A vehicle lightweight level determination method, device, equipment, medium and product

Abstract

This invention discloses a method, apparatus, device, medium, and product for determining the overall vehicle lightweighting level. The method includes: acquiring a target vehicle model and identifying multiple competing vehicle models corresponding to the target model; analyzing the equivalent weight of the multiple competing vehicle models relative to the boundary of the target vehicle model; wherein the equivalent weight includes weight differences caused by factors such as battery, motor, size, configuration, performance, materials, and overall vehicle weight; and determining the overall vehicle lightweighting level of the multiple competing vehicle models based on the equivalent weight corresponding to each competing vehicle model. This method considers the influence of factors such as battery, motor, size, configuration, performance, materials, and overall vehicle weight on vehicle weight, and derives the equivalent weight of competing vehicle models based on the boundary of the target vehicle model, enabling a more comprehensive and objective determination of the overall vehicle lightweighting level.

Description

TECHNICAL FIELD

[0001] The embodiment of the application relates to the technical field of electric vehicles, and particularly relates to a vehicle lightweight level determination method, device, equipment, medium and product. BACKGROUND

[0002] Automobile lightweight refers to reducing the curb weight of an automobile as much as possible under the premise of ensuring the strength and safety performance of the automobile, thereby improving the power performance of the automobile. How to determine the lightweight level of a new energy automobile has become a problem to be solved in lightweight engineering development.

[0003] The method of the prior art determines the lightweight coefficient of an electric vehicle based on the curb weight, battery capacity, maximum endurance mileage, footprint area and total motor power of the electric vehicle.

[0004] However, with the rapid development of electric vehicles, the differences in vehicle configuration, battery, material, motor power and vehicle weight are becoming more and more obvious. However, the influence of factors such as vehicle configuration, battery and material is not considered in the prior art, and the lightweight level of the vehicle cannot be comprehensively and truly determined. SUMMARY

[0005] The application provides a vehicle lightweight level determination method, device, equipment, medium and product to solve the problem that the influence factors of the lightweight coefficient of an electric vehicle are not considered comprehensively in the prior art, and the lightweight level of the vehicle cannot be comprehensively and truly determined.

[0006] According to an aspect of the application, a vehicle lightweight level determination method is provided, comprising:

[0007] acquiring a target vehicle model and determining a plurality of competitive vehicle models corresponding to the target vehicle model;

[0008] analyzing equivalent weights of the plurality of competitive vehicle models under the boundary of the target vehicle model; wherein the equivalent weights include weight differences caused by factors such as battery, motor, size, configuration, performance, material and vehicle weight;

[0009] determining the vehicle lightweight level of the plurality of competitive vehicle models according to the equivalent weights corresponding to each competitive vehicle model.

[0010] According to another aspect of the application, a vehicle lightweight level determination device is provided, comprising:

[0011] a determination module configured to acquire a target vehicle model and determine a plurality of competitive vehicle models corresponding to the target vehicle model;

[0012] An analysis module is configured to analyze equivalent weights of the plurality of competitive vehicle models under the equivalent boundary of the target vehicle model, wherein the equivalent weights include weight differences caused by batteries, electric machines, sizes, configurations, performances, materials, and whole vehicle weights.

[0013] A determination module is configured to determine whole vehicle lightweight levels of the plurality of competitive vehicle models according to the equivalent weights corresponding to each of the competitive vehicle models.

[0014] According to another aspect of the present application, an electronic device is provided, which comprises:

[0015] at least one processor;

[0016] and a memory connected to the at least one processor in communication;

[0017] wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the whole vehicle lightweight level determination method according to any one of the embodiments of the present application.

[0018] According to another aspect of the present application, a computer readable storage medium is provided, which stores computer instructions for enabling a processor to implement the whole vehicle lightweight level determination method according to any one of the embodiments of the present application when executed by the processor.

[0019] According to another aspect of the present application, a computer program product is provided, which implements the whole vehicle lightweight level determination method according to any one of the embodiments of the present application when executed by a processor.

[0020] The technical solution of the embodiments of the present application determines the equivalent weights of the competitive vehicle models by considering the influences of batteries, electric machines, sizes, configurations, performances, materials, and whole vehicle weights on vehicle weights, solves the problem that the prior art cannot comprehensively and truly determine the whole vehicle lightweight level, and achieves the beneficial effect of more comprehensively and objectively determining the whole vehicle lightweight level.

[0021] It should be understood that the content described in this part is not intended to identify key or important features of the embodiments of the present application, nor is it used to limit the scope of the present application. Other features of the present application will become apparent through the following description. BRIEF DESCRIPTION OF DRAWINGS

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart illustrating a method for determining the lightweight level of a vehicle according to Embodiment 1 of the present invention.

