Remaining endurance mileage determination method, electronic equipment and vehicle

Abstract

The invention provides a remaining endurance mileage determination method, electronic equipment and a vehicle, and the method comprises the steps: collecting vehicle operation parameters according to a preset first sampling interval, and determining a working condition proportion of each driving working condition according to the vehicle operation parameters and a preset power consumption statistical table; collecting vehicle power utilization parameters according to a preset second sampling interval, and determining average energy consumption in the historical mileage according to the working condition proportion and the vehicle power utilization parameters; wherein the first acquisition interval is greater than the second acquisition interval; and determining and displaying the remaining endurance mileage according to the current battery remaining capacity and the average energy consumption. The probability statistical method is introduced into the calculation process of the average energy consumption in a mode of determining each driving working condition, so that the car using habit of the user is better determined, the calculation optimization of the average energy consumption is realized, the accuracy of the average energy consumption is improved, the accuracy of the residual endurance mileage is improved, the mileage anxiety feeling of the user is reduced, and the user experience is improved. And the vehicle use experience of the user is improved.

Description

Technical Field

[0001] The present application relates to the technical field, and in particular to a method for determining remaining cruising range, an electronic device, and a vehicle. Background Art

[0002] The accuracy of the remaining range of pure electric new energy vehicles is often a focus of users. If the remaining range is not accurate enough, it will cause mileage anxiety for users, especially when the battery is low. Users often struggle with whether to use the car normally or find a charging station for charging as soon as possible, which brings a bad driving experience to users. Summary of the invention

[0003] In view of this, the purpose of the present application is to propose a method for determining the remaining cruising range, an electronic device and a vehicle, so as to improve the accuracy of the remaining cruising range.

[0004] Based on the above purpose, the present application provides a method for determining the remaining cruising range, including:

[0005] Collecting vehicle operating parameters according to a preset first sampling interval, and determining the operating condition proportion of each driving condition according to the vehicle operating parameters and a preset power consumption statistical table;

[0006] Collecting the vehicle power consumption parameters according to a preset second sampling interval, and determining the average energy consumption within the historical mileage according to the operating condition proportion and the vehicle power consumption parameters; wherein the first collection interval is greater than the second collection interval;

[0007] The remaining cruising range is determined and displayed based on the current remaining battery power and the average energy consumption.

[0008] Based on the same inventive concept, the present disclosure also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable by the processor, wherein the processor implements the method as described above when executing the computer program.

[0009] Optionally, determining the operating condition proportion of each driving condition according to the vehicle operating parameters and a preset power consumption statistics table includes:

[0010] Determining a target statistical parameter corresponding to the vehicle operation parameter in the power consumption statistical table, and performing a cumulative counting on the target statistical parameter;

[0011] Determining statistical parameters of each driving condition in the power consumption statistical table, and determining the sum of all statistical parameters as the statistical total;

[0012] The ratio of each of the statistical parameters to the statistical total is respectively determined as the operating condition proportion of the corresponding driving condition.

[0013] By introducing statistics into the calculation process of average energy consumption and determining the proportion of working conditions, the user's driving habits can be transformed into a probability statistics method under statistics. As the driving mileage increases, the statistical results will become closer and closer to the user's driving habits, thereby improving the accuracy of the calculation of average energy consumption.

[0014] Optionally, the vehicle operation parameters include monitoring vehicle speed, monitoring torque and battery power consumption; and determining the target statistical parameters corresponding to the vehicle operation parameters in the power consumption statistical table includes:

[0015] Determining, in the power consumption statistical table, a target vehicle speed interval item corresponding to the monitored vehicle speed and a target torque interval item corresponding to the monitored torque;

[0016] In the power consumption statistics table, determining a parameter selection range according to the target torque interval item and the target vehicle speed interval item, and determining a target power interval item corresponding to the battery consumption power in the parameter selection range;

[0017] The statistical parameter corresponding to the target power interval item in the parameter selection range is determined as the target statistical parameter.

[0018] The discrete values ​​within a certain range are uniformly divided through the parameter selection range to reduce the proportion of transient values ​​and amplify the ratio of the sampling points in the steady-state part, so as to achieve the purpose of improving the calculation accuracy.

[0019] Optionally, the battery power consumption includes low voltage power consumption and high voltage power consumption; and determining a target power interval item corresponding to the battery power consumption in the parameter selection range includes:

[0020] Determining a target low-voltage interval item corresponding to the low-voltage power consumption and a target high-voltage interval item corresponding to the high-voltage power consumption in the parameter selection range;

[0021] The search item corresponding to the target high-pressure interval item and the target low-pressure interval item in the parameter selection range is determined as the target power interval item.

[0022] By dividing the power consumption of the low-voltage system and the high-voltage system separately, the accuracy of the statistical data is further improved, and the accuracy of the calculation of the average energy consumption is further improved, so that the remaining cruising range can be accurately calculated. Because the more content the statistical table is divided into, the more accurate the calculation result will be.

[0023] Optionally, determining the average energy consumption within the historical mileage according to the operating condition proportion and the vehicle power consumption parameter includes:

[0024] Determine the total energy consumption within the historical mileage according to the vehicle power consumption parameter and the operating condition ratio;

[0025] The ratio of the total energy consumption to the historical mileage is determined as the average energy consumption.

[0026] Using historical mileage for calculation has more data and can improve the accuracy of the corresponding average energy consumption calculation.

