Method and device for determining remaining endurance of shared vehicle

Abstract

The invention provides a method and device for determining the remaining endurance of a shared vehicle, and relates to the technical field of shared vehicle operation, and the method comprises the steps: obtaining historical endurance data corresponding to a battery bound on the shared vehicle, and determining the reference endurance mileage of the battery based on the historical endurance data; determining an environment correction coefficient according to the current vehicle use environment of the shared vehicle, and determining a battery health degree satisfied by the battery based on the life cycle data of the battery; correcting the reference endurance mileage based on the environment correction coefficient and the battery health degree to obtain an actual endurance mileage; and determining the remaining endurance mileage according to the actual endurance mileage. According to the method and device for determining the remaining endurance of the shared vehicle, the vehicle use environment and the battery health degree are fully considered, the corrected actual endurance mileage and the corrected remaining endurance mileage are more accurate, the situation of midway power failure caused by inconsistent endurance calculation is avoided, and the use experience of a user is improved.

Description

Technical Field

[0001] This invention relates to the technical field of shared vehicle operation, and in particular to a method and apparatus for determining the remaining range of a shared vehicle. Background Technology

[0002] In the operation of shared vehicles, accurately calculating the remaining driving range is a core requirement for ensuring user travel experience and optimizing operators' battery swapping scheduling strategies. However, traditional range calculation methods often rely on inherent battery parameters, neglecting the impact of environmental variables such as temperature and humidity on battery performance. This can easily lead to inflated range estimates. Furthermore, traditional range calculations often ignore user behavior, failing to reflect actual battery energy consumption. Additionally, batch variations in batteries can result in inconsistent range calculation results. These issues often lead to low battery swapping scheduling efficiency for shared vehicle operators. For example, low-range batteries may be mistakenly assigned to high-frequency demand areas, and the calculated battery range may not reflect actual power consumption, causing power outages mid-trip and ultimately impacting the user experience. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to provide a method and apparatus for determining the remaining range of a shared vehicle, so as to alleviate the above-mentioned technical problems.

[0004] In a first aspect, embodiments of the present invention provide a method for determining the remaining range of a shared vehicle. The method includes: acquiring historical range data corresponding to a battery bound to the shared vehicle; determining a baseline range of the battery based on the historical range data; determining an environmental correction coefficient based on the current usage environment of the shared vehicle; and determining a battery health level satisfied by the battery based on the battery's lifecycle data; correcting the baseline range based on the environmental correction coefficient and the battery health level to obtain the actual range corresponding to the battery; and determining the remaining range of the shared vehicle based on the actual range.

[0005] In conjunction with the first aspect, the present invention provides a first possible implementation of the first aspect, wherein the method further includes: in response to the battery being installed in the shared vehicle, extracting the battery's identification code and the battery's feature data; establishing an association between the identification code and the vehicle identification code of the shared vehicle, and recording the time information corresponding to the association; receiving dynamic data uploaded by the shared vehicle, and storing the association, the dynamic data, the battery's feature data, and the actual driving range corresponding to the battery in a pre-configured dynamic database.

[0006] In conjunction with the first possible implementation of the first aspect, this embodiment of the invention provides a second possible implementation of the first aspect, wherein the step of obtaining the historical range data corresponding to the battery bound to the shared vehicle includes: extracting the identification code of the battery bound to the shared vehicle; using the identification code as an index to search for the historical range data of a preset number of shared vehicles most recently bound to the battery in the dynamic database, and determining the weight parameter of the shared vehicle according to the order in which the shared vehicle and the battery are bound.

[0007] In conjunction with the second possible implementation of the first aspect, this embodiment of the invention provides a third possible implementation of the first aspect, wherein the step of determining the baseline driving range of the battery based on the historical driving range data includes: calculating the single-vehicle driving range of each shared vehicle bound to the battery based on the historical driving range data; and superimposing the single-vehicle driving range of each shared vehicle according to the weighting parameter to obtain the baseline driving range of the battery.

[0008] In conjunction with the first aspect, this embodiment of the invention provides a fourth possible implementation of the first aspect, wherein the aforementioned environmental correction coefficient includes a temperature correction coefficient and a road condition correction coefficient; the step of determining the environmental correction coefficient based on the current usage environment of the shared vehicle includes: determining the temperature correction coefficient based on the current temperature parameters of the battery; determining the basic road condition coefficient of the shared vehicle based on the road condition information currently being driven by the shared vehicle; and determining the behavior coefficient of the shared vehicle based on the driving state of the shared vehicle; and determining the road condition correction coefficient based on the basic road condition coefficient and the behavior coefficient.

[0009] In conjunction with the first aspect, this embodiment of the invention provides a fifth possible implementation of the first aspect, wherein the battery lifecycle data includes the number of charge-discharge cycles and the cumulative usage time characterizing the battery; the step of determining the battery health level satisfied by the battery based on the battery lifecycle data includes: determining the battery health level of the battery according to a pre-configured degradation model based on the number of cycles and the cumulative usage time.

