Transmission load spectrum generation method and device, vehicle and medium

Abstract

The invention relates to the technical field of transmissions, in particular to a transmission load spectrum generation method and device, a vehicle and a medium, and the method comprises the steps: obtaining the environment data and operation data of a plurality of test vehicles; determining a plurality of dimensions of target scenes in the operation process of the corresponding test vehicle according to the environment data, calculating a load spectrum of the corresponding test vehicle according to the operation data, and segmenting the operation data into a plurality of scene fragment data according to the plurality of dimensions of target scenes; and determining a test score corresponding to the test vehicle according to the load spectrum of the test vehicle and the corresponding multiple scene fragment data, selecting a target test vehicle from the multiple test vehicles according to the test score, and generating a load spectrum of the transmission according to the load spectrum of each scene fragment data of the target test vehicle. Therefore, the problems of limited number of tested vehicles, insufficient scene representativeness, single driving style, high cost and the like in related technologies are solved.

Description

Technical Field

[0001] The present application relates to the technical field of transmissions, and in particular to a method, device, vehicle and medium for generating a transmission load spectrum. Background Art

[0002] In the process of vehicle product definition, the reliability index of the power transmission system module occupies a crucial position. The vehicle B10 life index requires that core modules such as the engine, transmission and axle achieve equal life design to ensure the long-term stable operation of the vehicle. In order to accurately obtain load spectrum data, these data are not only important inputs for the development and design of the transmission module, but also indispensable indicators for product definition.

[0003] However, the traditional method collects load spectrum data by arranging multiple sensors on limited test vehicles. This method not only lacks representativeness of samples, but is also limited by the driving styles of a few drivers, making it difficult to fully reflect the complex and changeable actual user driving habits and road scenes. This limitation results in the lack of comprehensiveness, accuracy and authenticity of the collected load spectrum data, which in turn affects the design quality of the transmission module and the overall reliability of the product. Summary of the invention

[0004] The present application provides a transmission load spectrum generation method, device, vehicle and medium to solve the problems in the related art such as limited number of test vehicles, insufficient scene representativeness, single driving style and high cost.

[0005] A first aspect embodiment of the present application provides a method for generating a transmission load spectrum, comprising the following steps: acquiring environmental data and operating data of each of a plurality of test vehicles; determining target scenarios of multiple dimensions during the operation of the corresponding test vehicles based on the environmental data, calculating the load spectrum of the corresponding test vehicle based on the operating data, and dividing the operating data into multiple scene segment data based on the target scenarios of the multiple dimensions; determining a test score of the corresponding test vehicle based on the load spectrum of the test vehicle and the corresponding multiple scene segment data, selecting a target test vehicle from the multiple test vehicles based on the test score, and generating a load spectrum of the transmission based on the load spectrum of each scene segment data of the target test vehicle.

[0006] Optionally, a test score of a corresponding test vehicle is determined based on the load spectrum of the test vehicle and the corresponding multiple scene fragment data, including: determining the load spectrum of each scene fragment data based on the load spectrum of the test vehicle and the corresponding multiple scene fragment data; performing equal load interval equal damage transformation on the load spectrum of each scene fragment data of each test vehicle, and calculating the test score of each scene fragment data based on the transformed value; and calculating the test score of the corresponding test vehicle based on the test score of each scene fragment data.

[0007] Optionally, the load spectrum of each scene segment data of each test vehicle is converted into equal damage in equal load intervals, including: determining an SN curve for equal damage conversion in equal load intervals according to the target gear; and converting the load spectrum of each scene segment data into equal damage in equal load intervals according to the SN curve.

[0008] Optionally, segmenting the operation data into a plurality of scene fragment data according to target scenes of multiple dimensions includes: determining segmentation priorities of the target scenes of multiple dimensions; and segmenting the operation data in sequence according to the segmentation priorities to obtain a plurality of scene fragment data.

[0009] Optionally, after generating the load spectrum of the transmission according to the load spectrum of each scene segment data of the target test vehicle, it also includes: setting the user's driving habit scenario; and optimizing the load spectrum of the transmission according to the driving habit scenario.

