Vehicle data processing method and device, electronic equipment and storage medium

Abstract

Embodiments of the present application disclose a vehicle data processing method and device, electronic equipment and a storage medium. The method is applied to an electronic control unit, and comprises the following steps: obtaining a data processing request from a diagnostic device, wherein the data processing request comprises a target data item and a function identifier, the target data item is used to indicate a vehicle data type that needs to be obtained, and the function identifier is used to indicate a data processing rule; obtaining vehicle data corresponding to the vehicle data type in response to the target data item, to obtain a group of vehicle data; processing each group of vehicle data based on the data processing rule in response to the function identifier, to obtain a processing result corresponding to the data processing rule in each group of vehicle data; and sending the processing result and the function identifier to the diagnostic device. By using the embodiments of the present application, the communication resources of the vehicle bus can be reduced when the vehicle data is obtained through the diagnostic device.

Description

Technical Field

[0001] This invention relates to the field of vehicle technology, and more particularly to vehicle data processing methods, apparatus, electronic devices, and storage media. Background Technology

[0002] Currently, acquiring vehicle data is a crucial step in vehicle diagnostics to support subsequent vehicle condition analysis and diagnosis.

[0003] However, when acquiring vehicle data, diagnostic equipment needs to continuously send requests to the vehicle to obtain the data. This is especially true when long-term data collection is required, which consumes a large amount of vehicle bus communication resources. Summary of the Invention

[0004] To address the aforementioned issues, embodiments of the present invention provide a vehicle data processing method, apparatus, electronic device, and storage medium that can reduce the occupation of vehicle bus communication resources when acquiring vehicle data through diagnostic equipment.

[0005] In a first aspect, embodiments of the present invention provide a vehicle data processing method, including: A data processing request is obtained from the diagnostic device. The data processing request includes a target data item and a function identifier. The target data item indicates the type of vehicle data to be acquired, and the function identifier indicates the data processing rules. In response to the target data item, vehicle data corresponding to the vehicle data type is obtained to obtain group a of vehicle data; In response to the function identifier, each group of vehicle data is processed based on the data processing rules to obtain the processing result corresponding to the data processing rules in each group of vehicle data; The processing result and the function identifier are sent to the diagnostic device.

[0006] Secondly, embodiments of the present invention provide a vehicle data processing device, the device comprising an acquisition unit and a processing unit; The acquisition unit is used to acquire a data processing request from the diagnostic device. The data processing request includes a target data item and a function identifier. The target data item is used to indicate the type of vehicle data to be acquired, and the function identifier is used to indicate the data processing rules. The processing unit is used to respond to the target data item, obtain vehicle data corresponding to the vehicle data type, and obtain a set of vehicle data; In response to the function identifier, each group of vehicle data is processed based on the data processing rules to obtain the processing result corresponding to the data processing rules in each group of vehicle data; The processing result and the function identifier are sent to the diagnostic device.

[0007] Thirdly, embodiments of the present invention provide an electronic device, the electronic device including a processor and a memory, the processor being connected to the memory, the memory being used to store a computer program, and the processor being used to execute the computer program stored in the memory, so that the electronic device performs the method as described in the first aspect.

[0008] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program that is executed by a processor to implement the method described in the first aspect.

[0009] Fifthly, embodiments of this application provide a computer program product, the computer program product including a non-transitory computer-readable storage medium storing a computer program, the computer being operable to perform the method as described in the first aspect.

[0010] Implementing the embodiments of this application has the following beneficial effects: In this embodiment, a data processing request is first obtained from the diagnostic device. This request includes a target data item and a function identifier. The target data item indicates the type of vehicle data to be acquired, and the function identifier indicates the data processing rules. Then, in response to the target data item, vehicle data corresponding to the vehicle data type is acquired, resulting in group a of vehicle data. Next, in response to the function identifier, each group of vehicle data is processed based on the data processing rules to obtain the processing result corresponding to the rules in each group. Finally, the processing result and function identifier are sent to the diagnostic device. Thus, by having the electronic control unit acquire and process vehicle data according to the data processing request, obtain the processing result, and then send the processing result and function identifier to the diagnostic device, the number of communications between the electronic control unit and the diagnostic device is reduced when acquiring vehicle data through the diagnostic device, thereby reducing the occupation of communication resources on the vehicle bus. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of the present invention or the background art, the drawings used in the embodiments of the present invention or the background art will be described below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 This is a schematic diagram of the architecture of a vehicle data processing system provided in an embodiment of this application; Figure 2 This is a flowchart of a vehicle data processing method provided in an embodiment of this application; Figure 3 This is a schematic diagram of a target electronic control unit determination method provided in an embodiment of this application; Figure 4 This is a schematic diagram of an execution time node provided in an embodiment of this application; Figure 5 This is a schematic diagram of a splicing method provided in an embodiment of this application; Figure 6 This is a schematic diagram of the data content of a data processing request provided in an embodiment of this application; Figure 7 This is a schematic diagram of the structure of a vehicle data processing device provided in an embodiment of this application; Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0013] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0014] The terms "first," "second," "third," and "fourth," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or modules is not limited to the listed steps or modules, but may optionally include steps or modules not listed, or may optionally include other steps or modules inherent to these processes, methods, products, or devices.

[0015] In this document, the term "embodiment" means that a particular feature, result, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0016] The Electronic Control Unit (ECU) is the core control module of an automotive electronic system. It precisely regulates the engine, transmission, and other powertrain systems by monitoring sensor data in real time, optimizing fuel efficiency and emissions. It manages safety functions such as the Anti-lock Braking System (ABS) and Electronic Stability Program (ESP) to ensure driving stability. It controls the vehicle's electronic devices (such as lights and air conditioning) to enhance comfort. It supports intelligent driving assistance systems (such as adaptive cruise control and automatic parking) and enables data exchange between systems via the Controller Area Network (CAN) bus. It also possesses fault diagnosis and Over-The-Air (OTA) upgrade capabilities to ensure efficient, safe, and intelligent vehicle operation.

