Method, device and equipment for identifying vehicle with abnormal oil consumption and medium

Abstract

The invention discloses a method, a device and equipment for identifying a vehicle with abnormal fuel consumption and a medium. The method comprises the following steps: screening a plurality of target vehicles with the same running route and static attribute information in a preset time interval; respectively determining the fuel consumption value of each target vehicle in the time interval; forming a fuel consumption interval according to the minimum fuel consumption value and the maximum fuel consumption value in all the target vehicles; dividing the fuel consumption interval into a plurality of fuel consumption sections according to a preset fuel consumption interval; and according to the number of the target vehicles in each fuel consumption section, identifying the vehicles with abnormal fuel consumption in the target vehicles. The vehicle with abnormal fuel consumption can be identified according to the fuel consumption distribution proportion of a large number of vehicles with the same running route and static attribute information, and the identification result is closer to the actual use condition of the vehicle, so that the vehicle with abnormal fuel consumption can be identified more accurately.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle fuel consumption identification, and in particular to a method, device, equipment and medium for identifying vehicles with abnormal fuel consumption. Background Art

[0002] Fuel consumption is the main cost expenditure in vehicle operation. When the vehicle's fuel consumption is abnormal, additional fuel expenses will be incurred, resulting in increased vehicle operating costs.

[0003] In related technologies, abnormal fuel consumption is typically determined by calculating the vehicle's fuel consumption per 100 kilometers based on the vehicle's total fuel consumption and total mileage. A normal fuel consumption range per 100 kilometers is then set based on the vehicle model. The system then determines whether the vehicle's fuel consumption per 100 kilometers falls within the set normal fuel consumption range. If not, the vehicle's fuel consumption is considered abnormal.

[0004] However, fuel consumption fluctuates throughout a vehicle's lifecycle, across different mileage segments and time periods. Furthermore, fuel consumption per 100 kilometers (km) can vary depending on the vehicle owner's usage scenarios and locations. Therefore, determining whether a vehicle's fuel consumption is abnormal based solely on whether it falls within a fixed, normal fuel consumption range is inaccurate and prone to errors.

[0005] Therefore, how to accurately judge whether there is an abnormality in vehicle fuel consumption is a technical problem that needs to be solved urgently. Summary of the Invention

[0006] The present application provides a method, device, equipment and medium for identifying vehicles with abnormal fuel consumption, which can solve the technical problem in the prior art that it is impossible to accurately determine whether the vehicle's fuel consumption is abnormal based on a set fixed fuel consumption range.

[0007] In a first aspect, an embodiment of the present application provides a method for identifying a vehicle with abnormal fuel consumption, the method comprising:

[0008] Filter multiple target vehicles with the same running routes and static attribute information within a preset time interval;

[0009] Determining the fuel consumption value of each target vehicle within the time interval;

[0010] A fuel consumption range is formed according to the minimum fuel consumption value and the maximum fuel consumption value of all target vehicles;

[0011] Dividing the fuel consumption range into a plurality of fuel consumption sections according to a preset fuel consumption interval;

[0012] According to the number of target vehicles in each fuel consumption section, vehicles with abnormal fuel consumption among the target vehicles are identified.

[0013] In conjunction with the first aspect, in one embodiment, identifying vehicles with abnormal fuel consumption among target vehicles based on the number of target vehicles in each fuel consumption section includes:

[0014] Determine a first ratio of the number of target vehicles in the first fuel consumption section with the largest fuel consumption value to the total number of target vehicles;

[0015] Determining whether the first proportion is less than a preset proportion threshold;

[0016] If so, the proportions of the fuel consumption sections adjacent to the first fuel consumption section are calculated in sequence until a target fuel consumption section is found, such that the total proportion of all fuel consumption sections between the first fuel consumption section and the target fuel consumption section is greater than or equal to the proportion threshold, and all target vehicles between the first fuel consumption section and the target fuel consumption section are identified as vehicles with abnormal fuel consumption;

[0017] Otherwise, it is determined that there is no vehicle with abnormal fuel consumption among the target vehicles.

