Method, device, electronic equipment and storage medium for obtaining average fuel consumption of vehicle

Abstract

The application provides a method and device for obtaining vehicle average fuel consumption, electronic equipment and storage medium, which can be used in the field of automobile technology. The method comprises the following steps: obtaining a predicted driving average fuel consumption based on navigation information of a current trip of a target vehicle; obtaining historical accessory energy consumption of the target vehicle within a preset time range, and obtaining an accessory average fuel consumption according to the historical accessory energy consumption; obtaining a predicted average fuel consumption according to the predicted driving average fuel consumption and the accessory average fuel consumption; obtaining a historical average fuel consumption based on historical total fuel consumption and historical total trip of the target vehicle; obtaining a trip average fuel consumption based on trip fuel consumption and driving mileage of a driven distance in the current trip of the target vehicle; and obtaining the vehicle average fuel consumption by weighted calculation according to the predicted average fuel consumption, the historical average fuel consumption and the trip average fuel consumption. The method improves the accuracy of measuring the vehicle average fuel consumption.

Description

Technical Field

[0001] This application relates to the field of automotive technology, and more particularly to a method, apparatus, electronic device, and storage medium for obtaining average fuel consumption of a vehicle. Background Technology

[0002] Average fuel consumption is the amount of fuel a vehicle uses per unit distance traveled. It reflects the average fuel consumption level over a vehicle's historical mileage. By using average fuel consumption, drivers can understand the vehicle's fuel consumption, thereby judging the vehicle's performance and estimating the remaining driving range.

[0003] Existing methods for calculating average fuel consumption have imperfect calculation strategies, resulting in low accuracy of the calculated average fuel consumption data and discrepancies between the average fuel consumption displayed on the vehicle's instrument panel and the actual average fuel consumption of the vehicle. Summary of the Invention

[0004] This application provides a method, apparatus, electronic device, and storage medium for obtaining average fuel consumption of a vehicle, in order to solve the problem of low accuracy in existing average fuel consumption calculation methods.

[0005] According to the first aspect disclosed in this application, a method for obtaining the average fuel consumption of a vehicle is provided, comprising:

[0006] Based on the navigation information of the target vehicle's current journey, obtain the predicted average driving fuel consumption;

[0007] Obtain the historical accessory energy consumption of the target vehicle within a preset time range, and obtain the average fuel consumption of the accessory based on the historical accessory energy consumption;

[0008] The predicted average fuel consumption is obtained based on the predicted average driving fuel consumption and the predicted average fuel consumption of the accessories;

[0009] Based on the historical total fuel consumption and historical total mileage of the target vehicle, obtain the historical average fuel consumption;

[0010] Based on the fuel consumption and mileage of the target vehicle in its current journey, the average fuel consumption for the journey is obtained;

[0011] The vehicle's average fuel consumption is calculated by weighting the predicted average fuel consumption, the historical average fuel consumption, and the trip average fuel consumption.

[0012] In one feasible implementation, obtaining the predicted driving average fuel consumption based on the navigation information of the target vehicle's current journey includes:

[0013] Based on the traffic condition information in the navigation information, the navigation route in the navigation information is divided into multiple navigation segments;

[0014] Based on the navigation information, the navigation vehicle speed for each navigation segment is obtained;

[0015] Based on the preset mapping relationship between vehicle speed and average fuel consumption, the average fuel consumption of each navigation segment is obtained according to the navigation vehicle speed of each navigation segment.

[0016] The fuel consumption of each navigation segment is obtained by multiplying the segment mileage of each navigation segment with the average fuel consumption of the navigation segment.

[0017] The predicted fuel consumption for the current trip is obtained by summing the fuel consumption of each navigation segment.

[0018] The predicted average fuel consumption is obtained by dividing the predicted fuel consumption by the total mileage of the current trip.

[0019] In one feasible implementation, obtaining the average fuel consumption of the attachments based on the historical attachment energy consumption includes:

[0020] Obtain the travel distance of the target vehicle within the preset time range;

[0021] Based on the target vehicle's fuel-electric conversion coefficient, the historical accessory energy consumption is converted into accessory fuel consumption.

[0022] Divide the fuel consumption of the accessory by the driving distance to obtain the average fuel consumption of the accessory.

[0023] In one feasible implementation, obtaining the predicted average fuel consumption based on the predicted driving average fuel consumption and the accessory average fuel consumption includes:

[0024] Obtain the historical average vehicle speed and historical navigation speed within a preset route range;

[0025] Based on the preset mapping relationship between the deviation value and the correction coefficient, the corresponding correction coefficient is obtained according to the deviation value between the historical average vehicle speed and the historical navigation vehicle speed.

