Power battery selection methods, devices, computer equipment, and storage media

Abstract

This application relates to a method, apparatus, computer equipment, and storage medium for selecting a power battery. The method includes: obtaining the minimum energy of the power battery under candidate material systems based on the operating conditions of the target vehicle; obtaining the actual energy of the power battery based on the minimum energy and a margin coefficient variable; the actual energy is represented by the margin coefficient variable; obtaining the total lifespan of the power battery based on the actual energy; obtaining the total lifespan cost of the target vehicle based on the total lifespan of the power battery; adjusting the margin coefficient value of the margin coefficient variable to minimize the total lifespan cost; using the margin coefficient value corresponding to the candidate material systems when the total lifespan cost is minimized; and selecting a power battery based on multiple candidate material systems and the corresponding margin coefficient for each candidate material system. This method enables accurate selection of power batteries.

Description

Technical Field

[0001] This application relates to the field of new energy technology, and in particular to a method, apparatus, computer equipment, storage medium and computer program product for selecting power batteries. Background Technology

[0002] Over the past decade, power batteries, especially lithium-ion power batteries, have been widely used in both passenger and commercial vehicles, with their market share steadily increasing. This phenomenon is largely attributed to subsidies received when electric vehicles were introduced to various markets as a new type of clean transportation. However, with the gradual withdrawal of these subsidies, some consumers are hesitant to purchase electric vehicles. These concerns include range anxiety, charging inconvenience, and uncertainty about the lifecycle cost (LCC) of electric vehicles. This concern is particularly pronounced among commercial vehicle owners who use electric vehicles as operational tools. Therefore, for electric vehicle developers, the selection of power batteries must not only meet the overall vehicle's power requirements but also comprehensively consider the optimal solution for the lifecycle cost of electric vehicles from the user's perspective.

[0003] Currently, the selection of power batteries is limited to whether the battery capacity can meet the power requirements of the drive motor and the driving range. In reality, the lifespan of an electric vehicle often far exceeds that of its power battery. The lifespan of the power battery significantly impacts the driving and maintenance costs of an electric vehicle, thus affecting the total lifecycle cost for the user. Therefore, the accuracy of current power battery selection methods is not high. Summary of the Invention

[0004] Therefore, it is necessary to provide a power battery selection method, device, computer equipment, computer-readable storage medium, and computer program product that can accurately select power batteries to address the above-mentioned technical problems.

[0005] Firstly, this application provides a method for selecting a power battery. The method includes:

[0006] Based on the operating conditions of the target vehicle, the minimum energy of the power battery under the alternative material system is obtained, and the actual energy of the power battery is obtained based on the minimum energy and the margin coefficient variable; the actual energy is represented by the margin coefficient variable.

[0007] Based on the actual energy, obtain the total lifespan of the power battery, and based on the total lifespan of the power battery, obtain the total lifespan cost of the target vehicle.

[0008] Adjust the margin coefficient value of the margin coefficient variable to minimize the total life cycle cost. Under the condition of minimizing the total life cycle cost, the corresponding margin coefficient value is used as the margin coefficient of the candidate material system.

[0009] The selection of power batteries is based on multiple alternative material systems and the margin coefficient corresponding to each alternative material system.

[0010] In one embodiment, based on the operating conditions of the target vehicle, the lowest energy of the power battery under the alternative material system is obtained, including:

[0011] Determine the initial mass of the power battery under the alternative material system, and determine the initial full-load mass of the target vehicle under the alternative material system based on the initial mass;

[0012] Based on the operating conditions and the initial full load weight of the vehicle, obtain the average drive power, maximum drive power, and additional power consumption of the vehicle's electronic systems.

[0013] Based on the average drive power and the maximum drive power, the rated power and peak power of the motor are obtained to determine the efficiency of the electric drive system.

[0014] Based on the target vehicle's driving range, average power consumption per kilometer under operating conditions, rated motor power, additional power consumption, and electric drive system efficiency, the minimum energy of the power battery under the alternative material system is obtained.

[0015] In one embodiment, the method further includes:

[0016] Determine the battery pack mass energy density of the power battery under the alternative material system;

[0017] Based on the actual energy and the energy density of the battery pack, obtain the actual mass of the power battery under the alternative material system;

[0018] Adjust the initial full-load weight of the vehicle based on the difference between the actual weight and the initial weight.

[0019] In one embodiment, the overall lifespan of the power battery is obtained based on the actual energy, including:

[0020] The rated discharge rate and peak discharge rate of the power battery are obtained based on the actual energy, electric drive system efficiency, motor rated power and motor peak power.

[0021] Based on the statistical data of user charging behavior, operating conditions and actual energy of the target vehicle in the target market, obtain the average charging rate, the maximum charging rate and the state-of-charge time curve of the power battery.

[0022] The cycle life of the power battery is obtained based on the rated discharge rate, peak discharge rate, average charge rate, maximum charge rate and state-of-charge time curves.

[0023] Obtain the ambient temperature-time curve of the target market, and obtain the temperature-time curve of the power battery based on the statistical data of operating conditions and user charging behavior;

[0024] The calendar life of the power battery is obtained based on the state-of-charge time curve and the temperature-time curve.

[0025] The overall lifespan of the power battery is obtained based on the cycle life and calendar life.

[0026] In one embodiment, the total lifecycle cost of the target vehicle is obtained based on the overall lifespan of the power battery, including:

[0027] Based on the actual energy, the purchase cost of the power battery is obtained, and the vehicle purchase cost of the target vehicle is determined based on the purchase cost of the power battery; the purchase cost of the power battery is a part of the vehicle purchase cost;

[0028] Based on the overall lifespan and purchase cost of the power battery, obtain the vehicle operating cost of the target vehicle;

[0029] The total lifecycle cost of the target vehicle is obtained based on the vehicle purchase cost and vehicle operating cost.

