Whole vehicle weight obtaining method, device and equipment and storage medium

Abstract

The invention discloses a whole vehicle weight acquisition method and device, computer equipment and a storage medium, and aims to solve the problem that an accurate whole vehicle weight target and an accurate decomposition system weight target cannot be determined according to an actual vehicle model in the prior art. The method comprises the following steps: predicting the weight of a first assembly part of a first system assembly in a vehicle system assembly through a preset weight prediction model; the weight of a second assembly part of a second system assembly in the vehicle system assembly is searched by searching a database, and the first system assembly and the second system assembly are obtained by splitting based on the characteristics of the vehicle system assembly; and obtaining the weight of the whole vehicle according to the weight of the first assembly part and the weight of the second assembly part.

Description

Technical Field

[0001] The present invention relates to the technical field of automobile lightweighting, and in particular to a method, device, equipment and storage medium for obtaining the weight of a whole vehicle. Background Art

[0002] Under the premise of ensuring the strength and safety performance of the car, reducing the overall equipment mass of the car as much as possible can effectively improve the car's power and reduce fuel consumption, thereby effectively reducing emission pollution.

[0003] In the prior art, big data analysis is usually used to fit the whole vehicle, and then the weight target of the whole vehicle is set through the fitted whole vehicle weight correlation model. Then, according to the weight ratio of each system and the set whole vehicle weight target, the weight target of each system is obtained. However, in the actual research and development process, the weight of the whole vehicle is affected by many factors, and these factors also affect the proportion of each system. In particular, in new energy vehicles, the proportion of batteries is significantly different from that of traditional vehicles. Therefore, if the weight of the whole vehicle is decomposed or the weight target of the whole vehicle is set according to a fixed ratio, it is impossible to obtain an accurate weight target for the whole vehicle and the weight targets for each system. Summary of the invention

[0004] The embodiments of the present invention provide a method, device, computer equipment and storage medium for obtaining the weight of a whole vehicle, so as to solve the problem that the prior art cannot accurately determine the weight target of the whole vehicle and the weight target of the decomposition system according to the actual vehicle model.

[0005] In a first aspect, the present invention provides a method for obtaining vehicle weight, comprising:

[0006] Predicting the weight of a first assembly part of a first system assembly in a vehicle system assembly by using a preset weight prediction model;

[0007] Searching a database to find the weight of a second assembly part of a second system assembly in the vehicle system assembly, wherein the first system assembly and the second system assembly are obtained based on feature separation of the vehicle system assembly;

[0008] The weight of the entire vehicle is obtained according to the weight of the first assembly parts and the weight of the second assembly parts.

[0009] In a possible design, the first system assembly and the second system assembly are separated in the following manner based on the characteristics of the vehicle system assembly:

[0010] Determining a reference system assembly corresponding to the vehicle system assembly, wherein the reference system assembly refers to a system assembly of the same type as the vehicle system assembly in a competing vehicle;

[0011] Screening out a third system assembly having a changed weight from among the control system assemblies;

[0012] The vehicle system assembly corresponding to the third system assembly is used as the first system assembly;

[0013] Screening out a fourth system assembly whose weight does not change compared to the control system assembly;

[0014] The vehicle system assembly corresponding to the fourth system assembly is used as the second system assembly.

[0015] In a possible design, obtaining the vehicle weight according to the weight of the first assembly part and the weight of the second assembly part includes:

[0016] Determine the initial weight of the vehicle;

[0017] Adding the weight of the first assembly part and the weight of the second assembly part to obtain a predicted vehicle weight;

[0018] If the initial weight of the whole vehicle is inconsistent with the predicted weight of the whole vehicle, the weight of the vehicle assembly parts is corrected by using the preset weight target and the lightweight rate of the reference system assembly corresponding to the vehicle system assembly to obtain the weight of the whole vehicle, and the weight of the vehicle assembly parts includes the weight of the first assembly parts and / or the weight of the second assembly parts.

[0019] In a possible design, the weight of the vehicle assembly parts is corrected by presetting the weight target and the lightweight ratio of the reference system assembly corresponding to the vehicle system assembly, including:

[0020] If the preset weight target is not equal to the predicted vehicle weight, calculating the average of the lightweight rates of the control system assemblies corresponding to the vehicle system assembly as the expected average;

[0021] If the lightweight ratio of the vehicle system assembly is equal to the expected average value, the weight of the vehicle assembly parts is corrected by the expected average value.

[0022] In a possible design, the method of correcting the weight of the vehicle assembly parts by using the expected mean value includes:

[0023] Calculating an expected difference between the expected weight of the assembly parts and the weight of the vehicle assembly parts by using the expected mean value;

[0024] The weight of the vehicle assembly part is corrected according to the expected difference.

[0025] In a possible design, after calculating the average of the lightweight rates of the reference system assemblies corresponding to the vehicle system assembly as the expected average, the method further includes:

[0026] If the lightweight rate of the vehicle system assembly is not equal to the expected mean, obtaining an expected standard mean through the expected mean and the standard deviation of the expected mean;

[0027] If the lightweight rate of the vehicle system assembly is equal to the expected standard mean, the weight of the vehicle assembly parts is corrected by the expected standard mean.

[0028] In a possible design, the method of correcting the weight of the vehicle assembly parts by using the expected standard mean value includes:

[0029] Calculating an expected standard deviation between the expected standard weight and the weight of the vehicle assembly part by using the expected standard mean;

[0030] The vehicle assembly part weight is corrected according to the expected standard deviation value.

[0031] In a possible design, predicting the weight of a first assembly part of a first system assembly in a vehicle system assembly by using a preset weight prediction model includes:

[0032] Predicting the initial assembly parts weight of the first system assembly in the vehicle system assembly by using the weight prediction model;

[0033] Obtaining a correlation index of the weight prediction model by using a weight mean of a control system assembly corresponding to the vehicle system assembly;

[0034] If the correlation index exceeds the expected index, the initial assembly part weight is used as the first assembly part weight.

[0035] In a second aspect, a vehicle weight acquisition device is provided, comprising:

[0036] A prediction module, used to predict the weight of a first assembly part of a first system assembly in the vehicle system assembly by using a preset weight prediction model;

[0037] A search module, configured to search a database to find a weight of a second assembly part of a second system assembly in the vehicle system assembly, wherein the first system assembly and the second system assembly are obtained based on feature separation of the vehicle system assembly;

[0038] An acquisition module is used to acquire the weight of the entire vehicle according to the weight of the first assembly part and the weight of the second assembly part.

[0039] In a third aspect, a computer device is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned vehicle weight acquisition method when executing the computer program.

[0040] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned method for obtaining the weight of the entire vehicle are implemented.