[0010] Optionally, after generating the load spectrum of the transmission according to the load spectrum of each scene segment data of the target test vehicle, the method further includes: determining a life mileage design scheme of the transmission according to the load spectrum of the transmission.

[0011] Optionally, the load spectrum includes at least one of a vehicle torque load spectrum, a vehicle damage load spectrum, and a vehicle rotation number load spectrum.

[0012] A second aspect of the present application provides a transmission load spectrum generating device, including: an acquisition module, used to acquire environmental data and operating data of each of multiple test vehicles; a processing module, used to determine target scenarios of multiple dimensions during the operation of the corresponding test vehicles based on the environmental data, calculate the load spectrum of the corresponding test vehicle based on the operating data, and divide the operating data into multiple scene segment data based on the target scenarios of multiple dimensions; a generation module, used to determine a test score of the corresponding test vehicle based on the load spectrum of the test vehicle and the corresponding multiple scene segment data, select a target test vehicle from the multiple test vehicles based on the test score, and generate a transmission load spectrum based on the load spectrum of each scene segment data of the target test vehicle.

[0013] A third aspect of the present application provides a vehicle, the vehicle comprising a transmission, the transmission being designed based on a transmission load spectrum generated by a transmission load spectrum generation method as described in the above embodiment.

[0014] A fourth aspect of the present application provides a computer-readable storage medium having a computer program stored thereon, the program being executed by a processor to implement a transmission load spectrum design generated by the transmission load spectrum generation method of the above embodiment.

[0015] Therefore, this application includes the following beneficial effects:

[0016] The embodiments of the present application obtain and analyze the environmental data of the test vehicle to achieve accurate identification of multi-dimensional complex scenes, thereby improving the comprehensiveness and meticulousness of vehicle performance evaluation. Use these data to calculate the load spectrum, gain an in-depth understanding of the stress conditions of vehicle components, and lay the foundation for durability testing and design optimization. By segmenting the scene fragment data, the data is easier to analyze for specific scenarios. Combine the load spectrum and scenario data to develop a scientific test scoring system to ensure the effectiveness and pertinence of the test. Select the optimal test vehicle based on the score, and accurately generate the transmission load spectrum to support the durability test, performance evaluation and design optimization of the transmission, which not only improves the representativeness and credibility of the test, but also reduces the test cost and time. As a result, technical problems such as the limited number of test vehicles, insufficient scene representativeness, single driving style and high cost in related technologies are solved.

[0017] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0019] Figure 1 A flow chart of a transmission load spectrum generating method provided according to an embodiment of the present application;

[0020] Figure 2 A schematic diagram of fragment evaluation provided according to an embodiment of the present application;

[0021] Figure 3 A schematic diagram of gear ratios provided according to an embodiment of the present application;

[0022] Figure 4 A schematic diagram of a cycle counting method provided according to an embodiment of the present application;

[0023] Figure 5 This is an example diagram of a transmission load spectrum generating device provided according to an embodiment of the present application;

[0024] Figure 6 It is a schematic diagram of the structure of a vehicle provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0025] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0026] The following describes the transmission load spectrum generation method, device, vehicle and medium of the embodiment of the present application with reference to the accompanying drawings. In view of the problem that the load spectrum mentioned in the above background technology cannot cope with complex scenes, the present application provides a transmission load spectrum generation method, in which the environmental data of the test vehicle is obtained and analyzed to achieve accurate identification of multi-dimensional complex scenes, thereby improving the comprehensiveness and meticulousness of vehicle performance evaluation. The load spectrum is calculated using these data to gain an in-depth understanding of the stress conditions of vehicle components, laying the foundation for durability testing and design optimization. By segmenting the scene fragment data, the data is easier to analyze for specific scenes. Combined with the load spectrum and scene data, a scientific test scoring system is formulated to ensure the effectiveness and pertinence of the test. The optimal test vehicle is selected based on the score, and the transmission load spectrum is accurately generated to support the durability test, performance evaluation and design optimization of the transmission, which not only improves the representativeness and credibility of the test, but also reduces the test cost and time. As a result, the problems of limited number of test vehicles, insufficient scene representativeness, single driving style and high cost in the related technology are solved.