[0030] In one embodiment, the selection of a power battery is performed based on multiple alternative material systems and the margin coefficient corresponding to each alternative material system, including:

[0031] Obtain the total lifecycle cost of the target vehicle for each alternative material system;

[0032] The candidate material system corresponding to the minimum total life cycle cost is selected as the target material system.

[0033] Based on the target material system and the corresponding margin coefficient, vehicle performance simulation tests are conducted to obtain test results; the test results include vehicle power performance or driving range.

[0034] If the test results meet the preset conditions, the power battery is selected based on the target material system and the margin coefficient corresponding to the target material system.

[0035] Secondly, this application also provides a power battery selection device. The device includes:

[0036] The acquisition module is used to obtain the minimum energy of the power battery under the alternative material system based on the operating conditions of the target vehicle, and to obtain the actual energy of the power battery based on the minimum energy and the margin coefficient variable; the actual energy is represented by the margin coefficient variable.

[0037] The calculation module is used to obtain the total lifespan of the power battery based on the actual energy, and to obtain the total lifespan cost of the target vehicle based on the total lifespan of the power battery.

[0038] The parameter tuning module is used to adjust the margin coefficient value of the margin coefficient variable to minimize the total life cycle cost. Under the condition of minimizing the total life cycle cost, the corresponding margin coefficient value is used as the margin coefficient of the candidate material system.

[0039] The selection module is used to select power batteries based on multiple alternative material systems and the margin coefficient corresponding to each alternative material system.

[0040] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to perform the following steps:

[0041] Based on the operating conditions of the target vehicle, the minimum energy of the power battery under the alternative material system is obtained, and the actual energy of the power battery is obtained based on the minimum energy and the margin coefficient variable; the actual energy is represented by the margin coefficient variable.

[0042] Based on the actual energy, obtain the total lifespan of the power battery, and based on the total lifespan of the power battery, obtain the total lifespan cost of the target vehicle.

[0043] Adjust the margin coefficient value of the margin coefficient variable to minimize the total life cycle cost. Under the condition of minimizing the total life cycle cost, the corresponding margin coefficient value is used as the margin coefficient of the candidate material system.

[0044] The selection of power batteries is based on multiple alternative material systems and the margin coefficient corresponding to each alternative material system.

[0045] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, performs the following steps:

[0046] Based on the operating conditions of the target vehicle, the minimum energy of the power battery under the alternative material system is obtained, and the actual energy of the power battery is obtained based on the minimum energy and the margin coefficient variable; the actual energy is represented by the margin coefficient variable.

[0047] Based on the actual energy, obtain the total lifespan of the power battery, and based on the total lifespan of the power battery, obtain the total lifespan cost of the target vehicle.

[0048] Adjust the margin coefficient value of the margin coefficient variable to minimize the total life cycle cost. Under the condition of minimizing the total life cycle cost, the corresponding margin coefficient value is used as the margin coefficient of the candidate material system.

[0049] The selection of power batteries is based on multiple alternative material systems and the margin coefficient corresponding to each alternative material system.

[0050] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, performs the following steps:

[0051] Based on the operating conditions of the target vehicle, the minimum energy of the power battery under the alternative material system is obtained, and the actual energy of the power battery is obtained based on the minimum energy and the margin coefficient variable; the actual energy is represented by the margin coefficient variable.

[0052] Based on the actual energy, obtain the total lifespan of the power battery, and based on the total lifespan of the power battery, obtain the total lifespan cost of the target vehicle.

[0053] Adjust the margin coefficient value of the margin coefficient variable to minimize the total life cycle cost. Under the condition of minimizing the total life cycle cost, the corresponding margin coefficient value is used as the margin coefficient of the candidate material system.

[0054] The selection of power batteries is based on multiple alternative material systems and the margin coefficient corresponding to each alternative material system.

[0055] The aforementioned power battery selection method, device, computer equipment, storage medium, and computer program product, based on the operating conditions of the target vehicle, obtains the minimum energy of the power battery under the candidate material system, and obtains the actual energy of the power battery based on the minimum energy and the margin coefficient variable; the actual energy is represented by the margin coefficient variable; based on the actual energy, the overall lifespan of the power battery is obtained, and based on the overall lifespan of the power battery, the total life cycle cost of the target vehicle is obtained; the margin coefficient value of the margin coefficient variable is adjusted to minimize the total life cycle cost, and the corresponding margin coefficient value is used as the margin coefficient for the candidate material system when the total life cycle cost is minimized; based on multiple candidate material systems and the margin coefficient corresponding to each candidate material system, power battery selection is performed. By incorporating the optimization of the total life cycle cost of electric vehicles into the power battery selection method, while meeting the vehicle's power performance requirements, the method enables precise selection of power batteries, minimizing the overall ownership cost for users of electric vehicles and effectively alleviating consumers' economic concerns about purchasing electric vehicles. Attached Figure Description

[0056] Figure 1 This is a diagram illustrating the application environment of a power battery selection method in one embodiment.

[0057] Figure 2 This is a flowchart illustrating a power battery selection method in one embodiment;

[0058] Figure 3 This is a logic flowchart for selecting a power battery in one embodiment;

[0059] Figure 4 This is a structural block diagram of a power battery selection device in one embodiment;

[0060] Figure 5 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0062] The power battery selection method provided in this application embodiment can be applied to computer equipment. It is understood that, in situations such as... Figure 1In the illustrated application environment, the computer device can specifically be terminal 102 or server 104. Terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be integrated onto server 104 or located in the cloud or on other network servers. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. Server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers.