[0017] Vehicles contain multiple ECUs. Here are some common ECUs and their functions: Engine Control Unit (ECU): Primarily controls engine operation, including fuel injection, ignition timing, throttle opening, and exhaust gas recirculation. It monitors various engine parameters, such as engine speed, temperature, and intake air volume, using sensors. Based on preset programs and algorithms, it adjusts the engine's operating state to achieve optimal performance, fuel economy, and emissions control.

[0018] Transmission control unit: Responsible for controlling the shifting operation of the automatic transmission. Based on signals such as vehicle speed, engine speed, and accelerator pedal position, it precisely controls the shift timing and shift quality to ensure that the vehicle obtains the appropriate gear ratio under different driving conditions, thereby improving driving performance and fuel efficiency.

[0019] Body control module: Manages various electrical devices and functions of the vehicle body, such as door locks, window regulators, headlight control, windshield wipers, and anti-theft systems. It coordinates the operation of these devices to achieve intelligent body control, improving vehicle comfort and safety.

[0020] Electronic Stability Program Control Unit (ESC): Also known as the vehicle's electronic stability system, it monitors the vehicle's driving status, such as speed, steering angle, and lateral acceleration, to determine in real time whether the vehicle is at risk of losing control. When it detects instability such as skidding or fishtailing, it automatically applies different braking forces to each wheel and adjusts the engine's output torque to help the driver maintain control of the vehicle, improving driving stability and safety.

[0021] Airbag control unit: Monitors vehicle collision signals and, upon detecting a collision, quickly triggers the corresponding airbags and seatbelt pretensioners to protect passengers from injury. It uses devices such as acceleration sensors to sense the intensity and direction of the collision, determines whether airbag deployment is necessary based on a preset algorithm, and controls the airbag inflation rate and pressure.

[0022] Smart key control unit: Responsible for communicating with the vehicle's smart key to enable keyless entry and start functions. When a user carrying the smart key approaches the vehicle, the key's signal is automatically detected, and the doors are unlocked. After entering the vehicle, the user does not need to insert the key; simply pressing the start button will verify the key's legitimacy and start the engine.

[0023] Infotainment system control unit: Controls the vehicle's infotainment system, including functions such as audio and video playback, navigation, Bluetooth connectivity, and vehicle information display. It is typically connected to in-vehicle displays, speakers, microphones, and other devices to provide users with a wealth of entertainment and information services.

[0024] Battery Management System (BMS): Primarily used in electric or hybrid vehicles, it manages the charging, discharging, power monitoring, and battery balancing of the battery pack. It monitors parameters such as voltage, current, and temperature of the battery pack in real time to assess the battery's condition and take appropriate measures to protect the battery, extend its lifespan, and ensure the vehicle's power performance and safety.

[0025] See Figure 1 , Figure 1 This is a schematic diagram of the architecture of a vehicle data processing system provided in an embodiment of this application. The vehicle data processing system includes a diagnostic device and an electronic control unit (ECU). The diagnostic device and the ECU interact with each other, for example, the diagnostic device sends a data processing request to the ECU, and the ECU sends the processing result and function identifier to the diagnostic device.

[0026] It should be noted that the vehicle data processing method provided in this application embodiment is applied to the electronic control unit of a vehicle.

[0027] See Figure 2 , Figure 2 This is a flowchart illustrating a vehicle data processing method provided in an embodiment of this application. The vehicle data processing method provided in this embodiment includes, but is not limited to, the following steps: Step S101: Obtain a data processing request from the diagnostic device; The data processing request includes a target data item and a function identifier. The target data item indicates the type of vehicle data to be acquired, and the function identifier indicates the data processing rules. Step S102: In response to the target data item, obtain the vehicle data corresponding to the vehicle data type to obtain group a of vehicle data; Step S103: In response to the function identifier, process each group of vehicle data based on the data processing rules to obtain the processing result corresponding to the data processing rules in each group of vehicle data; Step S104: Send the processing results and function identifiers to the diagnostic device.

[0028] In one possible embodiment, a data processing request is obtained from the diagnostic device. First, the device receives instructions input by a technician through its human-machine interface, parses and encapsulates these instructions into a data processing request, and sends it to the electronic control unit (ECU) via a communication interface, such as a CAN bus or Ethernet. The ECU's communication module monitors network port or bus signals. Upon receiving a data processing request, it acquires and validates the request to ensure it conforms to a preset protocol specification, such as JSON or XML format requirements.

[0029] In a specific embodiment, a technician selects target data items and statistical content on the diagnostic device, and the device automatically generates a data processing request. Different data processing requests may contain the same data items and formats, but may have different statistical functions.

[0030] For details, please refer to Figure 3 , Figure 3 This is a schematic diagram of a target electronic control unit (ECU) determination method provided in an embodiment of this application. A data processing request is received by the vehicle bus. Each ECU determines whether to execute the operation corresponding to the data processing request based on the request. For example, the first, second, third, fourth, and fifth ECUs obtain a data processing request from the vehicle bus and first determine the target ECU from among the five ECUs based on the request. Specifically, all five ECUs receive the data processing request and, based on the target data item and function identifier in the request, determine whether they have stored the corresponding type of vehicle data and whether they have the ability to execute the corresponding data processing rules. If an ECU determines that it can process the request, it becomes the target ECU and continues to execute the subsequent data processing flow. If all ECUs cannot process the request, an error message is returned to the diagnostic device via the vehicle bus, indicating that the data processing task cannot be completed. This makes vehicle data processing more flexible and efficient, enabling dynamic allocation of processing tasks according to actual needs, improving resource utilization and data processing efficiency.

[0031] In one possible embodiment, after obtaining a data processing request from the diagnostic device, the obtained data processing request is decoded to separate the target data item and function identifier. For example, if the data processing request is transmitted in a target format, it is decoded and extracted using a target parsing library in a programming language. The validity of the target data item and function identifier is verified by comparing it with a predefined dictionary or enumeration list to confirm that it is within the range of valid values. If invalid data exists, a request error message is returned to the diagnostic device.

