by the target fault code, the method further includes: Multiple fault levels are set for the fault codes in the fault code list; the fault level is used to indicate the risk level of the fault corresponding to the fault code; based on the target fault code and the fault level, the target fault information collected when the vehicle malfunctions is determined.

[0012] According to a second aspect of the embodiments of this application, a vehicle fault diagnosis method is provided, applied to a big data platform, wherein the infrastructure of the big data platform includes: a vehicle control unit and a server connected to the control unit via a CAN network; the method includes: The control unit acquires the target fault code and the target fault information indicated by the target fault code based on the fault occurring in the vehicle; the target fault code is a fault code from a list of reproducible fault codes; the target fault information includes at least the fault enabling conditions, fault confirmation conditions, fault confirmation time, or operating parameters at the time of the fault; the target fault information is uploaded to the CAN network at a first time interval greater than or equal to a time threshold; the vehicle is diagnosed based on the diagnostic results obtained from the CAN network; the diagnostic results include at least the fault status, fault location, and fault handling method; the server determines the diagnostic result of the target fault based on the target fault information obtained from the CAN network.

[0013] According to a third aspect of the embodiments of this application, a vehicle fault diagnosis device is provided, applied to a vehicle control unit, the control unit transmitting data with a big data platform via a CAN network, the device comprising: An acquisition module is used to acquire, based on the fault occurring in the vehicle, a target fault code and target fault information indicated by the target fault code; the target fault code is a fault code from a list of reproducible fault codes; the target fault information includes at least the fault enabling conditions, fault confirmation conditions, fault confirmation time, or operating parameters at the time of the fault; a transmission module is used to upload the target fault information to the CAN network at a first time interval greater than or equal to a time threshold; a diagnostic module is used to diagnose the vehicle based on diagnostic results acquired from the CAN network; the diagnostic results include at least the fault status, fault location, and fault handling method.

[0014] According to a fourth aspect of the embodiments of this application, a vehicle is provided, the vehicle comprising: a memory for storing executable program code; and a control unit for calling and running the executable program code from the memory, causing the vehicle to perform the above-described method.

[0015] According to a fifth aspect of the embodiments of this application, a big data platform is provided, the infrastructure of which includes: a vehicle control unit and a server connected to the control unit via a CAN network for performing the above-described method.

[0016] According to a sixth aspect of the embodiments of this application, a computer program product is provided, including a computer program, characterized in that the computer program implements the above-described method when executed by a processor.

[0017] In this application's solution, when a vehicle malfunctions, firstly, based on the generated fault codes and fault code list, the target fault code and the target fault information it indicates can be quickly identified. High-frequency storage is used to store the target fault information at the controller's underlying layer, achieving persistent storage of fault information and providing complete raw data support for subsequent fault diagnosis. Specifically, by combining the identified target fault information with the set storage duration and second time interval, the storage space for the target fault is calculated in real time, achieving reasonable allocation of storage resources and avoiding insufficient storage or resource waste. Secondly, the target fault information is transmitted at low frequency to the big data platform via the CAN network, which greatly reduces the transmission frequency and the number of messages, thereby reducing the occupation of the CAN bus by fault-related information. Finally, the big data platform analyzes the target fault information, identifies the problem, and provides technical personnel with repair guidance. The generated diagnostic results are sent to the vehicle's control unit, which diagnoses the vehicle based on the diagnostic results. This allows for the acquisition of key signals before and after the fault without requiring on-site fault reproduction by repair personnel, enabling remote fault diagnosis to quickly identify the problem and guide repair.

[0018] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0020] Figure 1 This is a schematic diagram of a vehicle fault diagnosis method provided in an embodiment of this application.

[0021] Figure 2 This is a flowchart illustrating a vehicle fault diagnosis method provided in an embodiment of this application.

[0022] Figure 3 This is a flowchart illustrating a method for obtaining a target fault code, provided in an embodiment of this application.

[0023] Figure 4 This is a flowchart illustrating a method for storing target fault information provided in an embodiment of this application.

[0024] Figure 5 This is a flowchart illustrating another vehicle fault diagnosis method provided in an embodiment of this application.

[0025] Figure 6 This is a schematic diagram of a remote diagnostic process provided in an embodiment of this application.

[0026] Figure 7 This is a schematic diagram of the structure of a vehicle fault diagnosis device provided in an embodiment of this application.