[0063] In one embodiment, such as Figure 2 As shown, a method for selecting a power battery is provided, which can be applied to... Figure 1 Taking terminal 102 as an example, the explanation includes the following steps:

[0064] Step 202: Based on the operating conditions of the target vehicle, obtain the minimum energy of the power battery under the alternative material system, and obtain the actual energy of the power battery based on the minimum energy and the margin coefficient variable; the actual energy is represented by the margin coefficient variable.

[0065] Optionally, determine the initial mass of the power battery under the alternative material system, and determine the initial full-load mass of the target vehicle under the alternative material system based on the initial mass; obtain the average drive power, maximum drive power, and additional power consumption of the vehicle's electronic system based on the operating conditions and the initial full-load mass; obtain the rated power and peak power of the motor based on the average drive power and maximum drive power to determine the efficiency of the electric drive system; obtain the minimum energy of the power battery under the alternative material system based on the target vehicle's range, the average power consumption per kilometer under the operating conditions, the rated power of the motor, the additional power consumption, and the efficiency of the electric drive system; and use the minimum energy and margin coefficient variables to represent the actual energy of the power battery.

[0066] Furthermore, the energy density of the battery pack under the alternative material system is determined; based on the actual energy and the energy density of the battery pack, the actual mass of the power battery under the alternative material system is obtained; based on the difference between the actual mass and the initial mass, the initial full-load mass of the vehicle is adjusted.

[0067] Specifically, such as Figure 3 As shown, the target vehicle and target market are determined based on operating condition data and the initially set vehicle full-load mass M0 (including the initially set power battery mass M). b0 ), calculate the average drive power P of the whole vehicle. avg Maximum drive power P max and the additional power consumption P of the vehicle's electronic systems ele .

[0068] The operating condition data can be collected from actual electric vehicles on the road, or obtained by reasonably correcting and converting the operating condition data of traditional fuel vehicles for the same purpose and market. The operating condition data should include parameters such as vehicle speed-time, motor power-time, and additional power consumption-time.

[0069] The average driving power P of the whole vehicle avg and maximum drive power P max Calculate the rated power P of the motor respectively. rated and peak power P peak Find the minimum value and select a suitable motor.

[0070] Among them, P rated ≥P avg ,P peak ≥P max .

[0071] Based on the target vehicle's designed driving range S, the average power consumption per kilometer e under operating conditions, and the motor's rated power P rated Additional power consumption P of the vehicle's electronic systems ele The minimum energy E0 of the power battery is obtained by calculating the efficiency η of the electric drive system. Multiplying this minimum energy by a margin factor a yields the actual energy E of the power battery.

[0072]

[0073] E = a·E0

[0074] 1≤a<2

[0075] The actual mass M of the power battery is calculated based on the actual energy E of the power battery and the mass energy density ρ of the battery pack provided by the battery supplier. b .

[0076] The actual mass M of the power battery b Compared with the initially designed power battery mass M b0 The difference is calculated to adjust the vehicle's full load weight to M.

[0077] Step 204: Based on the actual energy, obtain the total lifespan of the power battery, and based on the total lifespan of the power battery, obtain the total lifespan cost of the target vehicle.

[0078] Optionally, the rated discharge rate and peak discharge rate of the power battery are obtained based on actual energy, electric drive system efficiency, motor rated power, and motor peak power; the average charging rate, maximum charging rate, and state-of-charge (SOT) curve of the power battery are obtained based on user charging behavior statistics, operating conditions, and actual energy of the target vehicle in the target market; the cycle life of the power battery is obtained based on the rated discharge rate, peak discharge rate, average charging rate, maximum charging rate, and SOT curve; the ambient temperature time curve of the target market is obtained, and the temperature time curve of the power battery is obtained based on operating conditions and user charging behavior statistics; the calendar life of the power battery is obtained based on the SOT curve and temperature time curve; and the overall life of the power battery is obtained based on the cycle life and calendar life.

[0079] Furthermore, based on the actual energy, the purchase cost of the power battery is obtained, and the vehicle purchase cost of the target vehicle is determined based on the purchase cost of the power battery; the purchase cost of the power battery is a part of the vehicle purchase cost; based on the overall lifespan of the power battery and the purchase cost of the power battery, the vehicle operating cost of the target vehicle is obtained; based on the vehicle purchase cost and the vehicle operating cost, the total life cycle cost of the target vehicle is obtained.

[0080] Specifically, such as Figure 3 As shown, based on the actual energy E of the power battery, the efficiency η of the electric drive system, and the rated power P of the motor... rated and motor peak power P peak Calculate the rated discharge rate C of the power battery. rated and peak discharge rate C peak .

[0081]

[0082]

[0083] Based on the charging behavior statistics of target market users of the target vehicle, operating conditions, and the actual energy E of the power battery, the average charging rate C of the power battery is calculated. avg Maximum charging rate C max And the State of Charge (SOC) time curve of the power battery.

[0084] According to the rated discharge rate C of the power battery rated and peak discharge rate C peak and the average charging rate C of the power battery avg Maximum charging rate C maxThe cycle life of the power battery is determined by combining the State of Charge (SOC)-time curve of the power battery with the battery life model provided by the battery supplier or obtained through self-testing.

[0085] Based on the target market, the local ambient temperature-time curve can be determined. Then, by substituting operational data and user charging behavior statistics into the battery electrothermal model, the temperature rise of the power battery during operation and charging can be obtained. Combining the ambient temperature and battery temperature rise, the temperature-time curve of the power battery is obtained.

[0086] The calendar life of the power battery is calculated based on its SOC-time curve and temperature-time curve. However, considering the uneven heat dissipation of the power battery and the fact that the lifespan of the entire battery pack is limited by the most severely degraded individual cell, the highest internal temperature of the power battery should be used to calculate the battery's calendar life.

