Intelligent automobile detection and diagnosis method and system

Abstract

The application is suitable for the technical field of automobile detection and diagnosis, and provides an intelligent automobile detection and diagnosis method and system. The application determines the current detection automobile, matches automobile data in a preset shared driving database, compares data to obtain a data comparison result, constructs a target endurance interval, compares the current endurance data with the target endurance interval to determine whether technical detection and diagnosis is needed. The automobile data matching can be performed, multiple related shared data can be selected, the historical driving data of the current detection automobile is compared, the target endurance interval is constructed, and then the current endurance data of the current detection automobile is compared with the target endurance interval to determine whether technical detection and diagnosis is needed, so that the strictly selected shared driving data is used to provide a simple and fast preliminary comparison and judgment for the current detection automobile, and whether technical detection and diagnosis is needed is provided as a basis through non-technical detection and diagnosis.

Description

Technical Field

[0001] This invention belongs to the field of automotive testing and diagnostic technology, and in particular relates to an intelligent automotive testing and diagnostic method and system. Background Technology

[0002] Automotive inspection and diagnostics is a technical process that involves inspecting and analyzing the operating status of a vehicle without disassembling it or with minimal disassembly. It aims to identify potential faults and assess vehicle performance by acquiring and processing real-time or historical data of vehicle operating parameters, thereby improving vehicle operating safety and reliability. It is an important foundational technology in modern intelligent connected vehicles and intelligent operation and maintenance systems.

[0003] Existing automotive testing and diagnosis technologies are typically specialized and systematic technical tests and diagnoses, which are highly complex and require specialized expertise. They often require qualified technicians to use specialized testing equipment in standardized testing facilities. While they can provide accurate analysis of vehicle performance and fault conditions, the process is relatively cumbersome and the testing cycle is long. In practical applications, there is a lack of simple and quick preliminary assessment methods that can provide a basis for determining whether technical testing and diagnosis are necessary through non-technical testing and diagnosis. Summary of the Invention

[0004] The purpose of this invention is to provide an intelligent vehicle testing and diagnostic method and system, which aims to solve the technical problems existing in the prior art mentioned in the background.

[0005] The embodiments of the present invention are implemented as follows: An intelligent vehicle inspection and diagnostic method, the method specifically includes the following steps: Identify the vehicle currently being inspected and obtain its basic vehicle information. Based on the basic vehicle information, vehicle data is matched in a preset shared driving database to select multiple relevant shared vehicles and corresponding shared data; The historical driving data of the currently detected vehicle is obtained, and the historical driving data is compared with multiple related shared data according to multiple preset driving factors to obtain the data comparison results; Based on the data comparison results, construct the target range. Obtain the current range data of the vehicle being tested, compare the current range data with the target range range, and determine whether technical testing and diagnosis are required.

[0006] As a further limitation of the technical solution of this embodiment of the invention, the step of determining the currently detected vehicle and obtaining the basic vehicle information of the currently detected vehicle specifically includes the following steps: Receive non-technical testing and diagnostic requests; Based on the aforementioned non-technical inspection and diagnostic request, determine the vehicle currently requiring inspection; Obtain the basic vehicle information of the currently detected vehicle, which includes user information, vehicle brand, model, production date, and registration date.

[0007] As a further limitation of the technical solution of this embodiment of the invention, the step of matching vehicle data in a preset shared driving database according to the basic vehicle information and selecting multiple relevant shared vehicles and corresponding relevant shared data specifically includes the following steps: Based on the aforementioned basic vehicle information, several key pieces of information are generated; Based on the aforementioned key information, relevant cars are matched in a preset shared driving database, and multiple relevant shared cars are selected; Extract relevant sharing data corresponding to multiple shared cars from the shared driving database.