[0027] Figure 8 This is a schematic diagram of another vehicle fault diagnosis device provided in an embodiment of this application.

[0028] Figure 9 This is a structural schematic diagram of a vehicle provided in an embodiment of this application.

[0029] The accompanying drawings have illustrated specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through specific embodiments. Detailed Implementation

[0030] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0031] In conventional technology, when a vehicle malfunctions, maintenance personnel need to go to the site to diagnose the problem, which increases manpower and time costs. Furthermore, maintenance personnel need to reproduce the fault in order to accurately pinpoint the problem. However, some intermittent faults are often difficult to reproduce. At the same time, the signal period on most CAN buses is now longer and the signal volume is increased, which makes fault analysis difficult and increases the CAN load rate.

[0032] The vehicle fault diagnosis method provided in this application aims to solve the above-mentioned technical problems of the prior art.

[0033] The technical solution of this application and how it solves the above-mentioned technical problems will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0034] Figure 1 This is a schematic diagram illustrating a vehicle fault diagnosis method provided in an embodiment of this application. Figure 1 As shown, the vehicle fault diagnosis method provided in this application embodiment is executed by a first module 100, which includes a control unit 101, a gateway 102, a cloud platform 103, and a big data platform 104.

[0035] In one alternative implementation, the first module 100 refers to a software unit or module. Specifically, the first module 100 is used to identify the frozen frames and key signals of the fault, and to remotely analyze and repair the fault.

[0036] In another alternative implementation, the first module 100 refers to a hardware device.

[0037] For example, the first module 100 may include, but is not limited to, vehicle control strategies, databases, etc.

[0038] For example, the first module 100 may include, but is not limited to, electronic devices with data processing capabilities such as computers, host computers, servers, or data centers.

[0039] Optionally, the first module 100 described above can communicate via a wired or wireless connection. The wired connection may include, but is not limited to, a bus, fiber optic cable, or network cable. The wireless connection may include, for example, transmission control protocol / internet protocol (TCP / IP), wireless local area network protocol (WLAN), and remote direct memory access (RDMA) over converged ethernet (RoCE) network protocol.

[0040] The following is combined Figure 1 The first module 100 shown illustrates the vehicle fault diagnosis method provided in this application embodiment: First, the control unit 101 detects a fault in the vehicle, determines the fault code corresponding to the fault, and determines that the fault code is a target fault code and the target fault information indicated by the target fault code based on a successful match between the fault code and a fault code in the fault code list. Then, the target fault information is uploaded to the CAN network at a first time interval greater than or equal to a time threshold. The control unit 101 also stores the target fault information according to a set second time interval. Second, the CAN network filters and performs address conversion on the target fault information through the gateway 102 and sends it to the cloud platform 103. In addition, the target fault information is stored and forwarded to the big data platform 104 according to the cloud platform protocol and rules. Finally, the big data platform 104 performs online analysis and fault tracing based on the received target fault information, determines the diagnosis result of the target fault information, and transmits the diagnosis result to the control unit 101 via the cloud platform 103, the gateway 102, and the CAN network. The control unit 101 diagnoses the vehicle based on the received diagnosis result.

[0041] Below Figure 1 Based on the first module 100 shown, the vehicle fault diagnosis method provided in the embodiments of this application will be further described, such as... Figure 2 The diagram shows a flowchart of a vehicle fault diagnosis method. In a specific embodiment, this vehicle fault diagnosis method can be applied to, for example... Figure 7 The vehicle fault diagnosis device 700 shown is illustrated below. The specific process of this embodiment will be described below. Of course, it is understood that this method can be executed by a cloud server with computing power.

[0042] The following will address Figure 2The process shown is described in detail and applied to the vehicle control unit. The control unit transmits data with the big data platform through the CAN network. The vehicle fault diagnosis method may specifically include the following steps 201 to 203.

[0043] Step 201: Based on the fault that occurred in the vehicle, obtain the target fault code of the fault and the target fault information indicated by the target fault code; the target fault code is a fault code in a list of fault codes that can be reproduced; the target fault information includes at least the enabling conditions of the fault, the confirmation conditions of the fault, the confirmation time of the fault, or the operating parameters at the time of the fault.

[0044] In this embodiment, the fault code is a set of standardized codes automatically generated by the on-board diagnostics (OBD) system when it detects an abnormality in the vehicle or exceeds a preset threshold. These codes are used to identify the fault type, fault location, and fault status.