[0041] The above-mentioned vehicle weight acquisition method, device, computer equipment and storage medium first predict the weight of the first assembly part of the first system assembly in the vehicle system assembly through a preset weight prediction model. Then, by searching the database, the weight of the second assembly part of the second system assembly in the vehicle system assembly is searched, wherein the first system assembly and the second system assembly are obtained based on the characteristics of the vehicle system assembly. Finally, the weight of the vehicle is obtained according to the weight of the first assembly part and the weight of the second assembly part. The present invention classifies the vehicle system assembly according to the characteristics of the vehicle system assembly, and divides it into the first system assembly and the second system assembly. The weight of the first assembly part of the first system assembly is obtained by the weight prediction model, and the weight of the second assembly part of the second system assembly is obtained by searching the database. Compared with the prior art, the weight of the vehicle is estimated by the weight of the competing vehicle first, and then the weight of the assembly parts of each system assembly is obtained according to the weight ratio of the system assembly. The present invention is more accurate and reasonable in calculating the weight of the system assembly parts, and the weight of the vehicle finally obtained based on the weight of the system assembly parts is also more accurate and reasonable. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0043] Figure 1 It is a schematic diagram of a process of a method for obtaining vehicle weight in one embodiment of the present invention;

[0044] Figure 2 1 is a schematic diagram of probability interval distribution of LACU strategy in a vehicle weight acquisition method in one embodiment of the present invention;

[0045] Figure 3 is a schematic diagram of a vehicle weight acquisition device in one embodiment of the present invention;

[0046] Figure 4is a schematic diagram of a computer device in one embodiment of the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] Vehicle lightweighting technology has become an important indicator for measuring the level of the automotive industry and product development capabilities. Lightweighting of vehicles can effectively save fuel and reduce energy consumption. In traditional solutions, the research on lightweighting technology for vehicles mainly focuses on the research and development of lightweight materials, lightweight optimization of vehicle structures, and some lightweight processes. However, the above research methods are considered from the perspective of the weight of the entire vehicle. By adjusting the materials, structure, and process of the entire vehicle, the purpose of lightweighting the entire vehicle can be achieved.

[0049] However, for the lightweight of the whole vehicle, it is more important to set a reasonable and accurate vehicle weight in the initial stage of vehicle development, and determine the weight of each system assembly and assembly parts through the vehicle weight. A reasonable and accurate vehicle weight can effectively prevent the increase of R&D costs and the waste of development resources. In addition, improving the accuracy of the vehicle weight will make the design of each system assembly more reasonable and the performance better, effectively improving the vehicle's R&D efficiency.

[0050] In the prior art, there are generally two ways to set the weight of the vehicle and the weight of each system assembly or assembly parts in the initial stage of research and development:

[0051] Method 1: Through big data analysis, the influencing parameter information such as vehicle size parameters, fuel consumption, engine power, etc. is fitted to obtain the vehicle weight correlation model. Then, the vehicle weight is obtained through the vehicle weight correlation model and the key factors of the vehicle model. Next, according to the weight ratio of each system assembly of the vehicle, the weight of each system assembly is obtained. For example, based on the Excel internal function Linest, a multivariate linear regression analysis method is obtained, and then a univariate linear regression model of influencing parameter information such as design unit area, mass, and listing year is established to obtain the vehicle weight. Finally, the weight of each system assembly of the vehicle is obtained through the proportion method.

[0052] Method 2: First, determine the weight of the key system assembly of the vehicle, then use the weight ratio of the system assembly to obtain the weight of other system assemblies of the vehicle, and then add up the weight of all system assemblies of the vehicle to obtain the weight of the entire vehicle. For example, first disassemble the weight data of the competitor's vehicle, then use the lightweight coefficient of the competitor's body-in-white as the basis, and use the proportional method to obtain the weight of the entire vehicle that takes into account both lightweight and rigidity.

[0053] However, the above solutions all have shortcomings: in method 1, since the weight of the whole vehicle is affected by many factors, a univariate linear regression model is established from the influencing parameter information such as unit area mass and projected area, and the weight of the whole vehicle obtained by this method is not accurate due to many factors such as vehicle performance, materials, and shape. In addition, since the proportions of system assemblies of different models are very different, the weight of each system assembly obtained by the proportion method is neither accurate nor reasonable.

[0054] In the second method, the weight data of the key system assembly is obtained by disassembling the actual vehicle of the competitor. Then, the system assembly weight and the vehicle weight of the vehicle to be developed are predicted based on the size, stiffness data, and lightweight coefficient of the competitor. This method relies too much on the data of competitor vehicles, which leads to the following problems: First, it is difficult to find models with exactly the same or very close product positioning in vehicle development. Second, disassembling competitor vehicles will cost a lot of cost and time. Third, even for competitor vehicles of the same model, there will be large differences in the detailed technical solutions, so the proportion of each system assembly is quite different. Therefore, it is impossible to obtain an accurate and reasonable system assembly or a reasonable vehicle weight through the proportion of the system assembly.

[0055] In summary, the weight of the whole vehicle itself is affected by many factors, such as the size, shape, functional configuration, performance requirements, material application, and optimization design capabilities of the whole vehicle. The proportions of the system assemblies of different models are also different, and even vary greatly. Especially in new energy vehicles, the absolute values ​​of the weights of battery packs of different models and their proportions vary greatly. If the weight of the system assembly of the whole vehicle is decomposed or the weight of the whole vehicle is obtained according to a fixed ratio, a large weight error will be found in the later stage of research and development, which leads to the inability to carry out research and development and design according to the originally set weight of the whole vehicle and the decomposed weight of the system assembly during the research and development process, and it is impossible to design and analyze related performance and components, which leads to repeated research and development processes and waste of research and development resources. Therefore, an embodiment of the present invention provides a method for determining the weight of system assembly parts, which can be applied in a computer device. The computer device can be implemented with an independent server or a server cluster composed of multiple servers, which is not limited here. The method disassembles the vehicle into multiple vehicle system assemblies, and divides the vehicle system assemblies into a first system assembly and a second system assembly according to the characteristics of the vehicle system assembly, thereby respectively obtaining the weight of the first assembly parts and the weight of the second assembly parts, and finally obtaining the weight of the whole vehicle based on the weight of the first assembly parts and the weight of the second assembly parts. Since the method disassembles the vehicle into multiple vehicle system assemblies, then calculates the weight of different system assemblies respectively, and finally obtains the weight of the whole vehicle, the method essentially sets the weight of each vehicle system assembly while setting the weight of the whole vehicle.

[0056] In one embodiment, if Figure 1 As shown, a method for determining the weight of system assembly parts is provided, and the method is described by taking the application of the method in a computer device as an example, comprising the following steps:

[0057] S10: Predicting the weight of a first assembly part of a first system assembly in the vehicle system assembly by using a preset weight prediction model.

[0058] S20: searching a database to find the weight of a second assembly part of a second system assembly in the vehicle system assembly.