[0008] As a further limitation of the technical solution of this embodiment of the invention, the step of obtaining the historical driving data of the currently detected vehicle, comparing the historical driving data with multiple related shared data according to multiple preset driving factors, and obtaining the data comparison results specifically includes the following steps: Obtain the historical driving data of the currently detected vehicle; Extract multiple relevant driving data and multiple relevant range data from multiple related shared data sources; Based on multiple preset driving factors, the historical driving data is compared with multiple related driving data, and multiple comparison values ​​are calculated. The comparison values ​​are compared with preset standard values, and multiple qualified values ​​are selected. Based on multiple target values, select multiple valid battery range data from multiple relevant battery range data; The multiple valid battery life data are arranged and compared to obtain the data comparison results.

[0009] As a further limitation of the technical solution of this embodiment of the invention, the calculation formula for the plurality of comparison values ​​is as follows: ; in, For historical driving data and the first Comparison values ​​between relevant driving data; The first in historical driving data The factor values ​​for each driving factor are: One driving factor; For the first The first of the relevant driving data The factor values ​​for each driving factor; For the preset first Factor weights for each driving factor.

[0010] As a further limitation of the technical solution of this embodiment of the invention, the step of constructing the target range according to the data comparison results specifically includes the following steps: Based on the data comparison results, select multiple target battery life data from the multiple valid battery life data. Based on multiple target range data, a target range is constructed.

[0011] As a further limitation of the technical solution of this embodiment of the invention, the step of obtaining the current range data of the currently detected vehicle, comparing the current range data with the target range range, and determining whether technical testing and diagnosis are required specifically includes the following steps: Obtain the current range data of the currently detected vehicle; Compare the current battery range with the target battery range; When the current battery life is lower than the target battery life range, it is determined that technical testing and diagnosis are required. When the current range data is within or above the target range, it is determined that no technical detection or diagnosis is required.

[0012] An intelligent vehicle detection and diagnostic system includes a vehicle information acquisition module, a vehicle data matching module, a data comparison and processing module, a target range construction module, and a range comparison and judgment module, wherein: The vehicle information acquisition module is used to determine the currently detected vehicle and acquire the basic vehicle information of the currently detected vehicle; The vehicle data matching module is used to match vehicle data in a preset shared driving database according to the basic vehicle information, and select multiple relevant shared vehicles and corresponding relevant shared data. The data comparison and processing module is used to acquire the historical driving data of the currently detected vehicle, compare the historical driving data with multiple related shared data according to multiple preset driving factors, and obtain the data comparison results; The target range construction module is used to construct a target range based on the data comparison results. The range comparison and judgment module is used to obtain the current range data of the currently detected vehicle, compare the current range data with the target range range, and determine whether technical testing and diagnosis are required.

[0013] As a further limitation of the technical solution of this embodiment of the invention, the data comparison processing module specifically includes: A historical data acquisition unit is used to acquire the historical driving data of the currently detected vehicle. The relevant data extraction unit is used to extract multiple relevant driving data and multiple relevant range data from multiple relevant shared data. The comparison value calculation unit is used to compare the historical driving data with multiple related driving data according to multiple preset driving factors, and calculate multiple comparison values; A numerical comparison unit is used to compare multiple comparison values ​​with preset standard values ​​and select multiple qualified values; The battery life data selection unit is used to select multiple valid battery life data from multiple relevant battery life data according to multiple target values; The sorting and comparison unit is used to sort and compare multiple valid battery life data to obtain data comparison results.

[0014] As a further limitation of the technical solution of this embodiment of the invention, the battery life comparison and judgment module specifically includes: The current range acquisition unit is used to acquire the current range data of the currently detected vehicle; A range comparison unit is used to compare the current range data with the target range range. The technical detection and diagnosis judgment unit is used to determine that technical detection and diagnosis is required when the current range data is lower than the target range range; and to determine that technical detection and diagnosis is not required when the current range data is within or higher than the target range range.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This invention provides a simple and quick preliminary comparison assessment of the vehicle under test by: identifying the vehicle currently being tested; matching vehicle data in a preset shared driving database; comparing data and obtaining comparison results; constructing a target driving range; and comparing the current driving range data with the target driving range to determine whether technical testing and diagnosis are required. The invention enables vehicle data matching, selecting multiple relevant shared data sets, comparing them with the historical driving data of the currently tested vehicle to construct a target driving range, and then comparing the current driving range data of the currently tested vehicle with the target driving range to determine whether technical testing and diagnosis are required. This provides a basis for non-technical testing and diagnosis by leveraging carefully selected shared driving data to determine whether technical testing and diagnosis are necessary. Attached Figure Description

