Method and device for predicting remaining mileage of vehicle, vehicle, medium and product

Abstract

The embodiment of the invention provides a remaining mileage prediction method and device of a vehicle, the vehicle, a medium and a product. The method comprises the steps that when the current vehicle speed of a vehicle is smaller than a preset vehicle speed, a first ECR of the vehicle between the starting moment and the current moment of a current discharging period is calculated; and then, fusing the first ECR and a preset ECR to obtain a second ECR. And predicting the remaining mileage of the vehicle according to the second ECR and the remaining capacity of the battery. Wherein the preset ECR is determined in advance according to historical driving data of the vehicle. The method is used for achieving the technical effect of improving the prediction precision of the remaining mileage.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of vehicles, in particular to a residual mileage prediction method and device of a vehicle, a vehicle, a medium and a product. BACKGROUND

[0002] With the transformation of the global transportation field towards sustainable development, electric trucks have gradually become an important alternative option for traditional diesel-powered trucks due to their low emissions and low operating costs.

[0003] In actual applications, accurate prediction of the cruising range (also known as residual mileage) is the core support for the large-scale application of electric trucks and the efficient operation of the freight network. Currently, the residual energy of the battery is calculated by collecting real-time data such as the state of charge (SOC) and actual capacity of the power battery from the battery management system (BMS). Then, the value obtained by dividing the calculated residual energy by the predefined energy consumption rate (ECR) is determined as the predicted residual mileage.

[0004] However, the prior art has the technical problem of low prediction accuracy of the residual mileage. SUMMARY

[0005] The embodiments of the present application provide a residual mileage prediction method and device of a vehicle, a vehicle, a medium and a product, to achieve the technical effect of improving the prediction accuracy of the residual mileage of the vehicle.

[0006] In a first aspect, the embodiments of the present application provide a residual mileage prediction method of a vehicle, comprising:

[0007] When the current speed of the vehicle is less than a preset speed, calculating a first ECR of the vehicle between the start time of the current discharge period and the current time;

[0008] Fusing the first ECR and a preset ECR to obtain a second ECR, wherein the preset ECR is determined in advance according to historical driving data of the vehicle;

[0009] According to the second ECR and the battery residual capacity, predicting the residual mileage of the vehicle.

[0010] In the technical solution, by calculating the first ECR from the start of the current discharge period to the current time when the current vehicle speed is less than the preset vehicle speed, the interference of kinetic energy change of acceleration or deceleration on energy consumption data is avoided to ensure that the first ECR can truly reflect the real-time energy consumption of the current discharge period. Then, the preset ECR determined based on historical driving data is fused based on the first ECR to balance the real-time and long-term stable energy consumption characteristics. Finally, the second ECR and the remaining capacity of the battery are used to calculate the range, solving the problem of insufficient accuracy of a single ECR and significantly improving the accuracy of the remaining range prediction, which can provide a reliable basis for route planning and charging for the driver.

[0011] In a possible implementation, the fusing the first ECR and the preset ECR to obtain a second ECR comprises:

[0012] performing weighted summation on the first ECR and the preset ECR to obtain the second ECR.

[0013] The weight of the preset ECR decreases in the current discharge period, and the weight of the first ECR increases in the current discharge period.

[0014] In the technical solution, the second ECR determined can adapt to the requirements of different stages of the current discharge period: in the initial stage when the data for determining the first ECR is insufficient, the preset ECR determined based on historical driving data is used to ensure reliability; in the later stage, the weight of the first ECR is increased with the accumulation of driving data, so that the second ECR calculated is adapted to the current working condition. By dynamically adjusting the weight, the limitation of fixed weight is avoided, and the accuracy of the second ECR is further improved to provide a more suitable energy consumption basis for the remaining range prediction.

[0015] In a possible implementation, the calculating the first ECR from the start of the current discharge period to the current time of the vehicle when the current vehicle speed is less than the preset vehicle speed comprises:

[0016] When the current vehicle speed of the vehicle is less than the preset vehicle speed and the time length from the last time the first ECR is calculated is greater than a first preset time length, the first ECR from the start of the current discharge period to the current time of the vehicle is calculated.

[0017] In the technical solution, on the basis that the current vehicle speed of the vehicle is less than the preset vehicle speed, the condition that the time length from the last time the first ECR is calculated is greater than a first preset time length is added to avoid the case that the first ECR is frequently calculated in a congested road section, thereby effectively saving the computing resources of the vehicle.

[0018] In a possible implementation, the method further comprises:

[0019] when a time duration from a last time of calculating the first ECR is greater than a second preset time duration, or when a driving distance of the vehicle after the last time of calculating the first ECR is greater than a preset distance, calculating the first ECR of the vehicle between a starting time of a current discharge period and a current time;

[0020] wherein the second preset time duration is greater than the first preset time duration.

[0021] In the technical solution, it is considered that the vehicle may continuously drive in a certain speed range without being less than a preset speed in a highway scene or other scenes. Since the first ECR is used to calculate the final second ECR, in order to ensure the accuracy of the first ECR, the second preset time duration and the preset distance can be preset, so that the first ECR is updated in time when the time duration from the last time of calculating the first ECR is greater than the second preset time duration, or when the driving distance of the vehicle after the last time of calculating the first ECR is greater than the preset distance, so as to ensure the accuracy of the second ECR generated subsequently, and further ensure the precision of the remaining mileage predicted based on the second ECR.

[0022] In a possible implementation, before the first ECR and the preset ECR are fused to obtain the second ECR, the method further includes:

[0023] determining an ECR of each historical discharge period according to historical driving data of the vehicle;

[0024] determining the preset ECR according to the ECR of each historical discharge period.

[0025] In the technical solution, the ECR of each historical discharge period is used to calculate the preset ECR with the historical discharge period as a unit, and the preset ECR is used as a fusion reference. In actual application, the discharge period is also used as a unit, so the reliability of the preset ECR as the fusion reference is ensured.

