TWM575160U - Vehicle data acquisition automatic adaptation device - Google Patents

Abstract

The present invention provides a vehicle data acquisition automatic adaptation device, comprising: a database module for establishing a vehicle data database, the database comprising an adaptation table and a plurality of data sub-tables, the adaptation table is used for Recording the correspondence between the vehicle type and the data sub-table identification, the data sub-table is used to record the acquisition rule of the vehicle data in a certain vehicle type; the target vehicle type acquisition module is used to acquire the target vehicle type of the target vehicle; the positioning module, a target data sub-table corresponding to the target vehicle type according to the target vehicle type; a monitoring module for monitoring data obtained by the on-board computer broadcast to obtain a data source; and an acquisition module for using the target data according to the target data The vehicle data acquisition rules recorded in the table obtain vehicle data in the data source. The new model has universal applicability and can be applied to various types of vehicles, breaking through the limitations of the prior art that can only be applied in a single vehicle.

Description

Vehicle data acquisition automatic adaptation device

The present invention relates to the field of vehicles, and in particular, to a method and an apparatus for automatically adapting vehicle data acquisition.

The function of the CAN decoding module is to access various information such as vehicle speed, speed, water temperature, voltage, mileage, oil quantity, key status, door status, lighting status, etc., by connecting to the vehicle CAN bus, and converting it into relative The standard format is output to other devices for use by other devices, such as car display screens, parking sensors, and lane offset alarms. The CAN decoding modules on the market are all single models. Because the CAN data format is proprietary to each car manufacturer, there is no fixed format, and the data difference between different brands is very large. Moreover, the information available on a single model is very large, and the decoding workload of a single model is already large. At present, the monitoring and decoding on the market are all for a single model. Users can only use a single module for a single model. Once the brand model is replaced, only the module is reburned or replaced, and the crossover model is very inconvenient.

In order to solve the above problems, the present invention provides a method and device for automatically adapting vehicle data acquisition.

The present invention is realized by the following technical solutions. A vehicle data acquisition automatic adaptation method comprises: establishing a vehicle data adaptation database, the data library comprising an adaptation table and a plurality of data sub-tables, wherein the adaptation table is used for recording the correspondence between the vehicle type and the data sub-table identifier Relationship, the data sub-table is used to record the acquisition rule of the vehicle data in a certain vehicle type; acquire the target vehicle type of the target vehicle; locate the target data sub-table corresponding to the target vehicle type according to the target vehicle type; monitor the on-board computer broadcast The data is obtained from the data source; and the vehicle data is obtained from the data source according to the vehicle data acquisition rules recorded in the target data sub-table.

Further, the method further includes: monitoring data broadcasted by the on-board computer; analyzing the data to extract target vehicle data.

Further, the extracting the target vehicle data includes: acquiring the first data package according to the first preset time; performing a target operation for generating the target vehicle data, and monitoring the data in the second preset time to obtain the second data The package; and the horizontal comparison of the first data package and the second data package to obtain the first range.

Further, the method further includes: recording a positioning parameter of the target vehicle data; the positioning parameter includes a communication rate, a monitoring data packet identifier, a valid byte group, a binary conversion identifier, and a data conversion formula.

Further, if different positioning parameters of the vehicle data can be represented as a communication rate, a monitoring packet identification, a valid byte, a binary conversion identifier, and a data conversion formula, the logical structure of each data sub-table is designed as It includes six fields: vehicle data type, communication rate, monitor packet identification, valid byte, binary conversion identifier, and data conversion formula.

Further, if the fields of the positioning parameters of different vehicle materials are different, the logical structure of each data sub-table is designed to include the vehicle data type and the BLOB two fields.

A vehicle data acquisition automatic adaptation device comprises: a database module for establishing a vehicle data adaptation database, the database comprising an adaptation table and a plurality of data sub-tables, the adaptation table is used for recording the vehicle The correspondence between the type and the data sub-table identifier, the data sub-table is used to record the acquisition rule of the vehicle data in a certain vehicle type; the target vehicle type acquisition module is used to acquire the target vehicle type of the target vehicle; the positioning module is used for Determining, according to the target vehicle type, a target data sub-table corresponding to the target vehicle type; a monitoring module, configured to monitor data collected by the on-board computer to obtain a data source; and acquiring a module, configured to record according to the target data sub-table The vehicle data acquisition rule obtains the vehicle data in the data source.