[0024] Figure 2 This is a schematic diagram showing the detailed parameters of the vehicle model provided in Embodiment 1 of the present invention;

[0025] Figure 3 This is a schematic diagram of the equivalent weight of a competing vehicle provided in Embodiment 1 of the present invention;

[0026] Figure 4 This is a scatter plot of battery charge versus battery weight provided in an embodiment of the present invention.

[0027] Figure 5 A scatter plot of motor power versus motor weight provided in an embodiment of the present invention;

[0028] Figure 6a A scatter plot of front axle load versus front brake disc weight provided in an embodiment of the present invention;

[0029] Figure 6b A scatter plot of rear axle load versus rear brake disc weight provided in one embodiment of the present invention;

[0030] Figure 7 This is a flowchart illustrating a method for determining the lightweight level of a vehicle according to Embodiment 2 of the present invention.

[0031] Figure 8 This is a schematic diagram of a vehicle lightweighting level determination device provided in Embodiment 3 of the present invention;

[0032] Figure 9 This is a schematic diagram of the electronic device used in a method for determining the lightweight level of a vehicle according to an embodiment of the present invention. Detailed Implementation

[0033] To enable those skilled in the art to better understand the present invention, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention. It should be understood that the various steps described in the method embodiments of the present invention can be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0034] The term "comprising" and its variations as used herein are open-ended inclusions, meaning "including but not limited to". The term "based on" means "at least partially based on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Definitions of other terms will be given in the description below.

[0035] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention 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 the invention 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 a 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.

[0036] It should be noted that the terms "a" and "a plurality of" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0037] The names of the messages or information exchanged between the multiple devices in the embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0038] Example 1

[0039] Figure 1This is a flowchart illustrating a method for determining the lightweight level of a vehicle according to Embodiment 1 of the present invention. This method is applicable to determining the lightweight level of new energy vehicles. The method can be executed by a vehicle lightweight level determination device, which can be implemented by software and / or hardware and is generally integrated into an electronic device. In this embodiment, the electronic device includes, but is not limited to, a computer device.

[0040] like Figure 1 As shown, the method for determining the lightweight level of a vehicle provided in Embodiment 1 of the present invention includes the following steps:

[0041] S110. Obtain the target vehicle model and identify multiple competing vehicle models corresponding to the target vehicle model.

[0042] The target vehicle is a newly developed new energy vehicle; the competing vehicle can be a new energy vehicle with a similar size and form to the target vehicle.

[0043] In this embodiment, new energy vehicles with similar dimensions to the target vehicle can be searched from databases or websites as competing models. For example, if the target vehicle is an SUV, then the competing models are also SUVs. There is no specific limit to the number of competing models; it can be determined based on the search results. If a large number of competing models are found, 8 to 10 can be selected; if a smaller number are found, 3 to 5 can be selected.

[0044] S120. Analyze the equivalent weight of the multiple competing models to the target model boundary.

[0045] The equivalent weight includes the weight differences caused by factors such as battery, motor, size, configuration, performance, materials, and overall vehicle weight.

[0046] In this embodiment, after obtaining the target vehicle model, detailed parameters of the target vehicle model can be obtained from a database or website, including parameters such as battery, motor, vehicle size, vehicle configuration, materials, performance, and vehicle weight; after identifying competing vehicle models, detailed parameters of competing vehicle models can also be obtained from a database or website.

[0047] Figure 2 This is a schematic diagram of detailed vehicle parameters provided in Embodiment 1 of the present invention, as shown below. Figure 2 As shown, the new model is the target model, and models 1 to 8 are competing models. Figure 2It showcases multiple parameters of the target vehicle and competing models, including battery, motor, dimensions, configuration, performance, materials, and overall vehicle weight. Battery parameters include battery capacity, battery type, and battery weight; motor parameters include front and rear motor power; dimensions include vehicle length, width, height, and wheelbase; configurations include seat leg rests, refrigerator, and second-row screens; performance refers to the vehicle's safety compliance level; and materials include the proportion of aluminum in the body-in-white and the aluminum four doors.

[0048] In this embodiment, based on the target vehicle model, the equivalent weight of each competing vehicle model under the boundary of the target vehicle model can be comprehensively analyzed from various factors such as battery, motor, size, configuration, performance, materials and overall vehicle weight.

[0049] Furthermore, the equivalent weight of the multiple competing models at the target model boundary was analyzed, including:

[0050] For each competitor model, the sum of the weight differences between the total weight of the competitor model and the weights corresponding to each equivalent factor is taken as the equivalent weight of the competitor model under the boundary of the target model.

[0051] The equivalent factors include the differences in battery weight, motor power weight, size weight, configuration weight, performance weight, material weight, and overall vehicle weight between the competing vehicle and the target vehicle.