[0059] The first system assembly and the second system assembly in steps S10-S20 are obtained by classifying the vehicle system assembly based on the characteristics of the vehicle system assembly, wherein the vehicle system assembly is obtained by disassembling the vehicle structure. Then, the weights of the first system assembly and the second system assembly are determined in different ways.

[0060] First, the weight of the first system assembly is determined by step S10, that is, the weight of the first assembly parts is determined. Specifically, the weight of the first assembly parts of the first system assembly in the vehicle system assembly is predicted by a weight prediction model, wherein the weight prediction model refers to a model that can predict the weight of the first system assembly, and the weight prediction model includes but is not limited to a regression model, a classification model, etc. The vehicle system assembly refers to each collection obtained by disassembling the whole vehicle, and the assembly is a whole composed of a series of parts or products, which realizes a specific function. The vehicle system assembly includes but is not limited to an engine assembly, a transmission assembly, a drive axle assembly, and a brake system, etc. Each assembly contains different parts. For example, the engine assembly includes but is not limited to a cylinder block, a cylinder head, a timing gear chamber, a valve cover, a crankshaft, etc., and the drive axle assembly includes but is not limited to a main reducer, a differential, a bridge housing, a steering knuckle, etc.

[0061] Next, the weight of the second system assembly, that is, the weight of the second assembly parts, is determined through step S20. Specifically, the weight of the second assembly parts of the second system assembly in the vehicle system assembly is found through the database. Among them, the database uses the key parameter information of the system assembly as a field, so that the weight of the corresponding system assembly can be read directly through the key parameter information or a combination of key parameter information. Among them, the key parameter information includes but is not limited to the surface area and material of the system assembly. The data in the database can be obtained by collecting data from competing vehicles, or it can be predicted by the model corresponding to the current vehicle, which is not limited here.

[0062] S30: Obtaining the weight of the entire vehicle according to the weight of the first assembly parts and the weight of the second assembly parts.

[0063] In this embodiment, the weight of the whole vehicle is obtained based on the weight of the first assembly parts and the weight of the second assembly parts. Specifically, since the whole vehicle is disassembled into multiple vehicle system assemblies, the weight of the first assembly parts and the second assembly parts can be added together to obtain the weight of the whole vehicle, or the weight of the first assembly parts and the second assembly parts can be further adjusted according to the weight to obtain the weight of the whole vehicle, which is not limited here.

[0064] It should be noted that this embodiment classifies the vehicle system assembly into a first system assembly and a second system assembly. The weight of the first assembly parts of the first system assembly is obtained through a weight prediction model, while the weight of the second assembly parts of the second system assembly is obtained by searching a database. Compared with the prior art, which first estimates the weight of the entire vehicle through the weight of competing vehicles, and then obtains the weight of the assembly parts of each system assembly based on the weight ratio of the system assembly, the present invention calculates the weight of the system assembly parts more accurately and reasonably, and the final vehicle weight obtained based on the weight of the system assembly parts is also more accurate and reasonable.

[0065] In one embodiment, in step S20, the first system assembly and the second system assembly are separated in the following manner:

[0066] S21: determining a reference system assembly corresponding to the vehicle system assembly, where the reference system assembly refers to a system assembly of the same type as the vehicle system assembly in a competing vehicle;

[0067] S22: Screening out the third system assembly whose weight has changed from the control system assembly.

[0068] S23: taking the vehicle system assembly corresponding to the third system assembly as the first system assembly.

[0069] S24: Screening out the fourth system assembly whose weight does not change with respect to the control system assembly.

[0070] S25: Using the vehicle system assembly corresponding to the fourth system assembly as the second system assembly.

[0071] In this embodiment, the reference system assembly corresponding to the vehicle system assembly is determined through the key parameter information of the vehicle system assembly, wherein the reference system assembly refers to a system assembly of the same type as the vehicle system assembly in a competing vehicle, and the key parameter information refers to preset parameter information that can determine the reference system assembly, including but not limited to size parameters, fuel consumption, engine power, etc. The types of vehicle system assemblies include but are not limited to engine assemblies, steering gear assemblies, transmission assemblies, front and rear axles, frames, etc. The system assembly of the same type as the vehicle system assembly means: when the vehicle system assembly is an engine assembly, its corresponding reference system assembly is the engine assembly in a competing vehicle; when the vehicle system assembly is a frame, its corresponding reference system assembly is the frame in a competing vehicle.

[0072] After determining one or more control system assemblies corresponding to the vehicle system assembly, the vehicle system assembly is screened by the weight of the control system assembly. Specifically, the third system assembly whose weight changes among the control system assemblies is screened out; the vehicle system assembly corresponding to the third system assembly is used as the first system assembly. Next, the fourth system assembly whose weight does not change among the control system assemblies is screened out; the vehicle system assembly corresponding to the fourth system assembly is used as the second system assembly.

[0073] Among them, steps S22-S25 are essentially to determine whether the weight of the vehicle system assembly will change with the change of key parameter information. If it will not change, the vehicle system assembly is classified as the second system assembly, and the weight of the second assembly parts corresponding to the second system assembly can be directly read from the database. If it will change, it means that the vehicle system assembly will change due to the influence of different factors. At this time, the weight of the vehicle assembly cannot be directly determined based on the existing parts weight or assembly parts weight, and must be calculated based on the weight prediction model. Therefore, the vehicle system assembly is classified as the first system assembly.

[0074] For example, the vehicle system assembly includes self-developed fixed-model engines and certain configuration products in electronic appliances, such as T-BOX. The weight of these engines and configuration products will not change due to changes in their key parameter information. Therefore, self-developed fixed-model engines and certain configuration products in electronic appliances are classified as the second system assembly. In this case, the corresponding weight of the engine or configuration product can be directly queried through the database.

[0075] It should be noted that the present embodiment essentially provides a method for classifying vehicle system assemblies based on the characteristics of the vehicle system assemblies, and the characteristics are mainly based on whether the weight of the corresponding system assemblies in the existing models has changed. The system assembly whose weight will change is taken as the first system assembly, and its weight is obtained by the weight prediction model. The system assembly whose weight will not change is taken as the second system assembly, and the assembly parts of the system assembly in the database are directly read to obtain the weight of the second assembly parts. In order to improve the error caused by the prior art in directly obtaining the vehicle weight of the vehicle system assembly based on the data related to the competing vehicles, so as to make the calculation of the weight of the first assembly parts and the weight of the second assembly parts more accurate and reasonable, and finally the vehicle weight obtained based on the weight of the first assembly parts and the weight of the second assembly parts is more accurate and reasonable.

[0076] In one embodiment, in step S30, obtaining the weight of the vehicle according to the weight of the first assembly part and the weight of the second assembly part specifically includes the following steps:

[0077] S31: Determine the initial weight of the vehicle.