[0032] In one possible embodiment, in response to a target data item, vehicle data corresponding to the vehicle data type is obtained, resulting in a set of vehicle data, where a is a positive integer. The target data item can be one or more items. When there is only one target data item, a is also 1; when there are multiple target data items, a is an integer greater than 1, and the value of a matches the number of target data items. Based on the target data item, the corresponding vehicle data is retrieved from the vehicle data repository. For example, if the target data item is "vehicle speed," relevant records are queried from a table or data structure storing vehicle speed data. The vehicle data repository can be a local database, a memory cache, or obtained from the ECU via real-time communication.

[0033] Specifically, group A of vehicle data refers to vehicle-related information comprising multiple different sets or batches. Each set of data can independently describe the characteristics, status, or operational status of a vehicle in a certain aspect or within a certain time period. This data may cover the following aspects: Basic vehicle information: such as vehicle model, chassis number, production date, vehicle color, etc. Each set of data corresponds to these basic attributes of a different individual vehicle.

[0034] Driving data, such as vehicle speed, mileage, fuel consumption, and engine speed, may be grouped and recorded according to different driving segments, time intervals, or driving behaviors to analyze vehicle driving performance and energy consumption.

[0035] Fault data includes various fault codes, fault descriptions, and fault occurrence times. Different sets of data can correspond to different fault events or fault conditions within different time periods, which helps in fault diagnosis and vehicle maintenance.

[0036] Sensor data: Data collected by various sensors on the vehicle, such as temperature sensors, pressure sensors, position sensors, etc. Each set of data may represent the measurement value of different sensors at a specific time or under specific operating conditions, and is used to monitor the operating status of various components of the vehicle.

[0037] Maintenance and repair data: Records information such as the time, items, repair personnel, and replaced parts for each vehicle maintenance and repair. Different sets of data correspond to different maintenance and repair records, making it easy to track the vehicle's maintenance history and maintenance cycle.

[0038] For example, if the target data items are vehicle speed and temperature, then the number of vehicle data sets is 2. The two sets of vehicle data can be represented by arrays. For example, the vehicle data corresponding to vehicle speed can be [50, 53, 55, 57, 60, 55], and the vehicle data corresponding to temperature can be [38, 39, 40, 41, 39, 40].

[0039] Furthermore, if the data is stored in different locations, such as some data in the engine ECU and some in the transmission ECU, it is necessary to send a data request command to the corresponding ECU through the vehicle's internal communication network and wait for the ECU to respond and return the data, and finally integrate them to form group a of vehicle data.

[0040] In one possible embodiment, in response to a function identifier, each group of vehicle data is processed based on data processing rules to obtain the processing result corresponding to the data processing rule in each group of vehicle data. The specific data processing rule is determined according to the function identifier. For example, if the function identifier is "maximum value calculation," the corresponding calculation function is activated. Then, for each group of vehicle data, the data processing rule is executed sequentially. Taking the calculation of the average value as an example, the values ​​in each group of data are traversed, summed, and divided by the number of data points to obtain the average value. If data filtering is required, data that meets the requirements is filtered out according to set conditions.

[0041] During the processing, any abnormal situations that may occur are captured and handled, such as missing data or incorrect data types. Abnormal information is recorded through logs, and a strategy of filling in or skipping abnormal data with default values ​​is adopted as appropriate.

[0042] In one possible embodiment, processing results and function identifiers are sent to the diagnostic device. The processing results and function identifiers for each set of vehicle data are encapsulated into a structured data format, such as constructing an object containing function identifiers and a list of processing results. The encapsulated data is sent back to the diagnostic device through the same communication channel as the received request. After receiving the data, the diagnostic device parses the data and displays the processing results on the interface for easy viewing and analysis by technicians.

[0043] In this embodiment, when acquiring vehicle data through diagnostic equipment, the number of communications between the electronic control unit and the diagnostic equipment is reduced, thereby reducing the occupation of communication resources on the vehicle bus. Furthermore, during data acquisition, the data source is quickly located based on the target data item, reducing unnecessary data queries. During data processing, the algorithm module is invoked based on the function identifier, avoiding redundant calculations and invalid operations, thus improving data processing efficiency. In addition, technicians can customize the target data item and function identifier to adjust data processing requirements at any time, making this solution highly flexible and scalable.

[0044] Optionally, the data processing request may also include: data collection duration and data collection frequency; in step S102, obtaining vehicle data corresponding to the vehicle data type to obtain group a of vehicle data may include the following steps: Step S201: Determine the first storage space based on the target data item, data acquisition duration, and data acquisition frequency; Step S202: Collect vehicle data corresponding to the vehicle data type within the data collection duration according to the data collection frequency to obtain group a of vehicle data; Step S203: Store the vehicle data of group a into the first storage space.

[0045] In one possible embodiment, the diagnostic device receives instructions input by a technician through a human-machine interface, such as setting the data acquisition duration to "30 minutes" and the data acquisition frequency to "once per second." These parameters, along with the target data item and function identifier, are encapsulated into a data processing request and sent to the electronic control unit via communication interfaces such as CAN bus and Ethernet. The validity of the data acquisition duration and frequency in the data processing request is verified by checking against predefined rules. For example, the data acquisition duration must be a positive integer and conform to the system's maximum supported duration, and the acquisition frequency must be within a reasonable range supported by the device. If the parameters are invalid, a request error message is returned to the diagnostic device.

[0046] In one possible embodiment, a first storage space is determined based on the target data item, data acquisition duration, and data acquisition frequency. Based on the target data item, a pre-established data dictionary is consulted to obtain the size of a single data entry corresponding to the vehicle data type. For example, for the "engine speed" data type, each record may occupy 4 bytes. Then, based on the data acquisition duration and frequency, the expected amount of data to be acquired within that duration is calculated: Expected data acquisition amount = data acquisition duration × data acquisition frequency × single data entry size. For example, if the data acquisition duration is 30 minutes (1800 seconds), the data acquisition frequency is once per second, and the single data entry is 4 bytes, then the expected data acquisition amount is 1800 × 1 × 4 = 7200 bytes. Based on the calculated expected data acquisition amount and the system storage strategy, the size of the first storage space is determined, and corresponding contiguous storage space is allocated on the storage devices, including local hard drives and on-board memory.

