Vehicle starting economy judgment method, device, terminal and storage medium

Abstract

The present invention provides a method, device, terminal and storage medium for judging the economic efficiency of vehicle starting. The method comprises: obtaining key feature data of the vehicle's historical starting state and engine fuel efficiency economic index data, wherein the key feature data is data characterizing the driver's operating characteristics when the vehicle starts; clustering the key feature data and the engine fuel efficiency economic index data to obtain the optimal class in which the engine fuel efficiency economic index data is in the optimal working range of the engine; judging the economy of the vehicle at subsequent starting according to the key feature data corresponding to the optimal class. The present invention can make a more scientific and reasonable judgment on the economy of the vehicle starting and better guide the driver's starting operation.

Description

Technical Field

[0001] The present invention relates to the field of energy-saving driving technology, and in particular to a vehicle starting economy judgment method, device, terminal and storage medium. Background Art

[0002] With the continuous development of my country's economy and technology, cars have gradually become one of the indispensable means of transportation in modern society. The continuous increase in the number of cars has not only brought convenience to people's lives, but also brought a series of problems, such as energy shortages and air pollution. In order to solve the problems caused by the large-scale use of vehicles, in addition to using scientific and technological means to continuously improve vehicle performance, the study of the economic efficiency of drivers' driving behavior is also of great significance. Vehicle drivers are an important part of the human-vehicle-road road transportation system, and the degree of standardization of drivers' driving behavior has a great impact on the amount of fuel used in road transportation. Even among professional drivers in professional transport fleets, different driving habits of different drivers also have a difference of 2% to 12% in automobile fuel consumption. Therefore, comprehensively improving the operational standardization of the driver team and promoting energy-saving driving behavior are of great practical significance for alleviating fuel shortages and environmental pollution.

[0003] The inventor discovered during the process of implementing the present invention that, currently, when judging the vehicle starting economy, it is usually judged by judging whether the driver has stepped on the accelerator pedal hard, that is, judging by judging the instantaneous speed of the engine. However, judging by judging the instantaneous speed of the engine has a single indicator and an inaccurate judgment result. On the other hand, it is difficult to provide operational guidance to the driver. Summary of the invention

[0004] The embodiments of the present invention provide a method, device, terminal and storage medium for judging the economy of vehicle starting, so as to solve the problem that the current judgment of the economy of vehicle starting is inaccurate and it is difficult to provide operation guidance to the driver.

[0005] In a first aspect, an embodiment of the present invention provides a method for determining the starting economy of a vehicle, comprising:

[0006] Acquire key characteristic data of the vehicle's historical starting state and engine fuel efficiency economy index data, wherein the key characteristic data is data characterizing the operating characteristics of the driver when the vehicle starts;

[0007] Clustering is performed using the key feature data and the engine fuel efficiency and economy index data to obtain an optimal class in which the engine fuel efficiency and economy index data is in an optimal engine operating range;

[0008] The economy of the vehicle during subsequent starting is determined based on the key feature data corresponding to the optimal class.

[0009] In a possible implementation, obtaining engine fuel efficiency economic index data of a vehicle's historical starting state includes:

[0010] Obtain the engine speed, engine torque and instantaneous fuel consumption of the vehicle's historical starting state;

[0011] The engine fuel efficiency economy index data of the vehicle's historical starting state is obtained according to the engine speed, the engine torque and the instantaneous fuel consumption.

[0012] In a possible implementation, obtaining engine fuel efficiency economy index data of a vehicle in a historical starting state according to the engine speed, the engine torque, and the instantaneous fuel consumption includes:

[0013] according to , obtain engine fuel efficiency economic index data of the vehicle's historical starting state;

[0014] in, The engine fuel efficiency economic index data of the vehicle's historical starting state, is the instantaneous fuel consumption, is the engine speed, is the engine torque.

[0015] In a possible implementation, clustering is performed using the key feature data and the engine fuel efficiency and economy index data to obtain an optimal class in which the engine fuel efficiency and economy index data is in an optimal engine operating range, including:

[0016] Using the key feature data and the engine fuel efficiency economy index data to perform clustering to obtain an optimal clustering result;

[0017] From the optimal clustering results, it is determined that the class whose engine fuel efficiency economy index data is in the optimal working range of the engine and has the highest proportion is the optimal class.

