Vehicle door load information determination method, device, and electronic device

Abstract

This application discloses a method, apparatus, and electronic device for determining load information of a vehicle door. The method includes: acquiring initial user profile information of the vehicle, initial attribute information of the vehicle, and initial environmental information of the environment in which the vehicle is located; generating original load information of the vehicle door based on the initial user profile information, initial attribute information, and initial environmental information, wherein the original load information is used to represent the initial distribution state of the load borne by the vehicle door under different environments; converting the original load information to obtain target load information of the vehicle door; and determining the test information of the vehicle door based on the target load information and the number of times the vehicle door has been used. This application solves the technical problem that test information is difficult to reflect the correlation between load exposure intensity and failure under different types of conditions.

Description

Technical Field

[0001] This application relates to the field of vehicles, and more specifically, to a method, apparatus, and electronic device for determining load information of a vehicle door. Background Technology

[0002] Currently, the durability design and verification of car doors are generally based on the "average service life of typical users". Test information for car doors is generated by applying a uniform tightening factor to several operating conditions. For example, test information for car doors is generated by applying tightening factors to normal opening and closing conditions and light impact conditions respectively.

[0003] However, the methods for obtaining test information mentioned above are overly stringent and make it difficult to make phased corrections to the test information based on actual door conditions and fault data. This results in the test information failing to reflect the technical problem of load exposure intensity and fault correlation under different types of conditions.

[0004] There is currently no effective solution to the aforementioned technical problems. Summary of the Invention

[0005] This application provides a method, apparatus, and electronic device for determining load information of a vehicle door, in order to at least solve the technical problem that test information is difficult to reflect the correlation between load exposure intensity and fault under different types of conditions.

[0006] According to one aspect of the embodiments of this application, a method for determining load information of a vehicle door is provided. The method includes: acquiring initial user profile information of the vehicle, initial attribute information of the vehicle, and initial environmental information of the environment in which the vehicle is located, wherein the initial user profile information is used to represent the usage state of the vehicle when the account corresponding to the vehicle logs into the vehicle, the initial attribute information is used to represent at least the attributes of the vehicle door, and the initial environmental information is used to represent the characteristics of the environment; generating original load information of the vehicle door based on the initial user profile information, initial attribute information, and initial environmental information, wherein the original load information is used to represent the initial distribution state of the load borne by the vehicle door under different environments; converting the original load information to obtain target load information of the vehicle door, wherein the target load information is used to represent the target distribution state of the load borne by the vehicle door under different environments; and determining test information of the vehicle door based on the target load information and the number of times the vehicle door has been used, wherein the test information is used to represent the number of tests conducted on the vehicle door under load.

[0007] Based on the initial user profile information, initial attribute information, and initial environmental information, this application can generate the original load information of the car door, that is, it can obtain the initial distribution state of the load borne by the car door under different environments. Then, by transforming the above-mentioned original load information, the target load information can be obtained, that is, the target distribution state of the load borne by the car door under different environments can be obtained. Then, according to the transformed target load information, the number of times the car door is used is allocated, and test information representing the number of tests of the car door under load can be obtained. This achieves the purpose of improving the accuracy of test information, thereby solving the technical problem that test information is difficult to reflect the load exposure intensity and fault correlation under different types of conditions, and thus realizing the technical effect that test information can reflect the load exposure intensity and fault correlation under different types of conditions.

[0008] Optionally, based on the initial user profile information, initial attribute information, and initial environment information, the original load information of the vehicle door is generated, including: preprocessing the initial user profile information to obtain the target user profile information of the vehicle; preprocessing the initial attribute information to obtain the target attribute information of the vehicle; and preprocessing the initial environment information to obtain the target environment information of the vehicle; performing type recognition on the target user profile information to obtain the type recognition result, wherein the type recognition result is used to represent the relationship between the vehicle's usage type and its operational or residential type; and generating the original load information based on the type recognition result and the target attribute information and target environment information.

[0009] After obtaining the initial user profile information, initial attribute information, and initial environment information, preprocessing these information yields the target user profile information, target attribute information, and target environment information. Based on the type identification results obtained from the target user profile information, the target attribute information and target environment information are then used to generate the original payload information. This achieves the goal of generating original payload information based on the initial user profile information, initial attribute information, and initial environment information, thereby improving the accuracy of the original payload information.

[0010] Optionally, based on the type recognition result, the target attribute information and target environment information are used to generate original load information, including: in response to the type recognition result being a first type recognition result, the target attribute information and target environment information are combined into first load structure information, wherein the first type recognition result is used to indicate that the usage type is operation type, the first load structure information is used to indicate the structure of the load unit for the operation type vehicle, and the load unit is the feature type to which the load belongs; under the first load structure information, the first occurrence frequency of different loads corresponding to the load unit is recorded; according to the different door positions of the vehicle door, the recorded first occurrence frequency is normalized to obtain the first original load information, wherein the original load information includes: the first original load information.

[0011] Based on different type recognition results, target attribute information and target environment information can be combined into corresponding load structure information. Under the corresponding load structure information, the occurrence frequency of different loads corresponding to the load unit is recorded, and the recorded occurrence frequency is normalized according to different door positions of the vehicle door to obtain the corresponding original load information. This achieves the goal of generating original load information based on type recognition results from target attribute information and target environment information, thereby improving the accuracy of the original load information.

[0012] Optionally, based on the type recognition result, the target attribute information and target environment information are used to generate original load information, including: in response to the type recognition result being a second type recognition result, the target attribute information and target environment information are combined into second load structure information, wherein the second type recognition result is used to indicate that the usage type is household type, and the second load structure information is used to indicate the structure of the load unit for a household type vehicle, and the load unit is the feature type to which the load belongs; under the second load structure information, the second occurrence frequency of different loads corresponding to the load unit is recorded; according to the different door positions of the vehicle door, the recorded second occurrence frequency is normalized to obtain the second original load information, wherein the original load information includes: the second original load information.

[0013] Based on different type recognition results, target attribute information and target environment information can be combined into corresponding load structure information. Under the corresponding load structure information, the occurrence frequency of different loads corresponding to the load unit is recorded, and the recorded occurrence frequency is normalized according to different door positions of the vehicle door to obtain the corresponding original load information. This achieves the goal of generating original load information based on type recognition results from target attribute information and target environment information, thereby improving the accuracy of the original load information.

[0014] Optionally, the original load information is transformed to obtain the target load information of the door, including: weighting the original load information using the weights of the original load information; and normalizing the weighted original load information to obtain the target load information.

[0015] By weighting and normalizing the generated raw load information, the target load information can be obtained, thereby achieving the goal of obtaining the target load distribution state of the door under different environments, and thus realizing the technical effect of improving the accuracy of the target load information.

[0016] Optionally, the method further includes: determining the relative risk ratios between multiple fault sample data and multiple normal sample data of the car door to obtain multiple relative risk ratios; averaging the multiple relative risk ratios to obtain an average risk ratio; and determining the average risk ratio as a weight.

[0017] Since the weights of the original load information are obtained by averaging the relative risk ratios between multiple fault sample data and multiple normal sample data, the availability of the weights can be guaranteed, thereby achieving the technical effect of improving the effectiveness of weighted processing.

[0018] Optionally, based on the target load information and the number of times the door is used, the test information of the door is determined, including: determining the door opening frequency information, wherein the door opening frequency information is used to represent the door opening frequency per unit mileage; determining the first product between the door opening frequency represented by the door opening frequency information and the target number of times the door is used, and determining the first product as the number of times of use; and allocating the number of times of use to the load units of the vehicle under different loads according to the target load information to obtain the test information.

