Vehicle performance evaluation method, system and device based on vehicle network data
By obtaining vehicle configuration labels and operation data, classifying and generating evaluation models, the problem that the existing technology is difficult to comprehensively evaluate vehicle performance in complex scenarios is solved, and the dynamic and economic evaluation of the vehicle in a diversified environment is achieved.
Patent Information
- Application Number
- CN202411037100.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-07-31
- Publication Date
- 2024-12-20
AI Technical Summary
The existing vehicle performance evaluation methods are based on a single regulatory cycle or specific use scenarios, making it difficult to achieve full coverage in complex application scenarios, and it is impossible to fully evaluate the operating performance of vehicles in various environments.
By obtaining the configuration labels and operation data of the target vehicle, vehicle classification is carried out, and matching data samples are obtained from the Internet of Vehicles database, power and economic evaluation models are generated, and performance evaluation is performed.
It has achieved a comprehensive assessment of the power and economy of the vehicle in different environments, providing more accurate and comprehensive performance evaluation results, and adapting to diverse application scenarios.
Smart Images
Figure CN119164667A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of engine data processing, and in particular to a vehicle performance evaluation method, system and device based on vehicle network data. Background Art
[0002] The performance of a vehicle is directly related to the customer's benefits. The performance of a vehicle mainly includes power and economy. Power is related to the timeliness of the vehicle, whether there is sufficient power to achieve rapid transportation, and is also related to the user's benefits. The higher the timeliness, the lower the cost per unit time. Economy is directly related to the cost of the user in the process of using the vehicle. In the prior art, the evaluation method of vehicle performance is to verify the performance of the vehicle based on regulatory cycles or specific usage scenarios. However, the verification samples and scenarios are relatively simple, and it is difficult to achieve full coverage in the face of complex vehicle application scenarios. Summary of the invention
[0003] In order to solve the above technical problems, the present application provides a vehicle performance evaluation method, system and device based on vehicle network data, which are used to evaluate the operating performance of the vehicle in various environments.
[0004] The technical solution provided in this application is described below:
[0005] The first aspect of the present application provides a vehicle performance evaluation method based on vehicle network data, comprising:
[0006] Obtain the configuration tags and operating data of the target vehicle;
[0007] determining a vehicle classification of the target vehicle based on the configuration tag and the operating data;
[0008] Acquire an evaluation model according to the vehicle classification;
[0009] The target vehicle is subjected to a performance evaluation according to the evaluation model.
[0010] Optionally, obtaining an evaluation model according to the vehicle classification includes:
[0011] Acquire a target data sample from a vehicle networking database according to the vehicle classification, wherein the target data sample and the target vehicle carry the same configuration tag;
[0012] Screening the target data samples according to a preset period to obtain dynamic effective data and economic effective data;
[0013] The dynamic efficiency data and the economic efficiency data are respectively collected into a sample database;
[0014] The sample database is analyzed according to preset rules to generate an evaluation model.
[0015] Optionally, the performing performance evaluation on the target vehicle according to the evaluation model includes:
[0016] Obtaining the operation record uploaded by the vehicle terminal of the target vehicle through the Internet of Vehicles database;
[0017] Acquiring target parameters required by the evaluation model from the operation record;
[0018] The evaluation model is used to evaluate the performance of the target vehicle on the target parameters.
[0019] Optionally, determining the vehicle classification of the target vehicle according to the configuration tag and the operating data includes:
[0020] Determining the load capacity and engineering purpose of the target vehicle according to the configuration tag;
[0021] determining an operating environment of the target vehicle according to the operating data;
[0022] Acquire vehicle data having the same load capacity and engineering purpose through a vehicle networking database;
[0023] Performing a secondary screening on the vehicle data according to the operating environment to obtain a screening result;
[0024] The screening results are collected and determined as the vehicle classification of the target vehicle.
[0025] Optionally, the evaluation model includes a dynamic evaluation model and an economic evaluation model.
