Gearbox type selection matching method and system

Abstract

The invention belongs to the technical field of automobile development, and particularly relates to a gearbox type selection matching method and system.The method comprises the steps that big data information of a target automobile model in the market is collected, and the driving characteristics of the whole automobile are determined; combining the whole vehicle driving characteristics of different dimensions to form common working condition points of the whole vehicle; carrying out statistics on the sampling data of different common working condition points, calculating the relative proportion of each common working condition point in all common working condition points, and obtaining the weight coefficient of each common working condition point; on the basis of the target vehicle type related parameters, the minimum fuel consumption value of each gearbox to be selected under each common working condition point is calculated; and respectively carrying out weighted correction on the minimum fuel consumption value of each gearbox to be selected under each common working condition point by using the weight coefficient to obtain a comprehensive fuel consumption result of each gearbox to be selected, and selecting the gearbox with the minimum comprehensive fuel consumption as a performance optimal selection result. And deep matching of the gearbox with a target vehicle model and a subdivided market is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of vehicle development, and particularly relates to a gearbox selection and matching method and system. Background Art

[0002] The mainstream AMT mechanical gearboxes currently used in heavy commercial vehicles usually adopt multi-stage gear pairs for speed reduction to achieve more gears and gear ratios, so as to meet different power requirements. And it is easy to design a variety of different speed ratio selection schemes for multi-stage gear pairs. It is necessary to complete the selection and demonstration in advance at the early stage of gearbox development.

[0003] As the core competitiveness of heavy commercial vehicles, vehicle economy is an important basis for gearbox selection. Different gearbox speed ratio schemes have different fuel consumption performances under different vehicle operating conditions, and the fuel consumption performance is also affected by the AMT shift points at the same time. The selection and demonstration is extremely difficult. And it is impossible to decouple the influence of AMT shift points on fuel consumption. Summary of the Invention

[0004] The purpose of the present invention is to provide a gearbox selection and matching method and system to solve the problems that different gearbox speed ratio schemes are good and bad under different vehicle operating conditions, it is difficult to compare and evaluate, and it is impossible to decouple the influence of AMT shift points on fuel consumption.

[0005] In the first aspect, the technical solution of the present invention provides a gearbox selection and matching method, including the following: Collect big data information of the target vehicle model in the market and determine the vehicle driving characteristics; Combine the vehicle driving characteristics in different dimensions to form common vehicle operating points; Statistically analyze the sampling data of different common vehicle operating points, calculate the relative proportion of each common vehicle operating point among all common vehicle operating points, and obtain the weight coefficient of each common vehicle operating point; Based on the relevant parameters of the target vehicle model, calculate the minimum fuel consumption value of each candidate gearbox under each common vehicle operating point respectively; Use the weight coefficient to weightedly correct the minimum fuel consumption value of each candidate gearbox under each common vehicle operating point respectively, obtain the comprehensive fuel consumption result of each candidate gearbox, and select the gearbox with the smallest comprehensive fuel consumption as the optimal performance selection result.

[0006] As a preference of the technical solution of the present invention, the vehicle driving characteristics include slope characteristics and vehicle speed characteristics; the step of collecting big data information of the target vehicle model in the market and determining the vehicle driving characteristics includes: Collect the operation data of a set number of target vehicle models in the target sub-market; Clean the collected original data, organize the data after cleaning, and classify and group the data according to the set slope intervals and vehicle speed intervals; Count the data volume of different slope intervals passed by the vehicle, calculate the proportion of the data volume of each slope interval in the total data volume, and the proportion value constitutes the slope feature; Count the data volume of different vehicle speed intervals passed by the vehicle, calculate the proportion of the data volume of each vehicle speed interval in the total data volume, and the proportion value constitutes the vehicle speed feature.

[0007] As an optimization of the technical solution of the present invention, the steps of combining the driving characteristics of the whole vehicle in different dimensions to form the common working condition points of the whole vehicle include: Analyze the proportion distribution of different slopes in the slope feature, obtain the slope intervals with a proportion greater than the first proportion threshold, and determine the slope point range with the main proportion for the slope intervals with a proportion exceeding the first proportion threshold; Analyze the proportion distribution of different vehicle speeds in the vehicle speed feature, obtain the vehicle speed intervals with a proportion greater than the second proportion threshold, and determine the vehicle speed point range with the main proportion for the vehicle speed intervals with a proportion exceeding the second proportion threshold; Select the interval quantity according to the slope point range with the main proportion and the vehicle speed point range with the main proportion; Within the slope point range with the main proportion and the vehicle speed point range with the main proportion, determine the common slope points and common vehicle speed points according to the selected interval quantity; Pair and combine the determined common slope points and common vehicle speed points to form the common working condition points of the whole vehicle with slope-vehicle speed characteristics; among them, each combination corresponds to a specific common working condition point.

