Method and device for calculating dynamic driving endurance of vehicle

Abstract

The embodiment of the invention provides a vehicle dynamic driving endurance calculation method and device, and relates to the technical field of vehicle endurance. The method comprises the steps that the average power consumption corresponding to the nearest driving target distance of a vehicle is counted; in the pre-defined area, receiving area reference power consumption sent by the cloud, and determining a corresponding up-down floating range based on the area reference power consumption; calculating estimated dynamic energy consumption according to the average power consumption and the regional reference power consumption, and calculating estimated driving mileage based on residual available electric energy and the estimated dynamic energy consumption, the estimated dynamic energy consumption being in accordance with the up-down floating range; and updating the meter display endurance value based on the estimated driving mileage. By adopting the technical scheme, the influence of environment change on the residual endurance can be reduced in the pre-defined area in combination with the car using habit of the driver and the area reference power consumption, the more accurate estimated driving mileage is obtained, and the user experience is improved.

Description

Technical Field

[0001] The disclosed embodiments relate to the field of vehicle endurance technology, and more particularly to a method and device for calculating vehicle dynamic driving endurance. Background Art

[0002] With the rapid development of new energy vehicles, the market is expanding rapidly, and pure electric vehicles have gained more and more users. Compared with traditional fuel vehicles, electric vehicles have huge advantages in electrification and intelligence. With the technological development and market competition of pure electric vehicles, the electrification and intelligence configuration of vehicles are also getting higher and higher. Such as ultra-large size, ultra-high resolution central control screen; in-car artificial intelligence; laser radar; millimeter wave radar; in-car holographic imaging; car refrigerator; in-car theater; seat heating, ventilation, massage; mobile phone wireless charging, etc. At the same time as intelligence, the power consumption of the whole vehicle has also fluctuated sharply, which greatly affects the accuracy of the battery life and aggravates the user's mileage anxiety. In the survey, users have also received feedback many times from users hoping to use dynamic battery life based on personal driving habits to obtain more accurate battery life estimates.

[0003] The current range calculation method is mostly a fixed calculation based on the announced value of the power gauge. There are also range calculations that change according to the actual vehicle load power consumption. They only take into account the driving style of the vehicle, and do not take into account the possible impacts in various scenarios such as environmental changes and cross-regional situations. As a result, the calculated remaining range is not accurate enough, which may affect the user experience. Summary of the invention

[0004] In order to solve the above technical problems or at least partially solve the above technical problems, an embodiment of the present disclosure provides a vehicle dynamic driving endurance calculation method and device.

[0005] A first aspect of an embodiment of the present disclosure provides a method for calculating a vehicle's dynamic driving range, the method comprising:

[0006] Count the average power consumption corresponding to the vehicle's most recent target distance;

[0007] In a pre-defined area, receiving the regional benchmark power consumption sent by the cloud, and determining the corresponding upper and lower floating range based on the regional benchmark power consumption;

[0008] Calculating an estimated dynamic energy consumption according to the average power consumption and the regional benchmark power consumption, and calculating an estimated driving mileage based on the remaining available power and the estimated dynamic energy consumption, wherein the estimated dynamic energy consumption complies with the upper and lower floating range;

[0009] The displayed endurance value is updated based on the estimated mileage.

[0010] In one example, the counting of the average power consumption corresponding to the vehicle's most recent target distance includes:

[0011] The average power consumption corresponding to the vehicle's most recent target distance is counted, and the average power consumption corresponding to the target distance is sent to the cloud. The average power consumption is corrected by the power consumption of different driving distances under the same working conditions.

[0012] In one example, the regional benchmark power consumption is calculated by collecting the average power consumption corresponding to the target distance of multiple vehicles of the same model as the vehicle in the pre-defined area in the cloud.

[0013] In one example, the method further includes:

[0014] When a preset number threshold value among the average power consumptions corresponding to the target distances of the plurality of vehicles exceeds the upper and lower floating range, obtaining the upper and lower floating range corrected by the cloud, and the coverage rate of the upper and lower floating range is greater than a first preset ratio;

[0015] When the accuracy of the upper and lower floating range is monitored to reach the actual proportion within the preset time, the upper and lower floating range corrected by the cloud is obtained, and the coverage rate of the upper and lower floating range is greater than the second preset proportion, the second preset proportion is greater than the first preset proportion, and the second preset proportion is less than the actual proportion.

