Data acquisition method based on OBD (On-Board Diagnostic) system and related equipment

Abstract

The invention 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, and matching a to-be-queried target item; based on the to-be-queried target item, collecting current target operation data of the vehicle; whether the target query instruction is consistent with the to-be-queried target item or not is judged, and if yes, the target operation data serve as output data to be output; if not, matching a target algorithm for operation, and outputting the operated data as the output data; and judging whether the output data is within a corresponding safety threshold, and if not, matching a preset fault reason and outputting. According to the invention, the flexibility and accuracy of the OBD system in the aspect of data acquisition can be improved.

Description

Technical Field

[0001] The present application relates to the technical field of data acquisition in an on-board diagnostic system, and in particular to a data acquisition method and related equipment based on an OBD on-board diagnostic system. Background Art

[0002] On-Board Diagnostic (OBD) is a system used to monitor the performance and emissions of automobile engines. With the development of the automobile industry, the OBD system has become one of the standard configurations of modern vehicles. Through this system, various operating parameters of the vehicle can be obtained in real time, thereby helping the driver to promptly discover potential problems and improve driving safety and maintenance efficiency. In addition, the application of the OBD system has also expanded to the fields of remote monitoring and fault diagnosis, providing important technical support for automobile maintenance services.

[0003] In order to effectively monitor and manage the vehicle status, existing technical solutions usually adopt the following methods: first, manually read the vehicle's operating data by connecting to a dedicated OBD scanning tool; second, use the application on the mobile device to communicate with the vehicle's OBD interface through Bluetooth or Wi-Fi to automatically collect the required operating information; third, the remote data collection function integrated in the Internet of Vehicles platform can extract key indicators from multiple vehicles in batches regularly or on demand. Although these methods can meet the needs of users to a certain extent, they still have some limitations in actual operation.

[0004] The common OBD data collection method currently relies mainly on a simple command sending and response mechanism, which cannot flexibly respond to complex and changing query requirements. For example, when users want to obtain comprehensive evaluation results under specific conditions, traditional methods can only return data of a single dimension, and cannot combine multiple factors for in-depth analysis. In addition, for data processing in certain special cases, such as low threshold alarms, the existing technology also lacks effective solutions, which may cause users to miss important warning information, thereby affecting driving safety. Therefore, how to improve the flexibility and accuracy of the OBD system in data collection has become a key issue that needs to be solved urgently. 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 the OBD system in data acquisition.

[0006] In a first aspect, an embodiment of the present application discloses a data collection method based on an OBD vehicle diagnostic system, which adopts the following scheme: A data collection method based on an OBD vehicle diagnostic system includes: receiving a target query instruction and matching a target item to be queried; based on the target item to be queried, collecting the current target operation data of the vehicle; judging whether the target query instruction is consistent with the target item to be queried, if so, outputting the target operation data as output data; if not, matching a target algorithm for operation, and outputting the operated data as the output data; judging whether the output data is within a corresponding safety threshold, if not, matching a preset fault cause for output.

[0007] By adopting the above technical solution, accurate collection and processing of vehicle operation data can be achieved. Specifically: receiving the target query instruction and matching the target item to be queried ensures the purposefulness and accuracy of data collection. Collecting the current target operation data of the vehicle based on the target item to be queried ensures the authenticity and timeliness of the data. Determine whether the target query instruction is consistent with the target item to be queried, and match the target algorithm for calculation when they are inconsistent, thereby improving the flexibility and adaptability of data processing. Determine whether the output data is within the corresponding safety threshold. If not, output the preset fault cause, enhance the security of the system, and timely discover and warn potential problems.

[0008] Optionally, before receiving the target query instruction and matching the target item to be queried, it also includes: establishing a mapping table between the target query instruction and the target item to be queried; wherein, after receiving the target query instruction, matching the target item to be queried corresponding to the target query instruction from the mapping table.

[0009] By adopting the above technical solution, the mapping relationship between the target query instruction and the target item to be queried can be established in advance, so that the corresponding target item to be queried can be quickly and accurately matched after receiving the target query instruction, thereby improving the efficiency and accuracy of data collection. At the same time, it avoids human errors caused by manual matching and improves the stability and reliability of the system.