[0052] The corresponding calculation formula is as follows:

[0053]

[0054] Where, m 等效 Here, m represents the equivalent weight, and m represents the vehicle weight of the competing model. This represents the sum of weight differences caused by multiple factors, where n represents the number of factors. In this embodiment, n is set to 7.

[0055] The equivalent weight of each competing model can be calculated using the formula above.

[0056] S130. Determine the overall lightweighting level of the multiple competing models based on the equivalent weight of each competing model.

[0057] In this embodiment, the standard for judging the overall vehicle lightweighting level is: the lower the equivalent weight, the better the overall vehicle lightweighting level.

[0058] Figure 3 This is a schematic diagram of the equivalent weight of a competing vehicle provided in Embodiment 1 of the present invention, as shown below. Figure 3 As shown, model 1 has the lightest equivalent weight and the best overall vehicle lightweighting level.

[0059] This invention provides a method for determining the overall vehicle lightweighting level. First, a target vehicle model is obtained, and multiple competing vehicle models corresponding to the target model are identified. Then, the equivalent weight of the multiple competing vehicle models relative to the boundary of the target vehicle model is analyzed. This equivalent weight includes weight differences caused by factors such as battery, motor, size, configuration, performance, materials, and overall vehicle weight. Finally, the overall vehicle lightweighting level of the multiple competing vehicle models is determined based on their equivalent weights. This method introduces the equivalent weight of competing vehicle models to determine the overall vehicle lightweighting level, considering the impact of factors such as battery, motor, size, configuration, performance, materials, and overall vehicle weight on the overall vehicle weight, thus enabling a more comprehensive and objective determination of the overall vehicle lightweighting level.

[0060] Based on the above embodiments, modified embodiments of the above embodiments are proposed. It should be noted that, in order to keep the description brief, only the differences from the above embodiments are described in the modified embodiments.

[0061] Furthermore, the determination of battery weight differences includes:

[0062] Generate the first regression formula corresponding to battery capacity and battery weight;

[0063] After confirming that the first regression formula is usable, the difference in battery capacity between the target model and the competitor model is substituted into the first regression formula as an independent variable to obtain the difference in battery weight between the competitor model and the target model.

[0064] In this embodiment, by finding the correlation between battery capacity and battery weight, a regression formula corresponding to battery capacity and battery weight can be generated as the first regression formula. There are no specific limitations on the method of generating the first regression formula. For example, battery pack energy density analysis can be performed to draw a scatter plot of battery capacity and battery weight for competing models. Figure 4 This is a scatter plot of battery charge versus battery weight provided in an embodiment of the present invention, as shown below. Figure 4 As shown, the horizontal axis represents battery capacity in kWh; the vertical axis represents battery weight in kg. A trend line can be generated based on the scatter plot of battery capacity and battery weight of competing models. The first regression formula corresponding to battery capacity and battery weight can be determined based on the points on the trend line.

[0065] Among them, the linear regression line corresponding to the first regression formula represents the average battery weight of all competing vehicles. The weight below the average line indicates that the lightweight level is better than the average level and the energy density of the battery pack is higher.

[0066] In this embodiment, based on the correlation coefficient R of the trend line 2 To determine whether the generated first regression formula is usable, if R... 2If the value is greater than 0.75, it is considered that there is a strong linear relationship between the independent and dependent variables, and the first regression formula can be used.

[0067] In this embodiment, it is necessary to calculate the battery weight difference between all competing models and the target model. The calculation method is the same. Taking one competing model as an example, the battery capacity of the competing model is obtained from its detailed parameters, and the battery capacity of the target model is obtained from its detailed parameters. The difference between the two battery capacities is used as the dependent variable X and substituted into the first regression formula to calculate the battery weight difference Y between the competing model and the target model.

[0068] Furthermore, the determination of the motor power-weight difference includes:

[0069] Generate a second regression formula corresponding to motor power and motor weight;

[0070] After confirming that the second regression formula is usable, the difference in motor power between the target model and the competitor model is substituted into the second regression formula as an independent variable to obtain the difference in motor weight between the competitor model and the target model.

[0071] Among them, the difference in motor weight can be understood as the difference in vehicle weight caused by different motor power. Since the target model and the competing models use different motor power, there will be a difference in motor power weight.

[0072] In this embodiment, by finding the correlation between motor power and motor weight, a regression formula corresponding to motor power and motor weight can be generated as a second regression formula. There are no specific limitations on the method for generating the second regression formula. For example, motor power density analysis is performed, and scatter plots of motor power and motor weight for multiple vehicle models are drawn. Figure 5 This is a scatter plot of motor power versus motor weight provided in an embodiment of the present invention, as shown below. Figure 5 As shown, the horizontal axis represents motor power in kW, and the vertical axis represents motor weight in kg. A trend line can be generated from the scatter plot, and the second regression formula corresponding to motor power and motor weight can be determined based on the points on the trend line.