[0016] Figure 1 A flowchart of the intelligent vehicle detection and diagnosis method provided in an embodiment of the present invention is shown; Figure 2The following diagram illustrates the application architecture of the intelligent vehicle testing and diagnostic system provided in an embodiment of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0018] Understandably, current automotive testing and diagnosis is typically a specialized and systematic technical process, characterized by its complexity and high professional threshold. It often requires qualified technicians to use specialized testing equipment in standardized testing facilities. While this approach enables accurate analysis of vehicle performance and fault conditions, the process is relatively cumbersome and time-consuming. In practical applications, there is a lack of simple and quick preliminary assessment methods that can provide a basis for determining whether technical testing and diagnosis are necessary through non-technical methods.

[0019] To address the aforementioned problems, this invention discloses an intelligent vehicle detection and diagnosis method and system. The method involves: identifying the vehicle currently being tested and obtaining its basic vehicle information; matching vehicle data in a pre-defined shared driving database based on this information, selecting multiple relevant shared vehicles and corresponding shared data; acquiring the vehicle's historical driving data, comparing it with the pre-defined shared data based on multiple driving factors, and obtaining the comparison results; constructing a target driving range based on the comparison results; acquiring the vehicle's current driving range data, comparing it with the target driving range, and determining whether technical detection and diagnosis are required. This method enables vehicle data matching, selecting multiple relevant shared data, comparing them with the vehicle's historical driving data to construct a target driving range, and then comparing the vehicle's current driving range data with the target driving range to determine whether technical detection and diagnosis are needed. By leveraging carefully selected shared driving data, it provides a simple and rapid preliminary comparison and judgment for the vehicle under test, offering a basis for determining whether technical detection and diagnosis are required through non-technical methods.

[0020] Specifically, Figure 1 A flowchart of the intelligent vehicle detection and diagnosis method provided in an embodiment of the present invention is shown.

[0021] In a preferred embodiment of the present invention, an intelligent vehicle detection and diagnosis method specifically includes the following steps: Step S101: Determine the currently detected vehicle and obtain the basic vehicle information of the currently detected vehicle.

[0022] In this embodiment of the invention, a car driver can submit a non-technical inspection and diagnosis request through the vehicle's infotainment system or a mobile smart device. By receiving the non-technical inspection and diagnosis request from the car driver, and based on the non-technical inspection and diagnosis request, the system determines the car currently being inspected, and then obtains basic car information such as the user information, car brand, model, production date, and registration date of the car currently being inspected, providing an information basis for subsequent matching and analysis.

[0023] It is understood that, in the embodiments of the present invention, non-technical testing and diagnosis refers to vehicle testing and diagnosis that does not require professionally qualified technicians, does not require the use of specialized testing equipment, and does not require a testing site with standardized conditions.

[0024] Specifically, in another preferred embodiment provided by the present invention, determining the currently detected vehicle and obtaining the basic vehicle information of the currently detected vehicle specifically includes the following steps: Receive non-technical testing and diagnostic requests; Based on the aforementioned non-technical inspection and diagnostic request, determine the vehicle currently requiring inspection; Obtain the basic vehicle information of the currently detected vehicle, which includes user information, vehicle brand, model, production date, and registration date.

[0025] Furthermore, the intelligent vehicle detection and diagnosis method also includes the following steps: Step S102: Based on the basic vehicle information, perform vehicle data matching in the preset shared driving database, and select multiple relevant shared vehicles and corresponding relevant shared data.

[0026] In this embodiment of the invention, by identifying basic vehicle information, extracting multiple key pieces of information from the basic vehicle information, and then matching related vehicles in a preset shared driving database according to the multiple key pieces of information, selecting multiple related shared vehicles, and then extracting the relevant shared data corresponding to the multiple related shared vehicles from the shared driving database.