[0010] Optionally, based on the target item to be queried, collecting the vehicle's current target operating data specifically includes: based on the target item to be queried, a preset interval time and a preset number of collections, collecting multiple operating data of the vehicle; judging whether the difference between the multiple operating data exceeds a preset threshold, if so, outputting an exception to remind, if not, taking the last data as the target operating data.

[0011] By adopting the above technical solution, it is possible to ensure that the collected data is more accurate and reliable. First, by setting a preset interval time and a preset number of collections, the vehicle's operating data can be collected multiple times, thereby reducing the data deviation caused by a single collection. Secondly, by judging the difference between multiple operating data, if the difference exceeds the preset threshold, an abnormal reminder is immediately output, which helps to promptly discover and deal with potential problems and improve the safety of the system. If the difference does not exceed the threshold, the last data is used as the target operating data to ensure the validity and accuracy of the data.

[0012] Optionally, before receiving the target query instruction and matching the target item to be queried, it also includes: sending a communication request instruction and communication rules to establish a communication connection, the communication rules including communication time, target pin and target check bit; if the communication is successfully established, data is collected and output based on the communication rules.

[0013] By adopting the above technical solution, it is possible to ensure that a reliable communication connection is established before receiving the target query instruction, thereby improving the accuracy and reliability of data collection. Specifically, the communication request instruction and communication rules can pre-set the communication time, pin and verification method to ensure that the devices of both parties can exchange data under the correct configuration. If the communication is successful, data is collected and output according to the predetermined communication rules to avoid data errors or losses caused by communication problems.

[0014] Optionally, when the target query instruction is to query vehicle speed data, the target item to be queried is matched to the running speed within a first preset time, it is determined that the target query instruction is inconsistent with the target item to be queried, the target algorithm matched is a speed average algorithm, the running speed within the first preset time is calculated based on the speed average algorithm, and the target average is obtained as output data for output; When the target query instruction is to query fault code data, the target items to be queried are matched with the current fault code, the historical fault code and the permanent fault code, and it is determined that the target query instruction is consistent with the target item to be queried, then the collected current fault code, the historical fault code and the permanent fault code are output; The fault code data is output and displayed based on a preset display algorithm, and the preset display algorithm 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); Among them, P represents power system related faults, C represents chassis related faults, B represents body related faults, and U represents network system related faults; X1 is the first bit of the valid bit of the collected target operation data, and X2 is the second bit of the valid bit of the collected target operation data.

[0015] By adopting the above technical solution, accurate data processing and output are achieved for different types of query instructions: when the target query instruction is to query vehicle speed data, it can automatically match the running speed within the first preset time, and when it is determined that the query instruction is inconsistent with the item to be queried, the speed average algorithm is used to calculate the average speed of the vehicle within the time period, thereby improving data accuracy and reliability. For the query needs of fault code data, not only can the current fault code, historical fault code and permanent fault code be obtained at the same time, but also it supports the analysis of various types of fault codes (such as power system, chassis, body or network system faults) based on specific display algorithms, ensuring comprehensive coverage and accurate expression of fault information, helping to quickly locate the source of the problem and improve maintenance efficiency and service quality.

[0016] 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, and it is judged that the target query instruction is consistent with the target item to be queried, and 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, and it is judged that 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 the second preset time is obtained as the output data for output.

[0017] By adopting the above technical solution, accurate query and processing of vehicle tire pressure and oxygen sensor data can be achieved. For tire pressure data, the pressure values ​​of the four tires can be obtained and output in real time, ensuring that the driver can understand the status of each tire in a timely manner and improve driving safety. When the target query instruction is to query oxygen sensor data, when the target item to be queried is inconsistent with the target query instruction, the voltage value within the second preset time is accurately calculated by matching a specific algorithm, thereby providing a reliable basis for subsequent diagnosis.