[0087] The total lifespan L of an electric vehicle's power battery is obtained by combining the cycle life and calendar life of the power battery, which is the warranty that electric vehicle manufacturers often provide, such as 8 years or 120,000 kilometers.

[0088] Calculate the purchase cost C of the power battery based on its actual energy E. b The purchase cost of the power battery, C b The purchase cost C of electric vehicles aqs Part of it.

[0089] C aqs =C b +C car +C fee -C sus =b·E+C car +C fee -C sus

[0090] Among them, the user's vehicle purchase cost C aqs The price of an electric vehicle (including the cost of purchasing the power battery C) b Other costs and profits C car In addition to purchase tax, license plate fees, and handling fees, etc., C fee Subtracting the car purchase subsidy C sus (If applicable). Under the same material system, the purchase cost C of the power battery. b Generally, it has a linear proportional relationship with the battery energy E, and its coefficient is assumed to be b. This patent aims to explore the selection of power batteries, so under normal circumstances, it will only affect the first part of the formula, namely the purchase cost C of the power battery. b In very rare cases, this may also affect the car purchase subsidy C. sus .

[0091] Based on the total lifespan L of the power battery and the purchase cost C of the power battery b Calculate the user's cost of using the electric vehicle C opt .

[0092] C opt =C eng +C mat +C exc

[0093]

[0094] The cost of using an electric vehicle should include three parts: the electricity cost C consumed during driving. eng The maintenance cost C of electric vehicles mat And the cost of replacing the battery C exc Where t is the usage time of the electric vehicle. This patent aims to explore the selection of power batteries, so generally, it only affects the third part of the above formula, namely the cost C of battery replacement. exc .

[0095] The lifecycle cost (LCC) of an electric vehicle from a user's perspective is the vehicle purchase cost (C). aqs Vehicle operating costs C opt Other costs C oth (Sum of costs such as disposal and environmental costs):

[0096] LCC = C aqs +C opt +C oth

[0097] In the above formula, the vehicle purchase cost C aqs Related to the choice of materials and energy E of the power battery. Vehicle operating cost C. mat The factors related to the selection of materials, lifespan (L), and energy (E) of the power battery are all relevant. Among these, the lifespan (L) of the power battery, under the same operating conditions, is also affected by changes in energy (E). Within the range of commonly available power batteries on the market, other costs (C)... oth The correlation with the selection of power batteries can be ignored.

[0098] In one feasible implementation, the lifespan influencing factor of the power battery is not limited to the options listed in the specific implementation; the overall lifespan of the power battery is not limited to the calculation methods using calendar life and cycle life; the power battery is not limited to lithium-ion batteries, but can cover rechargeable power batteries of any material system; in the calculation of the total life cycle cost, the impact of the power battery lifespan on the cost can also be included in the scrap cost.

[0099] Step 206: Adjust the margin coefficient value of the margin coefficient variable to minimize the total life cycle cost. Under the condition of minimizing the total life cycle cost, the corresponding margin coefficient value is used as the margin coefficient corresponding to the candidate material system.

[0100] Specifically, such as Figure 3 As shown, a computational model is established in MATLAB, using the minimum energy value E0 of the power battery as the initial value. By adjusting the energy margin coefficient 'a' of the power battery, the margin coefficient that minimizes the total life cycle cost of the electric vehicle can be found, i.e., the optimal energy level of the power battery under this overall operating condition can be determined. Generally speaking, as the power battery energy increases, the vehicle purchase cost C... aqs While the cost increases, under the same operating conditions, the lifespan of the power battery will be extended, thereby reducing the operating cost of electric vehicles. mat .

[0101] Step 208: Select a power battery based on multiple alternative material systems and the margin coefficient corresponding to each alternative material system.

[0102] Optionally, obtain the total life cycle cost of the target vehicle for each candidate material system; select the candidate material system with the lowest total life cycle cost as the target material system; conduct vehicle performance simulation tests based on the target material system and its corresponding margin coefficient to obtain test results; the test results include vehicle power performance or driving range; if the test results meet preset conditions, select a power battery based on the target material system and its corresponding margin coefficient.

[0103] Specifically, such as Figure 3 As shown, power batteries with different material systems differ significantly in energy density, price per kilowatt-hour, and lifespan models. When comparing different material systems for power batteries, the optimal battery energy should be calculated within each material system before comparing their total lifespan costs.

[0104] Furthermore, after finalizing the material system, energy, and other parameters of the power battery, all parameters need to be substituted into the vehicle performance simulation system to verify their effectiveness. If the vehicle's power performance or driving range cannot be guaranteed, the parameters of the motor or power battery need to be adjusted so that the simulation results ultimately meet the vehicle's requirements. At the same time, other factors that constrain the power battery, such as space size and shape, must also be considered.

[0105] In the aforementioned power battery selection method, the minimum energy of the power battery under the candidate material systems is obtained based on the operating conditions of the target vehicle. The actual energy of the power battery is then obtained based on the minimum energy and a margin coefficient variable. The actual energy is represented by the margin coefficient variable. Based on the actual energy, the overall lifespan of the power battery is obtained, and based on the overall lifespan of the power battery, the total life cycle cost of the target vehicle is obtained. The margin coefficient value of the margin coefficient variable is adjusted to minimize the total life cycle cost. Under the condition of minimizing the total life cycle cost, the corresponding margin coefficient value is used as the margin coefficient for the candidate material systems. Power battery selection is performed based on multiple candidate material systems and the corresponding margin coefficient for each candidate material system. By incorporating the optimization of the total life cycle cost of electric vehicles into the power battery selection method, precise selection of power batteries can be achieved while meeting the vehicle's power performance requirements, minimizing the overall ownership cost for users of electric vehicles and effectively alleviating consumers' economic concerns about purchasing electric vehicles.

