Battery reuse assistance method and battery reuse assistance device

Abstract

The present invention provides a battery reuse assistance method that makes it possible to accurately calculate the sale price of a battery at the scheduled time for sale. This battery reuse assistance method comprises: a step (S1) for acquiring a scheduled time for sale of a battery by a user; a step (S2) for predicting, on the basis of the acquired scheduled time for the sale, battery deterioration from primary use of the battery by the user and from secondary use of the battery by a secondary use destination; a step (S3) for calculating a residual value of the battery on the basis of the result of the prediction of the battery deterioration; and a step (S4) for calculating the sale price of the battery on the basis of transaction price information that defines the relationship between the calculated residual value of the battery and the transaction price.

Description

Battery Reuse Support Method and Battery Reuse Support Device

[0006]

[0001] The present disclosure relates to a battery reuse support method and a battery reuse support device.

[0002] Patent Document 1 discloses a support system that acquires the planned selling time of a battery from a user in order to support the reuse of the battery, and based on the time information, notifies the user of the trading price of the battery at the planned selling time for each of a plurality of product types in which the battery can be mounted.

[0003] International Publication No. 2021 / 193006

[0004] However, in Patent Document 1, the trading price of a general battery at the planned selling time is determined as the trading price of the target battery. Therefore, it is expected that the accuracy of the trading price (selling price) of the battery is poor.

[0005] In view of the above problems, an object of the present disclosure is to provide a battery reuse support method and a battery reuse support device that can accurately calculate the selling price of a battery at the planned selling time.

[0006] A battery reuse support method and a battery reuse support device according to an aspect of the present disclosure acquire the planned selling time of a battery by a user, predict the battery deterioration during the primary use of the battery by the user and during the secondary use of the battery by the secondary use destination based on the acquired planned selling time, calculate the residual value of the battery based on the prediction result of the battery deterioration, and use transaction price information that defines the relationship between the calculated residual value of the battery and the transaction price to calculate the selling price of the battery.

[0007] According to the present disclosure, it is possible to provide a battery reuse support method and a battery reuse support device that can accurately calculate the selling price of a battery at the planned selling time.

[0008] This is a block diagram showing an example of a battery reuse support system according to the first embodiment. This is a schematic diagram showing an example of vehicle usage information according to the first embodiment. This is a schematic diagram showing an example of assumed usage conditions and usage information for a secondary use destination according to the first embodiment. This is a schematic diagram showing an example of input to a usage prediction model according to the first embodiment. This is a schematic diagram showing an example of output to a usage prediction model according to the first embodiment. This is a schematic diagram showing an example of output to a capacity estimation model according to the first embodiment. This is a schematic diagram showing an example of a battery degradation prediction result according to the first embodiment. This is a schematic diagram showing an example of a battery degradation prediction result according to the first embodiment. This is a schematic diagram showing an example of a battery degradation prediction result according to the first embodiment. This is a schematic diagram showing an example of a battery degradation prediction result according to the first embodiment. This is a schematic diagram showing an example of a battery degradation prediction result according to the first embodiment. This is a schematic diagram showing an example of a battery degradation prediction result according to the first embodiment. This is a schematic diagram showing an example of a battery degradation prediction result according to the first embodiment. This is a schematic diagram showing an example of transaction price information for a secondary use destination according to the first embodiment. This is a schematic diagram showing an example of lithium price according to the first embodiment. This is a schematic diagram showing an example of cobalt price according to the first embodiment. This is a schematic diagram showing an example of nickel price according to the first embodiment. This is a flowchart showing an example of a battery reuse support method according to the first embodiment. This is a flowchart showing an example of battery degradation prediction processing according to the first embodiment. This is a flowchart showing an example of battery degradation prediction processing according to the first embodiment. This is a flowchart illustrating an example of battery degradation prediction processing according to the first embodiment. This is a flowchart illustrating an example of battery degradation prediction processing according to the first embodiment. This is a flowchart illustrating an example of battery degradation prediction processing and sales price calculation processing according to the first embodiment. This is a flowchart illustrating an example of usage method proposal processing according to the second embodiment. This is a schematic diagram showing an example of battery degradation prediction results according to the second embodiment. This is a schematic diagram showing an example of battery degradation prediction results according to the third embodiment. This is a schematic diagram showing an example of a proposed usage method according to the fourth embodiment. This is a schematic diagram showing an example of battery degradation prediction results according to the fourth embodiment. This is a schematic diagram showing an example of transaction price information for a secondary user according to the fifth embodiment. This is a schematic diagram showing an example of a single price display according to the fifth embodiment.This is a schematic diagram showing an example of a price range display according to the fifth embodiment. This is a schematic diagram showing an example of a violin plot of battery residual value according to the sixth embodiment.

[0009] The first to sixth embodiments of this disclosure will be described below with reference to the drawings. In the drawings, identical or similar parts are denoted by the same or similar reference numerals, and redundant descriptions are omitted. The first to sixth embodiments shown below are illustrative examples of apparatus and methods for realizing the technical idea of ​​this disclosure, and the technical idea of ​​this disclosure is not limited to the structure, arrangement, etc. of the components described below.

[0010] (First Embodiment) <Battery Reuse Support System> The battery reuse support system according to the first embodiment includes a battery reuse support device 1 which is a server device, a vehicle 3 owned by user 2 (hereinafter referred to as "own vehicle"), a plurality of vehicles other than own vehicle 3 (hereinafter referred to as "other vehicles") 3a to 3c, an information terminal (user terminal) 4 usable by user 2, and information terminals (secondary user terminals) 4a to 4c usable by secondary users. The battery reuse support device 1, own vehicle 3, other vehicles 3a to 3c, user terminal 4, and secondary user terminals 4a to 4c can send and receive data or information from each other via a network (communication network) 6 such as the Internet.