[0008] As an optimization of the technical solution of the present invention, the steps of counting the sampling data of different common working condition points and calculating the relative proportion of each common working condition point in all common working condition points to obtain the weight coefficient of each common working condition point include: Count the sampling data volume of each common working condition point; Sum up the sampling data quantities of each common working condition point obtained by statistics to obtain the total sampling data quantity of all common working condition points; Use each common working condition point 's sampling data volume Divide by the total sampling data quantity N of all common working condition points to obtain the relative proportion of each common working condition point in all common working condition points, that is, the weight coefficient of this common working condition point ; Calculation formula: , where ; Obtain the weight coefficient of each common working condition point .

[0009] As an optimization of the technical solution of the present invention, the steps of calculating the minimum fuel consumption value of each candidate transmission at each common operating condition point based on the relevant parameters of the target vehicle model include: Based on the relevant parameters of the target vehicle model, calculate the fuel consumption values of the highest gear and the second highest gear of each candidate transmission at common operating condition points; Select the value with lower fuel consumption among the highest gear and the second highest gear as the minimum fuel consumption value of the transmission at the common operating condition point.

[0010] As an optimization of the technical solution of the present invention, the steps of weighted correction of the minimum fuel consumption value of each candidate transmission at each common operating condition point with weight coefficients to obtain the comprehensive fuel consumption results of each candidate transmission, and selecting the transmission with the smallest comprehensive fuel consumption as the performance optimal selection result include: For each candidate transmission , calculate the comprehensive fuel consumption of the candidate transmission according to the weighted summation formula ; Weighted summation formula: , is the weight coefficient of the th common operating condition point, is the th candidate transmission at the th common operating condition point of the minimum fuel consumption value, , , , is the total number of candidate transmissions, is the total number of common operating condition points; Compare the comprehensive fuel consumption of each candidate transmission calculated to to obtain the minimum value of the comprehensive fuel consumption; According to the minimum value of the comprehensive fuel consumption, determine the candidate transmission with the minimum comprehensive fuel consumption, and this transmission is the performance optimal selection result.

[0011] As an optimization of the technical solution of the present invention, the method further includes: analyzing the fuel consumption results of the selected optimal transmission, and extracting the relationship between the best economic shift point and the common operating condition point according to the distribution of the value with lower fuel consumption between the highest gear and the second highest gear.

[0012] As an optimization of the technical solution of the present invention, the steps of analyzing the fuel consumption results of the selected optimal transmission and extracting the relationship between the best economic shift point and the common operating condition point according to the distribution of the value with lower fuel consumption between the highest gear and the second highest gear include: For each common operating condition point , compare the fuel consumption of the highest gear and the fuel consumption of the second highest gear ; If , it is marked that the highest gear at this operating point is the low fuel consumption gear; If , then mark the second highest gear as the low fuel consumption gear; According to the marking result, find the common operating points where the low fuel consumption gear changes from the highest gear to the second highest gear, or from the second highest gear to the highest gear, and record them as shift transition points; For each shift transition point, obtain its adjacent common operating points with different gear markings and a fuel consumption difference greater than the set threshold, and record them as shift boundary operating points; Based on the slope and vehicle speed information of the shift boundary operating points, obtain the relationship between the optimal economic shift point and the common operating points.

[0013] In a second aspect, the technical solution of the present invention also provides a gearbox selection and matching system, including a big data analysis module, a common operating point generation module, a weight coefficient calculation module, a fuel consumption calculation module, and a correction processing module; The big data analysis module is used to collect big data information of the target vehicle model in the market and determine the vehicle driving characteristics; The common operating point generation module is used to combine the vehicle driving characteristics in different dimensions to form vehicle common operating points; The weight coefficient calculation module is used to statistically analyze the sampling data of different common operating points, calculate the relative proportion of each common operating point among all common operating points, and obtain the weight coefficient of each common operating point; The fuel consumption calculation module is used to calculate the minimum fuel consumption value of each candidate gearbox at each common operating point based on the relevant parameters of the target vehicle model; The correction processing module is used to weightedly correct the minimum fuel consumption value of each candidate gearbox at each common operating point with the weight coefficient to obtain the comprehensive fuel consumption result of each candidate gearbox, and select the gearbox with the minimum comprehensive fuel consumption as the optimal performance selection result.

[0014] As an optimization of the technical solution of the present invention, the vehicle driving characteristics include slope characteristics and vehicle speed characteristics; the big data analysis module is specifically used to collect the operation data of a set number of target vehicle models in the target sub - market; clean the collected original data, sort the cleaned data, and classify the data according to the set slope intervals and vehicle speed intervals; statistically analyze the data volume of different slope intervals passed by the vehicle, calculate the proportion of the data volume of each slope interval in the total data volume, and the proportion value constitutes the slope characteristics; statistically analyze the data volume of different vehicle speed intervals passed by the vehicle, calculate the proportion of the data volume of each vehicle speed interval in the total data volume, and the proportion value constitutes the vehicle speed characteristics.

