An analysis method for large-scale measured configurations

Abstract

The present invention provides an analysis method for a large number of measured configurations, including: step 1, obtaining all configuration information of all rectified vehicle models for the rectification project; step 2, grouping all configuration information according to the declared value of the grouping parameter; step 3, clarifying the deemed coverage of each measured configuration with the configuration group as the unit; step 4, starting from a single configuration, starting to diverge and create a branch chain until the configuration set that can be covered by all nodes on the current branch chain is the whole group of configurations; step 5, performing deduplication processing on feasible solutions to obtain the final feasible solution / set of the rectification plan, and screening the optimal solution / set of the rectification plan; step 6, selecting a solution that can be implemented for detection from the feasible solution set of the rectification plan in combination with the actual production situation of the prototype vehicle. The present invention can quickly find the best measured solution and help enterprises complete the corresponding project rectification with the least number of prototype vehicles, the least prototype vehicle configuration and the least cost.

Description

Technical Field

[0001] The present invention belongs to the technical field of vehicle inspection and certification, and in particular relates to an analysis method for large-scale measured configurations. Background Art

[0002] In the invention patent with publication number CN119250846A, "Method for Generating Optimal and Feasible Solutions of Measured Schemes for Multiple Filing Declaration Values", a method for obtaining the optimal and feasible solutions of measured schemes is introduced. The general principle is as follows: Assume that a certain vehicle model has three configurations for a certain measured item, namely configurations A, B, and C. There is a certain equivalent relationship between these three configurations, such as Figure 1 As shown, when configuration A is measured, configurations A and B can be regarded as configuration A. We call this relationship that when configuration A is measured, it can cover configuration A and configuration B; similarly, when configuration B is measured, it can cover configuration B and configuration C; when configuration C is measured, it can only cover configuration C.

[0003] The current requirement is that for a test project, we hope to use the least configuration to measure and ensure that each configuration can be covered. The original patent provides a method. First, randomly select one configuration from the three configurations and judge whether the result of the selected configuration covers the full set A, B, and C. If so, it means that the measured configuration can meet the requirements. Here, the results of randomly selecting one of the three configurations are Type, that is, select A, B, C separately. Obviously, any one of them will not meet the requirements. At this time, start to select a combination of 2 configurations, that is, At this time, there are also 3 results, namely selecting A and B, A and C, and B and C. The union of the results covered by the combination of A and B is the full set. Obviously, the result covered by the combination of A and C is also the full set, and the result covered by B and C is not the full set. Therefore, when 2 configurations are selected for actual measurement, they are the optimal solutions of the detection plan. At this time, there are 2 optimal solutions.

[0004] If you want to get other feasible solutions, you only need to select The result is ok.

[0005] From the above principle, it can be seen that this method fully considers all combinations, but there are certain problems. Assume that there are n configurations that need to be analyzed. According to the above principle, if the best measured solution requires k configurations to be measured, then the calculation steps to obtain the optimal solution should be:

[0006] (1)

[0007] The computational steps to obtain a feasible solution should be:

[0008] (2)

[0009] Previous patents addressed the problem of how to obtain the best actual measurement plan for a single vehicle model in a certain project. In this type of problem, the magnitude of n is very small, and the original method is sufficient to support it. However, with the update of testing plan standards and requirements, the limitations of the original method will become increasingly apparent.

[0010] For example, in 2024, when the Motor Transport Center of the Ministry of Transport solicited opinions on the revision of the JT / T 1178.1-2018 standard, hereinafter referred to as Amendment No. 1, it proposed to cancel the speed and tonnage restrictions for active safety devices such as ESC and AEBS, hoping to make them standard devices or functions. When the relevant staff of the testing agency evaluated the impact of the revision opinions on actual work, they found that if a company has 500 models, these 500 models originally did not need to install active safety devices, but with the update of the standards, they now need to be installed. Taking the installation of ESC as an example, these 500 models all need to provide reports on the operation 02 inspection project. The reports of these models are either actual measurement reports or deemed reports. The 02 project is not only related to the installed ESC model and manufacturer, but also to tire specifications, curb weight, brake components, etc. If these parameters and components have multiple specifications, different specifications will form different 02 project configurations based on the relationship between permutations and combinations. If a car model has an average of 4 02 project configurations, there are 500*4=2000 configurations that need to be analyzed. If only 50 configurations are actually measured in actual situations, all configurations can be covered. That is, there are 50 configurations for actual measurement, and any one of the remaining 1950 configurations can find one or more configurations in the 50 measured configurations to be considered equivalent. Substituting n=2000 and k=50 into Formula 1, the result can be calculated to be approximately: According to the method of the previous patent, at least this level of calculation is required to obtain the optimal solution. Obviously, the problem cannot be solved satisfactorily. Summary of the Invention