[0018] Optionally, when the target query instruction is to query the fuel system monitoring data, the target item to be queried is matched with the ratio of air intake flow and fuel injection amount, and it is judged that the target query instruction is inconsistent with the target item to be queried. The matched target algorithms are the air intake flow algorithm and the actual fuel injection amount algorithm, and based on the air intake flow algorithm and the actual fuel injection amount algorithm, the ratio of the two is calculated and output as output data.

[0019] By adopting the above technical solution, it is possible to provide accurate data processing methods for different target query instructions. When the target query instruction is to query the fuel system monitoring data, the system first matches the target item to be queried as the ratio of air intake flow and fuel injection amount, and then determines the inconsistency between the target query instruction and the target item to be queried, and then matches the corresponding target algorithm-air intake flow algorithm and actual fuel injection algorithm. By calculating the air intake flow and fuel injection amount, the ratio of the two is finally output as the result data. This processing method not only improves the accuracy and reliability of the data, but also can more intuitively reflect the operating status of the fuel system, which helps to timely discover potential problems and take corresponding measures.

[0020] In a second aspect, an embodiment of the present application discloses a remote monitoring system based on an OBD vehicle diagnostic system, which adopts the following scheme: A remote monitoring data acquisition system based on an OBD vehicle diagnostic system comprises: a receiving module, used for receiving a target query instruction and matching a target item to be queried; a collecting module, used for collecting the current target operation data of a vehicle based on the target item to be queried; a judging module, used for judging whether the target query instruction is consistent with the target item to be queried, if so, outputting the target operation data as output data; if not, matching a target algorithm for operation, and outputting the operated data as the output data; and a reminder mode, used for judging whether the output data is within a corresponding safety threshold, if not, matching a preset fault cause for output.

[0021] By adopting the above technical solution, the remote monitoring data acquisition system can realize real-time monitoring and data analysis of vehicle operation status. The specific effects are as follows: The receiving module accurately matches the target query instruction with the target item to be queried, ensuring the accuracy of data collection. At the same time, the judgment module can verify the consistency of the target query instruction and the target item to be queried, avoiding data deviation caused by instruction errors. When the target query instruction is inconsistent with the target item to be queried, the system will automatically match the target algorithm for calculation, thereby improving the flexibility and adaptability of the system and being able to handle various complex data requirements. The reminder mode can trigger the preset reminder method based on whether the output data is within the corresponding safety threshold, promptly notifying the user of potential problems or risks, and enhancing the security and practicality of the system.

[0022] In a third aspect, an embodiment of the present application discloses an electronic device, which adopts the following solution: An electronic device comprises: a memory and a processor, wherein the memory is used to store a computer program; and the processor is used to implement the steps of any of the above methods when executing the computer program.

[0023] In a fourth aspect, an embodiment of the present application discloses a computer-readable storage medium, which adopts the following scheme: A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of any of the above methods are implemented.

[0024] In summary, the present application includes at least one of the following beneficial technical effects: 1. Improve the accuracy and reliability of OBD data collection by judging the consistency between the received target query instruction and the target item to be queried, and matching the corresponding algorithm for calculation when there is inconsistency, to ensure that the output data meets the specific needs of users; 2. The system has enhanced its ability to identify abnormal conditions. By performing differential judgment on multiple collected operating data, it will immediately issue an abnormal reminder once a situation exceeding the preset threshold is found, which helps to detect problems early and take measures; 3. It realizes effective early warning for situations below the safety threshold, and improves driving safety by judging whether the output data is within the safety threshold and matching the preset fault cause to give a prompt when it is not within the safety threshold. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 A process architecture applied to a data collection method based on an OBD vehicle diagnostic system disclosed in an embodiment of the present application; Figure 2 A flow chart of a data collection method based on an OBD vehicle diagnostic system disclosed in an embodiment of the present application; Figure 3 A schematic diagram of the structure of a remote monitoring system based on an OBD vehicle diagnostic system disclosed in another embodiment of the present application; Figure 4 This is a schematic diagram of the structure of an electronic device disclosed in yet another embodiment of the present application. DETAILED DESCRIPTION

[0026] The present application is further described in detail below in conjunction with the accompanying drawings.

[0027] The embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although the embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided to make the present application more thorough and complete, and to fully convey the scope of the present application to those skilled in the art.