[0015] As a preference of the technical solution of the present invention, the common operating condition point generation module is specifically configured to analyze the proportion distribution of different slopes in the slope characteristics, obtain the slope intervals with proportions greater than the first proportion threshold, and determine the slope point ranges with the main proportions as the slope intervals with proportions exceeding the first proportion threshold; analyze the proportion distribution of different vehicle speeds in the vehicle speed characteristics, obtain the vehicle speed intervals with proportions greater than the second proportion threshold, and determine the vehicle speed point ranges with the main proportions as the vehicle speed intervals with proportions exceeding the second proportion threshold; select the interval amount according to the slope point ranges with the main proportions and the vehicle speed point ranges with the main proportions; within the slope point ranges with the main proportions and the vehicle speed point ranges with the main proportions, determine the common slope points and common vehicle speeds according to the selected interval amount; pair and combine the determined common slope points and common vehicle speeds to form the common operating conditions of the whole vehicle with slope-vehicle speed characteristics; where each combination corresponds to a specific common operating condition point.

[0016] As a preference of the technical solution of the present invention, the weight coefficient calculation module is specifically configured to count the sampling data volume of each common operating condition point; sum up the sampling data quantities of each common operating condition point obtained by statistics to obtain the total sampling data quantity of all common operating condition points; respectively use the sampling data volume of each common operating condition point divide by the total sampling data quantity N of all common operating condition points to obtain the relative proportion of each common operating condition point among all common operating condition points, that is, the weight coefficient of this common operating condition point ; calculation formula: , where ; obtain the weight coefficients of each common operating condition point .

[0017] As a preference of the technical solution of the present invention, the fuel consumption calculation module is specifically configured to calculate the fuel consumption values of the highest gear and the second highest gear of each candidate transmission at the common operating condition points respectively based on the relevant parameters of the target vehicle model; select the lower fuel consumption value between the highest gear and the second highest gear as the lowest fuel consumption value of this transmission at this common operating condition point.

[0018] As a preference of the technical solution of the present invention, the correction processing module is specifically configured to, for each candidate transmission , calculate the comprehensive fuel consumption of this candidate transmission according to the weighted summation formula ; weighted summation formula: , is the weight coefficient of the th common operating condition point, is the th candidate transmission at the th common operating condition point, , , is the total number of candidate transmissions, is the total number of common operating points; for the comprehensive fuel consumption of each candidate gearbox calculated from to compare and obtain the minimum value of the comprehensive fuel consumption; according to the minimum value of the comprehensive fuel consumption, determine the candidate gearbox with the minimum comprehensive fuel consumption, and this gearbox is the optimal performance selection result.

[0019] As an optimization of the technical solution of the present invention, the system further includes a shift point generation module, which is used to analyze the fuel consumption results of the selected optimal gearbox, and extract the relationship between the best economic shift point and the common operating points according to the distribution of the lower fuel consumption values in the highest gear and the second highest gear.

[0020] As an optimization of the technical solution of the present invention, the method further includes: a shift point generation module, specifically for each common operating point , compare the fuel consumption in the highest gear and the fuel consumption in the second highest gear; if , mark the highest gear as the low fuel consumption gear at this operating point; if

[0021] , mark the second highest gear as the low fuel consumption gear; according to the marking results, find the common operating points where the low fuel consumption gear changes from the highest gear to the second highest gear, or from the second highest gear to the highest gear, and record them as shift transition points; for each shift transition point, obtain the adjacent common operating points with different gear markings and a fuel consumption difference greater than the set threshold, and record them as shift boundary operating points; according to the slope and vehicle speed information of the shift boundary operating points, obtain the relationship between the best economic shift point and the common operating points. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solution of the present invention, the following will briefly introduce the drawings required for the description. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0023] Figure 1 is the method flow chart provided by the embodiment of the present invention.

[0024] Figure 2 It is the system connection block diagram provided by the embodiment of the present invention.

[0025] Figure 3 It is the slope feature diagram of the specific embodiment of the present invention.

[0026] Figure 4 It is the vehicle speed feature diagram of the specific embodiment of the present invention. Specific Embodiments

[0027] To make the objectives, features, and advantages of the present invention more obvious and understandable, the technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in this specific embodiment. Obviously, the embodiments described below are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application.