[0026] Optionally, the generation process of the dynamic performance evaluation model includes:
[0027] Acquire the dynamic performance test data of the vehicle type included in the vehicle classification from the vehicle networking database, and confirm the dynamic performance data sample from the dynamic performance test data according to the preset period;
[0028] Performing a dynamic analysis on the dynamic sample data to obtain a dynamic analysis result, wherein the dynamic analysis includes starting acceleration capability and overtaking capability;
[0029] A dynamics evaluation model is generated according to the dynamics analysis results.
[0030] Optionally, the generation process of the economic evaluation model includes:
[0031] Obtaining economic test data of the vehicle types included in the vehicle classification from the Internet of Vehicles database, and confirming economic data samples from the economic test data according to the preset period;
[0032] Performing an economic analysis on the economic sample data to obtain an economic analysis result, wherein the analysis content of the economic analysis includes acceleration capability and fuel consumption;
[0033] An economic evaluation model is generated according to the economic analysis results.
[0034] The second aspect of the present application provides a vehicle performance evaluation system based on vehicle network data, comprising:
[0035] A first acquisition unit, used to acquire a configuration tag and operating data of a target vehicle;
[0036] a determination unit, configured to determine a vehicle classification of the target vehicle according to the configuration tag and the operation data;
[0037] A second acquisition unit, used for acquiring an evaluation model according to the vehicle classification;
[0038] A performance evaluation unit is used to perform performance evaluation on the target vehicle according to the evaluation model.
[0039] Optionally, the second acquiring unit is further used for:
[0040] Acquire a target data sample from a vehicle networking database according to the vehicle classification, wherein the target data sample and the target vehicle carry the same configuration tag;
[0041] Screening the target data samples according to a preset period to obtain dynamic effective data and economic effective data;
[0042] The dynamic efficiency data and the economic efficiency data are respectively collected into a sample database;
[0043] The sample database is analyzed according to preset rules to generate an evaluation model.
[0044] Optionally, the performance evaluation unit is further used for:
[0045] Obtaining the operation record uploaded by the vehicle terminal of the target vehicle through the Internet of Vehicles database;
[0046] Acquiring target parameters required by the evaluation model from the operation record;
[0047] The evaluation model is used to evaluate the performance of the target vehicle on the target parameters.
[0048] Optionally, the determining unit is further configured to:
[0049] Determining the load capacity and engineering purpose of the target vehicle according to the configuration tag;
[0050] determining an operating environment of the target vehicle according to the operating data;
[0051] Acquire vehicle data having the same load capacity and engineering purpose through a vehicle networking database;
[0052] Performing a secondary screening on the vehicle data according to the operating environment to obtain a screening result;
[0053] The screening results are collected and determined as the vehicle classification of the target vehicle.
[0054] Optionally, the performance evaluation unit includes a dynamic evaluation model module and an economic evaluation model module.
[0055] Optionally, the dynamic performance evaluation model module is used to:
[0056] Acquire the dynamic performance test data of the vehicle type included in the vehicle classification from the vehicle networking database, and confirm the dynamic performance data sample from the dynamic performance test data according to the preset period;
[0057] Performing a dynamic analysis on the dynamic sample data to obtain a dynamic analysis result, wherein the dynamic analysis includes starting acceleration capability and overtaking capability;
[0058] A dynamics evaluation model is generated according to the dynamics analysis results.
[0059] Optionally, the economic evaluation model module is used to:
[0060] Obtaining economic test data of the vehicle types included in the vehicle classification from the Internet of Vehicles database, and confirming economic data samples from the economic test data according to the preset period;
[0061] Performing an economic analysis on the economic sample data to obtain an economic analysis result, wherein the analysis content of the economic analysis includes acceleration capability and fuel consumption;
[0062] An economic evaluation model is generated according to the economic analysis results.
[0063] A third aspect of the present application provides a vehicle performance evaluation device based on vehicle network data, the device comprising:
[0064] Processor, memory, input-output unit, and bus;
[0065] The processor is connected to the memory, the input and output unit, and the bus;
[0066] The memory stores a program, and the processor calls the program to execute the first aspect and any optional method in the first aspect.
