Data acquisition method based on OBD on-board diagnostic system and related equipment

Abstract

The application relates to the technical field of data acquisition in an on-board diagnostic system, in particular to a data acquisition method based on an OBD on-board diagnostic system and related equipment. The data acquisition method comprises the following steps: receiving a target query instruction, matching a target item to be queried; based on the target item to be queried, acquiring target running data of a vehicle at present; judging whether the target query instruction is consistent with the target item to be queried, if yes, the target running data is taken as output data for output; if no, a target algorithm is matched for operation, and the operated data is taken as the output data for output; judging whether the output data is within a corresponding safety threshold, if no, a preset fault reason is matched for output. The application can improve the flexibility and accuracy of the OBD system in data acquisition.

Description

Technical Field

[0001] This application relates to the field of data acquisition technology in on-board diagnostic systems, and in particular to a data acquisition method and related equipment based on an OBD on-board diagnostic system. Background Technology

[0002] On-Board Diagnostics (OBD) is a system used to monitor the performance and emissions of a vehicle's engine. With the development of the automotive industry, OBD systems have become a standard feature in modern vehicles. This system allows for the real-time acquisition of various vehicle operating parameters, helping drivers to promptly identify potential problems and improving driving safety and maintenance efficiency. Furthermore, the application of OBD systems has expanded to areas such as remote monitoring and fault diagnosis, providing crucial technical support for automotive repair services.

[0003] To achieve effective monitoring and management of vehicle status, existing technical solutions typically employ the following methods: First, manually reading various vehicle operating data by connecting a dedicated OBD scanning tool; second, using mobile applications to communicate with the vehicle's OBD interface via Bluetooth or Wi-Fi to automatically collect necessary operating information; and third, utilizing remote data acquisition functions integrated into vehicle networking platforms to extract key indicators from multiple vehicles periodically or on demand. While these methods can meet user needs to some extent, they still have limitations in practical operation.

[0004] Currently, common OBD data acquisition methods mainly rely on simple command sending and response mechanisms, which cannot flexibly handle complex and ever-changing query needs. For example, when users want comprehensive evaluation results under specific conditions, traditional methods often only return data from a single dimension, rather than combining multiple factors for in-depth analysis. Furthermore, for data processing in certain special situations, such as low-threshold alarms, existing technologies lack effective solutions, potentially causing users to miss important warning information and thus affecting driving safety. Therefore, improving the flexibility and accuracy of OBD systems in data acquisition has become a critical issue that urgently needs to be addressed. Summary of the Invention

[0005] The purpose of this application is to overcome the above-mentioned technical problems and provide a data acquisition method and related equipment based on an OBD vehicle diagnostic system, which can improve the flexibility and accuracy of OBD system in data acquisition.

[0006] Firstly, one embodiment of this application discloses a data acquisition method based on an OBD vehicle diagnostic system, which adopts the following scheme:

[0007] A data acquisition method based on an OBD vehicle diagnostic system includes: receiving a target query command and matching a target item to be queried; collecting the current target operating data of the vehicle based on the target item to be queried; determining whether the target query command and the target item to be queried are consistent; if so, outputting the target operating data as output data; if not, performing calculations using a target algorithm and outputting the calculated data as the output data; determining whether the output data is within a corresponding safety threshold; if not, matching a preset fault cause and outputting it.

[0008] By adopting the above technical solution, accurate collection and processing of vehicle operation data can be achieved. Specifically: receiving target query instructions and matching them with the target items ensures the purposefulness and accuracy of data collection. Collecting the vehicle's current target operation data based on the target items guarantees the authenticity and timeliness of the data. Determining whether the target query instruction matches the target item, and performing calculations using the target algorithm when they don't match, improves the flexibility and adaptability of data processing. Determining whether the output data is within the corresponding safety threshold; otherwise, outputting a preset fault cause, enhances system security and allows for timely detection and warning of potential problems.