[0027] It is understood that in the embodiments of the present invention, several key pieces of information, including the car brand, model, production date, and registration date, are included.

[0028] It is understandable that multiple related shared cars are all the same brand and model as the car currently being inspected, and all are close to the production date and registration date of the car currently being inspected. In this embodiment of the invention, "close to" means that the dates are within 30 days of each other.

[0029] It is understood that, in the embodiments of the present invention, the relevant shared data consists of relevant driving data, relevant range data and other data, wherein the relevant range data is the average full-charge range of the corresponding relevant shared car.

[0030] It is understandable that the cars in question are not actually shared cars, but rather cars whose drivers share driving data, range data, and other data with a shared driving database, and are thus given a name.

[0031] Specifically, in another preferred embodiment provided by the present invention, the step of matching vehicle data in a preset shared driving database according to the basic vehicle information and selecting multiple relevant shared vehicles and corresponding relevant shared data specifically includes the following steps: Based on the aforementioned basic vehicle information, several key pieces of information are generated; Based on the aforementioned key information, relevant cars are matched in a preset shared driving database, and multiple relevant shared cars are selected; Extract relevant sharing data corresponding to multiple shared cars from the shared driving database.

[0032] Furthermore, the intelligent vehicle detection and diagnosis method also includes the following steps: Step S103: Obtain the historical driving data of the currently detected vehicle, and compare the historical driving data with multiple related shared data according to multiple preset driving factors to obtain the data comparison results.

[0033] In this embodiment of the invention, historical driving data of the currently detected vehicle is acquired, and multiple related driving data and multiple related range data are extracted from multiple related shared data. Then, according to multiple driving factors such as driving scenario, driving mileage, driving habits, and charging scenario, the historical driving data is compared with the multiple related driving data to calculate multiple comparison values. These comparison values ​​are then compared with preset standard values, and multiple acceptable values ​​lower than the standard values ​​are selected from the multiple comparison values. Furthermore, from the multiple related range data, multiple corresponding effective range data are selected according to the multiple acceptable values, and the multiple effective range data are arranged and compared in descending order of range value. The data comparison results are recorded. Specifically, the calculation formula for the multiple comparison values ​​is as follows: ; in, For historical driving data and the first Comparison values ​​between relevant driving data; The first in historical driving data The factor values ​​for each driving factor are: One driving factor; For the first The first of the relevant driving data The factor values ​​for each driving factor; For the preset first Factor weights for each driving factor.

[0034] Understandably, when comparing historical driving data with multiple related driving data, it is necessary to quantify driving factors such as driving scenarios, mileage, driving habits, and charging scenarios in each data set. Specifically, driving scenarios include urban, rural, and highway driving, with different values ​​representing different scenarios; mileage is directly expressed in kilometers; driving habits are represented by different values ​​based on different levels of driving intensity (reflected in rapid acceleration, sudden braking, etc.); and charging scenarios include home charging, commercial charging, battery swapping, and combined charging, with different values ​​representing different charging scenarios. Among these, combined charging refers to a charging scenario that combines home and commercial charging.

[0035] Specifically, in another preferred embodiment provided by the present invention, the step of obtaining the historical driving data of the currently detected vehicle, comparing the historical driving data with multiple related shared data according to multiple preset driving factors, and obtaining the data comparison results specifically includes the following steps: Obtain the historical driving data of the currently detected vehicle; Extract multiple relevant driving data and multiple relevant range data from multiple related shared data sources; Based on multiple preset driving factors, the historical driving data is compared with multiple related driving data, and multiple comparison values ​​are calculated. The comparison values ​​are compared with preset standard values, and multiple qualified values ​​are selected. Based on multiple target values, select multiple valid battery range data from multiple relevant battery range data; The multiple valid battery life data are arranged and compared to obtain the data comparison results.

[0036] Furthermore, the intelligent vehicle detection and diagnosis method also includes the following steps: Step S104: Construct the target range based on the data comparison results.