[0073] Among them, the correlation coefficient R of the trend line can be used as a basis. 2 To determine whether the generated second regression formula is usable, if R... 2 If the value is greater than 0.75, it is considered that there is a strong linear relationship between the independent and dependent variables, and the second regression formula can be used.

[0074] In this embodiment, it is necessary to calculate the difference in motor power and weight between all competing models and the target model. The calculation method is the same. Taking one competing model as an example: obtain the motor power of the competing model from its detailed parameters, obtain the motor power of the target model from its detailed parameters, and substitute the difference between the two motor powers as the dependent variable X into the second regression formula to calculate the difference in motor weight Y between the competing model and the target model.

[0075] Further determination of dimensional and weight variations includes:

[0076] The first dimensional weight difference is obtained by determining the weight difference between the target model and the competing model corresponding to the overall vehicle length;

[0077] The second dimensional weight difference is obtained by determining the weight difference between the target vehicle model and the competing vehicle model corresponding to the overall vehicle width;

[0078] The third dimensional weight difference is obtained by determining the weight difference between the target model and the competing model corresponding to the overall vehicle height;

[0079] The sum of the first size-weight difference, the second size-weight difference, and the third size-weight difference is used to obtain the size-weight difference between the target vehicle and the competing vehicle.

[0080] Among them, the size-weight difference can be understood as the difference in the overall vehicle weight caused by the different vehicle sizes; the size-weight difference can be calculated from multiple aspects, such as the size-weight difference between the target model and the competitor's model from the three aspects of vehicle length, vehicle width and vehicle height.

[0081] The first dimension weight difference refers to the weight difference caused by the difference in vehicle length; the second dimension weight difference refers to the weight difference caused by the difference in vehicle width; and the third dimension weight difference refers to the weight difference caused by the difference in vehicle height.

[0082] In this embodiment, there is no specific limitation on the method for calculating the weight difference of the first dimension, the weight difference of the second dimension, and the weight difference of the third dimension; any feasible method can be used for calculation.

[0083] One feasible method for calculating the weight difference of the first dimension is as follows: Model the target vehicle model to obtain a vehicle model; slice the length data of the vehicle model using software to obtain the weight m corresponding to multiple preset lengths. 长 ; Calculate multiple m 长 The average weight Δm corresponding to the preset length is obtained from the average value. 长 Calculate the length difference between the target vehicle model and a competing vehicle model, and calculate the relationship between the length difference and a preset multiple; calculate the multiple and Δm. 长The product of these values ​​yields the first dimensional weight difference between the target model and its competitor. Understandably, for ease of calculation, the preset length can be an integer, such as 10mm. If the length difference between the target model and a competitor is 50mm, then the first dimensional weight difference is 5*Δm. 长 .

[0084] The weight difference for the second and third dimensions can be calculated using the methods described above, and will not be elaborated upon here.

[0085] The experiment showed that if the length difference between the target model and the competitor model is 10mm, the corresponding weight difference ranges from 2kg to 4kg; if the width difference between the target model and the competitor model is 10mm, the corresponding weight difference ranges from 4kg to 6kg; and if the height difference between the target model and the competitor model is 10mm, the corresponding weight difference ranges from 2kg to 4kg.

[0086] In this embodiment, the weight differences caused by differences in vehicle length, width, and height are taken into account; the sum of the weight differences of the three factors is taken as the sum of the size and weight differences between the target model and the competing models.

[0087] Furthermore, the determination of the weight difference includes:

[0088] The differences in vehicle configuration are determined by comparing the target model with the competing models;

[0089] Based on the aforementioned differences in configuration, the weight difference between the target vehicle and the competing vehicle is determined by querying the weight corresponding to each configuration in the configuration table.

[0090] In this embodiment, since new energy vehicles have increasingly rich configurations, different configurations have a significant impact on the overall vehicle weight. Therefore, it is necessary to consider the impact of configuration on the overall vehicle weight. The weight difference due to different configurations can be understood as the difference in overall vehicle weight caused by different configurations.

[0091] The configuration information of the target model and competing models can be obtained from the parameter table. Based on the configuration information, the differences between the two models in terms of configuration can be clearly understood, such as the difference in the number of in-vehicle screens, the difference in tire specifications, and the difference in whether there is an in-vehicle refrigerator. The configuration table records the weight corresponding to different configurations. For example, if the difference between the target model and the competing model in terms of in-vehicle configuration is an in-vehicle refrigerator, then the weight of an in-vehicle refrigerator is taken as the configuration weight difference between the target model and the competing model.