[0027] Specifically, Figure 1 A schematic flow chart of a transmission load spectrum generating method provided in an embodiment of the present application.

[0028] like Figure 1 As shown, the transmission load spectrum generating method includes the following steps:

[0029] In step S101 , environmental data and operating data of each of a plurality of test vehicles are obtained.

[0030] Among them, environmental data may include altitude, longitude, latitude, atmospheric temperature and pressure, etc., and operating data may include vehicle speed, mileage, engine speed and load, throttle, reference torque, effective torque percentage, friction torque percentage, braking and clutch status, etc.

[0031] It can be understood that the embodiments of the present application can obtain the operating data of multiple test vehicles under different environments, so as to have a more comprehensive understanding of the performance of the vehicle under different conditions, thereby facilitating subsequent data analysis.

[0032] It should be noted that the operation data needs to be processed, where the data processing includes stationarity testing and calculation;

[0033] Specifically, the engine torque is:

[0034] Torque=Treference*(Prealratio-Pfrictionratio) / 10

[0035] Wherein, Treference is the engine reference torque, Prealratio is the engine effective torque percentage, and Pfrictionratio is the friction torque percentage;

[0036] The transmission ratio is:

[0037] i g =0.377*r*n / (i0*U a )

[0038] Among them, r is the tire rolling radius, n is the engine speed, i0 is the rear axle speed ratio, U a is the vehicle speed, i g is the transmission ratio;

[0039] The rolling radius of the tire is:

[0040] r=F*d / (2*Pi)

[0041] Where F is the coefficient, d is the total design diameter of the tire, and Pi is the pi;

[0042] The transmission output torque is:

[0043] M out =Torque*i g *η g

[0044] Among them, η g is the transmission efficiency;

[0045] The transmission output speed is:

[0046] n g =n / i g

[0047] Where n is the engine speed.

[0048] In step S102, target scenes of multiple dimensions during the operation of the corresponding test vehicle are determined according to the environmental data, a load spectrum of the corresponding test vehicle is calculated according to the operation data, and the operation data is divided into multiple scene segment data according to the target scenes of multiple dimensions.

[0049] Among them, the target scene may include a landform scene and a road category scene, wherein the landform scene may include a plain scene, a hilly scene, a mountainous scene and a plateau scene, the road category scene may include a highway scene, a provincial road scene, an urban road scene and a rural road scene, and the load spectrum may include at least one of a vehicle torque load spectrum, a vehicle damage load spectrum and a vehicle rotation number load spectrum, wherein the load spectrum obtains at least one of a vehicle torque load spectrum, a vehicle damage load spectrum and a vehicle rotation number load spectrum based on a data processing program.

[0050] It is understandable that, by integrating environmental data, the embodiments of the present application accurately divide multiple dimensional target scenarios during the operation of the test vehicle, calculate the load spectrum based on the operation data, and further refine the operation data into multiple scenario segment data, realizing the refinement processing of the data, thereby improving the accuracy of vehicle performance analysis.

[0051] Specifically, the torque load spectrum of the test vehicle is:

[0052]

[0053] Wherein, i is the vehicle code, n is the number of load levels, g is the number of transmission gears, and Ti is the torque load spectrum of the i-th vehicle;

[0054] The segment damage load spectrum of the test vehicle is:

[0055]

[0056] Wherein, Li is the segment damage load spectrum of the i-th vehicle;

[0057] The rotation cycle load spectrum of the test vehicle is:

[0058]

[0059] Wherein, Ci is the rotation cycle load spectrum of the i-th vehicle.

[0060] It should be noted that in the classification of landform scenarios, it is set that the average altitude h < a of the vehicle is plain, a ≤ h < b is hilly, h > b is mountainous, and h > c is plateau. Among them, based on the mileage dimension, the landform proportion distribution of the selected time period of the transmission-matched vehicle of this type is obtained, as shown in Table 1 below.

[0061] Table 1 Landform Scenario Distribution

[0062] Serial number vehicle Plains hills Mountain area plateau 1 S1 80％ 20％ 0％ 0％ 2 S2 7％ 34％ 59％ 0％ … … … … … …

[0063] Based on the landform scenario data of the test vehicle, the landform scenario distribution based on mileage is determined as:

[0064]

[0065] Wherein, j is the segment code and m is the total number of segments.