[0106] In one embodiment, a power battery selection method includes:

[0107] Determine the initial mass of the power battery under the alternative material system, and based on the initial mass, determine the initial full-load mass of the target vehicle under the alternative material system; based on the operating conditions and the initial full-load mass of the vehicle, obtain the average drive power, maximum drive power, and additional power consumption of the vehicle's electronic system; based on the average drive power and maximum drive power, obtain the rated power and peak power of the motor to determine the efficiency of the electric drive system; based on the target vehicle's driving range, the average power consumption per kilometer under the operating conditions, the rated power of the motor, the additional power consumption, and the efficiency of the electric drive system, obtain the minimum energy of the power battery under the alternative material system.

[0108] Determine the battery pack mass energy density of the power battery under the alternative material system; obtain the actual mass of the power battery under the alternative material system based on the actual energy and the battery pack mass energy density; adjust the initial full-load mass of the vehicle based on the difference between the actual mass and the initial mass.

[0109] The actual energy of the power battery is obtained based on the minimum energy and margin coefficient variables; the actual energy is represented by the margin coefficient variable.

[0110] Based on actual energy, electric drive system efficiency, motor rated power, and motor peak power, the rated discharge rate and peak discharge rate of the power battery are obtained. Based on user charging behavior statistics, operating conditions, and actual energy of the target vehicle in the target market, the average charging rate, maximum charging rate, and state-of-charge (SOT) curve of the power battery are obtained. Based on the rated discharge rate, peak discharge rate, average charging rate, maximum charging rate, and SOT curve, the cycle life of the power battery is obtained. The ambient temperature time curve of the target market is obtained, and the temperature time curve of the power battery is obtained based on operating conditions and user charging behavior statistics. Based on the SOT curve and temperature time curve, the calendar life of the power battery is obtained. Based on the cycle life and calendar life, the overall life of the power battery is obtained.

[0111] Based on the actual energy, obtain the purchase cost of the power battery, and determine the vehicle purchase cost of the target vehicle based on the purchase cost of the power battery; the purchase cost of the power battery is part of the vehicle purchase cost; based on the total lifespan of the power battery and the purchase cost of the power battery, obtain the vehicle operating cost of the target vehicle; based on the vehicle purchase cost and the vehicle operating cost, obtain the total life cycle cost of the target vehicle.

[0112] Adjust the margin coefficient value of the margin coefficient variable to minimize the total life cycle cost. Under the condition of minimizing the total life cycle cost, the corresponding margin coefficient value is used as the margin coefficient of the candidate material system.

[0113] Obtain the total lifecycle cost of the target vehicle for each candidate material system; select the candidate material system with the lowest total lifecycle cost as the target material system; conduct vehicle performance simulation tests based on the target material system and its corresponding margin coefficient to obtain test results; the test results include vehicle power performance or driving range; if the test results meet the preset conditions, select the power battery based on the target material system and its corresponding margin coefficient.

[0114] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0115] Based on the same inventive concept, this application also provides a power battery selection device for implementing the power battery selection method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations in one or more power battery selection device embodiments provided below can be found in the limitations of the power battery selection method described above, and will not be repeated here.

[0116] In one embodiment, such as Figure 4 As shown, a power battery selection device 400 is provided, including: an acquisition module 401, a calculation module 402, a parameter adjustment module 403, and a selection module 404, wherein:

[0117] The acquisition module 401 is used to acquire the minimum energy of the power battery under the alternative material system according to the operating conditions of the target vehicle, and to acquire the actual energy of the power battery according to the minimum energy and the margin coefficient variable; the actual energy is represented by the margin coefficient variable.

[0118] The calculation module 402 is used to obtain the total lifespan of the power battery based on the actual energy, and to obtain the total lifespan cost of the target vehicle based on the total lifespan of the power battery.

[0119] The parameter adjustment module 403 is used to adjust the margin coefficient value of the margin coefficient variable to minimize the total life cycle cost. Under the condition of minimizing the total life cycle cost, the corresponding margin coefficient value is used as the margin coefficient corresponding to the candidate material system.

[0120] The selection module 404 is used to select a power battery based on multiple alternative material systems and the margin coefficient corresponding to each alternative material system.

[0121] In one embodiment, the acquisition module 401 is further configured to determine the initial mass of the power battery under the alternative material system, determine the initial full-load mass of the target vehicle under the alternative material system based on the initial mass; acquire the average drive power, maximum drive power, and additional power consumption of the vehicle's electronic system based on the operating conditions and the initial full-load mass; acquire the rated power and peak power of the motor based on the average drive power and maximum drive power to determine the efficiency of the electric drive system; and acquire the minimum energy of the power battery under the alternative material system based on the target vehicle's range, the average power consumption per kilometer under the operating conditions, the rated power of the motor, the additional power consumption, and the efficiency of the electric drive system.

[0122] In one embodiment, the acquisition module 401 is further configured to determine the battery pack mass energy density of the power battery under the alternative material system; obtain the actual mass of the power battery under the alternative material system based on the actual energy and the battery pack mass energy density; and adjust the initial full-load mass of the vehicle based on the difference between the actual mass and the initial mass.