[0018] In a possible implementation, after determining from the optimal clustering result that the engine fuel efficiency economy index data is in the optimal working range of the engine and the class with the highest proportion is the optimal class, the method further includes:

[0019] Verify whether the optimal class is reasonable according to the proportion of the engine fuel efficiency economy index data corresponding to the optimal class in the optimal working range of the engine;

[0020] If the optimal class is reasonable, the economy of the vehicle during subsequent starting is determined based on the key feature data corresponding to the optimal class.

[0021] In a possible implementation, judging the economy of the vehicle when starting subsequently according to the key feature data corresponding to the optimal class includes:

[0022] Recording the key feature data corresponding to the optimal class as standard key feature data;

[0023] Determine whether the key characteristic data of the vehicle when it starts subsequently is within the range of the standard key characteristic data;

[0024] If the key characteristic data of the vehicle when starting subsequently is within the range of the standard key characteristic data, then the vehicle is determined to start subsequently as an economical start;

[0025] If the key feature data of the vehicle when it subsequently starts is beyond the range of the standard key feature data, the standard key feature data is fed back to the driver of the vehicle.

[0026] In a possible implementation, the key feature data includes at least two of a transmission gear position, an accelerator pedal force, and an engine speed.

[0027] In a second aspect, an embodiment of the present invention provides a vehicle starting economy determination device, comprising:

[0028] An acquisition module, used to acquire key characteristic data of the vehicle's historical starting state and engine fuel efficiency economy index data, wherein the key characteristic data is data characterizing the operating characteristics of the driver when the vehicle starts;

[0029] A processing module, used for clustering the key feature data and the engine fuel efficiency and economy index data to obtain an optimal class in which the engine fuel efficiency and economy index data is in an optimal working range of the engine;

[0030] The judgment module is used to judge the economy of the vehicle when it starts subsequently according to the key feature data corresponding to the optimal class.

[0031] In a third aspect, an embodiment of the present invention provides a terminal, comprising a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to perform the steps of the method described in the first aspect or any possible implementation of the first aspect.

[0032] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described in the first aspect or any possible implementation method of the first aspect are implemented.

[0033] The embodiment of the present invention provides a method, device, terminal and storage medium for judging the economy of vehicle starting. The method obtains key feature data and engine fuel efficiency index data representing the operating characteristics of the driver when the vehicle starts in the historical starting state of the vehicle, and then uses the key feature data and the engine fuel efficiency index data to perform cluster analysis to obtain the optimal class in which the engine fuel efficiency index data is in the optimal working range of the engine, so as to judge the economy of the vehicle when starting subsequently according to the key feature data corresponding to the optimal class in which the engine fuel efficiency index data is in the optimal working range of the engine, so as to make the judgment of the economy of the vehicle starting more scientific and reasonable. In addition, since the key feature data corresponding to the optimal class can represent the driver's operating characteristics corresponding to the optimal vehicle starting economy, the driver's starting operation can be better guided. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0035] Figure 1 is a flow chart of the implementation of the vehicle starting economy determination method provided by an embodiment of the present invention;

[0036] Figure 2 is a SSE variation curve diagram provided by an embodiment of the present invention;

[0037] Figure 3 It is a schematic diagram of the classification results of gearbox gear and specific fuel consumption under the optimal clustering result provided by an embodiment of the present invention;

[0038] Figure 4 It is a schematic diagram of the classification results of the accelerator pedal force and the specific fuel consumption under the optimal clustering result provided by an embodiment of the present invention;

[0039] Figure 5 It is a schematic diagram of the classification results of engine speed and specific fuel consumption under the optimal clustering result provided by an embodiment of the present invention;

[0040] Figure 6 is a universal characteristic diagram of an engine provided by an embodiment of the present invention;

[0041] Figure 7 is a schematic diagram of the structure of a vehicle starting economy determination device provided by an embodiment of the present invention;

[0042] Figure 8 is a schematic diagram of a terminal provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present invention. However, it should be clear to those skilled in the art that the present invention may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present invention.

[0044] In order to make the purpose, technical solutions and advantages of the present invention more clear, specific embodiments will be described below in conjunction with the accompanying drawings.