[0010] In conjunction with the first possible implementation of the first aspect, this embodiment of the invention provides a sixth possible implementation of the first aspect, wherein the step of receiving the dynamic data uploaded by the shared vehicle includes: receiving dynamic data uploaded by the shared vehicle at preset frequencies; wherein the preset frequencies include a first frequency, a second frequency, and a third frequency; the first frequency, the second frequency, and the third frequency decrease sequentially; the dynamic data includes: real-time dynamic data uploaded by the shared vehicle at the first frequency, statistical data uploaded by the shared vehicle at the second frequency, historical data uploaded by the shared vehicle at the third frequency, and road condition types traversed by the shared vehicle based on road condition tags.

[0011] In conjunction with the first possible implementation of the first aspect, this embodiment of the invention provides a seventh possible implementation of the first aspect, wherein the above method further includes: in response to a disassembly operation performed on the battery, decoupling the association between the battery's identification code and the vehicle identification code of the shared vehicle; recording the time information corresponding to the disassembly operation; and uploading the battery's feature data and the time information corresponding to the disassembly operation to the dynamic database.

[0012] In conjunction with the first aspect, this invention provides an eighth possible implementation of the first aspect, wherein the method further includes: calculating the actual driving range of the shared vehicles within the operational fence to obtain a battery list of the shared vehicles within the operational fence, wherein the battery list displays the actual driving range of each battery in a preset order; responding to a query operation for the battery list by displaying the battery list through a graphical user interface of the operational terminal; and responding to a scheduling operation for the battery by matching the scheduling demand area of ​​each battery based on the actual driving range of each battery, so as to perform battery swapping scheduling based on the scheduling demand area.

[0013] Secondly, embodiments of the present invention also provide a device for determining the remaining range of a shared vehicle. The device includes: an acquisition module, configured to acquire historical range data corresponding to a battery bound to the shared vehicle, and determine a baseline range of the battery based on the historical range data; a determination module, configured to determine an environmental correction coefficient based on the current usage environment of the shared vehicle, and determine the battery health level satisfied by the battery based on the battery's life cycle data; a correction module, configured to correct the baseline range based on the environmental correction coefficient and the battery health level to obtain the actual range corresponding to the battery; and a calculation module, configured to determine the remaining range of the shared vehicle based on the actual range.

[0014] The embodiments of the present invention bring the following beneficial effects: The method and apparatus for determining the remaining range of a shared vehicle provided in this invention can acquire historical range data corresponding to the battery bound to the shared vehicle, determine the baseline range of the battery based on the historical range data, determine an environmental correction coefficient based on the current usage environment of the shared vehicle, and determine the battery health level required by the battery based on the battery's life cycle data; correct the baseline range based on the environmental correction coefficient and battery health level to obtain the actual range corresponding to the battery; and determine the remaining range of the shared vehicle based on the actual range. In the correction process, the usage environment and battery health are fully considered, making the corrected actual range closer to the actual situation, thus making the remaining range more accurate and avoiding power outages due to inaccurate range calculations, thereby improving the user experience.

[0015] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained in accordance with the structures particularly pointed out in the description, claims and drawings.

[0016] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0017] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating a method for determining the remaining range of a shared vehicle, provided as an embodiment of the present invention; Figure 2 A flowchart illustrating another method for determining the remaining range of a shared vehicle, provided in an embodiment of the present invention; Figure 3 A schematic diagram of a device for determining the remaining range of a shared vehicle provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Current traditional methods for calculating battery life have multiple shortcomings and are difficult to adapt to the dynamic characteristics of shared scenarios. Specific problems are as follows: (1) Data silo problem: It usually relies on the fixed battery parameters of a single vehicle, such as the year of manufacture, nominal capacity, voltage, and remaining SOC, for static conversion. It cannot meet the core needs of cross-vehicle battery access in the shared vehicle operation scenario. That is, after the same battery is replaced to different vehicles, the traditional algorithm cannot trace its historical range performance, resulting in a large deviation between the calculation results and the actual range. (2) Lack of environmental factors: Traditional range calculation methods do not take into account the impact of environmental variables such as temperature and humidity on battery performance. However, the batteries of shared vehicles are characterized by lithium batteries having a capacity decay of up to 30% in low-temperature environments (such as -10℃) and a decrease in discharge efficiency in high-temperature and high-humidity environments. Since traditional calculation methods ignore environmental factors, it is easy to lead to problems such as overestimating the range, which in turn leads to a sudden drop in battery power during the user's use of the vehicle, causing user dissatisfaction. (3) User behavior and road condition deviation: Traditional range calculation usually does not take into account the user's riding behavior, such as the user's riding habits of shared bicycles, including frequent rapid acceleration and deceleration. In addition, it does not take into account the differences in road conditions, such as the dynamic impact of uphill sections and congested urban sections on energy consumption. The power consumption per unit mileage of the same battery can vary by 20%-40% under different users and different road conditions. Therefore, traditional range calculation methods are difficult to reflect the actual energy consumption. (4) Insufficient adaptation to differences in battery batches: When shared vehicles are frequently operated, they usually face the situation of frequently replacing batteries of different batches and different health conditions. Traditional range calculation algorithms usually cannot take into account the relationship between battery performance and vehicle model, resulting in poor consistency of range calculation results when the same vehicle is equipped with different batches of batteries. Furthermore, it is difficult for shared vehicle operators to formulate a unified scheduling strategy based on range data.