[0018] In one embodiment, determining the fuel consumption value of each target vehicle within the time interval includes:

[0019] The fuel consumption per 100 kilometers of each target vehicle within the time interval is determined respectively.

[0020] In one embodiment, determining the fuel consumption per 100 kilometers of each target vehicle within the time interval includes:

[0021] The fuel consumption per 100 kilometers of each target vehicle in the time interval is calculated based on the daily mileage and daily fuel consumption of each target vehicle in the time interval.

[0022] In one embodiment, the static attribute information includes the vehicle's brand, model, purpose, and usage scenario.

[0023] In one embodiment, after identifying a vehicle with abnormal fuel consumption among target vehicles, the method further includes:

[0024] Sending a fuel consumption abnormality prompt message to the vehicle with the abnormal fuel consumption.

[0025] In a second aspect, an embodiment of the present application provides a device for identifying a vehicle with abnormal fuel consumption, the device comprising:

[0026] A screening module, which is used to screen multiple target vehicles with the same running routes and static attribute information within a preset time interval;

[0027] a determination module, configured to determine the fuel consumption value of each target vehicle within the time interval;

[0028] A composition module, which is used to form a fuel consumption range according to the minimum fuel consumption value and the maximum fuel consumption value of all target vehicles;

[0029] a division module, configured to divide the fuel consumption interval into a plurality of fuel consumption sections according to a preset fuel consumption interval;

[0030] The identification module is used to identify vehicles with abnormal fuel consumption among the target vehicles according to the number of target vehicles in each fuel consumption section.

[0031] In conjunction with the second aspect, in one embodiment, the identification module is further configured to:

[0032] Determine a first ratio of the number of target vehicles in the first fuel consumption section with the largest fuel consumption value to the total number of target vehicles;

[0033] Determining whether the first proportion is less than a preset proportion threshold;

[0034] If so, the proportions of the fuel consumption sections adjacent to the first fuel consumption section are calculated in sequence until a target fuel consumption section is found, such that the total proportion of all fuel consumption sections between the first fuel consumption section and the target fuel consumption section is greater than or equal to the proportion threshold, and all target vehicles between the first fuel consumption section and the target fuel consumption section are identified as vehicles with abnormal fuel consumption;

[0035] Otherwise, it is determined that there is no vehicle with abnormal fuel consumption among the target vehicles.

[0036] In one embodiment, the static attribute information includes the vehicle's brand, model, purpose, and usage scenario.

[0037] In one embodiment, the determining module is further configured to:

[0038] The fuel consumption per 100 kilometers of each target vehicle within the time interval is determined respectively.

[0039] In one embodiment, the determining module is further configured to:

[0040] The fuel consumption per 100 kilometers of each target vehicle in the time interval is calculated based on the daily mileage and daily fuel consumption of each target vehicle in the time interval.

[0041] In one embodiment, the device is further configured to: after identifying a vehicle with abnormal fuel consumption among target vehicles, issue fuel consumption abnormality prompt information of the vehicle with abnormal fuel consumption.

[0042] In a third aspect, an embodiment of the present application provides a device for identifying vehicles with abnormal fuel consumption, wherein the device comprises a processor, a memory, and a program for identifying vehicles with abnormal fuel consumption stored in the memory and executable by the processor, wherein when the program for identifying vehicles with abnormal fuel consumption is executed by the processor, the steps of the method for identifying vehicles with abnormal fuel consumption as described in any one of the above items are implemented.

[0043] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, characterized in that a program for identifying vehicles with abnormal fuel consumption is stored on the computer-readable storage medium, wherein when the program for identifying vehicles with abnormal fuel consumption is executed by a processor, the steps of the method for identifying vehicles with abnormal fuel consumption as described in any one of the above items are implemented.