[0019] Since the number of times a door is used is determined by the first product between the door opening frequency and the target number of uses, the number of uses is then allocated to the load units of vehicles under different loads according to the target load information obtained by conversion. This can obtain test information, thereby achieving the goal of improving the accuracy of test information and realizing the technical effect that the test information can reflect the load exposure intensity and fault correlation under different types of loads.

[0020] Optionally, the method further includes: in response to the test information being abnormal, re-executing the following steps: obtaining initial user profile information, initial attribute information, and initial environment information; generating original load information based on the initial user profile information, initial attribute information, and initial environment information; converting the original load information to obtain target load information; and determining test information based on the target load information and the number of times the door is used; or, in response to the weight of the original load information being an abnormal weight, adjusting the weight and determining the adjusted weight as the weight.

[0021] If the test information is abnormal, the process of determining the test information of the door is triggered to be re-executed. If the weight of the original load information is abnormal, the weight self-adjustment is triggered. This achieves the goal of improving the accuracy of the test information and realizes the technical effect that the test information can reflect the load exposure intensity and fault correlation under different types.

[0022] According to one aspect of the embodiments of this application, a device for determining the load information of a vehicle door is provided. The device may include: an acquisition unit, configured to acquire initial user profile information of a vehicle, initial attribute information of the vehicle, and initial environmental information of the environment in which the vehicle is located, wherein the initial user profile information is used to represent the usage state of the vehicle when the account corresponding to the vehicle logs into the vehicle, the initial attribute information is used to represent at least the attributes of the vehicle door, and the initial environmental information is used to represent the characteristics of the environment; a generation unit, configured to generate original load information of the vehicle door based on the initial user profile information, the initial attribute information, and the initial environmental information, wherein the original load information is used to represent the initial distribution state of the load borne by the vehicle door under different environments; a conversion unit, configured to convert the original load information to obtain target load information of the vehicle door, wherein the target load information is used to represent the target distribution state of the load borne by the vehicle door under different environments; and a first determination unit, configured to determine test information of the vehicle door based on the target load information and the number of times the vehicle door has been used, wherein the test information is used to represent the number of tests conducted on the vehicle door under load.

[0023] According to another aspect of the embodiments of this application, a processor is also provided. The processor is used to run a program, wherein the program is executed by the processor to perform the methods described in the embodiments of this application.

[0024] According to another aspect of the embodiments of this application, a vehicle is also provided, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of this application when it runs.

[0025] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided. This computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device where the computer-readable storage medium is located to perform the methods of the embodiments of this application.

[0026] According to another aspect of the embodiments of this application, a computer program product is also provided, the computer program product including a computer program, wherein the computer program implements the method in the embodiments of this application when executed by a processor.

[0027] According to another aspect of the embodiments of this application, a computer program product is also provided, including a non-volatile computer-readable storage medium for storing a computer program, which, when executed by a processor, implements the method in the embodiments of this application.

[0028] According to another aspect of the embodiments of this application, the embodiments of this application also provide a computer program that, when executed by a processor, implements the methods described in the embodiments of this application.

[0029] In this embodiment, when determining the test information of the vehicle door, the initial user profile information, initial attribute information, and initial environmental information of the vehicle's environment are obtained. Based on the initial user profile information, initial attribute information, and initial environmental information, the original load information of the vehicle door is generated. The original load information is converted to obtain the target load information of the vehicle door. Based on the target load information and the number of times the vehicle door is used, the test information of the vehicle door is determined. Since this application can generate the original load information of the vehicle door based on the initial user profile information, initial attribute information, and initial environmental information, that is, it can obtain the initial distribution state of the load borne by the vehicle door in different environments. Then, by converting the original load information, the target load information can be obtained, that is, the target distribution state of the load borne by the vehicle door in different environments can be obtained. Then, according to the converted target load information, the number of times the vehicle door is used is allocated to obtain the test information representing the number of tests of the vehicle door under load. This achieves the goal of improving the accuracy of the test information, thereby solving the technical problem that the test information is difficult to reflect the load exposure intensity and fault correlation under different types of conditions, and thus realizing the technical effect that the test information can reflect the load exposure intensity and fault correlation under different types of conditions. Attached Figure Description

[0030] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0031] Figure 1 This is a flowchart of a method for determining load information of a vehicle door according to an embodiment of this application;

[0032] Figure 2 This is a flowchart of a method for determining the load spectrum of a vehicle door in a real user scenario, according to an embodiment of this application.

[0033] Figure 3 This is a schematic diagram of a load information determination system for a vehicle door according to an embodiment of this application;

[0034] Figure 4 This is a schematic diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0035] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present application.

[0036] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0037] According to an embodiment of this application, a method for determining load information of a vehicle door is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0038] Figure 1 This is a flowchart of a method for determining the load information of a vehicle door according to an embodiment of this application, such as... Figure 1 As shown, the method may include the following steps:

[0039] Step S101: Obtain the initial user profile information of the vehicle, the initial attribute information of the vehicle, and the initial environment information of the environment in which the vehicle is located. The initial user profile information is used to indicate the usage status of the vehicle when the account corresponding to the vehicle logs into the vehicle. The initial attribute information is used to indicate at least the attributes of the doors in the vehicle. The initial environment information is used to indicate the characteristics of the environment.

[0040] In the technical solution provided in step S101 of this application, the initial user profile information can be used to represent the vehicle's usage status when the account corresponding to the vehicle logs into the vehicle. The vehicle's usage status can be described by its usage attributes and its permanent environment. For example, the initial user profile information can also be called initial user profile data. The vehicle's usage attributes can include at least one of the following: the vehicle's active days, average daily mileage, nighttime usage frequency, nighttime door opening ratio, average parking time, and average passenger capacity. The vehicle's permanent environment can include the vehicle's permanent location and permanent type. The permanent location can be at least one of the following: City A, City B, and City C, etc. The permanent type can be at least one of the following: city type, town type, and internal road type, etc. These are merely illustrative examples and are not specifically limited.

[0041] In this embodiment, the aforementioned initial attribute information can at least represent the attributes of the vehicle doors, windows, and Global Positioning System (GPS). For example, the aforementioned initial attribute information can be reflected by the raw signals from the Telematics Box (T-Box).

[0042] In this embodiment, the aforementioned initial environmental information can be used to represent environmental characteristics. For example, the aforementioned initial environmental information can be hourly meteorological data for a city, which may include at least one of the following: hourly temperature data, humidity data, and weather type data for a city, etc. This is only an example and is not specifically limited.

[0043] In this embodiment, the initial user profile information of the vehicle, the initial attribute information of the vehicle, and the initial environmental information of the environment in which the vehicle is located are obtained. Optionally, after accessing the vehicle's log information, this embodiment extracts information from the log information to obtain the initial user profile information, initial attribute information, and initial environmental information of the environment in which the vehicle is located, thereby achieving the purpose of obtaining the initial user profile information, initial attribute information, and initial environmental information.

[0044] Optionally, this embodiment can search the vehicle's initial user profile information, initial attribute information, and initial environment information of the vehicle's environment from the vehicle's usability database, thereby achieving the purpose of obtaining the initial user profile information, initial attribute information, and initial environment information.

[0045] Step S102: Based on the initial user profile information, initial attribute information and initial environment information, generate the original load information of the car door, wherein the original load information is used to represent the initial distribution state of the load borne by the car door under different environments.

[0046] In the technical solution provided by step S102 of this application, the aforementioned raw load information can be used to represent the initial distribution state of the load borne by the vehicle door under different environments. For example, the aforementioned raw load information can be the raw load spectrum, which can be represented by the original proportion of each load unit. To illustrate, the load unit can be a statistical unit formed by combining the following features: duration (duration_s), interval (interval_s), temperature (temp), humidity (humidity), window status (win_st), and weather status (weather_type), etc. This is just an example and is not a specific limitation.