[0011] The present invention discloses an analysis method for a large number of measured configurations, the analysis method for a large number of measured configurations comprising the following steps:

[0012] Step 1: Obtain all configuration information of all modified models for the modification project and integrate this information;

[0013] Step 2: Group the configuration information obtained in step 1 according to the declared values of the grouping parameters. The declared values of the grouping parameters must be completely consistent to be classified into the same configuration group.

[0014] Step 3: Taking the configuration group as a unit, determine the deemed coverage of each configuration in the configuration group according to the deemed coverage criteria during the actual measurement;

[0015] Step 4: In the configuration group, start with a single configuration and create a branch chain until the configuration set that can be covered by all nodes on the current branch chain is the entire configuration group;

[0016] Step 5: De-duplicate the feasible solutions to obtain the final feasible solution / set of the rectification plan, and select the combination with the least number of configurations as the optimal solution / set of the rectification plan;

[0017] Step 6: From the feasible solution set of the rectification plan, based on the actual production situation of the prototype vehicle and in accordance with the principle of minimum configuration quantity, select the plan that can be tested.

[0018] Furthermore, in step 1, the declared values of the parameters that are not applicable to the modified vehicle model are uniformly written as "N / A".

[0019] Furthermore, in step 3, each configuration in the group of configurations is traversed and analyzed in turn. When the configuration is actually measured, it is determined whether the remaining configurations can be regarded as the same as the configuration, until all the configurations in the group are traversed and analyzed, and the result after the configurations in the group are regarded as the same as each other is obtained.

[0020] Furthermore, in step 3, the result is stored in a dictionary data format, where the key of the dictionary is each configuration, and the corresponding value is the deemed configuration that can be covered when the configuration is actually measured. Each value in the dictionary must also include the key corresponding to this value.

[0021] Furthermore, in step 4, the following steps are included:

[0022] In step 4.1, starting from a single configuration, we begin to diverge and create a branch chain, and based on the result of step 3, we obtain the configuration set that the node can cover;

[0023] In step 4.2, determine whether the covering set already contains all configurations of the entire group. If the covering set already contains the entire group of configurations, then the current node configuration is the optimal solution for the rectification plan, and the analysis of the current branch is stopped;

[0024] In step 4.3, if the coverage set does not contain the entire set of configurations, a new configuration needs to be added as the next node, and the corresponding coverage set needs to be updated based on the result of step 3. Then, step 4.2 is repeated until the configuration set that can be covered by all nodes on the current branch chain is the entire set of configurations. The node configuration combination on the chain is the feasible solution to the rectification plan.

[0025] Furthermore, in step 5, each branch chain will obtain a feasible solution for the rectification plan. These feasible solutions may be repeated and need to be deduplicated. The result obtained after deduplication is the final set of feasible solutions. In the final set of feasible solutions, the combinations with the least number of configurations are selected. These combinations are the optimal solutions for the rectification plan.

[0026] Furthermore, in step 6, the determination of whether the test can be carried out is made starting from the scheme with the least measured configuration; each configuration requires the production of a corresponding prototype vehicle. If the prototype vehicle of the corresponding configuration cannot be produced, the determination is made in an increasing manner according to the number of measured configurations until a measured configuration that can be tested is selected.

