Automobile wire harness length estimation method, estimation device, and electronic device

Abstract

The application provides a kind of automobile wire harness length estimation method, estimation device and electronic device, estimation method includes obtaining the main size parameter of target automobile, input main stem length estimation model to multiple main size parameter, obtain the main stem wire harness length of target automobile;Obtain the model parameter of target automobile, input branch length estimation model to model parameter, obtain the branch wire harness length of target automobile;Sum the main stem wire harness length and branch wire harness length of target automobile to obtain the wire harness length of target automobile.The estimation method of the application in the design stage of automobile, just input main stem length estimation model to main size parameter, input branch length estimation model to model parameter, can obtain the wire harness length of automobile, calculation process is automatically carried out, improves the calculation efficiency of wire harness, and improves the accuracy of estimated wire harness length.

Description

Technical Field

[0001] This invention belongs to the field of automotive wiring harnesses, and specifically relates to a method for estimating the length of automotive wiring harnesses, as well as an estimation device and electronic device for performing the estimation method. Background Technology

[0002] The function of automotive wiring harnesses is to facilitate the installation and connection of electrical components throughout the vehicle. Wiring harness design plays a crucial role in the realization of the vehicle's electrical functions. Because the installation requirements of various electrical systems and the entire vehicle are constantly changing during development, wiring harnesses generally need continuous adjustment and optimization to accommodate these systems. However, wiring harnesses are characterized by high cost and long development cycles. The length of the entire vehicle's wiring harness directly determines its cost. Therefore, estimating the length of the entire vehicle's wiring harness in the early stages of a project, with limited input, is of great significance for subsequent wiring harness cost analysis and optimization.

[0003] Due to the complexity of wiring harness design and the diversity of influencing variables, the common practice in the early stages of automotive development to estimate the length of the entire vehicle's wiring harness is to roughly calculate the length based on basic project information such as design drawings, ensuring that the length is sufficient. Then, during mass production, each wiring harness is optimized individually. This approach is inefficient and inaccurate, resulting in significant waste of raw materials and a large amount of secondary work. Therefore, currently, there is no quick and reliable method to accurately predict wiring harness length and cost in the early stages of automotive development, which negatively impacts cost control and optimization in automotive development. Summary of the Invention

[0004] The purpose of this invention is to solve the problem that existing methods for estimating the length of vehicle wiring harnesses are inefficient and inaccurate, making it impossible to accurately control wiring harness costs in the early stages of vehicle development.

[0005] To address the aforementioned technical problems, embodiments of the present invention disclose a method for estimating the length of automotive wiring harnesses, comprising: obtaining multiple key dimensional parameters of a target vehicle; inputting the multiple key dimensional parameters into a trunk length estimation model to obtain the trunk wiring harness length of the target vehicle, wherein the trunk length estimation model includes the relationship between multiple key dimensional parameters of historical vehicles and the trunk wiring harness length; obtaining the vehicle model parameters of the target vehicle; inputting the vehicle model parameters into a branch length estimation model to obtain the branch wiring harness length of the target vehicle, wherein the branch length estimation model includes the relationship between historical vehicle model parameters and branch wiring harness lengths; and summing the trunk wiring harness length and the branch wiring harness length of the target vehicle to obtain the total wiring harness length of the target vehicle.

[0006] The above technical solution divides the wiring harness into branch harnesses and trunk harnesses for separate calculation. During the calculation process, only the main dimensional parameters of the target vehicle need to be input into the trunk length estimation model, and the vehicle model parameters into the branch length estimation model. The trunk harness length and branch harness length are calculated separately, thereby estimating the wiring harness length of the target vehicle. This invention automates the estimation process and is fast, improving estimation efficiency. Furthermore, it correlates the trunk harness length with the main dimensional parameters and the branch harness length with the vehicle model parameters, so the estimation results dynamically change with variations in the main dimensional parameters and vehicle model parameters, improving the accuracy of wiring harness length estimation in the early stages of vehicle project development.

[0007] According to another specific embodiment of the present invention, an estimation method disclosed in the present invention includes the steps of obtaining multiple main dimensional parameters of a target vehicle, which include: determining multiple measurement points of the target vehicle, and obtaining multiple lateral dimensions, multiple longitudinal dimensions, and multiple vertical dimensions based on the multiple measurement points.