[0066] The landform scenario distribution of the test vehicle is shown in Table 2 below.

[0067] Table 2 Landform Scenario Distribution of Test Vehicle

[0068] Number of vehicles Plains hills Mountain area plateau Sample size S or larger 45％ 20％ 20％ 15％ mileage … … … …

[0069] In the road category scene classification, the road proportion distribution of this type of transmission matching vehicle in the selected time period is obtained based on the mileage dimension, as shown in Table 3 below.

[0070] Table 3 Distribution of road category scenes

[0071] Serial number vehicle high speed national highway Provincial Highway Urban roads Country Road 1 S1 80％ 15％ 0％ 5％ 0％ 2 S2 0％ 60％ 20％ 0％ 20％ … … … … … … …

[0072] According to the road category data of the test vehicle, the road category scene distribution based on mileage is determined as follows:

[0073]

[0074] The distribution of road category scenarios for the test vehicles is shown in Table 4 below.

[0075] Table 4 Road category scene distribution of test vehicles

[0076] Number of vehicles high speed national highway Provincial Highway Urban roads Country Road Sample size S or larger 30％ 30％ 10％ 10％ 20％ mileage … … … … …

[0077] In an embodiment of the present application, the operation data is divided into multiple scene fragment data according to the target scenes of multiple dimensions, including: determining the segmentation priority of the target scenes of multiple dimensions; and segmenting the operation data in turn according to the segmentation priority to obtain multiple scene fragment data.

[0078] It can be understood that the embodiment of the present application optimizes the allocation of test resources by setting segmentation priorities, ensuring that high-impact scenarios are given priority, thereby improving the efficiency of testing and analysis, not only speeding up problem identification, but also providing accurate data support for decision-making.

[0079] In step S103, a test score of the corresponding test vehicle is determined based on the load spectrum of the test vehicle and the corresponding multiple scene segment data, a target test vehicle is selected from the multiple test vehicles based on the test score, and a load spectrum of the transmission is generated based on the load spectrum of each scene segment data of the target test vehicle.

[0080] It can be understood that the embodiment of the present application determines the test score by comprehensively evaluating the load spectrum and scene clip data of the test vehicle, and accurately selects the target test vehicle based on this, which helps to more accurately reflect the actual performance level of the vehicle. The transmission load spectrum generated based on the scene clip data load spectrum of the target test vehicle provides more detailed and accurate data support for the design and optimization of the transmission, which helps to improve the performance and service life of the transmission.

[0081] Specifically, taking the vehicle evaluation value formation process as an example, the load spectrum evaluation value under the terrain scene and road category characteristics, such as Figure 2 As shown, G ixp, where i is the i-th vehicle, x is the landform number, where x=1 is a plain, x=2 is a hill, x=3 is a mountainous area, x=4 is a plateau, and p is the segment number, where p can be 1, 2, … j, j+1; R iyp , where y is a numbered road, y=1 is a highway, y=2 is a national road, y=3 is a provincial road, y=4 is an urban road, and y=5 is a rural road.

[0082] By comprehensively considering the evaluation values ​​under each driving scene segment and performing weighted average processing, a comprehensive and objective vehicle evaluation value is obtained, and the target test vehicles are ranked from low to high according to the obtained evaluation value. The higher the evaluation value of the vehicle, the greater the damage it has suffered during the test, and the higher the percentile value of the load distribution;

[0083] The vehicle evaluation value is:

[0084]

[0085] Among them, rankload i is the evaluation value of the load condition of the i-th vehicle, rankload ij is the load condition evaluation value of the jth segment of the i-th vehicle, rankD i is the driving habit scenario evaluation value of the i-th vehicle, rankD ij is the driving habit scene evaluation value of the jth segment of the i-th vehicle, S ij is the mileage of the jth segment of the i-th vehicle, and m is the total number of scene segments of vehicle i;

[0086] Among them, the load condition evaluation value is:

[0087] rankload ij =fscore((Gj,Rj,Dj,Li) ij )

[0088] Among them, (Gj, Rj, Dj, Li) ij is the load spectrum data of the j common gear of the i vehicle segment, Gj is the proportion of landform scenes in the selected time period of the vehicle with the j common gear, Rj is the proportion of roads in the selected time period of the vehicle with the j common gear, and Dj is the proportion of driving habits in the selected time period of the vehicle with the j common gear.