[0045] In this embodiment of the application, the fault code list establishes a correspondence mechanism between fault codes, fault information, and vehicle fault levels. The fault codes recorded in the list refer to faults that need to be reproduced, mainly including intermittent vehicle faults, condition-triggered faults, dynamic operating condition faults, communication-related soft faults, sensor / actuator accuracy abnormality faults, non-persistent historical faults, and intermittent functional abnormality faults. The fault information consists of the fault freeze frame and key information.

[0046] In this embodiment, the target fault code is the fault code corresponding to the fault that needs to be reproduced currently occurring in the vehicle; the target fault information is the information required to reproduce the target fault based on the fault code list. For example, information such as catalytic converter oxygen storage, accelerator pedal opening, vehicle speed, brake pedal opening, and actual engine torque.

[0047] For example, since the vehicle's control unit has limited memory and expanding memory would increase costs, and considering that not all faults need to be reproduced for quick identification, such as circuit-level faults of vehicle components, fault codes corresponding to faults that need to be reproduced can be filtered out to save storage space and reduce the load on the CAN network.

[0048] Furthermore, to determine which fault codes require monitoring and which do not, a fault code list can be created to record fault codes that require fault reproduction. For example, if the engine's electric water pump occasionally fails to respond to the desired water pump speed command output by the engine controller after startup, and the actual speed of the engine water pump deviates significantly from the target speed, or the water pump is unresponsive or not working, then the vehicle's control unit needs to monitor the desired speed and actual speed of the engine water pump to pinpoint the operating condition fault. However, if the engine water pump controller circuit is open, monitoring is not required.

[0049] In one implementation, the vehicle's controller unit establishes a vehicle fault monitoring strategy based on the fault code list, including the fault enabling conditions, fault confirmation conditions, fault confirmation time, and operating parameters at the time of the fault, in order to identify the interactive information and perception information that need to be monitored.

[0050] Furthermore, the control unit monitors the feedback signals from various sensors and actuators of the vehicle, as well as the vehicle's operating conditions or system variables, according to the monitoring strategy, and detects in real time whether the vehicle is operating normally.

[0051] For example, sensor feedback signals include engine coolant temperature, engine intake air temperature, ambient temperature, altitude, engine load, engine speed, front oxygen voltage, rear oxygen voltage, and battery SOC (State of Charge); actuator feedback signals include clutch status, accelerator pedal opening, brake pedal opening, gear signal, fan duty cycle, and water pump duty cycle; operating conditions include engine operating status, vehicle operating status, and driving mode; system variables include vehicle speed and desired water pump or fan speed.

[0052] For example, if a vehicle detects a fault and determines that the fault code corresponding to the fault matches a fault code in the fault code list, the control unit records the fault code as the target fault code and determines the target fault information indicated by the target fault code from the fault code list. The control unit collects the target fault information from the feedback signals of various sensors and actuators of the vehicle, as well as the vehicle's operating conditions or system variables, so as to facilitate subsequent maintenance personnel to locate the cause of the fault through the target fault code and the target fault information.

[0053] Step 202: Upload the target fault information to the CAN network at a first time interval greater than or equal to a time threshold.

[0054] In this embodiment, the first time interval is used to indicate low-frequency transmission fault information to the CAN network.

[0055] For example, in order to ensure that the data is not lost when the power is off and that information can be directly read from the control unit when the fault recurs, the control unit transmits the target fault code and target fault information within the storage period to the lower layer of the control unit, and stores the target fault code and target fault information at high frequency at the lower layer of the control unit. This can be understood as writing the signal into the internal hardware storage area of ​​the vehicle's controller to permanently save the information.

[0056] Furthermore, based on the recording of the target fault code and target fault information at the bottom layer of the control unit, in order to reduce the CAN load rate and shorten the signal transmission time of the CAN network, the application layer of the control unit can select to trigger the corresponding target fault information according to the fault code flag bit. The fault code flag bit is a set of status bits used to describe the current state of the target fault code, which can be understood as the status label of the fault code.

[0057] Furthermore, after the control unit packages the target fault information at its lower level, it transmits the packaged target fault information to the CAN network at a low frequency according to the transmission period defined by the CAN network, for example, the first time interval can be set to 10 seconds. Since the packaging and transmission are performed at a low frequency according to the predefined period of the CAN network at the lower level of the control unit, rather than being sent to the CAN network immediately when a fault is triggered, the transmission frequency and the number of messages can be greatly reduced, thereby reducing the occupation of the CAN bus by fault-related information and significantly reducing the load rate of the vehicle's CAN network.