[0037] In this embodiment of the invention, according to the data comparison results and the preset effective quantity, the target range data with the first effective quantity is selected from multiple effective range data, and the shortest target range data is taken as the minimum end of the interval, and the longest target range data is taken as the maximum end of the interval to construct the target range interval.

[0038] Specifically, in another preferred embodiment provided by the present invention, constructing the target range based on the data comparison results specifically includes the following steps: Based on the data comparison results, select multiple target battery life data from the multiple valid battery life data. Based on multiple target range data, a target range is constructed.

[0039] Furthermore, the intelligent vehicle detection and diagnosis method also includes the following steps: Step S105: Obtain the current range data of the vehicle being tested, compare the current range data with the target range range, and determine whether technical testing and diagnosis are required.

[0040] In this embodiment of the invention, the current range data of the vehicle being tested is obtained, and then the current range data is compared with the target range range to determine whether technical testing and diagnosis are required. Specifically, if the current range data is lower than the target range range, it is determined that technical testing and diagnosis are required, and at this time, an abnormal detection warning signal is generated and displayed; if the current range data is within the target range range or higher than the target range range, it is determined that technical testing and diagnosis are not required.

[0041] It is understandable that the current range data represents the average range of the tested vehicle on a full charge.

[0042] Specifically, in another preferred embodiment provided by the present invention, the step of obtaining the current range data of the currently detected vehicle, comparing the current range data with the target range range, and determining whether technical testing and diagnosis are required specifically includes the following steps: Obtain the current range data of the currently detected vehicle; Compare the current battery range with the target battery range; When the current battery life is lower than the target battery life range, it is determined that technical testing and diagnosis are required. When the current range data is within or above the target range, it is determined that no technical detection or diagnosis is required.

[0043] Furthermore, Figure 2 The following diagram illustrates the application architecture of the intelligent vehicle testing and diagnostic system provided in an embodiment of the present invention.

[0044] Specifically, in another preferred embodiment of the present invention, an intelligent vehicle testing and diagnostic system includes: The vehicle information acquisition module 101 is used to determine the currently detected vehicle and acquire the basic vehicle information of the currently detected vehicle.

[0045] In this embodiment of the invention, a car driver can submit a non-technical inspection and diagnosis request through the vehicle's infotainment system or a mobile smart terminal. The vehicle information acquisition module 101 receives the non-technical inspection and diagnosis request submitted by the car driver, determines the vehicle to be inspected based on the non-technical inspection and diagnosis request, and then acquires basic vehicle information such as user information, vehicle brand, model, production date, and registration date of the vehicle to be inspected, providing an information basis for subsequent matching and analysis.

[0046] The vehicle data matching module 102 is used to perform vehicle data matching in a preset shared driving database according to the basic vehicle information, and select multiple relevant shared vehicles and corresponding relevant shared data.

[0047] In this embodiment of the invention, the vehicle data matching module 102 identifies basic vehicle information, extracts multiple key information from the basic vehicle information, and then performs relevant vehicle matching in a preset shared driving database according to the multiple key information, selects multiple relevant shared vehicles, and then extracts the relevant shared data corresponding to the multiple relevant shared vehicles from the shared driving database.

[0048] The data comparison and processing module 103 is used to acquire the historical driving data of the currently detected vehicle, compare the historical driving data with multiple related shared data according to multiple preset driving factors, and obtain the data comparison result.

[0049] In this embodiment of the invention, the data comparison processing module 103 acquires the historical driving data of the currently detected vehicle, and extracts multiple related driving data and multiple related range data from multiple related shared data. Then, according to multiple driving factors such as driving scenario, driving mileage, driving habits, and charging scenario, the historical driving data is compared with the multiple related driving data to calculate multiple comparison values. These comparison values ​​are then compared with preset standard values. From the multiple comparison values, multiple acceptable values ​​lower than the standard values ​​are selected. Furthermore, from the multiple related range data, multiple corresponding effective range data are selected according to the multiple acceptable values. The multiple effective range data are then arranged and compared in descending order of range value, and the data comparison results are recorded. Specifically, the calculation formula for the multiple comparison values ​​is as follows: ; in, For historical driving data and the first Comparison values ​​between relevant driving data; The first in historical driving data The factor values ​​for each driving factor are: One driving factor; For the first The first of the relevant driving data The factor values ​​for each driving factor; For the preset first Factor weights for each driving factor.