[0045] See also Figure 1 , which shows a flow chart of the implementation of the vehicle starting economy determination method provided by an embodiment of the present invention, and is described in detail as follows:

[0046] In step 101, key feature data of the vehicle's historical starting state and engine fuel efficiency economy index data are obtained, where the key feature data is data characterizing the driver's operating characteristics when the vehicle starts.

[0047] In step 102, clustering is performed using the key feature data and the engine fuel efficiency and economy index data to obtain an optimal class in which the engine fuel efficiency and economy index data is in the optimal working range of the engine.

[0048] In step 103, the economy of the vehicle when starting subsequently is determined based on the key feature data corresponding to the optimal class.

[0049] In this embodiment, in order to more scientifically and reasonably judge the economy of vehicle starting and better guide the driver's starting operation, subsequent cluster analysis is performed in combination with the engine fuel efficiency economy index data and the key feature data characterizing the driver's operating characteristics when the vehicle starts, so as to select the key feature data corresponding to the optimal class in which the engine fuel efficiency economy index data is in the optimal working range of the engine to judge the vehicle starting economy.

[0050] For example, considering the difficulty of acquiring key feature data representing the driver's operating characteristics when the vehicle starts and the difficulty of guiding the driver's operation, at least two of the gearbox position, the accelerator pedal force and the engine speed can be selected as key feature data representing the driver's operating characteristics when the vehicle starts. For example, the gearbox position, the accelerator pedal force and the engine speed are selected as key feature data representing the driver's operating characteristics when the vehicle starts, so as to better guide the driver's economical starting operation in combination with the gearbox position, the accelerator pedal and the engine speed.

[0051] Optionally, in order to make the vehicle starting economy judgment more scientific and reasonable, when obtaining the key feature data of the vehicle's historical starting status and the engine fuel efficiency economy index data, the key feature data of the historical starting status and the engine fuel efficiency economy index data of vehicles of the same model and running on the same route can be obtained.

[0052] Optionally, to obtain the engine fuel efficiency economic index data of the vehicle's historical starting state, the engine speed, engine torque and instantaneous fuel consumption of the vehicle's historical starting state can be obtained first, and then the engine fuel efficiency economic index data of the vehicle's historical starting state can be obtained based on the engine speed, engine torque and instantaneous fuel consumption. , obtain the engine fuel efficiency economic index data of the vehicle's historical starting state. Therefore, based on the engine fuel efficiency economic index data, the vehicle's ability to travel economically with the smallest possible fuel consumption while ensuring power is measured, so as to select the key characteristic data corresponding to the optimal vehicle starting economy through the engine fuel efficiency economic index data.

[0053] in, The engine fuel efficiency economic index data of the vehicle's historical starting state, is the instantaneous fuel consumption in liters per hour ( ), convert the units to kilograms per hour by multiplying by 0.85 for density conversion ( ), convert the units to grams per hour by multiplying by 1000 ( ), is the engine speed in revolutions per minute (r / min), and 100 is the factor that converts the speed from revolutions per minute to revolutions per second. Because the formula for power is ,in is the angular velocity in radians per second (rad / s), and the angular velocity , so 2400 is the constant used to convert rotational speed to angular velocity, is the engine torque, in Newton rice( ), 9550 is a constant used to convert torque to power. This is because in the International System of Units, the unit of power is watt (W), and 1 horsepower (hp) is approximately equal to 735.5 watts. So, multiply the torque M by the angular velocity Divide it by 9550 to get the value of power P. Expressed as the mass of fuel consumed per unit of power, in grams per kilowatt-hour ( ).

[0054] Optionally, in order to more accurately obtain the optimal class in which the engine fuel efficiency and economy index data are in the optimal operating range of the engine, the key feature data and the engine fuel efficiency and economy index data can be first clustered to obtain the optimal clustering result, and then the class in which the engine fuel efficiency and economy index data are in the optimal operating range of the engine and has the highest proportion can be determined from the optimal clustering result as the optimal class.

[0055] For example, taking the key characteristic data including the gear position of the transmission, the accelerator pedal force and the engine speed as an example, the process of obtaining the optimal class of the engine fuel efficiency economy index data in the optimal working range of the engine is explained:

[0056] First, the transmission gear position, accelerator pedal force (%), engine speed (r / min), engine torque (%), and instantaneous fuel consumption (L / h) of vehicles of the same model and running on the same route in the historical starting state are obtained.