[0027] The beneficial effects achieved by the present invention are:

[0028] This invention innovatively utilizes grouping parameters, achieving two key breakthroughs. First, it rationally divides a large number of diverse configurations into multiple configuration groups, significantly optimizing the structure and efficiency of configuration management. Second, by requiring only comparisons of non-grouped parameters, this approach significantly reduces the number of parameters required to be determined for each configuration group when analyzing the configuration. Furthermore, each configuration group can perform analysis simultaneously. This parallel processing model significantly shortens overall analysis time and improves efficiency.

[0029] In the process of exploring feasible configuration combinations, this paper uses recursive analysis to systematically try all possible configuration combinations. Each step is based on the current selection and recursively explores further. If the current selection does not lead to a valid solution, it will try higher-dimensional combinations by adding new node configurations until all possible solutions are found.

[0030] Taking a specific example, this solution can accurately find all the measured configuration combinations that can cover all the rectification configurations, and screen out the combination with the least number of configurations, and then determine the corresponding optimal solution and feasible solution. Compared with the original solution, the new solution can effectively control the amount of calculation and avoid unnecessary resource consumption by carefully setting the termination conditions. At the same time, with the help of the backtracking search mechanism, the iteration process is accelerated, helping companies to quickly lock in the best measured solution. It not only significantly reduces the labor cost of corporate certification personnel, but also helps companies to efficiently complete the corresponding project rectification work with the least number of prototypes, the most streamlined prototype configuration and the lowest testing costs while ensuring the accuracy of calculations, bringing significant economic benefits and time cost advantages to the company. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a diagram of the equivalent relationship between the three configurations;

[0032] Figure 2is a flow chart of an analysis method for a large number of measured configurations;

[0033] Figure 3 This is a schematic diagram of the deemed conditions for Project 02;

[0034] Figure 4 This is a schematic diagram of the grouping parameters and group declaration values of the 54 items in the present invention;

[0035] Figure 5 This is a diagram showing the equivalent relationship between the three configurations in the second embodiment of the present invention;

[0036] Figure 6 This is a flowchart of analyzing coverage relationships with configuration 1 as the initial node in embodiment 2 of the present invention;

[0037] Figure 7 This is a flowchart of analyzing coverage relationships with configuration 2 as the initial node in embodiment 2 of the present invention;

[0038] Figure 8 This is a flowchart of analyzing coverage relationships with configuration 3 as the initial node in embodiment 2 of the present invention. DETAILED DESCRIPTION

[0039] The present invention will be further described below with reference to specific embodiments, and the advantages and features of the present invention will become clearer as the description proceeds. However, these embodiments are merely exemplary and do not constitute any limitation to the scope of the present invention. It should be understood by those skilled in the art that the details and forms of the technical solutions of the present invention may be modified or replaced without departing from the spirit and scope of the present invention, and such modifications and replacements fall within the scope of protection of the present invention.

[0040] Example 1

[0041] like Figure 2 As shown, the Automobile Transport Center of the Ministry of Transport intends to propose amendments to the content of the operation declaration. Each automobile company needs to prepare rectifications for the vehicle model declaration based on the content of the amendment order. The corresponding rectification work can adopt an analysis method for large-scale measured configurations proposed in this application. The analysis method for large-scale measured configurations includes the following steps:

[0042] Step 1: Obtain all configuration information and corresponding configurations of all modified vehicle models in a certain modification project, and integrate all vehicle model configuration results together;

[0043] Obtain all configuration information of all rectified vehicle models in a certain rectification project. This information can be manually sorted and provided by enterprise certification personnel, or a single vehicle model can obtain the corresponding configuration according to the method provided in the patent "A method for generating test item configurations for multiple filing declaration values", and then all vehicle model configuration results are integrated together to obtain a total of N configurations.

[0044] In addition, there are some special parameters that require data cleaning. Some parameters are not applicable to the corresponding rectified models. It is stipulated here that for non-applicable models, the declared values of these parameters are uniformly N / A.

[0045] For example, when the rectified vehicle is a trailer, the chassis manufacturer's declared value needs to be corrected to "N / A" because the trailer does not have corresponding chassis components.