[0050] Specifically, in another preferred embodiment provided by the present invention, the data comparison processing module 103 specifically includes: A historical data acquisition unit is used to acquire the historical driving data of the currently detected vehicle. The relevant data extraction unit is used to extract multiple relevant driving data and multiple relevant range data from multiple relevant shared data. The comparison value calculation unit is used to compare the historical driving data with multiple related driving data according to multiple preset driving factors, and calculate multiple comparison values; A numerical comparison unit is used to compare multiple comparison values ​​with preset standard values ​​and select multiple qualified values; The battery life data selection unit is used to select multiple valid battery life data from multiple relevant battery life data according to multiple target values; The sorting and comparison unit is used to sort and compare multiple valid battery life data to obtain data comparison results.

[0051] Furthermore, the intelligent vehicle testing and diagnostic system also includes: The target range construction module 104 is used to construct a target range based on the data comparison results.

[0052] In this embodiment of the invention, the target range construction module 104 selects the first number of target range data from multiple valid range data according to the data comparison results and the preset valid number, and constructs the target range range by taking the shortest target range data as the minimum end of the range and the longest target range data as the maximum end of the range.

[0053] The range comparison and judgment module 105 is used to obtain the current range data of the currently detected vehicle, compare the current range data with the target range range, and determine whether technical testing and diagnosis are required.

[0054] In this embodiment of the invention, the range comparison and judgment module 105 acquires the current range data of the vehicle being tested, and then compares the current range data with the target range range to determine whether technical testing and diagnosis are required. Specifically, if the current range data is lower than the target range range, it is determined that technical testing and diagnosis are required, and an abnormal detection warning signal is displayed. If the current range data is within the target range range or higher than the target range range, it is determined that technical testing and diagnosis are not required.

[0055] Specifically, in another preferred embodiment provided by the present invention, the battery life comparison and judgment module 105 specifically includes: The current range acquisition unit is used to acquire the current range data of the currently detected vehicle; A range comparison unit is used to compare the current range data with the target range range. The technical detection and diagnosis judgment unit is used to determine that technical detection and diagnosis is required when the current range data is lower than the target range range; and to determine that technical detection and diagnosis is not required when the current range data is within or higher than the target range range.

[0056] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

Claims

1. An intelligent vehicle inspection and diagnostic method, characterized in that, The method specifically includes the following steps: Identify the vehicle currently being inspected and obtain its basic vehicle information. Based on the basic vehicle information, vehicle data is matched in a preset shared driving database to select multiple relevant shared vehicles and corresponding shared data; The historical driving data of the currently detected vehicle is obtained, and the historical driving data is compared with multiple related shared data according to multiple preset driving factors to obtain the data comparison results; Based on the data comparison results, construct the target range. Obtain the current range data of the vehicle being tested, compare the current range data with the target range range, and determine whether technical testing and diagnosis are required.

2. The intelligent vehicle detection and diagnosis method according to claim 1, characterized in that, The process of determining the currently inspected vehicle and obtaining its basic vehicle information specifically includes the following steps: Receive non-technical testing and diagnostic requests; Based on the aforementioned non-technical inspection and diagnostic request, determine the vehicle currently requiring inspection; Obtain the basic vehicle information of the currently detected vehicle, which includes user information, vehicle brand, model, production date, and registration date.

3. The intelligent vehicle detection and diagnosis method according to claim 1, characterized in that, The step of matching vehicle data in a preset shared driving database based on the basic vehicle information and selecting multiple relevant shared vehicles and corresponding relevant shared data specifically includes the following steps: Based on the aforementioned basic vehicle information, several key pieces of information are generated; Based on the aforementioned key information, relevant cars are matched in a preset shared driving database, and multiple relevant shared cars are selected; Extract relevant sharing data corresponding to multiple shared cars from the shared driving database.