[0009] Optionally, before receiving the target query instruction and matching the target item to be queried, the method further includes: establishing a mapping table between the target query instruction and the target item to be queried; wherein, after receiving the target query instruction, the target item to be queried corresponding to the target query instruction is matched from the mapping table.

[0010] By adopting the above technical solution, a mapping relationship between the target query command and the target item to be queried can be established in advance. This allows for quick and accurate matching of the corresponding target item upon receiving the query command, improving the efficiency and accuracy of data collection. Simultaneously, it avoids human errors caused by manual matching, enhancing the stability and reliability of the system.

[0011] Optionally, the step of collecting the current target operating data of the vehicle based on the target item to be queried specifically includes: collecting multiple operating data of the vehicle based on the target item to be queried, a preset interval time, and a preset number of collections; determining whether the difference between the multiple operating data exceeds a preset threshold; if so, outputting an error to remind the user; if not, using the last data as the target operating data.

[0012] By adopting the above technical solution, the collected data can be made more accurate and reliable. First, by setting preset intervals and preset collection times, vehicle operation data can be collected multiple times, thereby reducing data deviation caused by single collections. Second, by judging the differences between multiple operation data points, if the difference exceeds a preset threshold, an anomaly alert is immediately output. This helps to promptly identify and handle potential problems, improving system security. If the difference does not exceed the threshold, the last data point is used as the target operation data, ensuring the validity and accuracy of the data.

[0013] Optionally, before receiving the target query instruction and matching the target item to be queried, the method further includes: sending a communication request instruction and communication rules to establish a communication connection, wherein the communication rules include communication time, target pin, and target check bit; if the communication is successfully established, data is collected and output based on the communication rules.

[0014] By adopting the above technical solution, a reliable communication connection can be established before receiving the target query command, thereby improving the accuracy and reliability of data acquisition. Specifically, the communication request command and communication rules can be pre-set with the communication time, pins, and verification methods to ensure that both devices can exchange data under the correct configuration. If communication is successful, data is acquired and output according to the predetermined communication rules, avoiding data errors or loss due to communication problems.

[0015] Optionally, when the target query instruction is to query vehicle speed data, the target item to be queried is the running speed within a first preset time period. It is determined that the target query instruction and the target item to be queried are inconsistent. The matching target algorithm is the speed average algorithm. The running speed within the first preset time period is calculated based on the speed average algorithm to obtain the target average value as output data.

[0016] When the target query instruction is to query fault code data, the target item to be queried is matched as the current fault code, historical fault code and permanent fault code. If the target query instruction is consistent with the target item to be queried, the collected current fault code, historical fault code and permanent fault code are output.

[0017] The fault code data is output and displayed based on a preset display algorithm, which is as follows:

[0018] If(X1<0X40) P + HEX(X1*0X100 + X2);

[0019] Else if(X1<0X80 )) C + HEX((X1-0X40)*0X100 + X2);

[0020] Else if(X1<0XC0) B + HEX((X1-0X80)*0X100 + X2);

[0021] Else U + HEX((X1-0XC0)*0X100 + X2);

[0022] Wherein, P represents powertrain-related faults, C represents chassis-related faults, B represents body-related faults, and U represents network system-related faults; X1 is the first valid bit of the collected target operating data, and X2 is the second valid bit of the collected target operating data.

[0023] By adopting the above technical solutions, precise data processing and output are achieved for different types of query commands: when the target query command is to query vehicle speed data, the system can automatically match the operating speed within a first preset time period. If the query command and the item to be queried are inconsistent, a speed averaging algorithm is applied to calculate the average speed of the vehicle within that time period, improving data accuracy and reliability. For fault code data queries, the system can simultaneously obtain current fault codes, historical fault codes, and permanent fault codes. It also supports parsing various types of fault codes (such as powertrain, chassis, body, or network system faults) based on specific display algorithms, ensuring comprehensive coverage and accurate expression of fault information. This helps to quickly locate the source of the problem and improve repair efficiency and service quality.