[0028] As Figure 1 shown, the embodiment of the present invention provides a gearbox selection and matching method, including the following: S1: Collect big data information of the target vehicle model in the market and determine the vehicle driving characteristics; This step specifically includes: S11: Collect the operation data of a set number of target vehicle models in the target market segment; Collect the operation data of a certain number of target vehicle models in the target market segment, covering various types of information on vehicle driving. The data can be obtained through channels such as in-vehicle data acquisition devices, vehicle management systems, and third-party data platforms. The data acquisition time should be representative and can reflect the driving conditions of the vehicle at different times and road conditions. Collect the driving data of multiple taxis on urban roads within a week, including driving time, geographical location, instantaneous vehicle speed, slope of the road section where the vehicle is located, etc.

[0029] S12: Clean the collected original data, organize the cleaned data, and classify and sort the data according to the set slope intervals and vehicle speed intervals; Clean the collected original data to remove incorrect, duplicate, and abnormal data. If there are situations where the vehicle speed is negative or the slope value is significantly unreasonable in the data, it is necessary to verify and process them. Organize the cleaned data, classify it according to slope and vehicle speed, which is convenient for subsequent statistical analysis. Classify and sort the data according to slope intervals (such as 0 - 5%, 5 - 10%, etc.) and vehicle speed intervals (such as 0 - 20 km / h, 20 - 40 km / h, etc.).

[0030] S13: Statistically count the data volume of different slope intervals passed by the vehicle, calculate the proportion of the data volume of each slope interval in the total data volume, and the proportion value constitutes the slope feature; S14: Statistically analyze the data volume of different vehicle speed intervals that the vehicle has traveled through, calculate the proportion of the data volume of each speed interval in the total data volume, and the proportion values constitute the speed characteristics.

[0031] For the slope characteristic H, statistically analyze the data volume of different slope intervals that the vehicle has traveled through, calculate the proportion of the data volume of each slope interval in the total data volume, and obtain the proportion distribution of different slopes. Suppose it is calculated that the data volume in the slope interval of 0 - 5% accounts for 30% of the total data volume, and the interval of 5% - 10% accounts for 20%, etc. These proportion values constitute the slope characteristic H. For the speed characteristic V, similarly statistically analyze the proportion of the data volume of different speed intervals. If the data volume in the speed interval of 0 - 20 km / h accounts for 40% of the total data volume, and the interval of 20 - 40 km / h accounts for 30%, etc., these proportion values are the speed characteristic V.

[0032] In a specific embodiment, big data information of 476 target vehicles with 570 horsepower operating for one month in the scenario of the long-distance trunk transportation segment market was statistically analyzed, and the proportion distribution of different slopes that the vehicle has traveled through was obtained (such as Figure 3 ), and the proportion distribution of different vehicle speeds that the vehicle has traveled through was obtained (such as Figure 4 ).

[0033] S2: Combine the vehicle running characteristics of different dimensions to form the common operating points of the vehicle; In a specific embodiment, this step includes: The proportion in the range of slope -1% to 1% reaches more than 80%, which belongs to the main proportion range. Considering that the downhill state is not the main fuel consumption state, finally 0%, 0.5%, and 1% are determined as the common slope points. The proportion in the range of vehicle speed 70 km / h to 95 km / h reaches more than 60%, which belongs to the main proportion range. Finally, 70 km / h, 75 km / h, 80 km / h, 85 km / h, 90 km / h, and 95 km / h are determined as the common vehicle speed points. The combined common operating points are shown in Table 1.

[0034] Table 1: Table of common operating points

[0035] S3: Statistically analyze the sampling data of different common operating points, calculate the relative proportion of each common operating point among all common operating points, and obtain the weight coefficients of each common operating point; This step specifically includes: S31: Statistically analyze the sampling data volume of each common operating point; S32: Sum up the sampling data quantities of each common operating point obtained statistically to obtain the total sampling data quantity of all common operating points; S33: Respectively use each common operating point Sampling data volume Divide by the total number N of sampling data at all common operating conditions to obtain the relative proportion of each common operating condition among all common operating conditions, that is, the weight coefficient of this common operating condition ; Calculation formula: , where ; S34: Obtain the weight coefficients of each common operating condition .