[0123] In one embodiment, the calculation module 402 is further configured to: obtain the rated discharge rate and peak discharge rate of the power battery based on actual energy, electric drive system efficiency, motor rated power, and motor peak power; obtain the average charging rate, maximum charging rate, and state-of-charge (SOT) curve of the power battery based on user charging behavior statistics, operating conditions, and actual energy of the target vehicle in the target market; obtain the cycle life of the power battery based on the rated discharge rate, peak discharge rate, average charging rate, maximum charging rate, and SOT curve; obtain the ambient temperature time curve of the target market; obtain the temperature time curve of the power battery based on operating conditions and user charging behavior statistics; obtain the calendar life of the power battery based on the SOT curve and temperature time curve; and obtain the overall lifespan of the power battery based on the cycle life and calendar life.

[0124] In one embodiment, the calculation module 402 is further configured to obtain the power battery purchase cost based on the actual energy, and determine the vehicle purchase cost of the target vehicle based on the power battery purchase cost; the power battery purchase cost is a part of the vehicle purchase cost; obtain the vehicle operating cost of the target vehicle based on the total lifespan of the power battery and the power battery purchase cost; and obtain the total life cycle cost of the target vehicle based on the vehicle purchase cost and the vehicle operating cost.

[0125] In one embodiment, the selection module 404 is further configured to obtain the total lifecycle cost of the target vehicle corresponding to each candidate material system; select the candidate material system with the lowest total lifecycle cost as the target material system; perform vehicle performance simulation tests based on the target material system and the margin coefficient corresponding to the target material system to obtain test results; the test results include vehicle power performance or driving range; and, if the test results meet preset conditions, select a power battery based on the target material system and the margin coefficient corresponding to the target material system.

[0126] Each module in the aforementioned power battery selection device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0127] In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as follows: Figure 5 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs in the non-volatile storage media to run. The database stores margin coefficient data for various material systems. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When executed by the processor, the computer program implements a power battery selection method.

[0128] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0129] In one embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor executes the computer program to perform the following steps: based on the operating conditions of the target vehicle, obtaining the minimum energy of the power battery under the alternative material systems, and obtaining the actual energy of the power battery based on the minimum energy and a margin coefficient variable; the actual energy is represented by the margin coefficient variable; based on the actual energy, obtaining the total lifespan of the power battery, and based on the total lifespan of the power battery, obtaining the total lifespan cost of the target vehicle; adjusting the margin coefficient value of the margin coefficient variable to minimize the total lifespan cost, and using the corresponding margin coefficient value as the margin coefficient corresponding to the alternative material systems when the total lifespan cost is minimized; and selecting a power battery based on multiple alternative material systems and the margin coefficient corresponding to each alternative material system.

[0130] In one embodiment, when the processor executes the computer program, it further performs the following steps: determining the initial mass of the power battery under the alternative material system; determining the initial full-load mass of the target vehicle under the alternative material system based on the initial mass; obtaining the average drive power, maximum drive power, and additional power consumption of the vehicle's electronic system based on the operating conditions and the initial full-load mass; obtaining the rated power and peak power of the motor based on the average drive power and maximum drive power to determine the efficiency of the electric drive system; and obtaining the minimum energy of the power battery under the alternative material system based on the target vehicle's range, the average power consumption per kilometer under the operating conditions, the rated power of the motor, the additional power consumption, and the efficiency of the electric drive system.

[0131] In one embodiment, when the processor executes the computer program, it also performs the following steps: determining the battery pack mass energy density of the power battery under the alternative material system; obtaining the actual mass of the power battery under the alternative material system based on the actual energy and the battery pack mass energy density; and adjusting the initial full-load mass of the vehicle based on the difference between the actual mass and the initial mass.

[0132] In one embodiment, when the processor executes the computer program, it further performs the following steps: obtaining the rated discharge rate and peak discharge rate of the power battery based on actual energy, electric drive system efficiency, motor rated power, and motor peak power; obtaining the average charging rate, maximum charging rate, and state-of-charge (SOT) curve of the power battery based on user charging behavior statistics, operating conditions, and actual energy of the target vehicle in the target market; obtaining the cycle life of the power battery based on the rated discharge rate, peak discharge rate, average charging rate, maximum charging rate, and SOT curve; obtaining the ambient temperature time curve of the target market, and obtaining the temperature time curve of the power battery based on operating conditions and user charging behavior statistics; obtaining the calendar life of the power battery based on the SOT curve and temperature time curve; and obtaining the overall lifespan of the power battery based on the cycle life and calendar life.

[0133] In one embodiment, when the processor executes the computer program, it further performs the following steps: obtaining the purchase cost of the power battery based on the actual energy, and determining the vehicle purchase cost of the target vehicle based on the purchase cost of the power battery; the purchase cost of the power battery is a part of the vehicle purchase cost; obtaining the vehicle operating cost of the target vehicle based on the total lifespan of the power battery and the purchase cost of the power battery; and obtaining the total life cycle cost of the target vehicle based on the vehicle purchase cost and the vehicle operating cost.

[0134] In one embodiment, when the processor executes the computer program, it further performs the following steps: obtaining the total life cycle cost of the target vehicle corresponding to each candidate material system; selecting the candidate material system corresponding to the minimum total life cycle cost as the target material system; performing vehicle performance simulation tests based on the target material system and the margin coefficient corresponding to the target material system, and obtaining test results; the test results include vehicle power performance or driving range; and, if the test results meet preset conditions, selecting a power battery based on the target material system and the margin coefficient corresponding to the target material system.

[0135] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When executed by a processor, the computer program performs the following steps: based on the operating conditions of the target vehicle, obtaining the minimum energy of the power battery under the alternative material systems, and obtaining the actual energy of the power battery based on the minimum energy and a margin coefficient variable; the actual energy is represented by the margin coefficient variable; based on the actual energy, obtaining the total lifespan of the power battery, and based on the total lifespan of the power battery, obtaining the total lifespan cost of the target vehicle; adjusting the margin coefficient value of the margin coefficient variable to minimize the total lifespan cost, and using the corresponding margin coefficient value as the margin coefficient corresponding to the alternative material systems when the total lifespan cost is minimized; and selecting a power battery based on multiple alternative material systems and the margin coefficient corresponding to each alternative material system.