[0026] The predicted average fuel consumption is obtained by correcting the sum of the predicted driving average fuel consumption and the average fuel consumption of the accessories based on the correction coefficient.

[0027] In one feasible implementation, the average fuel consumption of the vehicle satisfies the following formula:

[0028] D = R1*A + R2*B + R3*C

[0029] Where D represents the vehicle's average fuel consumption, R1 represents the first weighting factor, A represents the predicted average fuel consumption, R2 represents the second weighting factor, B represents the historical average fuel consumption, R3 represents the third weighting factor, and C represents the trip-average fuel consumption.

[0030] Where R1+R2+R3=1.

[0031] In one feasible implementation, the method further includes:

[0032] Based on the navigation information, the total mileage of the current trip and the average navigation speed are obtained;

[0033] Based on the preset mapping relationship between mileage, vehicle speed and the first weighting factor, the corresponding first weighting factor is obtained according to the total mileage of the current trip and the average navigation speed.

[0034] In one feasible implementation, the second weighting factor and the third weighting factor satisfy the following formula:

[0035] R2 = R3 = 0.5 * (1 - R1)

[0036] Where R1 represents the first weighting factor, R2 represents the second weighting factor, and R3 represents the third weighting factor.

[0037] According to a second aspect disclosed in this application, an apparatus for obtaining average fuel consumption of a vehicle is provided, comprising:

[0038] The driving fuel consumption acquisition module is used to obtain the predicted driving average fuel consumption based on the navigation information of the target vehicle's current journey.

[0039] The accessory fuel consumption acquisition module is used to acquire the historical accessory energy consumption of the target vehicle within a preset time range, and to acquire the average accessory fuel consumption based on the historical accessory energy consumption.

[0040] The predicted fuel consumption acquisition module is used to acquire the predicted average fuel consumption based on the predicted average fuel consumption of the drive and the average fuel consumption of the accessories;

[0041] The historical fuel consumption acquisition module is used to acquire the historical average fuel consumption based on the historical total fuel consumption and historical total mileage of the target vehicle.

[0042] The trip fuel consumption acquisition module is used to obtain the average trip fuel consumption based on the trip fuel consumption and mileage of the target vehicle in the current trip.

[0043] The vehicle fuel consumption acquisition module is used to calculate the vehicle average fuel consumption by weighting the predicted average fuel consumption, the historical average fuel consumption, and the trip average fuel consumption.

[0044] According to a third aspect disclosed in this application, an electronic device is provided, including a processor and a memory communicatively connected to the processor;

[0045] The memory stores computer-executed instructions;

[0046] The processor executes computer execution instructions stored in the memory to implement the method described in any one of the first aspects.

[0047] According to a fourth aspect disclosed in this application, a computer-readable storage medium is provided, wherein computer-executable instructions are stored therein, which, when executed by a processor, are used to implement the method described in any one of the first aspects.

[0048] According to the fifth aspect disclosed in this application, a computer program product is provided, comprising a computer program that, when executed by a processor, is used to implement the method described in any one of the first aspects.

[0049] Compared with the prior art, this application has the following beneficial effects:

[0050] This application provides a method, apparatus, electronic device, and storage medium for obtaining vehicle average fuel consumption. By combining navigation information with the vehicle's current operating environment and conditions, it predicts the fuel consumption of the user's current trip. Through a certain weight allocation, it comprehensively considers the vehicle's historical average fuel consumption, as well as the weight ratio of the predicted average fuel consumption of the current trip and the average fuel consumption of the distance already traveled in the current trip in the vehicle's average fuel consumption, thereby improving the accuracy of vehicle average fuel consumption calculation. Attached Figure Description

[0051] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without inventive effort. Wherein:

[0052] Figure 1 A flowchart illustrating a method for obtaining average fuel consumption of a vehicle, provided in an embodiment of this application;

[0053] Figure 2 A flowchart illustrating another method for obtaining average vehicle fuel consumption provided in this application embodiment;

[0054] Figure 3 A schematic diagram of a device for obtaining average fuel consumption of a vehicle provided in an embodiment of this application;

[0055] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0056] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0057] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0058] Average fuel consumption is the amount of fuel a vehicle uses per unit distance traveled (usually measured in liters per 100 kilometers), reflecting the vehicle's fuel efficiency in real-world use. As a crucial indicator of a vehicle's fuel economy, average fuel consumption allows drivers to understand their car's fuel consumption, thus assessing its performance and estimating the remaining driving range. Lower average fuel consumption means the vehicle can travel a greater distance with the same amount of fuel, while higher average fuel consumption indicates the vehicle requires more fuel under the same driving conditions.