[0058] Step 203: Perform a diagnosis on the vehicle based on the diagnostic results obtained from the CAN network; the diagnostic results include at least the fault status, fault location, and fault handling method.

[0059] In this embodiment of the application, the diagnostic result is obtained by the big data platform based on the target fault information received from the CAN network, or by relevant personnel through fault analysis and tracing by downloading the target fault information from the big data platform.

[0060] For example, after the packaged target fault information is transmitted to the CAN network at low frequency, the CAN network filters and performs address translation on the data packets through the gateway and devices before sending them to the cloud platform to block external attacks and protect the internal network, thus realizing the firewall function.

[0061] Furthermore, in accordance with the cloud platform protocol and rules, data packets are received and stored in the cloud platform's storage area. After parsing the address-translated data packets, the information required for fault reproduction is forwarded to the big data platform. The big data platform receives the data tracking messages sent by the cloud platform, which contain target fault information, namely freeze frames and key signals. It completes the data parsing of the data tracking messages and stores the target fault information.

[0062] In addition, based on real-time capture and parsing of target fault information, combined with fault code flags, the big data platform can monitor the real-time status of fault codes, distinguishing between current faults, historical faults, and permanent faults. When a new fault code is detected, it can trigger an early warning, such as a platform pop-up or message push. Simultaneously, the parsed target fault information is temporarily cached and persistently stored, with the caching period configurable as needed, such as 7 days or 30 days, ensuring that the target fault information can be quickly retrieved within the platform.

[0063] For example, the big data platform restores the cached target fault information into complete operating condition data at the moment the fault occurred, including all original snapshot information such as engine speed, vehicle speed, load, temperature, voltage, and mileage. The restored data is completely consistent with the target fault information stored at the controller's underlying layer, ensuring the authenticity and integrity of the "on-site snapshot." Furthermore, based on the restored target fault information, online analysis and data download are performed to meet the fault diagnosis and data retention needs of relevant technical personnel, achieving efficient data utilization.

[0064] For example, relevant technicians can generate diagnostic results, including fault status, fault location, and fault handling methods, by analyzing freeze frames and key signals before and after the fault. This shortens the time to pinpoint the cause of the fault. In addition, for emergency or dangerous fault events, early warnings or repair guidance can be provided. Furthermore, for abnormal events of the vehicle, an active triggering mechanism and a problem database can be established to achieve secondary data mining.

[0065] In this embodiment, by using a fault code list, when a vehicle malfunctions, the fault code and the fault code information it indicates can be quickly identified. The fault code information is stored at a high frequency at the control unit's underlying layer and transmitted at a low frequency via the CAN network to the big data platform. While ensuring the integrity of the operating data before and after the fault, this significantly reduces the transmission frequency and the number of messages, thereby reducing the CAN bus's usage of fault-related information. Finally, the big data platform is used to acquire, analyze, and pinpoint the problem, providing rapid repair guidance. This enables the acquisition of key signals before and after the fault without upgrading the CAN network architecture or increasing the CAN load rate, and without requiring repair personnel to go to the site to reproduce the fault. This allows for remote fault diagnosis, rapid problem identification, and repair guidance.

[0066] Regarding how to obtain the target fault code, embodiments of this application provide an optional implementation method, such as... Figure 3 The flowchart shown is a method for obtaining a target fault code, which may specifically include the following steps 301 to 306.

[0067] Step 301: Set multiple fault levels for the fault codes in the fault code list; the fault level is used to indicate the risk level of the fault corresponding to the fault code.

[0068] In this embodiment of the application, since the current fault management mode is becoming increasingly complex, in order to adapt to the management mode of multiple controllers reporting vertically and hierarchically, it is necessary to classify the fault levels of the whole vehicle. The fault levels of the whole vehicle can be divided into four levels according to the degree of risk of the fault: affecting vehicle safety, affecting vehicle power, affecting vehicle function, and warning type. For example, faults affecting vehicle safety include vehicle high voltage power failure and vehicle emergency power failure; faults affecting vehicle power include drive function disabling fault and vehicle drive performance degradation fault; and faults affecting vehicle function or warning type include alarm faults and minor faults.