[0057] Then according to , calculate the engine fuel efficiency economy index data of each vehicle.

[0058] Then, the transmission gear position, accelerator pedal force, engine speed and corresponding engine fuel efficiency economy index data of vehicles of the same model and running on the same route in the historical starting state are used as sample data for clustering models such as k-means model.

[0059] Randomly obtain k data from the sample data as the class center of the initial clustering, calculate the distance from each data point in the sample data to the k data, and assign the data point to the class where the nearest class center is located until all data points in the sample data are assigned, and obtain a clustering result.

[0060] The cluster center is updated according to the clustering result, and the updated cluster center is compared with the cluster center before the update. If the cluster center changes, the sample data is clustered again according to the updated cluster center, and the cluster center is updated repeatedly until the cluster center no longer changes. The total square error sum (SSE) when the number of clusters is k is obtained, which is recorded as .

[0061] Randomly obtain k+1 data from the sample data as the class center of the initial cluster, repeat the above clustering process, and get By analogy, we get , Wait, draw as Figure 2 The SSE change curve shown in the figure is as follows, until the SSE has no obvious change, the clustering result corresponding to the number of clusters when the SSE has no obvious change is determined as the optimal clustering result.

[0062] For example, the classification results of the gearbox gear and specific fuel consumption (i.e., engine fuel efficiency economic index), the classification of the accelerator pedal force and specific fuel consumption, and the classification of the engine speed and specific fuel consumption under the optimal clustering result can be as follows: Figure 3-Figure 5 The BSFC value corresponding to each class center under the optimal clustering result, the number of samples contained in the class where each class center belongs, and other information are shown in Table 1.

[0063] Table 1

[0064]

[0065] Combination Figure 6 The engine universal characteristic diagram shown in the figure shows that the optimal working range of the engine is the engine fuel efficiency and economic index data is 160 and below, the BSFC value corresponding to the class center in Table 1 is 160 The following classes are class 2, class 3, class 5, class 9, and class 10, among which the BSFC value of class 10 is less than 160 The proportion of is the highest, which is 86.7%, so class 10 can be determined as the optimal class.

[0066] Optionally, after determining from the optimal clustering results that the class whose engine fuel efficiency and economy index data is in the optimal working range of the engine and has the highest proportion is the optimal class, it is also possible to verify whether the optimal class is reasonable based on the proportion of the engine fuel efficiency and economy index data corresponding to the optimal class in the optimal working range of the engine; if the optimal class is reasonable, the economy of the vehicle during subsequent starting is judged based on the key feature data corresponding to the optimal class.

[0067] For example, according to Table 1, the BSFC value of the best class, i.e. class 10, is less than 160. The proportion is 86.7%, the aggregation effect is better, the optimal class is reasonable, and the key feature data corresponding to the optimal class can be used as standard data for judging the economy of the vehicle during subsequent starting.

[0068] For example, if the optimal class is verified to be unreasonable based on the proportion of engine fuel efficiency and economy index data corresponding to the optimal class in the optimal engine working range, for example, the proportion of engine fuel efficiency and economy index data corresponding to the optimal class in the optimal engine working range is small, then the clustering results can be further optimized. After obtaining a reasonable optimal class, the economy of the vehicle during subsequent starting can be judged based on the key feature data corresponding to the optimal class.

[0069] Optionally, after the optimal class is determined and is reasonable, the process of judging the economy of the vehicle at subsequent starting according to the key characteristic data corresponding to the optimal class may be:

[0070] The key feature data corresponding to the optimal class is recorded as the standard key feature data, and it is determined whether the key feature data of the vehicle when it is subsequently started is within the range of the standard key feature data. If the key feature data of the vehicle when it is subsequently started is within the range of the standard key feature data, it is determined that the vehicle is subsequently started as an economical start. If the key feature data of the vehicle when it is subsequently started exceeds the range of the standard key feature data, the standard key feature data is fed back to the driver of the vehicle.