[0011] The vehicle 3 is an electric vehicle (EV) or a plug-in hybrid vehicle, etc., equipped with a battery (secondary battery) 7. The battery 7 may be, for example, a lithium-ion secondary battery or a nickel-metal hydride secondary battery. The battery 7 is a target battery that is to be sold to a secondary user. The vehicle 3 acquires usage information regarding the usage status of the vehicle 3 and battery status information regarding the state of the battery 7 installed in the vehicle 3 using various sensors. The vehicle 3 transmits the acquired usage information and battery status information to the battery reuse support device 1.

[0012] The usage information of the vehicle 3 includes, for example, charging frequency, charging method (e.g., normal charging or fast charging), purpose (e.g., commuting or leisure use), and driving frequency. The usage information of the vehicle 3 may also include driving information regarding the driving state of the vehicle 3, environmental information regarding the surrounding environment of the vehicle 3, and charging information for the vehicle 3. Driving information may include speed, acceleration, distance traveled, and driving frequency. Environmental information may include ambient temperature, location, date, gradient, atmospheric pressure, and humidity. Charging information may include charging frequency, charging method, and charging time. Battery status information may include battery voltage, current, temperature, resistance, and cumulative time (e.g., cumulative discharge time from a new state).

[0013] Other vehicles 3a to 3c are electric vehicles (EVs) or plug-in hybrid vehicles, etc., equipped with batteries (secondary batteries) 7a to 7c. Figure 1 shows three other vehicles 3a to 3c as examples, but the number of other vehicles is not limited. Other vehicles 3a to 3c acquire usage information regarding their usage status and battery status information regarding the state of the batteries 7a to 7c installed in them, using various sensors. Other vehicles 3a to 3c transmit the acquired usage information and battery status information to the battery reuse support device 1.

[0014] The usage information for other vehicles 3a to 3c is the same as the usage information for the own vehicle 3. The usage information for other vehicles 3a to 3c includes, for example, charging frequency, charging method, purpose, and driving frequency. The usage information for other vehicles 3a to 3c may include driving information regarding the driving status of other vehicles 3a to 3c, environmental information regarding the surrounding environment of other vehicles 3a to 3c, and charging information for other vehicles 3a to 3c. Driving information may include speed, acceleration, distance traveled, and driving frequency. Environmental information may include outside temperature, location, date, gradient, atmospheric pressure, and humidity. Charging information may include charging frequency, charging method, and charging time. The battery status information for other vehicles 3a to 3c is the same as the battery status information for the own vehicle 3. The battery status information for other vehicles 3a to 3c may include battery voltage, current, temperature, resistance, and cumulative time.

[0015] For example, the usage information for the own vehicle 3 and other vehicles 3a to 3c may include the user (user ID), date, discharge time, and charge time, as shown in Figure 2.

[0016] The user terminal 4 shown in Figure 1 is, for example, a mobile device such as a smartphone or tablet, or a notebook or desktop personal computer (PC). The user terminal 4 may also be an in-vehicle device such as a navigation system installed in the vehicle 3. The user terminal 4 is equipped with a display unit 5 that has a display screen visible to the user 2. The display unit 5 may be arranged separately from the user terminal 4.

[0017] The user terminal 4 prompts user 2 to input the planned sale date (desired sale date) of the battery 7 via an application or the like. The user terminal 4 obtains the planned sale date (desired sale date) of the battery 7 from user 2 based on user 2's actions. The user terminal 4 transmits the obtained planned sale date to the battery reuse support device 1. The planned sale date of the battery 7 may be the planned sale date for the battery 7 alone, or it may be the planned sale date for the entire vehicle 3 in which the battery 7 is installed.

[0018] Secondary use terminals 4a to 4c are, for example, mobile terminal devices such as smartphones or tablets, or notebook or desktop personal computers (PCs). Secondary use destinations that have secondary use terminals 4a to 4c are, for example, individuals, companies, or stores that purchase batteries 7 from user 2 for secondary use in purposes such as used vehicles, reuse, repurposing, or recycling. The type of secondary use destination is not particularly limited. Figure 1 shows four secondary use terminals 4a to 4c as examples, but the number of secondary use terminals and secondary use destinations is not particularly limited.

[0019] The secondary use terminals 4a to 4c obtain usage information regarding the usage method of the secondary use battery 7 (secondary use usage information), specifications regarding the performance (specs) of the secondary use (secondary use specifications), and transaction price information of the secondary use battery from the secondary use terminals. The secondary use terminals 4a to 4c transmit the obtained secondary use usage information, secondary use specifications, and transaction price information to the battery reuse support device 1. If secondary use usage information does not exist, the usage conditions expected for the same type of secondary use (secondary use expected usage conditions) may be used in the processing described later instead of secondary use usage information. The secondary use usage information and secondary use expected usage conditions each include, for example, charging conditions, discharging conditions, ambient temperature, and cumulative time, as shown in Figure 3.

[0020] The secondary use specifications include the changes in battery capacity over time, the minimum battery capacity, the secondary use period, and the end date of secondary use, which are required for each secondary use. Note that the secondary use specifications may not be separate from the secondary use information, but may be included within the secondary use information. That is, the secondary use information may include the changes in battery capacity over time, the minimum battery capacity, the secondary use period, and the end date of secondary use, which are required for each secondary use.

[0021] The battery reuse support device 1 shown in Figure 1 comprises a processing unit 10, a storage unit 20, and a communication unit 30. The processing unit 10 may include a processor such as a central processing unit (CPU), a storage device, and an input / output device. The storage unit 20 may include any of semiconductor storage devices, magnetic storage devices, and optical storage devices, and may include storage media such as registers, cache memory, ROM (Read Only Memory) and RAM (Random Access Memory) used as main memory. The functions of the processing unit 10 may be configured in a single piece of hardware, or they may be divided and configured in multiple pieces of hardware. The functions of the processing unit 10 are realized, for example, by the processor of the processing unit 10 executing a computer program (battery reuse support program) stored in the storage unit 20.