[0008] According to another specific embodiment of the present invention, an estimation method disclosed in the present invention is characterized in that the estimation method further includes constructing a trunk length estimation model, including: decomposing the trunk harness into multiple segments according to a historical automotive trunk harness topology scheme, wherein the starting point and ending point of each segment are one of multiple measurement points; constructing a trunk harness channel model based on the multiple segments; and establishing a relationship function between each segment in the trunk harness channel model and at least one associated major dimension parameter.

[0009] According to another specific embodiment of the present invention, an estimation method disclosed in the embodiment of the present invention further includes: determining the trunk wiring harness topology scheme of the target vehicle; determining each segment of the trunk wiring harness topology scheme of the target vehicle according to the trunk wiring harness channel model; and calculating the length of each segment of the trunk wiring harness topology scheme of the target vehicle according to the relationship function between the segments in the trunk wiring harness channel model and the associated main size parameters.

[0010] According to another specific embodiment of the present invention, an estimation method disclosed in this embodiment of the present invention includes a relationship function between segments and at least one associated primary dimensional parameter comprising at least one of the following formulas:

[0011] S i =[(H x ×K i2 ) 2 +(L x ×K i1 ) 2 ] 0.5 ×K i0 ,

[0012] S i =Lx ×K i1 +H x ×K i2 +Y,

[0013] S i =L x ×K i1 +W x ×K i3 +Y,

[0014] Among them, S i H is the length of the i-th segment. x For the vertical dimension among the main dimensional parameters of the segmented association, L x For the longitudinal dimension in the main dimension parameters of segmented association, W x K is the lateral dimension among the main dimensional parameters of the segmented association. i0 K i1 K i2 and K i3 represents the piecewise variable coefficients, and Y represents the additional length.

[0015] According to another specific embodiment of the present invention, an estimation method disclosed in this embodiment includes a trunk length prediction model comprising:

[0016]

[0017] Among them, L t The length of the main trunk harness, A is the correction factor, and S i Let be the length of the i-th segment of the main wiring harness topology of the target vehicle.

[0018] According to another specific embodiment of the present invention, an estimation method disclosed in the embodiment of the present invention includes vehicle model parameters including at least one of body type, driving type, power type, wheelbase, vehicle length, vehicle width, vehicle height, and number of connectors.

[0019] According to another specific embodiment of the present invention, an estimation method disclosed in the embodiment of the present invention further includes constructing a branch length estimation model, including: obtaining multiple vehicle model parameters and corresponding multiple branch harness lengths of historical vehicles, and fitting the functional relationship between vehicle model parameters and branch harness lengths by multiple linear regression.

[0020] According to another specific embodiment of the present invention, an estimation method disclosed in this embodiment includes a branch length prediction model comprising:

[0021] B=aX1+bX2+cX3+dX4+eX5+fX6+gX7+hX8+Z

[0022] Where B is the branch harness length, X1 is the body type, X2 is the driving type, X3 is the power type, X4 is the wheelbase, X5 is the vehicle length, X6 is the vehicle width, X7 is the vehicle height, X8 is the number of connectors, a is the body type variable coefficient, b is the driving type variable coefficient, c is the power type variable coefficient, d is the wheelbase variable coefficient, e is the vehicle length variable coefficient, f is the vehicle width variable coefficient, g is the vehicle height variable coefficient, h is the number of connectors variable coefficient, and Z is the correction value.

[0023] The present invention also discloses an automotive wiring harness length estimation device, comprising: a data acquisition module for acquiring multiple main dimensional parameters and vehicle model parameters of a target vehicle; and a calculation module connected to the data acquisition module, wherein the data acquisition module transmits the multiple main dimensional parameters and vehicle model parameters to the calculation module; the calculation module inputs the multiple main dimensional parameters into a trunk length prediction model to obtain the trunk wiring harness length of the target vehicle, wherein the trunk length prediction model includes the relationship between multiple main dimensional parameters of historical vehicles and the trunk wiring harness length; the calculation module also inputs the vehicle model parameters into a branch length prediction model to obtain the branch wiring harness length of the target vehicle, wherein the branch length prediction model includes the relationship between historical vehicle model parameters and the branch wiring harness length; and sums the trunk wiring harness length and branch wiring harness length of the target vehicle to obtain the wiring harness length of the target vehicle.