[0016] In one example, the method further includes:

[0017] Access historical and climate data;

[0018] Based on the high energy consumption scenarios in the historical data, increase the upward range and reduce the downward range;

[0019] Based on the changes in the climate data, the updating frequency of the upper and lower floating range is increased.

[0020] In one example, the estimating the dynamic energy consumption according to the average power consumption and the regional benchmark power consumption includes:

[0021] By calculating the difference between the power consumption of different driving distances and the average power consumption of the target distance, the corresponding behavior weight is determined according to the minimum difference;

[0022] The estimated dynamic energy consumption is obtained by performing a weighted sum calculation based on the average power consumption, the regional benchmark power consumption, the behavior weight and the regional weight.

[0023] In one example, updating the displayed endurance value based on the estimated mileage includes:

[0024] The displayed cruising range value is updated according to the difference ratio between the displayed cruising range value and the estimated mileage.

[0025] In one example, the estimating the dynamic energy consumption according to the average power consumption and the regional benchmark power consumption includes:

[0026] In the case of cross-region driving, the dynamic energy consumption is estimated by calculating the average power consumption and the regional benchmark power consumption according to the regional center distance ratio.

[0027] A second aspect of an embodiment of the present disclosure provides a vehicle dynamic driving endurance calculation device, the device comprising:

[0028] The power consumption statistics module is used to count the average power consumption corresponding to the vehicle's recent target distance;

[0029] A data receiving module, used to receive the regional benchmark power consumption sent by the cloud within a pre-defined area, and determine the corresponding upper and lower floating range based on the regional benchmark power consumption;

[0030] an estimated calculation module, configured to calculate an estimated dynamic energy consumption according to the average power consumption and the regional benchmark power consumption, and to calculate an estimated driving mileage based on the remaining available power and the estimated dynamic energy consumption, wherein the estimated dynamic energy consumption complies with the upper and lower floating range;

[0031] The endurance update module is used to update the displayed endurance value based on the estimated mileage.

[0032] A third aspect of an embodiment of the present disclosure provides a vehicle, the server comprising: a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor executes the method of the first aspect above.

[0033] A fourth aspect of an embodiment of the present disclosure provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the method of the first aspect described above can be implemented.

[0034] The disclosed embodiment provides a method and device for calculating the dynamic driving range of a vehicle, the method comprising: calculating the average power consumption corresponding to the vehicle's most recent target driving distance, then receiving the regional benchmark power consumption sent by the cloud within a pre-defined area, and determining the corresponding upper and lower floating range based on the regional benchmark power consumption, then calculating the estimated dynamic energy consumption based on the average power consumption and the regional benchmark power consumption, and calculating the estimated driving mileage based on the remaining available power and the estimated dynamic energy consumption, the estimated dynamic energy consumption conforming to the upper and lower floating range, and finally updating the displayed driving range value based on the estimated driving mileage. The use of this technical solution can reduce the impact of environmental changes on the remaining driving range within a pre-defined area, combine the driver's vehicle usage habits and the regional benchmark power consumption, obtain a more accurate estimated driving mileage, and improve the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0036] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0037] Figure 1 It is a flow chart of a method for calculating vehicle dynamic driving endurance provided by an embodiment of the present disclosure;

[0038] Figure 2 It is a flowchart of another vehicle dynamic driving endurance calculation method provided by an embodiment of the present disclosure;

[0039] Figure 3 It is a flowchart of another method for calculating the dynamic driving endurance of a vehicle provided by an embodiment of the present disclosure;

[0040] Figure 4 It is a flowchart of another method for calculating vehicle dynamic driving endurance provided by an embodiment of the present disclosure;

[0041] Figure 5 It is a structural schematic diagram of a vehicle dynamic driving endurance calculation device provided by an embodiment of the present disclosure;

[0042] Figure 6 It is a structural schematic diagram of a vehicle in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0043] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0044] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.

[0045] Figure 1 The present invention provides a flow chart of a vehicle dynamic driving range calculation method provided by an embodiment of the present invention, which can be executed by an electronic device. The electronic device may include but is not limited to devices such as vehicle-mounted devices and vehicle controllers.

[0046] like Figure 1 As shown, the method provided in this embodiment includes the following steps:

[0047] S110, calculating the average power consumption corresponding to the vehicle's most recent target driving distance.

[0048] In the disclosed embodiment, the electronic device may count the average power consumption corresponding to the vehicle's most recent target distance.

[0049] Optionally, the average power consumption may be an average power consumption after the vehicle travels a certain distance.