[0036] The sum of the total number of sampling data at common operating conditions is 6,524,691. The relative proportions of each common operating condition are calculated to obtain the weight coefficients as shown in Table 2

[0037] Table 2: Weight coefficient table

[0038] S4: Based on the relevant parameters of the target vehicle model, calculate the minimum fuel consumption values of each candidate transmission at each common operating condition respectively In this step, import the relevant parameters of the target vehicle model into the fuel consumption calculation module, calculate the fuel consumption values of the highest gear and the second highest gear of each candidate transmission at the common operating conditions respectively, and take the lower fuel consumption value of the two gears as the minimum fuel consumption value of this transmission at this common operating condition. The specific calculation process of the fuel consumption calculation module for calculating the fuel consumption value can be calculated by the calculation method of existing vehicles

[0039] In a specific embodiment, import the engine universal characteristic data table of the target vehicle model, the main reduction ratio of the drive axle, the tire rolling radius, the vehicle's different slope - vehicle speed driving resistance table, and the gear ratios of each gear of the candidate transmissions G1, G2, G3, G4, G5, etc. The highest / second highest gear fuel consumption is calculated by finding the corresponding gear ratio and driving resistance in the vehicle model parameters and finally back - calculating to the engine universal characteristics. The minimum fuel consumption values at each common operating condition are marked with a gray background color, as shown in Table 3

[0040] Table 3: Fuel consumption table for each operating condition

[0041] S5: Use the weight coefficients to weighted - correct the minimum fuel consumption values of each candidate transmission at each common operating condition respectively, obtain the comprehensive fuel consumption results of each candidate transmission, and select the transmission with the smallest comprehensive fuel consumption as the optimal performance selection result

[0042] This step specifically includes: S51: For each candidate transmission , calculate the comprehensive fuel consumption of this candidate transmission according to the weighted summation formula ; Weighted summation formula: , is the The weight coefficient of a common operating condition point is the lowest fuel consumption value of the th candidate transmission at the th common operating condition point, where is the total number of candidate transmissions, and is the total number of common operating condition points; S52: Compare the comprehensive fuel consumption of each candidate transmission calculated to obtain the minimum value of the comprehensive fuel consumption;

[0043] In a specific embodiment, this step uses the weight coefficient to perform a weighted sum of the lowest fuel consumption values at each common operating condition point to obtain the comprehensive fuel consumption results of each candidate transmission, and identifies the G5 transmission as the optimal selection, as shown in Table 4.

[0044] Table 4: Comprehensive fuel consumption table

[0045] In some embodiments, the steps of combining the vehicle driving characteristics in different dimensions to form the common operating condition points of the vehicle include: S21: Analyze the proportion distribution of different slopes in the slope characteristics, obtain the slope intervals with a proportion greater than the first proportion threshold, and determine the slope point range with the main proportion as the slope intervals with a proportion exceeding the first proportion threshold; For example, through statistical analysis, it is found that the proportion of slopes in the range of 0 - 5% is 30%, the proportion of slopes in the range of 5 - 10% is 20%, the proportion of slopes in the range of 15 - 20% is 8%, and the proportion of other slope intervals is less than 5%. Then, the slope point range with the main proportion can be determined as the intervals of 0 - 5%, 5 - 10%, and 15 - 20%.

[0046] S22: Analyze the proportion distribution of different vehicle speeds in the vehicle speed characteristics, obtain the vehicle speed intervals with a proportion greater than the second proportion threshold, and determine the vehicle speed point range with the main proportion as the vehicle speed intervals with a proportion exceeding the second proportion threshold; For example, if the proportion of vehicle speeds in the range of 0 - 20 km / h is 40%, the proportion of vehicle speeds in the range of 20 - 40 km / h is 30%, and the proportion of vehicle speeds in the range of 60 - 80 km / h is 15%, then the vehicle speed point range with the main proportion is the intervals of 0 - 20 km / h, 20 - 40 km / h, and 60 - 80 km / h.

[0047] S23: Select the interval according to the slope point range with the main proportion and the vehicle speed point range with the main proportion; The selection of the interval needs to comprehensively consider the precision requirements of the data and the computational complexity. If the interval is too small, it will lead to an excessive number of common operating condition points, increasing the workload of subsequent calculations; if the interval is too large, some important operating condition information may be lost.

[0048] For example, for the slope range of 0 - 5%, the interval can be selected as 1%, then the common slope points can be determined as 1%, 2%, 3%, 4%; for the vehicle speed range of 0 - 20 km / h, the interval is selected as 5 km / h, and the common vehicle speed points are 5 km / h, 10 km / h, 15 km / h.

[0049] S24: Within the slope point range with the main proportion and the vehicle speed point range with the main proportion, determine the common slope points and common vehicle speed points according to the selected interval; S25: Pair and combine the determined common slope points and common vehicle speed points to form the common operating condition points of the whole vehicle with slope-vehicle speed characteristics; among them, each combination corresponds to a specific common operating condition point.

[0050] For example, if the common slope points are 1% and 2%, and the common vehicle speed points are 5 km / h and 10 km / h, then the formed common operating condition points are (1%, 5 km / h), (1%, 10 km / h), (2%, 5 km / h), (2%, 10 km / h), which are marked as C1, C2, C3, C4 in sequence.