[0089] It should be noted that the load spectra of the commonly used gears in the scene condition segments are compared, and the damage score is defined as high in the same load range, and the evaluation scores are arranged from high to low to obtain the arrangement distribution. Among them, the distribution of commonly used gears, such as Figure 3 As shown, the commonly used gears are 8th and 7th, that is, the gears whose sum of gear mileage accounts for more than 80%.

[0090] The driving habit scenario evaluation values ​​are:

[0091] rankD ij =fscore(D(p) ij )

[0092] Where D(p) ij is the driving habit scene data of vehicle i segment j.

[0093] It should be noted that the scores of the scenes with intense driving of the i-th car are defined as high, and the evaluation scores are obtained, and the evaluation scores are arranged according to the high and low evaluation scores to obtain the arrangement distribution.

[0094] In an embodiment of the present application, a test score of a corresponding test vehicle is determined based on the load spectrum of the test vehicle and the corresponding multiple scene fragment data, including: determining the load spectrum of each scene fragment data based on the load spectrum of the test vehicle and the corresponding multiple scene fragment data; performing equal load interval equal damage conversion on the load spectrum of each scene fragment data of each test vehicle, and calculating the test score of each scene fragment data based on the converted value; and calculating the test score of the corresponding test vehicle based on the test score of each scene fragment data.

[0095] Among them, equal damage conversion in the same load range can be used to convert the load spectrum data recorded by different test vehicles or the same test vehicle in different scene segments according to a unified damage standard or model.

[0096] It can be understood that the embodiment of the present application achieves a refined evaluation of the vehicle under different operating conditions by determining the load spectrum of each scene segment data, performs equal damage conversion and scoring under unified standards, constructs a comprehensive test vehicle performance evaluation system, and improves the accuracy of the evaluation.

[0097] Specifically, the torque load spectrum of the target scene segment data is:

[0098]

[0099] Among them, i is the vehicle code, n is the load level number, g is the number of transmission gears, and j is the code of vehicle i in scene segment j;

[0100] The fragment damage load spectrum of the target scene fragment data is:

[0101]

[0102] The rotation number load spectrum of the target scene segment data is:

[0103]

[0104] In an embodiment of the present application, the load spectrum of each scene segment data of each test vehicle is converted into equal damage in equal load intervals, including: determining an SN curve for equal damage conversion in equal load intervals according to the target gear; and converting the load spectrum of each scene segment data into equal damage in equal load intervals according to the SN curve.

[0105] The target gear refers to the specific gear that the transmission is in during vehicle testing or actual operation.

[0106] It can be understood that the embodiment of the present application can more accurately reflect the stress characteristics and fatigue life of the components under the gear through the specific bending fatigue curve of the target gear, and improve the accuracy of the fatigue life assessment of the vehicle and components through the equivalent damage transformation of the load spectrum.

[0107] Specifically, the damage equivalent conversion formula is:

[0108]

[0109] Among them, S1 is the maximum grade load, S i N is the number of cycles to convert to the maximum load level, N i is the number of cycles of other load levels, and a is the index of the gear S-N fatigue curve;

[0110] The design load spectrum of the transmission is the life mileage corresponding to the maximum torque under the target gear. Therefore, it is necessary to perform equal damage conversion on the load spectrum of each level and uniformly convert each level of load into the life mileage under the maximum level of load. Among them, according to the different failure modes of gears in different target gears, the load spectrum of gear 1 is converted to the maximum load according to the bending fatigue SN curve of the gear, and the load spectra of the remaining gears are converted to the maximum load according to the contact fatigue SN curve of the gear.

[0111] It should be noted that for mechanical transmissions, the life of the transmission depends largely on the life of the gears. Therefore, the load spectrum of the transmission should mainly consider the load spectrum of the gears. When the gears are under load, not all teeth are stressed at the same time. The stress on each tooth is a pulsating cycle. The main factor that causes fatigue damage to the gears is closely related to the stress amplitude of each tooth and the number of cycles.