[0024] Optionally, when the target query instruction is to query tire pressure data, the target item to be queried is matched with four tire pressure values. If the target query instruction is consistent with the target item to be queried, the four tire pressure values ​​are output. When the target query instruction is to query oxygen sensor data, the target item to be queried is matched with the voltage signal change of the oxygen sensor. If the target query instruction is inconsistent with the target item to be queried, the target algorithm is matched with the oxygen sensor voltage value algorithm, and the voltage value within a second preset time period is obtained as the output data and output.

[0025] By adopting the above technical solution, accurate querying and processing of vehicle tire pressure and oxygen sensor data can be achieved. For tire pressure data, the pressure values ​​of all four tires can be acquired and output in real time, ensuring the driver is aware of the status of each tire and improving driving safety. When the target query instruction is to query oxygen sensor data, if the target item to be queried does not match the target query instruction, a specific matching algorithm accurately calculates the voltage value within a second preset time period, thus providing a reliable basis for subsequent diagnosis.

[0026] Optionally, when the target query instruction is to query fuel system monitoring data, the target item to be queried is the ratio of air intake flow rate to fuel injection quantity. If the target query instruction is inconsistent with the target item to be queried, the target algorithm to be matched is the air intake flow rate algorithm and the actual fuel injection quantity algorithm. Based on the air intake flow rate algorithm and the actual fuel injection quantity algorithm, the ratio of the two is calculated and output as output data.

[0027] By adopting the above technical solution, precise data processing methods can be provided for different target query commands. When the target query command is to query fuel system monitoring data, the system first matches the target item to be queried as the ratio of air intake flow rate to fuel injection quantity. Then, it determines if the target query command is inconsistent with the target item to be queried, and then matches the corresponding target algorithm—the air intake flow rate algorithm and the actual fuel injection quantity algorithm. By calculating the air intake flow rate and fuel injection quantity, the final output is the ratio of the two as the result data. This processing method not only improves the accuracy and reliability of the data, but also reflects the operating status of the fuel system more intuitively, helping to promptly identify potential problems and take corresponding measures.

[0028] Secondly, one embodiment of this application discloses a remote monitoring system based on an OBD vehicle diagnostic system, which adopts the following solution:

[0029] A remote monitoring data acquisition system based on an OBD vehicle diagnostic system includes: a receiving module for receiving a target query command and matching the target item to be queried; an acquisition module for acquiring the current target operating data of the vehicle based on the target item to be queried; a judging module for judging whether the target query command is consistent with the target item to be queried; if so, the target operating data is output as output data; if not, a target algorithm is matched for calculation, and the calculated data is output as the output data; and a reminder mode for judging whether the output data is within the corresponding safety threshold; if not, a preset fault cause is matched and output.

[0030] By adopting the above technical solution, this remote monitoring data acquisition system can achieve real-time monitoring and data analysis of vehicle operating status. The specific effects are as follows:

[0031] The receiving module accurately matches the target query command with the target item to be queried, ensuring the accuracy of data collection. Simultaneously, the judgment module verifies the consistency between the target query command and the target item to be queried, avoiding data deviations caused by incorrect commands. When the target query command and the target item to be queried are inconsistent, the system automatically matches the target algorithm for calculation, thereby improving the system's flexibility and adaptability, and enabling it to handle various complex data requirements. The alert mode can trigger preset alerts based on whether the output data is within the corresponding safety threshold, promptly notifying users of potential problems or risks, enhancing the system's security and usability.

[0032] Thirdly, one embodiment of this application discloses an electronic device that adopts the following solution:

[0033] An electronic device includes: a memory and a processor, the memory being used to store a computer program; the processor being used to execute the computer program to implement the steps of the method as described in any of the preceding claims.

[0034] Fourthly, one embodiment of this application discloses a computer-readable storage medium, which adopts the following scheme:

[0035] A computer-readable storage medium having a computer program stored thereon, the computer program being executed by a processor to perform the steps of the method as described in any of the preceding claims.