[0071] For example, taking the key feature data including the gear position of the gearbox, the accelerator pedal force and the engine speed as an example, after determining the optimal class and the optimal class is reasonable, combined with Figure 3-Figure 5 , the value corresponding to the center point of the gearbox gear, accelerator pedaling force and engine speed in the optimal class can be determined as the standard key feature data. Exemplarily, if the value corresponding to the center point of the gearbox gear, accelerator pedaling force and engine speed in the optimal class is the gearbox gear 3-4 gear, the accelerator pedaling force is less than 20%, and the engine speed is less than 615 rpm, then the gearbox gear 3-4 gear, the accelerator pedaling force is less than 20%, and the engine speed is less than 615 rpm as the standard key feature data. When the vehicle starts later, the corresponding gearbox gear, accelerator pedaling force and engine speed can be obtained. If the gearbox gear is 3-4 gear, the accelerator pedaling force is less than 20%, and the engine speed is less than 615 rpm, it can be determined that the starting state meets the economic requirements and is an economic start. At the same time, the gearbox gear 3-4 gear, the accelerator pedaling force is less than 20%, and the engine speed is less than 615 rpm can also be used as the optimal starting operation, as a warning reminder, at the right time, such as when the vehicle starts and does not meet the economic requirements or before the vehicle starts, feedback to the driver of the vehicle to improve the economy of the vehicle starting operation.

[0072] Among them, when obtaining the corresponding gearbox gear position, accelerator pedal force and engine speed when the vehicle starts later, the driving data of the vehicle when starting can be obtained first. If the current driving speed of the vehicle is v, the driving speed at the previous moment is v1, v1 is equal to 0 and v is greater than 0, it can be determined that the vehicle is currently in the starting state, and the gearbox gear position, accelerator pedal force and engine speed at the moment when the driving speed is v can be obtained to judge the subsequent vehicle starting economy.

[0073] The embodiment of the present invention mainly collects key feature data of the vehicle's historical starting status and the engine fuel efficiency economy index data, and then uses the k-means model for clustering to determine the optimal fuel efficiency economy range (that is, the engine fuel efficiency economy index data is in the optimal class of the engine's optimal working range), and then determines the economic gear, throttle opening and speed of the vehicle's start according to the optimal fuel efficiency economy range, so as to judge the economy of the vehicle's start, guide the driver's starting operation, and achieve the effect of starting fuel saving.

[0074] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0075] The following is an embodiment of the device of the present invention. For details not described in detail therein, reference may be made to the corresponding method embodiment described above.

[0076] Figure 7 The schematic diagram of the structure of the vehicle starting economy judging device provided by the embodiment of the present invention is shown. For the convenience of explanation, only the part related to the embodiment of the present invention is shown, which is described in detail as follows:

[0077] like Figure 7 As shown, the vehicle starting economy determination device includes: an acquisition module 71 , a processing module 72 and a determination module 73 .

[0078] An acquisition module 71 is used to acquire key characteristic data of the vehicle's historical starting state and engine fuel efficiency economy index data, where the key characteristic data is data characterizing the driver's operating characteristics when the vehicle starts;

[0079] The processing module 72 is used to perform clustering using the key feature data and the engine fuel efficiency and economy index data to obtain an optimal class in which the engine fuel efficiency and economy index data is in the optimal working range of the engine;

[0080] The judgment module 73 is used to judge the economy of the vehicle when it starts subsequently according to the key characteristic data corresponding to the optimal class.

[0081] The embodiment of the present invention obtains key feature data and engine fuel efficiency index data representing the driver's operating characteristics when the vehicle starts in the historical starting state of the vehicle, and then uses the key feature data and the engine fuel efficiency index data to perform cluster analysis to obtain the optimal class in which the engine fuel efficiency index data is in the optimal working range of the engine, so as to judge the economy of the vehicle when starting subsequently according to the key feature data corresponding to the optimal class in which the engine fuel efficiency index data is in the optimal working range of the engine, so that the judgment of the vehicle starting economy is more scientific and reasonable, and because the key feature data corresponding to the optimal class can represent the driver's operating characteristics corresponding to the optimal vehicle starting economy, the driver's starting operation can be better guided.

[0082] In a possible implementation, the acquisition module 71 may be used to acquire the engine speed, engine torque and instantaneous fuel consumption of the vehicle in the historical starting state;

[0083] The engine fuel efficiency economy index data of the vehicle's historical starting state is obtained based on the engine speed, engine torque and instantaneous fuel consumption.