[0112] The embodiment of the present application uses a cycle counting method to accurately analyze the relationship between load and speed, such as Figure 4As shown. First, the load is finely divided into eight levels. The basis for each level of division is the proportion relative to the maximum load. The specific coefficients are set to 0.125, 0.275, 0.425, 0.575, 0.725, 0.85, 0.95 and up to 1. Each level of load is accurately matched with the corresponding speed information. Further, according to the continuous action time of each level of load in the actual working condition and the corresponding speed information in this time period, the number of cycles of each level of load is accurately calculated:

[0113]

[0114] Among them, Δt1 is the time history of the i-th level load, τ i is the load of the ith level.

[0115] In an embodiment of the present application, after generating the load spectrum of the transmission according to the load spectrum of each scene segment data of the target test vehicle, it also includes: setting the user's driving habit scenario; optimizing the load spectrum of the transmission according to the driving habit scenario.

[0116] Among them, driving habit scenarios may include sudden acceleration, sudden deceleration, long clutching, long braking and number of gear shifting, etc.

[0117] It is understandable that the embodiments of the present application can construct scenarios that conform to the user's actual driving behavior by collecting and analyzing the user's driving habit data. Optimizing the load spectrum of the transmission based on these scenarios can ensure that the transmission is more in line with the user's driving habits in daily driving, reduce unnecessary wear of the transmission caused by differences in driving habits, and extend the service life of the transmission.

[0118] Specifically, based on the load condition evaluation value, the sample of s-sized vehicles or larger vehicles is ranked from high to low. Among them, the three key nodes of the distribution are focused on: the 5% percentile, the median value, and the 95% percentile. Three representative user level categories are divided into the following: the niche user level, which represents users who drive smoothly or have no special needs; the average user level, which reflects the general situation of most drivers; and the aggressive user level, which corresponds to those user groups with more aggressive driving styles and higher requirements for vehicle performance.

[0119] Among them, the distribution of user load conditions of terrain scenes / road categories is:

[0120] min_levelG&R=rankload i (0%…5%…15%)

[0121] ave_levelG&R=rankload i (40%…50%…60%)

[0122] agg_levelG&R=rankload i (80%…95%…100%);

[0123] Similarly, a similar analysis process was performed for the driving habit scenario evaluation values ​​of these vehicles to determine the 5% percentile, median, and 95% percentile values ​​under the driving habit scenario, and the corresponding niche user level, average user level, and aggressive user level were defined accordingly;

[0124] Among them, driving habit scene distribution:

[0125] min_levelD=rankD i (0%…5%…15%)

[0126] ave_levelD=rankD i (40%…50%…60%)

[0127] agg_levelD=rankD i (80%…95%…100%).

[0128] It should be noted that the driving habit scenarios are analyzed according to the number of kilometers per thousand or the proportion to obtain the distribution of transmission matching driving habits, as shown in Table 5 below.

[0129] Table 5 Distribution of driving habit scenarios

[0130] Serial number vehicle Rapid acceleration Rapid deceleration Long time clutch Long brake time Number of gear shifts 1 S1 50 60 100 67 352 … … … … … … …

[0131] In the embodiment of the present application, after generating the load spectrum of the transmission according to the load spectrum of each scene segment data of the target test vehicle, it also includes: determining the life mileage design scheme of the transmission according to the load spectrum of the transmission.

[0132] It is understandable that the embodiments of the present application target different user groups for different requirements on the performance and service life of the transmission. By designing the life mileage of the transmission through the load spectrum of the transmission, the production process and resource allocation of the transmission are rationally planned to avoid unnecessary waste and redundancy, thereby helping to reduce production costs and improve production efficiency.

[0133] Specifically, for a sample of s-trolleys or larger vehicles, an in-depth analysis is conducted based on the B10 design life mileage. According to the definition of the user level, vehicles that meet the average user standard and whose cumulative mileage just reaches the B10 life mileage requirement are selected to obtain the average user level load spectrum based on the actual operating mileage.