[0027] Optionally, the vehicle power consumption parameters include battery current and battery voltage; and determining the total energy consumption within the historical mileage according to the vehicle power consumption parameters and the operating condition proportion includes:

[0028] Performing a time-based integral calculation on the product of the battery current and the battery voltage to obtain a battery calculated energy consumption;

[0029] Determine the target operating condition ratio corresponding to the battery calculated energy consumption, and perform weighted average calculation on the battery calculated energy consumption and the corresponding target operating condition ratio to obtain a weighted average energy consumption;

[0030] Determine the number of collected samples according to the historical mileage and the second collection interval;

[0031] The product of the weighted average energy consumption and the number of collected samples is determined as the total energy consumption.

[0032] The weighted average calculation is used to eliminate the influence of interference data and improve the accuracy of average energy consumption and total energy consumption.

[0033] Optionally, determining the target operating condition ratio corresponding to the calculated energy consumption of the battery includes:

[0034] Determining a target power ratio interval including the battery calculation energy consumption from a plurality of preset power ratio intervals;

[0035] The operating condition proportion corresponding to the target proportion power interval is determined as the target operating condition proportion.

[0036] While ensuring the accuracy of the calculation, it is necessary to ensure the efficiency of the calculation process. By reducing the amount of data calculation and improving the calculation efficiency through the proportion of power intervals.

[0037] Optionally, determining the number of collected samples according to the historical mileage and the second collection interval includes:

[0038] Determine the driving time for the historical mileage;

[0039] The ratio of the driving duration to the second collection interval is determined as the number of collected samples.

[0040] When collecting data, there may be some data that exceeds the boundary and needs to be eliminated. The elimination operation may cause the number of collected samples to change. The number of collected samples calculated based on the driving time and the second collection interval will not be affected by data elimination, thereby improving the accuracy of the calculation of total energy consumption.

[0041] Based on the same inventive concept, the present disclosure also provides a vehicle, comprising the electronic device as described above.

[0042] From the above, it can be seen that the method for determining the remaining cruising range, the electronic device, and the vehicle provided by the present application can collect vehicle operating parameters according to a preset first sampling interval, and determine the proportion of each driving condition according to the vehicle operating parameters and the preset power consumption statistics table; collect vehicle power consumption parameters according to a preset second sampling interval, and determine the average energy consumption within the historical mileage according to the proportion of the operating conditions and the vehicle power consumption parameters; wherein the first collection interval is greater than the second collection interval; and determine and display the remaining cruising range based on the current remaining battery power and the average energy consumption. By introducing the probability statistics method into the calculation process of the average energy consumption by determining each driving condition, the user's car usage habits can be better determined, the calculation optimization of the average energy consumption can be achieved, the accuracy of the average energy consumption can be improved, and then the accuracy of the remaining cruising range can be improved, the user's mileage anxiety can be reduced, and the user's car experience can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the present application or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0044] Figure 1 This is a flow chart of a method for determining the remaining cruising range according to an embodiment of the present application;

[0045] Figure 2 A flow chart for determining the proportion of each driving condition in an embodiment of the present application;

[0046] Figure 3 A flowchart of determining a target power interval item corresponding to battery consumption power according to an embodiment of the present application;

[0047] Figure 4 A flow chart for determining average energy consumption within historical mileage for an embodiment of the present application;

[0048] Figure 5 A flow chart for determining the total energy consumption within the historical mileage for an embodiment of the present application;

[0049] Figure 6This is a schematic diagram of the structure of a device for determining the remaining cruising range according to an embodiment of the present application;

[0050] Figure 7 It is a schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0051] In order to make the objectives, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0052] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should be the usual meanings understood by people with ordinary skills in the field to which the present application belongs. The "first", "second" and similar words used in the embodiments of the present application do not represent any order, quantity or importance, but are only used to distinguish different components. "Including" or "comprising" and similar words mean that the elements or objects appearing in front of the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0053] It should be understood herein that any number of elements in the drawings is for illustration rather than limitation, and any naming is only for distinction rather than having any limiting meaning.

[0054] Based on the description of the above background technology, the related technology also has the following situations:

[0055] In the related technology, the following formula is generally used to calculate the remaining cruising range:

[0056] Remaining cruising range (in km) = current remaining battery power (in kwh) / average energy consumption (in kwh / km);

[0057] It can be seen from the calculation formula of the remaining cruising range that if you want to improve the accuracy of the remaining cruising range, you can start from two aspects. On the one hand, you can improve the accuracy of the current remaining battery power, and on the other hand, you can improve the accuracy of the average energy consumption. The current remaining battery power is detected and determined by the battery management system, and the development of battery-related technologies is already quite mature. The current battery remaining power detection and correction technology is relatively complete, so the current determination of the remaining battery power is usually more accurate, and there is no unified way to calculate the average energy consumption. Different calculation methods will lead to large differences in the accuracy of the average energy consumption.

[0058] The usual way to calculate average energy consumption is to count the average energy consumption per unit historical mileage of the vehicle (generally, the mileage per unit historical mileage is small, such as 10km), and assume that the driver will also drive the vehicle according to the average energy consumption in the future. The calculation process of average energy consumption is as follows:

[0059] Average energy consumption = (accumulated battery power consumption per unit historical mileage) / unit historical mileage

[0060] = (integral of battery power per unit historical mileage) / unit historical mileage

[0061] = (integral of battery current*voltage within unit historical mileage) / unit historical mileage;

[0062] The unit historical mileage in the related art is a relatively small mileage, for example, the unit historical mileage is set to 10km, or 20km, etc.;

[0063] However, the disadvantage of this method is that it arbitrarily assumes that the average energy consumption per unit historical mileage represents the average energy consumption of future users when driving the vehicle, ignoring the fact that the unit historical mileage cannot fully reflect the user's driving habits, thus leading to inaccurate calculation of the average energy consumption.