[0036] In summary, this application includes at least one of the following beneficial technical effects:

[0037] 1. Improved the accuracy and reliability of OBD data acquisition by judging the consistency between the received target query command and the target item to be queried, and matching the corresponding algorithm to perform calculations when there is a discrepancy, ensuring that the output data meets the user's specific needs;

[0038] 2. The system's ability to identify abnormal situations has been enhanced. By performing difference analysis on multiple collected operational data, an abnormality alert is immediately issued once a situation exceeding a preset threshold is detected, which helps to identify problems early and take measures.

[0039] 3. Effective early warning for situations below the safety threshold is achieved. By judging whether the output data is within the safety threshold and matching the preset fault cause to provide a prompt when it is not within the safety threshold, driving safety is improved. Attached Figure Description

[0040] Figure 1 This is the process architecture used in a data acquisition method based on an OBD vehicle diagnostic system disclosed in an embodiment of this application;

[0041] Figure 2This is a flowchart illustrating a data acquisition method based on an OBD vehicle diagnostic system disclosed in an embodiment of this application;

[0042] Figure 3 This is a schematic diagram of the structure of a remote monitoring system based on an OBD vehicle diagnostic system, as disclosed in another embodiment of this application.

[0043] Figure 4 This is a schematic diagram of the structure of an electronic device disclosed in another embodiment of this application. Detailed Implementation

[0044] The present application will be further described in detail below with reference to the accompanying drawings.

[0045] Embodiments of this application will now be described in more detail with reference to the accompanying drawings. While embodiments of this application are shown in the drawings, it should be understood that this application may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to make this application more thorough and complete, and to fully convey the scope of this application to those skilled in the art.

[0046] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a” and “the” as used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0047] It should be understood that although the terms "first," "second," etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0048] The technical solutions of the embodiments of this application are described in detail below with reference to the accompanying drawings.

[0049] [First Embodiment]

[0050] See Figure 1This application discloses a process architecture for a data acquisition method based on an OBD vehicle diagnostic system, involving an electronic device (mobile phone, tablet, or computer), an OBD device (corresponding to the OBD system), and a vehicle ECU (Electronic Control Unit). The electronic device has a corresponding APP software installed and wirelessly connects to the OBD device to achieve communication with the OBD system. The OBD device is installed in the vehicle through the OBD interface to enable communication between the OBD system and the vehicle ECU. The OBD device is used to collect vehicle operating data, and then either processes the operating data or directly transmits it to the APP of the electronic device for display.

[0051] Specifically, a data acquisition method based on an OBD vehicle diagnostic system includes the following steps:

[0052] S10. Receive the target query instruction and match the target item to be queried;

[0053] In this context, when a user selects "query vehicle speed" via an electronic device, the system will match the vehicle's average speed over a first preset time period. Of course, the target query command can be one of the following: query vehicle speed data, fault code data, tire pressure data, oxygen sensor data, or fuel system monitoring data.

[0054] Specifically, prior to step S10, the following steps are also included:

[0055] S01. Establish a mapping table between the target query command and the target item to be queried;

[0056] The mapping table is a pre-stored database containing the relationship between various query commands and their corresponding data items. For example, if the target query command is to query vehicle speed data, the corresponding data item to be queried is the average running speed of the car within a first preset time period. If the target query command is to query fault code data, the corresponding data items to be queried are the current fault code, historical fault codes, and permanent fault codes.

[0057] Based on the mapping table settings, in step S10, after receiving the target query instruction, the system will quickly and accurately match the corresponding target item to be queried according to the pre-established mapping table, so as to improve the efficiency and accuracy of data collection.

[0058] Furthermore, prior to step S10, the following steps are also included:

[0059] S02. Send communication request instructions and communication rules to establish a communication connection;

[0060] In step S02, the OBD device establishes a communication connection with the vehicle's ECU. The OBD device establishes a communication connection with the vehicle's ECU by sending CAN protocol (Controller Area Network) commands, KWP protocol, or VPW protocol, etc.

[0061] The communication rules include communication time, target pin, and target checksum. The communication time is the time parameter for each data communication. The target pin is, for example, pin 10 of the OBD interface, and the target checksum is, for example, CRC-16. This ensures a smooth communication link between the system and the OBD interface, reducing the risk of data loss due to communication failures.