4. The intelligent vehicle detection and diagnosis method according to claim 1, characterized in that, The process of acquiring the historical driving data of the currently detected vehicle, comparing the historical driving data with multiple related shared data according to multiple preset driving factors, and obtaining the data comparison results specifically includes the following steps: Obtain the historical driving data of the currently detected vehicle; Extract multiple relevant driving data and multiple relevant range data from multiple related shared data sources; Based on multiple preset driving factors, the historical driving data is compared with multiple related driving data, and multiple comparison values ​​are calculated. The comparison values ​​are compared with preset standard values, and multiple qualified values ​​are selected. Based on multiple target values, select multiple valid battery range data from multiple relevant battery range data; The multiple valid battery life data are arranged and compared to obtain the data comparison results.

5. The intelligent vehicle detection and diagnosis method according to claim 4, characterized in that, The formulas for calculating the multiple comparison values ​​are as follows: ； in, For historical driving data and the first Comparison values ​​between relevant driving data; The first in historical driving data The factor values ​​for each driving factor are: One driving factor; For the first The first of the relevant driving data The factor values ​​for each driving factor; For the preset first Factor weights for each driving factor.

6. The intelligent vehicle detection and diagnosis method according to claim 1, characterized in that, The process of constructing the target driving range based on the data comparison results includes the following steps: Based on the data comparison results, select multiple target battery life data from the multiple valid battery life data. Based on multiple target range data, a target range is constructed.

7. The intelligent vehicle detection and diagnosis method according to claim 1, characterized in that, The process of obtaining the current range data of the vehicle under test, comparing the current range data with the target range range, and determining whether technical testing and diagnosis are required specifically includes the following steps: Obtain the current range data of the currently detected vehicle; Compare the current battery range with the target battery range; When the current battery life is lower than the target battery life range, it is determined that technical testing and diagnosis are required. When the current range data is within or above the target range, it is determined that no technical detection or diagnosis is required.

8. An intelligent vehicle testing and diagnostic system, characterized in that, The system includes a vehicle information acquisition module, a vehicle data matching module, a data comparison and processing module, a target range construction module, and a range comparison and judgment module, wherein: The vehicle information acquisition module is used to determine the currently detected vehicle and acquire the basic vehicle information of the currently detected vehicle; The vehicle data matching module is used to match vehicle data in a preset shared driving database according to the basic vehicle information, and select multiple relevant shared vehicles and corresponding relevant shared data. The data comparison and processing module is used to acquire the historical driving data of the currently detected vehicle, compare the historical driving data with multiple related shared data according to multiple preset driving factors, and obtain the data comparison results; The target range construction module is used to construct a target range based on the data comparison results. The range comparison and judgment module is used to obtain the current range data of the currently detected vehicle, compare the current range data with the target range range, and determine whether technical testing and diagnosis are required.

9. The intelligent vehicle testing and diagnostic system according to claim 8, characterized in that, The data comparison and processing module specifically includes: A historical data acquisition unit is used to acquire the historical driving data of the currently detected vehicle. The relevant data extraction unit is used to extract multiple relevant driving data and multiple relevant range data from multiple relevant shared data. The comparison value calculation unit is used to compare the historical driving data with multiple related driving data according to multiple preset driving factors, and calculate multiple comparison values; A numerical comparison unit is used to compare multiple comparison values ​​with preset standard values ​​and select multiple qualified values; The battery life data selection unit is used to select multiple valid battery life data from multiple relevant battery life data according to multiple target values; The sorting and comparison unit is used to sort and compare multiple valid battery life data to obtain data comparison results.

10. The intelligent vehicle testing and diagnostic system according to claim 8, characterized in that, The battery life comparison and judgment module specifically includes: The current range acquisition unit is used to acquire the current range data of the currently detected vehicle; A range comparison unit is used to compare the current range data with the target range range. The technical detection and diagnosis judgment unit is used to determine that technical detection and diagnosis is required when the current range data is lower than the target range range; and to determine that technical detection and diagnosis is not required when the current range data is within or higher than the target range range.

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