[0092] Furthermore, the determination of performance-weight differences includes:

[0093] The differences in vehicle safety levels between the target vehicle model and the competing vehicle model include differences in vehicle frontal collision speed and differences in vehicle obstacle weight.

[0094] The percentage increase in energy during the first frontal collision is determined based on the difference in the vehicle's frontal collision speed.

[0095] The first percentage increase in thickness of the key force-bearing structure in the frontal collision is determined based on the percentage increase in the first frontal collision energy.

[0096] The percentage increase in the second frontal collision energy is determined based on the difference in the weight of the barrier under the vehicle's operating conditions.

[0097] The second percentage increase in thickness of the force-bearing structure to resist the second increase in frontal collision energy is determined based on the second percentage increase in frontal collision energy.

[0098] The weights corresponding to the first thickness percentage and the second thickness percentage are used as the performance weight difference between the target vehicle and the competing vehicle.

[0099] Among these factors, vehicle safety is of paramount importance, and therefore vehicle safety levels are constantly being upgraded. It is necessary to consider the impact of vehicle safety levels on overall vehicle weight. Performance-weight differences can be understood as the differences in overall vehicle weight caused by different safety levels.

[0100] In this embodiment, the upgrade of the vehicle's safety level will lead to an increase in the vehicle's frontal collision speed. The increase in the vehicle's frontal collision speed will result in an increase in the frontal collision energy. To resist the increase in frontal collision energy, it is necessary to increase the thickness of the key frontal collision load-bearing structure. The key frontal collision load-bearing structure may include an energy-absorbing box, longitudinal beams, and a lower torsion box.

[0101] For example, the safety level of the competing vehicle corresponds to a frontal collision speed of 50 kph, while the safety level of the target vehicle corresponds to a frontal collision speed of 56 kph. According to the kinetic energy formula... The calculation shows that the frontal collision energy of the target model is 25% higher than that of the competing model. To resist the increase in frontal collision energy, the key frontal collision stress-bearing structure of the competing model needs to be thickened by 25%. The weight increase corresponding to the 25% thickening of the key frontal collision stress-bearing structure can be regarded as the performance weight difference.

[0102] In this embodiment, the upgrade of the vehicle's safety level will lead to an increase in the weight of the vehicle's working barrier. The increase in the weight of the vehicle's working barrier will lead to an increase in frontal collision energy. In order to resist the increase in frontal collision energy, it is necessary to increase the thickness of the load-bearing structure.

[0103] For example, the vehicle barrier weight corresponding to the safety level of the competing model is 1500kg, while the vehicle barrier weight corresponding to the safety level of the target model is 1650kg. According to the kinetic energy formula... The calculation shows that the frontal collision energy of the target model is 10% higher than that of the competing model. To counteract the increased frontal collision energy, the thickness of the B-pillar of the competing model needs to be increased by 10%. The weight increase resulting from the 10% increase in the thickness of the B-pillar can be considered as the performance-weight difference.

[0104] Furthermore, the determination of material weight variation includes:

[0105] Obtain the first material used in the overall structure of the target vehicle model and the second material used in the overall structure of the competitor vehicle model;

[0106] Based on the first material and the second material, the material weight difference between the target vehicle model and the competing vehicle model is determined using the conversion formula for the corresponding weight of the materials.

[0107] In this embodiment, considering the impact of the materials of the vehicle structure on the overall vehicle weight, the main factors include the proportion of aluminum alloy in the body, and the impact of the materials used in the four doors, front and rear hoods, and chassis on the overall vehicle weight.

[0108] Specifically, the materials used in the overall structure of the target model can be obtained from the vehicle's detailed parameter table as the first material, and the materials used in the overall structure of the competitor model can be obtained as the second material. The weight difference between the target model and the competitor model can be calculated based on the material differences between the two models. Specifically, the conversion formula for the corresponding weight of the materials can be used for calculation.

[0109] Furthermore, determining the vehicle weight difference includes: determining the vehicle weight difference between the target model and the competing model; and using the increase in chassis and body-in-white weight caused by the vehicle weight difference as the vehicle weight difference between the target model and the competing model.

[0110] In this embodiment, considering the impact of vehicle weight on the weight of the chassis and body-in-white, a heavier vehicle weight will lead to an increase in the weight of the chassis load-bearing components and the body-in-white to support the overall vehicle weight.

[0111] The vehicle weights of the target model and competing models can be obtained from the vehicle's detailed parameter table or through other means; no specific restrictions are placed here. Vehicle weight can include the weight of the front axle load and the rear axle load. The increase in chassis weight is mainly reflected in the increased weight of chassis load-bearing components, which can include front and rear brake discs, front and rear calipers, and front and rear subframes, etc.