[0044] The embodiments of the present application provide a method, apparatus, device, and medium for identifying vehicles with abnormal fuel consumption. The method involves screening multiple target vehicles with identical routes and static attribute information within a preset time interval; determining the fuel consumption value of each target vehicle within the time interval; forming a fuel consumption interval based on the minimum and maximum fuel consumption values ​​of all target vehicles; dividing the fuel consumption interval into multiple fuel consumption segments according to preset fuel consumption intervals; and identifying vehicles with abnormal fuel consumption among the target vehicles based on the number of target vehicles in each fuel consumption segment. The method identifies vehicles with abnormal fuel consumption based on the fuel consumption distribution ratio of a large number of vehicles with identical routes and static attribute information. The identification result is closer to the actual vehicle usage, making the identification of vehicles with abnormal fuel consumption more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 This is a flow chart of an embodiment of a method for identifying vehicles with abnormal fuel consumption according to the present application;

[0046] Figure 2 This is a functional module diagram of an embodiment of a device for identifying vehicles with abnormal fuel consumption according to the present application;

[0047] Figure 3 This is a schematic diagram of the hardware structure of the device for identifying vehicles with abnormal fuel consumption involved in the embodiment of the present application. DETAILED DESCRIPTION

[0048] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0049] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0050] In a first aspect, embodiments of the present application provide a method for identifying vehicles with abnormal fuel consumption. This method can be used on an Internet of Vehicles platform or other vehicle management platforms.

[0051] In one embodiment, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the method for identifying vehicles with abnormal fuel consumption in this application. Figure 1 As shown, the method for identifying a vehicle with abnormal fuel consumption includes:

[0052] Step S101: Filter multiple target vehicles with the same running routes and static attribute information within a preset time interval.

[0053] It's worth noting that after a vehicle leaves the factory, the IoV platform records each vehicle's static attribute information. This static attribute information includes the vehicle's make, model, purpose, and usage scenario. Vehicle makes include pickup trucks, vans, light trucks, or heavy trucks; model includes the specific model; purpose includes long-distance or short-distance freight; and usage scenarios include transporting construction materials, machinery, or agricultural products.

[0054] The IoV platform also collects information about each vehicle's daily driving, including mileage, fuel consumption, and starting and ending locations. This information derives each vehicle's daily mileage, fuel consumption, and route. For example, a vehicle might travel from Wuhan to Changsha.

[0055] The time interval can be set according to the identification requirements of vehicles with abnormal fuel consumption. In this embodiment, it is set on a monthly basis. For example, the time interval can be set to March to June.

[0056] Based on the input static attribute information and collected routes, the IoV platform selects multiple vehicles with the same route, make, model, purpose, and usage scenario within a preset time period as target vehicles. For example, the platform selects multiple vehicles operating from March to June, with a route from Wuhan to Guangzhou, a van make, HD13-512 model, a long-distance transport purpose, and a usage scenario of transporting construction materials.

[0057] Explanatory note: since different temperatures, altitudes, air pressures, road conditions, and different uses and usage scenarios when a vehicle is running will all affect the vehicle's fuel consumption, a screening time interval is set in this embodiment to ensure the consistency of the vehicle's running temperature, and the same running route is used as the screening dimension to ensure the consistency of the vehicle's running altitude, air pressure and road conditions. At the same time, the same use and usage scenarios are screened to eliminate the influence of external factors such as temperature, altitude, air pressure, road conditions, and different uses and usage scenarios on the identification of abnormal vehicle fuel consumption, thereby improving the accuracy of identifying vehicles with abnormal fuel consumption.

[0058] Step S201: Determine the fuel consumption value of each target vehicle within the time interval.

[0059] Optionally, the fuel consumption value is the fuel consumption per 100 kilometers, and the fuel consumption per 100 kilometers can better reflect the long-term fuel consumption trend of the vehicle.