[0064] The remaining cruising range determination method, electronic device and vehicle provided in the embodiment of the present application can collect vehicle operating parameters according to a preset first sampling interval, and determine the proportion of each driving condition according to the vehicle operating parameters and a preset power consumption statistics table; collect vehicle power consumption parameters according to a preset second sampling interval, and determine the average energy consumption within the historical mileage according to the proportion of the conditions and the vehicle power consumption parameters; wherein the first collection interval is greater than the second collection interval; and determine and display the remaining cruising range according to the current remaining battery power and the average energy consumption. By introducing the probability statistics method into the calculation process of the average energy consumption by determining each driving condition, the user's car usage habits can be better determined, and the calculation optimization of the average energy consumption can be achieved, thereby improving the accuracy of the average energy consumption, thereby improving the accuracy of the remaining cruising range, reducing the user's mileage anxiety, and improving the user's car experience.

[0065] The following describes in detail the method for determining the remaining cruising range provided by the embodiments of the present application in conjunction with the accompanying drawings.

[0066] In some embodiments, Figure 1 As shown, a method for determining a remaining cruising range includes:

[0067] Step 101: Collect vehicle operating parameters according to a preset first sampling interval, and determine the proportion of each driving condition according to the vehicle operating parameters and a preset power consumption statistics table.

[0068] In specific implementation, the regular sampling interval of vehicle operation data is generally in the millisecond level. The vehicle operation parameters collected at the millisecond level sampling interval are transient data. The transient data may deviate from the current scene due to various operating conditions during vehicle driving (such as bad road conditions, slope conditions, etc.), which manifests as sudden increase or decrease in fluctuating data. These vehicle operation parameters that deviate from the current scene will affect the accuracy of the calculation of average energy consumption and are noise data. Therefore, when calculating the average energy consumption, it is necessary to reduce or even eliminate the influence of these noise data.

[0069] The embodiment of the present application chooses to reduce or even eliminate the influence of noise data by changing the sampling interval of vehicle operating parameters, and changes transient vehicle operating parameters into steady-state vehicle operating parameters by setting a larger first sampling interval. Exemplarily, taking the first sampling interval of 1 second as an example, the corresponding sampling frequency is 1 second / time, the first sampling interval is in the second level, the conventional collection of vehicle operating parameters is 10 milliseconds, and the corresponding sampling frequency is 10 milliseconds / time, which is in the millisecond level. Then, the vehicle operating parameters are collected once at the first sampling interval, and the conventional collection will be performed 100 times. If there is 1 noise data in the 100 collections, unless the noise appears in the 100th collection, it will not cause problems with the accuracy of the vehicle operating parameters collected according to the first sampling interval.

[0070] If there is one noise data in 100 collections, there will be an error of about 1% when calculating according to the millisecond-level collection data. If the vehicle operating parameters are collected according to the first sampling interval of seconds, the probability of noise data appearing in the 100th collection is 1%. Then, the vehicle operating parameters collected according to the first sampling interval of seconds will have an error of 1% × 1% = 0.01%, which greatly reduces the probability of error and improves the accuracy of the collected data. By changing the sampling interval of the vehicle operating parameters, the vehicle operating parameters are changed from millisecond-level transient data to second-level steady-state data, which improves the accuracy of the vehicle operating parameters themselves, because compared with the transient values, the steady-state values ​​can more accurately reflect the user's driving habits and behaviors. Using steady-state values ​​for calculation can improve the accuracy of average energy consumption and optimize the accuracy of the remaining cruising range from the data collection process.

[0071] The purpose of collecting vehicle operation parameters is to determine the user's vehicle usage habits. The vehicle usage habits can be expressed as a percentage. The higher the percentage of the driving condition, the more time the user has driven the vehicle in this driving condition, indicating that the user is accustomed to driving the vehicle in this driving condition. The vehicle operation parameters include monitoring vehicle speed, monitoring torque and battery power consumption. The monitoring vehicle speed represents the vehicle speed value collected when data is collected at the first sampling interval, the monitoring torque represents the torque value of the motor output collected when data is collected at the first sampling interval, and the battery power consumption represents the battery power consumption value sent by the battery management system when data is collected at the first sampling interval.

[0072] The power consumption statistics table is a distribution relationship table showing power consumption under different driving conditions. For example, the power consumption statistics table is shown in Table 1:

[0073] Table 1 Power consumption statistics

[0074]

[0075] Among them, when the vehicle is in driving state (it can be judged based on whether the vehicle speed is greater than 1 kph, when the vehicle speed is greater than 1, it is determined that the vehicle is in driving state, when the vehicle speed is less than or equal to 1, it is determined that the vehicle is in stationary state, and the vehicle driving data in the stationary state does not participate in the statistics), the components that cause the battery's remaining power consumption to decrease can be roughly divided into three parts: motor system, low-voltage system (such as instruments, lights, fans, etc.), and high-voltage system (such as air conditioning system), so the user's car usage habits can be combined with the power consumption of the three systems for statistical division, among which the power consumption of the low-voltage system and the high-voltage system can be combined into the battery power consumption, which can reduce the corresponding data volume and improve the calculation efficiency. The power consumption statistics table shown in Table 1 is obtained.