[0026] In a possible implementation, the determining of the ECR of each historical discharge period according to the historical driving data of the vehicle includes:

[0027] for each historical discharge period, determining energy consumption of each trip contained in the historical discharge period according to the historical driving data of the vehicle;

[0028] accumulating the energy consumption of each trip contained in the historical discharge period to obtain total energy consumption of the historical discharge period;

[0029] dividing the total energy consumption of the historical discharge period by a value obtained by dividing a historical distance of the vehicle in the historical discharge period by the historical distance of the vehicle in the historical discharge period to determine the ECR of the historical discharge period.

[0030] In this technical solution, by refining each historical discharge cycle into two stages, namely the travel stage and the non-travel stage, only the cumulative energy consumption of the travel stage is determined as the effective energy consumption of the historical discharge cycle. This avoids the influence of random energy consumption in the non-travel stage on the final calculated preset ECR, thereby improving the accuracy of the predicted ECR calculation.

[0031] In one possible implementation, determining the preset ECR based on the ECR of each historical discharge cycle includes:

[0032] The average value of the ECR of all historical discharge cycles is determined as the preset ECR;

[0033] Alternatively, the median value of the ECR of all historical discharge cycles can be determined as the preset ECR;

[0034] Alternatively, the preset ECR can be obtained by processing the ECR of all historical discharge cycles using IQR;

[0035] Alternatively, the preset ECR can be obtained by processing the ECR of all historical discharge cycles using the pruning mean method.

[0036] This technical solution ensures that outliers do not affect the preset ECR, thus guaranteeing the accuracy of the preset ECR.

[0037] In one possible implementation, before determining the ECR for each historical discharge cycle based on the vehicle's historical driving data, the method includes:

[0038] The historical discharge cycle of the vehicle is determined based on the historical battery state and / or historical SOC in the vehicle's historical driving data;

[0039] Based on the historical vehicle speed from the vehicle's historical driving data, the historical mileage is determined within each historical discharge cycle.

[0040] In this technical solution, historical discharge cycles and historical mileage are accurately segmented from historical driving data by using parameters such as historical battery status, historical SOC, and historical vehicle speed, laying the foundation for subsequent calculation of preset ECR.

[0041] In one possible implementation, predicting the vehicle's remaining range based on the second ECR and the remaining battery capacity includes:

[0042] The remaining range of the vehicle is determined by dividing the remaining battery capacity by the second ECR.

[0043] Secondly, embodiments of this application provide a vehicle remaining mileage prediction device, comprising:

[0044] The calculation module is used to calculate the first ECR of the vehicle between the start time of the current discharge cycle and the current time when the current vehicle speed is less than the preset vehicle speed;

[0045] A fusion module is used to fuse the first ECR and a preset ECR to obtain a second ECR; wherein the preset ECR is determined in advance based on the vehicle's historical driving data;

[0046] A prediction module is used to predict the remaining range of the vehicle based on the second ECR and the remaining battery capacity.

[0047] In one possible implementation, the fusion module is specifically used for:

[0048] The second ECR is obtained by weighted summation of the first ECR and the preset ECR.

[0049] The weight of the preset ECR decreases during the current discharge cycle, while the weight of the first ECR increases during the current discharge cycle.

[0050] In one possible implementation, the computing module is specifically used for:

[0051] When the current speed of the vehicle is less than the preset speed, and the time elapsed since the last calculation of the first ECR is greater than the first preset time elapsed, the first ECR of the vehicle between the start time of the current discharge cycle and the current time is calculated.

[0052] In one possible implementation, the computing module is further configured to:

[0053] If the time elapsed since the last calculation of the first ECR is greater than a second preset time elapsed, or if the distance traveled by the vehicle after the last calculation of the first ECR is greater than a preset distance, calculate the first ECR of the vehicle between the start time of the current discharge cycle and the current time.

[0054] Wherein, the second preset duration is longer than the first preset duration.

[0055] In one possible implementation, the vehicle's remaining mileage prediction device further includes a determination module. Before fusing the first ECR and a preset ECR to obtain a second ECR, the determination module is used to:

[0056] Based on the vehicle's historical driving data, determine the ECR for each historical discharge cycle;

[0057] The preset ECR is determined based on the ECR of each historical discharge cycle.

[0058] In one possible implementation, the determining module is specifically used for:

[0059] For each historical discharge cycle, the energy consumption of each trip included in the historical discharge cycle is determined based on the vehicle's historical driving data;

[0060] The energy consumption of each stroke included in the historical discharge cycle is summed to obtain the total energy consumption of the historical discharge cycle.

[0061] The total energy consumption of the historical discharge cycle is divided by the historical distance traveled by the vehicle during the historical discharge cycle, and the result is determined as the ECR of the historical discharge cycle.

[0062] In one possible implementation, the determining module is specifically used for:

[0063] The average value of the ECR of all historical discharge cycles is determined as the preset ECR;

[0064] Alternatively, the median value of the ECR of all historical discharge cycles can be determined as the preset ECR;

[0065] Alternatively, the preset ECR can be obtained by processing the ECR of all historical discharge cycles using IQR;

[0066] Alternatively, the preset ECR can be obtained by processing the ECR of all historical discharge cycles using the pruning mean method.

[0067] In one possible implementation, before determining the ECR for each historical discharge cycle based on the vehicle's historical driving data, the determining module is further configured to:

[0068] The historical discharge cycle of the vehicle is determined based on the historical battery state and / or historical SOC in the vehicle's historical driving data;

[0069] Based on the historical vehicle speed from the vehicle's historical driving data, the historical mileage is determined within each historical discharge cycle.

[0070] In one possible implementation, the prediction module is specifically used for:

[0071] The remaining range of the vehicle is determined by dividing the remaining battery capacity by the second ECR.

[0072] Thirdly, embodiments of this application provide a vehicle, including: a vehicle body, a memory, and a processor;

[0073] The memory stores computer-executed instructions;

[0074] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect or various possible implementations of the first aspect as described above.