[0112] In this embodiment, the difference in vehicle weight can be calculated based on a regression analysis formula relating vehicle weight and the weight of chassis load-bearing components. For example, Figure 6a This is a scatter plot of front axle load versus front brake disc weight provided in an embodiment of the present invention. Figure 6a The corresponding formula for the weight regression of the front brake disc is generated. Figure 6b A scatter plot of rear axle load versus rear brake disc weight provided in an embodiment of the present invention, based on... Figure 6b The corresponding formula for the weight regression of the brake disc is generated; similarly, the formula for the weight regression of each load-bearing component in the chassis can be generated. Based on the formula for the weight regression of each load-bearing component, the chassis weight corresponding to the vehicle weight of the target model and the chassis weight corresponding to the vehicle weight of the competitor model can be calculated. The difference between the two chassis weights is taken as the increase in chassis weight. The analysis shows that for every 100kg increase in vehicle weight, the chassis weight increases by 6-10kg.

[0113] Among them, the body-in-white refers to the body that has been welded but not yet painted. Based on the impact of the body-in-white weight on vehicle safety, the body-in-white weight corresponding to the vehicle weight of the target model and the body-in-white weight corresponding to the vehicle weight of the competitor model can be calculated according to the kinetic energy formula. The difference between the two body-in-white weights is taken as the increase in body-in-white weight. The analysis shows that for every 100kg increase in vehicle weight, the body-in-white weight increases by 6-8kg.

[0114] Example 2

[0115] Figure 7 This is a flowchart illustrating a method for determining the lightweight level of a vehicle according to Embodiment 2 of the present invention. Embodiment 2 is an optimization based on the above embodiments. For details not covered in this embodiment, please refer to the above embodiments.

[0116] like Figure 7 As shown in Embodiment 2 of the present invention, a method for determining the lightweight level of a vehicle includes the following steps:

[0117] S210. Obtain the target vehicle model and identify multiple competing vehicle models corresponding to the target vehicle model.

[0118] S220. Analyze the equivalent weight of the multiple competing models at the boundary of the target vehicle.

[0119] The equivalent weight includes the weight differences caused by factors such as battery, motor, size, configuration, performance, materials, and overall vehicle weight.

[0120] S230. Determine the overall lightweighting level of the multiple competing models based on the equivalent weight of each competing model.

[0121] S240. Based on the equivalent weight of the competitor's model with the best lightweight level, complete the target vehicle weight setting for the target model.

[0122] In this embodiment, based on the equivalent weight of competing models with the best lightweighting level, and considering an annual reduction of 1% to 2% in lightweighting efficiency, the target vehicle weight is set. The calculation formula is as follows:

[0123] m 目标 =m 等效1 -(1%~2%)*m 等效1

[0124] Where, m 目标 This indicates the target vehicle weight setting for the target model, in meters. 等效1 This represents the equivalent weight of the competitor's model with the best level of lightweighting.

[0125] The second embodiment of the present invention provides a method for determining the overall vehicle lightweighting level. This method can not only comprehensively and objectively determine the overall vehicle lightweighting level, but also guide the setting of the target vehicle weight.

[0126] Example 3

[0127] Figure 8 This is a schematic diagram of a vehicle lightweighting level determination device provided in Embodiment 3 of the present invention. The device is applicable to determining the lightweighting level of new energy vehicles. The device can be implemented by software and / or hardware and is generally integrated into an electronic device.

[0128] like Figure 8 As shown, the device includes: a determination module 110, an analysis module 120, and a judgment module 130.

[0129] The determination module 110 is used to acquire the target vehicle model and determine multiple competing vehicle models corresponding to the target vehicle model;

[0130] The analysis module 120 is used to analyze the equivalent weight of the multiple competing models to the target vehicle boundary; wherein, the equivalent weight includes the weight differences caused by factors such as battery, motor, size, configuration, performance, materials and overall vehicle weight;

[0131] The determination module 130 is used to determine the overall vehicle lightweighting level of the multiple competing models based on the equivalent weight corresponding to each competing model.

[0132] In this embodiment, the device first obtains the target vehicle model through the determination module 110 and identifies multiple competing vehicle models corresponding to the target vehicle model; then, the analysis module 120 analyzes the equivalent weight of the multiple competing vehicle models under the boundary of the target vehicle model; wherein, the equivalent weight includes the weight differences caused by factors such as battery, motor, size, configuration, performance, materials and overall vehicle weight; finally, the judgment module 130 judges the overall vehicle lightweighting level of the multiple competing vehicle models based on the equivalent weight corresponding to each competing vehicle model.