[0028] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "an" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0029] It should be understood that although the terms "first", "second", etc. may be used in the present application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0030] The technical solution of the embodiments of the present application is described in detail below with reference to the accompanying drawings.

[0031] [First embodiment] See also Figure 1 , which is a process architecture applied by a data collection method based on an OBD vehicle diagnostic system disclosed in an embodiment of the present application, involving an electronic device (mobile phone, tablet or computer), an OBD device (corresponding to the OBD system) and an automobile ECU (Electronic Control Unit). The electronic device is installed with corresponding APP software and is wirelessly connected to the OBD device to achieve communication with the OBD system. The OBD device is installed on the automobile through the OBD interface to achieve communication between the OBD system and the automobile ECU. The OBD device is used to collect automobile operation data, so as to calculate the operation data or directly transmit it to the APP of the electronic device for display.

[0032] Specifically, a data collection method based on an OBD vehicle diagnostic system includes the following steps: S10, receiving a target query instruction and matching a target item to be queried; Among them, when receiving a target query instruction, for example, the user selects "query vehicle speed" through the electronic device, the corresponding matching target item system matches and queries the average running speed of the vehicle within the first preset time. Of course, the target query instruction here can be one of querying vehicle speed data, fault code data, tire pressure data, oxygen sensor data, querying fuel system monitoring data, etc.

[0033] Specifically, before step S10, the method further includes: S01, establishing a mapping table between target query instructions and target items to be queried; The mapping table is a pre-stored database that contains the relationship between various query instructions and their corresponding data items. For example, if the target query instruction is to query the vehicle speed data, the corresponding query data item is the average running speed of the vehicle within the first preset time. If the target query instruction is to query the fault code data, the corresponding query data item is the current fault code, historical fault code and permanent fault code.

[0034] Based on the setting of the mapping table, 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 to improve the efficiency and accuracy of data collection.

[0035] Furthermore, before step S10, the method further includes: S02, sending a communication request instruction and a communication rule to establish a communication connection; In step S02, the OBD device is connected to the vehicle ECU through communication. The OBD device is connected to the vehicle ECU through communication by sending CAN (Controller Area Network) protocol commands, KWP protocol or VPW protocol.

[0036] The communication rules include communication time, target pin and target check bit. The communication time is the time parameter for each data communication. The target pin is, for example, the 10th pin of the OBD interface. The target check bit is, for example, CRC-16. This ensures that the communication link between the system and the OBD interface is unimpeded and reduces the risk of data loss due to communication failure.

[0037] S03. If the communication is established successfully, data is collected and output based on the communication rules.

[0038] If the communication is successful, data collection and output are performed according to predetermined communication rules, thereby avoiding data errors or losses caused by communication problems.

[0039] S20, based on the target item to be queried, collecting the current target operation data of the vehicle; Among them, the corresponding operation data is collected based on the target item to be queried, which increases the pertinence, timeliness and authenticity of data collection. For example, if the target item to be queried is to query the fault code data, the current fault code, historical fault code and permanent fault code of the vehicle are collected accordingly.

[0040] Specifically, step S20 also includes: S21, collecting multiple operation data of the vehicle based on the target item to be queried, the preset interval time and the preset number of collections; Wherein, the preset interval time is, for example, 1S, and the preset number of collections is 3 times, then 3 operation data are collected accordingly. Thus, by designing the preset interval time and the preset number of collections, the operation data of the vehicle can be collected multiple times, thereby reducing the data deviation caused by a single collection.

[0041] S22, determining whether the difference between the multiple operation data exceeds a preset threshold, if so, outputting an abnormality to remind, if not, taking the last data as the target operation data.

[0042] Among them, by judging the difference between multiple operating data, if the difference exceeds the preset threshold, an abnormal reminder is immediately output, which helps to timely discover and deal with potential problems and improve the safety of the system. Finally, only when all collected data do not exceed the threshold, the last data is used as the target operating data, which further ensures the validity and accuracy of the data.