[0078] S32: Add the weight of the first assembly parts and the weight of the second assembly parts to obtain a predicted weight of the entire vehicle.

[0079] S33: If the initial weight of the whole vehicle is inconsistent with the predicted weight of the whole vehicle, the weight of the vehicle assembly parts is corrected by using the preset weight target and the lightweight rate of the reference system assembly corresponding to the vehicle system assembly to obtain the weight of the whole vehicle, wherein the weight of the vehicle assembly parts includes the weight of the first assembly parts and / or the weight of the second assembly parts.

[0080] In this embodiment, the initial weight of the vehicle is first determined, wherein the method for determining the initial weight of the vehicle can be obtained by methods in the prior art, for example, based on the vehicle data of multiple competing vehicles, multiple key variable parameters of the vehicle weight are determined, thereby establishing a multivariate linear regression model including vehicle volume, maximum engine power and preset mileage comprehensive fuel consumption, and obtaining the initial weight of the vehicle by fitting the multivariate linear regression model.

[0081] Then, the weight of the first assembly parts and the weight of the second assembly parts are added to obtain the predicted weight of the whole vehicle. Next, it is determined whether the initial weight of the whole vehicle is consistent with the predicted weight of the whole vehicle. If they are consistent, the predicted weight of the whole vehicle is used as the final weight of the whole vehicle. If they are inconsistent, multiple reference system assemblies with the same key parameter information as the vehicle system assembly are obtained. Finally, the weight of the vehicle assembly parts is corrected by the preset weight target and the lightweight rate of the reference system assembly to obtain the weight of the whole vehicle. Among them, the weight of the vehicle assembly parts refers to the weight of the vehicle system assembly. Since the vehicle system assembly includes the first system assembly and / or the second system assembly, the weight of the vehicle assembly parts includes the weight of the first assembly parts and / or the weight of the second assembly parts. Lightweighting is to minimize the deadweight of the structure under given boundary conditions while meeting certain life and reliability requirements. The lightweight rate refers to the probability of weight reduction or fuel consumption of the lightweight system assembly. The preset weight target refers to the weight target set in advance according to the design requirements. The design requirements can be formulated by the project team or obtained through market analysis, which is not limited here. The preset weight target may be the predicted weight of the entire vehicle, or may be any other possible weight range, which is not limited here.

[0082] Specifically, the initial weight of the whole vehicle is obtained by the existing technology, and then the predicted weight of the whole vehicle is obtained by summing the weight of the first assembly part and the weight of the second assembly part. Next, the initial weight of the whole vehicle and the predicted weight of the whole vehicle are compared, and the assembly parts of the control system assembly of the competing vehicle are used as a reference to obtain the lightweight rate of the control system assembly, and then the predicted weight of the whole vehicle is corrected, that is, the weight of the first assembly part and the weight of the second assembly part are corrected to correct the weight of the whole vehicle. For example, the weight of the first assembly part is p1, the weight of the second assembly part is p2, and the original predicted weight of the whole vehicle is (p1+p2). Through the lightweight rate of the control system assembly, it is concluded that the weight of the first assembly part should be corrected to P1, and the weight of the second assembly part should be corrected to P2. Therefore, the final corrected weight of the whole vehicle is (P1+P2).

[0083] For example, build the BOM structure based on the whole vehicle, determine the vehicle system assembly, and then obtain the predicted weight of the whole vehicle according to the above steps. Compare the initial weight of the whole vehicle with the predicted weight of the whole vehicle as follows:

[0084] When the initial weight of the vehicle is greater than the predicted weight of the vehicle, a certain intermediate value between the initial weight and the predicted weight of the vehicle is taken as the final vehicle weight. The lightweighting rate is obtained by comparing the system assembly, thereby improving the lightweighting rates of the first system assembly and the second system assembly, and correcting and increasing the weight of the first assembly parts and the second assembly parts to obtain the corrected vehicle weight.

[0085] When the initial weight of the vehicle is less than the predicted weight of the vehicle, a certain intermediate value between the predicted weight of the vehicle and the initial weight of the vehicle is taken as the final vehicle weight, and the lightweight rate is obtained by comparing the system assembly, thereby reducing the lightweight rates of the first system assembly and the second system assembly, and correcting and increasing the weight of the first assembly parts and the second assembly parts, thereby obtaining the corrected vehicle weight.

[0086] In addition, since the preset weight target can be specified according to the needs of the project team, when the project team determines the preset weight target as the predicted weight of the vehicle, regardless of the comparison result between the initial weight of the vehicle and the predicted weight of the vehicle, this embodiment directly uses the predicted weight of the vehicle as the weight of the vehicle, and there is no need to correct the weight of the first assembly parts and the weight of the second assembly parts.

[0087] Specifically, the weight of a Class A SUV (Sports Utility Vehicle) needs to be calculated. At this time, the initial weight of the vehicle is 1524 kg using existing technology. Then, the vehicle system assembly of the SUV is obtained, and the weight information of the assembly parts is as shown in the following table.

[0088]

[0089] From the above table, we can see that the total weight of the system assembly parts of the SUV is 1546.55kg, so the predicted weight of the whole vehicle is 1547kg.

[0090] Next, the predicted weight of the vehicle is compared with the initial weight of the vehicle. The initial weight of the vehicle M = 1524kg < predicted weight of the vehicle = 1547kg. At this time, the middle value between the initial weight of the vehicle and the predicted weight of the vehicle is taken as the final weight of the vehicle. After comparative analysis with the control system assembly, it is found that the predicted weight of system assembly parts such as the body in white, door assembly, and tires are heavier than the corresponding parts of the core competitive assembly. Through the data of the core competitive vehicle, the lightweight rate k of the predicted value is adjusted to obtain the corrected predicted value. Then the weight of each system assembly is obtained as shown in the following table, and then the weight of the vehicle is obtained.

[0091]

[0092] It should be noted that, since the preset weight target includes the design and development requirements of the R&D group, the present embodiment corrects the predicted weight of the whole vehicle, and the obtained vehicle weight not only meets the needs of the R&D group, but also takes into account the positioning and concept of the system assembly in the market in combination with competing vehicles. Specifically, in the actual R&D process, the predicted weight of the whole vehicle can be directly used as the final vehicle weight, but the vehicle design process needs to be combined with the positioning and concept of many competing vehicles on the current market. Therefore, the present embodiment corrects the predicted weight of the whole vehicle based on the comparison results of the initial weight of the whole vehicle and the predicted weight of the whole vehicle and the lightweight rate of the competing vehicles, so as to obtain a more reasonable vehicle weight, effectively preventing the dilemma of not being able to directly use the predicted weight of the whole vehicle due to actual market demand in the later R&D or design process, and obtaining a more reasonable and accurate predicted weight of the whole vehicle, reducing repeated and redundant design and R&D processes, speeding up the R&D speed, and reducing the consumption of R&D funds.