[0062] S03. If communication is successfully established, data will be collected and output based on the communication rules.

[0063] If communication is successful, data is collected and output according to the predetermined communication rules, which can avoid data errors or loss due to communication problems.

[0064] S20. Based on the target item to be queried, collect the current target operation data of the vehicle;

[0065] This method of collecting corresponding operational data based on the target item to be queried increases the relevance, timeliness, and accuracy of data collection. For example, if the target item to be queried is fault code data, then the current fault codes, historical fault codes, and permanent fault codes of the vehicle will be collected.

[0066] Specifically, step S20 also includes:

[0067] S21. Based on the target item to be queried, the preset interval time, and the preset number of collections, collect multiple operational data of the vehicle;

[0068] For example, a preset interval time of 1 second and a preset number of data collections of 3 will result in the collection of 3 operational data points. Thus, by designing preset interval times and preset number of data collections, vehicle operational data can be collected multiple times, thereby reducing data deviations caused by single data collections.

[0069] S22. Determine whether the difference between multiple running data exceeds a preset threshold. If yes, output an error to alert the user. If no, use the last data as the target running data.

[0070] Specifically, by judging the differences between multiple operational data points, an anomaly alert is immediately output if the difference exceeds a preset threshold. This helps to promptly identify and address potential problems, improving system security. Finally, only when all collected data does not exceed the threshold is the last collected data used as the target operational data, further ensuring data validity and accuracy.

[0071] S30. Determine whether the target query instruction matches the target item to be queried. If yes, output the target running data as output data; otherwise, perform the matching target algorithm and output the calculated data as output data.

[0072] The purpose of determining whether the target query command matches the target item to be queried is to determine whether data acquisition requires indirect computation. When the target query command does not match the target item to be queried, a matching algorithm is used to indirectly obtain the desired output result, thereby improving the flexibility and adaptability of data processing.

[0073] Step S40: Determine whether the output data is within the corresponding safety threshold. If not, output the data according to the preset fault cause.

[0074] The system determines whether the output data is within the corresponding safety threshold, such as driving speed threshold or safe tire pressure threshold. If not, it outputs a preset fault reason, such as speeding or excessive tire pressure, which enhances the system's safety and helps car owners to detect and warn of potential problems in a timely manner.

[0075] For example, when the target query instruction is to query vehicle speed data, the target item to be queried is the running speed within a first preset time period. It is determined that the target query instruction and the target item to be queried are inconsistent. The matching algorithm is the speed average algorithm. The running speed within the first preset time period is calculated based on the speed average algorithm, and the target average value is output as the output data.

[0076] In step S40, after obtaining the target average value, it is further determined whether the speed is within a safe speed threshold, which includes speed thresholds for general road conditions and speed thresholds for highways. Highway periods can be identified based on the ETC connection to obtain the time period, speed, and distance traveled during speeding, thus reminding the driver to drive safely.

[0077] When the target query command is to query fault code data, the target item to be queried is the current fault code, historical fault code, and permanent fault code. If the target query command is consistent with the target item to be queried, the collected current fault code, historical fault code, and permanent fault code will be output.

[0078] To avoid fault code data being too technical and difficult to understand, the system uses a preset display algorithm to convert the fault codes for output display. The preset display algorithm is as follows:

[0079] If(X1<0X40) P + HEX(X1*0X100 + X2);

[0080] Else if(X1<0X80 )) C + HEX((X1-0X40)*0X100 + X2);

[0081] Else if(X1<0XC0) B + HEX((X1-0X80)*0X100 + X2);

[0082] Else U + HEX((X1-0XC0)*0X100 + X2);

[0083] Where P represents powertrain-related faults, C represents chassis-related faults, B represents body-related faults, and U represents network system-related faults; X1 is the first valid bit of the collected target operating data, and X2 is the second valid bit of the collected target operating data. For example:

[0084] Req: 08 07 E0 02 21 00 00 00 00 00 00

[0085] Ans: 08 07 E8 07 61 00 02 00 47 39 33

[0086] If the start bit of the valid bits is 03, then the valid data is 00 47 39 33, X1 = 00, X2 = 47.