[0050] Specifically, the electronic device can count the average power consumption of the vehicle after the vehicle has traveled the target distance most recently.

[0051] S120: In a predefined area, receiving a regional benchmark power consumption sent by the cloud, and determining a corresponding upper and lower floating range based on the regional benchmark power consumption.

[0052] In an embodiment of the present disclosure, the electronic device can receive the regional benchmark power consumption sent by the cloud within a pre-defined area, and determine a corresponding upper and lower floating range based on the regional benchmark power consumption.

[0053] Optionally, the pre-demarcated area can be pre-demarcated in a region. For example, the city is used as the region for division, and additional regions are added if the terrain and climate in the region are complex, such as the city of xx needs to be divided into multiple regions.

[0054] Optionally, the regional benchmark electric consumption may be average electric consumption data used to characterize most (95%) vehicles in a certain area.

[0055] Optionally, the upper and lower floating range can be a range within which the power consumption data is allowed to float up and down. For example, the initial setting of the upper and lower floating ranges is 20% of the regional benchmark power consumption. Assuming the power consumption is 20kwh / 100km, the upper limit is calculated to be 22kwh / 100km and the lower limit is 18kwh / 100km. The upper and lower floating ranges can be calculated by the cloud based on 20% of the regional benchmark power consumption and sent to the electronic device, or calculated by the electronic device based on 20% after receiving the regional benchmark power consumption.

[0056] Specifically, when the vehicle travels into a pre-defined area, the electronic device can receive the regional benchmark power consumption and upper and lower floating range corresponding to the pre-defined area sent by the cloud, or the electronic device can receive the regional benchmark power consumption corresponding to the pre-defined area sent by the cloud, and calculate the upper and lower floating range based on the regional benchmark power consumption.

[0057] S130, calculating an estimated dynamic energy consumption according to the average power consumption and the regional benchmark power consumption, and calculating an estimated mileage based on the remaining available power and the estimated dynamic energy consumption, wherein the estimated dynamic energy consumption complies with the upper and lower floating range.

[0058] In an embodiment of the present disclosure, the electronic device may calculate an estimated dynamic energy consumption based on the average power consumption and the regional benchmark power consumption, and calculate an estimated driving mileage based on the remaining available power and the estimated dynamic energy consumption.

[0059] Optionally, the estimated dynamic energy consumption can be the estimated electric energy required to be consumed when the vehicle travels in a predefined area. The estimated dynamic energy consumption complies with the upper and lower floating ranges, for example, the floating upper limit is 22kwh / 100km, and when the actual calculated estimated dynamic energy consumption is 25kwh / 100km, the estimated dynamic energy consumption is 22kwh / 100km.

[0060] Optionally, the remaining available electric energy may be the remaining electric energy of the vehicle at this time.

[0061] Optionally, the estimated mileage may be an estimated remaining mileage of the vehicle.

[0062] Specifically, after obtaining the average power consumption and the regional benchmark power consumption, the electronic device can calculate the estimated dynamic energy consumption based on the average power consumption and the regional benchmark power consumption, and the estimated dynamic energy consumption conforms to the upper and lower floating range, and calculate the estimated mileage based on the remaining available power and the estimated dynamic energy consumption.

[0063] S140: Update the displayed endurance value based on the estimated mileage.

[0064] In the disclosed embodiment, the electronic device may update the displayed endurance value based on the estimated mileage.

[0065] Optionally, the displayed endurance value may be a meter on the vehicle for displaying the remaining endurance value.

[0066] Specifically, after obtaining the estimated mileage, the electronic device can update the displayed endurance value based on the estimated mileage.

[0067] Therefore, in the disclosed embodiment, the method includes: counting the average power consumption corresponding to the vehicle's most recent target distance, then receiving the regional benchmark power consumption sent by the cloud in a pre-defined area, and determining the corresponding upper and lower floating range based on the regional benchmark power consumption, and then calculating the estimated dynamic energy consumption based on the average power consumption and the regional benchmark power consumption, and calculating the estimated mileage based on the remaining available power and the estimated dynamic energy consumption, the estimated dynamic energy consumption conforming to the upper and lower floating range, and finally updating the displayed endurance value based on the estimated mileage. The use of this technical solution can reduce the impact of environmental changes on the remaining endurance in a pre-defined area, combine the driver's car usage habits and the regional benchmark power consumption, obtain a more accurate estimated mileage, and improve the user experience.