[0022] The communication unit 30 is a wireless communication unit that provides wireless communication functionality between the battery reuse support device 1 and external devices. The battery reuse support device 1 transmits and receives data or information via the communication unit 30 to its own vehicle 3, other vehicles 3a to 3c, user terminal 4, and secondary use terminals 4a to 4c, etc.

[0023] The storage unit 20 includes a vehicle information database (vehicle information DB) 21, a user information database (user information DB) 22, and a secondary user information database (secondary user information DB) 23. The vehicle information DB 21 stores usage status information and battery status information of other vehicles 3a to 3c. The user information DB 22 stores information about user 2 (user information), such as usage status information and battery status information of the own vehicle 3, and the planned sale date of the battery 7. The secondary user information DB 23 stores secondary user information for each secondary user, such as secondary user usage information, secondary user specifications, and transaction price information. The secondary user information DB 23 may pre-store multiple types of assumed usage conditions for secondary users.

[0024] The processing unit 10 includes a model generation unit 11, a deterioration prediction unit 12, and a sales price calculation unit 13 as its functional configuration. The model generation unit 11 generates a vehicle usage prediction model by statistical processing (first statistical processing) based on usage information of other vehicles 3a to 3c. The first statistical processing may employ, for example, machine learning or multivariate analysis. The vehicle usage prediction model may employ, for example, a neural network model or a linear regression model. The vehicle usage prediction model is a model that predicts and outputs the future usage status of a vehicle in multiple patterns by inputting individual parameters (first parameters). Individual parameters may be used, for example, as input data (explanatory variables) to the vehicle usage prediction model, or as parameters (coefficients) that constitute the vehicle usage prediction model. Individual parameters may be parameters that change the output pattern of the vehicle usage prediction model (for example, patterns of charging frequency, charging method, driving frequency, driving distance, etc.).

[0025] For example, as shown in Figure 4, individual parameters such as driving information (e.g., mileage, driving frequency), environmental information (e.g., outside temperature), and charging information (e.g., charging method, charging frequency) included in the usage information of other vehicles 3a to 3c are input to the vehicle usage prediction model. Depending on the input of the individual parameters, the vehicle usage prediction model predicts and outputs a time schedule including normal charging (NC), driving, parking, and fast charging (QC) as a pattern of the vehicle's future usage, as shown in Figure 5. For example, the higher the charging frequency and driving frequency as individual parameters input to the vehicle usage prediction model, the more the vehicle usage prediction model predicts a pattern with high charging frequency and driving frequency as the vehicle's future usage. The vehicle usage prediction model may predict a pattern of future usage for one vehicle based on the input of one piece of usage information from the usage information of other vehicles 3a to 3c, or it may predict patterns of future usage for multiple vehicles.

[0026] Furthermore, the model generation unit 11 generates a capacity estimation model by statistical processing (second statistical processing) based on the battery status information of other vehicles 3a to 3c. The second statistical processing may employ, for example, machine learning or multivariate analysis. The capacity estimation model may employ, for example, a neural network model or a linear regression model. The capacity estimation model is a model that estimates and outputs the change in battery remaining capacity (fully charged capacity) over time by inputting individual parameters (second parameters). The individual parameters may be used, for example, as input data (explanatory variables) to the capacity estimation model, or as parameters (coefficients) that constitute the capacity estimation model. As individual parameters, when the capacity estimation model estimates the battery remaining capacity at the time of primary use, for example, the pattern of future vehicle usage output by the vehicle usage prediction model, as shown in Figure 4, is input to the capacity estimation model. Furthermore, when the capacity estimation model estimates the remaining battery capacity during secondary use, the charging conditions, discharge conditions, ambient temperature, and cumulative time included in the secondary use information or assumed secondary use conditions are input to the capacity estimation model as individual parameters.

[0027] The capacity estimation model estimates and outputs the change in battery capacity over time from the past or present to the future, as shown in Figure 6, in response to the input of individual parameters. The battery capacity estimated by the capacity estimation model decreases over time. For example, if the charging frequency and driving frequency of the future vehicle usage patterns output by the vehicle usage prediction model are high, battery degradation will progress more easily, and therefore the battery capacity estimated by the capacity estimation model may be low. Also, if the voltage of the charging or discharging conditions included in the secondary use information or assumed secondary use conditions is high, if the ambient temperature is high or low, or if the cumulative time is long, battery degradation will progress more easily, and therefore the battery capacity estimated by the capacity estimation model may be low. The capacity estimation model may estimate the change in one battery capacity over time for the input of a pattern of future vehicle usage, or it may estimate the change in multiple battery capacities over time.

[0028] The degradation prediction unit 12 uses the vehicle usage prediction model and capacity estimation model generated by the model generation unit 11 to predict the performance degradation (battery degradation) of the battery 7 during primary and secondary use. For example, based on the planned sale date of the battery 7, the degradation prediction unit 12 uses the vehicle usage prediction model and capacity estimation model generated by the model generation unit 11 to predict the battery degradation during primary use up to the planned sale date of the battery 7. Furthermore, based on the planned sale date of the battery 7 and the secondary use information or assumed usage conditions of the secondary use location, the degradation prediction unit 12 uses the capacity estimation model generated by the model generation unit 11 to predict the battery degradation during secondary use from the planned sale date of the battery 7.

[0029] When predicting battery degradation during primary use, the degradation prediction unit 12 uses usage information from other vehicles 3a to 3c to predict vehicle usage patterns using a vehicle usage prediction model. Furthermore, using the vehicle usage patterns predicted by the vehicle usage prediction model, the degradation prediction unit 12 estimates the change in battery capacity over time using a capacity estimation model. Furthermore, based on the change in battery capacity over time estimated by the capacity estimation model, the degradation prediction unit 12 predicts battery degradation during primary use and calculates an index indicating the degree of battery degradation during primary use. For example, the degradation prediction unit 12 calculates a higher degree of battery degradation if the charging frequency included in the usage information of other vehicles 3a to 3c is high, if the number of rapid charging instances included in the usage information of other vehicles 3a to 3c is high, or if the driving frequency included in the usage information of other vehicles 3a to 3c is high.