[0021] The aforementioned problems often lead to low battery swapping and dispatch efficiency for shared vehicle operators. For example, low-range batteries may be mistakenly allocated to high-frequency demand areas, and when the battery range does not match the actual situation, the shared vehicle may lose power midway, thus affecting the user's experience of using the shared vehicle.

[0022] Based on this, the present invention provides a method and apparatus for determining the remaining range of shared vehicles, so as to improve the accuracy of the calculation of the remaining range of shared vehicles and thus alleviate the above-mentioned technical problems.

[0023] To facilitate understanding of this embodiment, a method for determining the remaining range of a shared vehicle disclosed in this embodiment of the invention will first be described in detail.

[0024] In one possible implementation, this invention provides a method for determining the remaining range of a shared vehicle. This method can be applied to a backend server for shared vehicle operation or to a user terminal. Users install the corresponding application (APP) for the shared vehicle on their terminal, register as legitimate users through the APP, and then log in to the backend server to use the shared vehicle. Furthermore, the shared vehicles in this invention include shared electric bicycles, shared cars, and other shared vehicles that require battery power. Specifically, such as… Figure 1 The flowchart shown illustrates a method for determining the remaining range of a shared vehicle, which includes the following steps: Step S102: Obtain the historical range data corresponding to the battery bound to the shared vehicle, and determine the base range of the battery based on the historical range data. In this embodiment of the invention, the reference driving range refers to the reference driving range after the battery is fully charged. In order to make the battery's driving range calculation more accurate, the above-mentioned reference driving range is determined based on the battery's historical driving range data, rather than based on the battery's inherent parameters, so that the calculated driving range is more consistent with the actual driving range.

[0025] Step S104: Determine the environmental correction coefficient based on the current usage environment of the shared vehicle, and determine the battery health level required by the battery based on the battery life cycle data. Step S106: Correct the baseline driving range based on the environmental correction coefficient and battery health to obtain the actual driving range corresponding to the battery. Step S108: Determine the remaining range of the shared vehicle based on the actual range.

[0026] In practical use, in this embodiment of the invention, in addition to considering the battery's historical range data, environmental and road condition information are also fully considered to obtain the corresponding correction coefficient. At the same time, combined with the battery health, the corrected actual range is more in line with the actual situation.

[0027] Furthermore, the actual driving range mentioned above also represents the actual driving range after the battery is fully charged. In actual use, the actual driving range can be calculated once each time the battery is fully charged, and the mileage of the shared vehicle after this charge is recorded. The remaining driving range in step S108 above can be obtained by subtracting the mileage of the shared vehicle recorded at this time from the most recently calculated actual driving range.

[0028] In addition, the load of the shared vehicle can be detected by sensors. For example, when the load exceeds a preset load threshold, the remaining driving range can be appropriately reduced. The specific reduction in the remaining driving range can be set according to the load. For example, a correspondence between the load and the correction amount of the remaining driving range can be established under laboratory conditions. Then, the correction amount corresponding to the detected actual load can be determined according to the correspondence. Finally, the correction amount is subtracted from the remaining driving range obtained in step S108 above, which can further correct the remaining driving range.

[0029] Once the corresponding application (APP) is installed on the user's terminal, the user can use the shared vehicle. At this time, the remaining range can be displayed on the user's terminal's graphical user interface. It can also provide range reminders based on the current road conditions. For example, the user terminal's graphical user interface may display "The current dynamic range of remaining range is 51-62km" and "The current road is a gentle slope, with an estimated range of 56km." This not only reminds the user of the current remaining range but also allows the user to assess whether the shared vehicle meets their travel needs based on the current road conditions, which helps to improve the interactivity of the shared vehicle and the user's travel experience.

[0030] In practical use, in order to accurately calculate the remaining range of shared vehicles, this embodiment of the invention can achieve full-dimensional data collection and association. Specifically, each battery can be equipped with a non-volatile storage chip, such as a BMS (Battery Management System) module with RFID (Radio Frequency Identification) function, or a battery tag with a built-in QR code, etc., which can be used to store the battery's unique identification code (BID), initial parameters, such as the rated capacity C0, rated voltage U0, production date and other characteristic data at the time of manufacture, as well as the battery's life cycle data (number of charge and discharge cycles N, cumulative calendar days used D), etc.