[0024] The present invention also discloses an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the automotive wiring harness length estimation method of the present invention. Attached Figure Description

[0025] Figure 1 This is a flowchart of the automotive wiring harness length estimation method provided by the present invention;

[0026] Figure 2 This is a schematic diagram of some of the lateral dimensions among the multiple main dimensional parameters in the automotive wiring harness length estimation method provided by this invention;

[0027] Figure 3 This is a schematic diagram of some longitudinal dimensions among the multiple main dimensional parameters in the automotive wiring harness length estimation method provided by the present invention;

[0028] Figure 4 This is a schematic diagram of the main harness path and its multiple segments in the main harness channel model of the automotive harness length estimation method provided by the present invention.

[0029] Figure 5 This is a schematic diagram showing the position of the wiring harness segment S23 in the vehicle body in the automotive wiring harness length estimation method provided by the present invention;

[0030] Figure 6This is a schematic diagram showing the relationship between the wiring harness segment S23 and the associated main dimensional parameters in the automotive wiring harness length estimation method provided by this invention;

[0031] Figure 7 This is a schematic diagram of the branch length prediction model in the automotive wiring harness length estimation method provided by the present invention.

[0032] Explanation of reference numerals in the attached figures:

[0033] 1. Harness segmentation; 2. Measurement points; 21. Right point inside the rear panel. Detailed Implementation

[0034] In the early stages of automotive development, it is necessary to estimate the length of the entire vehicle's wiring harness. However, automotive wiring harness layout is complex, and due to the constantly changing installation requirements of various electrical systems and the entire vehicle during development, wiring harnesses generally need to be continuously adjusted and optimized to match each system. Wiring harness design is complex and involves diverse variables, making accurate calculation of harness length difficult. Currently, there is no quick and reliable method to accurately estimate wiring harness length and cost in the early stages of automotive development, which negatively impacts cost control and optimization. To address these issues, this invention provides a method for estimating automotive wiring harness length. It pre-obtains a trunk length estimation model and a branch length estimation model. In the early stages of automotive development, by determining several key dimensional parameters of the vehicle and inputting the trunk length estimation model, the trunk wiring harness length can be obtained; by determining the vehicle model parameters and inputting the branch length estimation model, the branch wiring harness length can be obtained. Summing the trunk and branch wiring harness lengths yields the total wiring harness length for the vehicle. This method enables automatic estimation of wiring harness length before the start of wiring harness design in the early stages of the project, improving estimation efficiency and providing high accuracy.

[0035] To better understand the automotive wiring harness length estimation method, estimation device, and electronic equipment provided in this application, the specific implementation process of the automotive wiring harness length estimation method, estimation device, and electronic equipment will be described in detail below with reference to the accompanying drawings.

[0036] Before proceeding with a detailed explanation, some concepts in this invention will be explained as follows:

[0037] In the early stages of automotive development, the vehicle for which wiring harness estimation is required is defined as the target vehicle, while similar vehicles that have already been designed are defined as historical vehicles. Wiring harnesses whose paths from start to end point have a functional relationship with the vehicle's main dimensional parameters are defined as trunk wiring harnesses; the remaining wiring harnesses are defined as branch wiring harnesses. Main dimensional parameters refer to dimensions that have a significant impact on the entire vehicle or the user, including dimensions and data between multiple major components, as well as dimensions and data between multiple key points in the vehicle design, such as the dimensions of the front bulkhead, roof, seats and wheels, door sills and wheels, and instrument panel and seats. Vehicle model parameters refer to other relevant parameters that affect the length of the vehicle's wiring harness, such as the vehicle's body type, powertrain type, body parameters, and number of electrical components.

[0038] Example 1

[0039] The automotive wiring harness length estimation method provided by this invention, such as... Figure 1 As shown, the estimation method includes: obtaining multiple main size parameters of the target vehicle, inputting the multiple main size parameters into the trunk length estimation model to obtain the trunk harness length of the target vehicle; obtaining the vehicle model parameters of the target vehicle, inputting the vehicle model parameters into the branch length estimation model to obtain the branch harness length of the target vehicle; and summing the trunk harness length and branch harness length of the target vehicle to obtain the harness length of the target vehicle.

[0040] The trunk length estimation model is determined based on historical vehicle trunk wiring harness data, including the relationship between several key dimensional parameters of historical vehicles and trunk wiring harness length. The branch length estimation model is determined based on historical vehicle branch wiring harness data, including the relationship between historical vehicle model parameters and branch wiring harness length.

