Automobile power detection method, device and computer equipment

Abstract

The present application relates to the technical field of automobile performance detection, and discloses an automobile power detection method, device and computer equipment. By obtaining a fitness value and judging whether the fitness value exceeds a preset fitness value, if it exceeds the preset fitness value, it indicates that the current external environment is the external environment most often encountered in actual driving. If the current speed in this external environment is within the preset speed range, a timing instruction can be executed to time the acceleration time per 100 kilometers. During this process, the current speed of the automobile is still obtained in real time. If the current speed exceeds the preset speed value, the timing is stopped, and the timing result is sent to a mobile terminal to complete the automobile power detection. Since the acceleration time per 100 kilometers in the present application is tested in the external environment most often encountered in driving, the timing result can represent the time taken for the automobile to accelerate per 100 kilometers under normal circumstances. Compared with an ideal environment, the acceleration time per 100 kilometers in the present application is more accurate.

Description

Technical Field

[0001] The present application relates to the technical field of automobile performance detection, and in particular to an automobile power detection method, device and computer equipment. Background Art

[0002] The 0-100km / h acceleration time is one of the important indicators for evaluating the performance of a car, which refers to the acceleration time from 0 to 100km / h. Therefore, manufacturers usually mark the official 0-100km / h acceleration time in the vehicle's brochure. However, in actual tests, the actual measured 0-100km / h acceleration time is often inconsistent with the official 0-100km / h acceleration time. Therefore, there is currently a lack of a method that can accurately measure the 0-100km / h acceleration time. Summary of the invention

[0003] The main purpose of this application is to provide a method, device and computer equipment for detecting automobile power, aiming to solve the technical problem that the acceleration time per 100 kilometers measured in the prior art is not accurate enough.

[0004] The present application proposes a vehicle power detection method, which is applied to a mobile terminal, wherein the mobile terminal is communicatively connected with the vehicle, and comprises:

[0005] Get the current speed of the car in real time;

[0006] Acquiring a fitness value of the vehicle, wherein the fitness value is used to detect an environmental state of the vehicle;

[0007] Determine whether the current speed is within a preset speed range and whether the fitness value exceeds a preset fitness value;

[0008] If the current speed is within the preset speed range and the fitness value exceeds the preset fitness value, executing a start timing instruction;

[0009] It is determined whether the current speed exceeds a preset speed value. If the current speed exceeds the preset speed value, a stop timing instruction is executed, and the timing result is sent to the mobile terminal to complete the vehicle power detection.

[0010] Preferably, the step of obtaining the current speed of the vehicle in real time comprises:

[0011] Establishing a wireless connection with the car to send a request signal to the car to obtain vehicle condition data;

[0012] Receiving vehicle condition data fed back by the vehicle, wherein the vehicle condition data includes engine output speed, tire rolling radius, gear ratio of the gearbox, and total reduction ratio of the rear axle;

[0013] The current speed of the vehicle is calculated according to the vehicle condition data fed back by the vehicle, wherein the calculation formula is:

[0014] V = (0.377*N*R) / (Ig*I0);

[0015] Wherein, V represents the current speed of the vehicle, N represents the engine output speed, R represents the tire rolling radius, Ig represents the gear ratio of the gearbox, and I0 represents the total reduction ratio of the rear axle.

[0016] Preferably, the step of obtaining the fitness value of the car includes:

[0017] Acquire a first image of the road on which the vehicle is currently traveling;

[0018] Performing denoising on the first image based on a connected component labeling algorithm to obtain a second image;

[0019] parsing the second image to obtain second image data values, wherein the second image data values ​​include a road surface flatness value, a crack value, a slope value, and a road surface width value;

[0020] Determining whether the second image data value is less than a preset data value;

[0021] If the second image data value is less than a preset data value, obtaining the drag coefficient of the vehicle;

[0022] The second image data value is multiplied by the drag coefficient to obtain the adaptation value.

[0023] Preferably, the step of performing denoising on the first image based on a connected component labeling algorithm comprises:

[0024] Marking black pixels in the first image to obtain a plurality of marking points;

[0025] Randomly select four marking points at the four edges of the first image as feature points;

[0026] Filling the first image according to the feature points to obtain a non-black area and a black area;

[0027] The black area is extracted as a target information area to obtain a second image.