[0059] Average fuel consumption can be calculated and monitored in several ways. One simple method is to calculate average fuel consumption using historical mileage and fuel consumption data. This is achieved by dividing the distance traveled by the amount of fuel consumed. However, this method doesn't consider the varying driving conditions, driving style, and speed of each trip, and it doesn't reflect the average fuel consumption of the current trip. The calculated average fuel consumption data has low accuracy, leading to discrepancies between the average fuel consumption displayed on the vehicle's dashboard and the actual average fuel consumption. This results in drivers being unable to accurately understand the fuel consumption of their current trip based on the displayed average fuel consumption, and consequently, incorrectly estimating the remaining driving range.

[0060] To address the aforementioned issues, this application proposes a method for obtaining average vehicle fuel consumption. By combining navigation information and identifying the vehicle's operating environment and conditions, the method predicts the user's trip fuel consumption and assigns a certain weight to the predicted fuel consumption and the current fuel consumption, thereby improving the accuracy of the average vehicle fuel consumption calculation.

[0061] The technical solution of the method for obtaining vehicle average fuel consumption provided in this application will be described in detail below through specific embodiments. It should be noted that the following embodiments may exist alone or in combination with each other, and the same or similar content may not be described again in different embodiments.

[0062] It should be noted that the execution subject of the method for obtaining the average fuel consumption of a vehicle provided in this application embodiment can be a vehicle system or a cloud server. When the execution subject is a cloud server, the cloud server and the target vehicle communicate and connect through vehicle networking or other means.

[0063] Compared to in-vehicle infotainment systems, cloud servers possess superior computing and data processing capabilities. Therefore, using cloud servers as the execution source results in faster execution speeds, lower hardware requirements for the vehicle, and no additional cost to the vehicle.

[0064] The cloud server may store data related to multiple vehicles, and the VIN (Vehicle Identification Number) can be used as an identification index to store the data of the corresponding vehicle.

[0065] Figure 1 This is a flowchart illustrating a method for obtaining average vehicle fuel consumption according to an embodiment of this application. (See attached diagram.) Figure 1 In some embodiments, the method for obtaining average vehicle fuel consumption includes the following steps:

[0066] S101, based on the navigation information of the target vehicle's current journey, obtains the predicted average driving fuel consumption.

[0067] The purpose of adding the predicted average fuel consumption obtained from navigation information is that if the instrument panel only displays the average fuel consumption obtained from historical data, it cannot accurately reflect the average fuel consumption of the current trip, because the driving data of the current trip is different from the historical data, and the corresponding average fuel consumption will also be different. Therefore, by adding the predicted average fuel consumption obtained from navigation information, a more accurate average fuel consumption of the vehicle can be obtained in the future.

[0068] S102, obtain the historical accessory energy consumption of the target vehicle within a preset time range, and obtain the average fuel consumption of the accessory based on the historical accessory energy consumption.

[0069] During vehicle operation, in addition to the energy consumption of the vehicle's driving system, there is also the energy consumption of vehicle accessories. The main form of energy consumption for accessories is electricity. Accessory energy consumption data is stored in the vehicle controller, which can retrieve relevant accessory energy consumption data. Furthermore, since the energy consumption of accessories is in the form of electricity, it needs to be converted to obtain the average fuel consumption of accessories.

[0070] Since the energy consumption of accessories is not related to vehicle speed but rather to the duration of accessory use, a preset time range is used to obtain historical accessory energy consumption data within a certain time range to predict the average accessory energy consumption of the target vehicle. Specifically, the preset time range should start from the current moment and obtain historical accessory energy consumption data within the preset historical time range. The purpose of starting from the current moment is to make the historical accessory energy consumption data as close as possible to the current accessory usage status of the vehicle.

[0071] Specifically, accessory energy consumption includes low-pressure accessory energy consumption and high-pressure accessory energy consumption. High-pressure accessories include air conditioning compressors, high-pressure fuel pumps, power steering pumps, etc., while low-pressure accessories include headlights, speakers, wiper switches, electric sunroofs, etc.

[0072] S103, obtain the predicted average fuel consumption based on the predicted average fuel consumption of the drive and the average fuel consumption of the accessories.

[0073] During vehicle operation, energy consumption mainly includes two parts: driving energy consumption and energy consumption of accessories other than driving. Therefore, after obtaining the predicted average driving fuel consumption and accessory average fuel consumption respectively, the two can be combined to obtain the predicted average fuel consumption of the target vehicle.

[0074] S104: Based on the target vehicle's historical total fuel consumption and historical total mileage, obtain the historical average fuel consumption.