[0043] S30, determining whether the target query instruction is consistent with the target item to be queried, if so, outputting the target operation data as output data; if not, matching the target algorithm to perform calculations, and outputting the calculated data as output data; Among them, it is determined whether the target query instruction is consistent with the target item to be queried. The purpose of this setting is to determine whether the acquisition of data requires indirect calculation. When the target query instruction is inconsistent with the target item to be queried, the target algorithm is matched for calculation to indirectly obtain the desired output result, thereby improving the flexibility and adaptability of data processing.

[0044] Step S40: determine whether the output data is within the corresponding safety threshold. If not, match the preset fault cause for output.

[0045] Among them, it is judged whether the output data is within the corresponding safety threshold, such as the driving speed threshold, the safe tire pressure threshold, etc. If not, the preset fault cause is output, such as speeding, excessive tire pressure, etc., which enhances the safety of the system and helps car owners to discover and warn of potential problems in time.

[0046] For example, when the target query instruction is to query vehicle speed data, the target item to be queried is matched to the running speed within the first preset time, and it is determined that the target query instruction is inconsistent with the target item to be queried. The matching target algorithm is the speed average algorithm, and the running speed within the first preset time is calculated based on the speed average algorithm to obtain the target average value as output data; In step S40, after obtaining the target average value, it is also determined whether it is within the safe speed threshold, which includes the speed threshold for general road conditions and the high-speed speed threshold. The high-speed period can be identified based on the ETC connection to obtain the time period, speed and driving distance of the speeding to remind the owner to drive safely.

[0047] When the target query instruction is to query fault code data, the target items to be queried are matched with the current fault code, historical fault code and permanent fault code. If the target query instruction is judged to be consistent with the target item to be queried, the collected current fault code, historical fault code and permanent fault code will be output.

[0048] In order to prevent the fault code data from being too professional and difficult to understand, the system will use a preset display algorithm to convert the fault code for output display. The preset display algorithm 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); Among them, P represents power system related faults, C represents chassis related faults, B represents body related faults, and U represents network system related faults; X1 is the first bit of the valid bit of the collected target operation data, and X2 is the second bit of the valid bit of the collected target operation data, for example: Req: 08 07 E0 02 21 00 00 00 00 00 00 Ans: 08 07 E8 07 61 00 02 00 47 39 33 The valid bit starts at 03, so the valid data is 00 47 39 33, X1 = 00, X2 = 47.

[0049] Among them, corresponding to step S40, after obtaining the fault code data, it will also be determined whether the corresponding number of fault codes is within a safety threshold, such as 0. If it exceeds 1, the preset fault cause (such as P, C, B, U mentioned above) is matched and output.

[0050] When the target query instruction is to query tire pressure data, the target items to be queried are matched to four tire pressure values, and if it is determined that the target query instruction is consistent with the target item to be queried, the four tire pressure values ​​are output.

[0051] Among them, the four tire pressure values ​​are the left front, left rear, right front, and right rear tire pressure values, corresponding to the above step S40. If the tire pressure value of one of them is lower than the safe tire pressure value, it will match the tire pressure abnormality to prompt the owner to maintain the vehicle tire pressure.

[0052] When the target query instruction is to query the oxygen sensor data, the target item to be queried is matched with the voltage signal change of the oxygen sensor, it is judged that 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 the second preset time is obtained as output data for output.

[0053] The condition of the oxygen sensor can be reflected according to the change of the voltage signal of the oxygen sensor to reflect the failure and aging monitoring information of the oxygen sensor. The oxygen sensor voltage value algorithm is y1 = (x1*0x100+x2)*0.2, in units of Mv. Here, x1 is the first bit of the valid bit of the target operation data, and x2 is the second bit of the valid bit of the target operation data.

[0054] Specifically, corresponding to step S40, after obtaining the voltage value of the oxygen sensor, it will also be determined whether it is within the corresponding safety threshold, where 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 means that the mixture is too lean (corresponding to the preset fault cause); if it changes between 0.5-0.9V, it means that the mixture is too rich (corresponding to the preset fault cause); if it does not change between 0.4-0.5V, it means that the oxygen sensor is damaged (corresponding to the preset fault cause), so that the corresponding fault cause is output when it falls within different voltage ranges.