[0060] In one embodiment, determining the fuel consumption per 100 kilometers for each target vehicle within the time interval includes calculating the fuel consumption per 100 kilometers for each target vehicle within the time interval based on the daily mileage and daily fuel consumption of each target vehicle within the time interval. The specific method for calculating the fuel consumption per 100 kilometers for each target vehicle within the time interval includes calculating the total mileage within the time interval based on the daily mileage of each target vehicle, calculating the total fuel consumption within the time interval based on the daily fuel consumption, dividing the total fuel consumption by the total mileage to obtain the fuel consumption per kilometer, and thereby obtaining the fuel consumption per 100 kilometers for each target vehicle.

[0061] Step S301: forming a fuel consumption range according to the minimum fuel consumption value and the maximum fuel consumption value of all target vehicles.

[0062] For example, the Internet of Vehicles platform statistically sorts the fuel consumption values ​​of each target vehicle, obtains the minimum fuel consumption value min and the maximum fuel consumption value max, and generates a fuel consumption range [min, max].

[0063] Step S401: Divide the fuel consumption range into multiple fuel consumption sections according to preset fuel consumption intervals.

[0064] It is worth noting that the fuel consumption interval can be set as needed, and the fuel consumption segments can be divided into two or more segments. In this embodiment, the fuel consumption interval is set to 2L / 100km, and the multiple fuel consumption segments are divided as follows: [min, min+2], [min+2, min+4]...[max-4, max-2] [max-2, max].

[0065] Step S501: Identify vehicles with abnormal fuel consumption among target vehicles based on the number of target vehicles in each fuel consumption section.

[0066] Specifically, determine a first proportion of the number of target vehicles in the first fuel consumption section with the largest fuel consumption value to the total number of target vehicles; judge whether the first proportion is less than a preset proportion threshold; if so, calculate the proportions of fuel consumption sections adjacent to the first fuel consumption section in sequence until a target fuel consumption section is found, so that the total proportion of all fuel consumption sections between the first fuel consumption section and the target fuel consumption section is greater than or equal to the proportion threshold, and identify all target vehicles within the first fuel consumption section to the target fuel consumption section as vehicles with abnormal fuel consumption; otherwise, determine that there are no vehicles with abnormal fuel consumption among the target vehicles.

[0067] Exemplarily, after the fuel consumption ranges are defined, the fuel consumption range into which each target vehicle's fuel consumption value falls is determined, thereby determining the number of target vehicles in each fuel consumption range. A first percentage of the number of target vehicles in the first fuel consumption range [max-2, max], which has the highest fuel consumption value, relative to the total number of target vehicles is determined. In this embodiment, the percentage threshold is set to 5%.

[0068] If the first proportion is less than 5%, it indicates that the fuel consumption value of the target vehicle is accidental within the first fuel consumption section [max-2, max], and there is an abnormal fuel consumption problem. Then, it is judged whether the cumulative total proportion of the number of target vehicles in the [max-4, max-2] section adjacent to the first fuel consumption section [max-2, max] plus the corresponding first proportion of the [max-2, max] section is less than or equal to 5%. The judgment is made in sequence until the target section [max-m, max-n] (where mn = 2) with a cumulative total proportion greater than or equal to 5% is obtained. All target vehicles with fuel consumption values ​​in the [max-2, max] section to the [max-m, max-n] section are marked as vehicles with abnormal fuel consumption.

[0069] If the first proportion is greater than or equal to 5%, it indicates that fuel consumption is a common phenomenon within the first fuel consumption range [max-2, max]. Therefore, it is determined that all target vehicles do not have abnormal fuel consumption, that is, there is no vehicle with abnormal fuel consumption among the target vehicles.

[0070] It is worth noting that when calculating the proportion of the number of target vehicles in each fuel consumption section to the total number of target vehicles, the proportion corresponding to each fuel consumption section can be obtained by sorting the fuel consumption values ​​of the fuel consumption sections from small to large, or after determining that the first proportion of the first fuel consumption section is less than the proportion threshold, the proportion of the approached fuel consumption section can be calculated in sequence when judging forward in sequence.