[0136] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining the initial mass of the power battery under the alternative material system; determining the initial full-load mass of the target vehicle under the alternative material system based on the initial mass; obtaining the average drive power, maximum drive power, and additional power consumption of the vehicle's electronic system based on the operating conditions and the initial full-load mass; obtaining the rated power and peak power of the motor based on the average drive power and maximum drive power to determine the efficiency of the electric drive system; and obtaining the minimum energy of the power battery under the alternative material system based on the target vehicle's range, the average power consumption per kilometer under the operating conditions, the rated power of the motor, the additional power consumption, and the efficiency of the electric drive system.

[0137] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining the battery pack mass energy density of the power battery under the alternative material system; obtaining the actual mass of the power battery under the alternative material system based on the actual energy and the battery pack mass energy density; and adjusting the initial full-load mass of the vehicle based on the difference between the actual mass and the initial mass.

[0138] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: obtaining the rated discharge rate and peak discharge rate of the power battery based on actual energy, electric drive system efficiency, motor rated power, and motor peak power; obtaining the average charging rate, maximum charging rate, and state-of-charge (SOT) curve of the power battery based on user charging behavior statistics, operating conditions, and actual energy of the target vehicle in the target market; obtaining the cycle life of the power battery based on the rated discharge rate, peak discharge rate, average charging rate, maximum charging rate, and SOT curve; obtaining the ambient temperature time curve of the target market, and obtaining the temperature time curve of the power battery based on operating conditions and user charging behavior statistics; obtaining the calendar life of the power battery based on the SOT curve and temperature time curve; and obtaining the overall lifespan of the power battery based on the cycle life and calendar life.

[0139] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: obtaining the purchase cost of the power battery based on the actual energy, and determining the vehicle purchase cost of the target vehicle based on the purchase cost of the power battery; the purchase cost of the power battery is a part of the vehicle purchase cost; obtaining the vehicle operating cost of the target vehicle based on the total lifespan of the power battery and the purchase cost of the power battery; and obtaining the total life cycle cost of the target vehicle based on the vehicle purchase cost and the vehicle operating cost.

[0140] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: obtaining the total life cycle cost of the target vehicle corresponding to each alternative material system; selecting the alternative material system corresponding to the minimum total life cycle cost as the target material system; performing vehicle performance simulation tests based on the target material system and the margin coefficient corresponding to the target material system, and obtaining test results; the test results include vehicle power performance or driving range; and, if the test results meet preset conditions, selecting a power battery based on the target material system and the margin coefficient corresponding to the target material system.

[0141] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps: Based on the operating conditions of the target vehicle, obtain the minimum energy of the power battery under alternative material systems, and obtain the actual energy of the power battery based on the minimum energy and a margin coefficient variable; the actual energy is represented by the margin coefficient variable; based on the actual energy, obtain the total lifespan of the power battery, and based on the total lifespan of the power battery, obtain the total lifespan cost of the target vehicle; adjust the margin coefficient value of the margin coefficient variable to minimize the total lifespan cost, and, under the condition of minimizing the total lifespan cost, use the corresponding margin coefficient value as the margin coefficient corresponding to the alternative material systems; and select a power battery type based on multiple alternative material systems and the margin coefficient corresponding to each alternative material system.

[0142] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining the initial mass of the power battery under the alternative material system; determining the initial full-load mass of the target vehicle under the alternative material system based on the initial mass; obtaining the average drive power, maximum drive power, and additional power consumption of the vehicle's electronic system based on the operating conditions and the initial full-load mass; obtaining the rated power and peak power of the motor based on the average drive power and maximum drive power to determine the efficiency of the electric drive system; and obtaining the minimum energy of the power battery under the alternative material system based on the target vehicle's range, the average power consumption per kilometer under the operating conditions, the rated power of the motor, the additional power consumption, and the efficiency of the electric drive system.

[0143] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: determining the battery pack mass energy density of the power battery under the alternative material system; obtaining the actual mass of the power battery under the alternative material system based on the actual energy and the battery pack mass energy density; and adjusting the initial full-load mass of the vehicle based on the difference between the actual mass and the initial mass.

[0144] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: obtaining the rated discharge rate and peak discharge rate of the power battery based on actual energy, electric drive system efficiency, motor rated power, and motor peak power; obtaining the average charging rate, maximum charging rate, and state-of-charge (SOT) curve of the power battery based on user charging behavior statistics, operating conditions, and actual energy of the target vehicle in the target market; obtaining the cycle life of the power battery based on the rated discharge rate, peak discharge rate, average charging rate, maximum charging rate, and SOT curve; obtaining the ambient temperature time curve of the target market, and obtaining the temperature time curve of the power battery based on operating conditions and user charging behavior statistics; obtaining the calendar life of the power battery based on the SOT curve and temperature time curve; and obtaining the overall lifespan of the power battery based on the cycle life and calendar life.

[0145] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: obtaining the purchase cost of the power battery based on the actual energy, and determining the vehicle purchase cost of the target vehicle based on the purchase cost of the power battery; the purchase cost of the power battery is a part of the vehicle purchase cost; obtaining the vehicle operating cost of the target vehicle based on the total lifespan of the power battery and the purchase cost of the power battery; and obtaining the total life cycle cost of the target vehicle based on the vehicle purchase cost and the vehicle operating cost.