The utility model has the beneficial effects that the new embodiment discloses a method and a device for automatically acquiring vehicle data acquisition, which can explore rules for analyzing and acquiring vehicle data in various vehicles, and the obtained rules are The form of the database is recorded, and the state of each component of all vehicles is output in a uniform format, so that the device capable of automatically adapting the vehicle data acquisition in the present invention has universal applicability and can be applied to various types of vehicles, breaking through The prior art can only be limited in the application of a single vehicle.

In order to make the objects, technical solutions and advantages of the present invention more clear, the present invention will be further described in detail below with reference to the accompanying drawings.

The embodiment of the present invention provides an automatic adaptation method for vehicle data acquisition, as shown in FIG. 1 , which includes: S101. Establishing a vehicle data adaptation database, the database includes an adaptation table and a plurality of data sub-tables. The matching table is used to record the correspondence between the vehicle type and the data sub-table identification, and the data sub-table is used to record the acquisition rules of the vehicle data in a certain vehicle type. Specifically, the vehicle data acquisition rules in different vehicles are different, and therefore it is necessary to establish an adaptation database. How to obtain vehicle data acquisition rules will be elaborated below. S102. Obtain a target vehicle type of the target vehicle. S103. Locating a target data sub-table corresponding to the target vehicle type according to the target vehicle type. S104. Monitor the data of the on-board computer broadcast to get the data source. S105. Obtain vehicle data in the data source according to the vehicle data acquisition rule recorded in the target data sub-table.

Further, the obtained rules are recorded in the form of a database, and the state of each component of all vehicles can also be output in a uniform format. The data of each model is output to a head-up display, a mobile phone, a car display screen, and other devices that require the vehicle data in a uniform format.

The present embodiment uses a means of monitoring to acquire a data source, whereas in the prior art, vehicle data is typically acquired based on a diagnostic mode. In order to facilitate highlighting the technical advantages of the novel embodiment, the diagnostic mode and the listening mode are summarized as follows.

Diagnostic mode: After the hardware connection is completed, the connection is requested to the onboard computer, and a two-way communication link is established in response to the confirmation command from the onboard computer. In the diagnostic mode, the acquisition of vehicle internal data is based on the interaction with the onboard computer, and only one reply can be obtained per request. In order to obtain multiple internal data, multiple requests are required.

The advantage of the diagnostic model is the ability to obtain clear target data. The disadvantages are: (1) If the on-board computer is busy, it cannot respond in time, resulting in lag or even failure to obtain internal data. (2) Frequent inquiries will cause the on-board computer to overload, and thus cause vehicle safety hazards. The most common faults are the vehicle reporting fault code, the airbag light is on, and the ESP is working abnormally. In severe cases, the on-board computer may lock the engine out of theft for reasons such as theft, causing the vehicle to fail to ignite. (3) If an instruction to the vehicle computer requesting the internal data of the vehicle is sent incorrectly, it may cause abnormal control of the computer, and the consequences are unpredictable. (4) Based on the agreement followed by the diagnostic mode, the time interval between each query data must be greater than 50MS, and after sending the query, the on-board computer needs an average of 10~30MS to give a reply, and an interaction process takes nearly 70MS to obtain the internal information of the vehicle. At the expense of a lot of time, the timeliness is poor. For example, taking five kinds of data inside the vehicle as an example, if each data needs 70MS to obtain, then obtaining the above five materials requires at least 350MS. During the running of the vehicle, the internal data of the vehicle needs to be acquired by the loop, which means that there will be more than 350 MS intervals between each loop, which is unacceptable for the application scenario with high timeliness requirements. For example, the speed of the vehicle is normal. When the vehicle starts to accelerate from a standstill, the speed should be gradually displayed from 0-9. If the speed is too long, 0 will go directly to 10, and there will be no excessive jump display in the middle. The user experience is significant. decline. (5) In the diagnosis mode, the internal data type output by the on-board computer is limited. According to the different car manufacturers, about 20 kinds of data can be output, which cannot meet the display requirements.

Listening mode: Monitors data transmitted on the vehicle's internal network.