[0067] A fourth aspect of the present application provides a computer-readable storage medium, on which a program is stored. When the program is executed on a computer, the program executes the first aspect and any optional method in the first aspect.
[0068] It can be seen from the above technical solutions that this application has the following advantages:
[0069] The present application classifies the target vehicle by the configuration label and operating data carried by the target vehicle, and determines the operating status and vehicle status of the target vehicle through the classification results, so as to obtain sample data consistent with the target vehicle data as samples of the evaluation model, and train the evaluation model through the samples, so as to achieve the purpose of performance evaluation of the target vehicle through the evaluation model. BRIEF DESCRIPTION OF THE DRAWINGS
[0070] In order to more clearly illustrate the technical solution in the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.
[0071] Figure 1 A schematic flow chart of an embodiment of a vehicle performance evaluation method based on vehicle network data in the present application;
[0072] Figure 2 A flowchart of an embodiment of a method for obtaining an evaluation model of a vehicle performance evaluation method based on vehicle network data in the present application;
[0073] Figure 3 A schematic flow chart of an embodiment of a performance evaluation method of a vehicle performance evaluation method based on vehicle network data in the present application;
[0074] Figure 4 A schematic flow chart of an embodiment of a vehicle classification method of a vehicle performance evaluation method based on vehicle network data in the present application;
[0075] Figure 5 A schematic flow chart of an embodiment of a process for generating a dynamic evaluation model in a vehicle performance evaluation based on vehicle network data in the present application;
[0076] Figure 6 A schematic diagram of a flow chart of an embodiment of generating an economic evaluation model in vehicle performance evaluation based on vehicle network data in this application;
[0077] Figure 7 A schematic diagram of the structure of an embodiment of a vehicle performance evaluation system based on vehicle network data in the present application;
[0078] Figure 8 This is a schematic diagram of the structure of an embodiment of a vehicle performance evaluation device based on vehicle network data in the present application. DETAILED DESCRIPTION
[0079] It should be noted that the vehicle performance evaluation method based on vehicle network data provided in this application can be applied to a terminal, a system, or a server. For example, the terminal can be a smart phone or a computer, a tablet computer, a smart TV, a smart watch, a portable computer terminal, or a fixed terminal such as a desktop computer. This application uses the control terminal as the subject of the description to describe the embodiment.
[0080] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.
[0081] See also Figure 1 The present application first provides an embodiment of a vehicle performance evaluation method based on vehicle network data, the embodiment comprising:
[0082] S101, obtaining the configuration label and operation data of the target vehicle;
[0083] The sample data required for data evaluation of the target vehicle in this application is the vehicle that interacts with the Internet of Vehicles, and the vehicle operation data is fed back to the Internet of Vehicles database through the vehicle system during operation.
[0084] Based on the current vehicle base, the Internet of Vehicles database has a huge amount of vehicle configuration and vehicle operation data. However, in the process of evaluating the target vehicle, not all vehicle feedback data can be used as sample data for the target vehicle. Therefore, before evaluating the target vehicle, it is necessary to profile the vehicle usage status of the target vehicle based on the configuration tags and operation data fed back by the target vehicle to the Internet of Vehicles database.
[0085] S102, determining the vehicle classification of the target vehicle according to the configuration tag and the operation data;
[0086] The vehicle's configuration label is carried when it leaves the factory. The specific content of the configuration label is used to reflect the actual situation of the vehicle. The data contained in the configuration label includes but is not limited to: vehicle load capacity and vehicle purpose, etc., which are used to distinguish the actual engineering function of the vehicle. The specific information is not limited here.
[0087] In actual usage scenarios, vehicle operation data will be collected through on-board sensors when the vehicle is running. This data will be fed back to the Internet of Vehicles database. The operation data includes environmental information collected by environmental sensors. The actual usage environment and actual usage scenarios of the vehicle can be determined through environmental information.
[0088] After obtaining the configuration tag and operation data of the target vehicle, the actual control end will set a vehicle classification corresponding to the target vehicle based on the above information.