[0028] Preferably, the step of sending the timing result to the mobile terminal comprises:

[0029] Sending the timing result to the display interface of the mobile terminal;

[0030] Sending the timing result to the cloud server of the mobile terminal;

[0031] Receive ranking information fed back by the cloud server according to the timing result.

[0032] The present application also provides a vehicle power detection device, comprising:

[0033] The first acquisition module is used to acquire the current speed of the car in real time;

[0034] A second acquisition module is used to acquire a fitness value of the car, wherein the fitness value is used to detect the environmental state of the car;

[0035] A first judgment module is used to judge whether the current speed is within a preset speed range and whether the fitness value exceeds a preset fitness value;

[0036] A first execution module, configured to execute a start timing instruction if the current speed is within a preset speed range and the fitness value exceeds a preset fitness value;

[0037] The second judgment module is used to judge whether the current speed exceeds the preset speed value. If the current speed exceeds the preset speed value, a stop timing instruction is executed and the timing result is sent to the mobile terminal to complete the vehicle power detection.

[0038] Preferably, the first acquisition module includes:

[0039] A first acquisition unit, used to establish a wireless connection with the vehicle, and to send a request signal for acquiring vehicle condition data to the vehicle;

[0040] A first receiving unit is used to receive vehicle condition data fed back by the vehicle, wherein the vehicle condition data includes engine output speed, tire rolling radius, gear ratio of the gearbox, and total reduction ratio of the rear axle;

[0041] The first calculation unit is used to calculate the current speed of the vehicle according to the vehicle condition data fed back by the vehicle, wherein the calculation formula is:

[0042] V = (0.377*N*R) / (Ig*I0);

[0043] Wherein, V represents the current speed of the vehicle, N represents the engine output speed, R represents the tire rolling radius, Ig represents the gear ratio of the gearbox, and I0 represents the total reduction ratio of the rear axle.

[0044] Preferably, the second acquisition module comprises:

[0045] A second acquisition unit, used to acquire a first image of the road surface on which the vehicle is currently traveling;

[0046] A denoising unit, configured to perform denoising processing on the first image based on a connected component labeling algorithm to obtain a second image;

[0047] A parsing unit, configured to parse the second image to obtain second image data values, wherein the second image data values ​​include a road surface flatness value, a crack value, a slope value, and a road surface width value;

[0048] A first judging unit, configured to judge whether the second image data value is less than a preset data value;

[0049] A third acquisition unit, configured to acquire a drag coefficient of the vehicle if the second image data value is less than a preset data value;

[0050] The second calculation unit is used to multiply the second image data value by the drag coefficient to obtain the adaptation value.

[0051] The present application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned vehicle power detection method when executing the computer program.

[0052] The present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned vehicle power detection method are implemented.

[0053] The beneficial effects of the present application are as follows: the present application provides a vehicle power detection method, which can determine whether the current vehicle speed and the environmental state of the vehicle are the most suitable for the 100 km / h acceleration test under the actual driving state according to the current vehicle speed and the fitness value of the vehicle, that is, by obtaining the fitness value and determining whether the fitness value exceeds the preset fitness value, if it exceeds the preset fitness value, it means that the current external environment is the external environment most often encountered in the actual driving process, if the current speed in this external environment is within the preset speed range value, the timing instruction can be executed to time the 100 km / h acceleration time, in this process, the current speed of the vehicle is still obtained in real time, if the current speed exceeds the preset speed value, the timing is stopped, and the timing result is sent to the mobile terminal to complete the vehicle power detection; since the 100 km / h acceleration time in the present application is tested in the external environment most often encountered in the driving process, the timing result can represent the time it takes for the vehicle to accelerate to 100 km / h under normal circumstances, so compared with the ideal environment, the 100 km / h acceleration time tested by the present application is more in line with the actual situation, so the tested 100 km acceleration time is also more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a flow chart of a vehicle power detection method according to an embodiment of the present application.

[0055] Figure 2 This is a schematic structural diagram of an automobile power detection device according to an embodiment of the present application.

[0056] Figure 3 A schematic diagram of the internal structure of a computer device according to an embodiment of the present application.