[0076] By using the grid division method shown in Table 1, statistics are collected during the first sampling interval T1 (e.g., 1 second) of vehicle operation, and the vehicle speed / torque / low-pressure system / high-pressure system power consumption is grid-divided in a range manner;

[0077] The grid-type division of vehicle speed and torque can be understood as mainly dividing the power consumption of the motor system by vehicle speed and torque;

[0078] To further improve the accuracy, the power consumption of the low-voltage system and the high-voltage system can be divided separately to obtain the power consumption statistics shown in Table 2:

[0079] Table 2 Power consumption statistics after high and low voltage division

[0080]

[0081] Among them, PL1 / PL2 / PL3 are the power division thresholds for dividing the low-voltage system, and they are all backward compatible, that is, when the low-voltage power is equal to PL2, the corresponding low-voltage interval item is determined to be PL1~PL2. PH1 / PH2 / PH3 are the power division thresholds for dividing the high-voltage system, and they are all backward compatible, that is, when the high-voltage power is equal to PH2, the corresponding low-voltage interval item is determined to be PH1~PH2. N1-N32 represent the statistical parameters of the corresponding driving conditions, and the values ​​of the statistical parameters are the statistical counts of the corresponding driving conditions. Among them, Tables 1 and 2 are examples, and the grid can be made finer by dividing more ranges to improve the statistical accuracy.

[0082] Taking the power consumption statistics table in Table 1 as an example, after the vehicle operation parameters are collected, the vehicle operation parameters are counted by a counter to determine the user's driving habits. That is, when the user drives the vehicle, every time the first sampling interval T1 passes, the VCU determines which area of ​​Table 1 the driving condition in the past T1 time belongs to according to the vehicle operation parameters, and then the corresponding statistical parameter value in the area is counted once. For example, if the monitored vehicle speed in the vehicle operation parameters is 15kph, the monitored torque in the vehicle operation parameters is 80NM, and the battery power consumption is between P1 and P2, then the driving condition corresponds to the area where N22 is located in the power consumption statistics table, and the corresponding statistical parameter is N22, so N22 needs to be counted and accumulated once, that is, N22=N22+1. If the initial value of N22 is N22=5, after the vehicle has traveled for T1 time, the area corresponding to the vehicle driving condition is still N22, and after a count accumulation, N22=6.

[0083] After obtaining the values ​​of each statistical parameter in the power consumption statistics table, continue to count the probability of each statistical parameter appearing in the entire power consumption statistics table: Taking the power consumption statistics table shown in Table 1 as an example, let Nsum = N1 + N2 + ... + N24, Nsum is the total number of statistics, indicating the total amount of statistical data. Then the proportion of each statistical parameter is N1 / Nsum, N2 / Nsum, N3 / Nsum, ..., N24 / Nsum, and this proportion is the proportion of the corresponding driving condition. For example, N22 / Nsum is the proportion of driving conditions with a monitored vehicle speed of 15kph, a monitored torque of 80NM, and a battery power consumption between P1 and P2.

[0084] By determining the proportion of working conditions, the user's driving habits can be transformed into a statistical probability statistical method. As the driving mileage increases, the statistical results are closer and closer to the user's driving habits, thereby improving the accuracy of the calculation of average energy consumption. The idea of ​​the embodiment of the present application is to improve the calculation accuracy by adjusting the proportion of transient values ​​(weighted ratio) and enlarging the ratio of the sampling points of the steady state part.

[0085] Step 102: Collect the vehicle power consumption parameters according to the preset second sampling interval, and determine the average energy consumption within the historical mileage according to the operating condition proportion and the vehicle power consumption parameters. The first collection interval is greater than the second collection interval.

[0086] In specific implementation, the calculation process of average energy consumption is as follows:

[0087] Average energy consumption = (battery power in historical mileage × integral of corresponding operating condition ratio) × Nsum / historical mileage = (battery current in historical mileage × battery voltage × integral of corresponding operating condition ratio) × Nsum / historical mileage;

[0088] Firstly, the unit historical mileage is changed to historical mileage to avoid the problem that the unit historical mileage cannot fully reflect the user's driving habits, thus leading to inaccurate calculation of average energy consumption, and ensure the accuracy of the average energy consumption calculation.

[0089] Then, for the driving conditions commonly used by users, the proportion of the conditions in the entire energy consumption calculation is enlarged by introducing a statistical method of the proportion of conditions, while for the driving conditions that are not commonly used, the proportion of the conditions in the entire energy consumption calculation is reduced by introducing a statistical method of the proportion of conditions. The average energy consumption is calculated by weighted average rather than absolute average; this can more accurately reflect the driving habits of each user when driving the vehicle, and link the driving habits with the calculation of average energy consumption; it should be noted that when calculating the proportion of conditions, the first sampling interval T1 needs to be much larger than the second sampling interval T2 of the vehicle's power consumption parameters, usually a comparison of s level (first sampling interval T1) VS ms level (second sampling interval T2).

[0090] The weighted average method is used to adjust the proportion of transient values ​​and amplify the ratio of the sampling points in the steady state to improve the accuracy of the calculation, so that the calculated average energy consumption is closer to the user's driving habits, thereby improving the accuracy of the remaining cruising range and improving the user's driving experience.

[0091] Step 103: Determine and display the remaining cruising range based on the current remaining battery power and average energy consumption.

[0092] In specific implementation, the calculation formula for the remaining cruising range is as follows:

[0093] Remaining cruising range (in km) = current remaining battery power (in kwh) / average energy consumption (in kwh / km);

[0094] Among them, since the current battery remaining power detection technology is already quite mature, the current battery remaining power value is generally more accurate, and the average energy consumption has been statistically optimized through weighted average, which has greatly reduced the error. Therefore, the accuracy of the remaining cruising range determined based on the current battery remaining power and the average energy consumption obtained after optimized calculation is greatly improved, which reduces the user's mileage anxiety and improves the user's car experience.