[0087] In step S40, after obtaining the fault code data, it is also determined whether the number of corresponding fault codes is within a safe threshold, such as 0. If it exceeds 1, the corresponding preset fault cause (such as P, C, B, U mentioned above) is matched and output.

[0088] When the target query command is to query tire pressure data, the target item to be queried is four tire pressure values. If the target query command is consistent with the target item to be queried, the four tire pressure values ​​will be output.

[0089] The four tire pressure values ​​are the left front, left rear, right front, and right rear tire pressure values, corresponding to step S40 above. If the tire pressure value of one of the tires is lower than the safe tire pressure value, it will be matched as an abnormal tire pressure to remind the owner to maintain the vehicle's tire pressure.

[0090] When the target query instruction is to query oxygen sensor data, the target item to be queried is the voltage signal change of the oxygen sensor. If the target query instruction and the target item to be queried are inconsistent, the matching algorithm is the oxygen sensor voltage value algorithm, and the voltage value within a second preset time period is obtained as the output data for output.

[0091] The condition of the oxygen sensor can be reflected by changes in its voltage signal, providing information on sensor failure and aging. The oxygen sensor voltage value is calculated as y1 = (x1 * 0x100 + x2) * 0.2, in MV. Here, x1 represents the first valid bit of the target operating data, and x2 represents the second valid bit.

[0092] Specifically, corresponding to step S40, after obtaining the oxygen sensor voltage value, it is also determined whether it is within the corresponding safety threshold. The safety threshold is set to 0.1-0.5V, 0.5-0.9V, and 0.4-0.5V. If the voltage changes between 0.1-0.5V, it indicates that the air-fuel mixture is too lean (corresponding to the preset fault cause). If it changes between 0.5-0.9V, it indicates that the air-fuel mixture is too rich (corresponding to the preset fault cause). If it remains unchanged between 0.4-0.5V, it indicates that the oxygen sensor is damaged (corresponding to the preset fault cause). Thus, the corresponding fault cause is output when the voltage falls within different voltage ranges.

[0093] When the target query command is to query fuel system monitoring data, the target item to be queried is the ratio of air intake flow rate to fuel injection quantity. If the target query command and the target item to be queried are inconsistent, the matching algorithm is the air intake flow rate algorithm and the actual fuel injection quantity algorithm. Based on the air intake flow rate algorithm and the actual fuel injection quantity algorithm, the ratio of the two is calculated and output as the output data.

[0094] The fuel system can reflect the air-fuel ratio by detecting the ratio of air intake flow to fuel injection quantity. The calculation method for air intake flow and fuel injection quantity is as follows:

[0095] Air intake flow rate: Calculation expression y=(x1*0x100+x2)*0.01, unit (g / s);

[0096] Actual fuel injection quantity: Calculation expression y=(x1*0x100+x2)*0.02, unit: (g / s);

[0097] Here, x1 and x2 are the same as above, corresponding to the first and second bits of the valid data of the target running data.

[0098] The vehicle control system controls the air-fuel mixture entering the engine to keep it fluctuating around the stoichiometric air-fuel ratio (theoretically, the exhaust emissions are lowest when the air-fuel ratio for complete combustion of the air-fuel mixture is 14.7). If the actual air-fuel ratio calculated by the air intake amount / actual fuel injection amount deviates too much, it will cause data stream abnormalities (corresponding to the reporting of relevant fault codes (P0167-P0194)). The preset fault causes output in step S40 include the mixture being too lean (rich), poor fuel trimming, fuel temperature sensor failure, and pressure sensor failure.

[0099] It should be noted that, based on the above examples of querying vehicle speed data, fault code data, tire pressure data, oxygen sensor data, and fuel system monitoring data, this embodiment does not limit the vehicle operation data queried by the target query command.