[0071] In a preferred embodiment, after identifying vehicles with abnormal fuel consumption among target vehicles, the system further includes: issuing a fuel consumption abnormality alert to notify the vehicle owner or vehicle management personnel of the abnormal fuel consumption. Furthermore, the IoV platform can analyze the cause of the abnormal fuel consumption based on the driver's driving habits and the vehicle's software and hardware configuration, combined with vehicle fuel consumption data, generate an analysis report, and provide feedback to vehicle management personnel, enabling them to promptly optimize vehicle usage and maintenance strategies.

[0072] The method for identifying vehicles with abnormal fuel consumption provided in this embodiment screens target vehicles from multiple dimensions, calculates the target vehicles' fuel consumption per 100 kilometers, and uses the fuel consumption distribution ratio to identify vehicles with abnormal fuel consumption. This makes the judgment result closer to the actual use of the vehicle, achieving more accurate identification of vehicles with abnormal fuel consumption. It can also issue a warning in a timely manner when abnormal vehicle fuel consumption is discovered, reducing the possibility of the problem escalating. Abnormal fuel consumption can often be related to mechanical failure or bad driving habits. Timely identification and resolution of the problem can improve the overall performance and driving safety of the vehicle. By analyzing the patterns and causes of abnormal fuel consumption, the vehicle's maintenance plan and service strategy can be optimized to ensure that the vehicle is in optimal condition.

[0073] In a second aspect, an embodiment of the present application further provides a device for identifying vehicles with abnormal fuel consumption. The device can be used in a vehicle networking platform.

[0074] In one embodiment, referring to Figure 2 , Figure 2 This is a functional module diagram of an embodiment of the device for identifying vehicles with abnormal fuel consumption in this application. Figure 2 As shown, the device for identifying a vehicle with abnormal fuel consumption includes:

[0075] The screening module is used to screen multiple target vehicles with the same running routes and static attribute information within a preset time interval.

[0076] It's worth noting that after a vehicle leaves the factory, the IoV platform records each vehicle's static attribute information. This static attribute information includes the vehicle's make, model, purpose, and usage scenario. Vehicle makes include pickup trucks, vans, light trucks, or heavy trucks; model includes the specific model; purpose includes long-distance or short-distance freight; and usage scenarios include transporting construction materials, machinery, or agricultural products.

[0077] The IoV platform also collects information about each vehicle's daily driving, including mileage, fuel consumption, and starting and ending locations. This information derives each vehicle's daily mileage, fuel consumption, and route. For example, a vehicle might travel from Wuhan to Changsha.

[0078] The time interval can be set according to the identification requirements of vehicles with abnormal fuel consumption. In this embodiment, it is set on a monthly basis. For example, the time interval can be set to March to June.

[0079] The screening module uses the input static attribute information and collected routes to select multiple vehicles with the same route, make, model, purpose, and usage scenario within a preset time period as target vehicles. For example, the target vehicles are vans, HD13-512 models, and long-distance transport vehicles operating from March to June, with the same route from Wuhan to Guangzhou and the same usage scenario as construction materials.

[0080] The determination module is used to respectively determine the fuel consumption value of each target vehicle within the time interval.

[0081] Optionally, the fuel consumption value is the fuel consumption per 100 kilometers, and the fuel consumption per 100 kilometers can better reflect the long-term fuel consumption trend of the vehicle.

[0082] In one embodiment, the determination module is further configured to calculate the fuel consumption per 100 kilometers of each target vehicle within the time interval based on the daily mileage and daily fuel consumption of each target vehicle within the time interval. The specific method for calculating the fuel consumption per 100 kilometers of each target vehicle within the time interval includes: calculating the total mileage within the time interval based on the daily mileage of each target vehicle, calculating the total fuel consumption within the time interval based on the daily fuel consumption, dividing the total fuel consumption by the total mileage to obtain the fuel consumption per kilometer, and further obtaining the fuel consumption per 100 kilometers of each target vehicle.