[0089] S103, obtaining an evaluation model according to the vehicle classification;
[0090] The controller will retrieve the vehicle data in the Internet of Vehicles database according to the vehicle classification of the target vehicle, so as to obtain the vehicle data with the same configuration labels and similar operating data as the target vehicle, and use these vehicle data as evaluation model samples to generate an evaluation model corresponding to the target vehicle.
[0091] S104: Evaluate the performance of the target vehicle according to the evaluation model.
[0092] After obtaining the evaluation model, the control end will perform performance evaluation on the target vehicle that needs to be evaluated according to the evaluation model. Specifically, after extracting effective data from the target vehicle and the sample data in the evaluation model at a fixed period, the extracted results are arranged and compared to obtain a comparison result between the actual performance of the target vehicle and the performance of similar vehicles, and the comparison result is used as the evaluation result of the vehicle performance evaluation.
[0093] Based on step S103, when the application obtains the evaluation model by vehicle classification, the evaluation model data is obtained through the following process, please refer to Figure 2 The present application embodiment provides an embodiment of a method for obtaining an evaluation model of a vehicle performance evaluation method based on vehicle network data, and the embodiment includes:
[0094] S201, acquiring a target data sample from a vehicle networking database according to the vehicle classification, wherein the target data sample and the target vehicle carry the same configuration tag;
[0095] Specifically, the feedback data of vehicles with the same configuration labels as the target vehicle in the Internet of Vehicles will be identified by the control end as preliminary screening sample data. After obtaining the preliminary screening sample data, it will be screened again according to the temperature and pressure of the operating environment to obtain sample data with the same labels in the same environment. The preliminary screening sample data and the collection that pass the environmental screening are the target data samples.
[0096] S202, screening the target data samples according to a preset period to obtain dynamic effective data and economic effective data;
[0097] After obtaining the target sample data, the controller will slice the target sample data. The purpose of slicing is to obtain the running data of the vehicle from startup to shutdown, and the cumulative mileage in the cycle needs to be greater than 1 km. If the cumulative mileage in the cycle is less than 1 km, it will be confirmed as invalid data by the controller. The filtered data will finally be collected into the slice database as the basic database for generating the evaluation model.
[0098] In actual situations, the vehicle's dynamic and economical effective data are extracted from the basic database.
[0099] Specifically, the process of selecting sliced data for economy is to remove operating conditions where the vehicle speed is 0 and operating conditions where the engine load rate is less than 0, and to aggregate the real-time fuel consumption, vehicle speed, and GPS mileage to form an economy database, which contains data that is economically valid data.
[0100] The dynamic slice data selection process is to obtain the vehicle gear, speed, mileage and other information when the vehicle speed is 0 through vehicle gear and speed monitoring, and to increase the vehicle speed through continuous gear shifting, so as to form a starting dynamics evaluation database; when the vehicle speed gear is the second highest gear, or the overspeed gear, and the vehicle speed increases, the current gear and speed information are obtained to form an evaluation database for the vehicle acceleration ability.
[0101] The data contained in the starting dynamics database and the acceleration capability evaluation database are collectively referred to as dynamics effective data.
[0102] S203, respectively collecting the dynamic efficiency data and the economic efficiency data into a sample database;
[0103] The dynamic performance evaluation and economic performance evaluation of the target vehicle are two different methods, so the required data will be collected into different sample databases respectively.
[0104] S204: Analyze the sample database according to preset rules to generate an evaluation model.
[0105] The dynamic data and economic data of the sample database are analyzed, and the analysis results are the evaluation model.
[0106] Based on step S104, the present application performs performance evaluation on the target vehicle in the following manner. For details, please refer to Figure 3 The present application embodiment provides an embodiment of a performance evaluation method of a vehicle performance evaluation method based on vehicle network data, and the embodiment includes:
[0107] S301, obtaining the operation record uploaded by the vehicle terminal of the target vehicle through the Internet of Vehicles database;
[0108] The operation record contains all the data fed back by the vehicle during operation. When these data are fed back to the Internet of Vehicles database, they will be marked with configuration tags and the vehicle's identity information. The configuration tags are used to determine the actual usage status and load status of the vehicle, and the identity information is used to determine the specific target vehicle.