[0100] In summary, the data acquisition method based on an OBD vehicle diagnostic system disclosed in the first embodiment of this invention improves the flexibility and adaptability of data acquisition. By matching the consistency between the target query command and the target item to be queried, and using a specific algorithm to perform calculations when there is a discrepancy, it ensures that the output data meets the user's needs. It enhances the system's ability to detect abnormal conditions by performing difference judgment on multiple data acquisitions, and immediately issuing an alert once an anomaly is detected, which helps to promptly discover and resolve problems. It achieves effective early warning in cases where safety thresholds are not met by judging whether the output data is within the corresponding safety threshold, and outputting a preset fault cause when it is not within the safety threshold, thereby improving driving safety.

[0101] [Second Embodiment]

[0102] Please see Figure 3 The second embodiment of this application discloses a remote monitoring system based on an OBD vehicle diagnostic system, which includes a receiving module 210, a data acquisition module 220, a judgment module 230, and an alert mode 240.

[0103] The receiving module 210 is used to receive a target query instruction and match the target item to be queried; the acquisition module 220 is used to acquire the current target operation data of the vehicle based on the target item to be queried; the judgment module 230 is used to judge whether the target query instruction is consistent with the target item to be queried. If yes, the target operation data is output as output data; if no, the target algorithm is matched for calculation, and the calculated data is output as the output data; the reminder mode 240 is used to judge whether the output data is within the corresponding safety threshold. If no, a preset fault cause is matched for output.

[0104] It should be noted that the remote monitoring system based on the OBD vehicle diagnostic system disclosed in the second embodiment of this application is the same as that in the first embodiment, and therefore will not be described in detail here. Optionally, the various modules and other operations or functions in this embodiment are respectively for implementing the methods in the foregoing embodiments.

[0105] [Third Embodiment]

[0106] Please see Figure 3 In the third embodiment of this application, an electronic device is disclosed, which includes a memory 310 and a processor 320. The memory 310 is used to store a computer program; the processor 320 is used to execute the computer program to implement the steps of the data acquisition method based on the OBD vehicle diagnostic system described in the first embodiment above. For details, please refer to the above, so it will not be described in detail here.

[0107] The technical effect of the electronic device provided in this embodiment in practical application is the same as that of the data acquisition method based on the OBD vehicle diagnostic system in the first embodiment.

[0108] [Fourth Embodiment]

[0109] A computer-readable storage medium is disclosed in the fourth embodiment of this application. The computer-readable storage medium is, for example, a non-volatile memory, such as magnetic media (e.g., hard disks, floppy disks, and magnetic tapes), optical media (e.g., CD-ROMs and DVDs), magneto-optical media (e.g., optical discs), and hardware devices specifically configured for storing and executing computer-executable instructions (e.g., read-only memory (ROM), random access memory (RAM), flash memory, etc.). A computer program is stored on the computer-readable storage medium. The computer-readable storage medium can be executed by one or more processors or processing devices to implement the data acquisition method based on the OBD on-board diagnostic system in the foregoing embodiments.

[0110] Furthermore, it is understood that the foregoing embodiments are merely illustrative examples of the present invention. Provided that the technical features do not conflict, the structure is not contradictory, and the purpose of the invention is not violated, the technical solutions of the various embodiments can be arbitrarily combined and used.

[0111] In the embodiments provided by this invention, it should be understood that the disclosed methods, systems, and devices can be implemented in other ways. For example, the modules included in the systems described above are merely illustrative, and the division of modules is only a logical functional division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0112] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0113] Furthermore, in the various embodiments of the present invention, the functional units / modules can be integrated into one processing unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated into one unit / module. The integrated unit / module described above can be implemented in hardware or in the form of hardware plus software functional units / modules.