[0083] The composition module is used to form a fuel consumption range according to the minimum fuel consumption value and the maximum fuel consumption value of all target vehicles.

[0084] For example, the component module is also used to statistically sort the fuel consumption values ​​of each target vehicle, obtain the minimum fuel consumption value min and the maximum fuel consumption value max, and generate a fuel consumption interval [min, max].

[0085] The division module is used to divide the fuel consumption interval into multiple fuel consumption sections according to the preset fuel consumption interval.

[0086] It is worth noting that the fuel consumption interval can be set as needed, and the fuel consumption segments can be divided into two or more segments. In this embodiment, the fuel consumption interval is set to 2L / 100km, and the multiple fuel consumption segments are divided as follows: [min, min+2], [min+2, min+4]...[max-4, max-2] [max-2, max].

[0087] The identification module is used to identify vehicles with abnormal fuel consumption among the target vehicles according to the number of target vehicles in each fuel consumption section.

[0088] Furthermore, in one embodiment, the identification module is further configured to:

[0089] Determine a first ratio of the number of target vehicles in the first fuel consumption section with the largest fuel consumption value to the total number of target vehicles;

[0090] Determining whether the first proportion is less than a preset proportion threshold;

[0091] If so, the proportions of the fuel consumption sections adjacent to the first fuel consumption section are calculated in sequence until a target fuel consumption section is found, such that the total proportion of all fuel consumption sections between the first fuel consumption section and the target fuel consumption section is greater than or equal to the proportion threshold, and all target vehicles between the first fuel consumption section and the target fuel consumption section are identified as vehicles with abnormal fuel consumption;

[0092] Otherwise, it is determined that there is no vehicle with abnormal fuel consumption among the target vehicles.

[0093] Exemplarily, after the fuel consumption ranges are defined, the identification module further determines the fuel consumption range into which each target vehicle's fuel consumption value falls, thereby determining the number of target vehicles in each fuel consumption range. A first percentage of the total number of target vehicles in the first fuel consumption range [max-2, max], which has the highest fuel consumption value, is determined. In this embodiment, the percentage threshold is set to 5%.

[0094] If the first proportion is less than 5%, it indicates that the fuel consumption value of the target vehicle is accidental within the first fuel consumption section [max-2, max], and there is an abnormal fuel consumption problem. Then, it is judged whether the cumulative total proportion of the number of target vehicles in the [max-4, max-2] section adjacent to the first fuel consumption section [max-2, max] plus the corresponding first proportion of the [max-2, max] section is less than or equal to 5%. The judgment is made in sequence until the target section [max-m, max-n] (where mn = 2) with a cumulative total proportion greater than or equal to 5% is obtained. All target vehicles with fuel consumption values ​​in the [max-2, max] section to the [max-m, max-n] section are marked as vehicles with abnormal fuel consumption.

[0095] If the first proportion is greater than or equal to 5%, it indicates that fuel consumption is a common phenomenon within the first fuel consumption range [max-2, max]. Therefore, it is determined that all target vehicles do not have abnormal fuel consumption, that is, there is no vehicle with abnormal fuel consumption among the target vehicles.

[0096] Furthermore, in one embodiment, the device is further configured to, after identifying a target vehicle with abnormal fuel consumption, issue a fuel consumption warning message indicating the vehicle's abnormal fuel consumption, thereby notifying the vehicle owner or vehicle management personnel of the abnormal fuel consumption. Furthermore, the IoV platform can analyze the cause of the abnormal fuel consumption based on the driver's driving habits and the vehicle's software and hardware configuration information, combined with vehicle fuel consumption data, generate an analysis report, and provide feedback to the vehicle management personnel, enabling them to promptly optimize vehicle usage and maintenance strategies.

[0097] Among them, the functional implementation of each module in the above-mentioned fuel consumption abnormal vehicle identification device corresponds to the various steps in the above-mentioned fuel consumption abnormal vehicle identification method embodiment, and their functions and implementation processes will not be repeated here one by one.