[0069] Step 302: Based on the target fault code and the fault level, determine the target fault information collected when the vehicle malfunctions.

[0070] For example, different fault levels require different amounts of fault information to be collected. A corresponding mechanism can be established between fault codes, vehicle fault levels, freeze frames, and key specific signals to determine how many key signals are needed for the analysis of each fault. At the same time, based on the matching relationship between actual vehicle faults and fault codes, once an abnormal event is determined to have occurred in the vehicle, the fault codes can be traced through the abnormal event. The fault codes correspond to high-frequency freeze frames and key signals, which can quickly determine the target fault information that needs to be collected when the vehicle is faulty.

[0071] Step 303: Based on the fault that occurred in the vehicle, obtain the target fault code of the fault and the target fault information indicated by the target fault code; the target fault code is a fault code in a list of fault codes that can be reproduced; the target fault information includes at least the enabling conditions of the fault, the confirmation conditions of the fault, the confirmation time of the fault, or the operating parameters at the time of the fault.

[0072] Step 303 further includes steps 313 to 323.

[0073] Step 313: Detect the fault that occurred in the vehicle and determine the fault code corresponding to the fault.

[0074] Step 323: Based on the successful match between the fault code and the fault codes in the fault code list, the fault code is determined to be the target fault code.

[0075] In this embodiment of the application, in conjunction with the content of step 201, the vehicle monitors the vehicle's operating status in real time. When a fault occurs, a corresponding fault code is generated. If the fault code matches a fault code in the fault code list, it means that the fault needs to be reproduced in subsequent diagnosis of the fault, thereby determining the fault as the target fault and the fault code as the target fault code.

[0076] Step 304: Store the target fault information according to the set second time interval; wherein the second time interval for storing the target fault information is less than the first time interval for uploading the target fault information.

[0077] For example, the storage duration can be set to 3 seconds before the fault occurs to 7 seconds after the fault occurs, and the second time interval can be set between 10ms and 100ms. For example, if the second time interval is 10ms, the control unit transmits the target fault code and target fault information from 3 seconds before the fault occurs to 7 seconds after the fault occurs to the underlying layer of the control unit, and stores the target fault code and target fault information at the underlying layer of the control unit at a frequency of once every 10ms.

[0078] Step 305: Upload the target fault information to the CAN network at a first time interval greater than or equal to a time threshold.

[0079] Step 306: Perform a diagnosis on the vehicle based on the diagnostic results obtained from the CAN network; the diagnostic results include at least the fault status, fault location, and fault handling method.

[0080] The specific steps of steps 303 and 305 to 306 can be found in steps 201 to 203, and will not be repeated here.

[0081] In this embodiment, a high-frequency storage method is used to store fault information at the controller's underlying layer, thereby achieving persistent storage of fault-related freeze frames and key signals. This ensures that no data on the operating conditions before and after the fault is missed or lost, providing complete and accurate raw data support for subsequent platform analysis and fault analysis.

[0082] Based on the above, this application provides an optional implementation method for storing target fault information, such as... Figure 4 The flowchart shown is a method for storing target fault information, which may specifically include the following steps 401 to 406.

[0083] Step 401: Based on the fault that occurred in the vehicle, obtain the target fault code of the fault and the target fault information indicated by the target fault code; the target fault code is a fault code in a list of fault codes that can be reproduced; the target fault information includes at least the enabling conditions of the fault, the confirmation conditions of the fault, the confirmation time of the fault, or the operating parameters at the time of the fault.

[0084] Step 402: Determine the storage duration of the fault; the storage duration is used to indicate the time period before and after the vehicle experiences the fault.

[0085] In this embodiment of the application, referring to step 304, the storage duration is set to 3 seconds before the fault occurs and 7 seconds after the fault occurs.

[0086] Step 403: Determine the storage space occupied by the fault based on the storage duration and the second time interval.

[0087] For example, referring to step 304, based on the storage duration of 3 seconds before the fault occurs to 7 seconds after the fault occurs and the storage frequency of 10ms, as well as the freeze frames and key signals corresponding to the fault codes, it can be determined that 1000 sets of freeze frames and key signals need to be stored within 10 seconds. Then, based on the signals contained in the freeze frames and key signals and the bytes occupied by each signal, the storage space size is calculated.

[0088] Step 404: Write the target fault information into the storage space according to the second time interval.