[0093] In one embodiment, step S33, namely, correcting the weight of the vehicle assembly parts by using the preset weight target and the lightweight ratio of the reference system assembly corresponding to the vehicle system assembly, specifically includes the following steps:

[0094] S331: If the preset weight target is not equal to the predicted vehicle weight, calculate the average of the lightweight rates of the reference system assemblies corresponding to the vehicle system assembly as the expected average.

[0095] S332: If the lightweight rate of the vehicle system assembly is equal to the expected average value, the weight of the vehicle assembly parts is corrected according to the expected average value.

[0096] In this embodiment, first, it is determined whether the preset weight target is equal to the predicted weight of the whole vehicle. If the preset weight target is equal to the predicted weight of the whole vehicle, the predicted weight of the whole vehicle is directly used as the weight of the whole vehicle; if the preset weight target is not equal to the predicted weight of the whole vehicle, the predicted weight of the whole vehicle needs to be further corrected to make it meet the preset weight target. Specifically, the mean of the lightweighting rates of all control system assemblies is calculated as the expected mean, where the mean of the lightweighting rate refers to the average value of the lightweighting rates of all control system assemblies. Then, it is determined that the lightweighting rate of the vehicle system assembly is equal to the expected mean. If the lightweighting rate of the vehicle system assembly is equal to the expected mean, the weight of the vehicle assembly parts is corrected by the expected mean.

[0097] Wherein, step S322 specifically includes the following steps:

[0098] Determine whether the lightweight rate of the first system assembly is equal to the expected mean;

[0099] If the lightweight rate of the first system assembly is equal to the expected mean, the weight of the first assembly parts is corrected by the expected mean, and the corrected weight of the first assembly parts is used as the weight of the third assembly parts.

[0100] Determine whether the lightweight ratio of the second system assembly is equal to the expected mean;

[0101] If the lightweight rate of the second system assembly is equal to the expected mean, the weight of the second assembly parts is corrected by the expected mean, and the corrected weight of the second assembly parts is used as the weight of the fourth assembly parts.

[0102] In the subsequent steps, the weight of the entire vehicle is obtained based on the corrected weight of the first assembly parts and the second assembly parts, that is, the weight of the third assembly parts and the weight of the fourth assembly parts.

[0103] Specifically, the method of correcting the weight of the vehicle assembly parts (that is, the weight of the first assembly parts and / or the weight of the second assembly parts) by the expected mean value is mainly achieved by comparing the lightweight rate of the assembly parts of the system assembly. For example, the system assembly includes multiple assembly parts, and the lightweight rate of the assembly parts is k. 1 , k 2 , k 3 ……k N , and then the lightweight ratio of the control system assembly is obtained as k = F(k 1 , k 2 , k 3 ……k N ), and thus the average value of the lightweight rate is obtained as the expected average value. Therefore, the corrected weight of the third assembly part M = k × M 第一总成零件重量 , the corrected weight of the fourth assembly part M = k × M 第二总成零件重量 .

[0104] In addition, the lightening rate k in this embodiment is calculated as follows Figure 2 The LACU (leadership, leading position, competitive in the industry, uncompetitive in the industry, full name Leading, Among The Leaders, Competitive, Uncompetitive) strategy shown is implemented. The lightweight rate follows a normal distribution. The smaller the lightweight rate, the better the weight. The probability of the lightweight rate in each LACU interval satisfies the following formula:

[0105]

[0106] The LACU boundary value of the lightweight ratio k is as follows:

[0107]

[0108] In the above formula, μ is the mean value of the lightweight ratio k of the control system assembly, and δ is its standard deviation.

[0109] When k=μ, the weight of the first assembly parts and / or the second assembly parts is corrected to obtain the weight of the third assembly parts and the weight of the fourth assembly parts, thereby obtaining the weight of the entire vehicle.

[0110] It should be noted that in this embodiment, the weight of the first assembly parts and / or the weight of the second assembly parts are corrected by comparing the lightweight rate of the system assembly, thereby effectively preventing the final vehicle weight from not meeting market expectations. By comparing the weight of the third assembly parts and / or the weight of the fourth assembly parts adjusted by the lightweight rate of the system assembly, a more reasonable and accurate vehicle weight is obtained, which will make the lightweight rate of the final vehicle weight in the expected position, that is, the expected LACU position, thereby preventing the discovery of the set vehicle weight not meeting its market positioning in the later stage of design or development, and re-designing the research and development, reducing redundant research and development time, and effectively preventing the waste of research and development resources.

[0111] In one embodiment, step S332, namely, correcting the weight of the vehicle assembly parts by using the expected mean value, specifically includes the following steps:

[0112] S41: Calculate the expected difference between the expected weight of the assembly parts and the weight of the vehicle assembly parts through the expected mean value.

[0113] S42: Correcting the weight of the vehicle assembly parts according to the expected difference.

[0114] In this embodiment, the expected difference between the expected weight of the assembly parts and the weight of the vehicle assembly parts is calculated by the expected mean value, and then the weight of the vehicle assembly parts is corrected according to the expected difference. The method of correcting the vehicle assembly parts according to the expected difference includes but is not limited to adding or subtracting the expected difference from the weight of the vehicle assembly parts.

[0115] Steps S41-S42 include two aspects: on the one hand, the expected difference between the expected assembly part weight and the first assembly part weight is calculated through the expected mean, and then the corrected first assembly part weight, that is, the third assembly part weight, is obtained through the expected difference and the first assembly part weight. On the other hand, the expected difference between the expected assembly part weight and the second assembly part weight is calculated through the expected mean, and then the corrected second assembly part weight, that is, the fourth assembly part weight, is obtained through the expected difference and the second assembly part weight.

[0116] Specifically, when k = μ, the weight of the third system assembly parts M = (1 + μ) × M 第一总成零件重量 , and the weight of the fourth system assembly parts is obtained as M = (1 + μ) × M 第二总成零件重量 , that is, the lightweighting rate remains the same as the average lightweighting rate of the control system assembly, so that the weight of the third assembly parts and the weight of the fourth assembly parts are at the average level of competing vehicles, and the final vehicle weight will also be at the average level of competing vehicles.

[0117] It should be noted that the present embodiment substantially provides a method for correcting the weight of the first assembly parts and / or the weight of the second assembly parts by means of the expected mean, thereby effectively preventing the weight of the first assembly parts or the weight of the second assembly parts from failing to meet the expected market positioning, that is, the expected LACU status, thereby preventing the discovery in the later stages of design or R&D that the set lightweight rate of the first system assembly or the second system assembly does not meet its market positioning, and thus preventing the need to re-carry out R&D design, thereby reducing redundant R&D time and effectively preventing the waste of R&D resources.