[0098] On the third aspect, an embodiment of the present application provides a device for identifying vehicles with abnormal fuel consumption. The device for identifying vehicles with abnormal fuel consumption can be a device with data processing capabilities such as a server.

[0099] Reference Figure 3 , Figure 3 Schematic diagram of the hardware structure of the device for identifying vehicles with abnormal fuel consumption involved in the embodiment of the present application. In the embodiment of the present application, the device for identifying vehicles with abnormal fuel consumption may include a processor, a memory, a communication interface, and a communication bus.

[0100] The communication bus may be of any type and is used to interconnect the processor, memory, and communication interface.

[0101] Communication interfaces include input / output (I / O) interfaces, physical interfaces, and logical interfaces, used to interconnect components within the vehicle identification device for abnormal fuel consumption, as well as interfaces used to interconnect the vehicle identification device with other devices (such as other computing devices or user devices). Physical interfaces can include Ethernet interfaces, fiber optic interfaces, ATM interfaces, etc.; user devices can include displays, keyboards, etc.

[0102] The memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0103] The processor may be a general-purpose processor that can call a program for identifying vehicles with abnormal fuel consumption stored in a memory and execute the method for identifying vehicles with abnormal fuel consumption provided in an embodiment of the present application. For example, the general-purpose processor may be a central processing unit (CPU). The method executed when the program for identifying vehicles with abnormal fuel consumption is called can refer to the various embodiments of the AAAA method of the present application and will not be repeated here.

[0104] Those skilled in the art will understand that Figure 3 The hardware structure shown in the figure does not constitute a limitation to the present application and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0105] In a fourth aspect, an embodiment of the present application also provides a computer-readable storage medium.

[0106] The computer-readable storage medium of the present application stores a program for identifying vehicles with abnormal fuel consumption, wherein when the program for identifying vehicles with abnormal fuel consumption is executed by a processor, the steps of the method for identifying vehicles with abnormal fuel consumption as described above are implemented.

[0107] Among them, the method implemented when the identification program of vehicles with abnormal fuel consumption is executed can refer to the various embodiments of the identification method of vehicles with abnormal fuel consumption in this application, and will not be repeated here.

[0108] It should be noted that the serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0109] The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices. The terms "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit the "first", "second" and "third" to different types.

[0110] In the description of the embodiments of this application, the words "exemplary," "for example," or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary," "for example," or "for example" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary," "for example," or "for example" is intended to present the relevant concepts in a concrete manner.

[0111] In the description of the embodiments of the present application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; “and / or” in the text is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, “multiple” refers to two or more than two.

[0112] In some processes described in the embodiments of the present application, multiple operations or steps are included that appear in a specific order. However, it should be understood that these operations or steps may not be performed in the order in which they appear in the embodiments of the present application or may be performed in parallel. The sequence numbers of the operations are only used to distinguish between different operations, and the sequence numbers themselves do not represent any order of execution. In addition, these processes may include more or fewer operations, and these operations or steps may be performed in sequence or in parallel, and these operations or steps may be combined.

[0113] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for enabling a terminal device to execute the methods described in each embodiment of the present application.

[0114] The above are only preferred embodiments of the present application and do 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 method for identifying vehicles with abnormal fuel consumption, characterized in that: The method for identifying a vehicle with abnormal fuel consumption comprises: Filter multiple target vehicles with the same running routes and static attribute information within a preset time interval; Determine the fuel consumption value of each target vehicle in the time interval respectively; A fuel consumption range is formed according to the minimum fuel consumption value and the maximum fuel consumption value of all target vehicles; Dividing the fuel consumption interval into a plurality of fuel consumption sections according to a preset fuel consumption interval; According to the number of target vehicles in each fuel consumption section, vehicles with abnormal fuel consumption among the target vehicles are identified.