[0031] Taking the method for determining the remaining range of a shared vehicle as shown in this embodiment of the invention as an example, when a battery is installed in a shared vehicle, the backend server can respond. Specifically, it can respond to the battery installation in the shared vehicle, then extract the battery's identification code (BID) and its characteristic data, such as the rated capacity C0, rated voltage U0, and production date at the time of manufacture, establish an association between the identification code and the vehicle identification code of the shared vehicle, and record the time information corresponding to this association. For example, the vehicle terminal of the shared vehicle reads the battery's identification code BID through RFID or barcode scanning, and automatically associates it with the vehicle identification code VID of the shared vehicle, records the timestamp T_bind of the battery installation in the shared vehicle, and establishes a "BID-VID-T_bind" association, which can realize cross-vehicle traceability of the battery. This association can be maintained in the backend server. Furthermore, the backend server can also receive dynamic data uploaded by the shared vehicle, and associate and store the above association, dynamic data, battery characteristic data, and the actual range of the battery, etc., in a pre-configured dynamic database to realize full-dimensional data acquisition and association between the battery and the shared vehicle.

[0032] Furthermore, when the battery is scheduled for swapping, the system can also respond to the battery removal operation and decouple the battery's identification code from the shared vehicle's identification code. For example, after the battery is removed from the old shared vehicle, the old shared vehicle's terminal can upload the "unbinding timestamp T_unbind" and "unbinding SOC_unbind" to the server. When the battery is reinstalled in a new shared vehicle, the new shared vehicle's terminal can automatically retrieve the latest historical data of the battery from the backend server after reading the BID (such as the base driving range L_base, battery health SOH, temperature correction coefficient, and road condition correction coefficients K_T and K_R), without re-initializing, thus achieving the effect of "battery swapping is instant adaptation".

[0033] Furthermore, shared vehicles can be equipped with corresponding environmental sensors and status sensors. Combined with the battery's BMS module, dynamic data collection and uploading can be achieved. Specifically, when the backend server receives dynamic data uploaded by shared vehicles, it can receive dynamic data uploaded by shared vehicles at preset frequencies. The preset frequencies include a first frequency, a second frequency, and a third frequency, with the first, second, and third frequencies decreasing sequentially. The dynamic data includes: real-time dynamic data uploaded by shared vehicles at the first frequency, statistical data uploaded by shared vehicles at the second frequency, historical data uploaded by shared vehicles at the third frequency, and road condition types marked by road condition tags.

[0034] In actual use, the real-time dynamic data uploaded by the shared vehicles at the first frequency, also known as high-frequency dynamic data, can be pre-configured to be uploaded once every 1 minute. The real-time dynamic data usually includes the real-time battery temperature T (°C), real-time voltage U (V), real-time current I (A), remaining power SOC (%), vehicle real-time speed v (km / h), and acceleration a (m / s²). The uploaded vehicle real-time speed v and acceleration a are usually used to determine whether the shared vehicle has a sudden acceleration / deceleration behavior in order to determine the driving status of the shared vehicle.

[0035] Furthermore, the statistical data uploaded by the shared vehicles at the second frequency can also be called mid-frequency statistical data. For example, the second frequency can be configured to upload once every 5 minutes. In this case, the statistical data can include the average speed v_avg, average acceleration a_avg, cumulative mileage ΔL (km), and cumulative power consumption ΔSOC (%) within 5 minutes. Furthermore, the historical data uploaded by the shared vehicles at the third frequency is also called low-frequency historical data. For example, the third frequency can be configured to upload the historical data of the previous day once for each natural day. For example, the current data is summarized and uploaded as historical data at 24:00 every day. In this case, the historical data can include the total riding mileage L_day (km) of the battery in the current shared vehicle, the total power consumption ΔSOC_day (%), the highest / lowest temperature T_max / T_min of the day, the number of rapid accelerations / decelerations of the day (a>0.5m / s² or a<-0.5m / s² is counted as 1 time), etc.

[0036] Furthermore, the aforementioned road condition types marked by road condition tags are typically a process of associating and tagging road condition data. Specifically, the backend server can combine real-time location data of shared vehicles (such as location data obtained from GPS, Beidou, and other positioning technologies) with road condition tags in the electronic map, such as "uphill section," "flat section," and "congested section." Then, it can tag each road section with a road condition type, such as L1=5km corresponding to "uphill section," L2=8km corresponding to "flat section," and so on. It can also calculate the power consumption per unit mileage under different road conditions, such as 1.2% / km for uphill sections and 0.8% / km for flat sections. This data can be stored as the road condition types traveled by shared vehicles to facilitate subsequent adjustments to the baseline driving range.

[0037] Furthermore, the dynamic data in the aforementioned dynamic database can serve as a data foundation and provide historical battery range data. Specifically, for ease of understanding, in Figure 1 On this basis, Figure 2A flowchart illustrating another method for determining the remaining range of a shared vehicle is provided, further explaining the baseline range and the process for correcting that range. Specifically, as... Figure 2 As shown, it includes the following steps: Step S202: Extract the identification code of the battery bound to the shared vehicle; Step S204: Using the identification code as an index, search the historical range data of a preset number of shared vehicles that are most recently bound to the battery in the dynamic database, and determine the weight parameters of the shared vehicles according to the order in which the shared vehicles are bound to the battery. Step S206: Calculate the single-vehicle range of each shared vehicle bound to the battery based on historical range data; Step S208: The single-vehicle range of each shared vehicle is calculated by superimposing the weight parameters to obtain the base range of the battery. Specifically, since the dynamic data in the dynamic database includes real-time dynamic data uploaded by shared vehicles at a first frequency, statistical data uploaded by shared vehicles at a second frequency, historical data uploaded by shared vehicles at a third frequency, and road condition types marked by road condition tags, the above steps S204 to S208 are actually processes of calling historical data and real-time data to determine the battery's baseline driving range.