[0055] When the target query instruction is to query the fuel system monitoring data, the target item to be queried is matched with the ratio of the air intake flow rate and the fuel injection amount. It is judged that the target query instruction is inconsistent with the target item to be queried. The matched target algorithms are the air intake flow rate algorithm and the actual fuel injection amount algorithm. Based on the air intake flow rate algorithm and the actual fuel injection amount algorithm, the ratio of the two is calculated and output as output data.

[0056] Among them, the fuel system can be reflected by detecting the ratio of air intake flow and fuel injection amount, that is, the air-fuel ratio. The algorithm of air intake flow and fuel injection amount is as follows: Air intake flow rate: calculation expression y = (x1*0x100+x2)*0.01, unit (g / s); Actual injection amount: calculation expression y = (x1*0x100+x2)*0.02, unit: (g / s); Here, x1 and x2 are the same as above, and correspond to the first and second data of the valid bits of the target running data to be collected.

[0057] Among them, the automobile control system controls the mixture entering the engine to keep it fluctuating near the theoretical air-fuel ratio (theoretically, when the air-fuel ratio of complete combustion of the mixture is 14.7, the exhaust emission is the lowest). When the actual air-fuel ratio calculated by the air intake volume / actual fuel injection volume deviates too much, it will cause data flow abnormality (correspondingly, the relevant fault code (P0167-P0194) will be reported). The preset fault causes output in step S40 include too lean (rich) mixture ratio, poor fuel correction, fuel temperature sensor failure, and pressure sensor failure.

[0058] It is explained here 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, in this embodiment, the vehicle operation data corresponding to the target query instruction is not limited.

[0059] In summary, the data collection method based on the OBD vehicle diagnostic system disclosed in the first embodiment of the present invention improves the flexibility and adaptability of data collection by matching the consistency of the target query instruction with the target item to be queried, and using a specific algorithm for calculation when there is inconsistency, thereby ensuring that the output data meets the user's needs; enhancing the system's ability to detect abnormal conditions, by performing difference judgment on data collected multiple times, and immediately issuing a reminder once an abnormality is found, which helps to promptly discover and solve problems; achieving effective early warning when the safety threshold is not met, by judging whether the output data is within the corresponding safety threshold, and outputting the preset fault cause when it is not within the safety threshold, thereby improving driving safety.

[0060] [Second embodiment] See also Figure 3 In the second embodiment of the present application, a remote monitoring system based on an OBD vehicle diagnostic system is disclosed. The system includes: a receiving module 210, a collection module 220, a judgment module 230 and a reminder mode 240.

[0061] Among them, the receiving module 210 is used to receive the target query instruction and match the target item to be queried; the collecting module 220 is used to collect the current target operation data of the vehicle based on the target item to be queried; the judging module 230 is used to judge whether the target query instruction is consistent with the target item to be queried, if so, the target operation data is output as output data; if not, 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 not, the preset fault cause is matched for output.

[0062] It should be noted that the method for remote monitoring of an OBD vehicle diagnostic system implemented by a remote monitoring system based on an OBD vehicle diagnostic system disclosed in the second embodiment of the present application is the same as the first embodiment, so it will not be described in detail here. Optionally, each module in this embodiment and the above-mentioned other operations or functions are respectively for implementing the methods in the aforementioned embodiments.

[0063] [Third embodiment] See also Figure 3 In the third embodiment of the present application, an electronic device is disclosed, which includes: a memory 310 and a processor 320, the memory 310 is used to store computer programs; the processor 320 is used to implement the steps of the data acquisition method based on the OBD vehicle diagnostic system described in the first embodiment when executing the computer program. For details, please refer to the above, so it will not be described in detail here.

[0064] The technical effect of the electronic device provided by this embodiment in actual application is the same as the technical effect of the data collection method based on the OBD vehicle diagnostic system in the first embodiment.

[0065] [Fourth embodiment] In the fourth embodiment of the present application, a computer-readable storage medium is disclosed. The computer-readable storage medium is, for example, a non-volatile memory, such as: magnetic media (such as hard disks, floppy disks and tapes), optical media (such as CDROM disks and DVDs), magneto-optical media (such as optical disks) and hardware devices specially constructed to store and execute computer-executable instructions (such as 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 vehicle diagnostic system in the aforementioned embodiment.