[0068] Optionally, S110 may specifically include: counting the average power consumption corresponding to the vehicle's most recent target distance, and sending the average power consumption corresponding to the target distance to the cloud, wherein the average power consumption is corrected by power consumption of different driving distances under the same operating conditions.

[0069] In the disclosed embodiment, the electronic device may count the average power consumption corresponding to the target distance traveled by the vehicle recently, and send the average power consumption corresponding to the target distance to the cloud.

[0070] Optionally, the target distance may be 50 km. The average power consumption of the target distance is obtained by correcting the power consumption of different driving distances under the same operating conditions.

[0071] For example, the electronic device can count the power consumption corresponding to the last 1km, 5km, and 50km of the vehicle, and make corrections based on different driving distances under the same working conditions. For example, under the same working conditions, the electronic device can obtain the power consumption corresponding to 50km of the vehicle, or obtain the power consumption corresponding to 1km and 5km of the vehicle multiple times, and accumulate the power consumption corresponding to 50km, etc., which is not limited here. Then, the average power consumption corresponding to the target distance is sent to the cloud in combination with the vehicle's location.

[0072] Optionally, the regional benchmark power consumption is calculated by collecting the average power consumption corresponding to the target distances of multiple vehicles of the same model as the vehicle in the pre-defined area through the cloud.

[0073] Specifically, within a pre-defined area, the cloud can collect the average power consumption corresponding to the target distance of multiple vehicles of the same model as the vehicle itself, for example, collect the average power consumption of 50 km of multiple vehicles of the same model as the vehicle itself within the pre-defined area, and multiply vehicles with different configurations by different bases. For example, under user operating test conditions of a certain vehicle model, four-wheel drive consumes 20% more power than two-wheel drive. In this case, two-wheel drive vehicles can be included in the regional calculation at 1 times the energy consumption, and four-wheel drive vehicles can be included in the regional calculation at 1.2 times the energy consumption. The regional benchmark power consumption is calculated, and the electronic equipment can update the regional benchmark power consumption every 4 hours and update the upper and lower floating range every day.

[0074] Figure 2 It is a flow chart of another vehicle dynamic driving endurance calculation method provided by an embodiment of the present disclosure.

[0075] like Figure 2 As shown, the method provided in this embodiment includes the following steps:

[0076] S210. When a preset number threshold value exists in the average power consumption corresponding to the target distance of the multiple vehicles and exceeds the upper and lower floating range, the upper and lower floating range corrected by the cloud is obtained, and the coverage rate of the upper and lower floating range is greater than a first preset ratio.

[0077] Optionally, the preset quantity threshold may be a pre-set quantity threshold, for example, the preset quantity threshold may be 10%, 20%, etc. of the vehicle power consumption data in the area.

[0078] Optionally, the first preset ratio may be a preset ratio. For example, the first preset ratio may be 95%.

[0079] Specifically, the cloud can detect the upper and lower floating range every day. When a preset number threshold value exists in the average power consumption corresponding to the target distance of multiple vehicles that exceeds the upper and lower floating range, that is, it is detected that the average power consumption corresponding to the target distance of multiple vehicles with a preset number threshold value in the pre-defined area exceeds the upper and lower floating range, the upper and lower floating range is corrected so that the coverage rate of the upper and lower floating range is greater than the first preset ratio. For example, when 10% of the average power consumption corresponding to the target distance of multiple vehicles exceeds the upper and lower floating range, the upper and lower floating range is corrected so that the coverage rate of the upper and lower floating range is greater than 95%, and the electronic device can obtain the upper and lower floating range corrected by the cloud.

[0080] S220. When it is monitored within a preset time that the accuracy of the upper and lower floating range reaches the actual ratio, the upper and lower floating range corrected by the cloud is obtained, and the coverage of the upper and lower floating range is greater than a second preset ratio.

[0081] Optionally, the second preset ratio is similar to the first preset ratio, and the second preset ratio is greater than the first preset ratio. For example, the second preset ratio may be 96%.

[0082] Optionally, the actual ratio may be a ratio at which the accuracy reaches a maximum threshold, and the second preset ratio is less than the actual ratio. For example, the actual ratio may be 98% or above.