[0046] For another example, the wheelbase has three parameters, namely QA1231, the distance from axle I to axle II (mm), QA1232, the distance from axle II to axle III (mm), and QA1233, the distance from axle III to axle IV (mm). If the remediated vehicle model is a two-axle vehicle with only axles I and II, then the vehicle model only needs to register the declared value of QA1231. QA1232 and QA1233 are not applicable to the two-axle vehicle, so the corresponding declared values also need to be corrected to N / A.

[0047] Step 2: Group all configurations in the rectification project according to the grouping parameters. According to the same type judgment conditions issued by the Automobile Transport Center of the Ministry of Transport, extract the parameters whose declared values must be the same to determine that the configurations are deemed to be the same as the grouping parameters; group the N configurations provided in step 1 according to the declared values of the grouping parameters, and divide the configurations with the same declared values of all the grouping parameters into one group.

[0048] In a specific embodiment, Figure 3 As shown, according to the criteria for determining the same type provided by the Ministry of Transport's Automobile Transportation Center, in test item number 54, only when the reported values for parameters such as chassis manufacturer, automatic emergency braking system (AEBS) type, automatic emergency braking system (AEBS) model, automatic emergency braking system (AEBS) manufacturer, anti-lock braking system (ABS) system controller model, and anti-lock braking system (ABS) system controller manufacturer are exactly the same can these parameters be used as a necessary condition for determining whether the relevant vehicle configurations can be considered the same. Based on this, these parameters can be defined as grouping parameters, which play a key role in classification and definition during the grouping process.

[0049] The N configurations are divided into n configuration groups according to the declared values of the grouping parameters. When the declared values of the grouping parameters are completely consistent, the corresponding configurations are divided into the same configuration group.

[0050] In this embodiment, rectification is carried out for 54 operational items, as shown in Table 1, which is the content organized according to the same type determination conditions issued by the Ministry of Transport. It is known that the grouping parameters of the 54 items should be: QB002, QJ001, QJ015, QJ017, QJ019, QJ021, QJ022, QB0815, QB0816, QB0817, QB0818, QB003, QA067, QB0741, QB0171, QB0751, QB0161, QA025, QA024, QA026, QJ029, QJ030, QJ071, QJ072, QJ031, QJ032, QA0481, QA029, QA027, QA028, and QA064.

[0051] In addition, if the declared values corresponding to several parameters in the grouping parameters cannot be determined, for example, 54 items involve rectification, and ABES parts may need to be replaced, but the company has not determined which AEBS supplier to use, then the corresponding AEBS category, model, and manufacturer are unknown. At this time, the corresponding parameters need to be ignored. On the basis of ignoring, continue to process according to the original steps. In the final result, multiplying the number of declared value groups of ignored parameters can also get the final result. For example, if the AEBS category, model, and manufacturer are ignored, and the analysis is continued according to the original steps, it is found that at least 5 configurations need to be measured to complete the rectification, but the subsequent company determines that 3 sets of AEBS parts will be used, then preparations need to be made for actual testing. A configuration test.

[0052] Table 1 54 deemed operating conditions

[0053] Parameter code parameter Deemed requirements QB002 Chassis manufacturers same QA025 Automatic Emergency Braking System (AEBS) Category same QA024 Automatic Emergency Braking System (AEBS) Model same QA026 Automatic Emergency Braking System (AEBS) manufacturers same QJ029 Anti-lock braking system (ABS) system controller model same QJ030 Anti-lock braking system (ABS) system controller manufacturer same QJ071 Electronic Braking System (EBS) Controller Model same Q072 Electronic Braking System (EBS) control manufacturer same QJ031 Electronic Stability Control (ESC) Model same QJ032 Electronic Stability Control (ESC) manufacturers same QA0481 Automatic Emergency Braking System (AEBS) front obstacle detection sensor category same QA029 Number of Automatic Emergency Braking System (AEBS) front obstacle detection sensors same QA027 Automatic Emergency Braking System (AEBS) front obstacle detection sensor model same QA028 Manufacturer of front obstacle detection sensors for automatic emergency braking systems (AEBS) same QA064 Automatic Emergency Braking System (AEBS) front obstacle detection sensor installation location same QA0701 Maximum total mass Same or smaller QA094 Total mass of car train (kg) Same or smaller QJ001 Service brake system type same QB009 Tire specifications Tire section width and static load radius change the same or decrease by 5% QJ015 Brake caliper model same QJ017 Brake disc model same QJ019 Brake drum model same QJ021 Brake shoe model same QJ022 Brake lining specifications and models same QB0815 Number of tires (1st axle) same QB0816 Number of tires (second axle) same QB0817 Number of tires (3rd axle) same QB0818 Number of tires (4th axle) same QB003 Number of axes same QB0461 Axle layout same QA067 Vehicle Classification same