[0057] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0058] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0059] like Figure 1-Figure 3 As shown, the present application proposes a vehicle power detection method, which is applied to a mobile terminal, and the mobile terminal is connected to the vehicle for communication, including:

[0060] S1. Get the current speed of the car in real time;

[0061] S2, obtaining a fitness value of the car, wherein the fitness value is used to detect the environmental state of the car;

[0062] S3, determining whether the current speed is within a preset speed range and whether the fitness value exceeds a preset fitness value;

[0063] S4, if the current speed is within the preset speed range and the fitness value exceeds the preset fitness value, executing a start timing instruction;

[0064] S5. Determine whether the current speed exceeds a preset speed value. If the current speed exceeds the preset speed value, execute a stop timing instruction and send the timing result to the mobile terminal to complete the vehicle power detection.

[0065] As described in the above steps S1-S5, in the prior art, the external environment is usually set to the most ideal state by default before the 100 km / h acceleration test is performed. Therefore, the 100 km / h acceleration time measured at this time is the ideal value; however, in the actual driving process, the actual external environment is not the same as the ideal external environment. The car may be affected by factors such as wind force, road conditions, and ambient temperature. Therefore, the 100 km / h acceleration time measured in the actual external environment and the 100 km / h acceleration time tested in the ideal external environment usually have errors; therefore, the present application can determine whether the current vehicle speed and the environmental state of the car are the most suitable for the 100 km / h acceleration test under the actual driving state according to the current vehicle speed and the fitness value of the car, that is, by obtaining the fitness value and determining whether the fitness value exceeds the preset fitness value. If it exceeds the preset fitness value, it means that when The external environment before is the external environment most commonly encountered in actual driving. If the current speed in this external environment is within the preset speed range (i.e. 0-100km / h), the timing instruction can be executed to time the acceleration time to 100 kilometers. During this process, the current speed of the car is still obtained in real time. If the current speed exceeds the preset speed value (i.e. 100km / h), the timing is stopped and the timing result is sent to the mobile terminal to complete the car power detection. Since the acceleration time to 100 kilometers in this application is tested in the external environment most commonly encountered in driving, the timing result can represent the time it takes for the car to accelerate to 100 kilometers under normal circumstances. Therefore, compared with the ideal environment, the acceleration time to 100 kilometers tested in this application is more in line with the actual situation, so the tested acceleration time to 100 kilometers is also more accurate.

[0066] In one embodiment, the step S1 of acquiring the current speed of the vehicle in real time includes:

[0067] S11, establishing a wireless connection with the car to send a request signal for obtaining vehicle condition data to the car;

[0068] S12, receiving vehicle condition data fed back by the vehicle, wherein the vehicle condition data includes engine output speed, tire rolling radius, gear ratio of the gearbox, and total reduction ratio of the rear axle;

[0069] S13, calculating the current speed of the vehicle according to the vehicle condition data fed back by the vehicle, wherein the calculation formula is:

[0070] V = (0.377*N*R) / (Ig*I0);

[0071] Wherein, V represents the current speed of the vehicle, N represents the engine output speed, R represents the tire rolling radius, Ig represents the gear ratio of the gearbox, and I0 represents the total reduction ratio of the rear axle.

[0072] As described in the above steps S11-S13, in the prior art, the current vehicle speed is usually checked by checking the vehicle tachometer. However, since the vehicle tachometer is affected by many external conditions, in addition, according to the national standard "Automobile Speedometer" (GB15082-2008), the speed indicated by the speedometer shall not be lower than the actual speed, and the indicated speed and the actual speed shall conform to the following relationship: "0≤Indicated speed-actual speed≤Actual speed / 10+4km / h", so the speed in the vehicle tachometer is usually greater than the actual speed. If the acceleration time from 0 to 100 km / h is calculated by obtaining the speed in the vehicle tachometer, the acceleration time from 0 to 100 km / h will be inaccurate, resulting in deviations in the results of the vehicle power detection. Therefore, the present application obtains the vehicle condition data of the vehicle and calculates the current speed of the vehicle based on the vehicle condition data. The calculated current speed is the actual current speed of the vehicle. This can make the calculation result of the acceleration from 0 to 100 km / h more accurate, thereby reducing the deviation value of the subsequent vehicle power detection results.