[0095] In summary, the method for determining the remaining cruising range provided in the embodiment of the present application can collect vehicle operating parameters according to a preset first sampling interval, and determine the proportion of each driving condition according to the vehicle operating parameters and a preset power consumption statistics table; collect vehicle power consumption parameters according to a preset second sampling interval, and determine the average energy consumption within the historical mileage according to the proportion of the operating conditions and the vehicle power consumption parameters; determine the remaining cruising range according to the current remaining battery power and the average energy consumption and display it. By introducing the probability statistics method into the calculation process of the average energy consumption by determining each driving condition, the user's car usage habits can be better determined, and the calculation optimization of the average energy consumption can be achieved, thereby improving the accuracy of the average energy consumption, and then improving the accuracy of the remaining cruising range, reducing the user's mileage anxiety, and improving the user's car experience.

[0096] In some embodiments, Figure 2 As shown, the proportion of each driving condition is determined according to the vehicle operating parameters and the preset power consumption statistics table, including:

[0097] Step 201: Determine a target statistical parameter corresponding to a vehicle operating parameter in a power consumption statistical table, and perform a cumulative counting on the target statistical parameter.

[0098] In specific implementation, the vehicle operation parameters include monitoring vehicle speed, monitoring torque and battery power consumption; then the target statistical parameters corresponding to the vehicle operation parameters are determined in the power consumption statistical table, including:

[0099] Step 2011: Determine a target vehicle speed interval item corresponding to the monitored vehicle speed and a target torque interval item corresponding to the monitored torque in the power consumption statistics table.

[0100] In specific implementation, taking the power consumption statistics table shown in Table 1 as an example, the torque interval includes [-100, -50], (-50, 0], (0, 50], (50, 100], and the speed interval includes [1, 10], (10, 20]. If the monitored speed in the vehicle operation parameters is 15kph, 15kph is less than the upper boundary speed of 20kph in the speed interval (10, 20], and is greater than the lower boundary speed of 10kph in the speed interval (10, 20], then the corresponding target speed interval is (10, 20], and the target speed interval item is 10-20. If the monitored torque in the vehicle operation parameters is 80NM, 80NM is less than the upper boundary torque of 100NM in the torque interval (50, 100], and is greater than the lower boundary torque of 50NM in the torque interval (50, 100], then the corresponding target torque interval is (50, 100], and the target torque interval item is 50-100.

[0101] Step 2012: In the power consumption statistics table, a parameter selection range is determined according to the target torque range item and the target vehicle speed range item, and a target power range item corresponding to the battery consumption power is determined in the parameter selection range.

[0102] In specific implementation, when the target torque interval item is determined to be 50-100 and the target vehicle speed interval item is 10-20, the corresponding parameter selection range is N22-N24 in Table 1, so it is necessary to determine the final target statistical parameters within the parameter selection range, and N22, N23 and N24 correspond to a power interval respectively, among which the statistical parameter N22 corresponds to the power interval [P1, P2], the statistical parameter N23 corresponds to the power interval (P2, P3], and the statistical parameter N24 corresponds to the power interval (P3, P4). If the battery power consumption is within the power interval [P1, P2], then the target power interval item corresponding to the battery power consumption is P1-P2.

[0103] Step 2013: Determine the statistical parameter corresponding to the target power interval item in the parameter selection range as the target statistical parameter.

[0104] In specific implementation, if the target power interval item is P1~P2, then the driving condition corresponds to the area where N22 is located in the power consumption statistics table, and the corresponding statistical parameter is N22. The statistical parameter corresponding to the target power interval item in the parameter selection range is N22, and N22 is determined as the target statistical parameter.

[0105] When the target statistical parameter is determined to be N22, it is necessary to count and accumulate the target statistical parameter N22, that is, set N22 = N22 + 1. If the initial value of N22 is N22 = 5, after the vehicle has traveled for T1 time, the area corresponding to the vehicle driving condition is still N22, and after a count accumulation, N22 = 6.

[0106] Step 202: Determine the statistical parameters of each driving condition in the power consumption statistical table, and determine the sum of all statistical parameters as the statistical total.

[0107] In specific implementation, when calculating the proportion of working conditions, the numerator of the calculation is the value of the target statistical parameter N22. At this time, it is necessary to further determine the denominator of the proportion calculation. The denominator is the statistical total of the power consumption statistics table, and the statistical total is the sum of all statistical parameters in the power consumption statistics table, that is, the statistical total Nsum = N1 + N2 + ~ + N24, Nsum is the statistical total, which represents the total amount of statistical data.

[0108] Step 203: Determine the ratio of each statistical parameter to the statistical total as the operating condition ratio of the corresponding driving condition.

[0109] In specific implementation, the proportions of various statistical parameters are N1 / Nsum, N2 / Nsum, N3 / Nsum, ..., N24 / Nsum, which are the proportions of the corresponding driving conditions. Then N22 / Nsum is the proportion of the driving conditions where the monitored vehicle speed is 15kph, the monitored torque is 80NM, and the battery power consumption is between P1 and P2.

[0110] By determining the proportion of working conditions, the user's driving habits can be transformed into a statistical probability statistical method. As the driving mileage increases, the statistical results are closer and closer to the user's driving habits, thereby improving the accuracy of the calculation of average energy consumption. The idea of ​​the embodiment of the present application is to improve the calculation accuracy by adjusting the proportion of transient values ​​(weighted ratio) and enlarging the ratio of the sampling points of the steady state part.

[0111] In some embodiments, the battery power consumption includes low voltage power consumption and high voltage power consumption; Figure 3 As shown, the target power interval item corresponding to the battery consumption power is determined in the parameter selection range, including:

[0112] Step 301: Determine a target low-voltage interval item corresponding to low-voltage power consumption and a target high-voltage interval item corresponding to high-voltage power consumption in the parameter selection range.