[0041] The automotive wiring harness length estimation method of this invention, in the early stages of target vehicle development, after determining the main dimensional parameters and model parameters of the target vehicle, inputs the main dimensional parameters into the trunk length prediction model to obtain the trunk wiring harness length, and inputs the model parameters into the branch length prediction model to obtain the branch wiring harness length. The trunk and branch wiring harness lengths are calculated separately, thereby estimating the wiring harness length of the target vehicle. This invention automates the estimation process and is fast, improving estimation efficiency. Furthermore, it correlates the trunk wiring harness length with the main dimensional parameters and the branch wiring harness length with the model parameters, so the estimation results dynamically change with changes in the main dimensional parameters and model parameters, improving the accuracy of automotive wiring harness length estimation in the early stages of vehicle project development.

[0042] In one specific embodiment of the present invention, the step of obtaining multiple key dimensional parameters of the target vehicle includes: determining multiple measurement points of the target vehicle, wherein the measurement points include key positioning points along which the main wiring harness must pass, coordinate points of some important vehicle components, vehicle design reference points, etc. Multiple lateral dimensions, multiple longitudinal dimensions, and multiple vertical dimensions are obtained based on the multiple measurement points, wherein the lateral dimension refers to the dimension along the width direction of the vehicle body, the longitudinal dimension refers to the dimension along the length direction of the vehicle body, and the vertical dimension refers to the dimension along the height direction of the vehicle body; more specifically, the lateral dimension can be the lateral distance between a measurement point and some key positions (such as the middle position of the vehicle) or key components (such as wheels) of the vehicle, the lateral distance between the component where the measurement point is located and some key positions or key components of the vehicle, or the lateral distance between two measurement points, etc.; the longitudinal dimension can be the longitudinal distance between a measurement point and some key positions or key components of the vehicle, the longitudinal distance between the component where the measurement point is located and some key positions or key components of the vehicle, or the longitudinal distance between two measurement points, etc.; the vertical dimension can be the height of the component where the measurement point is located from the ground or from the bottom surface of the vehicle. During measurement, some measurement surfaces can also be determined. The main dimensional parameters can be obtained by measuring the distance between a measurement point and the measurement surface. For example, when measuring lateral distance, the surface at the middle of the width direction of the car, the surface at the middle of the width direction of the car seat, and the inner side of the car tire can be used as measurement surfaces; the ground and the bottom surface of the car are the measurement surfaces for measuring vertical distance.

[0043] like Figure 2 A schematic diagram showing some of the lateral dimensions is provided, such as... Figure 2 W102-1 represents the distance from the center of the right front wheel to the lateral center of the vehicle body, W102-2 represents the distance from the center of the left front wheel to the lateral center of the vehicle body, and W103 represents the distance from the leftmost end to the rightmost end of the vehicle body.

[0044] Figure 3 A schematic diagram showing some of the longitudinal dimensions is provided, such as... Figure 3 L103 indicates the distance from the frontmost to the rearmost point of the vehicle body, while L113 indicates the distance from the center of the front wheel to the driver's feet.

[0045] In one specific embodiment of the present invention, the estimation method further includes constructing a trunk length prediction model to establish the correlation between the length of the automotive trunk harness and the main dimensional parameters of the vehicle. The construction process includes: decomposing the trunk harness into multiple segments based on historical automotive trunk harness topology schemes and multiple measurement points of historical vehicles, wherein the start and end points of each segment are one of the multiple measurement points; constructing a trunk harness channel model based on the multiple segments, including the trunk harness path, segments, and length data of each segment; and establishing a relationship function between each segment and at least one associated main dimensional parameter based on the measurement points and lengths corresponding to each segment in the trunk harness channel model.

[0046] Specifically, after obtaining the historical automotive trunk wiring harness topology, all trunk wiring harnesses are broken down into several segments arranged between two measurement points. These measurement points are key positioning points that the trunk wiring harnesses must pass through, and the length of each segment is determined. Then, a trunk wiring harness channel model is built using all segments, including the path of the trunk wiring harness, each segment, and the measurement points at both ends of the segment. Figure 4 The diagram illustrates the main harness path and its multiple segments in the main harness channel model. It shows each harness segment 1 and its corresponding measurement points 2 at both ends. One of these measurement points is the right inner point 21 of the rear panel, a point that the main harness path will definitely pass through. The right inner point 21 of the rear panel lies on the intersection of the transverse and longitudinal planes where the rear wheel center of the measurement point (dimension L115) is located. Furthermore, by associating the measurement points involved in each segment, the segment length, and the main dimensional parameters, a main harness length prediction model is constructed. This allows for the adaptive dynamic change of the main harness length as the main dimensional parameters of the vehicle change.