[0118] In one embodiment, after step S331, that is, calculating the average of the lightweight rates of the reference system assemblies corresponding to the vehicle system assemblies as the expected average, the vehicle weight acquisition method further includes the following steps:

[0119] S51: If the lightweight ratio of the vehicle system assembly is not equal to the expected mean, an expected standard mean is obtained by using the expected mean and the standard deviation of the expected mean.

[0120] S52: If the lightweight rate of the vehicle system assembly is equal to the expected standard mean, the weight of the vehicle assembly parts is corrected according to the expected standard mean.

[0121] In the path where the lightweight rate of the vehicle system assembly is not equal to the expected mean, the expected standard mean is first obtained through the expected mean and the standard deviation of the expected mean. Among them, the standard deviation (SD, full name Standard Deviation, symbolized as σ) is also called the standard deviation and the mean square error, which is used to measure the degree of dispersion of the lightweight rates of all control system assemblies. Therefore, the expected standard mean is obtained through the expected mean and the standard deviation of the expected mean.

[0122] Then, it is determined whether the lightweight rate of the vehicle system assembly is equal to the expected standard mean. If it is equal, the weight of the vehicle assembly parts is corrected by the expected standard mean.

[0123] Specifically, on the one hand, if the lightweight rate of the first system assembly is not equal to the expected mean, the expected standard mean of the first system assembly is calculated by the expected mean and the standard deviation of the expected mean, and then it is determined whether the lightweight rate of the first system assembly is equal to the expected standard mean. If it is, the weight of the first assembly parts is corrected by the expected standard mean, and the corrected weight of the first assembly parts is used as the weight of the fifth assembly parts. On the other hand, if the lightweight rate of the second system assembly is not equal to the expected mean, the expected standard mean of the second system assembly is calculated by the expected mean and the standard deviation of the expected mean, and then it is determined whether the lightweight rate of the second system assembly is equal to the expected standard mean. If it is, the weight of the second assembly parts is corrected by the expected standard mean, and the corrected weight of the second assembly parts is used as the weight of the sixth assembly parts. In the subsequent steps, the weight of the whole vehicle is obtained by the weight of the fifth assembly parts and the weight of the sixth assembly parts.

[0124] Specifically, through the same steps as in the above steps S331-S332, it is obtained that μ is the mean value of the lightweight rate k of the control system assembly, and δ is its standard deviation.

[0125] When k = k L =μ-1.25δ, by correcting the weight of the first assembly parts and the second assembly parts, the weight of the fifth assembly parts and the weight of the sixth assembly parts are obtained, and then the weight of the whole vehicle is obtained.

[0126] It should be noted that in this embodiment, the weight of the first assembly parts and / or the weight of the second assembly parts are adjusted by comparing the lightweight rate of the system assembly. Since the lightweight rate of the vehicle system assembly does not meet the expected average, the final vehicle weight is effectively prevented from not meeting market expectations. By comparing the weight of the fifth assembly parts and / or the weight of the sixth assembly parts adjusted by the lightweight rate of the system assembly, a more reasonable and accurate vehicle weight is obtained, which will make the lightweight rate of the final vehicle weight in the expected position, that is, the expected LACU position, thereby preventing the discovery of the set vehicle weight not meeting its market positioning in the later stage of design or development, and re-designing the research and development, reducing redundant research and development time, and effectively preventing the waste of research and development resources.

[0127] In one embodiment, step S52, i.e., correcting the weight of the vehicle assembly parts by using the expected standard mean, specifically includes the following steps:

[0128] S521: Calculate the expected standard deviation between the expected standard weight and the vehicle assembly part weight using the expected standard mean.

[0129] S522: Correcting the vehicle assembly part weight according to the expected standard deviation value.

[0130] In this embodiment, the expected standard deviation between the expected standard weight and the weight of the vehicle assembly parts is calculated by the expected standard mean. Then, the weight of the vehicle assembly parts is corrected according to the expected standard deviation. The method of correcting the vehicle assembly parts according to the expected standard deviation includes but is not limited to adding or subtracting the expected standard deviation from the weight of the vehicle assembly parts.

[0131] Steps S521-S522 include two aspects: on the one hand, the expected standard deviation between the expected standard weight and the weight of the first assembly part is calculated through the expected standard mean, and then the corrected weight of the first assembly part, that is, the weight of the fifth assembly part, is obtained through the expected standard deviation and the weight of the first assembly part. On the other hand, the expected standard deviation between the expected standard weight and the weight of the second assembly part is calculated through the expected standard mean, and then the corrected weight of the second assembly part, that is, the weight of the sixth assembly part, is obtained through the expected standard deviation and the weight of the second assembly part.

[0132] Specifically, when k=k L =μ-1.25δ, the weight of the fifth system assembly parts is obtained as M = (1+μ-1.25δ)×M 第一总成零件重量 , and the weight of the sixth system assembly parts is obtained as M = (1 + μ - 1.25δ) × M 第二总成零件重量That is, the lightweighting rate is in the top 10% of the lightweighting rate of the control system assembly, so that the weight of the fifth system assembly parts and the weight of the sixth system assembly parts are at the leading L (Leader) level of the control system assembly parts weight, that is, the final vehicle weight will be at the leading L level of competing vehicles.

[0133] It should be noted that the present embodiment substantially provides a method for correcting the weight of the first assembly parts and / or the weight of the second assembly parts by means of the expected standard mean, thereby effectively preventing the weight of the first assembly parts and / or the weight of the second assembly parts from failing to meet the expected market positioning, that is, the expected LACU status, thereby preventing the discovery in the late stage of design or R&D that the set lightweight rate of the first system assembly and / or the second system assembly does not meet its market positioning, and thus preventing the need for re-R&D design, thereby reducing redundant R&D time and effectively preventing the waste of R&D resources.

[0134] In one embodiment, step S10, i.e., predicting the weight of a first assembly part of a first system assembly in a vehicle system assembly by using a preset weight prediction model, specifically includes the following steps:

[0135] S11: Predicting the initial assembly parts weight of the first system assembly in the vehicle system assembly by using the weight prediction model.

[0136] S12: Obtaining a correlation index of the weight prediction model through the weight mean of the control system assembly corresponding to the vehicle system assembly.

[0137] S13: If the correlation index exceeds the expected index, the initial assembly part weight is used as the first assembly part weight.

[0138] In this embodiment, the initial assembly part weight of the first system assembly in the vehicle system assembly is first predicted by the weight prediction model. Then, multiple control system assemblies with the same key parameter information as the vehicle assembly are collected, and then the correlation index of the weight prediction model is obtained by the weight average of all control system assemblies. If the correlation index exceeds the expected index, the initial assembly part weight is used as the first assembly part weight.