[0047] In this embodiment, after obtaining the initial user profile information, initial attribute information, and initial environmental information of the vehicle's environment, the original load information of the vehicle door is generated based on the initial user profile information, initial attribute information, and initial environmental information. Optionally, this embodiment, based on obtaining the initial user profile information, initial attribute information, and initial environmental information, uses the initial user profile information to generate the initial attribute information and initial environmental information as the original load information of the vehicle door, thereby achieving the purpose of obtaining the initial distribution state of the load borne by the vehicle door under different environments.

[0048] Optionally, based on the initial user profile information, initial attribute information, and initial environment information obtained, the initial user profile information, initial attribute information, and initial environment information are preprocessed respectively to obtain target user profile information, target attribute information, and target environment information. Using the target user profile information, the target attribute information and target environment information are used to generate the original load information of the car door, thereby achieving the purpose of obtaining the initial distribution state of the load borne by the car door under different environments.

[0049] Step S103: The original load information is converted to obtain the target load information of the door, wherein the target load information is used to represent the target distribution state of the load borne by the door under different environments.

[0050] In the technical solution provided by step S103 of this application, the target load information can be used to represent the target distribution state of the load borne by the door under different environments. For example, the target load information can be represented by the reliability weighted proportion of each load unit. To reflect this.

[0051] In this embodiment, after generating the original load information of the car door based on the initial user profile information, initial attribute information, and initial environmental information, the original load information is transformed to obtain the target load information of the car door. Optionally, this embodiment adjusts the original load information based on the generated original load information, and transforms the adjusted original load information to obtain the target load information of the car door, thereby achieving the purpose of determining the target distribution state of the load borne by the car door under different environments.

[0052] Optionally, this embodiment, based on the generated original load information, uses the weights of the original load information to weight the original load information, and transforms the weighted original load information to obtain the target load information of the car door, thereby achieving the purpose of determining the target distribution state of the load borne by the car door in different environments.

[0053] Step S104: Based on the target load information and the number of times the door has been used, determine the test information of the door, wherein the test information is used to represent the number of times the door has been tested under load.

[0054] In the technical solution provided in step S104 of this application, the test information can be used to represent the number of tests conducted on the door under load. For example, the test information can be displayed using a cyclic quota table, which can be a cyclic quota table at the door position-load unit level.

[0055] In this embodiment, the number of times the car door is used can be the total number of cycles of the door's lifespan. .

[0056] In this embodiment, after converting the original load information to obtain the target load information of the door, the test information of the door is determined based on the target load information and the number of times the door has been used. Optionally, this embodiment, based on the converted target load information, allocates the number of times the door has been used according to the target load information to obtain the test information of the door, thereby achieving the goal of improving the accuracy of the test information.

[0057] Optionally, based on the target load information obtained by conversion, the number of times the car door is used is allocated to the load units of the vehicle under different loads according to the target load information, so as to obtain the test information of the car door, thereby achieving the purpose of improving the accuracy of the test information.

[0058] In steps S101 to S104 of this application, when determining the test information of the car door, the initial user profile information of the vehicle, the initial attribute information of the vehicle, and the initial environmental information of the environment in which the vehicle is located are obtained; based on the initial user profile information, the initial attribute information, and the initial environmental information, the original load information of the car door is generated; the original load information is converted to obtain the target load information of the car door; based on the target load information and the number of times the car door is used, the test information of the car door is determined. Based on the initial user profile information, initial attribute information, and initial environmental information, this application can generate the original load information of the car door, that is, it can obtain the initial distribution state of the load borne by the car door under different environments. Then, by transforming the above-mentioned original load information, the target load information can be obtained, that is, the target distribution state of the load borne by the car door under different environments can be obtained. Then, according to the transformed target load information, the number of times the car door is used is allocated, and test information representing the number of tests of the car door under load can be obtained. This achieves the purpose of improving the accuracy of test information, thereby solving the technical problem that test information is difficult to reflect the load exposure intensity and fault correlation under different types of conditions, and thus realizing the technical effect that test information can reflect the load exposure intensity and fault correlation under different types of conditions.

[0059] The following section further describes the steps of generating the original load information of the car door based on the initial user profile information, initial attribute information, and initial environment information in this embodiment.

[0060] As an optional embodiment, step S102, based on the initial user profile information, initial attribute information, and initial environment information, generates the original load information of the vehicle door, including: preprocessing the initial user profile information to obtain the target user profile information of the vehicle; preprocessing the initial attribute information to obtain the target attribute information of the vehicle; and preprocessing the initial environment information to obtain the target environment information of the vehicle; performing type recognition on the target user profile information to obtain a type recognition result, wherein the type recognition result is used to represent the relationship between the vehicle's usage type and its operational or residential type; and generating the original load information based on the type recognition result and the target attribute information and target environment information.

[0061] In this embodiment, the preprocessing described above may include at least one of the following operations: cleaning operation, time format unification operation, and signal interpolation and alignment operation, etc.

[0062] In this embodiment, after obtaining the initial user profile information of the vehicle, the initial attribute information of the vehicle, and the initial environmental information of the environment in which the vehicle is located, the initial user profile information is preprocessed to obtain the target user profile information of the vehicle, the initial attribute information is preprocessed to obtain the target attribute information of the vehicle, and the initial environmental information is preprocessed to obtain the target environmental information of the vehicle; the target user profile information is then subjected to type recognition to obtain the type recognition result.

[0063] Optionally, this embodiment preprocesses the acquired initial user profile information to obtain target user profile information, preprocesses the acquired initial attribute information to obtain target attribute information, and preprocesses the acquired initial environment information to obtain target environment information. Then, the target user profile information is input into a type recognition model for type recognition to obtain the type recognition result. The type recognition model can be constructed based on a classification model.

[0064] In this embodiment, the type identification result can be used to represent the relationship between the vehicle's usage type and its operational or residential type. For example, the type identification result can be a first type identification result, which can be used to indicate that the usage type is operational, or the type identification result can be a second type identification result, which can be used to indicate that the usage type is residential.

[0065] In this embodiment, after performing type identification on the target user profile information and obtaining the type identification result, the target attribute information and target environment information are used to generate the original payload information based on the type identification result. Optionally, in this embodiment, based on the obtained type identification result, if the type identification result is a first type identification result, the target attribute information and target environment information are used to generate first payload structure information, and the original payload information can be generated using the first payload structure information. Alternatively, if the type identification result is a second type identification result, the target attribute information and target environment information are used to generate second payload structure information, and the original payload information can be generated using the second payload structure information.

[0066] After obtaining the initial user profile information, initial attribute information, and initial environment information, preprocessing these information yields the target user profile information, target attribute information, and target environment information. Based on the type identification results obtained from the target user profile information, the target attribute information and target environment information are then used to generate the original payload information. This achieves the goal of generating original payload information based on the initial user profile information, initial attribute information, and initial environment information, thereby improving the accuracy of the original payload information.

[0067] The following section further describes the steps of generating original payload information from target attribute information and target environment information based on the type recognition results described in this embodiment.

[0068] As an optional embodiment, based on the type recognition result, target attribute information and target environment information are generated into original load information, including: in response to the type recognition result being a first type recognition result, the target attribute information and target environment information are combined into first load structure information, wherein the first type recognition result is used to indicate that the usage type is operation type, the first load structure information is used to indicate the structure of the load unit for the operation type vehicle, and the load unit is the feature type to which the load belongs; under the first load structure information, the first occurrence frequency of different loads corresponding to the load unit is recorded; according to the different door positions of the vehicle door, the recorded first occurrence frequency is normalized to obtain the first original load information, wherein the original load information includes: the first original load information.

[0069] In this embodiment, the first type identification result can be used to indicate that the usage type is an operation type. For example, the operation type can be represented by U1, which is only an example and not a specific limitation.