[0113] In specific implementation, if you want to further improve the accuracy, you can divide the power consumption of the low-voltage system and the high-voltage system separately, and get the power consumption statistics table shown in Table 2: Among them, PL1 / PL2 / PL3 are the power division thresholds for dividing the low-voltage system, and they are all backward compatible, that is, when the low-voltage power is equal to PL2, the corresponding low-voltage interval item is determined to be PL1~PL2. PH1 / PH2 / PH3 are the power division thresholds for dividing the high-voltage system, and they are all backward compatible, that is, when the high-voltage power is equal to PH2, the corresponding low-voltage interval item is determined to be PH1~PH2.

[0114] If the low-voltage power consumption is between PL1 and PL2, PL1 and PL2 are determined as target low-voltage interval items; if the high-voltage power consumption is between PH1 and PH2, PH1 and PH2 are determined as target high-voltage interval items.

[0115] Step 302: Determine the search items corresponding to the target high voltage interval item and the target low voltage interval item in the parameter selection range as the target power interval item.

[0116] In specific implementation, according to Table 2, when the target low pressure interval item is PL1-PL2 and the target high pressure interval item is PH1-PH2, the corresponding search item is N29.

[0117] By dividing the power consumption of the low-voltage system and the high-voltage system separately, the accuracy of the statistical data is further improved, and the accuracy of the calculation of the average energy consumption is further improved, so that the remaining cruising range can be accurately calculated. Because the more content the statistical table is divided into, the more accurate the calculation result will be.

[0118] In some embodiments, Figure 4 As shown in the figure, the average energy consumption within the historical mileage is determined based on the proportion of working conditions and vehicle power consumption parameters, including:

[0119] Step 401: Determine the total energy consumption within the historical mileage according to the vehicle power consumption parameters and the proportion of operating conditions.

[0120] In the specific implementation, the battery current and battery voltage in each collected vehicle power parameter must first be determined, and then the power at each collection moment must be determined, and then the operating condition ratio of the power at different moments must be determined, and the product of the power and the operating condition ratio must be integrated over time to obtain the weighted average energy consumption within the historical mileage. Finally, the product of the weighted average energy consumption and Nsum must be determined as the total energy consumption, i.e., total energy consumption = (battery power within the historical mileage × integral of the corresponding operating condition ratio) × Nsum. Among them, the historical mileage is the total mileage from the first time the vehicle drove to the current moment. Using the historical mileage for calculation has more data, which can improve the accuracy of the corresponding average energy consumption calculation.

[0121] While ensuring accuracy, it is necessary to ensure the efficiency of the calculation process, so it is necessary to impose certain restrictions on historical mileage. If the historical mileage is less than or equal to the preset mileage threshold (for example, 500km), the historical mileage is used to calculate the average energy consumption; if the historical mileage is less than or equal to the preset mileage threshold (for example, 500KM), the mileage threshold is used to replace the historical mileage to calculate the average energy consumption. Among them, when using the mileage threshold to calculate the average energy consumption, it is necessary to use the mileage at the current moment as the starting point for mileage selection, and select 500km of mileage as the historical mileage. For example, if the historical mileage is 600km up to the current moment, the mileage of the last 500km is selected as the mileage for calculation, because the closer the data is to the current moment, the more it can reflect the user's car usage habits. By limiting the selection of historical mileage, the amount of calculation is reduced while ensuring the accuracy of the average energy consumption calculation, and the calculation efficiency is improved.

[0122] Step 402: Determine the ratio of total energy consumption to historical mileage as average energy consumption.

[0123] In specific implementation, average energy consumption = total energy consumption / historical mileage = (battery power within historical mileage × integral of corresponding operating condition proportion) × Nsum / historical mileage = (battery current within historical mileage × battery voltage × integral of corresponding operating condition proportion) × Nsum / historical mileage.

[0124] In some embodiments, the vehicle power parameters include battery current and battery voltage; Figure 5 As shown in the figure, the total energy consumption within the historical mileage is determined based on the vehicle's power consumption parameters and operating conditions, including:

[0125] Step 501: Perform time-based integral calculation on the product of the battery current and the battery voltage to obtain the battery calculated energy consumption.

[0126] In specific implementation, the corresponding energy consumption value is obtained by integrating the battery power within the historical mileage, and the battery power is the product of the battery current and the battery voltage. Therefore, by performing a time-based integral calculation on the product of the battery current and the battery voltage, the calculated battery energy consumption at each data collection moment can be obtained.

[0127] Step 502: Determine the target operating condition ratio corresponding to the battery calculated energy consumption, and perform weighted average calculation on the battery calculated energy consumption and the corresponding target operating condition ratio to obtain a weighted average energy consumption.

[0128] In specific implementation, the target operating condition ratio corresponding to the battery calculation energy consumption is determined, including:

[0129] Step 5021: Determine a target power ratio interval including battery calculation energy consumption from among a plurality of preset power ratio intervals.

[0130] In the specific implementation, take the case where only N1, N2 and N3 are present as an example. If the operating condition corresponding to N1 accounts for 10%, the operating condition corresponding to N2 accounts for 70%, and the operating condition corresponding to N3 accounts for 20%, and the power interval corresponding to N1 is [P1, P2]; the power interval corresponding to N2 is (P2, P3]; the power interval corresponding to N3 is (P3, P4]. If the battery calculated energy consumption X1 is within the power interval [P1, P2], [P1, P2] is used as the target power interval; if the battery calculated energy consumption X2 is within the power interval (P2, P3], (P2, P3] is used as the target power interval; if the battery calculated energy consumption X3 is within the power interval (P3, P4], (P3, P4] is used as the target power interval.

[0131] Step 5022: Determine the operating condition proportion corresponding to the target proportion power interval as the target operating condition proportion.