[0047] In one possible embodiment, vehicle data corresponding to the vehicle data type is collected within the data collection duration according to the data collection frequency, resulting in group a of vehicle data. A data collection timer is started, and the collection task is executed cyclically within the data collection duration, with the data collection frequency as the period. During each collection, a data request command is sent to the corresponding ECU through the vehicle's internal communication network, such as the CAN bus, based on the target data item, and the vehicle data returned by the ECU is received. Data integrity and validity are verified, such as checking the CRC checksum of the data frame and whether the data is within a reasonable value range. If the data is abnormal, it is marked, and a strategy is used to determine whether to re-collect or replace it with a default value. The data that passes the verification is grouped according to the different vehicle data types of the target data item, forming group a of vehicle data.

[0048] In one possible embodiment, the vehicle data of group A is stored in the first storage space. The collected vehicle data of group A is sequentially written to the corresponding storage area according to the determined address and storage format of the first storage space. Specifically, a sequential storage method can be used to ensure data continuity and facilitate subsequent fast retrieval. During the storage process, the amount of data stored and the storage status are recorded in real time. If a storage error occurs, such as disk space being full or storage device failure, data collection is stopped, an error log is generated, and a storage failure alarm message is sent to the diagnostic device.

[0049] In this embodiment, the setting of data acquisition duration and frequency allows technicians to flexibly adjust the acquisition strategy according to actual needs. For slowly changing data, such as vehicle coolant temperature, a longer acquisition duration and lower frequency can be set to reduce data redundancy. For rapidly changing and critical data, such as engine speed, a shorter duration and higher frequency are set to ensure data real-time performance and integrity. Furthermore, by pre-calculating the data volume to determine the initial storage space, waste or insufficiency of storage space is avoided. This prevents storage resources from becoming idle due to excessive space allocation and also prevents data loss due to exceeding storage capacity, thereby improving the efficiency of storage resource utilization and the security of data storage.

[0050] Optionally, step S201, determining the first storage space based on the target data item, data acquisition duration, and data acquisition frequency, may include the following steps: Step S301: Obtain the remaining storage space of the electronic control unit; Step S302: Determine the maximum and minimum byte lengths corresponding to the target data item based on the vehicle data type; Step S303: Determine the amount of data based on the data collection duration and frequency; Step S304: Determine the first storage space based on the remaining storage space, the amount of data, the maximum byte length, and the minimum byte length.

[0051] In one possible embodiment, the remaining storage space of the electronic control unit (ECU) is obtained. The ECU can query the usage of its own storage modules, such as flash memory, to calculate the remaining available storage space. For example, if the total storage capacity of the ECU is 1MB and 300KB has been used, then the remaining storage space is 700KB.

[0052] In one possible implementation, the maximum and minimum byte lengths corresponding to the target data item are determined based on the vehicle data type. The ECU has a built-in data dictionary, which includes byte length information for various vehicle data types for different target data items. For example, the "engine speed" data type normally occupies 2 bytes (the minimum byte length), but may occupy 4 bytes (the maximum byte length) in some high-precision measurement modes. By searching and matching in the data dictionary based on the target data item, the maximum and minimum byte lengths corresponding to that data item can be obtained.

[0053] In one possible embodiment, the number of data entries is determined based on the data acquisition duration and the data acquisition frequency. The data acquisition duration is converted into a time value in seconds. For example, if the data acquisition duration is set to 10 minutes, it is converted to 600 seconds. Based on the data acquisition frequency and the converted time value, the expected number of data entries to be collected within the given acquisition duration is calculated using the formula: Number of Data Entries = Data Acquisition Duration × Data Acquisition Frequency. If the data acquisition frequency is 2 times per second, the number of data entries is 600 × 2 = 1200.

[0054] In one possible embodiment, the first storage space is determined based on the remaining storage space, the amount of data, the maximum byte length, and the minimum byte length. Maximum space = amount of data × maximum byte length, minimum space = amount of data × minimum byte length. For example, the maximum space is 1200 × 4 = 4800 bytes, and the minimum space is 1200 × 2 = 2400 bytes. The calculated maximum and minimum spaces are compared with the remaining storage space of the ECU: If the minimum space ≤ the remaining storage space and the maximum space > the remaining storage space, the first storage space is allocated according to the minimum space size to save storage resources, while reserving some remaining space for other possible storage needs or to cope with data length fluctuations. If the minimum space ≤ the remaining storage space and the maximum space ≤ the remaining storage space, the first storage space is allocated according to the maximum space to ensure complete data storage even when the data byte length reaches its maximum value. If the minimum space > the remaining storage space, information about insufficient storage space is reported to the diagnostic equipment, prompting technicians to adjust the data acquisition duration and frequency or replace the storage device. In the ECU storage module, a contiguous storage area is allocated according to the determined first storage space size, and information such as the starting address and space size of the storage area is recorded for subsequent data storage.

[0055] In this embodiment, by comprehensively considering data acquisition duration, frequency, range of data type byte length variations, and remaining ECU storage space, storage space can be precisely allocated according to actual data storage needs. This avoids wasting storage resources due to excessive space reservation or data loss due to insufficient reservation, thus improving the efficiency of storage resource utilization. There is no need for manual estimation and adjustment of storage space; calculation and allocation are performed automatically based on input parameters and ECU storage status, reducing the complexity of storage management and maintenance costs.

[0056] In specific embodiments, in addition to estimating the required storage space based on the data item type, number, duration, and frequency, a fixed-size storage area can also be allocated initially, and then expanded if necessary.