[0047] The obtained historical automotive trunk wiring harness topology scheme can be a single historical automotive trunk wiring harness topology scheme or several historical automotive trunk wiring harness topology schemes. The paths involved in the trunk wiring harnesses of all historical automotive trunk wiring harness topology schemes are decomposed to obtain all wiring harness segments. In one specific embodiment of the invention, the obtained historical trunk wiring harness topology scheme is a 150% topology scheme, that is, a maximized topology scheme, which refers to a topology scheme library containing all current possibilities. This means obtaining all historical automotive trunk wiring harness topology schemes from the database, obtaining all historical automotive trunk wiring harness layout paths to build a trunk wiring harness channel model, thereby constructing a relatively comprehensive trunk wiring harness path library. The estimation method also includes: combining the number of electrical functions of the target vehicle and the layout location of the vehicle's electrical components, and then, based on the principle of achieving reliable connection of the vehicle's electrical signals and minimizing wiring harness length to reduce wiring harness costs, designing suitable trunk wiring harness paths to determine the target vehicle's trunk wiring harness topology scheme; and corresponding the target vehicle's trunk wiring harness topology scheme with the constructed trunk wiring harness channel model to determine each segment of the target vehicle's trunk wiring harness topology scheme. Then, based on the main size parameters of the target vehicle and the relationship function between all segments and associated main size parameters in the trunk wiring harness channel model, the length of each segment of the target vehicle's trunk wiring harness topology is calculated.

[0048] In one specific embodiment of the present invention, the relationship function between the segmentation and at least one of the associated primary dimensional parameters includes at least one of the following formulas:

[0049] S i =[(H x ×K i2 ) 2 +(L x ×K i1 ) 2 ] 0.5 ×K i0 ,

[0050] S i =L x ×K i1 +H x ×K i2 +Y,

[0051] S i =L x ×K i1 +W x ×K i3 +Y,

[0052] Among them, S i H is the length of the i-th segment. x For the vertical dimension among the main dimensional parameters of the segmented association, L xFor the longitudinal dimension in the main dimension parameters of segmented association, W x K is the lateral dimension among the main dimensional parameters of the segmented association. i0 K i1 K i2 and K i3 Let K be the piecewise variable coefficient, and Y be the additional length. The piecewise variable coefficient K... i0 K i1 K i2 and K i3 By fitting and correcting historical data, the historical data of each segment is integrated to obtain the optimal correction coefficient for each segment and iterated. The higher the fit, the closer the segment variable coefficient is to 1. In one specific embodiment of the present invention, the segment variable coefficient is in the range of 1 ± 0.15, indicating a high fit of the function. Y is obtained based on historical data and can be 0, i.e., without additional length, or it can be 100mm, 150mm, etc.

[0053] Specifically, such as Figure 5 As shown, the wire harness segment S in the box 23 The starting point is the point behind the right threshold, and the ending point is the vertex of the right rear wheel arch, as shown below. Figure 6 As shown, by fitting the main dimensional parameters related to the measurement points at the start and end points of this segment, the segment S is determined. 23 The hypotenuse of the right triangle formed by L115-2 and the height H1 of the right rear wheel arch, i.e., its segment S 23 The relevant key dimensional parameters are L115-2 and the rear wheel arch height H1; and S 23 The relationship function between the main dimensional parameters and the associated parameters is as follows:

[0054] S 23 =(L115-2 2 +H1 2 ) 0.5

[0055] Harness Segmentation 12 The segment from the right front inline (connector) point of the forward cabin to the front point of the right longitudinal beam of the forward cabin, S 12 The relationship function between the main dimensional parameters and the associated parameters is as follows:

[0056] S 12 =L104×K i1 +H2×K i2 +150

[0057] In the formula, H2 represents the height of the front bulkhead.

[0058] Harness Segmentation 16 S is the segment between the rear point of the right longitudinal beam of the forward compartment and the right rear inline point of the forward compartment line. 16The relationship function between the main dimensional parameters and the associated parameters is as follows:

[0059] S 16 =L113×K i1 +H2×K i2

[0060] Harness Segmentation 98 S is the segment between the vertex of the front right rear wheel arch and the right midpoint of the bottom of the rear floor. 98 The relationship function between the main dimensional parameters and the associated parameters is as follows:

[0061] S 98 =H1+W102-1×K i3

[0062] Harness Segmentation 131 S is the segment between the rear point of the instrument cluster channel and the inline point of the passenger seat on the instrument cluster. 131 The relationship function between the main dimensional parameters and the associated parameters is as follows:

[0063] S 131 =W102×K i3 +H3+150

[0064] H3 indicates the height of the rear passenger's center of gravity relative to the car floor.