[0083] Specifically, the cloud can continue to detect, and if it is monitored within a preset time that the accuracy of the up and down floating range reaches the actual proportion, the up and down floating range can be corrected so that the coverage of the up and down floating range is greater than the second preset proportion. For example, after monitoring for a period of time, when the accuracy of the up and down floating range reaches 98% or above, the up and down floating range can be corrected so that the coverage of the up and down floating range is less than 96%, and the electronic device can obtain the up and down floating range corrected by the cloud. The result may be that the up and down floating range is large for users in mountainous areas and small for users in plain cities.

[0084] Optionally, the vehicle dynamic driving endurance calculation method may also include: acquiring historical data and climate data; increasing the upward floating range and reducing the downward floating range based on high energy consumption scenarios in the historical data; and increasing the update frequency of the upper and lower floating ranges based on changes in the climate data.

[0085] Specifically, the electronic device can obtain historical data and climate data. For example, historical data can be major holidays such as Spring Festival travel and National Day, and climate data can be rain, snow, etc. Then, based on the high energy consumption scenes in the historical data (National Day and Spring Festival travel belong to high energy consumption scenes), the upward floating range is increased and the downward floating range is reduced; based on the changes in the climate data, the update frequency of the upper and lower floating ranges is increased, such as adjusting the data update frequency when the climate changes drastically, and speeding up the data update frequency.

[0086] Figure 3 It is a flow chart of another vehicle dynamic driving endurance calculation method provided in an embodiment of the present disclosure.

[0087] like Figure 3 As shown, the method provided in this embodiment includes the following steps:

[0088] S310 , by calculating the difference between the power consumption of different driving distances and the average power consumption of the target distance, a corresponding behavior weight is determined according to the minimum difference.

[0089] In the embodiment of the present disclosure, the electronic device may determine the corresponding behavior weight according to the minimum difference by calculating the difference between the power consumption at different driving distances and the average power consumption at the target distance.

[0090] Optionally, the behavior weight may be used to characterize the importance of the user behavior.

[0091] For example, the electronic device can obtain the power consumption of 1km, 5km and 50km, and then calculate the difference between the power consumption of different driving distances and the average power consumption of the target distance, and determine the corresponding behavior weight according to the minimum difference. For example, according to the average power consumption of 5km, when the power consumption of 5km is closer to the power consumption of 50km, that is, the difference between the power consumption of 5km and 50km is the smallest, it is calculated as 0%; if the power consumption of 1km is closer to the power consumption of 50km, that is, the difference between the power consumption of 1km and 50km is the smallest, it is calculated as 20%.

[0092] S320 , performing weighted sum calculation according to the average power consumption, the regional benchmark power consumption, the behavior weight and the regional weight to obtain the estimated dynamic energy consumption.

[0093] In the embodiment of the present disclosure, the electronic device may perform a weighted sum calculation based on the average power consumption, the regional benchmark power consumption, the behavior weight, and the regional weight to obtain the estimated dynamic energy consumption.

[0094] Specifically, after obtaining the behavior weight, the electronic device can perform a weighted sum calculation. The corresponding calculation formula is: estimated dynamic energy consumption = average power consumption of the vehicle over the past 50 km * weight (1-40% - behavior weight) + regional benchmark power consumption * regional weight (regional weight is fixed at 40%) + average power consumption of the vehicle per 1 km * behavior weight.

[0095] Optionally, S140 may specifically include: updating the displayed endurance value according to a difference ratio between the displayed endurance value and the estimated mileage.

[0096] In the disclosed embodiment, the electronic device may update the displayed endurance value according to the difference ratio between the displayed endurance value and the estimated mileage.

[0097] Specifically, after obtaining the estimated mileage, the electronic device can update the displayed endurance value according to the difference ratio between the displayed endurance value and the estimated mileage. For example, in order to ensure that the displayed endurance value is updated stably without jumping and a difference is allowed between the estimated mileage, when the displayed endurance value is less than the estimated mileage, the displayed distance is greater than 1km for every 1km decrease; when the difference ratio between the displayed endurance value and the estimated mileage is greater, the displayed endurance value decreases by less than 1km for every 1km traveled; when the difference ratio between the displayed endurance value and the estimated mileage is smaller, the displayed endurance value decreases by nearly 1km for every 1km traveled. This improves the user experience while ensuring the accuracy of the displayed endurance value.

[0098] Optionally, S130 may specifically include: in case of cross-region driving, estimating the dynamic energy consumption according to the average power consumption and the regional benchmark power consumption according to the regional center distance ratio.

[0099] In the embodiment of the present disclosure, in the case of cross-region driving, the electronic device can estimate the dynamic energy consumption according to the average power consumption and the regional benchmark power consumption according to the regional center distance ratio.