[0132] In specific implementation, if the battery calculated energy consumption X1 is within the power interval [P1, P2], 10% corresponding to the target power interval [P1, P2] is used as the target operating condition proportion; if the battery calculated energy consumption X2 is within the power interval (P2, P3], 70% corresponding to the target power interval (P2, P3] is used as the target operating condition proportion; if the battery calculated energy consumption X3 is within the power interval (P3, P4], 20% corresponding to the target power interval (P3, P4] is used as the target operating condition proportion.

[0133] The weighted average energy consumption = X1×10%+X2×70%+X3×20%. In actual use, the historical mileage of 500km may include a large amount of battery calculation energy consumption. The weighted average energy consumption can be calculated in the same way. The weighted average energy consumption = battery current × battery voltage × integral of the corresponding operating condition ratio in the historical mileage.

[0134] Step 503: Determine the number of collected samples according to the historical mileage and the second collection interval.

[0135] In specific implementation, step 503 includes:

[0136] Step 5031: Determine the driving duration of the historical mileage.

[0137] In specific implementation, because the second sampling interval of the vehicle power consumption parameters is 10ms, if the historical mileage is 500km, it is necessary to determine the driving time consumed by the vehicle to travel 500km, so as to determine the number of samples of the vehicle power consumption parameters collected during the historical mileage.

[0138] Step 5032: Determine the ratio of the driving duration to the second collection interval as the number of collection samples.

[0139] In specific implementation, the second collection interval is the collection frequency of the vehicle power consumption parameters, and the ratio of the driving time to the second collection interval is the number of collected samples; if the driving time is 6h, the number of collected samples = 6×3600000 / 10=2160000.

[0140] Among them, there may be some data that exceed the boundary and need to be eliminated during data collection, and the elimination operation may cause the number of collected samples to change. Because the statistical range of the operating condition ratio is P1~P4, if the battery calculated energy consumption corresponding to a certain vehicle power parameter exceeds the range of P1~P4, the battery calculated energy consumption will not be able to match the corresponding operating condition ratio, then the battery calculated energy consumption can be directly eliminated, and the number of collected samples can be reduced by 1. If there are 50 out-of-range elimination data among the 2160000 vehicle power parameters, the final number of collected samples = 2160000-50 = 2159950. Data elimination can further improve the calculation accuracy of total energy consumption, thereby improving the calculation accuracy of remaining cruising range.

[0141] Step 504: The product of the weighted average energy consumption and the number of collected samples is determined as the total energy consumption.

[0142] In specific implementation, the weighted average represents the energy consumption of a single collected data, and the product of the weighted average energy consumption and the number of collected samples is the total energy consumption consumed by the historical mileage.

[0143] It should be noted that the method of the embodiment of the present application can be performed by a single device, such as a computer or server. The method of this embodiment can also be applied to a distributed scenario and completed by multiple devices cooperating with each other. In the case of such a distributed scenario, one of the multiple devices can only perform one or more steps in the method of the embodiment of the present application, and the multiple devices will interact with each other to complete the described method.

[0144] It should be noted that the above describes some embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0145] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides a device for determining the remaining cruising range.

[0146] refer to Figure 6 , the remaining cruising range determining device comprises:

[0147] The operating condition proportion determination module 10 is configured to: collect vehicle operating parameters according to a preset first sampling interval, and determine the operating condition proportion of each driving condition according to the vehicle operating parameters and a preset power consumption statistical table;

[0148] The average energy consumption determination module 20 is configured to: collect vehicle power consumption parameters according to a preset second sampling interval, and determine the average energy consumption within the historical mileage according to the operating condition proportion and the vehicle power consumption parameters; wherein the first collection interval is greater than the second collection interval;

[0149] The cruising range determination module 30 is configured to determine and display the remaining cruising range according to the current remaining battery power and the average energy consumption.

[0150] For the convenience of description, the above device is described in terms of functions divided into various modules. Of course, when implementing the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0151] The device of the above embodiment is used to implement the corresponding remaining cruising range determination method in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0152] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for determining the remaining cruising range described in any of the above embodiments is implemented.

[0153] Figure 7 A more specific schematic diagram of the hardware structure of an electronic device provided in this embodiment is shown, and the device may include: a processor 1010, a memory 1020, an input / output interface 1030, a communication interface 1040, and a bus 1050. The processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040 are connected to each other through the bus 1050 in the device.

[0154] The processor 1010 can be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0155] The memory 1020 may be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 1020 may store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program codes are stored in the memory 1020 and are called and executed by the processor 1010.

[0156] The input / output interface 1030 is used to connect the input / output module to realize information input and output. The input / output module can be configured in the device as a component (not shown in the figure), or it can be externally connected to the device to provide corresponding functions. The input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.

[0157] The communication interface 1040 is used to connect a communication module (not shown) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired mode (such as USB, network cable, etc.) or a wireless mode (such as mobile network, WIFI, Bluetooth, etc.).

[0158] The bus 1050 includes a path that transmits information between the various components of the device (eg, the processor 1010, the memory 1020, the input / output interface 1030, and the communication interface 1040).

[0159] It should be noted that, although the above device only shows the processor 1010, the memory 1020, the input / output interface 1030, the communication interface 1040 and the bus 1050, in the specific implementation process, the device may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the above device may also only include the components necessary for implementing the embodiments of the present specification, and does not necessarily include all the components shown in the figure.

[0160] The electronic device of the above-mentioned embodiment is used to implement the corresponding remaining cruising range determination method in any of the above-mentioned embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0161] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the method for determining the remaining cruising range as described in any of the above embodiments.