[0073] In one embodiment, the step S2 of obtaining the fitness value of the car includes:

[0074] S21, acquiring a first image of the road on which the vehicle is currently traveling;

[0075] S22, performing denoising processing on the first image based on a connected component labeling algorithm to obtain a second image;

[0076] S23, analyzing the second image to obtain second image data values, wherein the second image data values ​​include a road surface flatness value, a crack value, a slope value, and a road surface width value;

[0077] S24, determining whether the second image data value is less than a preset data value;

[0078] S25, if the second image data value is less than a preset data value, obtaining the drag coefficient of the vehicle;

[0079] S26. Multiply the second image data value by the drag coefficient to obtain the adaptation value.

[0080] As described in the above steps S21-S26, a first image of the road surface on which the car is currently traveling can be obtained by obtaining a road surface photo taken by a camera, and a second image can be obtained by denoising the first image, so that from the analyzed second image, it is possible to determine whether the road surface is flat, whether there are cracks, whether there are uphills and downhills, and obtain second image data values ​​such as the road surface width value. If the above second image data value is less than the preset data value, it means that the current road condition is the usual external environment during actual driving. At this time, the car's drag coefficient can be obtained, and the above second image data value is multiplied by the drag coefficient to obtain an adaptation value. When the car is driving, due to the action of air, aerodynamic forces in three directions, namely longitudinal, lateral and vertical, are generated around the center of gravity of the car at the same time, which will have different effects on high-speed cars. Among them, the longitudinal aerodynamic force is the largest, accounting for about 8% of the overall air force 0% or more, therefore, the component of the air force in the driving direction that the car is subjected to when traveling in a straight line is called air resistance, and the drag coefficient is generally a function of the Reynolds number, and the car's air resistance is directly proportional to the drag coefficient. Therefore, by obtaining the car's drag coefficient, it is possible to understand the extent to which the car is affected by air resistance during driving. Therefore, the drag coefficient is multiplied by the second image data value, and the fitness value obtained can be used to calculate different fitness values ​​for different drag coefficients, that is, the fitness value corresponding to the car can be calculated for different types of cars. In this way, by checking the fitness value, it is possible to understand whether the environmental state of different types of cars is the external environment most commonly encountered by this type of car, so that when conducting a 100 km / h acceleration time test, although different types of cars face the same road conditions, their fitness values ​​are different, so the measured 100 km / h acceleration time is also more accurate.

[0081] In one embodiment, the step S22 of denoising the first image based on the connected component labeling algorithm includes:

[0082] S221, marking black pixels in the first image to obtain a plurality of marking points;

[0083] S222: Randomly select four marking points at the four edges of the first image as feature points;

[0084] S223, filling the first image according to the feature points to obtain a non-black area and a black area;

[0085] S224: Extract the black area as a target information area to obtain a second image.

[0086] As described in the above steps S221-S224, black pixels are generally crack areas. By marking the black pixels and filling the first image according to the feature points, the non-black areas and the melanin areas can be scanned more accurately, avoiding the possibility of black areas being easily eliminated. The black areas can be better detected and extracted as target information areas. The obtained second image has high precision and the black areas are more obvious, which facilitates the subsequent analysis of the second image, so that the obtained second image data values ​​are more accurate.

[0087] In one embodiment, the step S5 of sending the timing result to the mobile terminal includes:

[0088] S51, sending the timing result to the display interface of the mobile terminal;

[0089] S52, sending the timing result to the cloud server of the mobile terminal;

[0090] S53: Receive ranking information fed back by the cloud server according to the timing result.

[0091] As described in the above steps S51-S53, the timing results can be sent to the display interface of the mobile terminal so that the user can intuitively understand the time required for acceleration from 0 to 100 km / h. In addition, each timing result can also be sent to the cloud server of the mobile terminal. The cloud server can rank each timing result, so that the ranking of the acceleration time from 0 to 100 km / h can be understood by receiving the ranking information fed back by the cloud server. The ranking information includes not only the timing results, but also the current vehicle speed and fitness value of each test. In this way, it is convenient to understand the corresponding acceleration time from 0 to 100 km / h based on the current vehicle speed and fitness value, so as to make a comprehensive judgment on the vehicle power based on multiple timing results.