[0084] In a possible implementation, the acquisition module 71 may be used to , obtain engine fuel efficiency economic index data of the vehicle's historical starting state;

[0085] in, The engine fuel efficiency economic index data of the vehicle's historical starting state, is the instantaneous fuel consumption, is the engine speed, is the engine torque.

[0086] In a possible implementation, the processing module 72 may be used to perform clustering using the key feature data and the engine fuel efficiency economy index data to obtain an optimal clustering result;

[0087] From the optimal clustering results, the class whose engine fuel efficiency economy index data is in the optimal working range of the engine and has the highest proportion is determined as the optimal class.

[0088] In a possible implementation, the processing module 72 may also be used to verify whether the optimal class is reasonable according to the proportion of the engine fuel efficiency economy index data corresponding to the optimal class in the optimal engine working range;

[0089] If the optimal class is reasonable, the economy of the vehicle during subsequent starting is determined based on the key feature data corresponding to the optimal class.

[0090] In a possible implementation, the judgment module 73 may be used to record the key feature data corresponding to the optimal class as the standard key feature data;

[0091] Determine whether the key characteristic data of the vehicle when it starts subsequently is within the range of the standard key characteristic data;

[0092] If the key characteristic data of the vehicle when starting subsequently is within the range of the standard key characteristic data, then the vehicle is determined to be started economically when starting subsequently;

[0093] If the key characteristic data of the vehicle at a subsequent start exceeds the range of the standard key characteristic data, the standard key characteristic data is fed back to the driver of the vehicle.

[0094] In a possible implementation, the key feature data includes at least two of the gear position of the transmission, the accelerator pedal force, and the engine speed.

[0095] Figure 8 is a schematic diagram of a terminal provided by an embodiment of the present invention. Figure 8As shown, the terminal 8 of this embodiment includes: a processor 80, a memory 81, and a computer program 82 stored in the memory 81 and executable on the processor 80. When the processor 80 executes the computer program 82, the steps in the above-mentioned vehicle starting economy determination method embodiments are implemented, such as Figure 1 Alternatively, when the processor 80 executes the computer program 82, the functions of each module / unit in the above-mentioned device embodiments are implemented, for example Figure 7 The functions of each module / unit are shown.

[0096] Exemplarily, the computer program 82 may be divided into one or more modules / units, one or more modules / units are stored in the memory 81 and executed by the processor 80 to implement the present invention. One or more modules / units may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program 82 in the terminal 8. For example, the computer program 82 may be divided into Figure 7 The modules / units shown.

[0097] The terminal 8 may be a computing device such as a vehicle-mounted terminal, a handheld terminal, or a cloud server. The terminal 8 may include, but is not limited to, a processor 80 and a memory 81. Those skilled in the art will appreciate that Figure 8 It is only an example of terminal 8 and does not constitute a limitation on terminal 8. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the terminal may also include input and output devices, network access devices, buses, etc.

[0098] The processor 80 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0099] The memory 81 may be an internal storage unit of the terminal 8, such as a hard disk or memory of the terminal 8. The memory 81 may also be an external storage device of the terminal 8, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the terminal 8. Further, the memory 81 may also include both an internal storage unit of the terminal 8 and an external storage device. The memory 81 is used to store computer programs and other programs and data required by the terminal. The memory 81 may also be used to temporarily store data that has been output or is to be output.

[0100] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0101] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0102] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0103] In the embodiments provided by the present invention, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are only schematic, for example, the division of modules or units is only a logical function division, and 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 through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0104] 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.

[0105] In addition, each functional unit in each embodiment of the present invention 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.

[0106] If the integrated module / 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 present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned vehicle starting economy judgment method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form. The computer-readable medium can include: any entity or device that can carry computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium.

[0107] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should be included in the protection scope of the present invention.