[0051] In some embodiments, the method further includes: S6: Analyze the fuel consumption results of the selected optimal transmission, and extract the relationship between the best economic shift point and the common operating condition points according to the distribution of the lower fuel consumption values in the highest gear and the second highest gear.

[0052] The specific steps include: S61: For each common operating condition point , compare the fuel consumption of the highest gear and the fuel consumption of the second highest gear ; If , mark the highest gear as the low fuel consumption gear at this operating condition point; If , then mark the second highest gear as the low fuel consumption gear; S62: According to the marking results, find the common operating condition points where the low fuel consumption gear changes from the highest gear to the second highest gear, or from the second highest gear to the highest gear, and record them as shift transition points; S63: For each shift transition point, obtain the adjacent common operating points with different gear marks and a fuel consumption difference greater than the set threshold, and record them as shift boundary operating points; S64: Based on the slope and vehicle speed information of the shift boundary operating points, obtain the relationship between the optimal economic shift points and the common operating points.

[0053] In a specific embodiment, this step includes: According to the fuel consumption results in Table 3, for the G5 transmission, when the slope is 0%, the fuel consumption is lower in the second highest gear at a vehicle speed of 70 km / h, and the fuel consumption is lower in the highest gear at a vehicle speed of 75 km / h to 95 km / h. When the slope of the G5 transmission is 0.5%, the fuel consumption is lower in the second highest gear at a vehicle speed of 70 km / h to 90 km / h, and the fuel consumption is lower in the highest gear at a vehicle speed of 95 km / h. When the slope of the G5 transmission is 1%, the fuel consumption is always lower in the second highest gear. Therefore, the position of the optimal economic shift point is between 70 km / h and 75 km / h at a slope of 0%, between 90 km / h and 95 km / h at a slope of 0.5%, and maintaining the second highest gear at a slope of 1%, at the position of the bold curve in Table 5.

[0054] Table 5: Table of Optimal Economic Shift Point Positions

[0055] As Figure 2 shown, an embodiment of the present invention further provides a transmission selection and matching system, including a big data analysis module, a common operating point generation module, a weight coefficient calculation module, a fuel consumption calculation module, and a correction processing module; The big data analysis module is used to collect big data information of the target vehicle model in the market and determine the vehicle driving characteristics; The common operating point generation module is used to combine the vehicle driving characteristics in different dimensions to form vehicle common operating points; The weight coefficient calculation module is used to statistically analyze the sampling data of different common operating points, calculate the relative proportion of each common operating point among all common operating points, and obtain the weight coefficients of each common operating point; The fuel consumption calculation module is used to calculate the minimum fuel consumption values of each candidate transmission at each common operating point based on the relevant parameters of the target vehicle model; The correction processing module is used to weightedly correct the minimum fuel consumption values of each candidate transmission at each common operating point with the weight coefficients, obtain the comprehensive fuel consumption results of each candidate transmission, and select the transmission with the minimum comprehensive fuel consumption as the optimal performance selection result.

[0056] In some embodiments, the vehicle driving characteristics include slope characteristics and vehicle speed characteristics; the big data analysis module is specifically configured to collect the operation data of a set number of target vehicle models in the target market segment; clean the collected raw data, organize the cleaned data, and classify the data according to the set slope intervals and vehicle speed intervals; count the data volume of different slope intervals passed by the vehicle, calculate the proportion of the data volume of each slope interval in the total data volume, and the proportion value constitutes the slope characteristics; count the data volume of different vehicle speed intervals passed by the vehicle, calculate the proportion of the data volume of each vehicle speed interval in the total data volume, and the proportion value constitutes the vehicle speed characteristics.

[0057] In some embodiments, the common operating point generation module is specifically configured to analyze the proportion distribution of different slopes in the slope characteristics, obtain the slope intervals with a proportion greater than the first proportion threshold, and determine the slope point range with the main proportion as the slope intervals with a proportion exceeding the first proportion threshold; analyze the proportion distribution of different vehicle speeds in the vehicle speed characteristics, obtain the vehicle speed intervals with a proportion greater than the second proportion threshold, and determine the vehicle speed point range with the main proportion as the vehicle speed intervals with a proportion exceeding the second proportion threshold; select an interval amount according to the slope point range with the main proportion and the vehicle speed point range with the main proportion; within the slope point range with the main proportion and the vehicle speed point range with the main proportion, determine the common slope points and common vehicle speed points according to the selected interval amount; pair and combine the determined common slope points and common vehicle speed points to form the common operating points of the whole vehicle with slope-vehicle speed characteristics; where each combination corresponds to a specific common operating point.