[0075] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect or various possible implementations of the first aspect.

[0076] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect or various possible implementations of the first aspect.

[0077] The vehicle remaining range prediction method, device, vehicle, medium, and product provided in this application calculate the first ECR (Energy Recovery Rate) from the start of the current discharge cycle to the present when the vehicle's current speed is less than a preset speed. This avoids interference from kinetic energy changes during acceleration or deceleration on energy consumption data, ensuring that the first ECR accurately reflects the real-time energy consumption of the current discharge cycle. Then, a preset ECR determined based on historical driving data is integrated with the first ECR to balance real-time and long-term stable energy consumption characteristics. Finally, a second ECR and the remaining battery capacity are used to calculate the mileage, solving the problem of insufficient accuracy of a single ECR and significantly improving the accuracy of remaining range prediction. This provides a reliable basis for drivers to plan routes and charge their vehicles. Attached Figure Description

[0078] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0079] Figure 1 Flowchart of the vehicle remaining mileage prediction method provided in this application Figure 1 ;

[0080] Figure 2 This is a schematic diagram illustrating the definition of discharge cycle and stroke provided in the embodiments of this application;

[0081] Figure 3 A schematic diagram illustrating the functions of the weights of the preset ECR and the weights of the first ECR provided in the embodiments of this application;

[0082] Figure 4 A distribution chart of SOC consumption rate over 100 historical discharge cycles provided for embodiments of this application;

[0083] Figure 5 Flowchart of the vehicle remaining mileage prediction method provided in this application Figure 2 ;

[0084] Figure 6 A schematic diagram illustrating a scenario for the vehicle remaining mileage prediction method provided in this application;

[0085] Figure 7 A schematic diagram of the remaining mileage prediction device for the vehicle provided in this application;

[0086] Figure 8 A structural schematic diagram of the vehicle provided in this application.

[0087] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0088] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0089] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with relevant laws, regulations and standards, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0090] First, the application scenarios involved in this application will be explained:

[0091] As the global transportation sector transitions towards sustainable development, green transportation solutions centered on electrification have become a key direction for replacing traditional fossil fuel power. Electric trucks, with their advantages of low emissions and low operating costs, are gradually becoming an important alternative to traditional diesel-powered trucks.

[0092] Among them, electric heavy-duty trucks (eHDTs), as the core carrier of electrification in the freight sector, have completed value verification in various application scenarios, and have performed particularly well in short- and medium-distance scenarios. Specifically, short- and medium-distance scenarios mainly refer to transportation scenarios that serve intra-city delivery (such as port to urban warehouses, cargo transfer between urban business districts) and inter-regional distribution (such as transportation between logistics hubs in adjacent cities), with mileage ranges mostly concentrated between 100 and 300 kilometers.

[0093] In practical applications, accurate prediction of eHDT remaining mileage is the core support for its large-scale application and efficient operation of the freight network.

[0094] For fleet operations, range prediction determines the maximum driving range of an eHDT vehicle on a single charge. This forms the basis for operators to plan transportation routes and avoid mid-journey stoppages due to insufficient range. Simultaneously, based on the prediction results, charging station stops can be scheduled in advance to prevent vehicles from breaking down due to depleted battery power. Furthermore, accurate range prediction can also be used to estimate transportation time, providing precise data for delivery times and improving the reliability of customer service.

[0095] Furthermore, for drivers, accurate prediction of driving range can effectively alleviate their concerns about running out of power midway, avoid choosing conservative routes due to anxiety (such as detouring through unnecessary charging stations), and further ensure transportation efficiency.

[0096] As can be seen from the above, accurate range prediction is crucial for optimizing fleet operations and ensuring efficient transportation.

[0097] Currently, range prediction mainly involves collecting data such as the battery's SOC and actual capacity from the BMS in real time to calculate the battery's current remaining energy. Then, the calculated remaining energy is divided by a predefined ECR (Electronic Capacity Ratio) to determine the predicted remaining range.

[0098] Predefined ECRs typically involve conducting energy consumption tests under standardized scenarios to obtain the vehicle's average energy consumption rate under ideal operating conditions. For example, heavy-duty commercial vehicles (such as eHDT) can refer to the World Harmonized Transient Cycle (WHTC), while light-duty vehicles (such as passenger cars) can refer to the New European Driving Cycle (NEDC) or the World Harmonized Light Vehicles Test Cycle (WLTC), etc.

[0099] However, fluctuations in vehicle load conditions are ignored in existing technologies. Specifically, as a freight vehicle, the eHDT frequently switches between heavily loaded (fully loaded with goods) and empty (no goods on the return trip) states in actual operation. These load differences affect the motor's output power, leading to fluctuations in energy consumption. Furthermore, the predefined ECR is based on standardized load (such as half-load) testing and cannot adapt to actual load variations.

[0100] In other words, the calculation methods of existing technologies are divorced from the actual driving conditions of vehicles, resulting in low accuracy of the predicted remaining mileage.

[0101] Based on this, the technical concept of this application is as follows: During the research of the eHDT remaining mileage prediction scheme, the inventors discovered that although vehicle load significantly affects mileage consumption in real-world scenarios, each discharge cycle contains multiple alternating fully loaded and unloaded trips. The load differences of these alternating trips cancel each other out, resulting in a high degree of similarity and stability in the ECR of each discharge cycle. Simultaneously, due to the continuous nature of vehicle driving, the ECR at future times also exhibits strong consistency with the ECR at past times within the same discharge cycle. Therefore, the inventors conceived of using historical eHDT driving data to first calculate the average ECR (i.e., the preset ECR) corresponding to each historical discharge cycle, and then fusing it with the average ECR within the current discharge cycle of the vehicle (i.e., the first ECR), thereby effectively improving the accuracy of the final ECR (i.e., the second ECR), and thus enhancing the prediction accuracy of the remaining mileage.