[0075] The historical average fuel consumption can be obtained by dividing the historical total fuel consumption by the historical total mileage.

[0076] Specifically, historical total fuel consumption and historical total mileage can both be obtained from historical data stored in the vehicle controller.

[0077] S105, based on the fuel consumption and mileage of the target vehicle in the current trip, obtain the average fuel consumption of the trip.

[0078] The average fuel consumption can be obtained by dividing the fuel consumption of the current distance traveled by the distance traveled, which reflects the average fuel consumption of the sections already traveled along the navigation route.

[0079] S106 calculates the vehicle's average fuel consumption by weighting the predicted average fuel consumption, historical average fuel consumption, and trip-average fuel consumption.

[0080] The average fuel consumption of a vehicle is obtained by weighting the predicted average fuel consumption, the average historical fuel consumption, and the average fuel consumption per trip. Because it incorporates data from predicted fuel consumption, historical fuel consumption, and current fuel consumption, the obtained average fuel consumption of a vehicle has higher accuracy.

[0081] In this embodiment, by combining navigation information with the vehicle's current operating environment and conditions, the fuel consumption of the user's current trip is predicted. Through a certain weight allocation, the historical average fuel consumption of the vehicle, as well as the weight ratio of the predicted average fuel consumption of the current trip and the average fuel consumption of the distance already traveled in the current trip in the vehicle's average fuel consumption, are comprehensively considered, thereby improving the accuracy of the vehicle's average fuel consumption calculation.

[0082] exist Figure 1 Based on the embodiments shown, the following is combined with Figure 2 The technical solution for obtaining the average fuel consumption of a vehicle described above will be further introduced.

[0083] Figure 2 A flowchart illustrating another method for obtaining average vehicle fuel consumption provided in this application embodiment is shown below. Figure 2 In some embodiments, the method for obtaining average vehicle fuel consumption includes the following steps:

[0084] S201, Obtain navigation information for the target vehicle's current journey.

[0085] S202, based on traffic condition information in the navigation information, divides the navigation route in the navigation information into multiple navigation segments.

[0086] Since vehicle speed is affected by road traffic conditions and fuel consumption, more accurate speed data is needed to obtain more accurate fuel consumption data. Therefore, traffic information from navigation systems is used to divide the navigation route into multiple navigation segments.

[0087] Specifically, navigation routes can be obtained directly from data in existing navigation applications. Specifically, for existing navigation data, the navigation route is divided into multiple navigation segments based on traffic conditions during the navigation process. For example, smooth traffic is generally represented by a green line in the navigation application interface; congested traffic is generally represented by a yellow line; and extremely congested traffic is generally represented by a red line.

[0088] S203, based on navigation information, obtains the navigation vehicle speed for each navigation segment.

[0089] Depending on the traffic conditions of the route, the navigation application will provide a predicted navigation speed.

[0090] S204, based on the preset mapping relationship between vehicle speed and average fuel consumption, obtains the average fuel consumption corresponding to each navigation segment according to the navigation vehicle speed of each navigation segment.

[0091] Since a car's average fuel consumption is generally related to its speed, lower speeds typically result in lower average fuel consumption. This is because at low speeds, the engine load is lower, fuel combustion is more complete, and fuel utilization is relatively higher. Furthermore, at low speeds, vehicles often operate in higher gears, reducing mechanical losses and further improving fuel economy. As speed increases, average fuel consumption may begin to rise. At higher speeds, the vehicle experiences greater wind resistance, requiring the engine to consume more energy to overcome this resistance, thus increasing fuel consumption. Additionally, higher speeds lead to higher engine speeds, and some engine technologies may have lower fuel efficiency at higher speeds. Therefore, under normal driving conditions, a vehicle's average fuel consumption typically varies across different speed ranges.

[0092] Specifically, the mapping relationship between different vehicle speeds and average fuel consumption can be obtained through experimental calibration. In this way, the corresponding average fuel consumption can be obtained based on the navigation vehicle speed in the mapping relationship.

[0093] S205, based on the product of the mileage of each navigation segment and the average fuel consumption of navigation, obtains the fuel consumption of each navigation segment.

[0094] Since the average driving fuel consumption is measured in L / 100km, the fuel consumption of the navigation route can be obtained by multiplying the average driving fuel consumption by the mileage of the navigation route.

[0095] S206, based on the sum of fuel consumption of each navigation segment, obtains the predicted fuel consumption of the current trip.

[0096] In step S205, the fuel consumption of each navigation segment is calculated, and the fuel consumption of all navigation segments is summed to obtain the total predicted fuel consumption of the entire navigation route.