[0133] This embodiment provides a vehicle lightweighting level determination device, which can more comprehensively and objectively determine the vehicle lightweighting level.

[0134] Furthermore, the analysis module 120 is specifically used to: for each competitor model, take the sum of the weight differences between the overall weight of the competitor model and the weight differences corresponding to various equivalent factors as the equivalent weight of the competitor model under the boundary of the target model; wherein, the various equivalent factors include the differences in battery weight, motor power weight, size weight, configuration weight, performance weight, material weight, and overall vehicle weight between the competitor model and the target model.

[0135] Based on the above optimizations, the analysis module 120 includes a battery weight difference determination unit, a motor power weight difference determination unit, a size weight difference determination unit, a configuration weight difference determination unit, a performance weight difference determination unit, a material weight difference determination unit, and a vehicle weight difference determination unit.

[0136] A battery weight difference determination unit is used to generate a first regression formula corresponding to battery capacity and battery weight; after confirming that the first regression formula is available, the battery capacity difference between the target model and the competitor model is substituted into the first regression formula as an independent variable to obtain the battery weight difference between the competitor model and the target model.

[0137] The motor power-weight difference determination unit is used to generate a regression formula corresponding to motor power and motor weight; after confirming that the regression formula is usable, the difference in motor power between the target model and the competitor model is substituted into the regression formula as the dependent variable to obtain the difference in motor weight between the competitor model and the target model;

[0138] The size and weight difference determination unit is used to calculate the weight difference between the target model and the competitor model corresponding to the overall vehicle length to obtain the first size and weight difference; calculate the weight difference between the target model and the competitor model corresponding to the overall vehicle width to obtain the second size and weight difference; calculate the weight difference between the target model and the competitor model corresponding to the overall vehicle height to obtain the third size and weight difference; and calculate the sum of the first size and weight difference, the second size and weight difference, and the third size and weight difference to obtain the size and weight difference between the target model and the competitor model.

[0139] A weight difference determination unit is configured to compare the differences in vehicle configuration between the target model and the competing model to determine the difference configuration; the difference configuration is then used to determine the weight difference between the target model and the competing model by querying the weight corresponding to each configuration in the configuration table;

[0140] A performance-weight difference determination unit is used to compare the differences in vehicle safety levels between a target vehicle model and competing models. These differences correspond to differences in vehicle frontal collision speed and vehicle barrier weight. The unit calculates a first frontal collision energy increase percentage based on the difference in vehicle frontal collision speed using a kinetic energy formula. Based on this percentage, it determines a first percentage increase in thickness of the key frontal collision load-bearing structure to resist the increased frontal collision energy. Similarly, it calculates a second percentage increase in frontal collision energy based on the difference in vehicle barrier weight using a kinetic energy formula. Based on this second percentage increase, it determines a second percentage increase in thickness of the load-bearing structure to resist the increased second frontal collision energy. The weights corresponding to the first and second thickness percentages are used as the performance-weight difference between the target vehicle model and the competing models.

[0141] The material weight difference determination unit is used to obtain the materials used in the overall structure of the target vehicle model and the materials used in the overall structure of the competing vehicle model; and to calculate the material weight difference between the target vehicle model and the competing vehicle model according to the conversion formula of the corresponding material weight.

[0142] The vehicle weight difference determination unit is used to determine the weight difference between the target model and the competing model; the increase in weight of the chassis and body-in-white caused by the weight difference is taken as the vehicle weight difference between the target model and the competing model.

[0143] Furthermore, the device also includes a setting module for setting the target vehicle weight of the target model based on the equivalent weight of the competitor's model with the best lightweighting level.

[0144] The above-mentioned vehicle lightweighting level determination device can execute the vehicle lightweighting level determination method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0145] Example 4

[0146] Figure 9A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0147] like Figure 9 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0148] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0149] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the method for determining the level of vehicle lightweighting.

[0150] In some embodiments, the vehicle lightweighting level determination method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the vehicle lightweighting level determination method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the vehicle lightweighting level determination method by any other suitable means (e.g., by means of firmware).

[0151] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0152] In some embodiments, the method for determining the overall vehicle lightweighting level can be implemented as a computer program, which is implicitly included in a computer program product. When executed by a processor, the computer program implements the method for determining the overall vehicle lightweighting level of the present invention. The computer program product can be understood as a software product that primarily implements its solution through a computer program. The computer program used to implement the method of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer program causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer program can be executed entirely on a machine, partially on a machine, partially on a remote machine as a standalone software package, or entirely on a remote machine or server.