[0109] S302, obtaining target parameters required by the evaluation model from the operation record;
[0110] The operation record is the data generated when the vehicle is running. The operation record can be used to obtain the parameters required by the evaluation model to evaluate the vehicle.
[0111] The parameters required for the evaluation model are target parameters, which include but are not limited to: instantaneous fuel consumption, instantaneous fuel consumption, starting acceleration time, and gear acceleration time.
[0112] S303: Use the evaluation model to evaluate the performance of the target vehicle on the target parameters.
[0113] After obtaining the target parameters, the controller will calculate the target parameters according to the algorithm provided by the evaluation model, compare the calculation results with the average value of the corresponding data in the database, determine the range of the target parameters, and evaluate the performance of the target vehicle based on the range of the target parameters.
[0114] Based on step S102, the specific process of classifying the target vehicle in this application is as follows. Figure 4 The present application embodiment provides an embodiment of a vehicle classification method of a vehicle performance evaluation method based on vehicle network data, and the embodiment includes:
[0115] S401, determining the load capacity and engineering purpose of the target vehicle according to the configuration tag;
[0116] Specifically, the vehicles are classified according to the vehicle information entered into the vehicle terminal to form types in different sub-sectors; for example, the vehicles are classified according to their load weight and purpose, such as: 49-ton tractors, 31-ton engineering vehicles, 18-ton trucks, etc., to form a vehicle type library, which is not limited here.
[0117] S402, determining the operating environment of the target vehicle according to the operating data;
[0118] Based on the classified same vehicle models, that is, the type library of vehicles determined by configuration tags, the vehicle operation scenarios are classified according to the Internet of Vehicles data; the vehicle operation scenarios are classified by the topographic features and vehicle speed features obtained by the Internet of Vehicles data, and combined with the vehicle model classification in 1, a sample library of different operation scenarios under different vehicle models is formed. For example: urban sanitation vehicles, high-speed tractor vehicles, high-speed trucks, etc., which are not limited here.
[0119] S403, obtaining vehicle data having the same load capacity and engineering purpose through a vehicle networking database;
[0120] The above steps determine the scope of data selection. After the scope is determined, the controller obtains vehicle data of the same scope from the Internet of Vehicles database based on the scope.
[0121] S404, performing a secondary screening on the vehicle data according to the operating environment to obtain a screening result;
[0122] Specifically, the running state of a vehicle will be affected by the environment during operation. For example, in a low-pressure and low-temperature environment on a plateau, the actual acquired data is different from that of a vehicle traveling on a plain, so these vehicles will be excluded when determining the vehicle data.
[0123] S405: Collect the screening results, and determine the screening results as the vehicle classification of the target vehicle.
[0124] The range obtained according to the secondary screening result is the vehicle classification of the target vehicle, and the vehicle classification can be used to obtain corresponding data from the Internet of Vehicles database.
[0125] In the present application, the evaluation model includes a dynamic evaluation model and an economic evaluation model. The dynamic evaluation model is generated by analyzing the dynamic effective data contained in the target sample obtained from the Internet of Vehicles database, and the economic evaluation model is generated by analyzing the economic effective data contained in the target sample obtained from the Internet of Vehicles database. The generation process of the dynamic evaluation model and the economic evaluation model in the present application will be described below.
[0126] See also Figure 5The present application embodiment provides an embodiment of a process for generating a dynamic evaluation model in a vehicle performance evaluation based on vehicle network data, and the embodiment includes:
[0127] S501, acquiring the dynamic performance test data of the vehicle type included in the vehicle classification from the Internet of Vehicles database, and confirming the dynamic performance data sample from the dynamic performance test data according to the preset period;
[0128] Specifically, the dynamic test data is the data calculated for the vehicle dynamics when generating the evaluation model. The operating data of the target vehicle is more likely to fluctuate mainly due to the driving speed at that time. In the actual evaluation, in order to avoid the wrong evaluation results in the sample due to the difference between the sample running speed and the running data speed carried by the target vehicle, the data contained in the Internet of Vehicles database will be divided into intervals according to the speed when generating the evaluation model, and the speed in each interval will be calculated to obtain the dynamic data sample.