[0139] Specifically, the key parameter information of the first assembly system, such as the size (length, width, height, diameter), the material used, and the solution type, is obtained, and the weight prediction model of the first assembly system is established as follows:

[0140] Y=α 0 +α 1 x 1 +α 2 x 2 +α 3 x 3 +...+αp x p +C

[0141]

[0142] In the above model, Y is the dependent variable, α 0 and C is a dimensionless constant, x i (i=1,2…p) is the independent variable, which is the key parameter of the system assembly, α i is the regression coefficient (i=1,2…,p), which is the key parameter x of the weight prediction model i (i=1,2…,p) corresponding to the characteristic coefficient, that is, x 1 、x 2 、x 3 ……is the key factor affecting the weight of P assembly parts, α 1 , α 2 , α 3 ...is the regression coefficient of the corresponding independent variable. Among them, the dependent variable Y is also called the function value. In the functional relationship, it will change with the change of the independent variable. The dimensionless physical constant C is a dimensionless physical constant, that is, a pure number without any unit attached and a value that is independent of the unit system used.

[0143] RSS is the residual sum of squares, TSS is the total sum of squares, is the independent variable x i For dependent variables The predicted value of is the average value. is the independent variable x i For the dependent variable M 预测 The predicted weight value of is the average weight of all sample models. 2 is the correlation index, that is, the goodness of model fit, the correlation index R 2 The closer it is to 1, the better the regression fitting effect of the vehicle weight prediction model is. It is generally believed that the model fitting goodness of more than 0.8 is relatively high. Therefore, in this embodiment, the preset expected index is 0.8. 2 If it exceeds 0.8, the initial assembly part weight is taken as the first assembly part weight.

[0144] For example, the key parameter information of the first assembly system is input into the model to obtain the weight of the first assembly parts. The first assembly excess includes the weight of the assembly parts in the first assembly system, including but not limited to the weight of the body-in-white, hood cover, tires, battery pack and other assembly parts. Specifically, the first system assembly that needs to be calculated is the hood cover. First, the parameter information of the hood cover is obtained through technical means through multiple channels such as A2MAC1 and self-developed data, including weight, material, length, width, height, etc. Then, through regression analysis of the influencing factors of the hood cover weight, it is determined that the weight of the hood cover is mainly affected by two key parameters, one is the material used for the hood cover (steel or aluminum), and the other is the surface area of ​​the hood cover (length × width). The formula fitted with a large amount of data is as follows:

[0145] M 预测 =9.3682S―1.4355(if Steel)

[0146] =5.5087S―1.0456(if Alum)

[0147] In the above formula, S is the area of ​​the engine cover, which is obtained by the product of the length and width of the engine cover. For steel engine covers, the correlation index R of the fitting formula is 2 =0.824; for the aluminum engine cover, the correlation index R of the fitting formula 2 =0.829, indicating that the model can predict about 83% of the models on the market. Finally, based on the technical solution information of the vehicle to be developed (the technical solution information includes but is not limited to the material, the surface area of ​​the hood, etc.), the first weight assembly of the hood is calculated. For example, the hood to be developed uses a steel material solution and its surface area is 1.5m 2 , therefore, its weight is 9.3685×1.5-1.4355=12.617 (kg).

[0148] It should be noted that this embodiment obtains a more accurate weight of the first assembly parts through the correlation index. Before actual research and development, it is possible to more flexibly obtain a weight of the first assembly parts that is more in line with current needs based on the set expected index, thereby making the final vehicle weight obtained based on the weight of the first assembly parts and the weight of the second assembly parts more accurate and reasonable.

[0149] In one embodiment, in step S20, the weight of the second assembly parts of the second system assembly in the vehicle system assembly is searched by searching the database, wherein the database uses the part configuration, scheme, and assembly part weight of the system assembly as key fields of the database. Specifically, by analyzing the competing vehicles, the second assembly system is obtained, and the second assembly system is essentially a system assembly in which the weight of the assembly parts in the system assembly does not change, for example, a self-developed fixed-model engine, certain configuration products in electronic appliances, such as T-BOX, etc. Therefore, in this embodiment, on the one hand, the BOM (Bill of Materials) structure is built for the whole vehicle to obtain each assembly part in the second system assembly, and on the other hand, the weight of each assembly part in the second system assembly is directly queried based on the accumulated database, thereby obtaining the weight of the second assembly part.

[0150] For example, if the second system assembly to be calculated is a self-developed engine, the weight of the assembly parts of all self-developed engines in competing vehicles is first collected to form the following data table:

[0151] project Power model Variable box model Powertrain parts weight (kg) Project A 1.5TG 7WDCT 118.9 Project B 1.5TG CVT 112.35 Project C 1.5TG 7WDCT 120.8 Project D 1.5TG 7WDCT 120.8 Project E 2.0TGDI 8AT 159.8 Project F 2.0TGDI 8AT 158.8 Project G 2.0TM THS 141.9 Project H 1.5TG 7WDCT 121 I-Project 2.0ATK GMC 121.9 Project J 2.0TGDI 8AT 159.8 K Project 2.0TM THS 141.9 L Project 2.0TM GMC 141.9

[0152] Next, construct a data table of the weight of engine assembly parts as follows:

[0153]

[0154] Finally, the weight of the engine assembly is determined based on the engine parameters of the vehicle model to be developed. For example, if the engine parameters to be developed are the combination of 1.5TG+7WDCT, the weight M of the engine assembly is 120.8kg.

[0155] It should be noted that, since the vehicle system assemblies are classified in steps S10-S20, the weight of the second system assembly as an assembly part will not change with the change of parameters, therefore, this embodiment directly reads the corresponding assembly part weight or assembly part weight in the database for this part of the system assembly, that is, the second system assembly, to obtain the second assembly part weight, so as to reduce the time for weight calculation, speed up the research and development speed, and reduce the resource expenditure of research and development. In addition, by directly reading the weight that will not change, a more accurate and reasonable second assembly part weight can be better obtained, so that the final vehicle weight obtained based on the weight of the first assembly part and the weight of the second assembly part is also more accurate and reasonable.

[0156] It is worth noting that the vehicle weight acquisition method of the present invention confirms the weight and key parameter information of each system assembly part after disassembling the competing vehicle, and then analyzes it, and divides the vehicle system assembly into two categories (that is, the first assembly system and the second assembly system). One category obtains the weight of the first assembly parts through the weight prediction model, and the other category obtains the weight of the second assembly parts by directly calling the database according to the solution by establishing a database, thereby achieving fast and accurate vehicle weight. Compared with the prior art, the present invention not only accurately and quickly obtains the weight of each vehicle system assembly and the weight of the whole vehicle, but also obtains the weight of each system assembly through the predicted weight model and database accumulation at the same time, so there is no need to disassemble the competing vehicle before each research and development, which also solves the problem of too long time consumption, waste of resources, and strong hysteresis when confirming the weight of the whole vehicle in the prior art.