[0054] In addition, when processing Project 54 and other projects, since the declared value of the parameter QB0461 is in non-standard language, different declared values may have different text descriptions, but their Chinese meanings are the same, and they should be regarded as the same. However, in the actual batch processing process, it is difficult to determine whether different Chinese descriptions have the same Chinese meaning. Therefore, it is necessary to convert "determine whether the declared values of QB0461 are the same" into "determine whether the declared values of QB0741, QB0171, QB0751, and QB0161 are the same."

[0055] The principle of grouping is that only when the declared values of all grouping parameters are exactly the same can they be grouped together, such as Figure 4As shown, for example, the declared values of the first group of parameters are: 'N / A', 'Dual-circuit air brake, front and rear disc', '22.5', 'φ430X45', 'N / A', 'N / A', '22.5', '2', '4', '4', 'N / A', '3', 'Towing vehicle', '1', '2', '1st axle', '2nd axle, 3rd axle'. Only when the declared values corresponding to the grouping parameters are these values can the vehicle be classified into the first group.

[0056] Step 3: Taking the configuration group as a unit, determine the equivalent coverage of each configuration in the configuration group according to the equivalent judgment conditions during actual measurement; and use the same solution to obtain the equivalent coverage of the configurations of other configuration groups. Traverse and analyze each configuration in all configuration groups in turn, and according to the judgment logic of the equivalent requirements, analyze: when any configuration is measured, whether the remaining configurations in the configuration group can be regarded as the configuration, until all configurations in the configuration group are traversed and analyzed, and the result of the mutual equivalent judgment of the configurations in the group is obtained, and the result is stored in a special dictionary data format. The key of the dictionary is a single configuration, and the corresponding value is the equivalent configuration that can be covered when the configuration is measured. In each value of the dictionary, the key corresponding to this value must also be included.

[0057] Step 4: Starting from a single configuration, diverge and create a branch chain. Based on the result of step 3, obtain the configuration set that the node can cover. Determine whether the covered set is a complete set of configurations. If so, use the node configuration as the optimal solution for the rectification plan and stop the analysis of the current branch chain. If it is not a complete set of configurations, add a new configuration as the next node and update the corresponding covered set at the same time. This process continues until the configuration set that all nodes on the current branch chain can cover is a complete set of configurations. At this point, the node configuration combination on the chain is a feasible solution for the rectification plan.

[0058] In step 4.1, start creating branch chains by diverging from a single configuration. Based on the result of step 3, obtain the configuration set that the node can cover;

[0059] In step 4.2, determine whether the covering set already contains all configurations of the entire group. If the covering set already contains the entire group of configurations, then the current node configuration is the optimal solution for the rectification plan, and the analysis of the current branch is stopped;

[0060] In step 4.3, if the covered set does not contain the entire set of configurations, a new configuration needs to be added as the next node, and the corresponding covered set needs to be updated based on the result of step 3. Then, step 4.2 is repeated until the set of configurations that can be covered by all nodes on the current branch chain is the entire set of configurations. At this point, the node configuration combination on the chain is the feasible solution for the rectification plan;

[0061] Step 5: De-duplicate the feasible solutions to obtain the final feasible solution set of the rectification plan, and select the combination with the least number of configurations as the optimal solution of the rectification plan;

[0062] Each branch chain will obtain a feasible solution for the rectification plan. These feasible solutions may be repeated and need to be deduplicated. The result obtained after deduplication is the final set of feasible solutions. In the final set of feasible solutions, the combinations with the least number of configurations are selected. These combinations are the optimal solutions for the rectification plan.