[0058] In some embodiments, the weight coefficient calculation module is specifically configured to count the sampling data volume of each common operating point; sum up the sampling data quantities of each common operating point obtained by statistics to obtain the total sampling data quantity of all common operating points; divide the sampling data volume of each common operating point by the total sampling data quantity N of all common operating points to obtain the relative proportion of each common operating point among all common operating points, that is, the weight coefficient of the common operating point ; calculation formula: ; where, ; obtain the weight coefficients of each common operating point

[0059] In some embodiments, the fuel consumption calculation module is specifically configured to calculate the fuel consumption values of the highest gear and the second highest gear of each candidate transmission at the common operating points respectively based on the relevant parameters of the target vehicle model; select the lower fuel consumption value between the highest gear and the second highest gear as the lowest fuel consumption value of the transmission at the common operating point.

[0060] In some embodiments, the correction processing module is specifically configured to process each candidate transmission , calculate the comprehensive fuel consumption of the to-be-selected transmission according to the weighted summation formula ; Weighted summation formula: , is the weight coefficient of the -th common operating point, is the minimum fuel consumption value of the -th to-be-selected transmission at the -th common operating point, , , is the total number of to-be-selected transmissions, is the total number of common operating points; Compare the comprehensive fuel consumption to of each calculated to-be-selected transmission, and obtain the minimum value of the comprehensive fuel consumption; According to the minimum value of the comprehensive fuel consumption, determine the to-be-selected transmission with the minimum comprehensive fuel consumption, and this transmission is the optimal performance selection result.

[0061] In some embodiments, the system further includes a shift point generation module, which is used to analyze the fuel consumption results of the selected optimal transmission, and extract the relationship between the best economic shift point and the common operating points according to the distribution of the lower fuel consumption values between the highest gear and the second highest gear.

[0062] In some embodiments, the method further includes: a shift point generation module, which is specifically used for each common operating point , compare the fuel consumption of the highest gear and the fuel consumption of the second highest gear; If , mark the highest gear as the low fuel consumption gear at this operating point; If , then mark the second highest gear as the low fuel consumption gear; According to the marking results, find the common operating points where the low fuel consumption gear changes from the highest gear to the second highest gear, or from the second highest gear to the highest gear, and record them as shift transition points; For each shift transition point, obtain its adjacent common operating points with different gear markings and a fuel consumption difference greater than the set threshold, and record them as shift boundary operating points; According to the slope and vehicle speed information of the shift boundary operating points, obtain the relationship between the best economic shift point and the common operating points.

[0063] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A gearbox selection and matching method, characterized in that: The steps include: Collect big data information of target models in the market and determine the driving characteristics of the whole vehicle; Combine vehicle driving characteristics of different dimensions to form common vehicle operating points; The sampling data of different common operating points are counted, and the relative proportion of each common operating point in all common operating points is calculated to obtain the weight coefficient of each common operating point; Based on the relevant parameters of the target vehicle model, the minimum fuel consumption value of each candidate transmission under each common operating point is calculated respectively; The weight coefficient is used to perform weighted correction on the minimum fuel consumption value of each candidate gearbox under each common operating point to obtain the comprehensive fuel consumption results of each candidate gearbox, and the gearbox with the smallest comprehensive fuel consumption is selected as the optimal performance model result.

2. The gearbox selection and matching method according to claim 1, characterized in that: The vehicle driving characteristics include slope characteristics and vehicle speed characteristics; The steps of collecting big data information of the target vehicle model in the market and determining the driving characteristics of the whole vehicle include: Collect operating data of a set number of target models in target market segments; Clean the collected raw data, organize the cleaned data, and classify the data according to the set slope range and vehicle speed range; Count the data volume of different slope intervals that the vehicle has traveled, and calculate the proportion of the data volume of each slope interval to the total data volume. The proportion value constitutes the slope feature; The data volume of different speed intervals traveled by the vehicle is counted, and the proportion of the data volume of each speed interval to the total data volume is calculated. The proportion value constitutes the vehicle speed feature.

3. The gearbox selection and matching method according to claim 2, characterized in that: The steps of combining vehicle driving characteristics of different dimensions to form common vehicle operating points include: Analyze the distribution of proportions of different slopes in the slope characteristics, obtain the slope interval whose proportion is greater than the first proportion threshold, and determine the slope interval whose proportion exceeds the first proportion threshold as the slope point range of the main proportion; Analyze the distribution of proportions of different vehicle speeds in the vehicle speed characteristics, obtain a vehicle speed interval whose proportion is greater than a second proportion threshold, and determine the vehicle speed interval whose proportion exceeds the second proportion threshold as a vehicle speed point range of a main proportion; The interval is selected according to the range of the slope points that account for the majority and the range of the vehicle speed points that account for the majority; Within the range of the main proportion of the slope points and the range of the main proportion of the vehicle speed points, the common slope points and the common vehicle speed points are determined according to the selected interval amount; The determined common slope points and common vehicle speed points are paired and combined to form common operating points of the whole vehicle with slope-vehicle speed characteristics; wherein each combination corresponds to a specific common operating point.