[0038] Specifically, the benchmark driving range represents the driving range performance of the shared vehicles historically bound to the battery. Typically, the preset number of shared vehicles most recently bound to the battery can be selected based on experience, specifically three vehicles. For example, in step S204, the historical driving range data of the three shared vehicles most recently bound to the battery is used as an example. If there are fewer than three, all shared vehicles bound to the battery are selected. The historical driving range data searched here includes the driving range data of the three shared vehicles most recently bound to the battery, including the actual driving range of each shared vehicle in the historical calculation process. For example, the historical driving range data of the three shared vehicles includes: the historical driving range data L1 (km) and weight parameter w1 for vehicle 1, the historical driving range data L2 (km) and weight parameter w2 for vehicle 2, and the historical driving range data L3 (km) and weight parameter w3 for vehicle 3.

[0039] Furthermore, the single-vehicle range in step S206 above is calculated based on the total mileage and total power consumption of the battery on the i-th shared vehicle, as well as the remaining power of the battery. Specifically, the single-vehicle range is represented by Li (i=1,2,3), and the corresponding calculation formula can be expressed as: Li = (L_day_i / ΔSOC_day_i) ×SOC; Where L_day_i is the total daily mileage of the battery on the i-th shared vehicle, ΔSOC_day_i is the corresponding total daily power consumption, and SOC represents the current remaining power of the battery.

[0040] Furthermore, the weight parameter wi is set according to the principle of "the closer the binding time, the higher the weight". For example, the weight of the most recently bound vehicle is w1=0.5, the second most recent is w2=0.3, and the furthest is w3=0.2, and w1+w2+w3=1. Therefore, the above-mentioned baseline driving range is expressed as L_base = L1×w1+ L2×w2+ L3×w3.

[0041] For example, for a battery with BID=123, the historical range data of the three most recently linked shared vehicles is as follows: Vehicle 1: L_day1=80km, ΔSOC_day1=20%; Vehicle 2: L_day2=60km, ΔSOC_day2=15%; Vehicle 3: L_day3=40km, ΔSOC_day3=10% If the current battery's remaining SOC is 50%, then the single-vehicle range of the first shared vehicle is: L1 = (80 / 20) × 50 = 200 km, the single-vehicle range of the second shared vehicle is: L2 = (60 / 15) × 50 = 200 km, and the single-vehicle range of the third shared vehicle is: L3 = (40 / 10) × 50 = 200 km. The corresponding baseline driving range is expressed as follows: L_base=200×0.5 + 200×0.3 + 200×0.2=200km.

[0042] Furthermore, in this embodiment of the invention, the environmental correction factor used when correcting the baseline driving range includes a temperature correction factor and a road condition correction factor; the process of steps S210 to S214 is the process of determining the temperature correction factor and the road condition correction factor.

[0043] Step S210: Determine the temperature correction coefficient based on the current temperature parameters of the battery; In practical use, this temperature correction factor can adapt to the impact of temperature on battery life. Specifically, the real-time temperature of the battery can be collected by a temperature sensor as the current temperature parameter of the battery. Then, the temperature range to which the current temperature parameter belongs can be determined, and the parameter corresponding to this temperature range can be determined as the temperature correction factor. That is, the temperature range and the corresponding temperature correction factor can usually be determined based on the characteristics of the battery's discharge efficiency.

[0044] For example, the following shows several temperature ranges and their corresponding temperature correction factors, where the temperature correction factor is represented by K_T, and the current temperature parameter of the battery is represented by T: a1. When T∈[25℃,35℃], which is the optimal temperature range for battery operation: at this time, K_T=1.0, that is, no correction; a2. When T∈[10℃,25℃) or T∈(35℃,45℃], K_T=0.9, indicating that the battery discharge efficiency decreases slightly at this time; a3. When T∈[0℃,10℃) or T∈(45℃,50℃], K_T=0.7, indicating that the battery discharge efficiency decreases moderately at this time; a4. When T∈[-15℃,0℃), K_T=0.5, the battery discharge efficiency decreases significantly, such as a 50% capacity decay at -10℃; a5. When T < -15℃ or T > 50℃: K_T = 0.3, the battery discharge efficiency is severely reduced, and its use is restricted.

[0045] Step S212: Determine the basic road condition coefficient of the shared vehicle based on the road condition information currently being used by the shared vehicle; and, Step S214: Determine the behavior coefficient of the shared vehicle based on its driving status, and determine the road condition correction coefficient based on the road condition base coefficient and the behavior coefficient. In practice, after determining the temperature correction coefficient, the road condition correction coefficient is further determined. Specifically, as can be seen from the above steps S212 and S214, the road condition correction coefficient is determined by the road condition base coefficient and the behavior coefficient.