[0097] S207 divides the predicted fuel consumption by the total mileage of the current trip to obtain the predicted average fuel consumption.

[0098] The predicted average fuel consumption is obtained by dividing the total predicted fuel consumption by the total mileage of the entire navigation route. Calculating the total fuel consumption in segments improves the accuracy of the total fuel consumption estimate, which in turn improves the accuracy of the predicted average fuel consumption.

[0099] S208, obtain the target vehicle's historical accessory energy consumption and driving distance within a preset time range.

[0100] S209 converts historical accessory energy consumption into accessory fuel consumption based on the target vehicle's fuel-electric conversion coefficient.

[0101] Since the historical energy consumption of accessories is measured in kW / h, it needs to be converted from fuel to electricity. First, the energy consumption of accessories is converted into fuel consumption of accessories based on the fuel-electric conversion coefficient of the target vehicle.

[0102] Specifically, the oil-to-electric conversion coefficient of the target vehicle can be obtained through experimental measurement.

[0103] S210: Divide the fuel consumption of the accessory by the driving distance to obtain the average fuel consumption of the accessory.

[0104] In this process, dividing the fuel consumption of the accessory by the distance the vehicle travels within a preset time range yields the average fuel consumption of the accessory, which has the same unit of measurement as the predicted average fuel consumption.

[0105] S211, obtain the historical average vehicle speed and historical navigation speed within the preset route range.

[0106] Among them, the historical average vehicle speed and historical navigation speed within a preset distance range are obtained by using historical driving data recorded by the vehicle controller.

[0107] S212, based on the preset mapping relationship between the deviation value and the correction coefficient, obtain the corresponding correction coefficient according to the deviation value between the historical average vehicle speed and the historical navigation vehicle speed.

[0108] The difference between the historical average vehicle speed and the historical navigation speed can be used to obtain the deviation between the historical average vehicle speed and the historical navigation speed. Since the predicted average driving fuel consumption is calculated using the navigation speed, it will deviate from the actual average driving fuel consumption. Furthermore, since vehicle speed affects the calculation of average fuel consumption, the deviation between the navigation speed and the actual driving speed can be used to reflect the deviation between the predicted average driving fuel consumption and the actual average driving fuel consumption.

[0109] Therefore, by using the deviation between the historical average vehicle speed and the historical navigation vehicle speed, a corresponding correction coefficient is obtained to correct the predicted driving average fuel consumption.

[0110] Specifically, the preset mapping relationship between the deviation value and the correction coefficient can be obtained by calibrating through multiple experiments to obtain the correction coefficient corresponding to different deviation values.

[0111] S213, Based on the correction coefficient, the sum of the predicted average fuel consumption of the drive and the average fuel consumption of the accessories is corrected to obtain the predicted average fuel consumption.

[0112] By using correction parameters, the accuracy of predicting average fuel consumption can be improved.

[0113] Specifically, the predicted average fuel consumption satisfies the following formula:

[0114] A = (A1 + A2) * R

[0115] Where A represents the predicted average fuel consumption, A1 represents the predicted driving average fuel consumption, A2 represents the accessory average fuel consumption, and R represents the correction factor.

[0116] S214: Based on the target vehicle's historical total fuel consumption and historical total mileage, obtain the historical average fuel consumption.

[0117] S215, based on the fuel consumption and mileage of the target vehicle in the current trip, obtain the average fuel consumption of the trip.

[0118] S216, the vehicle's average fuel consumption is calculated by weighting the predicted average fuel consumption, historical average fuel consumption, and trip average fuel consumption.

[0119] The average fuel consumption of a vehicle satisfies the following formula:

[0120] D = R1*A + R2*B + R3*C

[0121] Where D represents the vehicle's average fuel consumption, R1 represents the first weighting factor, A represents the predicted average fuel consumption, R2 represents the second weighting factor, B represents the historical average fuel consumption, R3 represents the third weighting factor, and C represents the trip-average fuel consumption.

[0122] Where R1+R2+R3=1.

[0123] Specifically, by obtaining the weighting factors, the product of the first weighting factor and the predicted average fuel consumption, the product of the second weighting factor and the average historical fuel consumption, and the product of the third weighting factor and the average fuel consumption of the trip are obtained respectively. The three product results are then added together to obtain the average fuel consumption.

[0124] Preferably, based on navigation information, the total mileage of the current trip and the average navigation speed are obtained; based on the preset mapping relationship between mileage, speed and the first weighting factor, the corresponding first weighting factor is obtained according to the total mileage of the current trip and the average navigation speed.

[0125] The longer the journey and the higher the speed, the more accurate the predicted fuel consumption based on navigation information, and the larger the corresponding first weighting factor used in the subsequent weighted calculation. Conversely, if the target vehicle does not have navigation enabled, the first weighting factor is zero.