[0162] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0163] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the method for determining the remaining cruising range as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0164] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides a vehicle, including the electronic device or the device for determining the remaining cruising range of the above-mentioned embodiments, and the method for determining the remaining cruising range as described in any of the above-mentioned embodiments is executed through the electronic device or the device for determining the remaining cruising range of the above-mentioned embodiments, and has the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0165] It is understandable that before using the technical solutions of each embodiment of the present disclosure, the type, scope of use, usage scenarios, etc. of the personal information involved will be informed to the user in an appropriate manner, and the user's authorization will be obtained.

[0166] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly remind the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can independently choose whether to provide personal information to software or hardware such as an electronic device, application, server, or storage medium that performs the operation of the technical solution of the present disclosure according to the prompt message.

[0167] As an optional but non-limiting implementation, in response to receiving the user's active request, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0168] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0169] A person skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application is limited to these examples. In line with the concept of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0170] In addition, to simplify the description and discussion, and in order not to make the embodiments of the present application difficult to understand, the known power supply / ground connection with the integrated circuit (IC) chip and other components may or may not be shown in the provided drawings. In addition, the device can be shown in the form of a block diagram to avoid making the embodiments of the present application difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform to be implemented in the embodiments of the present application (that is, these details should be fully within the scope of understanding of those skilled in the art). In the case of elaborating specific details (e.g., circuits) to describe exemplary embodiments of the present application, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details or when these specific details are changed. Therefore, these descriptions should be considered to be illustrative rather than restrictive.

[0171] Although the present application has been described in conjunction with specific embodiments of the present application, many replacements, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

[0172] The embodiments of the present application are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the present application. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included in the protection scope of the present application.

Claims

1. A method for determining remaining cruising range, characterized in that: include: Collecting vehicle operating parameters according to a preset first sampling interval, and determining the operating condition proportion of each driving condition according to the vehicle operating parameters and a preset power consumption statistical table; Collecting the vehicle power consumption parameters according to a preset second sampling interval, and determining the average energy consumption within the historical mileage according to the operating condition proportion and the vehicle power consumption parameters; wherein the first collection interval is greater than the second collection interval; The remaining cruising range is determined and displayed based on the current remaining battery power and the average energy consumption.

2. The method for determining the remaining cruising range according to claim 1, characterized in that: Determining the proportion of each driving condition according to the vehicle operating parameters and a preset power consumption statistics table includes: Determining a target statistical parameter corresponding to the vehicle operation parameter in the power consumption statistical table, and performing a cumulative counting on the target statistical parameter; Determining statistical parameters of each driving condition in the power consumption statistical table, and determining the sum of all statistical parameters as the statistical total; The ratio of each of the statistical parameters to the statistical total is respectively determined as the operating condition proportion of the corresponding driving condition.

3. The method for determining the remaining cruising range according to claim 2, characterized in that: The vehicle operation parameters include monitoring vehicle speed, monitoring torque and battery power consumption; and determining the target statistical parameters corresponding to the vehicle operation parameters in the power consumption statistical table includes: Determining, in the power consumption statistical table, a target vehicle speed interval item corresponding to the monitored vehicle speed and a target torque interval item corresponding to the monitored torque; In the power consumption statistics table, determining a parameter selection range according to the target torque interval item and the target vehicle speed interval item, and determining a target power interval item corresponding to the battery consumption power in the parameter selection range; The statistical parameter corresponding to the target power interval item in the parameter selection range is determined as the target statistical parameter.

4. The method for determining the remaining cruising range according to claim 3, characterized in that: The battery power consumption includes low voltage power consumption and high voltage power consumption; and determining a target power interval item corresponding to the battery power consumption in the parameter selection range includes: Determining a target low-voltage interval item corresponding to the low-voltage power consumption and a target high-voltage interval item corresponding to the high-voltage power consumption in the parameter selection range; The search item corresponding to the target high-pressure interval item and the target low-pressure interval item in the parameter selection range is determined as the target power interval item.

5. The method for determining the remaining cruising range according to claim 1, characterized in that: The determining the average energy consumption within the historical mileage according to the operating condition proportion and the vehicle power consumption parameter includes: Determine the total energy consumption within the historical mileage according to the vehicle power consumption parameter and the operating condition ratio; The ratio of the total energy consumption to the historical mileage is determined as the average energy consumption.

6. The method for determining the remaining cruising range according to claim 5, characterized in that: The vehicle power consumption parameters include battery current and battery voltage; the total energy consumption within the historical mileage is determined according to the vehicle power consumption parameters and the operating condition proportion, including: Performing a time-based integral calculation on the product of the battery current and the battery voltage to obtain a battery calculated energy consumption; Determine the target operating condition ratio corresponding to the battery calculated energy consumption, and perform weighted average calculation on the battery calculated energy consumption and the corresponding target operating condition ratio to obtain a weighted average energy consumption; Determine the number of collected samples according to the historical mileage and the second collection interval; The product of the weighted average energy consumption and the number of collected samples is determined as the total energy consumption.

7. The method for determining the remaining cruising range according to claim 6, characterized in that: The determining of the target operating condition ratio corresponding to the calculated energy consumption of the battery includes: Determining a target power ratio interval including the battery calculation energy consumption from a plurality of preset power ratio intervals; The operating condition proportion corresponding to the target proportion power interval is determined as the target operating condition proportion.

8. The method for determining the remaining cruising range according to claim 6, characterized in that: The determining the number of collected samples according to the historical mileage and the second collection interval includes: Determine the driving time for the historical mileage; The ratio of the driving duration to the second collection interval is determined as the number of collected samples.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 8 is implemented.

10. A vehicle, characterized in that: Comprising the electronic device as claimed in claim 9.

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