[0046] Specifically, in this embodiment of the invention, the basic road condition coefficient is represented by K_R1, which is determined by the road condition information of the shared vehicle currently traveling. For example, K_R1=1.0 for flat road sections, K_R1=0.8 for gentle slope sections, and K_R1=0.6 for steep slope sections. The behavior coefficient is represented by K_R2. For example, if the number of rapid accelerations and decelerations is less than 5 times / hour, the corresponding K_R2=1.0; if the number of rapid accelerations and decelerations is 5-10 times / hour, the corresponding K_R2=0.9; and if the number of rapid accelerations and decelerations is greater than 10 times / hour, the corresponding K_R2=0.8. The road condition information of the shared vehicle currently traveling can be obtained from the electronic map, and the number of rapid accelerations and decelerations used to determine the behavior coefficient can be obtained from the aforementioned high-frequency dynamic data.

[0047] Furthermore, based on the aforementioned basic road condition coefficients and behavioral coefficients, the final determined road condition correction coefficient is expressed as: K_R = K_R1 × K_R2. For example, if the current road segment is a "gentle slope segment", K_R1 = 0.8, and the user's number of rapid accelerations and decelerations is 8 times / hour, the corresponding K_R2 = 0.9. Then, the road condition correction coefficient K_R is expressed as: K_R = 0.8 × 0.9 = 0.72.

[0048] Furthermore, after determining the road condition correction coefficient, the battery health is further determined based on the following step S216. In this embodiment of the invention, the battery health is determined based on the battery's lifecycle data. Specifically, the battery's lifecycle data includes the number of charge-discharge cycles and the cumulative usage time. Therefore, in step S216, the battery health is determined based on the number of cycles and the cumulative usage time according to a pre-configured degradation model.

[0049] Step S216: Determine the battery health based on the number of cycles and cumulative usage time according to a pre-configured degradation model; In practice, battery health is represented by SOH (State of Health), which reflects the degree of battery aging. Furthermore, in this embodiment of the invention, battery health is determined based on the number of cycles and cumulative usage time, according to a pre-configured degradation model.

[0050] Specifically, the formula for calculating battery health, or the expression for the degradation model, is: SOH = 1 - (N × 0.001 + D × 0.00005), where 0.001 is the health degradation coefficient after each cycle, and 0.00005 is the degradation coefficient for daily calendar aging. The value is based on the common aging curve in the lithium battery industry and can be fine-tuned according to the characteristics of battery batches. For example, if a battery has a cycle count of N=200 times and a cumulative usage period of D=365 days, then SOH=1 - (200×0.001 + 365×0.00005)=1 - (0.2 + 0.01825)=0.78175 (i.e. 78.18%).

[0051] Specifically, after obtaining the above-mentioned environmental correction coefficient and battery health, the baseline driving range is further corrected. The specific correction process includes the following steps.

[0052] Step S218: Correct the baseline driving range based on the environmental correction coefficient and battery health to obtain the actual driving range corresponding to the battery. Step S220: Determine the remaining range of the shared vehicle based on the actual range.

[0053] In specific implementation, L_actual represents the actual driving range. The correction process for the actual driving range is expressed as: L_actual = L_base × K_T × K_R × SOH, where L_base is the base driving range, K_T and K_R represent the temperature correction coefficient and the road condition correction coefficient, respectively, and SOH is the battery health. That is, in this embodiment of the invention, the actual driving range is the base driving range multiplied by the temperature correction coefficient, the road condition correction coefficient, and the battery health in the environmental correction coefficient to obtain the corrected range.

[0054] For example, continuing with the data from the previous example, L_base=200km, T= -10℃ (K_T=0.5), K_R=0.72, SOH=0.78175, then the actual driving range is expressed as: L_actual=200×0.5×0.72×0.78175≈56.29km. At the same time, it can also output the dynamic range (±10% error), that is, "51-62km".

[0055] Furthermore, the actual driving range, dynamic driving range range, and battery health information obtained above can be synchronized to the corresponding operator management platform on the backend server. The battery list can be displayed in descending order of actual driving range to support operators in quickly selecting high-endurance batteries.

[0056] Specifically, in this embodiment of the invention, the actual driving range of shared vehicles within the operational fence can be statistically analyzed to obtain a battery list of shared vehicles within the operational fence. This battery list displays the actual driving range of each battery in a preset order; for example, the battery list can be displayed in descending order of actual driving range. Then, in response to a query operation on the battery list, the battery list is displayed through the graphical user interface of the operational terminal. Furthermore, in response to a scheduling operation on the batteries, based on the actual driving range of each battery, the scheduling demand area for each battery is matched to perform battery swapping scheduling based on the scheduling demand area.