[0102] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0103] Figure 1 Flowchart of the vehicle remaining mileage prediction method provided in this application Figure 1 ,like Figure 1 As shown, the method includes:

[0104] S11. When the vehicle's current speed is less than the preset speed, calculate the first ECR of the vehicle between the start time of the current discharge cycle and the current time.

[0105] In this step, it is considered that at higher vehicle speeds, significant kinetic energy changes due to acceleration and deceleration can cause fluctuations in energy consumption data. However, when the vehicle speed is lower than the preset speed (such as in parking or low-speed driving scenarios), the vehicle's kinetic energy changes more gradually, resulting in more stable energy consumption data. In this case, the driving data from the start of the current discharge cycle to the current moment can accurately reflect the actual energy consumption level within this cycle. Therefore, when it is determined that the vehicle's current speed is lower than the preset speed, i.e., when the kinetic energy change is gradual, the first ECR of the vehicle between the start of the current discharge cycle and the current moment can be calculated.

[0106] The preset vehicle speed, which corresponds to the vehicle speed when it is parked or traveling at low speed, can be preset based on experience or experimental values, such as 5km / h, 6km / h, or 7km / h. This application does not impose any specific restrictions on this.

[0107] A discharge cycle refers to the complete period from the completion of a single full charge of a vehicle's battery to the initiation of the next charging operation. A discharge cycle consists of multiple trips, which are continuous driving processes from a starting point to a destination.

[0108] In practical applications, the vehicle's discharge cycle and range can be determined based on the vehicle's driving data.

[0109] The vehicle's discharge cycle can be determined in the following two ways:

[0110] 1. Timing can begin when the vehicle is confirmed to be charging. After the third preset duration is reached, the current moment is determined as the start of the discharge cycle and timing stops. Subsequently, timing will begin again the next time the vehicle is confirmed to be charging, and after the third preset duration is reached, the current moment is determined as the end of the discharge cycle and timing stops.

[0111] To avoid repeatedly plugging and unplugging the charging gun during charging, a timer can be started once the vehicle is confirmed to be charging. After the timer reaches the third preset duration, it indicates that the vehicle is in a stable charging state, and this moment is considered the start of the discharge cycle.

[0112] It should be understood that if the charging status changes during the above timing process, the timing will stop.

[0113] The third preset duration can be preset based on empirical or experimental values, and this application does not impose specific restrictions on it.

[0114] 2. When the State of Charge (SOC) is determined to be greater than the preset SOC, the current time can be set as the start time of the discharge cycle. Subsequently, when the SOC is determined to be greater than the preset SOC again, the current time can be set as the end time of the discharge cycle.

[0115] When the State of Charge (SOC) is greater than the preset SOC, it indicates that the vehicle is currently charging, and therefore the current moment can be determined as the start of the discharge cycle. After charging ends, the SOC will gradually decrease until the next charging begins, at which point the SOC will gradually increase until it exceeds the preset SOC again, at which point the current moment can be determined as the end of the discharge cycle.

[0116] The preset SOC is the SOC of the vehicle when it is close to full charge. It can be preset based on empirical or experimental values. This application does not impose specific restrictions on it.

[0117] In addition to the two implementation methods described above, post-processing can be performed on the determined discharge cycle. That is, after determining the discharge cycle, the time interval between two discharge cycles can be calculated. If the time interval is less than a preset time interval, the two discharge cycles are merged to correct abnormal discharge cycles.

[0118] It should be understood that the time interval between two discharge cycles can be the time interval between the start times of the two discharge cycles or the time interval between the end times of the two discharge cycles.

[0119] Specifically, when the vehicle speed increases to the preset starting speed, the current time is determined as the start time of the trip. When the vehicle speed decreases to the preset stopping speed, the timing starts. After the timing reaches the fourth preset duration, the current time is determined as the end time of the trip.

[0120] It should be understood that during the above timing process, if the vehicle speed increases to exceed the preset stop speed, the timing will stop.

[0121] It should be understood that the preset starting speed is the speed used to determine the start of the journey, and is the minimum starting speed when the vehicle is in normal driving condition; the preset stopping speed is the speed used to determine the end of the journey, and is the speed at which the vehicle is about to stop in normal driving condition. The preset starting speed and preset stopping speed can be calculated based on experimental and empirical values, and this application embodiment does not impose specific limitations on them.

[0122] It should be understood that the fourth preset duration is the longest tolerable stop duration within the stroke, which can be calculated based on experimental and empirical values. This application embodiment does not impose specific limitations on this.

[0123] Among them, battery charging status, SOC, and vehicle speed are all considered driving data.

[0124] Next, through Figure 2 The concepts of discharge cycle and stroke will be explained more clearly.

[0125] Figure 2 This is a schematic diagram illustrating the definition of the discharge cycle and stroke provided in an embodiment of this application. Figure 2 As shown, the lower broken line represents the SOC change during vehicle operation. Based on the determination method described above, there is one discharge cycle. The upper broken line represents the vehicle speed change during vehicle operation. Based on the determination method described above, this discharge cycle consists of 5 strokes (stroke 1, stroke 2, stroke 3, stroke 4, and stroke 5).

[0126] Wherein, the first ECR is the average ECR of the vehicle from the start time of the current discharge cycle to the current time. Specifically, calculating the first ECR of the vehicle from the start time of the current discharge cycle to the current time can be implemented as follows:

[0127] The first ECR is determined by dividing the total energy consumption from the start of the current discharge cycle to the current time by the distance the vehicle travels from the start of the current discharge cycle to the current time.

[0128] In one possible implementation, in addition to the prerequisite that the current vehicle speed is less than a preset vehicle speed, an additional prerequisite is that the time elapsed since the last calculation of the first ECR is greater than a first preset time elapsed. That is, when the vehicle's current speed is less than the preset vehicle speed and the time elapsed since the last calculation of the first ECR is greater than the first preset time elapsed, the first ECR of the vehicle between the start time of the current discharge cycle and the current time is calculated.