[0089] For example, the control unit allocates a fixed storage space according to the required storage space size, and this storage space has an indelible function.

[0090] Step 405: Upload the target fault information to the CAN network at a first time interval greater than or equal to a time threshold.

[0091] Step 406: Perform a diagnosis on the vehicle based on the diagnostic results obtained from the CAN network; the diagnostic results include at least the fault status, fault location, and fault handling method.

[0092] The specific steps of steps 401, 405 and 406 can be found in steps 201 to 203, and will not be repeated here.

[0093] In this embodiment of the application, by acquiring fault information and combining it with the set storage duration and the second time interval, the storage space of the fault is calculated in real time, thereby realizing the reasonable allocation of storage resources and avoiding insufficient storage or waste of resources.

[0094] Below Figure 1Based on the first module 100 shown, another vehicle fault diagnosis method provided in the embodiments of this application will be further described, such as... Figure 5 The flowchart shown illustrates another vehicle fault diagnosis method. In a specific embodiment, this vehicle fault diagnosis method can be applied to, for example... Figure 8 Another vehicle fault diagnosis device 800 is shown.

[0095] The following will address Figure 5 The process shown is described in detail and applied to a big data platform. The infrastructure of the big data platform includes: a vehicle control unit and a server connected to the control unit via a CAN network; the vehicle fault diagnosis device method may specifically include the following steps 501 to 502.

[0096] Step 501: The control unit acquires the target fault code and the target fault information indicated by the target fault code based on the fault occurring in the vehicle; the target fault code is a fault code from a list of reproducible fault codes; the target fault information includes at least the fault enabling conditions, fault confirmation conditions, fault confirmation time, or operating parameters at the time of the fault; the target fault information is uploaded to the CAN network at a first time interval greater than or equal to a time threshold; the vehicle is diagnosed based on the diagnostic results obtained from the CAN network; the diagnostic results include at least the fault status, fault location, and fault handling method.

[0097] Step 502: The server determines the diagnostic result of the target fault based on the target fault information obtained from the CAN network.

[0098] For example, the big data platform receives embedded messages transmitted at low frequency via the CAN network from the controller's underlying layer. These messages include fault codes, freeze frames, and key signals. The platform then performs data parsing and storage, enabling real-time monitoring of fault codes and restoration of frozen frame caches. It also supports online analysis and download of frozen frame data. Finally, the platform performs fault analysis and tracing through multi-dimensional data correlation and generates diagnostic results, providing data support for vehicle fault diagnosis and maintenance optimization.

[0099] Furthermore, the big data platform enables data transmission, processing, analysis, and tracing, and transmits diagnostic results back to the control unit via the CAN network, achieving full-process coverage of fault detection and location.

[0100] exist Figures 2 to 5 Based on the vehicle fault diagnosis method shown, the embodiments of this application further illustrate the vehicle fault diagnosis method, such as... Figure 6 The diagram shows a flowchart of a remote diagnostic process, which may include the following:

[0101] In one implementation, the controller monitoring module monitors the vehicle's operation in real time by combining sensor, actuator, and feedback signals with vehicle operating conditions or system variables. For the freeze frame and critical signal confirmation module, due to limited vehicle controller memory and the increased cost of expanding memory, fault codes are filtered to quickly identify those requiring fault reproduction. For the high-frequency storage module for freeze frames and critical signals, the storage space size is calculated based on the required storage time, and a fixed storage space is allocated, ensuring it is non-erasable. For the freeze frame and critical signal selection module, the corresponding freeze frame and critical signal are selected based on a pre-defined fault matching rule base, determined by an abnormal event. Finally, the freeze frame and critical signal output module transmits the freeze frame and critical signal to the CAN network at a low frequency according to a predefined period.

[0102] Furthermore, for gateways and devices, they are used to filter and address translate data packets and implement firewall functions, sending data packets carrying freeze frames and key signals to the cloud platform; for the cloud platform, they receive and parse data packets according to cloud platform protocols and rules, and simultaneously store and forward data packets to the big data platform; for the big data platform, by receiving raw data of embedded point messages, parsing embedded point messages, and caching and restoring fault code monitoring records, freeze frames, etc., they analyze and download data packets online to achieve fault analysis and source tracing.

[0103] To achieve the functions of the above embodiments, the vehicle fault diagnosis device method includes hardware structures and / or software modules corresponding to each function. Those skilled in the art should readily recognize that, based on the units and method steps described in conjunction with the embodiments disclosed in this application, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application scenario and design constraints of the technical solution.