[0057] In actual use, the battery swapping dispatch system is based on the battery's range data and can automatically match batteries. For example, high-range batteries (actual range L_actual > 60km) are allocated to high-frequency usage areas (such as business districts and subway stations), while low-range batteries (actual range L_actual < 20km) are allocated to areas near battery swapping stations, reducing ineffective transportation costs.

[0058] Furthermore, for the aforementioned dynamic database, based on the real-time dynamic data uploaded by shared vehicles at the first frequency, historical range data can be updated regularly every day. For example, at 24:00 every day, the backend server automatically updates the historical range data of each battery, that is, adds L_day and ΔSOC_day for the current shared vehicle on that day, and recalculates the baseline range L_base. At the same time, at 24:00 every Sunday, the segmented threshold of the temperature correction coefficient K_T and the base value of the road condition correction coefficient K_R1 can be fine-tuned based on the temperature parameters and road condition information of the week to ensure that the actual range and remaining range are adapted to seasonal changes and road condition updates.

[0059] In summary, the method for determining the remaining range of shared vehicles provided in this embodiment of the invention has the following beneficial effects: (1) Significantly improved measurement accuracy: For example, based on the actual test data of shared electric bicycle companies, in a low temperature environment of -10℃, the traditional algorithm has a range error of ±35%, while the method for determining the remaining range of shared vehicles provided in this embodiment of the invention can reduce the error to ±12%; on flat road sections at normal temperature (25℃), the error is further reduced to ±8%, effectively avoiding user complaints of "the estimated range does not match the actual range"; (2) Significant optimization of operational efficiency: Through the scheduling strategy of "matching high-endurance batteries with high-frequency demand areas", the battery utilization rate has increased by 28%. For example, the number of rides with high-endurance batteries has increased in the same period of time. At the same time, accurate range calculation reduces the situation of "misjudging low range and needing to swap batteries", the frequency of battery swapping has decreased by 19%, and the operator's battery swapping costs (labor, transportation) have been reduced accordingly. (3) Improved user experience and trust: The user terminal can transparently display the "dynamic range" and "road condition adapted range", which improves the accuracy of users' range expectations by 60% and reduces the complaint rate of "power outage due to insufficient range" by 41%. At the same time, clear range prompts help users plan their trips reasonably, and the rental rate increases by 15% (users choose to continue riding because "the range meets the needs"). (4) Enhanced battery lifecycle management capabilities: Based on battery health SOH data, operators can identify aging batteries (SOH < 60%) in advance and arrange for their retirement, avoiding operational risks caused by unstable battery life due to aging batteries; at the same time, by analyzing the SOH decay curves of different batches of batteries, they can select battery suppliers with stronger durability and reduce long-term procurement costs. (5) Strong scene adaptability and scalability: The method for determining the remaining range of shared vehicles provided in this embodiment of the invention can support the periodic fine-tuning of temperature segment thresholds and road condition coefficients, and can adapt to seasonal changes in different regions (such as low temperatures in winter in the north and high temperatures in summer in the south) and road condition updates (such as marking of newly built road sections); in addition, it can be extended to access environmental parameters such as "precipitation probability" and "wind speed" to further improve the calculation accuracy in complex environments.

[0060] Furthermore, based on the above embodiments, this invention also provides a device for determining the remaining range of a shared vehicle, such as... Figure 3 The diagram shows a structural schematic of a device for determining the remaining range of a shared vehicle. The device includes: The acquisition module 30 is used to acquire the historical range data corresponding to the battery bound to the shared vehicle, and determine the base range of the battery based on the historical range data. The determining module 32 is used to determine an environmental correction coefficient based on the current usage environment of the shared vehicle, and to determine the battery health level required by the battery based on the battery's life cycle data. Correction module 34 is used to correct the benchmark driving range based on the environmental correction coefficient and the battery health to obtain the actual driving range corresponding to the battery. The calculation module 36 is used to determine the remaining driving range of the shared vehicle based on the actual driving range.

[0061] The device for determining the remaining range of a shared vehicle provided in this embodiment of the invention has the same technical features as the method for determining the remaining range of a shared vehicle provided in the above embodiments, so it can also solve the same technical problems and achieve the same technical effects.

[0062] Furthermore, embodiments of the present invention also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above method.

[0063] This invention also provides a computer-readable storage medium storing a computer program, which, when executed by a processor, performs the steps of the above-described method.

[0064] Furthermore, embodiments of the present invention also provide a schematic diagram of the structure of an electronic device, such as... Figure 4 The diagram shows the structure of the electronic device, which includes a processor 41 and a memory 40. The memory 40 stores computer-executable instructions that can be executed by the processor 41, and the processor 41 executes the computer-executable instructions to implement the above-described method.

[0065] exist Figure 4 In the illustrated embodiment, the electronic device further includes a bus 42 and a communication interface 43, wherein the processor 41, the communication interface 43, and the memory 40 are connected via the bus 42.

[0066] The memory 40 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 43 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc. The bus 42 may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc. The bus 42 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0067] Processor 41 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 41 or by software instructions. Processor 41 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of this invention can be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in the memory, and the processor 41 reads the information in the memory and uses its hardware to complete the aforementioned method.