[0126] Specifically, the mapping relationship between mileage, vehicle speed and the first weighting factor can be obtained through multiple test calibrations, and the first weighting factor under different mileage and vehicle speed conditions can be obtained through multiple tests.

[0127] Specifically, the average speed of the vehicle can be obtained by dividing the total distance of the current trip by the travel time predicted by the navigation.

[0128] Preferably, the second weighting factor and the third weighting factor satisfy the following formula:

[0129] R2 = R3 = 0.5 * (1 - R1)

[0130] Where R1 represents the first weighting factor, R2 represents the second weighting factor, and R3 represents the third weighting factor.

[0131] In this embodiment, the accuracy of obtaining the vehicle's average fuel consumption is further improved by using techniques such as segmenting the navigation route to calculate the predicted fuel consumption, converting the energy consumption of the accessories into the average fuel consumption of the accessories, and correcting the predicted average fuel consumption using correction parameters.

[0132] Figure 3 This is a schematic diagram of a device for obtaining average vehicle fuel consumption according to an embodiment of this application. (See attached diagram.) Figure 3 The device for obtaining average vehicle fuel consumption includes various functional modules for implementing the aforementioned method for obtaining average vehicle fuel consumption, and any functional module can be implemented by software and / or hardware.

[0133] In some embodiments, the device 300 for obtaining average vehicle fuel consumption includes a drive fuel consumption acquisition module 301, an accessory fuel consumption acquisition module 302, a predicted fuel consumption acquisition module 303, a historical fuel consumption acquisition module 304, a trip fuel consumption acquisition module 305, and a vehicle fuel consumption acquisition module 306. Wherein:

[0134] The driving fuel consumption acquisition module 301 is used to acquire the predicted driving average fuel consumption based on the navigation information of the target vehicle's current journey.

[0135] The accessory fuel consumption acquisition module 302 is used to acquire the historical accessory energy consumption of the target vehicle within a preset time range, and to acquire the average accessory fuel consumption based on the historical accessory energy consumption.

[0136] The predicted fuel consumption acquisition module 303 is used to acquire the predicted average fuel consumption based on the predicted average fuel consumption of the drive and the average fuel consumption of the accessories;

[0137] The historical fuel consumption acquisition module 304 is used to obtain the historical average fuel consumption based on the historical total fuel consumption and historical total mileage of the target vehicle.

[0138] The trip fuel consumption acquisition module 305 is used to obtain the average trip fuel consumption based on the trip fuel consumption and mileage traveled in the current trip of the target vehicle;

[0139] The vehicle fuel consumption acquisition module 306 is used to calculate the vehicle's average fuel consumption by weighting the predicted average fuel consumption, historical average fuel consumption, and trip average fuel consumption.

[0140] In some embodiments, the drive fuel consumption acquisition module 301 is specifically used for:

[0141] Based on the traffic information in the navigation information, the navigation route in the navigation information is divided into multiple navigation segments;

[0142] Based on navigation information, obtain the navigation vehicle speed for each navigation segment;

[0143] Based on the preset mapping relationship between vehicle speed and average fuel consumption, the average fuel consumption of each navigation segment is obtained according to the navigation vehicle speed of each navigation segment.

[0144] The fuel consumption of each navigation segment is obtained by multiplying the segment mileage of each navigation segment with the average fuel consumption of the navigation segment.

[0145] Based on the sum of fuel consumption for each navigation segment, the predicted fuel consumption for the current trip is obtained.

[0146] Divide the predicted fuel consumption by the total mileage of the current trip to obtain the predicted average fuel consumption.

[0147] In some embodiments, the accessory fuel consumption acquisition module 302 is specifically used for:

[0148] Obtain the travel distance of the target vehicle within a preset time range;

[0149] Based on the target vehicle's fuel-electric conversion coefficient, historical accessory energy consumption is converted into accessory fuel consumption.

[0150] Divide the fuel consumption of the accessory by the driving distance to obtain the average fuel consumption of the accessory.

[0151] In some embodiments, the predicted fuel consumption acquisition module 303 is specifically used for:

[0152] Obtain the historical average vehicle speed and historical navigation speed within a preset route range;

[0153] Based on the preset mapping relationship between the deviation value and the correction coefficient, the corresponding correction coefficient is obtained according to the deviation value between the historical average vehicle speed and the historical navigation vehicle speed.

[0154] The predicted average fuel consumption is obtained by correcting the sum of the predicted driving average fuel consumption and the accessory average fuel consumption based on the correction factor.