[0129] For example, suppose the first ECR was calculated at time 1 and the current time is time 2, then "and the time since the last calculation of the first ECR" is the time between time 1 and time 2.

[0130] The first preset duration is the shortest time interval for calculating the first ECR, such as 1 minute, 2 minutes, 3 minutes, etc. It can be set according to the vehicle's computing resources and the accuracy requirements. This application embodiment does not impose specific restrictions on this.

[0131] Based on the vehicle's current speed being less than the preset speed, the condition that the time elapsed since the last calculation of the first ECR is greater than the first preset time is added to avoid frequent calculations of the first ECR in congested road sections, effectively saving the vehicle's computing resources.

[0132] Optionally, if the time elapsed since the last calculation of the first ECR is greater than a second preset time elapsed, or if the distance traveled by the vehicle after the last calculation of the first ECR is greater than a preset distance, the first ECR of the vehicle between the start time of the current discharge cycle and the current time is calculated.

[0133] The second preset duration is the longest tolerable duration for which the first ECR is not updated. It can be set according to the actual situation, such as 20 minutes, 25 minutes, 30 minutes, etc. This application embodiment does not impose specific restrictions on this.

[0134] The preset distance is the longest tolerable driving distance without updating the first ECR. It can be set according to the actual situation, such as 10 kilometers, 15 kilometers, 20 kilometers, etc. This application embodiment does not impose specific limitations on this.

[0135] In the above embodiments, considering highway scenarios or other scenarios, vehicles may continuously travel within a certain speed range, and the vehicle speed will not be less than a preset speed. Since the first ECR is used to calculate the final second ECR, in order to ensure the accuracy of the first ECR, a second preset duration and a preset distance can be preset so that the duration of the first ECR calculation is greater than the second preset duration, or, when the vehicle's travel distance after the last calculation of the first ECR is greater than the preset distance, the first ECR is updated in a timely manner to ensure the accuracy of the subsequently generated second ECR, thereby ensuring the accuracy of the remaining mileage predicted based on the second ECR.

[0136] S12. The first ECR and the preset ECR are fused to obtain the second ECR.

[0137] In this step, the preset ECR is determined in advance based on the vehicle's historical driving data, representing a stable energy consumption baseline. Therefore, the first ECR, dynamically calculated using short-term data, can be fused with the preset ECR, statically calculated using long-term data, thereby improving the accuracy of the fused second ECR.

[0138] It should be understood that the preset ECR calculation process will be... Figure 5 The embodiments shown are explained in detail, and will not be repeated here.

[0139] In one possible implementation, the first ECR and the preset ECR are weighted and summed to obtain the second ECR.

[0140] The second ECR can be calculated using the following formula:

[0141]

[0142] in, For the second ECR, For the first ECR, As the weight of the first ECR, To preset ECR, The weights for the preset ECR.

[0143] It should be understood that the weight of the first ECR and the weight of the preset ECR can be preset according to the actual situation, and the embodiments of this application do not impose specific restrictions on this.

[0144] In one possible implementation, the weight of the preset ECR decreases during the current discharge cycle, while the weight of the first ECR increases during the current discharge cycle.

[0145] The weights of the first ECR and the preset ECR can be calculated using the following formula:

[0146]

[0147]

[0148] in, This represents the distance the vehicle has traveled from the start of the current discharge cycle to the present moment. It is a constant parameter used to control the weights. and Follow The rate of change.

[0149] For example, in At that time, the weights of the preset ECR and the weights of the first ECR can be determined by... Figure 3 To express.

[0150] Figure 3 This is a schematic diagram illustrating the functions of the weights of the preset ECR and the weights of the first ECR provided in the embodiments of this application. Figure 3 As shown, at the beginning of a discharge cycle, the preset ECR is assigned a higher weight. This is because at the beginning of a discharge cycle, a sufficient amount of stable vehicle driving data has not yet been accumulated to accurately calculate the first ECR. In contrast, due to the larger amount of historical driving data, a more reliable ECR can be provided at the beginning of a discharge cycle. However, as the vehicle travels further, unpredictable factors such as traffic conditions, road types, and weather conditions have an increasingly significant impact on ECR prediction. Therefore, it is necessary to increase the weight of the first ECR calculated based on real-time driving data to obtain a second ECR that more accurately reflects the actual situation.

[0151] In other words, by decreasing the weight of the preset ECR within the current discharge cycle and increasing the weight of the first ECR within the current discharge cycle, the determined second ECR can be adapted to the needs of different stages of the current discharge cycle: initially, when the data used to determine the first ECR is insufficient, the preset ECR determined by historical driving data ensures reliability; later, as driving data accumulates, the weight of the first ECR is increased, making the calculated second ECR more consistent with the current operating conditions. By dynamically adjusting the weights, the limitations of fixed weights are avoided, further improving the accuracy of the second ECR and providing a more suitable energy consumption basis for remaining mileage prediction.

[0152] Furthermore, This can be understood as a fine-tuning knob to suit different scenarios. In highly variable environments requiring rapid adjustments, it can be... Set it to a smaller value. This will cause the weight of the first ECR to increase rapidly at the beginning of the discharge cycle, and then the rate of increase in the weight of the first ECR will slow down as distance accumulates. Conversely, in a more stable environment with less volatility, it can be set to a smaller value. Set to a larger value to allow for a smooth transition between the first ECR and the preset ECR dominating the second ECR calculation.

[0153] S13. Based on the second ECR and the remaining battery capacity, predict the vehicle's remaining range.

[0154] In this step, since the second ECR is the predicted ECR obtained through the above calculation, and the ECR and the remaining battery capacity are key parameters for calculating the remaining range, the remaining range of the vehicle can be predicted based on the second ECR and the remaining battery capacity.

[0155] The remaining battery capacity refers to the actual remaining charge of the vehicle's battery at the current moment.