[0070] In this embodiment, the aforementioned first load structure information can be used to represent the structure of a load unit for an operational vehicle, wherein the load unit can be a characteristic type to which the load belongs. For example, the aforementioned first load structure information can be as follows: Load unit structure = door_pos × win_st × duration_s × interval_s × temp × humidity × weather_type. This is only an example and is not specifically limited.

[0071] In this embodiment, after type identification is performed on the target user profile information to obtain the type identification result, in response to the type identification result being a first type identification result, the target attribute information and target environment information are combined into first load structure information. Under the first load structure information, the first occurrence frequency of different loads corresponding to the load unit is recorded. Optionally, based on the obtained type identification result, this embodiment performs relationship detection on the above type identification result. If the type identification result is detected to be a first type identification result, the target attribute information and target environment information are combined into first load structure information. Then, under the first load structure information, the first occurrence frequency of different loads corresponding to the load unit is statistically analyzed, that is, the occurrence frequency of each load unit in all cycles is statistically analyzed.

[0072] In this embodiment, the aforementioned original load information may include: first original load information.

[0073] In this embodiment, after recording the first occurrence frequencies of different loads corresponding to the load units under the first load structure information, the recorded first occurrence frequencies are normalized according to the different door positions of the vehicle doors to obtain the first original load information. Optionally, this embodiment normalizes the recorded first occurrence frequencies according to the different door positions of the vehicle doors, and determines the normalized first occurrence frequencies as the first original load information. For example, within the structural layer of the load units, the occurrence frequencies of each load unit in all cycles are normalized, and the normalized occurrence frequencies are determined as the original load spectrum.

[0074] Based on different type recognition results, target attribute information and target environment information can be combined into corresponding load structure information. Under the corresponding load structure information, the occurrence frequency of different loads corresponding to the load unit is recorded, and the recorded occurrence frequency is normalized according to different door positions of the vehicle door to obtain the corresponding original load information. This achieves the goal of generating original load information based on type recognition results from target attribute information and target environment information, thereby improving the accuracy of the original load information.

[0075] The following section further describes the steps of generating original payload information from target attribute information and target environment information based on the type recognition results described in this embodiment.

[0076] As an optional embodiment, based on the type recognition result, target attribute information and target environment information are generated into original load information, including: in response to the type recognition result being a second type recognition result, the target attribute information and target environment information are combined into second load structure information, wherein the second type recognition result is used to indicate that the usage type is household type, and the second load structure information is used to indicate the structure of the load unit for the household type vehicle, and the load unit is the feature type to which the load belongs; under the second load structure information, the second occurrence frequency of different loads corresponding to the load unit is recorded; according to the different door positions of the vehicle door, the recorded second occurrence frequency is normalized to obtain the second original load information, wherein the original load information includes: the second original load information.

[0077] In this embodiment, the second type identification result can be used to indicate that the usage type is a household type. For example, the household type can be represented by U2. This is only an example and is not a specific limitation.

[0078] In this embodiment, the aforementioned second load structure information can be used to represent the structure of a load unit for a household vehicle, wherein the load unit can be a characteristic type to which the load belongs. For example, the aforementioned second load structure information can be as follows: Load unit structure = door_pos × win_st × duration_s × interval_s × temp × humidity × weather_type. This is only an example and is not specifically limited.

[0079] In this embodiment, after type identification is performed on the target user profile information to obtain the type identification result, in response to the type identification result being a second type identification result, the target attribute information and target environment information are combined into second load structure information. Under the second load structure information, the second occurrence frequency of different loads corresponding to the load unit is recorded. Optionally, based on the obtained type identification result, this embodiment performs relationship detection on the above type identification result. If the type identification result is detected to be a second type identification result, the target attribute information and target environment information are combined into second load structure information. Then, under the second load structure information, the second occurrence frequency of different loads corresponding to the load unit is statistically analyzed, that is, the occurrence frequency of each load unit in all cycles is statistically analyzed.

[0080] In this embodiment, the aforementioned original load information may include: second original load information.

[0081] In this embodiment, after recording the second occurrence frequencies of different loads corresponding to the load units under the second load structure information, the recorded second occurrence frequencies are normalized according to the different door positions of the vehicle doors to obtain the second original load information. Optionally, this embodiment normalizes the recorded second occurrence frequencies according to the different door positions of the vehicle doors, and determines the normalized second occurrence frequencies as the second original load information. For example, within the structural layer of the load units, the occurrence frequencies of each load unit in all cycles are normalized, and the normalized occurrence frequencies are determined as the original load spectrum.

[0082] Based on different type recognition results, target attribute information and target environment information can be combined into corresponding load structure information. Under the corresponding load structure information, the occurrence frequency of different loads corresponding to the load unit is recorded, and the recorded occurrence frequency is normalized according to different door positions of the vehicle door to obtain the corresponding original load information. This achieves the goal of generating original load information based on type recognition results from target attribute information and target environment information, thereby improving the accuracy of the original load information.

[0083] The following section further describes the steps of converting the original load information to obtain the target load information of the door in this embodiment.

[0084] As an optional embodiment, step S103, converting the original load information to obtain the target load information of the door, includes: weighting the original load information using the weights of the original load information; and normalizing the weighted original load information to obtain the target load information.

[0085] In this embodiment, the aforementioned weights are risk weights based on the original payload information. .

[0086] In this embodiment, after generating the original load information of the car door based on the initial user profile information, initial attribute information, and initial environment information, the original load information is weighted using the weights of the original load information; the weighted original load information is then normalized to obtain the target load information.

[0087] Optionally, this embodiment adjusts the original load information based on the generated original load information, and normalizes the adjusted original load information to obtain the target load information. The normalization process described above can be represented by the following equation (1):

[0088] (1)

[0089] in, It can be used to represent the original proportion of load elements. It can be used to represent the risk weight of a load cell. It can be used to represent a set of load cells under the same user type u and gate position d.

[0090] By weighting and normalizing the generated raw load information, the target load information can be obtained, thereby achieving the goal of obtaining the target load distribution state of the door under different environments, and thus realizing the technical effect of improving the accuracy of the target load information.

[0091] The method for determining the load information of the vehicle door described in this embodiment will be further described below.

[0092] As an optional implementation method, the relative risk ratio between multiple fault sample data and multiple normal sample data of the car door is determined to obtain multiple relative risk ratios; the average risk ratio is calculated by averaging the multiple relative risk ratios to obtain the average risk ratio, and the average risk ratio is determined as the weight.

[0093] In this embodiment, the aforementioned relative risk ratio (RR) is the relative risk ratio between the fault group and the control group.

[0094] In this embodiment, after determining the relative risk ratios between multiple fault sample data and multiple normal sample data of the car door, and obtaining multiple relative risk ratios, the multiple relative risk ratios are averaged to obtain the average risk ratio, and the average risk ratio is determined as the weight.

[0095] Optionally, this embodiment uses the number of cycles per 100 km as the main indicator to perform risk calculations on the fault sample data of the vehicle door. This yields a first risk level of door failure under the fault sample data. Similarly, risk calculations are performed on the normal sample data of the vehicle door to obtain a second risk level of door failure under the normal sample data. A relative calculation is then performed between the first and second risk levels to obtain the relative risk ratio between the fault sample data and the normal sample data. Finally, the average risk ratio is calculated by averaging multiple relative risk ratios, and this average risk ratio is determined as the weight of the original load information.

[0096] Since the weights of the original load information are obtained by averaging the relative risk ratios between multiple fault sample data and multiple normal sample data, the availability of the weights can be guaranteed, thereby achieving the technical effect of improving the effectiveness of weighted processing.

[0097] The following section further describes the steps of determining the test information of the car door based on the target load information and the number of times the car door has been used in this embodiment.