[0129] S502, performing a dynamic analysis on the dynamic sample data to obtain a dynamic analysis result, wherein the dynamic analysis includes starting acceleration capability and overtaking capability;
[0130] The dynamics evaluation model generated according to the dynamics data samples is mainly used to evaluate the instantaneous acceleration performance of the slice data. The specific process is as follows:
[0131] Starting acceleration capability: Get continuous gear shift acceleration: 0-80km / h acceleration time;
[0132] Overtaking ability: Direct gear acceleration, the specific data obtained are: 1. Acceleration time from 50 to 80 km / h in the highest gear; 2. Acceleration time from 40 to 80 km / h in the second highest gear;
[0133] The average value of multiple data within a unit period is calculated to obtain the data samples within a single period.
[0134] S503: Generate a dynamic performance evaluation model according to the dynamic performance analysis result.
[0135] In the embodiment of the present application, the evaluation results given by the evaluation model for the dynamic performance are divided into: "strong dynamic performance", "normal dynamic performance", and "dynamic performance needs to be improved"; specifically, when the acceleration time is less than 0.85*average value, the output is "strong dynamic performance"; when the acceleration time is between 0.85*average value and 1.15*average value, the output is "normal dynamic performance"; when the acceleration time is greater than 1.15*average value, the output is "dynamic performance needs to be improved".
[0136] Among them, fuel consumption is divided into constant speed fuel consumption and comprehensive fuel consumption, and power is divided into starting acceleration ability and overtaking ability.
[0137] See also Figure 6 The present application embodiment provides an embodiment of a process for generating an economic evaluation model in a vehicle performance evaluation based on vehicle network data, and the embodiment includes:
[0138] S601, acquiring economic test data of vehicle types included in the vehicle classification from the Internet of Vehicles database, and confirming economic data samples from the economic test data according to the preset period;
[0139] The purpose of the economy test is to evaluate the fuel consumption of the vehicle. The specific evaluation method is to compare the fuel consumption of the target vehicle with the average fuel consumption of the same model under the same operating conditions.
[0140] In the actual process of acquiring sample data, other factors that affect fuel consumption are included, such as environmental factors, vehicle wear and tear, actual road conditions, etc., which are not specifically limited here. In order to reduce the impact of these factors on the evaluation, the sliced data in the Internet of Vehicles database needs to be reclassified before the actual generation of the economic evaluation model to obtain the economic sample data.
[0141] S602, performing an economic analysis on the economic sample data to obtain an economic analysis result, wherein the analysis content of the economic analysis includes acceleration capability and fuel consumption;
[0142] The instantaneous fuel consumption of the same type of vehicles and the mileage integral based on the instantaneous fuel consumption are used for the vehicle data carried by the vehicle data in the Internet of Vehicles database to calculate the constant speed fuel consumption (L / 100km) under unit weight, and the two constant speeds V1 and V2 are selected. The data with a speed deviation of <5km / h are valid data, and the segments with continuous running of more than >2km are valid segments.
[0143] The instantaneous fuel consumption and mileage integral based on vehicle speed are integrated to calculate the comprehensive fuel consumption for the data of characteristic scenes; L / 100km, the instantaneous fuel consumption integral and mileage integral are integrated for the data of a recording cycle according to the fragments filtered by the previous data;
[0144] The specific integral formula is:
[0145]
[0146] Where φ is the average fuel consumption, i is the instantaneous fuel consumption, and Hi is the instantaneous mileage.
[0147] S603: Generate an economic evaluation model according to the economic analysis results.
[0148] In the embodiment of the present application, the evaluation results given by the evaluation model for power are divided into: "excellent fuel consumption performance", "normal fuel consumption", and "fuel consumption needs to be improved"; specifically, when the current fuel consumption is less than 0.9*average fuel consumption, "excellent fuel consumption performance" is output; when the current fuel consumption is between 0.9*average fuel consumption and 1.1*average fuel consumption, "normal fuel consumption" is output; when the fuel consumption ratio is greater than 1.1 average fuel consumption, "fuel consumption needs to be improved" is output.