[0057] Optionally, each group of vehicle data includes b sub-data, where b is a positive integer; step S203, storing group a of vehicle data in the first storage space, may include the following steps: Step S401: Based on the data acquisition duration and data acquisition frequency, determine the acquisition sequence number of each of the b sub-data, and obtain b acquisition sequence numbers; Step S402: Determine the first data length of the target sub-data, where the target sub-data is any one of the b sub-data; Step S403: Determine the available data space for the target sub-data in the first storage space; Step S404: If the length of the first data is less than or equal to the available data space, determine the target storage space according to the available data space and the acquisition sequence number corresponding to the target sub-data; Step S405: Store the target sub-data in the target storage space; Step S406: If the length of the first data is greater than the available data space, determine the target expansion space according to the available data space and the acquisition sequence number corresponding to the target sub-data; Step S407: Store the target sub-data in the target extended space.

[0058] In one possible embodiment, based on the data acquisition duration and frequency, the acquisition sequence number of each of the b sub-data sets is determined, resulting in b acquisition sequence numbers. The total number of data acquisitions for each group of vehicle data is calculated based on the data acquisition duration and frequency; for example, if the acquisition duration is 60 seconds and the acquisition frequency is 2 times per second, the total number of acquisitions is 120. Following the chronological order of acquisition, for each group of vehicle data containing b sub-data sets, an acquisition sequence number from 1 to b is sequentially assigned to each sub-data set.

[0059] In one possible embodiment, a first data length for the target sub-data is determined, where the target sub-data is any one of b sub-data. The data type of the target sub-data is obtained through a data dictionary or a predefined data format specification, thereby determining its fixed data length. For example, if the target sub-data is "engine speed," and its data type is a 16-bit integer, then the first data length is 2 bytes.

[0060] In one possible embodiment, the available data space for the target sub-data in the first storage space is determined. The starting address and total size of the first storage space are determined. Based on the stored data, the remaining available data space is calculated. If no data storage has started, the available data space is the total size of the first storage space. If some data has been stored, the available data space is obtained by subtracting the occupied space from the total size. Simultaneously, the location information of the stored data within the first storage space is determined.

[0061] In one possible embodiment, if the length of the first data is less than or equal to the available data space, a target storage space is determined based on the available data space and the acquisition sequence number corresponding to the target sub-data, and the target sub-data is stored in the target storage space. Based on the available data space and the acquisition sequence number corresponding to the target sub-data, a contiguous and suitable storage area is determined in the first storage space as the target storage space. For example, if the starting address of the available data space is 0x1000, the acquisition sequence number of the target sub-data is 2, and the length of each sub-data is fixed at 2 bytes, then the starting address of the target storage space is 0x1002. The target sub-data is written into the first storage space according to the determined target storage space address, and the occupied space and remaining available space information are updated.

[0062] In one possible embodiment, if the length of the first data is greater than the available data space, a target extension space is determined based on the available data space and the acquisition sequence number corresponding to the target sub-data, and the target sub-data is stored in the target extension space. First, the remaining available data space in the first storage space is used to store as much of the target sub-data as possible, and the location and length of the stored portion are recorded. Based on the length of the remaining unstored data, additional target extension space is searched for or requested outside the first storage space; for example, a new memory block is requested from the ECU or a free area of ​​other storage devices is used. The remaining portion of the target sub-data is stored in the target extension space, and an association index is established between the storage locations of the target sub-data in the first storage space and the target extension space for subsequent data retrieval.

[0063] In one possible embodiment, if the target expansion space cannot be determined, the data length of the target sub-data is compressed so that the first data length is less than or equal to the available data space.

[0064] In one possible embodiment, if the collection sequence number of the target sub-data is 5, b is 10, and the length of the first data is greater than the available data space, if the target expansion space cannot be determined, then the first 5 sub-data are processed according to the data processing rules corresponding to the group of vehicle data to obtain a reference result, the reference result is stored, and the first 5 sub-data are deleted in order to store the last 5 sub-data.

[0065] In this embodiment of the application, when the length of sub-data exceeds the current available space, the target expansion space is determined and the remaining data is stored to ensure that each sub-data can be completely saved, avoiding data truncation and loss due to insufficient space, and ensuring the accuracy and integrity of the data.

[0066] Optionally, the function identifier corresponding to each group of vehicle data includes c sub-identifiers, where c is a positive integer, and each sub-identifier corresponds to a sub-rule in the data processing rules; in step S103, processing each group of vehicle data based on the data processing rules to obtain the processing result corresponding to the data processing rules in each group of vehicle data may include the following steps: Step S501: Obtain the identifier type of each sub-identifier, resulting in c identifier types; Step S502: Determine the target processing data corresponding to each identifier type in each group of vehicle data, and obtain c target processing data; Step S503: Based on the data acquisition duration and data acquisition frequency, determine the start time node and end time node of data acquisition for each target processing data, resulting in c start time nodes and c end time nodes. Step S504: Based on c identifier types, c collection start time nodes, and c collection end time nodes, determine the execution time node for each sub-identifier, thus obtaining c execution time nodes; Step S505: Based on the c execution time nodes and the c sub-rules corresponding to the c sub-identifiers, process the c target processing data to obtain the processing results corresponding to the data processing rules in each group of vehicle data.

[0067] In one possible implementation, the identifier type of each sub-identifier is obtained, resulting in c identifier types. After receiving the function identifier corresponding to each group of vehicle data, it is parsed, and the c sub-identifiers contained in the function identifier are separated one by one. For each sub-identifier, a predefined identifier type mapping table is queried. This mapping table records the identifier types corresponding to various types of sub-identifiers. For example, the "average calculation" sub-identifier corresponds to "statistical calculation type", and the "data filtering" sub-identifier corresponds to "data filtering type". By looking up the mapping table, the identifier type of each sub-identifier is obtained, thus obtaining c identifier types.

[0068] In one possible embodiment, target processing data corresponding to each identifier type in each group of vehicle data is determined, resulting in c target processing data. All data items in each group of vehicle data are traversed, and combined with the obtained c identifier types, target processing data corresponding to each identifier type is selected based on the correspondence between data items and identifier types. For example, if the identifier type is "engine performance analysis," then relevant data such as engine speed, intake air volume, and fuel injection quantity are selected from that group of vehicle data as target processing data.