[0098] As an optional embodiment, step S104, based on the target load information and the number of times the door is used, determines the test information of the door, including: determining the door opening frequency information, wherein the door opening frequency information is used to represent the door opening frequency per unit mileage; determining the first product between the door opening frequency represented by the door opening frequency information and the target number of times the door is used, and determining the first product as the number of times of use; and allocating the number of times of use to the load units of the vehicle under different loads according to the target load information to obtain the test information.

[0099] In this embodiment, the aforementioned door opening frequency information can be used to represent the door opening frequency per unit mileage. That is, the aforementioned door opening frequency information can be used to represent the door opening rate per unit mileage. .

[0100] In this embodiment, the target number of uses can be used to represent the target lifespan of the door. .

[0101] In this embodiment, after converting the original load information to obtain the target load information of the door, the door opening frequency information is determined; the door opening frequency information is determined to be the first product between the door opening frequency and the target number of times the door is used, and the first product is determined as the number of times it is used; according to the target load information, the number of times it is used is allocated to the load units of the vehicle under different loads to obtain test information.

[0102] Optionally, after determining the door opening frequency information, this embodiment calculates the product of the door opening frequency represented by the door opening frequency information and the target number of times the door is used, thereby obtaining the first product between the door opening frequency and the target number of times the door is used, and the first product is determined as the number of times the door is used. Then, based on the target load information obtained by conversion, the number of times the door is used is allocated to the load units of the vehicle under different loads according to the target load information, thereby obtaining the door test information. Among them, determining the first product as the number of times the door is used can be achieved by the following formula (2), and allocating the number of times the door is used to the load units of the vehicle under different loads according to the target load information, thereby obtaining the door test information, can be achieved by the following formula (3).

[0103] (2)

[0104] (3)

[0105] Since the number of times a door is used is determined by the first product between the door opening frequency and the target number of uses, the number of uses is then allocated to the load units of vehicles under different loads according to the target load information obtained by conversion. This can obtain test information, thereby achieving the goal of improving the accuracy of test information and realizing the technical effect that the test information can reflect the load exposure intensity and fault correlation under different types of loads.

[0106] The method for determining the load information of the vehicle door described in this embodiment will be further described below.

[0107] As an optional embodiment, the method further includes: in response to the test information being abnormal, re-executing the following steps: obtaining initial user profile information, initial attribute information, and initial environment information; generating original load information based on the initial user profile information, initial attribute information, and initial environment information; converting the original load information to obtain target load information; and determining test information based on the target load information and the number of times the door is used; or, in response to the weight of the original load information being an abnormal weight, adjusting the weight and determining the adjusted weight as the weight.

[0108] In this embodiment, it is determined whether the test information is abnormal. If the test information is determined to be abnormal, the following steps are repeated: obtaining initial user profile information, initial attribute information, and initial environment information; generating original load information based on the initial user profile information, initial attribute information, and initial environment information; converting the original load information to obtain target load information; and determining the test information based on the target load information and the number of times the door is used.

[0109] In this embodiment, it is determined whether the weight of the original load information is an abnormal weight. If it is determined that the weight of the original load information is an abnormal weight, the weight is increased and the increased weight is determined as the weight of the original load information. Alternatively, the weight is decreased and the decreased weight is determined as the weight of the original load information.

[0110] If the test information is abnormal, the process of determining the test information of the door is triggered to be re-executed. If the weight of the original load information is abnormal, the weight self-adjustment is triggered. This achieves the goal of improving the accuracy of the test information and realizes the technical effect that the test information can reflect the load exposure intensity and fault correlation under different types.

[0111] In this embodiment, based on the initial user profile information, initial attribute information, and initial environmental information, the original load information of the car door can be generated. That is, the initial distribution state of the load borne by the car door under different environments can be obtained. Then, the original load information is transformed to obtain the target load information, that is, the target distribution state of the load borne by the car door under different environments can be obtained. Then, according to the transformed target load information, the number of times the car door is used is allocated to obtain test information representing the number of tests the car door has undergone under load. This achieves the goal of improving the accuracy of test information, thereby solving the technical problem that test information is difficult to reflect the load exposure intensity and fault correlation under different types of conditions. In this way, the technical effect of test information being able to reflect the load exposure intensity and fault correlation under different types of conditions is achieved.

[0112] The technical solutions of the embodiments of this application will be illustrated below with reference to preferred embodiments.

[0113] Currently, the durability design and verification of car doors are generally based on the "average service life of typical users". Test information for car doors is generated by applying a uniform tightening factor to several operating conditions. For example, test information for car doors is generated by applying tightening factors to normal opening and closing conditions and light impact conditions respectively.

[0114] However, the methods for obtaining test information mentioned above are overly stringent and make it difficult to make phased corrections to the test information based on actual door conditions and fault data. This results in the test information failing to reflect the technical problem of load exposure intensity and fault correlation under different types of conditions.

[0115] To address the aforementioned technical problems, this application proposes a method for determining the load information of a vehicle door. Based on initial user profile information, initial attribute information, and initial environmental information, the method generates the original load information of the vehicle door, i.e., the initial distribution of the load borne by the vehicle door under different environments. Then, by transforming the original load information, the method obtains the target load information, i.e., the target distribution of the load borne by the vehicle door under different environments. Following the transformed target load information, the method allocates the number of times the vehicle door is used, thus obtaining test information representing the number of tests conducted on the vehicle door under load. This improves the accuracy of the test information, thereby solving the technical problem that test information is difficult to reflect the correlation between load exposure intensity and fault under different types of conditions. Ultimately, this achieves the technical effect that test information can reflect the correlation between load exposure intensity and fault under different types of conditions.

[0116] In this embodiment, by executing a door load spectrum determination method oriented towards real user scenarios, test information representing the number of tests conducted on the door under load can be obtained. For example, Figure 2 This is a flowchart of a method for determining the load spectrum of a vehicle door in a real-world user scenario, according to an embodiment of this application. Figure 2 As shown, the method may include the following steps:

[0117] Step S201: Input initial data and preprocess the initial data.

[0118] In the technical solution provided in step S201 of this application, the initial data may include: T-Box raw signal, city hourly meteorological data, fault data, and user profile data. The T-Box raw signal may include: door information, door lock information, window information, vehicle speed, total mileage, and GPS data, etc. The fault data may include: Vehicle Identification Number (VIN) and Diagnostic Trouble Code (DTC), etc. The user profile data may include: vehicle model data, city of residence data, and usage attribute data, etc.

[0119] In this embodiment, preprocessing the initial data may include: unifying all timestamps of the initial data to the Chinese time zone (Coordinated Universal Time (UTC) + 8); matching meteorological information based on the city corresponding to the VIN; handling missing signals: when the continuous missing time is ≤5s, forward padding is used, and when the continuous missing time is >5s, the data segment is filtered; and aligning multiple signals: synchronizing signals such as door, window, vehicle speed, and mileage according to time to ensure feature matching at the same moment.

[0120] After inputting initial data and preprocessing it, step S202 is executed to identify user types from the user profile information.

[0121] In the technical solution provided by step S202 of this application, the vehicle usage attributes are automatically identified based on user profile information or behavioral statistical characteristics (e.g., number of active days, average daily mileage, and nighttime door opening ratio). Thus, the vehicles can be divided into: U1 (operational vehicles), which are used frequently and have many environmental changes, and U2 (household vehicles), which are used infrequently and have relatively stable environments.

[0122] It should be noted that all subsequent statistical processes are modeled independently for each user type.

[0123] After identifying user types from user profile information, step S203 is executed to identify cyclic events and construct features.

[0124] In the technical solution provided by step S203 of this application, the complete opening and closing cycle is identified for the signal sequence of each door position: each 0–1–0 process is recorded as one cycle event, and the six doors (driver's seat, passenger's seat, left rear, right rear, hood, and trunk) are counted independently.