[0155] In some embodiments, the average fuel consumption of a vehicle satisfies the following formula:

[0156] D = R1*A + R2*B + R3*C

[0157] Where D represents the vehicle's average fuel consumption, R1 represents the first weighting factor, A represents the predicted average fuel consumption, R2 represents the second weighting factor, B represents the historical average fuel consumption, R3 represents the third weighting factor, and C represents the trip-average fuel consumption.

[0158] Where R1+R2+R3=1.

[0159] In some embodiments, the vehicle fuel consumption acquisition module 306 is specifically used for:

[0160] Based on navigation information, obtain the total mileage of the current trip and the average speed of the vehicle under navigation;

[0161] Based on the preset mapping relationship between mileage, vehicle speed and the first weighting factor, the corresponding first weighting factor is obtained according to the total mileage of the current trip and the average navigation speed.

[0162] In some embodiments, the second weighting factor and the third weighting factor satisfy the following formula:

[0163] R2 = R3 = 0.5 * (1 - R1)

[0164] Where R1 represents the first weighting factor, R2 represents the second weighting factor, and R3 represents the third weighting factor.

[0165] The device 300 for obtaining average vehicle fuel consumption provided in this application embodiment is used to execute the technical solution provided in the aforementioned method embodiment for obtaining average vehicle fuel consumption. Its implementation principle and technical effects are similar to those in the aforementioned method embodiment, and will not be repeated here.

[0166] It should be noted that the division of the various modules in the above device is merely a logical functional division. In actual implementation, they can be fully or partially integrated into a single physical entity, or they can be physically separated. Furthermore, these modules can be implemented entirely in software via processing elements, entirely in hardware, or partially in software via processing elements and partially in hardware. For example, the vehicle fuel consumption acquisition module can be a separate processing element, or it can be integrated into a chip within the device. Alternatively, it can be stored as program code in the device's memory, invoked and executed by a processing element. The implementation of other modules is similar. Moreover, these modules can be fully or partially integrated together, or implemented independently. The processing element here can be an integrated circuit with signal processing capabilities. During implementation, each step of the above method or each of the above modules can be completed through integrated logic circuits in the processor element or through software instructions.

[0167] Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. (See attached diagram.) Figure 4 The electronic device 400 includes: a processor 401, and a memory 402 communicatively connected to the processor 401;

[0168] Memory 402 stores instructions executed by the computer;

[0169] The processor 401 executes computer execution instructions stored in the memory 402 to implement the aforementioned technical solution of the method for obtaining the average fuel consumption of a vehicle.

[0170] In the aforementioned electronic device 400, the memory 402 and the processor 401 are electrically connected directly or indirectly to achieve data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines, such as bus connections. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be classified as address buses, data buses, control buses, etc., but this does not mean that there is only one bus or one type of bus. The memory 402 stores computer execution instructions for implementing the aforementioned method of obtaining the average fuel consumption of a vehicle, including at least one software functional module that can be stored in the memory 402 in the form of software or firmware. The processor 401 executes various functional applications and data processing by running the software program and module stored in the memory 402.

[0171] The memory 402 includes at least one type of readable storage medium, not limited to Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc. The memory 402 stores programs, which are executed by the processor 401 upon receiving execution instructions. Furthermore, the software programs and modules within the memory 402 may also include an operating system, which may include various software components and / or drivers for managing system tasks (e.g., memory management, storage device control, power management, etc.) and can communicate with various hardware or software components to provide an operating environment for other software components.

[0172] Processor 401 can be an integrated circuit chip with signal processing capabilities. The aforementioned processor 401 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor can be a microprocessor, or processor 401 can be any conventional processor.

[0173] The electronic device 400 is used to execute the technical solution provided in the aforementioned method embodiment for obtaining the average fuel consumption of a vehicle. Its implementation principle and technical effects are similar to those in the aforementioned method embodiment, and will not be repeated here.

[0174] This application also provides a computer-readable storage medium storing computer-executable instructions. When a processor executes the computer-executable instructions, it implements the aforementioned technical solution for obtaining the average fuel consumption of a vehicle.

[0175] The aforementioned computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The computer-readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0176] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the control unit of a device for obtaining average vehicle fuel consumption.

[0177] This application also provides a computer program product, including a computer program, which, when executed by a processor, is used to implement the aforementioned technical solution for obtaining the average fuel consumption of a vehicle.

[0178] In the above embodiments, those skilled in the art will understand that the above method embodiments can be implemented entirely or partially by software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented entirely or partially in the form of a computer program product. A computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless network, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that integrates one or more available media. The available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid-state drives (SSDs)).