[0153] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0154] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0155] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0156] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0157] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0158] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for determining the overall vehicle lightweighting level, characterized in that, The method includes: Obtain the target vehicle model and identify multiple competing models corresponding to the target vehicle model; The equivalent weight of the multiple competing models was analyzed and determined when it was compared to the target model's boundary. The equivalent weight included the weight differences caused by factors such as battery, motor, size, configuration, performance, materials, and overall vehicle weight. The overall lightweighting level of the multiple competing models is determined based on the equivalent weight of each competing model.

2. The method according to claim 1, characterized in that, The analysis yielded the equivalent weight of the multiple competing vehicle models at the target vehicle boundary, including: For each competitor model, the sum of the weight differences between the total weight of the competitor model and the weights corresponding to each equivalent factor is taken as the equivalent weight of the competitor model under the boundary of the target model. The equivalent factors include the differences in battery weight, motor power weight, size weight, configuration weight, performance weight, material weight, and overall vehicle weight between the competing vehicle and the target vehicle.

3. The method according to claim 2, characterized in that, The determination of the battery weight difference includes: Generate the first regression formula corresponding to battery capacity and battery weight; After confirming that the first regression formula is usable, the difference in battery capacity between the target model and the competitor model is substituted into the first regression formula as an independent variable to obtain the difference in battery weight between the competitor model and the target model.

4. The method according to claim 2, characterized in that, The determination of the difference in motor power weight includes: Generate a second regression formula corresponding to motor power and motor weight; After confirming that the second regression formula is usable, the difference in motor power between the target model and the competitor model is substituted into the first regression formula as an independent variable to obtain the difference in motor weight between the competitor model and the target model.

5. The method according to claim 2, characterized in that, The determination of the size and weight differences includes: The first dimensional weight difference is obtained by determining the weight difference between the target model and the competing model corresponding to the overall vehicle length; The second dimensional weight difference is obtained by determining the weight difference between the target vehicle model and the competing vehicle model corresponding to the overall vehicle width; The third dimensional weight difference is obtained by determining the weight difference between the target model and the competing model corresponding to the overall vehicle height; The sum of the first size-weight difference, the second size-weight difference, and the third size-weight difference is used to obtain the size-weight difference between the target vehicle and the competing vehicle.

6. The method according to claim 2, characterized in that, The calculation of the configuration weight difference includes: The differences in vehicle configuration are determined by comparing the target model with the competing models; Based on the aforementioned differences in configuration, the weight difference between the target vehicle and the competing vehicle is determined by querying the weight corresponding to each configuration in the configuration table.

7. The method according to claim 2, characterized in that, The determination of the performance weight difference includes: The differences in vehicle safety levels between the target vehicle model and the competing vehicle model include differences in vehicle frontal collision speed and differences in vehicle obstacle weight. The percentage increase in energy during the first frontal collision is determined based on the difference in the vehicle's frontal collision speed. The first percentage increase in thickness of the key force-bearing structure in the frontal collision is determined based on the percentage increase in the first frontal collision energy. The percentage increase in the second frontal collision energy is determined based on the difference in the weight of the barrier under the vehicle's operating conditions. The second percentage increase in thickness of the force-bearing structure to resist the second increase in frontal collision energy is determined based on the second percentage increase in frontal collision energy. The weights corresponding to the first thickness percentage and the second thickness percentage are used as the performance weight difference between the target vehicle and the competing vehicle.

8. The method according to claim 2, characterized in that, The determination of the material weight difference includes: Obtain the first material used in the overall structure of the target vehicle model and the second material used in the overall structure of the competitor vehicle model; Based on the first material and the second material, the material weight difference between the target vehicle model and the competing vehicle model is determined using the conversion formula for the corresponding weight of the materials.

9. The method according to claim 2, characterized in that, The determination of the vehicle weight difference includes: Determine the weight difference between the target vehicle model and the competing vehicle model; The increase in chassis and body-in-white weight caused by the weight difference is taken as the difference in overall vehicle weight between the target model and the competing model.

10. The method according to claim 1, characterized in that, The method further includes: The target vehicle weight is set based on the equivalent weight of competing models with the best lightweighting level.

11. A device for determining the level of lightweighting of a vehicle, characterized in that, The device includes: The determination module is used to acquire the target vehicle model and identify multiple competing vehicle models corresponding to the target vehicle model; The analysis module is used to analyze the equivalent weight of the multiple competing models to the boundary of the target model; wherein, the equivalent weight includes the weight differences caused by factors such as battery, motor, size, configuration, performance, materials and overall vehicle weight; The determination module is used to determine the overall vehicle lightweighting level of the multiple competing models based on the equivalent weight of each competing model.

12. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the vehicle lightweighting level determination method according to any one of claims 1-10.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the method for determining the level of vehicle lightweighting as described in any one of claims 1-10.

14. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method for determining the lightweight level of a vehicle according to any one of claims 1-10.

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