2. The method for identifying a vehicle with abnormal fuel consumption according to claim 1, characterized in that: The step of identifying vehicles with abnormal fuel consumption among target vehicles according to the number of target vehicles in each fuel consumption section includes: Determine a first ratio of the number of target vehicles in the first fuel consumption section with the largest fuel consumption value to the total number of target vehicles; Determining whether the first proportion is less than a preset proportion threshold; If so, the proportions of the fuel consumption sections adjacent to the first fuel consumption section are calculated in sequence until a target fuel consumption section is found, so that the total proportion of all fuel consumption sections between the first fuel consumption section and the target fuel consumption section is greater than or equal to the proportion threshold, and all target vehicles within the first fuel consumption section to the target fuel consumption section are marked as vehicles with abnormal fuel consumption; Otherwise, it is determined that there is no vehicle with abnormal fuel consumption among the target vehicles.

3. The method for identifying a vehicle with abnormal fuel consumption according to claim 1, characterized in that: The step of respectively determining the fuel consumption value of each target vehicle in the time interval includes: The fuel consumption per 100 kilometers of each target vehicle within the time interval is determined respectively.

4. The method for identifying a vehicle with abnormal fuel consumption as claimed in claim 3, characterized in that: The fuel consumption per 100 kilometers of each target vehicle in the time interval is determined respectively, including: The fuel consumption per 100 kilometers of each target vehicle in the time interval is calculated according to the daily mileage and daily fuel consumption of each target vehicle in the time interval.

5. The method for identifying a vehicle with abnormal fuel consumption as claimed in claim 1, characterized in that: The static attribute information includes the vehicle's brand, model, purpose and usage scenario.

6. The method for identifying a vehicle with abnormal fuel consumption as claimed in claim 1, characterized in that: After identifying the target vehicles with abnormal fuel consumption, the following steps are also included: Sending abnormal fuel consumption prompt information of the vehicle with abnormal fuel consumption.

7. A device for identifying vehicles with abnormal fuel consumption, characterized in that: The device for identifying a vehicle with abnormal fuel consumption comprises: A screening module, which is used to screen multiple target vehicles with the same running routes and static attribute information within a preset time interval; A determination module, which is used to respectively determine the fuel consumption value of each target vehicle within the time interval; A composition module, which is used to form a fuel consumption range according to the minimum fuel consumption value and the maximum fuel consumption value of all target vehicles; A division module, which is used to divide the fuel consumption interval into a plurality of fuel consumption sections according to a preset fuel consumption interval; The identification module is used to identify vehicles with abnormal fuel consumption among the target vehicles according to the number of target vehicles in each fuel consumption section.

8. The device for identifying a vehicle with abnormal fuel consumption as claimed in claim 7, characterized in that: The identification module is also used for: Determine a first ratio of the number of target vehicles in the first fuel consumption section with the largest fuel consumption value to the total number of target vehicles; Determining whether the first proportion is less than a preset proportion threshold; If so, the proportions of the fuel consumption sections adjacent to the first fuel consumption section are calculated in sequence until a target fuel consumption section is found, so that the total proportion of all fuel consumption sections between the first fuel consumption section and the target fuel consumption section is greater than or equal to the proportion threshold, and all target vehicles within the first fuel consumption section to the target fuel consumption section are marked as vehicles with abnormal fuel consumption; Otherwise, it is determined that there is no vehicle with abnormal fuel consumption among the target vehicles.

9. A device for identifying vehicles with abnormal fuel consumption, characterized in that: The device for identifying a vehicle with abnormal fuel consumption comprises a processor, a memory, and a program for identifying a vehicle with abnormal fuel consumption stored in the memory and executable by the processor, wherein when the program for identifying a vehicle with abnormal fuel consumption is executed by the processor, the steps of the method for identifying a vehicle with abnormal fuel consumption as described in any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a program for identifying vehicles with abnormal fuel consumption, wherein when the program for identifying vehicles with abnormal fuel consumption is executed by a processor, the steps of the method for identifying vehicles with abnormal fuel consumption as described in any one of claims 1 to 6 are implemented.

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