[0125] In this embodiment, the following key features are extracted: duration_s: door closing time - door opening time, representing the duration of opening and closing; divided into four levels, D1-D4, according to P5-P95, eliminating extremely short and long dwell anomalies; interval_s: current door opening time - last door closing time, representing the door opening interval; divided into four levels, I1-I4, according to P5-P95; win_st: statistics on the opening and closing status of the windows within the cycle; temp: temperature divided into intervals (T1-T8); humidity: humidity divided into intervals (H1-H4); weather_type: optional weather type (sunny, rainy, snowy, etc.); count_day, count_100km, day_hour: frequency and time period characteristics used for statistical analysis, number of door openings and closings per day, number of door openings and closings per 100 kilometers, and door opening time.

[0126] After identifying cyclic events and constructing features, step S204 is executed to generate the original load spectrum.

[0127] In the technical solution provided in step S204 of this application, within user types U1 and U2, a load cell structure is defined: Load cell structure = door_pos × win_st × duration_s × interval_s × temp × humidity × weather_type. The frequency of occurrence of each load cell is statistically analyzed and normalized within the load cell structure layer to obtain the original proportion. .

[0128] After generating the original load spectrum, step S205 is performed to determine the fault weights.

[0129] In the technical solution provided in step S205 of this application, the risk weight of each load unit can be calculated by comparing the exposure intensity of faulty vehicles and normal vehicles in different time windows. The weight calculation step may include the following steps: defining a window, using the first DTC report time of the faulty VIN as a benchmark, taking three different time windows before the first report, and simultaneously matching normal vehicle samples in terms of vehicle type, city, month, and mileage level; calculating the exposure intensity: the number of cycles for each load unit is mainly based on "times / 100 km", calculating the incidence ratio (RR) between the faulty group and the control group; performing empirical Bayesian (EB) shrinkage on the load unit-level RR value, with the shrinkage intensity... The risk weights are determined by categorizing samples by size and taking a robust average of the RR values ​​across the three time windows. .

[0130] After determining the fault weights, step S206 is executed to generate the weighted spectrum.

[0131] In the technical solution provided by step S206 of this application, within the same user type and gate level, each load unit is risk-weighted and renormalized. The renormalization process keeps the total number of lifetimes of each gate unchanged, only adjusting the relative proportion of each load unit to form a reliability weighted spectrum. The renormalization process can be expressed by the following formula (1):

[0132] (1)

[0133] in, It can be used to represent the original proportion of load elements. It can be used to represent the risk weight of a load cell. It can be used to represent a set of load cells under the same user type u and gate position d.

[0134] After generating the weighted spectrum, step S207 is executed to convert the weighted spectrum into bench test cycle quotas and set the target lifetime.

[0135] In the technical solution provided by step S207 of this application, the weighted spectrum is converted into bench test cycle quotas based on the actual usage intensity and lifespan target of the vehicle: the door opening rate per unit mileage is calculated at the VIN×door level, and the truncated mean of multiple VIN data is taken to obtain... Setting target lifespan mileage. Then, the total number of gate lifetime cycles can be calculated using the following formula (2). The total number of gate lifetime cycles is then allocated to each load unit according to a weighted ratio using the following formula (3). Two sets of spectrum structures (U1 / U2) are output to generate a gate-load unit level cycle quota table, which can be directly used for durability bench test design and verification.

[0136] (2)

[0137] (3)

[0138] After converting the weighted spectrum into bench test cycle quotas and setting the target lifetime, step S208 is executed to output the result file and verify the stability of the quota table.

[0139] In the technical solution provided in step S208 of this application, the following result files are generated: a hierarchical load spectrum table, a load unit cyclic quota table, a fault risk distribution and weight comparison table, and a visualization report. The visualization report may include: spectrum diagrams for each gate position, risk heatmaps, and distribution comparison diagrams, etc. The robustness and repeatability of the algorithm are ensured through spectrum stability verification (cross-month difference <10%) and data coverage verification (effective VIN coverage >90%).

[0140] After verifying the stability of the quota table in the output file, step S209 is executed to determine whether a phased update should be performed.

[0141] If it is determined that a phased update is needed, then step S201 is executed. If it is determined that no phased update is needed, then the execution of the door load spectrum determination method for real user scenarios ends.

[0142] In this embodiment, when determining the test information of the vehicle door, the initial user profile information, initial attribute information, and initial environmental information of the vehicle's environment are obtained. Based on the initial user profile information, initial attribute information, and initial environmental information, the original load information of the vehicle door is generated. The original load information is converted to obtain the target load information of the vehicle door. Based on the target load information and the number of times the vehicle door is used, the test information of the vehicle door is determined. Since this application can generate the original load information of the vehicle door based on the initial user profile information, initial attribute information, and initial environmental information, that is, it can obtain the initial distribution state of the load borne by the vehicle door in different environments, and then convert the above-mentioned original load information to obtain the target load information, that is, it can obtain the target distribution state of the load borne by the vehicle door in different environments, and then allocate the number of times the vehicle door is used according to the converted target load information, the test information representing the number of tests of the vehicle door under load can be obtained. This achieves the purpose of improving the accuracy of the test information, thereby solving the technical problem that the test information is difficult to reflect the load exposure intensity and fault correlation under different types of conditions, and thus realizing the technical effect that the test information can reflect the load exposure intensity and fault correlation under different types of conditions.

[0143] According to an embodiment of this application, a device for determining the load information of a vehicle door is also provided. It should be noted that this device can be used to execute a method for determining the load information of a vehicle door according to one of the embodiments.

[0144] Figure 3 This is a schematic diagram of a vehicle door load information determination device according to an embodiment of this application. Figure 3 As shown, the load information determination device 300 for the car door may include: an acquisition unit 301, a generation unit 302, a conversion unit 303, and a first determination unit 304.

[0145] The acquisition unit 301 is used to acquire the initial user profile information of the vehicle, the initial attribute information of the vehicle, and the initial environment information of the environment in which the vehicle is located. The initial user profile information is used to indicate the usage status of the vehicle when the account corresponding to the vehicle logs into the vehicle. The initial attribute information is used to indicate at least the attributes of the doors in the vehicle. The initial environment information is used to indicate the characteristics of the environment.

[0146] The generation unit 302 is used to generate the original load information of the car door based on the initial user profile information, initial attribute information and initial environment information, wherein the original load information is used to represent the initial distribution state of the load borne by the car door under different environments.

[0147] The conversion unit 303 is used to convert the original load information to obtain the target load information of the door, wherein the target load information is used to represent the target distribution state of the load borne by the door under different environments.

[0148] The first determining unit 304 is used to determine the test information of the door based on the target load information and the number of times the door has been used, wherein the test information is used to represent the number of times the door has been tested under load.

[0149] Optionally, the generation unit 302 may include: a preprocessing module, used to preprocess the initial user profile information to obtain the target user profile information of the vehicle, preprocess the initial attribute information to obtain the target attribute information of the vehicle, and preprocess the initial environmental information to obtain the target environmental information of the vehicle; an identification module, used to perform type identification on the target user profile information to obtain type identification results, wherein the type identification results are used to represent the relationship between the vehicle's usage type and its operational or residential type; and a generation module, used to generate the original payload information from the target attribute information and the target environmental information based on the type identification results.

[0150] Optionally, the generation module may include: a first combination submodule, configured to combine target attribute information and target environment information into first load structure information in response to a type identification result being a first type identification result, wherein the first type identification result indicates that the usage type is an operation type, and the first load structure information indicates the structure of the load unit for the operation type vehicle, and the load unit is the feature type to which the load belongs; a first recording submodule, configured to record the first occurrence frequency of different loads corresponding to the load unit under the first load structure information; and a first normalization submodule, configured to normalize the recorded first occurrence frequency according to the different door positions of the vehicle door to obtain first original load information, wherein the original load information includes: first original load information.