[0134] Among them, the average user level load spectrum is:

[0135]

[0136] Among them, (Gj, Rj, Dj, Ti) aveij is the average user load of vehicle segment j in i, and n(ave_level) is the vehicle that meets the average user level;

[0137] Similarly, vehicles that meet the radical user standards and whose cumulative mileage just reaches the B10 life mileage requirement are selected to obtain the radical user level load spectrum based on the actual operating mileage;

[0138] Among them, the horizontal load spectrum of aggressive users is:

[0139]

[0140] Among them, (Gj, Rj, Dj, Ti) aggij is the aggressive user load of vehicle segment j in i, and n(agg_level) is the number of vehicles that meet the aggressive user level.

[0141] According to the transmission load spectrum generation method proposed in the embodiment of the present application, by acquiring and analyzing the environmental data of the test vehicle, accurate identification of multi-dimensional complex scenes is achieved, thereby improving the comprehensiveness and meticulousness of vehicle performance evaluation. Use these data to calculate the load spectrum, and gain an in-depth understanding of the stress conditions of vehicle components, laying the foundation for durability testing and design optimization. By segmenting the scene fragment data, the data is easier to analyze for specific scenarios. Combine the load spectrum and scenario data to develop a scientific test scoring system to ensure the effectiveness and pertinence of the test. Select the optimal test vehicle based on the score, and accurately generate the transmission load spectrum to support the durability test, performance evaluation and design optimization of the transmission, which not only improves the representativeness and credibility of the test, but also reduces the test cost and time. As a result, the problems of limited number of test vehicles, insufficient scene representativeness, single driving style and high cost in related technologies are solved.

[0142] Next, a transmission load spectrum generating device proposed in accordance with an embodiment of the present application will be described with reference to the accompanying drawings.

[0143] Figure 5 It is a block diagram of a transmission load spectrum generating device according to an embodiment of the present application.

[0144] like Figure 5 As shown, the transmission load spectrum generating device 10 includes: an acquisition module 100 , a processing module 200 and a generating module 300 .

[0145] Among them, the acquisition module 100 is used to obtain the environmental data and operating data of each of the multiple test vehicles; the processing module 200 is used to determine the target scenes of multiple dimensions during the operation of the corresponding test vehicle according to the environmental data, calculate the load spectrum of the corresponding test vehicle according to the operating data, and divide the operating data into multiple scene fragment data according to the target scenes of multiple dimensions; the generation module 300 is used to determine the test score of the corresponding test vehicle according to the load spectrum of the test vehicle and the corresponding multiple scene fragment data, select the target test vehicle from the multiple test vehicles according to the test score, and generate the load spectrum of the transmission according to the load spectrum of each scene fragment data of the target test vehicle.

[0146] It should be noted that the above explanations of the embodiment of the transmission load spectrum generating method are also applicable to the transmission load spectrum generating device of this embodiment, and will not be repeated here.

[0147] According to the transmission load spectrum generating device proposed in the embodiment of the present application, by acquiring and analyzing the environmental data of the test vehicle, accurate identification of multi-dimensional complex scenes is achieved, thereby improving the comprehensiveness and meticulousness of vehicle performance evaluation. By using these data to calculate the load spectrum, we can gain an in-depth understanding of the stress conditions of vehicle components and lay the foundation for durability testing and design optimization. By segmenting the scene fragment data, the data is easier to analyze for specific scenarios. Combine the load spectrum and scenario data to develop a scientific test scoring system to ensure the effectiveness and pertinence of the test. Based on the score, the optimal test vehicle is selected, and the transmission load spectrum is accurately generated to support the durability test, performance evaluation and design optimization of the transmission, which not only improves the representativeness and credibility of the test, but also reduces the test cost and time. As a result, the problems of limited number of test vehicles, insufficient scene representativeness, single driving style and high cost in related technologies are solved.

[0148] Figure 6 A schematic diagram of the structure of a vehicle provided in an embodiment of the present application. The vehicle may include a transmission 601.

[0149] The transmission 601 is designed to obtain a transmission load spectrum generated by the transmission load spectrum generation method provided in the above embodiment.