The disadvantage of the listening mode is that the data being monitored is the original data, and the target data cannot be directly obtained. The advantages are: (1) One-way communication is not limited by the load status of the on-board computer, and there is no possibility of sending a wrong command to the on-board computer, which may cause serious consequences, and does not cause interference to the on-board computer. (2) It is not limited to the diagnostic mode, and the time interval is limited, and the timeliness is good. (3) There is no limit to the output content of the on-board computer in the diagnostic mode, and more types of internal data can be obtained.

Specifically, in order to evaluate the performance of acquiring vehicle internal data based on the listening mode, the new embodiment tests a lot of this, and the fastest group of data packets is separated by only 5MS, and a group of data packets contains multiple different materials. . The data acquisition speed of the monitor mode is more than ten times that of the diagnostic mode. Take Fox as an example. If you get the speed and speed in the diagnostic mode, you need to ask the vehicle speed 50MS first, wait for the 20MS to get the reply, then ask the speed by 50MS, wait for the 20MS to get the reply, wait for the 50MS to ask the speed, and wait for the 20MS to get a reply. And so on, the time interval for reading the vehicle speed twice in succession is 50+20+50+20+50+20=210MS. The monitoring method only needs to monitor the data packet and analyze the speed and speed from it. For Fox, only 5MS is needed.

In view of this, the present invention provides a method for acquiring vehicle data based on a listening mode. As shown in FIG. 2, the method includes: S201. Monitoring data broadcasted by an on-board computer. Specifically, in the new embodiment, the information of the on-board computer broadcast is obtained by monitoring the vehicle CAN bus bar and/or the LIN bus bar. Taking the CAN bus as an example, the hardware connection is first performed in S201, and the monitoring can be started after the relevant hardware connection is completed and the parameters are configured. The parameters include the communication frequency and the protocol specification. During the monitoring process, a large amount of vehicle data can be received without any two-way communication with the onboard computer. The data itself needs to be regularly transmitted in large quantities during the work of the vehicle. For example, the data of the engine needs to be transmitted to the instrument for display, and the gearbox data needs to be sent to the on-board computer for data sorting. The on-board computer needs various controls on the vehicle. All of this information needs to be transmitted in the body's internal network, and can also be obtained through monitoring. S202. Analyze the data to extract target vehicle data. The format of the target vehicle data may be completely different depending on the specifications of the different models. A large amount of comparative analysis of the data is needed to find out the law between the original data and the real data in order to get the correct target vehicle data. In order to obtain the vehicle data acquisition rules, for each vehicle data of each vehicle type, steps S201-S202 are required, and the acquisition rules of each vehicle data are obtained therefrom, and finally summarized as the vehicle data acquisition rules, and recorded in the data sub-table.

In the process of extracting a specific vehicle profile for each type of vehicle, the vehicle profile is referred to as target vehicle profile.

The extracting the target vehicle data specifically includes, as shown in FIG. 3: S2021. Acquire the first data packet according to the first preset time. The first preset time corresponding to different models may be different. The content format of the package in different models may also be different. S2022. Perform a target operation for generating the target vehicle data, and monitor the data in the second preset time to acquire the second data package. S2023. Horizontal comparison of the first data package and the second data package to obtain the first range. Because the target operation is released, the changed data may be the target vehicle data, and this part of the data constitutes the first range. The S2021-S2023 is repeatedly executed, and the first range is continuously reduced, and finally the target vehicle data is obtained.

Specifically, for a certain target vehicle data of a certain vehicle, under the premise of accurately extracting the target vehicle data, a positioning parameter of the target vehicle data may be recorded, where the positioning parameter is used to extract the monitoring result. A collection of parameters for the target vehicle data. In a feasible implementation manner, the positioning parameters include a communication rate, a monitoring data packet identifier, a valid byte group, a binary conversion identifier, and a data conversion formula.

Take the vehicle speed data as an example: the vehicle data acquisition rules of the three models B and C are recorded in the three data sub-tables labeled 0001, 0002, and 0003, respectively. The positioning parameters in the three sheets are shown in Table 1: Table 1  Data sub-table identification positioning parameter 0001500K00000111 third, fourth byte hexadecimal conversion to decimal 0002250K00000222 first, second byte hexadecimal conversion to decimal *20003125K00000333 seventh, eighth byte The hexadecimal conversion to decimal *3 shows that the speed acquisition rules of the above three models are: the CAN bus communication speed of the A model is 500K, the monitoring data package ID is 00000111, the valid data is the third, the fourth byte The conversion formula is hexadecimal to decimal. The CAN bus speed of the B model is 250K, the vehicle speed ID is 00000222, the valid data is the first, the second byte, and the conversion formula is hexadecimal to 10 The hexadecimal *2; C model CAN bus communication speed is 125K, the vehicle speed ID is 00000333, the valid data is the seventh, the eighth byte, the conversion formula is hexadecimal conversion to decimal *3.  