[0069] In one possible embodiment, based on the data acquisition duration and frequency, the start and end times for each target data processing point are determined, resulting in c start and c end times. The data acquisition duration is divided chronologically, and combined with the data acquisition frequency, the acquisition time corresponding to each time interval is determined. For example, if the data acquisition duration is 60 seconds and the acquisition frequency is once per second, there are a total of 60 acquisition times. For each target data processing point, the start and end times are determined from these acquisition times based on its data characteristics and processing requirements. For example, for data requiring analysis of engine performance during vehicle startup, the start time might be determined as the acquisition time corresponding to the vehicle startup moment, and the end time as the acquisition time corresponding to 10 seconds after startup, thus obtaining c start and c end times.

[0070] In one possible embodiment, based on c identifier types, c collection start time nodes, and c collection end time nodes, the execution time node for each sub-identifier is determined, resulting in c execution time nodes. Combining the c identifier types, c collection start time nodes, and c collection end time nodes, and considering the data processing characteristics and priorities of different identifier types, the execution time node for each sub-identifier is determined. For example, for the "real-time monitoring" identifier type, processing should be performed immediately after the target processing data is collected; for the "periodic statistics" identifier type, processing can be performed after the collection period ends, resulting in c execution time nodes. This ensures that data processing for different sub-identifiers can proceed in an orderly manner.

[0071] In one possible embodiment, c target processing data are processed according to c execution time nodes and c sub-rules corresponding to c sub-identifiers to obtain the processing result corresponding to the data processing rule in each group of vehicle data. At each execution time node corresponding to a sub-identifier, the corresponding target processing data is processed according to the sub-rule corresponding to that sub-identifier. If the sub-rule is "calculate the average value", the values ​​in the target processing data are summed and divided by the number of data points. If the sub-rule is "filter data greater than a threshold", data in the target processing data that are greater than the set threshold are filtered out. After the c target processing data are processed sequentially according to the corresponding sub-rules, the processing results are integrated to obtain the final processing result corresponding to the data processing rule in each group of vehicle data.

[0072] For example, see Figure 4 , Figure 4 This is a schematic diagram of an execution time node provided in an embodiment of this application. Execution time node 1 is earlier than execution time node 2, and execution time node 2 is earlier than execution time node 3. Therefore, the corresponding sub-rules are executed at the corresponding execution time nodes.

[0073] Optionally, the data processing request may also include a first identifier; step S104, sending the processing result and function identifier to the diagnostic device, may include the following steps: Step S601: If the first identifier indicates that the vehicle data of group a does not need to be returned, the processing result and the function identifier are concatenated to obtain the first data packet, and the first data packet is sent to the diagnostic device; Step S602: If the first identifier indicates that vehicle data group a needs to be returned, the vehicle data group a, the processing result and the function identifier are concatenated to obtain the second data packet, and the second data packet is sent to the diagnostic device.

[0074] In one possible embodiment, when the diagnostic device generates a data processing request, it embeds a first identifier into the request data packet according to the operator's operation or preset configuration. This first identifier can be a Boolean value, an enumerated value, etc. For example, 0 indicates that vehicle data for group A does not need to be returned, and 1 indicates that it needs to be returned. A conditional judgment is made based on the extracted first identifier value. If the first identifier indicates that vehicle data for group A does not need to be returned, the processing result and function identifier are concatenated according to a predefined data format. For example, they can be combined into a new object using key-value pairs, or the byte streams of the function identifier and processing result can be arranged sequentially according to a specific binary protocol format. If the first identifier indicates that vehicle data for group A needs to be returned, the vehicle data for group A, the processing result, and the function identifier are integrated. This can be done using a hierarchical structure, such as constructing nested objects. If a binary format is used, the length prefix and storage order of each data part are specified. The generated first or second data packet is sent back to the diagnostic device through the same communication channel as the received request. During the transmission process, the transmission status and timestamp are recorded. If the transmission fails due to network interruption or timeout, it is retransmitted according to the preset retry strategy, such as setting the maximum number of retries and the retry interval.

[0075] Furthermore, the diagnostic equipment's communication module listens to network port or bus signals and receives returned data packets. The received data packets undergo integrity verification; if verification is successful, they are parsed according to their format to extract function identifiers, processing results, and / or multiple sets of vehicle data, which are then displayed or further processed on the diagnostic equipment interface.

[0076] For example, see Figure 5 , Figure 5 This is a schematic diagram of a splicing method provided in an embodiment of this application. Each processing result is spliced ​​with its corresponding function identifier, wherein the data positions of the function identifier and the corresponding processing result can be interchanged. Each function identifier and its corresponding processing result are merged together and sequentially spliced ​​into a data string, which is the first data packet. For example, the structure of the data string in the diagram is: first processing result, first function identifier, second processing result, second function identifier, third processing result, third function identifier. Correspondingly, the structure of the data string can also be: first function identifier, first processing result, second function identifier, second processing result, third function identifier, third processing result.

[0077] In this embodiment, the returned data content is dynamically determined based on the first identifier. When technicians only need to focus on the processing results, such as viewing only the average engine speed, the transmission of large amounts of raw vehicle data is avoided, reducing data transmission volume, network load, and transmission time, thus improving communication efficiency. However, when it is necessary to analyze the correlation between raw data and processing results, such as investigating the cause of abnormal data, multiple sets of vehicle data can be returned completely, flexibly adapting to needs and improving transmission efficiency. This embodiment can also reduce unnecessary data transmission, resulting in lower hardware resource consumption for diagnostic equipment and data processing systems. Especially in resource-constrained in-vehicle environments, it can effectively prevent system performance degradation due to large amounts of data transmission, ensuring smooth operation of diagnostic equipment and reducing resource consumption.