[0157] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0158] In one embodiment, a vehicle weight acquisition device is provided, and the vehicle weight acquisition device corresponds to the vehicle weight acquisition method in the above embodiment. Figure 3 As shown, the vehicle weight acquisition device includes a prediction module 10, a search module 20 and an acquisition module 30. The functional modules are described in detail as follows:

[0159] A prediction module 10, used to predict the weight of a first assembly part of a first system assembly in a vehicle system assembly by using a preset weight prediction model;

[0160] A search module 20, configured to search a database to find a weight of a second assembly part of a second system assembly in the vehicle system assembly, wherein the first system assembly and the second system assembly are obtained based on feature splitting of the vehicle system assembly;

[0161] The acquisition module 30 is used to acquire the weight of the entire vehicle according to the weight of the first assembly part and the weight of the second assembly part.

[0162] For the specific definition of the vehicle weight acquisition device, please refer to the definition of the vehicle weight acquisition method above, which will not be repeated here. Each module in the above-mentioned vehicle weight acquisition device can be implemented in whole or in part by software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0163] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used for all data generated in the above-mentioned vehicle weight acquisition method. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a vehicle weight acquisition method is implemented.

[0164] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the following steps are implemented:

[0165] Predicting the weight of a first assembly part of a first system assembly in a vehicle system assembly by using a preset weight prediction model;

[0166] Searching a database to find the weight of a second assembly part of a second system assembly in the vehicle system assembly, wherein the first system assembly and the second system assembly are obtained based on feature separation of the vehicle system assembly;

[0167] The weight of the entire vehicle is obtained according to the weight of the first assembly parts and the weight of the second assembly parts.

[0168] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0169] Predicting the weight of a first assembly part of a first system assembly in a vehicle system assembly by using a preset weight prediction model;

[0170] Searching a database to find the weight of a second assembly part of a second system assembly in the vehicle system assembly, wherein the first system assembly and the second system assembly are obtained based on feature separation of the vehicle system assembly;

[0171] The weight of the entire vehicle is obtained according to the weight of the first assembly parts and the weight of the second assembly parts.

[0172] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0173] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0174] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for obtaining vehicle weight, It is characterized in that The method comprises: Predicting the weight of a first assembly part of a first system assembly in a vehicle system assembly by using a preset weight prediction model; Searching a database to find the weight of a second assembly part of a second system assembly in the vehicle system assembly, wherein the first system assembly and the second system assembly are obtained based on feature separation of the vehicle system assembly; The weight of the entire vehicle is obtained according to the weight of the first assembly parts and the weight of the second assembly parts.

2. The vehicle weight acquisition method according to claim 1, It is characterized in that The first system assembly and the second system assembly are separated in the following manner based on the characteristics of the vehicle system assembly: Determining a reference system assembly corresponding to the vehicle system assembly, wherein the reference system assembly refers to a system assembly of the same type as the vehicle system assembly in a competing vehicle; Screening out a third system assembly having a changed weight from among the control system assemblies; The vehicle system assembly corresponding to the third system assembly is used as the first system assembly; Screening out a fourth system assembly whose weight does not change compared to the control system assembly; The vehicle system assembly corresponding to the fourth system assembly is used as the second system assembly.

3. The vehicle weight acquisition method according to claim 1, It is characterized in that The obtaining the vehicle weight according to the weight of the first assembly part and the weight of the second assembly part includes: Determine the initial weight of the vehicle; Adding the weight of the first assembly part and the weight of the second assembly part to obtain a predicted vehicle weight; If the initial weight of the whole vehicle is inconsistent with the predicted weight of the whole vehicle, the weight of the vehicle assembly parts is corrected by using the preset weight target and the lightweight rate of the reference system assembly corresponding to the vehicle system assembly to obtain the weight of the whole vehicle, and the weight of the vehicle assembly parts includes the weight of the first assembly parts and / or the weight of the second assembly parts.

4. The vehicle weight acquisition method according to claim 3, It is characterized in that The method of correcting the weight of vehicle assembly parts by presetting a weight target and a lightweight ratio of a reference system assembly corresponding to the vehicle system assembly includes: If the preset weight target is not equal to the predicted vehicle weight, calculating the average of the lightweight rates of the control system assemblies corresponding to the vehicle system assembly as the expected average; If the lightweight rate of the vehicle system assembly is equal to the expected average value, the weight of the vehicle assembly parts is corrected by the expected average value.

5. The vehicle weight acquisition method according to claim 4, It is characterized in that The step of correcting the weight of the vehicle assembly parts by using the expected mean value includes: Calculating an expected difference between the expected weight of the assembly parts and the weight of the vehicle assembly parts by using the expected mean value; The vehicle assembly part weight is corrected according to the expected difference.

6. The vehicle weight acquisition method according to claim 4, It is characterized in that After calculating the average value of the lightweight ratio of the control system assembly corresponding to the vehicle system assembly as the expected average value, the method further includes: If the lightweight rate of the vehicle system assembly is not equal to the expected mean, obtaining an expected standard mean through the expected mean and the standard deviation of the expected mean; If the lightweight rate of the vehicle system assembly is equal to the expected standard mean, the weight of the vehicle assembly parts is corrected by the expected standard mean.

7. The vehicle weight acquisition method according to claim 6, It is characterized in that The step of correcting the weight of the vehicle assembly parts by using the expected standard mean value includes: Calculating an expected standard deviation between the expected standard weight and the weight of the vehicle assembly part by using the expected standard mean; The vehicle assembly part weight is corrected according to the expected standard deviation value.

8. The method for obtaining the vehicle weight according to any one of claims 1 to 7, It is characterized in that The method of predicting the weight of a first assembly part of a first system assembly in a vehicle system assembly by using a preset weight prediction model includes: Predicting the initial assembly parts weight of the first system assembly in the vehicle system assembly by using the weight prediction model; Obtaining a correlation index of the weight prediction model by using a weight mean of a control system assembly corresponding to the vehicle system assembly; If the correlation index exceeds the expected index, the initial assembly part weight is used as the first assembly part weight.

9. A vehicle weight acquisition device, It is characterized in that include: A prediction module, used to predict the weight of a first assembly part of a first system assembly in the vehicle system assembly by using a preset weight prediction model; A search module, configured to search a database to find a weight of a second assembly part of a second system assembly in the vehicle system assembly, wherein the first system assembly and the second system assembly are obtained based on feature separation of the vehicle system assembly; An acquisition module is used to acquire the weight of the entire vehicle according to the weight of the first assembly part and the weight of the second assembly part.

10. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, It is characterized in that When the processor executes the computer program, the steps of the vehicle weight acquisition method as described in any one of claims 1 to 8 are implemented.

11. A computer-readable storage medium storing a computer program. It is characterized in that When the computer program is executed by a processor, the steps of the vehicle weight acquisition method as described in any one of claims 1 to 8 are implemented.

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