[0030] The degradation prediction unit 12 may calculate, for example, the change over time (prediction line) of the remaining battery capacity, which is the full charge capacity, the change over time (prediction line) of the State of Health (SOH), or the change over time (prediction line) of the driving range, as an indicator of the degree of battery degradation. For example, when calculating the change over time of the remaining battery capacity, which is the full charge capacity, the change over time of the battery capacity estimated by the capacity estimation model may be used as is. Also, when calculating the change over time of SOH, for example, the change over time of SOH can be calculated based on the change over time of the battery capacity estimated by the capacity estimation model and the initial battery capacity included in the battery state information. Also, when calculating the change over time of the driving range, the change over time of the driving range can be calculated based on the change over time of the battery capacity estimated by the capacity estimation model and the vehicle's energy consumption included in the usage information.

[0031] The degradation prediction unit 12 uses, for example, usage information of multiple other vehicles 3a to 3c to predict usage patterns of multiple vehicles using a vehicle usage prediction model. Furthermore, the degradation prediction unit 12 uses the usage patterns of multiple vehicles predicted by the vehicle usage prediction model to estimate the time-dependent changes in the capacities of multiple batteries using a capacity estimation model. Furthermore, based on the time-dependent changes in the capacities of multiple batteries estimated by the capacity estimation model, the degradation prediction unit 12 predicts battery degradation during primary use and predicts the time-dependent changes (prediction lines) of multiple battery remaining capacities, as shown in Figure 7. That is, the time-dependent changes in the remaining capacities of multiple batteries are calculated in accordance with the usage information of multiple other vehicles 3a to 3c.

[0032] Figures 8 and 9 show the change in driving range over time (prediction line) as an indicator of the degree of battery degradation calculated by the degradation prediction unit 12. For example, if the charging frequency is relatively high, the number of times fast charging is used is relatively high, or the driving frequency is relatively high, battery degradation is likely to progress. In this case, as shown in Figure 8, the degradation prediction unit 12 calculates the driving range prediction line A, which is the shorter of the driving range prediction lines A and B. On the other hand, if the charging frequency is relatively low, the number of times fast charging is used is relatively low, or the driving frequency is relatively low, battery degradation is unlikely to progress. In this case, as shown in Figure 9, the degradation prediction unit 12 calculates the driving range prediction line B, which is the longer of the driving range prediction lines A and B.

[0033] Furthermore, when the usage information for other vehicles 3a to 3c indicates commuting, the charging frequency and driving frequency are higher than when they are used for leisure, so it is assumed that battery degradation will progress more easily. For this reason, as shown in Figure 8, the degradation prediction unit 12 calculates the driving range prediction line A, which is the shorter of the driving range prediction lines A and B. On the other hand, when the usage information for other vehicles 3a to 3c indicates leisure, the charging frequency and driving frequency are lower than when they are used for commuting, so it is assumed that battery degradation will not progress more easily. For this reason, as shown in Figure 9, the degradation prediction unit 12 calculates the driving range prediction line B, which is the longer of the driving range prediction lines A and B.

[0034] The degradation prediction unit 12 predicts the individual vehicle usage pattern of user 2 by inputting the usage information of its own vehicle 3, which is individual information of user 2, into a vehicle usage prediction model. The degradation prediction unit 12 estimates the change in user 2's individual battery capacity by inputting the individual vehicle usage pattern of user 2 into a capacity estimation model. Based on the estimation result of the change in user 2's individual battery capacity, the degradation prediction unit 12 predicts the battery degradation of user 2 during its individual first use. For example, based on the individual information of user 2, the degradation prediction unit 12 calculates a predicted driving range A that is narrower in distribution than the entire predicted driving range A, B, and C, as shown in Figure 10.

[0035] When predicting battery degradation during secondary use, the degradation prediction unit 12 uses secondary use information or assumed secondary use conditions to estimate the change in battery capacity over time using a capacity estimation model generated by the model generation unit 11. Furthermore, based on the change in battery capacity over time estimated by the capacity estimation model, the degradation prediction unit 12 predicts battery degradation during secondary use and calculates an index indicating the degree of battery degradation during secondary use. As an index indicating the degree of battery degradation during secondary use, the degradation prediction unit 12 may, for example, calculate the change in battery capacity over time (prediction line), which is the fully charged capacity, or the change in State of Health (SOH) over time (prediction line), or the change in driving range over time (prediction line), but will adopt one that is the same as the index indicating the degree of battery degradation during primary use. For example, the degradation prediction unit 12 inputs secondary use information or assumed secondary use conditions into the capacity estimation model to estimate the change in battery capacity over time during multiple secondary uses. Furthermore, the degradation prediction unit 12 calculates multiple time-dependent changes in battery capacity during secondary use (prediction lines), as shown in Figure 11, based on the time-dependent changes in multiple battery capacities estimated by the capacity estimation model.

[0036] The degradation prediction unit 12 calculates a predicted line A of the remaining battery capacity during the primary use period T1, from the present time t0 to the planned sale time t1, based on the planned sale time t1 of the battery 7, as the degradation during primary use. The remaining battery capacity during the primary use period T1 decreases over time from the remaining battery capacity P1 at the present time t0 to the remaining battery capacity P2 at the planned sale time t1. The degradation prediction unit 12 calculates the remaining battery capacity P2, which is the battery state value at the planned sale time t1.