[0063] Step 6: Select a measured configuration that can be used for testing from all possible measured configuration combinations.

[0064] Starting from the scheme with the least measured configuration, determine whether the test can be carried out one by one; if the existing sample vehicles are not sufficient to meet the test requirements, make judgments in an increasing manner according to the number of measured configurations until a measured configuration that can be tested is selected.

[0065] In theory, obtaining the optimal solution is the ideal solution to solve operational rectification tasks. This means that the company can complete the rectification task with the least number of prototypes, the least inspection configuration, the least testing costs, and the least corporate costs. However, in actual application, it is often necessary to examine the actual situation. For example, the optimal solution or a configuration in the optimal solution set cannot be produced due to the lack of certain parts. However, due to the timeliness of the rectification, the rectification task must be completed. At this time, it is necessary to find a configuration that can be produced in the feasible solution or feasible solution set of configuration number + 1. If the feasible solution or feasible solution set corresponding to the current configuration number cannot guarantee actual production, continue to configure the number + 1 until a feasible solution that meets the requirements can be found.

[0066] Example 2

[0067] like Figure 5 As shown, under three specific configuration combinations, the analysis method provided by the present invention for a large number of measured configurations is:

[0068] Starting from configuration 1:

[0069] The current combination is [Configuration 1], and the covered set is {Configuration 1, Configuration 2}

[0070] First, try to add configuration 2. The new combination is [configuration 1, configuration 2], and the new covering set is {configuration 1, configuration 2, configuration 3}. The termination condition is met, and [configuration 1, configuration 2] is added to the result.

[0071] Secondly, try to add configuration 3. The new combination is [configuration 1, configuration 3] and the new covering set is {configuration 1, configuration 2, configuration 3}. The termination condition is met and [configuration 1, configuration 3] is added to the result.

[0072] like Figure 6 As shown, the chain branches with configuration 1 as the initial node have been fully analyzed.

[0073] Starting from configuration 2:

[0074] The current combination is [Configuration 2], and the covered set is {Configuration 2, Configuration 3}.

[0075] First, try to add configuration 1. The new combination is [configuration 2, configuration 1], and the new covering set is {configuration 1, configuration 2, configuration 3}. The termination condition is met, and [configuration 1, configuration 2] is added to the result (due to duplication with the previous one after sorting, it will be removed later).

[0076] Secondly, try to add configuration 3. The new combination is [configuration 2, configuration 3] and the new covering set is {configuration 2, configuration 3}. The termination condition is not met, so continue to add nodes.

[0077] At this time, only configuration 1 can be added. The new combination is [configuration 2, configuration 3, configuration 1], and the new coverage set is {configuration 1, configuration 2, configuration 3}. The termination condition is met, and [configuration 2, configuration 3, configuration 1] is added to the result.

[0078] like Figure 7 As shown, the chain branches with configuration 2 as the initial node have been fully analyzed.

[0079] Starting from configuration 3:

[0080] The current combination is [Configuration 3] and the covered set is {Configuration 3}.

[0081] First, try to add configuration 1. The new combination is [configuration 3, configuration 1], and the new covering set is {configuration 1, configuration 2, configuration 3}. The termination condition is met, and [configuration 1, configuration 3] is added to the result (due to duplication with the previous one after sorting, it will be removed later).

[0082] Secondly, try to add configuration 2. The new combination is [configuration 3, configuration 2] and the new covering set is {configuration 2, configuration 3}. The termination condition is not met and a new node needs to be added.

[0083] At this time, only configuration 1 can be added. The new combination is [configuration 3, configuration 2, configuration 1], and the new coverage set is {configuration 1, configuration 2, configuration 3}. The termination condition is met, and [configuration 3, configuration 2, configuration 1] is added to the result (since the sorted result is repeated with the previous one, duplicates will be removed later).

[0084] like Figure 8 As shown, the chain branches with configuration 3 as the initial node have been fully analyzed.