[0092] The present application also provides a vehicle power detection device, comprising:

[0093] The first acquisition module 1 is used to acquire the current speed of the car in real time;

[0094] A second acquisition module 2 is used to acquire a fitness value of the car, wherein the fitness value is used to detect the environmental state of the car;

[0095] The first judgment module 3 is used to judge whether the current speed is within a preset speed range and whether the fitness value exceeds a preset fitness value;

[0096] A first execution module 4, configured to execute a start timing instruction if the current speed is within a preset speed range and the fitness value exceeds a preset fitness value;

[0097] The second judgment module 5 is used to judge whether the current speed exceeds the preset speed value. If the current speed exceeds the preset speed value, a stop timing instruction is executed and the timing result is sent to the mobile terminal to complete the vehicle power detection.

[0098] In one embodiment, the first acquisition module 1 includes:

[0099] A first acquisition unit, used to establish a wireless connection with the vehicle, and to send a request signal for acquiring vehicle condition data to the vehicle;

[0100] A first receiving unit is used to receive vehicle condition data fed back by the vehicle, wherein the vehicle condition data includes engine output speed, tire rolling radius, gear ratio of the gearbox, and total reduction ratio of the rear axle;

[0101] The first calculation unit is used to calculate the current speed of the vehicle according to the vehicle condition data fed back by the vehicle, wherein the calculation formula is:

[0102] V = (0.377*N*R) / (Ig*I0);

[0103] Wherein, V represents the current speed of the vehicle, N represents the engine output speed, R represents the tire rolling radius, Ig represents the gear ratio of the gearbox, and I0 represents the total reduction ratio of the rear axle.

[0104] In one embodiment, the second acquisition module 2 includes:

[0105] A second acquisition unit, used to acquire a first image of the road surface on which the vehicle is currently traveling;

[0106] A denoising unit, configured to perform denoising processing on the first image based on a connected component labeling algorithm to obtain a second image;

[0107] A parsing unit, configured to parse the second image to obtain second image data values, wherein the second image data values ​​include a road surface flatness value, a crack value, a slope value, and a road surface width value;

[0108] A first judging unit, configured to judge whether the second image data value is less than a preset data value;

[0109] A third acquisition unit, configured to acquire a drag coefficient of the vehicle if the second image data value is less than a preset data value;

[0110] The second calculation unit is used to multiply the second image data value by the drag coefficient to obtain the adaptation value.

[0111] In one embodiment, the denoising unit comprises:

[0112] A marking subunit, used for marking black pixels in the first image to obtain a plurality of marking points;

[0113] A selection subunit, used for randomly selecting four of the marking points as feature points at four edges of the first image;

[0114] A filling subunit, used for filling the first image according to the feature points to obtain a non-black area and a black area;

[0115] The extraction subunit is used to extract the black area as a target information area to obtain a second image.

[0116] In one embodiment, the second determination module 5 includes:

[0117] A first sending unit, used to send the timing result to the display interface of the mobile terminal;

[0118] A second sending unit, used to send the timing result to the cloud server of the mobile terminal;

[0119] A ranking unit is used to receive ranking information fed back by the cloud server according to the timing result.

[0120] like Figure 3 As shown, the present application also provides a computer device, which may be a server, and its internal structure may be as shown in Figure 3 As shown. The computer device includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store all data required for the process of the automobile power detection method. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the automobile power detection method is implemented.

[0121] Those skilled in the art will understand that Figure 3 The structure shown in is merely a block diagram of a portion of the structure related to the present application solution and does not constitute a limitation on the computer device to which the present application solution is applied.

[0122] An embodiment of the present application further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, any one of the above-mentioned vehicle power detection methods is implemented.

[0123] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing related hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided in this application and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0124] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0125] The above description is only a preferred embodiment of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A vehicle power detection method, applied to a mobile terminal, wherein the mobile terminal is connected to the vehicle for communication, characterized in that: include: Get the current speed of the car in real time; Acquiring a fitness value of the vehicle, wherein the fitness value is used to detect an environmental state of the vehicle; Determine whether the current speed is within a preset speed range and whether the fitness value exceeds a preset fitness value; If the current speed is within the preset speed range and the fitness value exceeds the preset fitness value, executing a start timing instruction; Determine whether the current speed exceeds a preset speed value, and if the current speed exceeds the preset speed value, execute a stop timing instruction, and send the timing result to the mobile terminal to complete the vehicle power detection; The obtaining of the fitness value of the car includes: Acquire a first image of the road on which the vehicle is currently traveling; Performing denoising on the first image based on a connected component labeling algorithm to obtain a second image; parsing the second image to obtain second image data values, wherein the second image data values ​​include a road surface flatness value, a crack value, a slope value, and a road surface width value; Determining whether the second image data value is less than a preset data value; If the second image data value is less than the preset data value, obtaining the drag coefficient of the vehicle; multiplying the second image data value by the drag coefficient to obtain the fitness value; The denoising process of the first image based on the connected component labeling algorithm includes: Marking black pixels in the first image to obtain a plurality of marking points; Randomly select four marking points at the four edges of the first image as feature points; Filling the first image according to the feature points to obtain a non-black area and a black area; The black area is extracted as a target information area to obtain the second image.