[0151] Optionally, the generation module may include: a second combination submodule, used to combine target attribute information and target environment information into second load structure information in response to the type recognition result being a second type recognition result, wherein the second type recognition result is used to indicate that the usage type is a household type, and the second load structure information is used to indicate the structure of the load unit for a household type vehicle, and the load unit is the feature type to which the load belongs; a second recording submodule, used to record the second occurrence frequency of different loads corresponding to the load unit under the second load structure information; and a second normalization submodule, used to normalize the recorded second occurrence frequency according to the different door positions of the vehicle door to obtain the second original load information, wherein the original load information includes: the second original load information.

[0152] Optionally, the conversion unit 303 may include: a weighting module for weighting the original load information using the weights of the original load information; and a normalization module for normalizing the weighted original load information to obtain the target load information.

[0153] Optionally, the load information determination device 300 for the vehicle door may further include: a second determination unit, used to determine the relative risk ratio between multiple fault sample data and multiple normal sample data of the vehicle door, and obtain multiple relative risk ratios; and a third determination unit, used to calculate the average risk ratio of the multiple relative risk ratios, obtain the average risk ratio, and determine the average risk ratio as a weight.

[0154] Optionally, the first determining unit 304 may include: a first determining module, used to determine the door opening frequency information, wherein the door opening frequency information is used to represent the door opening frequency per unit mileage; a second determining module, used to determine the first product between the door opening frequency represented by the door opening frequency information and the target number of uses of the door, and to determine the first product as the number of uses; and an allocation module, used to allocate the number of uses to the load units of the vehicle under different loads according to the target load information, to obtain test information.

[0155] Optionally, the load information determination device 300 for the vehicle door may further include: a response unit, configured to re-execute the following steps in response to the test information being abnormal: acquiring initial user profile information, initial attribute information, and initial environment information; generating original load information based on the initial user profile information, initial attribute information, and initial environment information; converting the original load information to obtain target load information; and determining test information based on the target load information and the number of times the vehicle door has been used; or, in response to the weight of the original load information being an abnormal weight, adjusting the weight and determining the adjusted weight as the weight.

[0156] In this embodiment, a device for determining the load information of a vehicle door is provided. The device may include: an acquisition unit, configured to acquire initial user profile information of the vehicle, initial attribute information of the vehicle, and initial environmental information of the environment in which the vehicle is located, wherein the initial user profile information represents the usage state of the vehicle when the account corresponding to the vehicle logs into the vehicle, the initial attribute information represents at least the attributes of the vehicle door, and the initial environmental information represents the characteristics of the environment; a generation unit, configured to generate original load information of the vehicle door based on the initial user profile information, initial attribute information, and initial environmental information, wherein the original load information represents the initial distribution state of the load borne by the vehicle door under different environments; a conversion unit, configured to convert the original load information to obtain target load information of the vehicle door, wherein the target load information represents the target distribution state of the load borne by the vehicle door under different environments; and a first determination unit, configured to determine test information of the vehicle door based on the target load information and the number of times the vehicle door has been used, wherein the test information represents the number of tests conducted on the vehicle door under load. Based on the initial user profile information, initial attribute information, and initial environmental information, this application can generate the original load information of the car door, that is, it can obtain the initial distribution state of the load borne by the car door under different environments. Then, by transforming the above-mentioned original load information, the target load information can be obtained, that is, the target distribution state of the load borne by the car door under different environments can be obtained. Then, according to the transformed target load information, the number of times the car door is used is allocated, and test information representing the number of tests of the car door under load can be obtained. This achieves the purpose of improving the accuracy of test information, thereby solving the technical problem that test information is difficult to reflect the load exposure intensity and fault correlation under different types of conditions, and thus realizing the technical effect that test information can reflect the load exposure intensity and fault correlation under different types of conditions.

[0157] According to an embodiment of this application, an electronic device is also provided. Figure 4 This is a schematic diagram of an electronic device according to an embodiment of this application, such as... Figure 4As shown, the electronic device 400 may include a memory 410 and a processor 420. The memory 410 is used to store an executable program; the processor 420 is used to run the program stored in the memory 410. When the program runs, it executes the method for determining the load information of the vehicle door of this application.

[0158] In this application, "multiple" refers to two or more.

[0159] In this application, unless otherwise expressly defined, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0160] The terms “first,” “second,” “third,” “fourth,” etc., in this application (if present) are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0161] In this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, in this application, the character " / " generally indicates that the preceding and following related objects have an "or" relationship.

[0162] According to an embodiment of this application, a processor is also provided for running a program, wherein the program is executed by the processor to perform the method for determining the load information of the vehicle door in the embodiment.

[0163] According to an embodiment of this application, a computer program product is also provided, which includes a computer program, wherein when the computer program is executed by a processor, it implements the method for determining the load information of the vehicle door in the embodiment.

[0164] According to an embodiment of this application, a computer program product is also provided, including a non-volatile computer-readable storage medium for storing a computer program. When the computer program is executed by a processor, it implements the method for determining the load information of the vehicle door in the embodiment.

[0165] According to an embodiment of this application, a computer program is also provided, which, when executed by a processor, implements the method for determining the load information of the vehicle door in the embodiment.

[0166] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided. The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the door load information determination method of the embodiment.

[0167] Computer-readable storage media, also known as computer storage media, may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. These propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable storage media can transmit, propagate, or transfer programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0168] The program code contained in a computer-readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, radio frequency, or any suitable combination thereof.

[0169] According to an embodiment of this application, a computer program product is also provided, which includes a computer program, wherein when the computer program is executed by a processor, it implements the method for determining the load information of the vehicle door in the embodiment.

[0170] According to an embodiment of this application, a computer program product is also provided, including a non-volatile computer-readable storage medium for storing a computer program. When the computer program is executed by a processor, it implements the method for determining the load information of the vehicle door in the embodiment.

[0171] According to an embodiment of this application, a computer program is also provided, which, when executed by a processor, implements the method for determining the load information of the vehicle door in the embodiment.

[0172] Optionally, when the above-mentioned computer program is executed by the processor, the program code implements the following steps: obtaining initial user profile information of the vehicle, initial attribute information of the vehicle, and initial environmental information of the environment in which the vehicle is located, wherein the initial user profile information is used to represent the usage status of the vehicle when the account corresponding to the vehicle logs into the vehicle, the initial attribute information is used to represent at least the attributes of the doors in the vehicle, and the initial environmental information is used to represent the characteristics of the environment; generating original load information of the doors based on the initial user profile information, initial attribute information, and initial environmental information, wherein the original load information is used to represent the initial distribution state of the load borne by the doors under different environments; converting the original load information to obtain target load information of the doors, wherein the target load information is used to represent the target distribution state of the load borne by the doors under different environments; determining the test information of the doors based on the target load information and the number of times the doors have been used, wherein the test information is used to represent the number of tests conducted on the doors under load.

[0173] Optionally, when the above computer program is executed by the processor, the program code implements the following steps: preprocessing the initial user profile information to obtain the target user profile information of the vehicle; preprocessing the initial attribute information to obtain the target attribute information of the vehicle; and preprocessing the initial environmental information to obtain the target environmental information of the vehicle; performing type recognition on the target user profile information to obtain the type recognition result, wherein the type recognition result is used to represent the relationship between the vehicle's usage type and its operational or residential type; and generating the original payload information based on the type recognition result and the target attribute information and target environmental information.