[0078] Optionally, the data processing request may also include a second identifier; in step S102, before obtaining vehicle data corresponding to the vehicle data type in response to the target data item and obtaining group a of vehicle data, the following steps may also be included: Step S701: Parse the data processing request to obtain the second identifier; Step S702: If the second identifier is the same as the system identifier of the electronic control unit, continue to parse the data processing request to obtain the target data item and function identifier.

[0079] In one possible embodiment, each ECU has a pre-defined unique system identifier stored in its non-volatile memory for identification. A second identifier extracted from the data processing request is compared with the system identifier obtained from the ECU. The comparison includes case sensitivity and character order or numerical value. Based on the comparison result, a conditional judgment is made: if the second identifier is identical to the system identifier, it indicates that the target ECU for the data processing request is this ECU, and the data processing request is further analyzed to extract target data items, function identifiers, and other key information. Once the second identifier and system identifier match successfully, and the target data items and function identifiers are successfully parsed, the data processing system continues with subsequent operations according to a predetermined process.

[0080] In a specific embodiment, when it is necessary to collect certain data from the vehicle ECU, such as the highest, lowest, and average speed of the vehicle engine ECU within 20 minutes, the diagnostic device can send a data acquisition and processing request to the engine ECU.

[0081] The data processing request includes: a target ECU system request ID (Identity document, ID), a target data item data identification (DID), a data acquisition duration, and a data acquisition frequency. The target ECU system request ID is the second identifier described in the previous embodiment, used to distinguish which ECU the request is sent to; for example, the second identifier for an engine is 0x7e0. The target data item DID can include multiple data points, such as engine speed DID of 0x0201 and intake air temperature of 0x0203. The data acquisition duration is, for example, 20 minutes. The data acquisition frequency is, for example, data is collected every 2 seconds. The function identifier can include multiple elements, such as 01 for average, 02 for maximum, 03 for minimum, 04 for median, 05 for sum, etc., all of which can be customized. The data processing request may also include a first identifier to determine whether the original vehicle data needs to be returned.

[0082] For example, see Figure 6 , Figure 6 This is a schematic diagram of the data content of a data processing request provided in an embodiment of this application. In this data processing request, if the second identifier is 0x7e0, the data processing request will be sent to the ECU corresponding to the vehicle engine. If the target data item is 0x0201, then the engine speed of the vehicle needs to be counted. The data collection duration is 20 minutes, and the data collection frequency is once every two seconds. If the function identifiers are 02 and 03, then the highest and lowest values ​​need to be calculated. If the first identifier is 1, then in addition to returning the highest and lowest values ​​and the corresponding function identifiers, the original vehicle data also needs to be returned.

[0083] The data processing request is then sent to the vehicle's ECU. Upon receiving the request, the ECU determines whether it was sent to its own system based on the system request ID in the request. If it's not a system ID, it doesn't process the request. If it is a system ID, it parses all the information in the request and stores it internally. It then checks if this information is correct, such as whether the requested DID exists and whether the requested function identifier is valid. If incorrect, it sends a request error message to the diagnostic equipment.

[0084] If the judgment is correct, the diagnostic device will begin executing the statistical task. Then, an array of data storage areas will be allocated within the ECU to store the collected data, and a timer will be started to keep track of the data. Every 2 seconds, the value of the DID data item to be statistically analyzed will be collected and stored in the storage area.

[0085] If the timer reaches the statistical time, such as 20 minutes, data collection stops. Statistical calculations are performed sequentially according to the function codes. For example, adding up all collected data and dividing by the number of collections gives the average value. The lowest data point is the minimum value, the highest data point is the maximum value, and so on. If there are multiple function codes, the calculation needs to be performed multiple times. The result corresponding to each function code is calculated.

[0086] Once all calculations are complete, the ECU can package each function identifier and its corresponding statistical result value and send it back to the diagnostic equipment. The diagnostic equipment can then directly obtain all the data to be statistically analyzed without needing to perform any calculations.

[0087] This significantly reduces the communication time and resources required for interactions with the vehicle's ECU, allowing the ECU to directly execute statistical functions internally upon request and return the results. Diagnostic equipment can also reduce the time spent on data statistical calculations.

[0088] In summary, in this embodiment, a data processing request is first obtained from the diagnostic device. This request includes a target data item and a function identifier. The target data item indicates the type of vehicle data to be acquired, and the function identifier indicates the data processing rules. Then, in response to the target data item, vehicle data corresponding to the vehicle data type is acquired, resulting in group a of vehicle data. Next, in response to the function identifier, each group of vehicle data is processed based on the data processing rules to obtain the processing result corresponding to the rules in each group. Finally, the processing result and function identifier are sent to the diagnostic device. Thus, by having the electronic control unit acquire and process vehicle data according to the data processing request, obtain the processing result, and then send the processing result and function identifier to the diagnostic device, the number of communications between the electronic control unit and the diagnostic device is reduced when acquiring vehicle data through the diagnostic device, thereby reducing the occupation of communication resources on the vehicle bus.

[0089] The methods of the embodiments of the present invention have been described in detail above, and the apparatus of the embodiments of the present invention is provided below.

[0090] See Figure 7 , Figure 7 This is a schematic diagram of the structure of a vehicle data processing device provided in an embodiment of this application. Figure 7As shown, the vehicle data processing device 800 includes an acquisition unit 801 and a processing unit 802. The acquisition unit 801 is used to acquire a data processing request from a diagnostic device. The data processing request includes a target data item and a function identifier. The target data item indicates the type of vehicle data to be acquired, and the function identifier indicates the data processing rules. The processing unit 802 is used to acquire vehicle data corresponding to the vehicle data type in response to the target data item, thereby obtaining a group of vehicle data. In response to the function identifier, it processes each group of vehicle data based on the data processing rules to obtain the processing result corresponding to the data processing rules in each group of vehicle data. The processing result and the function identifier are then sent to the diagnostic device.

[0091] In specific implementations, the acquisition unit 801 and the processing unit 802 in this application embodiment may also execute other implementations described in the vehicle data processing method of this application embodiment, which will not be repeated here.