[0037] Furthermore, the degradation prediction unit 12 calculates a prediction line B of the battery remaining capacity during secondary use, starting from the battery remaining capacity P2 at the planned sale time t1. The battery remaining capacity during secondary use decreases over time from the battery remaining capacity P2 at the planned sale time t1 to the battery remaining capacity P3 at the end of secondary use time t2. The prediction line B is calculated up to a predetermined time beyond the end of secondary use time t2. The predetermined time can be set as appropriate. The degradation prediction unit 12 calculates the battery remaining capacity P3, which is the battery state amount at the end of secondary use time t2.

[0038] The selling price calculation unit 13 calculates the remaining value of the battery 7 based on the battery degradation prediction results for primary and secondary use performed by the degradation prediction unit 12. The remaining value of the battery 7 is the value remaining in the battery 7 after secondary use. The remaining value of the battery 7 includes the value of the remaining time of the battery 7 after secondary use (remaining time value) and the value of the remaining capacity of the battery 7 after secondary use (remaining capacity value). However, the remaining value of the battery 7 may consist of only one of the remaining time of the battery 7 after secondary use (remaining time value) or the value of the remaining capacity of the battery 7 after secondary use (remaining capacity value).

[0039] The selling price calculation unit 13, for example, if it obtains prediction results for battery degradation during primary and secondary use as shown in Figure 12, calculates the remaining value of the battery 7 at the end of secondary use time t2, as shown in Figure 13, based on the end of secondary use time t2 included in the specifications for secondary use destination. The remaining value of the battery 7 includes the value of the remaining time Δt of the battery 7 after secondary use and the value of the remaining capacity ΔP of the battery 7 after secondary use. In Figure 13, the change C over time of the required battery capacity included in the specifications for secondary use destination is shown by a dashed line.

[0040] The remaining time Δt is the time from the end of secondary use time t2 to the time t3 when the remaining capacity of battery 7 decreases to the lower limit of capacity P4 included in the specifications for secondary use. The remaining time may also be the time from the end of secondary use time t2 to the time when the remaining capacity of battery 7 becomes zero. Furthermore, the remaining capacity ΔP is the difference between the remaining capacity P3 at the end of secondary use time t2 and the lower limit of capacity P4 included in the specifications for secondary use. The remaining capacity may also be the remaining capacity P3 at the end of secondary use time t2 itself.

[0041] The selling price calculation unit 13 calculates the selling price of the battery 7 based on the calculated remaining value of the battery 7, using transaction price information of secondary users, which is a calculation method that defines the relationship between the remaining value of the battery 7 and the transaction price of the battery 7. Transaction price information is set for each secondary user, for example, as shown in Figure 14. The transaction price information is set so that the transaction price of the battery 7 is higher the longer the remaining time, which is the remaining value of the battery 7, or the greater the remaining capacity, which is the remaining value of the battery 7. In other words, the transaction price of the battery 7 is set so that the greater the remaining value of the battery 7, the higher the transaction price of the battery 7. The selling price calculation unit 13 extracts the transaction price corresponding to the remaining value of the battery 7 from the transaction price information of secondary users stored in the secondary user information DB 23, and calculates the selling price of the battery 7 using the extracted transaction price. If there is transaction price information for multiple secondary users, the selling price calculation unit 13 may calculate the selling price of the battery 7 for each secondary user.

[0042] The selling price calculation unit 13 may calculate the selling price of the battery 7 based on the raw material prices of the battery 7. Figure 15 is an example of a projected value of the lithium price, which is a raw material price, from the present to the future; Figure 16 is an example of a projected value of the cobalt price, which is a raw material price, from the present to the future; and Figure 17 is an example of a projected value of the nickel price, which is a raw material price, from the present to the future. The selling price calculation unit 13 calculates a coefficient α based on the projected values ​​of the raw material prices shown in Figures 15 to 17 for the planned selling time of the battery 7, and the material composition ratio of the battery 7, etc. The selling price calculation unit 13 may calculate the selling price of the battery 7 by multiplying the transaction price corresponding to the residual value of the battery 7 in the transaction price information of the secondary use destination shown in Figure 14 by the calculated coefficient α.

[0043] The selling price calculation unit 13 may determine whether the battery 7 can be used for secondary use (in other words, whether the battery 7 can be sold to a secondary user) based on the specifications of the secondary user. For example, as shown in Figure 13, if the remaining battery capacity P3 at the end of secondary use time t2 is equal to or greater than the capacity P4 defined by the change in the required battery capacity over time C included in the specifications of the secondary user, the selling price calculation unit 13 determines that the battery can be used at the secondary user. On the other hand, although not shown in the figure, if the remaining battery capacity P3 at the end of secondary use time t2 is less than the capacity P4 defined by the change in the required battery capacity over time C included in the specifications of the secondary user, the selling price calculation unit 13 determines that the battery 7 cannot be used at the secondary user.

[0044] The selling price calculation unit 13 transmits the calculated selling price of the battery 7 to the user terminal 4 via the communication unit 30. The user terminal 4 receives the selling price of the battery 7 and causes the display unit 5 to display the received selling price of the battery 7. The user 2 can visually recognize the selling price of the battery 7 displayed on the display unit 5 and confirm how much the selling price of the battery 7 is at the planned selling time. Note that the display unit 5 may display, together with the selling price of the battery 7, a secondary use destination or the like corresponding to the selling price. Also, when there are selling prices of the battery 7 at a plurality of secondary use destinations, the selling price of the battery 7 may be displayed for each secondary use destination.

[0045] <Battery Reuse Support Method> Next, an example of the battery reuse support method according to the first embodiment will be described with reference to the flowcharts of FIGS. 18 to 24.

[0046] FIG. 18 shows an example of the overall procedure of the battery reuse support method according to the first embodiment. In step S1, the degradation prediction unit 12 acquires the planned selling time of the battery 7 by the user 2, which is transmitted from the user terminal 4. In step S2, based on the acquired planned selling time of the battery 7, the degradation prediction unit 12 predicts the battery degradation during the primary use by the user 2 until the planned selling time and during the secondary use by the secondary use destination from the planned selling time. In step S3, the selling price calculation unit 13 calculates the selling price of the battery 7 based on the prediction results of the battery degradation during the primary use and the secondary use by the degradation prediction unit 12. The selling price calculation unit 13 causes the display unit 5 to display the calculated selling price of the battery 7.