[0156] In practical applications, the remaining battery capacity can be obtained directly through the BMS, or it can be calculated based on the battery's rated capacity and actual SOC. This application embodiment does not impose specific restrictions on the method of obtaining the remaining battery capacity.

[0157] In one possible implementation, the remaining battery capacity can be divided by the value obtained from the second ECR to determine the vehicle's remaining range.

[0158] This application provides a method for predicting the remaining range of a vehicle. When the vehicle's current speed is less than a preset speed, a first ECR (Electronic Range Response) is calculated from the start of the current discharge cycle to the current time. Then, the first ECR and the preset ECR are fused to obtain a second ECR. Finally, the remaining range of the vehicle is predicted based on the second ECR and the remaining battery capacity. The preset ECR is determined in advance based on the vehicle's historical driving data. In this technical solution, by calculating the first ECR from the start of the current discharge cycle when the vehicle's current speed is less than the preset speed, the interference of kinetic energy changes during acceleration or deceleration on energy consumption data is avoided, ensuring that the first ECR accurately reflects the real-time energy consumption of the current discharge cycle. Then, the preset ECR, determined based on historical driving data, is fused with the first ECR to balance real-time and long-term stable energy consumption characteristics. Finally, the second ECR and the remaining battery capacity are used to calculate the range, solving the problem of insufficient accuracy of a single ECR, significantly improving the accuracy of remaining range prediction, and providing a reliable basis for drivers to plan routes and charge their vehicles.

[0159] In practical applications, for eHDT, the varying load on each trip leads to significant differences in energy consumption for each journey. For example, during delivery trips, the vehicle is heavily loaded, resulting in a higher ECR; during return trips, the vehicle is unloaded, resulting in a lower ECR. Furthermore, considering mountainous conditions, the starting and ending points of a journey may have different altitudes, further amplifying the energy consumption differences between each trip. However, a complete work process typically starts and returns from the same location, usually consisting of several round trips, including several high-load delivery trips and several unloaded return trips. In this case, although vehicle load significantly impacts trip energy consumption, the load differences in these alternating full-load and unloaded trips cancel each other out because each discharge cycle includes multiple such trips. This results in a high degree of similarity and stability in the ECR of each discharge cycle. Additionally, in mountainous conditions, the alternating trips also offset the impact of altitude differences on the ECR.

[0160] Therefore, based on the above analysis, it can be concluded that even without... Figure 1 Other data besides the data required in the illustrated embodiment (such as vehicle weight, altitude, and route information) can also be used to calculate a high-precision preset ECR through historical driving data.

[0161] Figure 4 This is a distribution chart of SOC consumption rate over 100 historical discharge cycles provided for embodiments of this application. Figure 4 As shown, the SOC consumption rate over 100 historical discharge cycles follows a concentrated normal distribution, with the data clustered around the mean, exhibiting low dispersion and small error. Since the ECR is obtained by multiplying the SOC consumption rate by the actual battery capacity and then dividing by 100, the ECR over 100 historical discharge cycles also follows a concentrated normal distribution with small error.

[0162] Next, through Figure 5 The method for determining the preset ECR is explained.

[0163] Figure 5 Flowchart of the vehicle remaining mileage prediction method provided in this application Figure 2 ,like Figure 5 As shown, the method prior to S12 includes:

[0164] S51. Determine the vehicle's historical discharge cycle based on the vehicle's historical battery state and / or historical SOC from the vehicle's historical driving data.

[0165] It should be understood that the implementation method of this step is similar to the method of determining the discharge cycle in S11. The difference is that in S11, if the time interval between two discharge cycles is less than the preset time interval, the two discharge cycles are merged. However, in this step, in order to avoid the impact of abnormal discharge cycles on the preset ECR calculation, if the time interval between two historical discharge cycles is less than the preset time interval, the two historical discharge cycles are discarded.

[0166] S52. Based on the historical vehicle speed in the vehicle's historical driving data, determine the historical mileage within each historical discharge cycle.

[0167] The historical driving data can be driving data from the past month, the past two months, or the past three months, or driving data within a specific historical time period. It can be determined according to the actual situation, and this application embodiment does not impose specific restrictions on it.

[0168] It should be understood that the implementation of this step is similar to the way the route is determined in S11, and will not be described again here.

[0169] In addition to determining the historical trips by referring to the method of determining the trips in S11, the historical driving distance corresponding to each historical trip can also be calculated, and historical trips with historical driving distances less than the preset driving distance can be discarded to avoid the impact of abnormal trips on the preset ECR calculation.

[0170] It should be understood that the preset driving distance is the shortest driving distance for a normal trip, which can be preset based on experimental or empirical values, and will not be elaborated here.

[0171] S53. Determine the ECR for each historical discharge cycle based on the vehicle's historical driving data.

[0172] In one possible implementation, the total energy consumption for each historical discharge cycle can be calculated, and the total energy consumption for the historical discharge cycle can be divided by the historical distance traveled by the vehicle within the historical discharge cycle to determine the ECR of the historical discharge cycle.

[0173] In another possible implementation, for each historical discharge cycle, the energy consumption of each trip within that cycle is determined based on the vehicle's historical driving data. The energy consumption of each trip within the historical discharge cycle is then summed to obtain the total energy consumption for that cycle. Finally, the total energy consumption of the historical discharge cycle is divided by the historical distance traveled by the vehicle within that cycle to determine the ECR (Energy Consumption Rate) for that historical discharge cycle.

[0174] In this implementation, considering that eHDTs with special applications such as concrete mixer trucks and refrigerated trucks often consume additional energy due to their auxiliary equipment (such as heating, ventilation and air conditioning (HVAC) systems, power take-off (PTO) systems, and cargo refrigeration systems), this energy consumption frequently occurs during the non-driving phase of a discharge cycle. In other words, even when the vehicle is stationary (such as during loading and unloading in a yard), these auxiliary devices may continue to operate and consume battery energy. Since this energy consumption is random and unpredictable, it needs to be subtracted from the total energy consumption of historical discharge cycles to ensure the accuracy of the ECR calculation for historical discharge cycles.