It should be noted that each data sub-table stores the vehicle data acquisition rules in the form of key-value pairs, and the keys of different data sub-tables may be the same or different. As we all know, the types of vehicle data that can be acquired based on the monitoring mode are very numerous, including but not limited to the speed, speed, water temperature, voltage, door, all lights, fuel quantity, throttle status, brake status, seat belt status, key status, steering wheel. Angle, gear position, total mileage, etc., and the positioning parameters of different vehicle data may also be different.

If the positioning parameters of different vehicle data can be expressed as communication rate, monitoring packet identification, effective byte, binary conversion identifier and data conversion formula, the logical structure of each data sub-table can be designed to include vehicle data. The six fields of type, communication rate, monitoring packet identification, valid byte, binary conversion identifier and data conversion formula are shown in Table 2: Table 2  Vehicle data type communication rate monitoring data packet identification effective bit group hex conversion identification and data conversion formula vehicle speed 250K00000222 first, the second byte hexadecimal conversion to decimal speed 500K00000153 fourth, fifth byte 16 Convert to decimal *3

If the fields of the positioning parameters of different vehicle data are different and there is no way to unify, the logical structure of each data sub-table can be designed to include the vehicle data type and the BLOB two fields, BLOB (binary large object), The binary large object is a container that can store the binary file. For the positioning parameters that cannot be unified, the BLOB is used for storage. In the storage process, the specific positioning parameters are stored in the BLOB, and the positioning parameters in different BLOBs are The fields do not affect each other and can be different. In the process of actual vehicle data acquisition, the content in the BLOB container is parsed to obtain specific positioning parameters.

Specifically, in order to implement the foregoing method embodiment, the new embodiment provides a vehicle data acquisition automatic adaptation device, as shown in FIG. 4, including: a database module 401, configured to establish a vehicle data adaptation database, The database includes an adaptation table and a plurality of data sub-tables for recording the correspondence between the vehicle type and the data sub-table identification, and the data sub-table is for recording the acquisition rules of the vehicle data in a certain vehicle type. The target vehicle type acquisition module 402 is configured to acquire a target vehicle type of the target vehicle. The positioning module 403 is configured to locate a target data sub-table corresponding to the target vehicle type according to the target vehicle type. The monitoring module 404 is configured to monitor data broadcasted by the on-board computer to obtain a data source. The obtaining module 405 is configured to obtain vehicle data in the data source according to the vehicle data acquisition rule recorded in the target data sub-table.

The novel device embodiments and method embodiments are based on the same novel concept.

The above is only the preferred embodiment of the present invention, and the scope of the present invention is not limited thereto, and the equivalent changes made by the novel claims are still within the scope of the present invention.

401‧‧‧Database Module

402‧‧‧Target Vehicle Type Acquisition Module

403‧‧‧ Positioning Module

404‧‧‧Monitor module

405‧‧‧Get the module

1 is a flow chart of a method for automatically acquiring vehicle data acquisition according to an embodiment of the present invention; FIG. 2 is a flowchart of a method for acquiring vehicle data based on a listening mode according to an embodiment of the present invention; FIG. The target vehicle data flow chart is extracted; FIG. 4 is a block diagram of a vehicle data acquisition automatic adaptation device provided by the new embodiment.

Claims (1)

A vehicle data acquisition automatic adaptation device, comprising: a database module, configured to establish a vehicle data adaptation database, the data library comprising an adaptation table and a plurality of data sub-tables, an adaptation table It is used to record the correspondence between the vehicle type and the data sub-table identification, the data sub-table is used to record the acquisition rules of the vehicle data in a certain vehicle type; the target vehicle type acquisition module is used to acquire the target vehicle type of the target vehicle; a group for locating a target data sub-table corresponding to the target vehicle type according to the target vehicle type; a monitoring module for monitoring data obtained by the on-board computer broadcast to obtain a data source; and acquiring a module for using the target The vehicle data acquisition rules recorded in the data sub-list obtain vehicle data in the data source.