[0047] Fig. 19 shows an example of the battery degradation prediction process included in step S2 of Fig. 18. In step S11, the model generation unit 11 acquires the usage status information and battery state information of other vehicles 3a to 3c transmitted from other vehicles 3a to 3c. In step S12, the model generation unit 11 stores the acquired usage status information and battery state information of other vehicles 3a to 3c in the vehicle information DB21. In step S13, the model generation unit 11 generates a vehicle usage prediction model by first statistical processing based on the usage status information of other vehicles 3a to 3c stored in the vehicle information DB21. In step S14, the model generation unit 11 generates a capacity estimation model by second statistical processing based on the battery state information of other vehicles 3a to 3c stored in the vehicle information DB21. In step S15, the degradation prediction unit 12 predicts battery degradation during primary use and secondary use using the vehicle usage prediction model and the capacity estimation model generated by the model generation unit 11.

[0048] Fig. 20 shows an example of the battery degradation prediction process included in step S2 of Fig. 18. In step S21, the degradation prediction unit 12 inputs the usage status information of other vehicles 3a to 3c including at least the charging frequency, charging method, usage, and driving frequency into the vehicle usage prediction model. In step S22, the degradation prediction unit 12 predicts and outputs the pattern of the vehicle usage status by the vehicle usage prediction model. The degradation prediction unit 12 inputs the pattern of the vehicle usage status output from the vehicle usage prediction model into the capacity estimation model. The degradation prediction unit 12 estimates and outputs the change over time of the remaining capacity of the vehicle battery by the capacity estimation model. The degradation prediction unit 12 predicts battery degradation based on the change over time of the remaining capacity of the battery output from the capacity estimation model.

[0049] Figure 21 shows an example of the battery degradation prediction process during initial use, which is included in step S2 of Figure 18. In step S31, the degradation prediction unit 12 acquires usage information of the user's vehicle 3, which is individual information of the user 2. In step S32, the degradation prediction unit 12 inputs the acquired individual usage information of the user's vehicle 3 into a vehicle usage prediction model, and the vehicle usage prediction model predicts and outputs a pattern of usage for the individual user's vehicle 3. In step S33, the degradation prediction unit 12 inputs the pattern of usage for the individual user's vehicle 3 output from the vehicle usage prediction model into a capacity estimation model, and the capacity estimation model predicts and outputs the change in the remaining capacity of the individual battery 7 over time. In step S34, the degradation prediction unit 12 predicts the performance degradation of the individual battery 7 during initial use based on the change in the remaining capacity of the individual battery 7 output from the capacity estimation model. In step S35, the degradation prediction unit 12 predicts the battery performance, such as the remaining capacity of the battery at the time of sale, based on the time when the user 2 wishes to sell the battery 7.

[0050] Figure 22 shows an example of the battery degradation prediction process during secondary use included in step S2 of Figure 18. In step S41, the degradation prediction unit 12 determines whether or not there is secondary use information transmitted from secondary use terminals 4a to 4c. If it is determined that there is secondary use information, the process proceeds to step S42. In step S42, the degradation prediction unit 12 acquires the secondary use information and inputs the acquired secondary use information into the capacity estimation model. On the other hand, if it is determined in step S41 that there is no secondary use information, the process proceeds to step S43. In step S43, instead of secondary use information, the degradation prediction unit 12 inputs the assumed secondary use conditions stored in the secondary use information DB 23 into the capacity estimation model. In step S44, the degradation prediction unit 12 estimates the change in battery capacity over time during secondary use using the capacity estimation model. In step S45, the degradation prediction unit 12 predicts battery degradation during secondary use based on the change in battery capacity over time estimated by the capacity estimation model.

[0051] Figure 23 shows an example of the battery degradation prediction process during secondary use included in step S2 of Figure 18, and the selling price calculation process included in step S3 of Figure 18. In step S51, the degradation prediction unit 12 predicts the battery degradation at the desired selling time after primary use and calculates the remaining battery capacity at the desired selling time. In step S52, the degradation prediction unit 12 predicts the battery degradation during secondary use from the desired selling time based on the remaining battery capacity at the desired selling time. In step S53, the degradation prediction unit 12 acquires the secondary use destination specifications transmitted from the secondary use destination terminals 4a to 4c. In step S54, the degradation prediction unit 12 calculates the remaining value of the battery 7 at the end of secondary use based on the end of secondary use time, etc., included in the acquired secondary use destination specifications. In step S55, the degradation prediction unit 12 calculates the selling price of the battery 7 based on the calculated remaining value of the battery 7.

[0052] <Effects> According to the first embodiment, the degradation prediction unit 12 acquires the planned sale date of the battery 7 by the user 2, and predicts the battery degradation during the primary use of the battery 7 by the user 2 and during the secondary use of the battery 7 by the secondary user, based on the acquired planned sale date. The selling price calculation unit 13 calculates the remaining value of the battery 7 based on the battery degradation prediction result. Based on the transaction price information which defines the relationship between the calculated remaining value of the battery and the transaction price, the selling price of the battery 7 is calculated. As a result, the remaining value of the battery 7 after the end of secondary use can be calculated, and the accuracy of calculating the selling price of the battery 7 can be improved.

[0053] Furthermore, according to the first embodiment, the remaining value of the battery at the end of its secondary use period is calculated. This makes it possible to calculate the remaining value of the battery 7 at the end of its secondary use period, thereby improving the accuracy of calculating the selling price of the battery 7.