[0065] Harness Segmentation 169 S is the segment between the upper right point and the lower right point of the tailgate. 169 The relationship function between the main dimensional parameters and the associated parameters is as follows:

[0066] S 169 =[L105 2 +(H4×K i1 ) 2 ] 0.5 ×K i0

[0067] H4 indicates the height of the rear roof.

[0068] Harness Segmentation 188 S represents the segment between the right front inline point and the right front point of the ceiling. 188 The relationship function between the main dimensional parameters and the associated parameters is as follows:

[0069] S 188 =[(H5-H2)] 2 +L99-1 2 ] 0.5

[0070] H5 indicates the height of the front roof.

[0071] Harness Segmentation 192S is the segment between the front left point and the center left point of the ceiling. 192 The relationship function between the main dimensional parameters and the associated parameters is as follows:

[0072] S 192 =[(H5-H2)] 2 +L99-1 2 ] 0.5 ×K i0 +L50-2×K i1 .

[0073] The length of the target vehicle's main wiring harness is obtained by summing the lengths of each segment of all calculated topology schemes for the target vehicle's main wiring harness. In one specific embodiment of the present invention, the main wiring harness length prediction model includes:

[0074]

[0075] Among them, L t The length of the main trunk harness, A is the correction factor, and S i Let be the length of the i-th segment.

[0076] The length of the target vehicle's main wiring harness is obtained by summing the lengths of each segment of the calculated target vehicle's main wiring harness topology and then correcting it using a correction coefficient. The correction coefficient A is obtained by fitting historical data; in one specific implementation, the correction coefficient is in the range of 1 ± 0.15, indicating a high degree of fit in the function fitting.

[0077] In one specific embodiment of the present invention, the vehicle model parameters include at least one of body type, driving type, power type, wheelbase, vehicle length, vehicle width, vehicle height and number of connectors. Preferably, the vehicle model parameters include multiple of the above parameters. More preferably, the vehicle model parameters include all of the above parameters.

[0078] Specifically, vehicle body types include sedan, hatchback, or SUV; driving types include left-hand drive and right-hand drive; and powertrain types include pure electric (EV), hybrid electric (HEV), plug-in hybrid electric (PHEV), extended-range electric (EREV), or fuel cell vehicle (FCV).

[0079] The branch length prediction model includes the relationship between historical vehicle body type, driving type, power type, wheelbase, vehicle length, vehicle width, vehicle height, and the number of connectors and the branch harness length; by inputting the specific vehicle model parameters of the target vehicle into the branch length prediction model, the branch harness length of the target vehicle can be obtained.

[0080] In one specific embodiment of the present invention, the method further includes constructing a branch length prediction model, including: obtaining multiple vehicle model parameters and corresponding multiple branch harness lengths of historical vehicles, and fitting the functional relationship between vehicle model parameters and branch harness lengths using multiple linear regression.

[0081] Specifically, different vehicle parameters can be defined as variables, such as: X1 is the body type, X2 is the driving type, X3 is the powertrain type, X4 is the wheelbase, X5 is the vehicle length, X6 is the vehicle width, X7 is the vehicle height, and X8 is the number of connectors. Furthermore, the categorical variables can be converted into numerical variables by encoding the body type, driving type, and powertrain type variables. For example, if the body type is a sedan, then X1 = 1; if the body type is a hatchback, then X1 = 2; if the body type is an SUV, then X1 = 3; if the driving type is left-hand drive, then X2 = 1; if the driving type is right-hand drive, then X2 = 2; if the powertrain type is EV, then X3 = 1; if the powertrain type is HEV, then X3 = 2; if the powertrain type is PHEV, then X3 = 3; if the powertrain type is EREV, then X3 = 4; and if the powertrain type is FCV, then X3 = 5. The variables are imported into multiple vehicle model parameters and corresponding branch harness length data from historical vehicles for regression fitting to obtain the functional relationship between each variable and the branch harness length. The specific fitting algorithm in the multiple linear regression method is not limited.