[0174] Optionally, when the above computer program is executed by the processor, the program code implements the following steps: in response to the type identification result being a first type identification result, the target attribute information and the target environment information are combined into first load structure information, wherein the first type identification result is used to indicate that the usage type is an operation type, the first load structure information is used to indicate the structure of the load unit for the operation type vehicle, and the load unit is the feature type to which the load belongs; under the first load structure information, the first occurrence frequency of different loads corresponding to the load unit is recorded; according to the different door positions of the vehicle door, the recorded first occurrence frequency is normalized to obtain the first original load information, wherein the original load information includes: the first original load information.

[0175] Optionally, when the above computer program is executed by the processor, the program code implements the following steps: in response to the type recognition result being a second type recognition result, the target attribute information and the target environment information are combined into second load structure information, wherein the second type recognition result is used to indicate that the usage type is a household type, and the second load structure information is used to indicate the structure of the load unit for a household type vehicle, and the load unit is the feature type to which the load belongs; under the second load structure information, the second occurrence frequency of different loads corresponding to the load unit is recorded; according to the different door positions of the vehicle door, the recorded second occurrence frequency is normalized to obtain the second original load information, wherein the original load information includes: the second original load information.

[0176] Optionally, when the above computer program is executed by the processor, the program code implements the following steps: weighting the original load information using the weights of the original load information; normalizing the weighted original load information to obtain the target load information.

[0177] Optionally, when the above computer program is executed by the processor, the program code implements the following steps: determining the relative risk ratios between multiple fault sample data and multiple normal sample data of the car door, respectively, to obtain multiple relative risk ratios; averaging the multiple relative risk ratios to obtain the average risk ratio, and determining the average risk ratio as a weight.

[0178] Optionally, when the above computer program is executed by the processor, the program code implements the following steps: determining the door opening frequency information, wherein the door opening frequency information is used to represent the door opening frequency per unit mileage; determining the first product between the door opening frequency represented by the door opening frequency information and the target number of uses of the door, and determining the first product as the number of uses; and allocating the number of uses to the load units of the vehicle under different loads according to the target load information to obtain test information.

[0179] Optionally, when the above computer program is executed by the processor, the program code implements the following steps: in response to the test information being abnormal, the following steps are re-executed: obtaining initial user profile information, initial attribute information, and initial environment information; generating original load information based on the initial user profile information, initial attribute information, and initial environment information; converting the original load information to obtain target load information; and determining test information based on the target load information and the number of times the door is used; or, in response to the weight of the original load information being an abnormal weight, adjusting the weight, and determining the adjusted weight as the weight.

[0180] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0181] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0182] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0183] The units described as separate components may or may not be physically separate. Similarly, the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0184] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0185] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to related technologies, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0186] The above are merely preferred embodiments of this application. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for determining the load information of a vehicle door, characterized in that, include: The system obtains initial user profile information of the vehicle, initial attribute information of the vehicle, and initial environment information of the environment in which the vehicle is located. The initial user profile information is used to indicate the usage status of the vehicle when the account corresponding to the vehicle logs into the vehicle. The initial attribute information is used to indicate at least the attributes of the vehicle doors. The initial environment information is used to indicate the characteristics of the environment. Based on the initial user profile information, the initial attribute information, and the initial environment information, the original load information of the car door is generated, wherein the original load information is used to represent the initial distribution state of the load borne by the car door under different environments; The original load information is transformed to obtain the target load information of the vehicle door, wherein the target load information is used to represent the target distribution state of the load borne by the vehicle door under different environments; Based on the target load information and the number of times the door has been used, test information for the door is determined, wherein the test information is used to represent the number of times the door has been tested under the load.

2. The method according to claim 1, characterized in that, Based on the initial user profile information, the initial attribute information, and the initial environment information, the original load information of the vehicle door is generated, including: The initial user profile information is preprocessed to obtain the target user profile information of the vehicle; the initial attribute information is preprocessed to obtain the target attribute information of the vehicle; and the initial environment information is preprocessed to obtain the target environment information of the vehicle. The target user profile information is subjected to type identification to obtain type identification results, wherein the type identification results are used to represent the relationship between the vehicle's usage type and its operational or residential type; Based on the type identification result, the target attribute information and the target environment information are used to generate the original payload information.

3. The method according to claim 2, characterized in that, Based on the type identification result, the target attribute information and the target environment information are used to generate the original payload information, including: In response to the type identification result being a first type identification result, the target attribute information and the target environment information are combined into first load structure information, wherein the first type identification result is used to indicate that the usage type is the operation type, and the first load structure information is used to indicate the structure of the load unit for the vehicle of the operation type, and the load unit is the feature type to which the load belongs; Under the first load structure information, the first occurrence frequency of different loads corresponding to the load unit is recorded; According to the different door positions, the recorded first occurrence frequency is normalized to obtain the first original load information, wherein the original load information includes: the first original load information.

4. The method according to claim 2, characterized in that, Based on the type identification result, the target attribute information and the target environment information are used to generate the original payload information, including: In response to the type identification result being a second type identification result, the target attribute information and the target environment information are combined into second load structure information, wherein the second type identification result is used to indicate that the usage type is the household type, and the second load structure information is used to indicate the structure of the load unit of the vehicle for the household type, and the load unit is the feature type to which the load belongs; Under the second load structure information, the second occurrence frequency of different loads corresponding to the load unit is recorded; According to the different door positions, the recorded second occurrence frequency is normalized to obtain the second original load information, wherein the original load information includes: the second original load information.

5. The method according to claim 1, characterized in that, The original load information is transformed to obtain the target load information of the vehicle door, including: The original load information is weighted using the weights of the original load information; The weighted original load information is normalized to obtain the target load information.

6. The method according to claim 5, characterized in that, The method further includes: The relative risk ratios between multiple fault sample data and multiple normal sample data of the vehicle door are determined respectively, resulting in multiple relative risk ratios; The average risk ratio is obtained by averaging the multiple relative risk ratios, and the average risk ratio is determined as the weight.

7. The method according to claim 1, characterized in that, Based on the target load information and the number of times the door has been used, the test information of the door is determined, including: Determine the door opening frequency information, wherein the door opening frequency information is used to represent the door opening frequency per unit mileage; Determine the first product between the door opening frequency represented by the door opening frequency information and the target number of times the door is used, and determine the first product as the number of times the door is used; According to the target load information, the number of uses is allocated to the load units of the vehicle under different loads to obtain the test information.

8. The method according to any one of claims 1 to 7, characterized in that, The method further includes: In response to the test information being abnormal, the following steps are re-executed: obtaining the initial user profile information, the initial attribute information, and the initial environment information; generating the original load information based on the initial user profile information, the initial attribute information, and the initial environment information; transforming the original load information to obtain the target load information; and determining the test information based on the target load information and the number of times the door has been used; or... In response to the weight of the original load information being an abnormal weight, the weight is adjusted, and the adjusted weight is determined as the original weight.

9. A device for determining the load information of a vehicle door, characterized in that, include: The acquisition unit is used to acquire the initial user profile information of the vehicle's account, the initial attribute information of the vehicle, and the initial environment information of the environment in which the vehicle is located. The initial user profile information is used to indicate the usage status of the vehicle when the account is logged into the vehicle, the initial attribute information is used to indicate at least the attributes of the vehicle doors, and the initial environment information is used to indicate the characteristics of the environment. The generation unit is used to generate the original load information of the car door based on the initial user profile information, the initial attribute information and the initial environment information, wherein the original load information is used to represent the initial distribution state of the load borne by the car door under different environments; A conversion unit is used to convert the original load information to obtain the target load information of the vehicle door, wherein the target load information is used to represent the target distribution state of the load borne by the vehicle door under different environments; The first determining unit is used to determine test reference information for the vehicle door based on the target load information and the number of times the vehicle door has been used, wherein the test reference information is used to represent the number of times the vehicle door has been tested under the load.

10. An electronic device, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program, when running, performs the method according to any one of claims 1 to 8.

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