[0100] For example, when driving across regions, passing through region A and region B, the total mileage is 100 km, of which 60 km is traveled in region A and 40 km is traveled in region B, that is, according to the regional center distance ratio of 3:2, the electronic device can calculate the estimated dynamic energy consumption and estimated mileage for 60% of the journey based on the regional benchmark power consumption and average power consumption of region A, and calculate the estimated dynamic energy consumption and estimated mileage for 40% of the journey based on the regional benchmark power consumption and average power consumption of region B.

[0101] In other examples, when the vehicle is restarted after being parked for a long time (24 hours), the estimated mileage is used as the displayed endurance value, and a pop-up window is displayed to inform the user (for example, 'Based on recent driving and regional energy consumption, your remaining mileage has been updated'); or after charging, the estimated mileage is used as the displayed endurance value.

[0102] Figure 4 It is a flow chart of another vehicle dynamic driving endurance calculation method provided in an embodiment of the present disclosure.

[0103] like Figure 4As shown, the electronic device can count the average power consumption corresponding to the vehicle's recent 1km, the average power consumption corresponding to 5km, and the average power consumption corresponding to the target distance (50km), the vehicle's location and driving habits, and send them to the cloud (automaker's big data cloud). The cloud obtains historical data and climate data, such as historical data of major holidays such as the Spring Festival and National Day, vehicle location area (latitude and longitude, altitude, slope), etc. Then the cloud can collect the average power consumption corresponding to the target distance of multiple vehicles of the same model as the vehicle, for example, collect the average power consumption of multiple vehicles of the same model as the vehicle within a pre-defined area for 50km, and multiply vehicles of different configurations by different bases, such as Under the user operating condition test conditions of a certain vehicle model, the four-wheel drive consumes 20% more electricity than the two-wheel drive. The two-wheel drive vehicle can be included in the regional calculation according to 1 times the energy consumption, and the four-wheel drive vehicle can be included in the regional calculation according to 1.2 times the energy consumption. The regional benchmark power consumption is calculated, and the corresponding upper and lower floating ranges are determined based on the regional benchmark power consumption. When the average power consumption corresponding to the target distances of multiple vehicles exceeds the upper and lower floating ranges by 10%, the upper and lower floating ranges are corrected so that the coverage rate of the upper and lower floating ranges is greater than 95%. After monitoring for a period of time, when the accuracy of the upper and lower floating ranges reaches 98% or above, the upper and lower floating ranges can be corrected so that the coverage rate of the upper and lower floating ranges is less than 96%. The electronic device can calculate the estimated dynamic energy consumption based on the average power consumption, the regional benchmark power consumption, the behavior weight and the regional weight; calculate the estimated mileage based on the remaining available power and the estimated dynamic energy consumption; when the vehicle is restarted after being parked for a long time (24 hours), the estimated mileage is directly used as the displayed endurance value, and a pop-up window is displayed to inform the user (for example, "Based on recent driving and regional energy consumption, your remaining mileage has been updated"); or after charging, the estimated mileage is directly used as the displayed endurance value; when the displayed endurance value is less than the estimated mileage, the displayed distance is greater than 1km for every 1km decrease, and the greater the ratio of the difference between the displayed endurance value and the estimated mileage, the less than 1km the displayed endurance value decreases for every 1km traveled; when the smaller the ratio of the difference between the displayed endurance value and the estimated mileage, the displayed endurance value decreases by nearly 1km for every 1km traveled.

[0104] Figure 5 is a schematic diagram of the structure of a vehicle dynamic driving endurance calculation device provided by an embodiment of the present disclosure. The vehicle dynamic driving endurance calculation device can be understood as the above-mentioned vehicle or a part of the functional modules in the above-mentioned vehicle. Figure 5 As shown, the vehicle dynamic driving endurance calculation device 500 includes:

[0105] The power consumption statistics module 510 is used to count the average power consumption corresponding to the vehicle's most recent target driving distance.

[0106] The data receiving module 520 is used to receive the regional benchmark power consumption sent by the cloud within a pre-defined area, and determine the corresponding upper and lower floating range based on the regional benchmark power consumption.

[0107] The estimated calculation module 530 is used to calculate the estimated dynamic energy consumption according to the average power consumption and the regional benchmark power consumption, and calculate the estimated mileage based on the remaining available power and the estimated dynamic energy consumption, and the estimated dynamic energy consumption complies with the upper and lower floating range.