[0092] See Figure 8 , Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. For example... Figure 8 As shown, the electronic device 900 includes a transceiver 901, a processor 902, and a memory 903, which are connected via a bus 904. The memory 903 stores computer programs and data, and can transmit the data stored in the memory 903 to the processor 902. The electronic device 900 can be the vehicle data processing device 800 described above, and the processor 902 can be the acquisition unit 801 and processing unit 802 described above. In this embodiment, the processor 902 is used to read the computer program in the memory 903 and execute some or all of the steps of the vehicle data processing method described above.

[0093] This application also provides a computer-readable storage medium storing a computer program that is executed by a processor to implement some or all of the steps of any of the vehicle data processing methods described in the above method embodiments.

[0094] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the vehicle data processing methods described in the above method embodiments.

[0095] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0096] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0097] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or modules may be electrical or other forms.

[0098] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0099] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software program modules.

[0100] If the integrated module is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0101] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A vehicle data processing method, characterized in that, Applied to an electronic control unit, the method includes: A data processing request is obtained from the diagnostic device. The data processing request includes a target data item and a function identifier. The target data item is used to indicate the type of vehicle data to be acquired, and the function identifier is used to indicate the data processing rules. In response to the target data item, vehicle data corresponding to the vehicle data type is obtained to obtain group a of vehicle data; In response to the function identifier, each group of vehicle data is processed based on the data processing rules to obtain the processing result corresponding to the data processing rules in each group of vehicle data; The processing result and the function identifier are sent to the diagnostic device.

2. The method as described in claim 1, characterized in that, The data processing request further includes: data collection duration and data collection frequency; obtaining vehicle data corresponding to the vehicle data type to obtain group a of vehicle data includes: The first storage space is determined based on the target data item, the data acquisition duration, and the data acquisition frequency; According to the data acquisition frequency, within the data acquisition duration, vehicle data corresponding to the vehicle data type is collected to obtain the a group of vehicle data; The data of the vehicles in group a is stored in the first storage space.

3. The method as described in claim 2, characterized in that, The step of determining the first storage space based on the target data item, the data acquisition duration, and the data acquisition frequency includes: Obtain the remaining storage space of the electronic control unit; Based on the vehicle data type, determine the maximum and minimum byte lengths corresponding to the target data item; The amount of data is determined based on the data collection duration and the data collection frequency; The first storage space is determined based on the remaining storage space, the amount of data, the maximum byte length, and the minimum byte length.

4. The method as described in claim 2 or 3, characterized in that, Each group of vehicle data includes b sub-data; storing the a group of vehicle data in the first storage space includes: Based on the data acquisition duration and the data acquisition frequency, the acquisition sequence number of each of the b sub-data is determined, resulting in b acquisition sequence numbers; Determine the first data length of the target sub-data, wherein the target sub-data is any one of the b sub-data; Determine the available data space for the target sub-data in the first storage space; If the length of the first data is less than or equal to the available data space, the target storage space is determined according to the available data space and the collection sequence number corresponding to the target sub-data; The target sub-data is stored in the target storage space; If the length of the first data is greater than the available data space, the target expansion space is determined according to the available data space and the collection sequence number corresponding to the target sub-data; The target sub-data is stored in the target extended space.

5. The method as described in claim 2, characterized in that, The functional identifier corresponding to each group of vehicle data includes c sub-identifiers, each sub-identifier corresponding to a sub-rule in the data processing rules; the step of processing each group of vehicle data based on the data processing rules to obtain the processing result corresponding to the data processing rules in each group of vehicle data includes: Obtain the identifier type for each sub-identifier, resulting in c identifier types; Determine the target processing data corresponding to each identifier type in each group of vehicle data to obtain c target processing data; Based on the data acquisition duration and the data acquisition frequency, the start time node and end time node of data acquisition for each target are determined, resulting in c start time nodes and c end time nodes. Based on the c identifier types, the c collection start time nodes, and the c collection end time nodes, the execution time node for each sub-identifier is determined, resulting in c execution time nodes; Based on the c execution time nodes and the c sub-rules corresponding to the c sub-identifiers, the c target processing data are processed to obtain the processing result corresponding to the data processing rule in each group of vehicle data.

6. The method as described in claim 1, characterized in that, The data processing request further includes a first identifier; sending the processing result and the function identifier to the diagnostic device includes: If the first identifier indicates that the vehicle data of group a does not need to be returned, the processing result and the function identifier are concatenated to obtain a first data packet, and the first data packet is sent to the diagnostic device; If the first identifier indicates that the vehicle data of group a needs to be returned, the vehicle data of group a, the processing result and the function identifier are concatenated to obtain a second data packet, and the second data packet is sent to the diagnostic device.

7. The method as described in claim 1, characterized in that, The data processing request further includes a second identifier; before obtaining vehicle data corresponding to the vehicle data type in response to the target data item, and obtaining group a of vehicle data, the method further includes: Parse the data processing request to obtain the second identifier; If the second identifier is the same as the system identifier of the electronic control unit, the data processing request is parsed to obtain the target data item and the function identifier.

8. A vehicle data processing device, characterized in that, Applied to electronic control units, the device includes an acquisition unit and a processing unit; The acquisition unit is used to acquire a data processing request from the diagnostic device. The data processing request includes a target data item and a function identifier. The target data item is used to indicate the type of vehicle data to be acquired, and the function identifier is used to indicate the data processing rules. The processing unit is used to respond to the target data item, obtain vehicle data corresponding to the vehicle data type, and obtain a set of vehicle data; In response to the function identifier, each group of vehicle data is processed based on the data processing rules to obtain the processing result corresponding to the data processing rules in each group of vehicle data; The processing result and the function identifier are sent to the diagnostic device.

9. An electronic device, characterized in that, include: A processor and a memory, the processor being connected to the memory, the memory being used to store a computer program, the processor being used to execute the computer program stored in the memory to cause the electronic device to perform the method as described in any one of claims 1-7.

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

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