Claims

1. A method for judging the economic efficiency of vehicle starting, characterized in that: include: Acquire key characteristic data of the vehicle's historical starting state and engine fuel efficiency economy index data, wherein the key characteristic data is data characterizing the driver's operating characteristics when the vehicle starts; the key characteristic data includes at least two of the gear position of the transmission, the accelerator pedal force, and the engine speed; Clustering is performed using the key feature data and the engine fuel efficiency and economy index data to obtain an optimal class in which the engine fuel efficiency and economy index data is in an optimal engine operating range; wherein the engine optimal operating range is determined according to an engine universal characteristic diagram; Determining the economy of the vehicle when starting subsequently according to the key feature data corresponding to the optimal class; Clustering is performed using the key feature data and the engine fuel efficiency and economy index data to obtain an optimal class in which the engine fuel efficiency and economy index data is in an optimal engine operating range, including: Using the key feature data and the engine fuel efficiency economy index data to perform clustering to obtain an optimal clustering result; Determine from the optimal clustering results that the engine fuel efficiency and economy index data is in the optimal engine working range and the class with the highest proportion of the engine fuel efficiency and economy index data in the optimal engine working range is the optimal class; After determining from the optimal clustering result that the engine fuel efficiency and economy index data is in the optimal engine working range and the class with the highest proportion of the engine fuel efficiency and economy index data in the optimal engine working range is the optimal class, the method further includes: Verify whether the optimal class is reasonable according to the proportion of the engine fuel efficiency economy index data corresponding to the optimal class in the optimal working range of the engine; If the optimal class is reasonable, the economy of the vehicle during subsequent starting is determined based on the key feature data corresponding to the optimal class.

2. The vehicle starting economy determination method according to claim 1, characterized in that: Obtain the engine fuel efficiency and economy index data of the vehicle's historical starting status, including: Obtain the engine speed, engine torque and instantaneous fuel consumption of the vehicle's historical starting state; The engine fuel efficiency economy index data of the vehicle's historical starting state is obtained according to the engine speed, the engine torque and the instantaneous fuel consumption.

3. The vehicle starting economy determination method according to claim 2, characterized in that: The engine fuel efficiency economy index data of the vehicle in the historical starting state is obtained according to the engine speed, the engine torque and the instantaneous fuel consumption, including: according to , obtain engine fuel efficiency economic index data of the vehicle's historical starting state; in, The engine fuel efficiency economic index data of the vehicle's historical starting state, is the instantaneous fuel consumption, is the engine speed, is the engine torque.

4. The vehicle starting economy determination method according to claim 1, characterized in that: The economy of the vehicle when starting subsequently is determined according to the key characteristic data corresponding to the optimal class, including: Recording the key feature data corresponding to the optimal class as standard key feature data; Determine whether the key characteristic data of the vehicle when it starts subsequently is within the range of the standard key characteristic data; If the key characteristic data of the vehicle when starting subsequently is within the range of the standard key characteristic data, then the vehicle is determined to start subsequently as an economical start; If the key feature data of the vehicle when it subsequently starts is beyond the range of the standard key feature data, the standard key feature data is fed back to the driver of the vehicle.

5. A vehicle starting economy judging device, characterized in that: include: An acquisition module, used to acquire key characteristic data of the vehicle's historical starting state and engine fuel efficiency economy index data, wherein the key characteristic data is data characterizing the driver's operating characteristics when the vehicle starts; the key characteristic data includes at least two of the gear position of the transmission, the accelerator pedal force and the engine speed; a processing module, configured to cluster the key feature data and the engine fuel efficiency and economy index data to obtain an optimal class in which the engine fuel efficiency and economy index data is in an optimal engine operating range; wherein the engine optimal operating range is determined according to an engine universal characteristic diagram; A judgment module, used for judging the economy of the vehicle when starting subsequently according to the key characteristic data corresponding to the optimal class; The processing module is specifically used for: Using the key feature data and the engine fuel efficiency economy index data to perform clustering to obtain an optimal clustering result; Determine from the optimal clustering results that the engine fuel efficiency and economy index data is in the optimal engine working range and the class with the highest proportion of the engine fuel efficiency and economy index data in the optimal engine working range is the optimal class; The processing module is further used for: Verify whether the optimal class is reasonable according to the proportion of the engine fuel efficiency economy index data corresponding to the optimal class in the optimal working range of the engine; If the optimal class is reasonable, the economy of the vehicle during subsequent starting is determined based on the key feature data corresponding to the optimal class.

6. A terminal, characterized in that: The method comprises a memory and a processor, wherein the memory is used to store a computer program, and the processor is used to call and run the computer program stored in the memory to execute the method according to any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 4 are implemented.

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