[0108] The cruising range updating module 540 is used to update the displayed cruising range value based on the estimated mileage.

[0109] In one example, the power consumption statistics module 510 can be specifically used to count the average power consumption corresponding to the vehicle's most recent target distance, and send the average power consumption corresponding to the target distance to the cloud, where the average power consumption is corrected by the power consumption of different driving distances under the same operating conditions.

[0110] In one example, the regional benchmark power consumption is calculated by collecting the average power consumption corresponding to the target distance of multiple vehicles of the same model as the vehicle in the pre-defined area in the cloud.

[0111] In one example, the vehicle dynamic driving endurance calculation device 500 may further include:

[0112] The first acquisition module is used to obtain the upper and lower floating range corrected by the cloud when a preset number threshold exists in the average power consumption corresponding to the target distance of the multiple vehicles that exceeds the upper and lower floating range, and the coverage rate of the upper and lower floating range is greater than a first preset ratio.

[0113] The second acquisition module is used to obtain the upper and lower floating range corrected by the cloud when it is monitored that the accuracy of the upper and lower floating range reaches the actual proportion within the preset time, the coverage rate of the upper and lower floating range is greater than the second preset proportion, the second preset proportion is greater than the first preset proportion, and the second preset proportion is less than the actual proportion.

[0114] In one example, the vehicle dynamic driving endurance calculation device 500 may further include:

[0115] The third acquisition module is used to acquire historical data and climate data.

[0116] The first adjustment module is used to increase the upward floating range and reduce the downward floating range based on the high energy consumption scenes in the historical data.

[0117] The second adjustment module is used to increase the updating frequency of the upper and lower floating range based on the change of the climate data.

[0118] In one example, the estimation calculation module 530 may specifically include:

[0119] The first calculation unit is used to calculate the difference between the power consumption of different driving distances and the average power consumption of the target distance, and determine the corresponding behavior weight according to the minimum difference.

[0120] The second calculation unit is used to perform weighted sum calculation according to the average power consumption, the regional benchmark power consumption, the behavior weight and the regional weight to obtain the estimated dynamic energy consumption.

[0121] In one example, the range update module 540 may be specifically configured to update the displayed range value according to a difference ratio between the displayed range value and the estimated mileage.

[0122] In one example, the estimation calculation module 530 may be specifically used to calculate the estimated dynamic energy consumption according to the average power consumption and the regional benchmark power consumption in accordance with the regional center distance ratio when traveling across regions.

[0123] The device provided in this embodiment can execute the method of any of the above embodiments, and its execution method and beneficial effects are similar, which will not be repeated here.

[0124] The embodiments of the present disclosure further provide a vehicle, which includes: a memory, in which a computer program is stored; and a processor, which is used to execute the computer program. When the computer program is executed by the processor, the method of any of the above embodiments can be implemented.

[0125] For example, Figure 6 Schematic diagram of a vehicle structure in the embodiment of the present disclosure. Figure 6 , which shows a schematic diagram of a structure of a vehicle 1000 suitable for implementing the embodiment of the present disclosure. The vehicle 1000 in the embodiment of the present disclosure may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 6 The vehicle shown is merely an example and should not bring any limitation to the functionality and scope of use of the embodiments of the present disclosure.

[0126] like Figure 6As shown, the vehicle 1000 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 1001, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1008 to a random access memory (RAM) 1003. In the RAM 1003, various programs and data required for the operation of the vehicle 1000 are also stored. The processing device 1001, the ROM 1002, and the RAM 1003 are connected to each other via a bus 1004. An input / output (I / O) interface 1005 is also connected to the bus 1004.

[0127] Typically, the following devices may be connected to the I / O interface 1005: input devices 1006 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 1007 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1008 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 may allow the vehicle 1000 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 6 The vehicle 1000 is shown with various devices, but it should be understood that it is not required to implement or have all of the devices shown. More or fewer devices may be implemented or have instead.

[0128] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device 1009, or installed from a storage device 1008, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.

[0129] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0130] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0131] The computer-readable medium may be included in the vehicle, or may exist independently without being installed in the vehicle.

[0132] The above-mentioned computer-readable medium carries one or more programs. When the above-mentioned one or more programs are executed by the vehicle, the vehicle: calculates the average power consumption corresponding to the vehicle's most recent target distance; receives the regional benchmark power consumption and the upper and lower floating range sent by the cloud within a pre-defined area; calculates the estimated dynamic energy consumption based on the average power consumption and the regional benchmark power consumption, and calculates the estimated mileage based on the remaining available power and the estimated dynamic energy consumption, and the estimated dynamic energy consumption is in line with the upper and lower floating range; updates the displayed endurance value based on the estimated mileage.