[0150] An embodiment of the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the load spectrum design of the transmission generated by the transmission load spectrum generation method as described above.

[0151] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms are not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0152] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0153] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0154] It should be understood that the various parts of the present application can be implemented in hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, the steps or methods can be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array, a field programmable gate array, etc.

[0155] A person of ordinary skill in the art may understand that all or part of the steps carried by the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the above-mentioned program may be stored in a computer-readable storage medium, which, when executed, includes one of the steps of the method embodiment or a combination thereof.

[0156] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for generating a transmission load spectrum, characterized in that: The following steps are involved: Obtaining environmental data and operating data of multiple test vehicles; Determine target scenes of multiple dimensions during the operation of the corresponding test vehicle according to the environmental data, calculate a load spectrum of the corresponding test vehicle according to the operation data, and divide the operation data into multiple scene segment data according to the target scenes of multiple dimensions; A test score of the corresponding test vehicle is determined according to the load spectrum of the test vehicle and the corresponding multiple scene segment data, a target test vehicle is selected from the multiple test vehicles according to the test score, and a load spectrum of the transmission is generated according to the load spectrum of each scene segment data of the target test vehicle.

2. The transmission load spectrum generating method according to claim 1, characterized in that: The step of determining a test score of the test vehicle according to the load spectrum of the test vehicle and the corresponding plurality of scene segment data comprises: Determining a load spectrum of each scene segment data according to the load spectrum of the test vehicle and the corresponding plurality of scene segment data; Perform equal load range and equal damage transformation on the load spectrum of each scene segment data of each test vehicle, and calculate the test score of each scene segment data according to the transformed value; The test score of the corresponding test vehicle is calculated according to the test score of each scene segment data.

3. The transmission load spectrum generating method according to claim 2, characterized in that: The equal load range equal damage conversion of the load spectrum of each scene segment data of each test vehicle includes: An SN curve for equal-load interval and equal-damage conversion is determined according to the target gear; and an equal-load interval and equal-damage conversion is performed on the load spectrum of each scene segment data according to the SN curve.

4. The transmission load spectrum generating method according to claim 1, characterized in that: The step of dividing the operation data into a plurality of scene segment data according to the target scenes of the plurality of dimensions comprises: Determining the segmentation priorities of the target scenes in the multiple dimensions; The operation data is segmented in sequence according to the segmentation priority to obtain a plurality of scene segment data.

5. The transmission load spectrum generating method according to claim 1, characterized in that: After generating the load spectrum of the transmission according to the load spectrum of each scene segment data of the target test vehicle, the method further includes: Set the user's driving habit scenario; The load spectrum of the transmission is optimized according to the driving habit scenario.

6. The transmission load spectrum generating method according to claim 1 or 5, characterized in that: After generating the load spectrum of the transmission according to the load spectrum of each scene segment data of the target test vehicle, the method further includes: A life mileage design scheme of the transmission is determined according to the load spectrum of the transmission.

7. The transmission load spectrum generating method according to claim 1, characterized in that: The load spectrum includes at least one of a vehicle torque load spectrum, a vehicle damage load spectrum, and a vehicle rotation number load spectrum.

8. A transmission load spectrum generating device, characterized in that: include: An acquisition module, used to acquire environmental data and operating data of each of the multiple test vehicles; A processing module, configured to determine target scenes of multiple dimensions during operation of a corresponding test vehicle according to the environmental data, calculate a load spectrum of the corresponding test vehicle according to the operation data, and divide the operation data into multiple scene segment data according to the target scenes of multiple dimensions; A generation module is used to determine a test score of a corresponding test vehicle based on the load spectrum of the test vehicle and corresponding multiple scene segment data, select a target test vehicle from the multiple test vehicles based on the test score, and generate a load spectrum of the transmission based on the load spectrum of each scene segment data of the target test vehicle.

9. A vehicle, characterized in that: The vehicle comprises a transmission, and the transmission is designed based on a load spectrum of the transmission generated by the transmission load spectrum generating method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program or instruction stored thereon, characterized in that: When the computer program or instruction is executed, the load spectrum design of the transmission generated by the transmission load spectrum generating method according to any one of claims 1 to 7 is obtained.

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