[0066] In addition, it can be understood that the aforementioned embodiments are only exemplary descriptions of the present invention. Under the premise that the technical features do not conflict, the structures do not contradict, and the purpose of the present invention is not violated, the technical solutions of the various embodiments can be arbitrarily combined and used in combination.

[0067] In the several embodiments provided by the present 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 system described above are only schematic, and the division of modules is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0068] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0069] In addition, each functional unit / module in each embodiment of the present invention may be integrated into one processing unit / module, or each unit / module may exist physically separately, or two or more units / modules may be integrated into one unit / module. The above-mentioned integrated unit / module may be implemented in the form of hardware or in the form of hardware plus software functional units / modules.

[0070] The above-mentioned integrated unit / module implemented in the form of a software functional unit / module can be stored in a computer-readable storage medium. The above-mentioned software functional unit is stored in a storage medium, including a number of instructions for enabling one or more processors of a computer device (which can be a personal computer, a server, or a network device, etc.) to perform some steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store program codes.

[0071] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions 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: Receive target query instructions and match target items to be queried; Based on the target item to be queried, collecting the current target operation data of the vehicle; Determine whether the target query instruction is consistent with the target item to be queried, if so, output the target operation data as output data; if not, match the target algorithm to perform calculation, and output the calculated data as the output data; Determine whether the output data is within the corresponding safety threshold, and if not, match the preset fault cause for output.

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: Establishing a mapping table between the target query instruction and the target item to be queried; After receiving the target query instruction, the target item to be queried corresponding to the target query instruction is matched from the mapping table.

3. The method according to claim 1, characterized in that The collecting of the current target operation data of the vehicle based on the target item to be queried specifically includes: Based on the target item to be queried, the preset interval time and the preset number of collection times, multiple operation data of the vehicle are collected; It is determined whether the difference between the multiple operation data exceeds a preset threshold value. If so, an abnormality is output to remind. If not, the last data is used as the target operation data.

4. 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: Sending a communication request instruction and a communication rule to establish a communication connection, wherein the communication rule includes a communication time, a target pin and a target check bit; If the communication is successfully established, data is collected and output based on the communication rules.

5. 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 matched to the running speed within a first preset time, it is determined that the target query instruction is inconsistent with the target item to be queried, the target algorithm to be matched is the speed average algorithm, the running speed within the first preset time is calculated based on the speed average algorithm, and the target average is obtained as output data for output; When the target query instruction is to query fault code data, the target items to be queried are matched with the current fault code, the historical fault code and the permanent fault code, and it is determined that the target query instruction is consistent with the target item to be queried, then the collected current fault code, the historical fault code and the permanent fault code are output; The fault code data is output and displayed based on a preset display algorithm, and the preset display algorithm 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); Among them, P represents power system related faults, C represents chassis related faults, B represents body related faults, and U represents network system related faults; X1 is the first bit of the valid bit of the collected target operation data, and X2 is the second bit of the valid bit of the collected target operation data.

6. The method according to claim 5, characterized in that When the target query instruction is to query tire pressure data, the target items to be queried are matched to four tire pressure values, and if it is determined that the target query instruction is consistent with the target items 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, it is determined that 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 the second preset time is obtained as the output data for output.

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

8. A remote monitoring data acquisition system based on an OBD vehicle diagnostic system, characterized in that: include: A receiving module is used to receive a target query instruction and match the target item to be queried; A collection module, used for collecting the current target operation data of the vehicle based on the target item to be queried; A judgment module is used to judge whether the target query instruction is consistent with the target item to be queried. If so, the target operation data is output as output data; if not, the target algorithm is matched to perform calculations, and the calculated data is output as the output data; The reminder mode is used to determine whether the output data is within the corresponding safety threshold. If not, the output is matched with the preset fault cause.

9. An electronic device, characterized in that: include: A memory and a processor, wherein the memory is used to store a computer program; and the processor is used to implement the steps of the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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