[0082] In one specific embodiment of the present invention, the branch length prediction model includes:

[0083] B=aX1+bX2+cX3+dX4+eX5+fX6+gX7+hX8+Z

[0084] In the formula, B is the branch harness length, a is the vehicle body type variable coefficient, b is the driving type variable coefficient, c is the power type variable coefficient, d is the wheelbase variable coefficient, e is the vehicle length variable coefficient, f is the vehicle width variable coefficient, g is the vehicle height variable coefficient, h is the connector quantity variable coefficient, and Z is the correction value.

[0085] Specifically, in this embodiment, vehicle model parameters are imported from multiple sets of historical vehicle model parameters and corresponding branch harness length data. A linear multivariate regression fitting method is then used to obtain the coefficients and correction values ​​for each variable. The obtained branch length prediction model is as follows: Figure 7As shown, the input variables are vehicle body type X1, driving type X2, power type X3, wheelbase X4, vehicle length X5, vehicle width X6, vehicle height X7, and number of connectors X8. Each variable is multiplied by its corresponding coefficient, and the sum of all obtained values ​​(SUM) is then applied. A correction value Z is added for adjustment, and the output is the branch harness length B. Finally, the main harness length and branch harness length of the target vehicle are summed to obtain the target vehicle's harness length, which is L. t +B.

[0086] This invention establishes the correlation between branch harness length and vehicle model parameter variables, such as body type, driving type, and power type, by constructing a regression model of branch harness and vehicle model parameter variables, thereby achieving accurate prediction of branch harness length.

[0087] The automotive wiring harness length estimation method provided by this invention clearly defines the main wiring harness and branch wiring harness. By using the main length prediction model and the branch length prediction model to calculate the length of the main wiring harness and the branch wiring harness respectively, the accurate prediction of the length of the entire vehicle wiring harness is achieved.

[0088] Example 2

[0089] The automotive wiring harness length estimation device provided by the present invention is used to execute the automotive wiring harness length estimation method of Embodiment 1. The estimation device includes a data acquisition module and a calculation module.

[0090] The data acquisition module is used to collect multiple key dimensional parameters and vehicle model parameters of the target vehicle.

[0091] The calculation module is connected to the acquisition module. The acquisition module transmits multiple key dimensional parameters and vehicle model parameters to the calculation module. The calculation module inputs the key dimensional parameters into the trunk length prediction model to obtain the trunk harness length of the target vehicle. The trunk length prediction model includes the relationship between multiple key dimensional parameters of historical vehicles and the trunk harness length. The calculation module also inputs the vehicle model parameters into the branch length prediction model to obtain the branch harness length of the target vehicle. The branch length prediction model includes the relationship between historical vehicle model parameters and branch harness lengths. Finally, the calculation module sums the trunk harness length and branch harness length of the target vehicle to obtain the total harness length of the target vehicle.

[0092] Example 3

[0093] The electronic device provided by the present invention includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the automotive wiring harness length estimation method of Embodiment 1.

[0094] It should be noted that, in addition to the specific embodiments described above, those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. Although the description of the present invention is presented in conjunction with preferred embodiments, this does not mean that the features of the invention are limited to these embodiments. On the contrary, the purpose of describing the invention in conjunction with the embodiments is to cover other options or modifications that may be derived based on the claims of the present invention. To provide a deep understanding of the invention, many specific details are included in the above description, and the invention may also be implemented without using these details. Furthermore, to avoid confusion or obscuring the focus of the invention, some specific details will be omitted in the description. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0095] It should be noted that similar reference numerals and letters in this specification are similar items in the following figures. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0096] While the present invention has been illustrated and described with reference to certain preferred embodiments, those skilled in the art should understand that the above description is a further detailed explanation of the invention in conjunction with specific embodiments, and should not be construed as limiting the specific implementation of the invention to these descriptions. Various changes in form and detail can be made by those skilled in the art, including several simple deductions or substitutions, without departing from the spirit and scope of the invention.

Claims

1. A method for estimating the length of automotive wiring harnesses, characterized in that, include: The target vehicle has multiple key size parameters, which are then input into a trunk length prediction model to obtain the trunk harness length of the target vehicle. The trunk length prediction model includes the relationship between multiple key size parameters of historical vehicles and the trunk harness length. Obtain the vehicle model parameters of the target vehicle, input the vehicle model parameters into the branch length prediction model, and obtain the branch harness length of the target vehicle. The branch length prediction model includes the relationship between the vehicle model parameters of historical vehicles and the branch harness length. The length of the wiring harness of the target vehicle is obtained by summing the length of the main wiring harness and the length of the branch wiring harness.