2. The vehicle power detection method according to claim 1, characterized in that: The step of obtaining the current speed of the vehicle in real time comprises: Establishing a wireless connection with the car to send a request signal to the car to obtain vehicle condition data; Receiving vehicle condition data fed back by the vehicle, wherein the vehicle condition data includes engine output speed, tire rolling radius, gear ratio of the gearbox, and total reduction ratio of the rear axle; The current speed of the vehicle is calculated according to the vehicle condition data fed back by the vehicle, wherein the calculation formula is: V=(0.377*N*R) / (I g *I0); Wherein, V represents the current speed of the vehicle, N represents the engine output speed, R represents the tire rolling radius, Ig represents the gear ratio of the gearbox, and I0 represents the total reduction ratio of the rear axle.

3. The vehicle power detection method according to claim 1, characterized in that: The step of sending the timing result to the mobile terminal comprises: Sending the timing result to the display interface of the mobile terminal; Sending the timing result to the cloud server of the mobile terminal; Receive ranking information fed back by the cloud server according to the timing result.

4. An automobile power detection device, characterized in that: include: The first acquisition module is used to acquire the current speed of the car in real time; A second acquisition module is used to acquire a fitness value of the car, wherein the fitness value is used to detect the environmental state of the car; A first judgment module is used to judge whether the current speed is within a preset speed range and whether the fitness value exceeds a preset fitness value; A first execution module, configured to execute a start timing instruction if the current speed is within a preset speed range and the fitness value exceeds the preset fitness value; A second judgment module is used to judge whether the current speed exceeds a preset speed value, and if the current speed exceeds the preset speed value, a stop timing instruction is executed, and the timing result is sent to the mobile terminal to complete the vehicle power detection; The second acquisition module includes: A second acquisition unit, used to acquire a first image of the road surface on which the vehicle is currently traveling; A denoising unit, configured to perform denoising processing on the first image based on a connected component labeling algorithm to obtain a second image; A parsing unit, configured to parse the second image to obtain second image data values, wherein the second image data values ​​include a road surface flatness value, a crack value, a slope value, and a road surface width value; A first judging unit, configured to judge whether the second image data value is less than a preset data value; A third acquisition unit, configured to acquire a drag coefficient of the vehicle if the second image data value is less than the preset data value; a second calculation unit, configured to multiply the second image data value by the drag coefficient to obtain the fitness value; The denoising unit comprises: A marking subunit, used for marking black pixels in the first image to obtain a plurality of marking points; A selection subunit, used for randomly selecting four of the marking points as feature points at four edges of the first image; A filling subunit, used for filling the first image according to the feature points to obtain a non-black area and a black area; The extraction subunit is used to extract the black area as a target information area to obtain the second image.

5. The vehicle power detection device according to claim 4, characterized in that: The first acquisition module includes: A first acquisition unit, used to establish a wireless connection with the vehicle, and to send a request signal for acquiring vehicle condition data to the vehicle; A first receiving unit is used to receive vehicle condition data fed back by the vehicle, wherein the vehicle condition data includes engine output speed, tire rolling radius, gear ratio of the gearbox, and total reduction ratio of the rear axle; The first calculation unit is used to calculate the current speed of the vehicle according to the vehicle condition data fed back by the vehicle, wherein the calculation formula is: V = (0.377*N*R) / (Ig*I0); Wherein, V represents the current speed of the vehicle, N represents the engine output speed, R represents the tire rolling radius, Ig represents the gear ratio of the gearbox, and I0 represents the total reduction ratio of the rear axle.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the vehicle power detection method according to any one of claims 1 to 3 are implemented.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the vehicle power detection method according to any one of claims 1 to 3 are implemented.

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