[0149] According to this embodiment and the aforementioned embodiments, statistical analysis is performed on data of specific vehicle models in specific scenarios to form a sample feature library of comprehensive fuel consumption, constant-speed fuel consumption, starting acceleration capability, and overtaking acceleration capability, thereby obtaining an evaluation model used in this application to evaluate vehicles.
[0150] The above is a detailed description of the implementation process of the vehicle performance evaluation method based on vehicle network data in the embodiment of the present application. The following is a detailed description of the vehicle performance evaluation system and device based on vehicle network data.
[0151] See also Figure 7 The present application provides an embodiment of a vehicle performance evaluation system based on vehicle network data, which includes:
[0152] The first acquisition unit 701 is used to acquire the configuration tag and operation data of the target vehicle;
[0153] A determination unit 702, configured to determine a vehicle classification of the target vehicle according to the configuration tag and the operation data;
[0154] A second acquisition unit 703, used to acquire an evaluation model according to the vehicle classification;
[0155] The performance evaluation unit 704 is used to perform performance evaluation on the target vehicle according to the evaluation model.
[0156] Optionally, the second acquiring unit 703 is further used to:
[0157] Acquire a target data sample from a vehicle networking database according to the vehicle classification, wherein the target data sample and the target vehicle carry the same configuration tag;
[0158] Screening the target data samples according to a preset period to obtain dynamic effective data and economic effective data;
[0159] The dynamic efficiency data and the economic efficiency data are respectively collected into a sample database;
[0160] The sample database is analyzed according to preset rules to generate an evaluation model.
[0161] Optionally, the performance evaluation unit 704 is further configured to:
[0162] Obtaining the operation record uploaded by the vehicle terminal of the target vehicle through the Internet of Vehicles database;
[0163] Acquiring target parameters required by the evaluation model from the operation record;
[0164] The evaluation model is used to evaluate the performance of the target vehicle on the target parameters.
[0165] Optionally, the determining unit 702 is further configured to:
[0166] Determining the load capacity and engineering purpose of the target vehicle according to the configuration tag;
[0167] determining an operating environment of the target vehicle according to the operating data;
[0168] Acquire vehicle data having the same load capacity and engineering purpose through a vehicle networking database;
[0169] Performing a secondary screening on the vehicle data according to the operating environment to obtain a screening result;
[0170] The screening results are collected and determined as the vehicle classification of the target vehicle.
[0171] Optionally, the performance evaluation unit 704 includes a dynamic performance evaluation model module 7041 and an economic performance evaluation model module 7042 .
[0172] Optionally, the dynamic performance evaluation model module 7041 is used to:
[0173] Acquire the dynamic performance test data of the vehicle type included in the vehicle classification from the vehicle networking database, and confirm the dynamic performance data sample from the dynamic performance test data according to the preset period;
[0174] Performing a dynamic analysis on the dynamic sample data to obtain a dynamic analysis result, wherein the dynamic analysis includes starting acceleration capability and overtaking capability;
[0175] A dynamics evaluation model is generated according to the dynamics analysis results.
[0176] Optionally, the economic evaluation model module 7042 is used to:
[0177] Obtaining economic test data of the vehicle types included in the vehicle classification from the Internet of Vehicles database, and confirming economic data samples from the economic test data according to the preset period;
[0178] Performing an economic analysis on the economic sample data to obtain an economic analysis result, wherein the analysis content of the economic analysis includes acceleration capability and fuel consumption;
[0179] An economic evaluation model is generated according to the economic analysis results.
[0180] In this embodiment, the functions of each unit are the same as those described above. Figures 1 to 6 The steps in the illustrated embodiments correspond to each other and will not be described again here.
[0181] See also Figure 8 The present application provides an embodiment of a vehicle performance evaluation device based on vehicle network data, including:
[0182] Processor 801, memory 802, input and output unit 803, bus 804;
[0183] The processor 801 is connected to the memory 802, the input and output unit 803 and the bus 804;
[0184] The processor 801 specifically performs Figures 1 to 6 The operations corresponding to the steps in the method are not described in detail here.