[0133] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0134] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0135] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the name of a unit does not, in some cases, limit the unit itself.

[0136] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0137] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0138] The embodiments of the present disclosure also provide a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, the method of any of the above embodiments can be implemented. The execution method and beneficial effects are similar and will not be repeated here.

[0139] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0140] The above description is only a specific embodiment of the present disclosure, so that those skilled in the art can understand or implement the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure will not be limited to the embodiments described herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for calculating vehicle dynamic driving endurance, characterized in that: include: Count the average power consumption corresponding to the vehicle's most recent target distance; In a pre-defined area, receiving the regional benchmark power consumption sent by the cloud, and determining the corresponding upper and lower floating range based on the regional benchmark power consumption; Calculating an estimated dynamic energy consumption according to the average power consumption and the regional benchmark power consumption, and calculating an estimated driving mileage based on the remaining available power and the estimated dynamic energy consumption, wherein the estimated dynamic energy consumption complies with the upper and lower floating range; The displayed endurance value is updated based on the estimated mileage.

2. The method according to claim 1, characterized in that The statistical average power consumption corresponding to the vehicle's most recent target distance includes: The average power consumption corresponding to the vehicle's most recent target distance is counted, and the average power consumption corresponding to the target distance is sent to the cloud. The average power consumption is corrected by the power consumption of different driving distances under the same working conditions.

3. The method according to claim 2, characterized in that The regional benchmark power consumption is calculated by collecting the average power consumption corresponding to the target distances of multiple vehicles of the same model as the vehicle in the pre-defined area through the cloud.

4. The method according to claim 3, characterized in that The method further comprises: When a preset number threshold value among the average power consumptions corresponding to the target distances of the plurality of vehicles exceeds the upper and lower floating range, obtaining the upper and lower floating range corrected by the cloud, and the coverage rate of the upper and lower floating range is greater than a first preset ratio; When the accuracy of the upper and lower floating range is monitored to reach the actual proportion within the preset time, the upper and lower floating range corrected by the cloud is obtained, and the coverage rate of the upper and lower floating range is greater than the second preset proportion, the second preset proportion is greater than the first preset proportion, and the second preset proportion is less than the actual proportion.

5. The method according to claim 1, characterized in that The method further comprises: Access historical and climate data; Based on the high energy consumption scenarios in the historical data, increase the upward range and reduce the downward range; Based on the changes in the climate data, the updating frequency of the upper and lower floating range is increased.

6. The method according to claim 1, characterized in that The calculating and estimating the dynamic energy consumption according to the average power consumption and the regional benchmark power consumption includes: By calculating the difference between the power consumption of different driving distances and the average power consumption of the target distance, the corresponding behavior weight is determined according to the minimum difference; The estimated dynamic energy consumption is obtained by performing a weighted sum calculation based on the average power consumption, the regional benchmark power consumption, the behavior weight and the regional weight.

7. The method according to claim 1, characterized in that The updating of the displayed endurance value based on the estimated mileage includes: The displayed cruising range value is updated according to the difference ratio between the displayed cruising range value and the estimated mileage.

8. The method according to claim 1, characterized in that The calculating and estimating the dynamic energy consumption according to the average power consumption and the regional benchmark power consumption includes: In the case of cross-region driving, the dynamic energy consumption is estimated by calculating the average power consumption and the regional benchmark power consumption according to the regional center distance ratio.

9. A vehicle dynamic driving endurance calculation device, characterized in that: The device comprises: The power consumption statistics module is used to count the average power consumption corresponding to the vehicle's recent target distance; A data receiving module, used to receive the regional benchmark power consumption sent by the cloud within a pre-defined area, and determine the corresponding upper and lower floating range based on the regional benchmark power consumption; an estimated calculation module, configured to calculate an estimated dynamic energy consumption according to the average power consumption and the regional benchmark power consumption, and to calculate an estimated driving mileage based on the remaining available power and the estimated dynamic energy consumption, wherein the estimated dynamic energy consumption complies with the upper and lower floating range; The endurance update module is used to update the displayed endurance value based on the estimated mileage.

10. A vehicle, characterized in that: include: A processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the processor executes the method according to any one of claims 1 to 8.

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