[0179] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0180] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for obtaining the average fuel consumption of a vehicle, characterized in that, include: Based on the navigation information of the target vehicle's current journey, obtain the predicted average driving fuel consumption; Obtain the historical accessory energy consumption of the target vehicle within a preset time range, and obtain the average fuel consumption of the accessory based on the historical accessory energy consumption; Obtain the historical average vehicle speed and historical navigation speed within a preset route range; Based on the preset mapping relationship between the deviation value and the correction coefficient, the corresponding correction coefficient is obtained according to the deviation value between the historical average vehicle speed and the historical navigation vehicle speed. The predicted average fuel consumption is obtained by correcting the sum of the predicted driving average fuel consumption and the average fuel consumption of the accessories based on the correction coefficient. Based on the historical total fuel consumption and historical total mileage of the target vehicle, obtain the historical average fuel consumption; Based on the fuel consumption and mileage of the target vehicle in its current journey, the average fuel consumption for the journey is obtained; The vehicle's average fuel consumption is calculated by weighting the predicted average fuel consumption, the historical average fuel consumption, and the trip average fuel consumption.

2. The method according to claim 1, characterized in that, The step of obtaining the predicted average driving fuel consumption based on the navigation information of the target vehicle's current journey includes: Based on the traffic condition information in the navigation information, the navigation route in the navigation information is divided into multiple navigation segments; Based on the navigation information, the navigation vehicle speed for each navigation segment is obtained; Based on the preset mapping relationship between vehicle speed and average fuel consumption, the average fuel consumption of each navigation segment is obtained according to the navigation vehicle speed of each navigation segment. The fuel consumption of each navigation segment is obtained by multiplying the segment mileage of each navigation segment with the average fuel consumption of the navigation segment. The predicted fuel consumption for the current trip is obtained by summing the fuel consumption of each navigation segment. The predicted average fuel consumption is obtained by dividing the predicted fuel consumption by the total mileage of the current trip.

3. The method according to claim 1, characterized in that, The step of obtaining the average fuel consumption of the accessory based on the historical accessory energy consumption includes: Obtain the travel distance of the target vehicle within the preset time range; Based on the target vehicle's fuel-electric conversion coefficient, the historical accessory energy consumption is converted into accessory fuel consumption. Divide the fuel consumption of the accessory by the driving distance to obtain the average fuel consumption of the accessory.

4. The method according to claim 1, characterized in that, The average fuel consumption of the vehicle satisfies the following formula: Where D represents the vehicle's average fuel consumption, R1 represents the first weighting factor, A represents the predicted average fuel consumption, R2 represents the second weighting factor, B represents the historical average fuel consumption, R3 represents the third weighting factor, and C represents the trip-average fuel consumption. Where R1+R2+R3=1.

5. The method according to claim 4, characterized in that, The method further includes: Based on the navigation information, the total mileage of the current trip and the average navigation speed are obtained; Based on the preset mapping relationship between mileage, vehicle speed and the first weighting factor, the corresponding first weighting factor is obtained according to the total mileage of the current trip and the average navigation speed.

6. The method according to claim 4, characterized in that, The second weighting factor and the third weighting factor satisfy the following formula: Where R1 represents the first weighting factor, R2 represents the second weighting factor, and R3 represents the third weighting factor.

7. A device for obtaining the average fuel consumption of a vehicle, characterized in that, include: The driving fuel consumption acquisition module is used to obtain the predicted driving average fuel consumption based on the navigation information of the target vehicle's current journey. The accessory fuel consumption acquisition module is used to acquire the historical accessory energy consumption of the target vehicle within a preset time range, and to acquire the average accessory fuel consumption based on the historical accessory energy consumption. The predicted fuel consumption acquisition module is used to acquire the historical average vehicle speed and historical navigation vehicle speed within a preset distance range; based on the preset mapping relationship between the deviation value and the correction coefficient, the corresponding correction coefficient is obtained according to the deviation value of the historical average vehicle speed and the historical navigation vehicle speed; the predicted average fuel consumption is obtained by correcting the sum of the predicted driving average fuel consumption and the accessory average fuel consumption based on the correction coefficient. The historical fuel consumption acquisition module is used to acquire the historical average fuel consumption based on the historical total fuel consumption and historical total mileage of the target vehicle. The trip fuel consumption acquisition module is used to obtain the average trip fuel consumption based on the trip fuel consumption and mileage of the target vehicle in the current trip. The vehicle fuel consumption acquisition module is used to calculate the vehicle average fuel consumption by weighting the predicted average fuel consumption, the historical average fuel consumption, and the trip average fuel consumption.

8. An electronic device, characterized in that, Includes a processor and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1 to 6.

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