[0085] At this point, all branch combinations have been completed. After deduplication, the following combination results exist in the solution results. These three measured solutions are all feasible solutions for the rectification plan:

[0086] The first measured solution: [Configuration 1, Configuration 2]

[0087] The second measured solution: [Configuration 1, Configuration 3]

[0088] The third measured solution: [Configuration 1, Configuration 2, Configuration 3]

[0089] Among them, the first two require the least number of measured configurations, which is 2, so the first two are the optimal solution sets of the measured solutions.

[0090] The above are only specific steps of the present invention and do not constitute any limitation to the scope of protection of the present invention; any technical solutions formed by equivalent transformation or equivalent replacement fall within the scope of protection of the present invention; the parts not elaborated in detail in the present invention belong to the common knowledge of those skilled in the art.

Claims

1. A method for analyzing large-scale measured configurations, characterized in that: The analysis method for a large number of measured configurations includes the following steps: Step 1: Obtain all configuration information of all modified models for the modification project and integrate this information; Step 2: Group the configuration information obtained in step 1 according to the declared values of the grouping parameters. The declared values of the grouping parameters must be completely consistent to be classified into the same configuration group. Step 3: Taking the configuration group as a unit, determine the deemed coverage of each configuration in the configuration group according to the deemed coverage criteria during the actual measurement; Step 4: In the configuration group, start with a single configuration and create a branch chain until the configuration set that can be covered by all nodes on the current branch chain is the entire configuration group; Step 5: De-duplicate the feasible solutions to obtain the final feasible solution / set of the rectification plan, and select the combination with the least number of configurations as the optimal solution / set of the rectification plan; Step 6: From the feasible solution set of the rectification plan, based on the actual production situation of the prototype vehicle and the principle of minimum configuration quantity, select the solution that can be tested; In step 4, the following steps are included: In step 4.1, starting from a single configuration, we begin to diverge and create a branch chain, and based on the result of step 3, we obtain the configuration set that the node can cover; In step 4.2, determine whether the covering set already contains all configurations of the entire group. If the covering set already contains the entire group of configurations, then the current node configuration is a feasible solution to the rectification plan, and the analysis of the current branch is stopped; In step 4.3, if the coverage set does not contain the entire set of configurations, a new configuration needs to be added as the next node, and the corresponding coverage set needs to be updated based on the result of step 3. Then, step 4.2 is repeated until the configuration set that can be covered by all nodes on the current branch chain is the entire set of configurations. The node configuration combination on the chain is the feasible solution to the rectification plan.

2. The analysis method for a large number of measured configurations according to claim 1, characterized in that: In step 1, write "N / A" for the declared values of parameters that are not applicable to the reworked vehicle model.

3. The analysis method for a large number of measured configurations according to claim 1, characterized in that: In step 3, each configuration in the group of configurations is traversed and analyzed in turn. When the configuration is actually measured, it is determined whether the remaining configurations can be regarded as the same as the configuration, until all the configurations in the group are traversed and analyzed, and the result after the configurations in the group are regarded as the same as each other is obtained.

4. The analysis method for a large number of measured configurations according to claim 3, characterized in that: In step 3, the result is stored in a dictionary data format. The key of the dictionary is each configuration, and the corresponding value is the deemed configuration that can be covered when the configuration is actually measured. Each value in the dictionary must also contain the key corresponding to this value.

5. The analysis method for a large number of measured configurations according to claim 1, characterized in that: In step 5, each branch chain will obtain a feasible solution for the rectification plan. These feasible solutions may be repeated and need to be deduplicated. The result obtained after deduplication is the final set of feasible solutions. In the final set of feasible solutions, the combinations with the least number of configurations are selected. These combinations are the optimal solutions for the rectification plan.

6. The analysis method for a large number of measured configurations according to claim 1, characterized in that: In step 6, the determination of whether the test can be carried out is made starting from the scheme with the least measured configurations. Each configuration requires the production of a corresponding prototype vehicle. If the prototype vehicle of the corresponding configuration cannot be produced, the determination is made in an increasing manner according to the number of measured configurations until a measured configuration that can be tested is selected.

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