[0054] Furthermore, according to the first embodiment, when predicting battery degradation during primary use, the model generation unit 11 acquires usage information and battery status information from each of the multiple other vehicles 3a to 3c. The model generation unit 11 generates a vehicle usage prediction model using the usage information through a first statistical process. The model generation unit 11 generates a capacity estimation model using the battery status information through a second statistical process. The degradation prediction unit 12 predicts battery degradation during primary use using the vehicle usage prediction model and capacity estimation model generated by the model generation unit 11. This makes it possible to predict battery degradation while considering the nonlinearity and time-series progression of battery degradation.

[0055] Furthermore, according to the first embodiment, the vehicle usage information includes charging frequency, charging method, application, and driving frequency. As a result, the vehicle usage pattern changes according to the charging frequency, charging method, application, and driving frequency, making it possible to predict battery degradation according to the vehicle usage pattern.

[0056] Furthermore, according to the first embodiment, the deterioration prediction unit 12 uses the usage information of each user's vehicle to generate a vehicle usage prediction model and predict the usage status of each user's vehicle. This improves the accuracy of predictions regarding the usage status of each user's vehicle.

[0057] Furthermore, according to the first embodiment, when predicting battery degradation during secondary use, the degradation prediction unit 12 uses the assumed usage conditions or usage information of the secondary use site to predict battery degradation during secondary use using a capacity estimation model generated by the model generation unit 11. This makes it possible to predict battery degradation based on the usage method (usage conditions) of the secondary use site, and thus determine the end date of secondary use.

[0058] Furthermore, according to the first embodiment, the selling price calculation unit 13 calculates the residual value of the battery 7 based on the specifications of the secondary use destination. This clarifies the residual value of the battery 7 after secondary use, and makes it possible to calculate the selling price of the battery 7 according to its residual value.

[0059] Furthermore, according to the first embodiment, the selling price calculation unit 13 calculates the selling price of the battery 7 based on the raw material price of the battery 7. This allows for consideration of fluctuating raw material prices, thereby improving the accuracy of predicting the selling price of the battery 7.

[0060] (Second Embodiment) As a second embodiment, we will describe a case in which we propose a usage method that encourages user 2 to improve the remaining battery capacity after initial use.

[0061] Referring to the flowchart in Figure 24, an example of the usage method proposal process according to the second embodiment will be explained. In step S61, the degradation prediction unit 12 uses the usage information of its own vehicle 3 to predict the vehicle usage pattern of user 2 using a vehicle usage prediction model. In step S62, the degradation prediction unit 12 uses the predicted vehicle usage pattern to estimate the change in battery remaining capacity using a capacity estimation model. Based on the estimated change in battery remaining capacity, the degradation prediction unit 12 predicts the battery degradation during the first use and calculates the battery remaining capacity at the time of planned sale.

[0062] In step S63, the degradation prediction unit 12 identifies factors that will cause the battery remaining capacity to be low at the time of planned sale, based on the vehicle usage pattern predicted by the vehicle usage prediction model. For example, the degradation prediction unit 12 identifies the charging frequency or driving frequency indicated by the vehicle usage pattern predicted by the vehicle usage prediction model as a factor that will cause the battery remaining capacity to be low at the time of planned sale. In step S64, the degradation prediction unit 12 proposes a vehicle usage pattern that will result in a higher battery remaining capacity at the time of planned sale to the user 2. For example, the degradation prediction unit 12 proposes a usage method that promotes improvement of the battery remaining capacity after initial use to the user 2 by displaying a vehicle usage pattern modified to reduce the charging frequency or driving frequency on the display unit 5 of the user terminal 4.

[0063] For example, the battery remaining capacity prediction line A in Figure 25 is calculated by predicting battery degradation during primary use using the vehicle usage pattern before the charging frequency was changed. On the other hand, the battery remaining capacity prediction line B is calculated by predicting battery degradation during primary use using the vehicle usage pattern after the charging frequency was changed. The battery remaining capacity of prediction line B will be greater than the battery remaining capacity of prediction line A.

[0064] According to the second embodiment, the degradation prediction unit 12 proposes to the user 2 a usage method (vehicle usage pattern) during the initial use that promotes an increase in the remaining capacity of the battery 7 after the initial use. As a result, the user 2 can increase the resale price of the battery 7 by using the vehicle in accordance with the proposed usage method.

[0065] (Third Embodiment) As a third embodiment, a case in which a recommended selling time is proposed to user 2 will be described. For example, the degradation prediction unit 12 predicts the degradation of the battery during primary and secondary use based on the user 2's planned selling time of the battery 7, and determines whether the battery 7 is suitable for secondary use (in other words, whether the battery 7 can be used until the end of secondary use). If it is determined that the battery 7 is not suitable for secondary use (the battery 7 cannot be used until the end of secondary use), the degradation prediction unit 12 proposes to user 2 a recommended selling time earlier than the planned selling time.

[0066] For example, as shown in Figure 26, the degradation prediction unit 12 calculates a predicted line A for the remaining battery capacity during primary use and a predicted line B for the remaining battery capacity during secondary use, based on the planned sale date t1. The primary use period T1 is from the current time t0 to the planned sale date t1, and the secondary use period T2 is from the planned sale date t1 to the end of secondary use date t2. The remaining battery capacity P3 at the end of secondary use date t2, as shown in the predicted line B for the remaining battery capacity during secondary use, will be less than the capacity P4 defined by the change in remaining battery capacity C required by the specifications of the secondary user. In this case, the degradation prediction unit 12 determines that the battery 7 is unusable at the secondary user (the battery 7 is not suitable for the secondary user).

[0067] Therefore, the degradation prediction unit 12 calculates (sets) a recommended sale time t1' before the planned sale time t1, so that the remaining battery capacity at the end of secondary use time t2 is equal to or greater than the capacity P4 defined by the change in remaining battery capacity C required by the specifications of the secondary user.