[0175] By refining each historical discharge cycle into two stages, travel and non-travel, and determining only the cumulative energy consumption during the travel stage as the effective energy consumption of that historical discharge cycle, the influence of random energy consumption during the non-travel stage on the final calculated preset ECR is avoided, thus improving the accuracy of the predicted ECR calculation.

[0176] S54. Determine the preset ECR based on the ECR of each historical discharge cycle.

[0177] In one possible implementation, the average value of the ECR for all historical discharge cycles can be determined as the preset ECR.

[0178] In another possible implementation, the median of the ECR across all historical discharge cycles can be used as the preset ECR.

[0179] In another possible implementation, the ECR of all historical discharge cycles can be processed using the interquartile range (IQR) to obtain a preset ECR.

[0180] In another possible implementation, the ECR of all historical discharge cycles can be processed by the pruning mean method to obtain the preset ECR.

[0181] Calculating the preset ECR using the four methods described above ensures that outliers do not affect the preset ECR and guarantees its accuracy.

[0182] In the above embodiments, historical discharge cycles and historical trips are accurately segmented from historical driving data using parameters such as historical battery state, historical SOC, and historical vehicle speed, laying the foundation for subsequent calculation of the preset ECR. Furthermore, taking advantage of the small differences in ECR across each historical discharge cycle, the preset ECR is calculated using the historical discharge cycle as the unit. In practical applications, the discharge cycle is also used as the unit, thus ensuring the reliability of the preset ECR as a fusion benchmark.

[0183] The driving distance and energy consumption involved in any of the above embodiments can be obtained directly by relevant sensors, or calculated based on parameters such as vehicle speed and battery power. This application does not impose specific restrictions on the calculation method of driving distance and energy consumption.

[0184] It should be understood that the following will be through Figure 6 An example is provided to illustrate the application scenarios of the vehicle remaining mileage prediction method.

[0185] Figure 6 A schematic diagram illustrating a scenario for the vehicle remaining mileage prediction method provided in this application, such as... Figure 6 As shown, in this scenario, the upper broken line represents the vehicle's speed change within a discharge cycle, while the middle broken line represents the vehicle's cumulative energy consumption change within a discharge cycle. Since the kinetic energy change is more drastic at the beginning of a discharge cycle, the calculated remaining distance will fluctuate significantly. Therefore, after the vehicle has traveled a certain distance (e.g., 2 kilometers), the aforementioned method for predicting the vehicle's remaining mileage can be activated to predict the remaining distance. At this point, the kinetic energy change is stable, and sufficient driving data ensures the accuracy of the first ECR calculation. The dots in the cumulative energy consumption broken line represent the stopping point for calculating the first ECR; that is, the stopping point is the moment when the vehicle speed is less than the preset speed.

[0186] For stop time 1, the first ECR corresponding to stop time 1 is calculated. Then, the second ECR corresponding to stop time 1 is determined based on the preset ECR. Next, based on the second ECR corresponding to stop time 1 and the remaining battery capacity, the remaining distance corresponding to stop time 1 is calculated. Then, as the vehicle travels, the remaining distance of the vehicle is calculated in real time based on the second ECR corresponding to stop time 1 and the real-time remaining battery capacity, until stop time 2. Similarly, the second ECR corresponding to stop time 2 is calculated, and the remaining distance of the vehicle is subsequently calculated in real time based on the second ECR calculated at stop time 2.

[0187] Figure 7 A schematic diagram of the remaining mileage prediction device for the vehicle provided in this application is shown below. Figure 7 As shown, the vehicle remaining mileage prediction device 70 provided in this embodiment includes:

[0188] The calculation module 701 is used to calculate the first ECR of the vehicle between the start time of the current discharge cycle and the current time when the current vehicle speed is less than the preset vehicle speed.

[0189] The fusion module 702 is used to fuse the first ECR and the preset ECR to obtain the second ECR. The preset ECR is determined in advance based on the vehicle's historical driving data.

[0190] The prediction module 703 is used to predict the remaining range of the vehicle based on the second ECR and the remaining battery capacity.

[0191] In one possible implementation, the fusion module 702 is specifically used for:

[0192] The second ECR is obtained by weighted summation of the first ECR and the preset ECR.

[0193] The weight of the preset ECR decreases during the current discharge cycle, while the weight of the first ECR increases during the current discharge cycle.

[0194] In one possible implementation, the computing module 701 is specifically used for:

[0195] When the vehicle's current speed is less than the preset speed, and the time elapsed since the last calculation of the first ECR is greater than the first preset time elapsed, calculate the first ECR of the vehicle between the start time of the current discharge cycle and the current time.

[0196] In one possible implementation, the computing module 701 is further configured to:

[0197] If the time elapsed since the last calculation of the first ECR is greater than a second preset time elapsed, or if the distance traveled by the vehicle after the last calculation of the first ECR is greater than a preset distance, calculate the first ECR of the vehicle between the start time of the current discharge cycle and the current time.

[0198] The second preset duration is longer than the first preset duration.

[0199] In one possible implementation, the vehicle's remaining range prediction device 70 further includes a determination module. Before fusing the first ECR and a preset ECR to obtain the second ECR, the determination module is used to:

[0200] Based on the vehicle's historical driving data, the ECR for each historical discharge cycle is determined.

[0201] The preset ECR is determined based on the ECR of each historical discharge cycle.

[0202] In one possible implementation, the determining module is specifically used for:

[0203] For each historical discharge cycle, the energy consumption of each trip included in the historical discharge cycle is determined based on the vehicle's historical driving data.

[0204] The total energy consumption of the historical discharge cycle is obtained by summing up the energy consumption of each stroke included in the historical discharge cycle.

[0205] The total energy consumption of the historical discharge cycle is divided by the historical distance traveled by the vehicle within the historical discharge cycle, and the result is determined as the ECR of the historical discharge cycle.