[0068] The computer program product of the method and apparatus for determining the remaining range of a shared vehicle provided in the embodiments of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the preceding method embodiments. For specific implementation, please refer to the method embodiments, which will not be repeated here.

[0069] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0070] Furthermore, in the description of the embodiments of the present invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in the present invention based on the specific circumstances.

[0071] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion 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 described in 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, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0072] In the description of this invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0073] Finally, it should be noted that the above embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for determining the remaining range of a shared vehicle, characterized in that, The method includes: Obtain historical range data corresponding to the battery bound to the shared vehicle, and determine the base range of the battery based on the historical range data; An environmental correction coefficient is determined based on the current usage environment of the shared vehicle, and the battery health level is determined based on the battery's life cycle data. The baseline driving range is corrected based on the environmental correction factor and the battery health to obtain the actual driving range corresponding to the battery. The remaining range of the shared vehicle is determined based on the actual driving range.

2. The method according to claim 1, characterized in that, The method further includes: In response to the battery being installed in the shared vehicle, the identification code of the battery and the characteristic data of the battery are extracted; Establish an association between the identification code and the vehicle identification code of the shared vehicle, and record the time information corresponding to the association; The system receives dynamic data uploaded by the shared vehicle and stores the association relationship, the dynamic data, the battery feature data, and the actual driving range corresponding to the battery in a pre-configured dynamic database.

3. The method according to claim 2, characterized in that, The steps to obtain historical range data corresponding to the batteries bound to shared vehicles include: Extract the identification code of the battery bound to the shared vehicle; Using the identification code as an index, the historical range data of a preset number of shared vehicles most recently bound to the battery are searched in the dynamic database, and the weight parameters of the shared vehicles are determined according to the order in which the shared vehicles are bound to the battery.

4. The method according to claim 3, characterized in that, The step of determining the baseline driving range of the battery based on the historical driving range data includes: The single-vehicle range of each of the shared vehicles bound to the battery is calculated based on the historical range data. The single-vehicle range of each of the shared vehicles is calculated by superimposing the weight parameters to obtain the base range of the battery.

5. The method according to claim 1, characterized in that, The environmental correction factor includes a temperature correction factor and a road condition correction factor; The step of determining the environmental correction factor based on the current usage environment of the shared vehicle includes: The temperature correction coefficient is determined based on the current temperature parameters of the battery; The road condition base coefficient of the shared vehicle is determined based on the road condition information currently being traveled by the shared vehicle, and the behavior coefficient of the shared vehicle is determined based on the driving status of the shared vehicle; the road condition correction coefficient is determined based on the road condition base coefficient and the behavior coefficient.

6. The method according to claim 1, characterized in that, The battery's lifecycle data includes the number of charge-discharge cycles and the cumulative usage time, which characterize the battery. The step of determining the battery health level met by the battery based on the battery's life cycle data includes: Based on the number of cycles and the cumulative usage time, the battery health is determined according to a pre-configured degradation model.

7. The method according to claim 2, characterized in that, The steps for receiving the dynamic data uploaded by the shared vehicle include: The system receives dynamic data uploaded by the shared vehicles at preset frequencies; wherein the preset frequencies include a first frequency, a second frequency, and a third frequency; the first frequency, the second frequency, and the third frequency decrease sequentially. The dynamic data includes: real-time dynamic data uploaded by the shared vehicles at the first frequency, statistical data uploaded by the shared vehicles at the second frequency, historical data uploaded by the shared vehicles at the third frequency, and road condition types marked by road condition tags.

8. The method according to claim 2, characterized in that, The method further includes: In response to a disassembly operation performed on the battery, the association between the battery's identification code and the vehicle identification code of the shared vehicle is severed; Record the time information corresponding to the disassembly operation, and upload the battery feature data and the time information corresponding to the disassembly operation to the dynamic database.

9. The method according to claim 1, characterized in that, The method further includes: The actual driving range of the shared vehicles within the operational fence is statistically analyzed to obtain a battery list of the shared vehicles within the operational fence. The battery list displays the actual driving range of each battery in a preset sorting order. In response to a query operation targeting the battery list, the battery list is displayed via the graphical user interface of the operating terminal; and, In response to the scheduling operation for the battery, based on the actual driving range of each battery, the scheduling demand area of ​​each battery is matched, so as to perform battery swapping scheduling based on the scheduling demand area.

10. A device for determining the remaining range of a shared vehicle, characterized in that, The device includes: The acquisition module is used to acquire the historical range data corresponding to the battery bound to the shared vehicle, and determine the base range of the battery based on the historical range data. The determination module is used to determine an environmental correction coefficient based on the current usage environment of the shared vehicle, and to determine the battery health level required by the battery based on the battery's life cycle data. The correction module is used to correct the baseline driving range based on the environmental correction coefficient and the battery health to obtain the actual driving range corresponding to the battery. The calculation module is used to determine the remaining driving range of the shared vehicle based on the actual driving range.

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