[0146] In one embodiment, when the computer program is executed by the processor, it further performs the following steps: obtaining the total life cycle cost of the target vehicle corresponding to each alternative material system; selecting the alternative material system corresponding to the minimum total life cycle cost as the target material system; performing vehicle performance simulation tests based on the target material system and the margin coefficient corresponding to the target material system, and obtaining test results; the test results include vehicle power performance or driving range; and, if the test results meet preset conditions, selecting a power battery based on the target material system and the margin coefficient corresponding to the target material system.

[0147] 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, and the collection, use and processing of the relevant data shall comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0148] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0149] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0150] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for selecting a power battery, characterized in that, The method includes: Based on the operating conditions of the target vehicle, the minimum energy of the power battery under the alternative material system is obtained, and the actual energy of the power battery is obtained based on the minimum energy and the margin coefficient variable; the actual energy is represented by the margin coefficient variable. Based on the actual energy, the total lifespan of the power battery is obtained, and based on the total lifespan of the power battery, the total lifespan cost of the target vehicle is obtained. Adjust the margin coefficient value of the margin coefficient variable to minimize the total life cycle cost. When the total life cycle cost is minimized, the corresponding margin coefficient value is used as the margin coefficient of the candidate material system. The selection of power batteries is based on multiple alternative material systems and the margin coefficient corresponding to each alternative material system. The process of obtaining the total lifecycle cost of the target vehicle based on the overall lifespan of the power battery includes: Based on the actual energy, the purchase cost of the power battery is obtained, and the vehicle purchase cost of the target vehicle is determined based on the purchase cost of the power battery; the purchase cost of the power battery is a part of the vehicle purchase cost; Based on the total lifespan of the power battery and the purchase cost of the power battery, the vehicle operating cost of the target vehicle is obtained. The total lifecycle cost of the target vehicle is obtained based on the vehicle purchase cost and the vehicle operating cost.

2. The method according to claim 1, characterized in that, The step of obtaining the minimum energy of the power battery under the alternative material system based on the operating conditions of the target vehicle includes: Determine the initial mass of the power battery under the alternative material system, and determine the initial full-load mass of the target vehicle under the alternative material system based on the initial mass; Based on the operating conditions and the initial full load weight of the vehicle, obtain the average driving power, maximum driving power, and additional power consumption of the vehicle's electronic systems. Based on the average drive power and the maximum drive power, the rated power and peak power of the motor are obtained to determine the efficiency of the electric drive system; Based on the target vehicle's driving range, the average power consumption per kilometer under operating conditions, the rated power of the motor, the additional power consumption, and the efficiency of the electric drive system, the minimum energy of the power battery under the alternative material system is obtained.

3. The method according to claim 2, characterized in that, The method further includes: Determine the battery pack mass energy density of the power battery under the candidate material system; Based on the actual energy and the mass energy density of the battery pack, the actual mass of the power battery under the alternative material system is obtained. The initial full-load weight of the vehicle is adjusted based on the difference between the actual weight and the initial weight.

4. The method according to claim 2, characterized in that, The step of obtaining the overall lifespan of the power battery based on the actual energy includes: The rated discharge rate and peak discharge rate of the power battery are obtained based on the actual energy, the efficiency of the electric drive system, the rated power of the motor, and the peak power of the motor. Based on the statistical data of user charging behavior of the target vehicle in the target market, the operating conditions, and the actual energy, the average charging rate, the maximum charging rate, and the state-of-charge time curve of the power battery are obtained. The cycle life of the power battery is obtained based on the rated discharge rate, the peak discharge rate, the average charge rate, the maximum charge rate, and the state-of-charge time curve. Obtain the ambient temperature-time curve of the target market, and obtain the temperature-time curve of the power battery based on the operating conditions and user charging behavior statistics. The calendar life of the power battery is obtained based on the state-of-charge time curve and the temperature-time curve. The overall lifespan of the power battery is obtained based on the cycle life and the calendar life.

5. The method according to claim 1, characterized in that, The selection of power batteries based on multiple alternative material systems and the margin coefficient corresponding to each alternative material system includes: Obtain the total lifecycle cost of the target vehicle for each alternative material system; The candidate material system corresponding to the minimum total life cycle cost is selected as the target material system. Based on the target material system and the margin coefficient corresponding to the target material system, a vehicle performance simulation test is performed to obtain the test results; the test results include the vehicle's power performance or driving range. If the test results meet the preset conditions, the power battery is selected based on the target material system and the margin coefficient corresponding to the target material system.

6. A power battery selection device, characterized in that, The device includes: The acquisition module is used to acquire the minimum energy of the power battery under the alternative material system according to the operating conditions of the target vehicle, and to acquire the actual energy of the power battery according to the minimum energy and the margin coefficient variable; the actual energy is represented by the margin coefficient variable. The calculation module is used to obtain the total lifespan of the power battery based on the actual energy, and to obtain the total lifespan cost of the target vehicle based on the total lifespan of the power battery. The parameter tuning module is used to adjust the margin coefficient value of the margin coefficient variable to minimize the total life cycle cost. When the total life cycle cost is minimized, the corresponding margin coefficient value is used as the margin coefficient of the candidate material system. The selection module is used to select power batteries based on multiple alternative material systems and the margin coefficient corresponding to each alternative material system. The process of obtaining the total lifecycle cost of the target vehicle based on the overall lifespan of the power battery includes: Based on the actual energy, the purchase cost of the power battery is obtained, and the vehicle purchase cost of the target vehicle is determined based on the purchase cost of the power battery; the purchase cost of the power battery is a part of the vehicle purchase cost; Based on the total lifespan of the power battery and the purchase cost of the power battery, the vehicle operating cost of the target vehicle is obtained. The total lifecycle cost of the target vehicle is obtained based on the vehicle purchase cost and the vehicle operating cost.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

9. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

Images