2. The estimation method as described in claim 1, characterized in that, The steps for obtaining multiple key dimensional parameters of a target vehicle include: determining multiple measurement points of the target vehicle, and obtaining multiple lateral dimensions, multiple longitudinal dimensions, and multiple vertical dimensions based on the multiple measurement points.

3. The estimation method as described in claim 2, characterized in that, The estimation method further includes constructing the trunk length prediction model, including: Based on the historical automotive trunk wiring harness topology, the trunk wiring harness is decomposed into multiple segments, wherein the start point and end point of each segment are one of the multiple measurement points; The main trunk cable channel model is constructed based on the multiple segments described above; Establish a relationship function between each segment in the main harness channel model and at least one associated primary dimension parameter.

4. The estimation method as described in claim 3, characterized in that, The estimation method further includes: Determine the trunk wiring harness topology scheme of the target vehicle, and determine each segment of the trunk wiring harness topology scheme of the target vehicle according to the trunk wiring harness channel model; The length of each segment of the trunk harness topology scheme of the target vehicle is calculated based on the relationship function between the segments and the associated main size parameters in the trunk harness channel model.

5. The estimation method as described in claim 4, characterized in that, The relationship function between the segmentation and at least one of the associated primary dimensional parameters includes at least one of the following: S i =[(H x ×K i2 ) 2 +(L x ×K i1 ) 2 ] 0.5 ×K i0 , S i =L x ×K i1 +H x ×K i2 +Y, S i =L x ×K i1 +W x ×K i3 +Y, Among them, S i H is the length of the i-th segment. x L is the vertical dimension among the main dimensional parameters associated with the segmentation. x For the segmentation, associate the longitudinal dimension in the main dimension parameter, W x K is the lateral dimension among the main dimension parameters associated with the segment. i0 K i1 K i2 and K i3 represents the piecewise variable coefficients, and Y represents the additional length.

6. The estimation method as described in claim 4, characterized in that, The trunk length prediction model includes: Among them, L t Where A is the length of the main trunk harness, and S is the correction factor. i The length of the i-th segment of the trunk wiring harness topology of the target vehicle.

7. The estimation method according to any one of claims 1-6, characterized in that, The vehicle parameters include at least one of the following: body type, driving type, power type, wheelbase, vehicle length, vehicle width, vehicle height, and number of connectors.

8. The estimation method as described in claim 7, characterized in that, The method further includes constructing the branch length prediction model, including: The vehicle model parameters and corresponding branch harness lengths of historical vehicles are obtained, and the functional relationship between the vehicle model parameters and the branch harness lengths is fitted by multiple linear regression.

9. The estimation method as described in claim 8, characterized in that, The branch length prediction model includes: B=aX1+bX2+cX3+dX4+eX5+fX6+gX7+hX8+Z Wherein, B is the length of the branch harness, X1 is the vehicle body type, X2 is the driving type, X3 is the power type, X4 is the wheelbase, X5 is the vehicle length, X6 is the vehicle width, X7 is the vehicle height, X8 is the number of connectors, a is the variable coefficient for vehicle body type, b is the variable coefficient for driving type, c is the variable coefficient for power type, d is the variable coefficient for wheelbase, e is the variable coefficient for vehicle length, f is the variable coefficient for vehicle width, g is the variable coefficient for vehicle height, h is the variable coefficient for number of connectors, and Z is the correction value.

10. A device for estimating the length of automotive wiring harnesses, characterized in that, The estimation device includes: The acquisition module is used to acquire multiple key size parameters of the target vehicle and the vehicle model parameters of the target vehicle; A calculation module is connected to the acquisition module. The acquisition module transmits multiple main size parameters and vehicle model parameters to the calculation module. The main size parameters are then input into a trunk length prediction model to obtain the trunk harness length of the target vehicle. The trunk length prediction model includes the relationship between multiple main size parameters of historical vehicles and the trunk harness length. The calculation module also inputs the vehicle model parameters into the branch length estimation model to obtain the branch harness length of the target vehicle. The branch length estimation model includes the relationship between the vehicle model parameters and the branch harness length of historical vehicles. The module then sums the trunk harness length and the branch harness length of the target vehicle to obtain the harness length of the target vehicle.

11. An electronic device comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the automotive wiring harness length estimation method according to any one of claims 1 to 9.

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