4. The gearbox selection and matching method according to claim 3, characterized in that: The steps of statistically analyzing the sampling data of different common operating points, calculating the relative proportion of each common operating point in all common operating points, and obtaining the weight coefficient of each common operating point include: Count the amount of sampled data at each common operating point; The number of sampling data of each common operating point obtained by statistics is summed up to obtain the total number of sampling data of all common operating points; Use each common operating point separately The amount of sampled data Divide by the total number of sampled data of all common operating points N to obtain the relative proportion of each common operating point in all common operating points, that is, the weight coefficient of the common operating point ; Calculation formula: ,in, ; Get the weight coefficient of each common working point .

5. The gearbox selection and matching method according to claim 4, characterized in that: Based on the relevant parameters of the target vehicle model, the steps of respectively calculating the minimum fuel consumption value of each candidate transmission under each common operating point include: Based on the relevant parameters of the target vehicle model, the fuel consumption values ​​of the highest gear and the second highest gear of each candidate transmission under common operating conditions are calculated respectively; The lower fuel consumption value between the highest gear and the second highest gear is selected as the minimum fuel consumption value of the gearbox under the common operating point.

6. The gearbox selection and matching method according to claim 5, characterized in that: The steps of weighting and correcting the minimum fuel consumption values ​​of each candidate gearbox under each common operating point by using the weight coefficient to obtain the comprehensive fuel consumption results of each candidate gearbox, and selecting a gearbox with the minimum comprehensive fuel consumption as the optimal performance model result include: For each candidate transmission , calculate the comprehensive fuel consumption of the candidate gearbox according to the weighted summation formula ; Weighted summation formula: , It is The weight coefficient of the commonly used operating points is: It is The gearbox to be selected is The lowest fuel consumption value under common operating conditions, , , is the total number of gearboxes to be selected, is the total number of commonly used operating points; The comprehensive fuel consumption of each candidate gearbox is calculated arrive Compare and obtain the minimum value of comprehensive fuel consumption; According to the minimum value of comprehensive fuel consumption, determine the candidate gearbox with the minimum comprehensive fuel consumption, and this gearbox is the optimal performance selection result.

7. The gearbox selection and matching method according to claim 6, characterized in that: The method also includes: analyzing the fuel consumption results of the selected optimal gearbox, and extracting the relationship between the best economic shift point and the common operating point according to the distribution of the lower fuel consumption value in the highest gear and the second highest gear.

8. The gearbox selection and matching method according to claim 7, characterized in that: The method further includes: analyzing the fuel consumption result of the selected optimal gearbox, and extracting the relationship between the best economic shift point and the common operating point according to the distribution of the lower fuel consumption value in the highest gear and the second highest gear, including: For each common operating point , compare the highest gear fuel consumption and the second highest gear fuel consumption size; like , marking the highest gear at this operating point as the low fuel consumption gear; like , then the second highest gear is marked as the low fuel consumption gear; According to the marking results, find the common operating point where the low fuel consumption gear changes from the highest gear to the second highest gear, or from the second highest gear to the highest gear, and record it as the gear shift transition point; For each gear shift transition point, the adjacent common operating condition points with different gear position marks and fuel consumption difference greater than a set threshold are recorded as gear shift boundary operating condition points; According to the slope and vehicle speed information of the shift boundary operating point, the relationship between the best economic shift point and the common operating point is obtained.

9. A gearbox selection and matching system, characterized in that: It includes big data analysis module, common operating point generation module, weight coefficient calculation module, fuel consumption calculation module and correction processing module; Big data analysis module, used to collect big data information of target models in the market and determine the driving characteristics of the whole vehicle; Common operating point generation module, used to combine vehicle driving characteristics of different dimensions to form common operating points of the vehicle; The weight coefficient calculation module is used to collect statistics on the sampling data of different common working points, calculate the relative proportion of each common working point in all common working points, and obtain the weight coefficient of each common working point; A fuel consumption calculation module is used to calculate the minimum fuel consumption value of each candidate transmission under each common operating point based on the relevant parameters of the target vehicle model; The correction processing module is used to use the weight coefficient to perform weighted correction on the minimum fuel consumption value of each candidate gearbox under each common operating point, obtain the comprehensive fuel consumption results of each candidate gearbox, and select the gearbox with the smallest comprehensive fuel consumption as the optimal performance model result.

10. The gearbox selection and matching system according to claim 9, characterized in that: The system also includes a shift point generation module for analyzing the fuel consumption results of the selected optimal gearbox, and extracting the relationship between the best economic shift point and the common operating point based on the distribution of the lower fuel consumption values ​​in the highest and second highest gears.

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