[0114] The integrated units / modules implemented as software functional units / modules described above can be stored in a computer-readable storage medium. The software functional units stored in this storage medium include several instructions to cause one or more processors of a computer device (which may be a personal computer, server, or network device, etc.) to execute some steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0115] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A data acquisition method based on an OBD vehicle diagnostic system, characterized in that, include: Establish a mapping table between the target query command and the target item to be queried; Receive the target query instruction and match the target item to be queried corresponding to the target query instruction from the mapping table; Based on the target item to be queried, collect the current target operation data of the vehicle; Determine whether the target query instruction matches the target item to be queried. If yes, the target running data is output as output data; otherwise, the target algorithm is matched and the calculated data is output as output data. Determine whether the output data is within the corresponding safety threshold; if not, match the preset fault cause and output it. Specifically, collecting the vehicle's current target operating data based on the target item to be queried includes: Based on the target item to be queried, the preset interval time, and the preset number of collections, multiple operational data of the vehicle are collected; Determine whether the difference between the multiple running data exceeds a preset threshold. If it does, output an error to alert the user. If not, use the last data as the target running data.

2. The method according to claim 1, characterized in that, Before receiving the target query instruction and matching the target item to be queried, the method further includes: A communication connection is established by sending a communication request command and communication rules, wherein the communication rules include communication time, target pin, and target parity bit. If communication is successfully established, data will be collected and output based on the communication rules.

3. The method according to claim 1, characterized in that, When the target query instruction is to query vehicle speed data, the target item to be queried is the running speed within a first preset time period. It is determined that the target query instruction and the target item to be queried are inconsistent. The matching target algorithm is the speed average algorithm. The running speed within the first preset time period is calculated based on the speed average algorithm to obtain the target average value as output data. When the target query instruction is to query fault code data, the target item to be queried is matched as the current fault code, historical fault code and permanent fault code. If the target query instruction is consistent with the target item to be queried, the collected current fault code, historical fault code and permanent fault code are output. The fault code data is output and displayed based on a preset display algorithm, which is as follows: If(X1 <0X40) P + HEX(X1*0X100 + X2); Else if(X1 <0X80 )) C + HEX((X1-0X40)*0X100 + X2); Else if(X1 < 0XC0) B + HEX((X1-0X80)*0X100 + X2); Else U + HEX((X1-0XC0)*0X100 + X2); Wherein, P represents powertrain-related faults, C represents chassis-related faults, B represents body-related faults, and U represents network system-related faults; X1 is the first valid bit of the collected target operating data, and X2 is the second valid bit of the collected target operating data.

4. The method according to claim 3, characterized in that, When the target query instruction is to query tire pressure data, the target item to be queried is four tire pressure values. If the target query instruction is consistent with the target item to be queried, the four tire pressure values ​​are output. When the target query instruction is to query oxygen sensor data, the target item to be queried is the voltage signal change of the oxygen sensor. It is determined that the target query instruction and the target item to be queried are inconsistent. The target algorithm is matched as the oxygen sensor voltage value algorithm, and the voltage value within a second preset time period is obtained as the output data and output.

5. The method according to claim 3, characterized in that, When the target query instruction is to query fuel system monitoring data, the target item to be queried is the ratio of air intake flow rate to fuel injection quantity. If the target query instruction is inconsistent with the target item to be queried, the target algorithm to be matched is the air intake flow rate algorithm and the actual fuel injection quantity algorithm. Based on the air intake flow rate algorithm and the actual fuel injection quantity algorithm, the ratio of the two is calculated and output as output data.

6. A remote monitoring data acquisition system based on an OBD vehicle diagnostic system, characterized in that, For performing the method according to any one of claims 1-5, comprising: The receiving module is used to receive the target query command and match the target item to be queried; The data acquisition module is used to collect the current target operating data of the vehicle based on the target item to be queried; The judgment module is used to determine whether the target query instruction is consistent with the target item to be queried. If so, the target running data is output as output data; if not, the target algorithm is matched and the calculated data is output as output data. The reminder mode is used to determine whether the output data is within the corresponding safety threshold. If not, it will output a preset fault reason.

7. An electronic device, characterized in that, include: Memory and processor, wherein the memory is used to store computer programs; The processor is configured to implement the steps of the method as described in any one of claims 1 to 5 when executing the computer program.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the method as described in any one of claims 1 to 5.

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