[0185] The present application also relates to a computer-readable storage medium on which a program is stored, wherein when the program is run on a computer, the computer is caused to execute any of the above methods.
[0186] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.
[0187] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.
[0188] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
[0189] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.
[0190] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, read-only memory), random access memory (RAM, random access memory), disk or optical disk and other media that can store program code.
Claims
1. A vehicle performance evaluation method based on vehicle network data, characterized in that: The method comprises: Obtain the configuration tags and operating data of the target vehicle; determining a vehicle classification of the target vehicle based on the configuration tag and the operating data; Acquire an evaluation model according to the vehicle classification; The target vehicle is subjected to a performance evaluation according to the evaluation model.
2. The vehicle performance evaluation method according to claim 1, characterized in that: The obtaining of the evaluation model according to the vehicle classification comprises: Acquire a target data sample from a vehicle networking database according to the vehicle classification, wherein the target data sample and the target vehicle carry the same configuration tag; Screening the target data samples according to a preset period to obtain dynamic effective data and economic effective data; The dynamic efficiency data and the economic efficiency data are respectively collected into a sample database; The sample database is analyzed according to preset rules to generate an evaluation model.
3. The vehicle performance evaluation method according to claim 1, characterized in that: The performing performance evaluation on the target vehicle according to the evaluation model comprises: Obtaining the operation record uploaded by the vehicle terminal of the target vehicle through the Internet of Vehicles database; Acquiring target parameters required by the evaluation model from the operation record; The evaluation model is used to evaluate the performance of the target vehicle on the target parameters.
4. The vehicle performance evaluation method according to claim 1, characterized in that: The determining the vehicle classification of the target vehicle according to the configuration tag and the operation data comprises: Determining the load capacity and engineering purpose of the target vehicle according to the configuration tag; determining an operating environment of the target vehicle according to the operating data; Acquire vehicle data having the same load capacity and engineering purpose through a vehicle networking database; Performing a secondary screening on the vehicle data according to the operating environment to obtain a screening result; The screening results are collected and determined as the vehicle classification of the target vehicle.
5. The vehicle performance evaluation method according to claim 1, characterized in that: The evaluation model includes a dynamic evaluation model and an economic evaluation model.
6. The vehicle performance evaluation method according to claim 5, characterized in that: The generation process of the dynamic evaluation model includes: Acquire the dynamic performance test data of the vehicle type included in the vehicle classification from the vehicle networking database, and confirm the dynamic performance data sample from the dynamic performance test data according to the preset period; Performing a dynamic analysis on the dynamic sample data to obtain a dynamic analysis result, wherein the dynamic analysis includes starting acceleration capability and overtaking capability; A dynamics evaluation model is generated according to the dynamics analysis results.
7. The vehicle performance evaluation method according to claim 5, characterized in that: The generation process of the economic evaluation model includes: Obtaining economic test data of the vehicle types included in the vehicle classification from the Internet of Vehicles database, and confirming economic data samples from the economic test data according to the preset period; Performing an economic analysis on the economic sample data to obtain an economic analysis result, wherein the analysis content of the economic analysis includes acceleration capability and fuel consumption; An economic evaluation model is generated according to the economic analysis results.
8. A vehicle performance evaluation system based on vehicle network data, characterized in that: The method comprises: A first acquisition unit, used to acquire a configuration tag and operating data of a target vehicle; a determination unit, configured to determine a vehicle classification of the target vehicle according to the configuration tag and the operation data; A second acquisition unit, used for acquiring an evaluation model according to the vehicle classification; A performance evaluation unit is used to perform performance evaluation on the target vehicle according to the evaluation model.
9. A vehicle performance evaluation device based on vehicle network data, characterized in that: The device comprises: Processor, memory, input-output unit, and bus; The processor is connected to the memory, the input and output unit, and the bus; The memory stores a program, and the processor calls the program to execute the method according to any one of claims 1 to 7.
10. A computer-readable storage medium having a program stored thereon, wherein the program, when executed on a computer, performs the method according to any one of claims 1 to 7.