[0104] exist Figures 2 to 6 Based on the vehicle fault diagnosis method shown, this application further describes a vehicle fault diagnosis device provided in its embodiments, such as... Figure 7 The diagram shows the structure of a vehicle fault diagnosis device 700, which includes: an acquisition module 710, a transmission module 720, and a diagnosis module 730.

[0105] The acquisition module 710 is configured to acquire, based on the fault occurring in the vehicle, a target fault code for the fault and target fault information indicated by the target fault code; the target fault code is a fault code from a list of reproducible fault codes; the target fault information includes at least the fault enabling conditions, fault confirmation conditions, fault confirmation time, or operating parameters at the time of the fault; wherein, the acquisition module 710 may include, for example, Figure 1 The control unit 101 in the first module 100 shown.

[0106] Transmission module 720 is configured to upload the target fault information to the CAN network at a first time interval greater than or equal to a time threshold; wherein, transmission module 720 may include, for example, Figure 1 The control unit 101 in the first module 100 shown.

[0107] The diagnostic module 730 is used to diagnose the vehicle based on diagnostic results obtained from the CAN network; the diagnostic results include at least the fault status, fault location, and fault handling method; wherein, the diagnostic module 730 may include, for example, Figure 1 The control unit 101 in the first module 100 shown.

[0108] In some embodiments, the acquisition module 710 includes: detecting a fault occurring in the vehicle and determining a fault code corresponding to the fault; and determining the fault code as the target fault code based on a successful match between the fault code and a fault code in the fault code list.

[0109] In some embodiments, the acquisition module 710 further includes: storing the target fault information according to a set second time interval; wherein the second time interval for storing the target fault information is less than the first time interval for uploading the target fault information.

[0110] In some embodiments, the acquisition module 710 further includes: determining the storage duration of the fault; the storage duration is used to indicate the time period before and after the vehicle experiences the fault; determining the storage space occupied by the fault based on the storage duration and the second time interval; and writing the target fault information into the storage space according to the second time interval.

[0111] In some embodiments, the acquisition module 710 further includes: setting multiple fault levels for fault codes in the fault code list; the fault level is used to indicate the risk level of the fault corresponding to the fault code; and determining the target fault information to be collected when the vehicle malfunctions based on the target fault code and the fault level.

[0112] exist Figures 2 to 6Based on the vehicle fault diagnosis method shown, this application also provides another vehicle fault diagnosis device for further explanation, such as... Figure 8 The schematic diagram of another vehicle fault diagnosis device shown is applied to a big data platform. The infrastructure of the big data platform includes: a vehicle control unit and a server connected to the control unit via a CAN network. The other vehicle fault diagnosis device 800 includes: a first processing module 810 and a second processing module 820.

[0113] The first processing module 810 is configured to: acquire, based on a fault occurring in the vehicle, a target fault code and target fault information indicated by the target fault code; the target fault code is a fault code from a list of reproducible fault codes; the target fault information includes at least the fault enabling conditions, fault confirmation conditions, fault confirmation time, or operating parameters at the time of the fault; upload the target fault information to the CAN network at a first time interval greater than or equal to a time threshold; and diagnose the vehicle based on diagnostic results obtained from the CAN network; the diagnostic results include at least the fault status, fault location, and fault handling method; wherein, the first processing module 810 may include, for example,... Figure 1 The control unit 101 in the first module 100 shown.

[0114] The second processing module 820 is used by the server to determine the diagnostic result of the target fault based on the target fault information obtained from the CAN network; wherein, the second processing module 820 may include, for example, Figure 1 The big data platform 104 in the first module 100 shown.

[0115] According to one aspect of the embodiments of this application, Figure 9 This is a schematic diagram of the structure of a vehicle provided in an embodiment of this application. Figure 9 As shown, the vehicle 900 includes a control unit 910 and one or more memory units 920. The one or more memory units 920 are used to store program instructions executed by the control unit 910. When the control unit 910 executes the program instructions, it implements the vehicle fault diagnosis method described above.

[0116] Furthermore, the control unit 910 may include one or more processing cores. The control unit 910 runs or executes instructions, programs, code sets, or instruction sets stored in the memory 920, and calls data stored in the memory 920. Optionally, the control unit 910 may be implemented using at least one hardware form selected from Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The control unit 910 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and Modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the displayed content; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor and may be implemented using a separate communication chip.