[0206] In one possible implementation, the determining module is specifically used for:

[0207] The average value of the ECR of all historical discharge cycles is determined as the preset ECR.

[0208] Alternatively, the median value of the ECR for all historical discharge cycles can be determined as the preset ECR.

[0209] Alternatively, the ECR of all historical discharge cycles can be processed using IQR to obtain a preset ECR.

[0210] Alternatively, the ECR of all historical discharge cycles can be processed by pruning the mean to obtain the preset ECR.

[0211] In one possible implementation, before determining the ECR for each historical discharge cycle based on the vehicle's historical driving data, the determining module is further configured to:

[0212] The vehicle's historical discharge cycles are determined based on the vehicle's historical battery state and / or historical SOC from its historical driving data.

[0213] Based on the vehicle's historical speed from its historical driving data, the historical mileage is determined within each historical discharge cycle.

[0214] In one possible implementation, the prediction module 703 is specifically used for:

[0215] The remaining range of the vehicle is determined by dividing the remaining battery capacity by the second ECR.

[0216] The vehicle remaining mileage prediction device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0217] Figure 8 This is a structural diagram of the vehicle provided in this application. Figure 8As shown, the vehicle 80 provided in this embodiment includes: a vehicle body 801, at least one processor 802, and a memory 803. Optionally, the vehicle 80 also includes a communication component 804. The processor 802, memory 803, and communication component 804 are connected via a bus 805.

[0218] In a specific implementation, at least one processor 802 executes computer execution instructions stored in memory 803, causing at least one processor 802 to perform the above-described method.

[0219] The specific implementation process of processor 802 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0220] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0221] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0222] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0223] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0224] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0225] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random-Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0226] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an application-specific integrated circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0227] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0228] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0229] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0230] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0231] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0232] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for predicting the remaining mileage of a vehicle, characterized in that, include: When the vehicle's current speed is less than the preset speed, calculate the first energy consumption rate (ECR) of the vehicle from the start of the current discharge cycle to the current time. The first ECR and the preset ECR are fused to obtain the second ECR; wherein the preset ECR is determined in advance based on the vehicle's historical driving data; The remaining range of the vehicle is predicted based on the second ECR and the remaining battery capacity.

2. The method according to claim 1, characterized in that, The step of fusing the first ECR and the preset ECR to obtain the second ECR includes: The second ECR is obtained by weighted summation of the first ECR and the preset ECR. The weight of the preset ECR decreases during the current discharge cycle, while the weight of the first ECR increases during the current discharge cycle.

3. The method according to claim 1 or 2, characterized in that, When the vehicle's current speed is less than a preset speed, calculating the first ECR of the vehicle between the start time of the current discharge cycle and the current time includes: When the current speed of the vehicle is less than the preset speed, and the time elapsed since the last calculation of the first ECR is greater than the first preset time elapsed, the first ECR of the vehicle between the start time of the current discharge cycle and the current time is calculated.

4. The method according to claim 3, characterized in that, The method further includes: If the time elapsed since the last calculation of the first ECR is greater than a second preset time elapsed, or if the distance traveled by the vehicle after the last calculation of the first ECR is greater than a preset distance, calculate the first ECR of the vehicle between the start time of the current discharge cycle and the current time. Wherein, the second preset duration is longer than the first preset duration.

5. The method according to any one of claims 1, 2, or 4, characterized in that, Before fusing the first ECR and the preset ECR to obtain the second ECR, the method further includes: Based on the vehicle's historical driving data, determine the ECR for each historical discharge cycle; The preset ECR is determined based on the ECR of each historical discharge cycle.

6. The method according to claim 5, characterized in that, The step of determining the ECR for each historical discharge cycle based on the vehicle's historical driving data includes: For each historical discharge cycle, the energy consumption of each trip included in the historical discharge cycle is determined based on the vehicle's historical driving data; The energy consumption of each stroke included in the historical discharge cycle is summed to obtain the total energy consumption of the historical discharge cycle. The total energy consumption of the historical discharge cycle is divided by the historical distance traveled by the vehicle during the historical discharge cycle, and the result is determined as the ECR of the historical discharge cycle.

7. The method according to claim 5, characterized in that, The step of determining the preset ECR based on the ECR of each historical discharge cycle includes: The average value of the ECR of all historical discharge cycles is determined as the preset ECR; Alternatively, the median value of the ECR of all historical discharge cycles can be determined as the preset ECR; Alternatively, the preset ECR can be obtained by processing the ECR of all historical discharge cycles using the interquartile range (IQR). Alternatively, the preset ECR can be obtained by processing the ECR of all historical discharge cycles using the pruning mean method.

8. The method according to claim 5, characterized in that, Before determining the ECR for each historical discharge cycle based on the vehicle's historical driving data, the method includes: The historical discharge cycle of the vehicle is determined based on the historical battery state and / or historical state of charge (SOC) in the vehicle's historical driving data. Based on the historical vehicle speed from the vehicle's historical driving data, the historical mileage is determined within each historical discharge cycle.

9. The method according to any one of claims 1, 2, 4 or 6-8, characterized in that, The step of predicting the remaining range of the vehicle based on the second ECR and the remaining battery capacity includes: The remaining range of the vehicle is determined by dividing the remaining battery capacity by the second ECR.

10. A vehicle remaining mileage prediction device, characterized in that, include: The calculation module is used to calculate the first ECR of the vehicle between the start time of the current discharge cycle and the current time when the current vehicle speed is less than the preset vehicle speed; A fusion module is used to fuse the first ECR and a preset ECR to obtain a second ECR; wherein the preset ECR is determined in advance based on the vehicle's historical driving data; A prediction module is used to predict the remaining range of the vehicle based on the second ECR and the remaining battery capacity.

11. A vehicle, characterized in that, include: Vehicle body, memory, and processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-9.

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

13. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-9.

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