[0117] According to one aspect of this application, a computer-readable storage medium is also provided, which may be included in the vehicle described in the above embodiments; or it may exist independently and not installed in the vehicle. The computer-readable storage medium carries computer-readable instructions that, when executed by a processor, implement the methods in any of the above embodiments.

[0118] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. Computer-readable storage media can be, for example, but not limited to: electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such transmitted data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0119] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.

[0120] 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 this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated 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 a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, 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.

[0121] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0122] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A vehicle fault diagnosis method, characterized in that, A control unit applied to a vehicle, wherein the control unit transmits data to a big data platform via a CAN network, including: Based on the fault that occurred in the vehicle, the target fault code and the target fault information indicated by the target fault code are obtained; the target fault code is a fault code in a list of fault codes that can be reproduced; the target fault information includes at least the enabling conditions of the fault, the confirmation conditions of the fault, the confirmation time of the fault, or the operating parameters at the time of the fault. The target fault information is uploaded to the CAN network at a first time interval greater than or equal to a time threshold. The vehicle is diagnosed based on the diagnostic results obtained from the CAN network; the diagnostic results include at least the fault status, fault location, and fault handling method.

2. The method according to claim 1, characterized in that, The method for obtaining the target fault code of the fault includes: The faults occurring in the vehicle are detected, and the corresponding fault codes are determined. If the fault code matches successfully with the fault codes in the fault code list, the fault code is determined to be the target fault code.

3. The method according to claim 1, characterized in that, After acquiring the target fault code and the target fault information indicated by the target fault code, the method further includes: The target fault information is stored according to a set second time interval; wherein the second time interval for storing the target fault information is less than the first time interval for uploading the target fault information.

4. The method according to claim 3, characterized in that, The method of storing the target fault information according to a set second time interval includes: Determine the storage duration of the fault; the storage duration is used to indicate the time period before and after the vehicle experiences the fault; Based on the storage duration and the second time interval, determine the storage space occupied by the fault; The target fault information is written into the storage space according to the second time interval.

5. The method according to claim 1, characterized in that, Before acquiring the target fault code and the target fault information indicated by the target fault code, the method further includes: Multiple fault levels are set for the fault codes in the fault code list; the fault level is used to indicate the risk level of the fault corresponding to the fault code. Based on the target fault code and the fault level, the target fault information collected when the vehicle malfunctions is determined.

6. A vehicle fault diagnosis method, characterized in that, The method is applied to a big data platform, the infrastructure of which includes: a vehicle control unit and a server connected to the control unit via a CAN network; the method includes: The control unit acquires the target fault code and the target fault information indicated by the target fault code based on the fault occurring in the vehicle; the target fault code is a fault code from a list of reproducible fault codes; the target fault information includes at least the fault enabling conditions, fault confirmation conditions, fault confirmation time, or operating parameters at the time of the fault; the control unit uploads the target fault information to the CAN network at a first time interval greater than or equal to a time threshold; and diagnoses the vehicle based on the diagnostic results obtained from the CAN network; the diagnostic results include at least the fault status, fault location, and fault handling method. The server determines the diagnostic result of the target fault based on the target fault information obtained from the CAN network.

7. A vehicle fault diagnosis device, characterized in that, A control unit applied to a vehicle, the control unit transmitting data with a big data platform via a CAN network, the device comprising: The acquisition module is used to acquire, based on the fault that occurred in the vehicle, the target fault code of the fault and the target fault information indicated by the target fault code; the target fault code is a fault code in a list of fault codes that can be reproduced; the target fault information includes at least the enabling conditions of the fault, the confirmation conditions of the fault, the confirmation time of the fault, or the operating parameters at the time of the fault. The transmission module is used to upload the target fault information to the CAN network at a first time interval greater than or equal to a time threshold. The diagnostic module is used to diagnose the vehicle based on diagnostic results obtained from the CAN network; the diagnostic results include at least the fault status, fault location, and fault handling method.

8. A vehicle, characterized in that, The vehicle includes: a memory for storing executable program code; and a control unit for calling and running the executable program code from the memory, causing the vehicle to perform the method as described in any one of claims 1 to 6.

9. A big data platform, characterized in that, The infrastructure of the big data platform includes: a vehicle control unit and a server connected to the control unit via a CAN network, for performing the method as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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