[0068] The degradation prediction unit 12 calculates a predicted line B' for the remaining battery capacity during secondary use by predicting battery degradation during secondary use, starting from the remaining battery capacity P5 at the set recommended sale time t1'. The primary use period T1' from the current time t0 to the recommended sale time t1' is shorter than the primary use period T1 from the current time t0 to the planned sale time t1. The secondary use period T2' from the recommended sale time t1' to the end of secondary use time t2' is the same as the secondary use period T2 from the planned sale time t1 to the end of secondary use time t2. The remaining battery capacity P6 at the end of secondary use time t2' on the predicted line B' for the remaining battery capacity during secondary use is greater than or equal to the capacity P7 defined by the change in remaining battery capacity C' required by the specifications of the secondary user. In this case, the degradation prediction unit 12 determines that the battery 7 is usable at the secondary user (the battery 7 is suitable for the secondary user).

[0069] The degradation prediction unit 12 displays the recommended selling time t1' for the battery 7 on the display unit 5, thereby suggesting the recommended selling time t1' to the user 2.

[0070] According to the third embodiment, the degradation prediction unit 12 proposes a recommended time for selling the battery 7 to the user 2 based on the battery degradation prediction results for secondary use. This makes it possible to propose a recommended time for selling the battery 7 to a secondary user even if it is not possible to sell the battery 7 to a secondary user at the planned time for sale.

[0071] (Fourth Embodiment) As a fourth embodiment, a case is described in which a method of use that suppresses battery degradation is proposed to the secondary user based on the prediction result of battery degradation during secondary use. The degradation prediction unit 12 predicts battery degradation during secondary use based on the charging conditions, discharge conditions, ambient temperature, and cumulative time on the upper side of the secondary use information in Figure 27, and calculates the predicted line B of the remaining battery capacity as shown in Figure 28. The remaining battery capacity P3 at the end of secondary use time t2 is less than the capacity P4 defined by the change in remaining battery capacity C required by the specifications of the secondary user, making secondary use of the battery 7 impossible.

[0072] Therefore, the degradation prediction unit 12 changes the usage method of the secondary use information to relax the usage conditions so that the remaining battery capacity at the end of secondary use time t2 is equal to or greater than the capacity P4 defined by the change in battery remaining capacity C required by the specifications of the secondary use destination. For example, the degradation prediction unit 12 changes the charging conditions, discharge conditions, ambient temperature, and cumulative time of the secondary use information in Figure 27 from the usage method shown in the upper section to the usage method shown in the lower section.

[0073] The degradation prediction unit 12 predicts battery degradation during secondary use based on the modified secondary use information, and calculates a predicted battery remaining capacity line B' as shown in Figure 28. The predicted battery remaining capacity line B' shows suppressed battery degradation compared to the predicted battery remaining capacity line B. The battery remaining capacity P5 at the end of secondary use time t2 of the predicted battery remaining capacity line B' is equal to or greater than the capacity P4 specified by the change in battery remaining capacity C required by the specifications of the secondary use site, and the battery 7 becomes usable at the secondary use site.

[0074] The degradation prediction unit 12 proposes a usage method to suppress battery degradation during secondary use to the secondary user by displaying the usage method after the change in secondary use information on the display units of the secondary user terminals 4a to 4c. For example, the degradation prediction unit 12 may display the usage methods before and after (upper and lower) the change in the charging conditions, discharge conditions, ambient temperature, and cumulative time of the secondary use information shown in Figure 27, or it may display only the usage method after the change (lower section).

[0075] According to the fourth embodiment, the degradation prediction unit 12 proposes a method of use that suppresses the degradation of the battery 7 to the secondary user based on the prediction result of battery degradation during secondary use. As a result, the secondary user can suppress the degradation of the battery 7 by adopting the method of use that suppresses the degradation of the battery 7 proposed by the degradation prediction unit 12, and can purchase a battery 7 at a lower transaction price.

[0076] (Fifth Embodiment) As a fifth embodiment, a case will be described in which the selling price of the battery 7 calculated by the selling price calculation unit 13 includes either a single price or a price range. For example, the selling price calculation unit 13 calculates a selling price in the range of 210,000 yen to 240,000 yen based on the remaining value of the battery 7 and using the transaction price information shown in Figure 29. As shown in Figure 30, the selling price calculation unit 13 displays "210,000 yen" as a single price, which is the lowest selling price within the range of 210,000 yen to 240,000 yen, along with the selling time. The selling price calculation unit 13 may display "240,000 yen," which is the maximum selling price, or "225,000 yen," which is the average selling price, instead of the minimum selling price. Alternatively, as shown in Figure 31, the selling price calculation unit 13 may display "210,000 yen to 240,000 yen," which is the price range from the lowest selling price to the maximum selling price, along with the selling time. In this case, the accuracy of the price range prediction may be displayed as a probability distribution.

[0077] According to the fifth embodiment, the selling price of the battery 7 calculated by the selling price calculation unit 13 includes either a single price or a price range. This allows the selling price of the battery 7 to be displayed as either a single selling price or a price range. Furthermore, by displaying the selling price of the battery 7 as a price range, the possibility of selling at the maximum selling price can be indicated.

[0078] (Sixth Embodiment) As a sixth embodiment, a case in which the selling price for multiple types of secondary uses is calculated will be described. The selling price calculation unit 13 generates a violin plot of battery residual value for multiple types of secondary uses, for example, as shown in Figure 32. Figure 32 illustrates cases where the secondary uses are used vehicles, reuse, repurpose, and recycling, but is not particularly limited. By considering the probability density for the overlap portion of residual value at each secondary use, the prediction accuracy can be improved.

[0079] According to the sixth embodiment, by considering multiple secondary use destinations, it is possible to select a secondary use destination that matches the transaction price and the degradation state of the battery 7. User 2 can sell the battery 7 at the optimal transaction price.

[0080] (Other Embodiments) As described above, this disclosure is based on the first to sixth embodiments, but the descriptions and drawings that constitute part of this disclosure should not be understood as limiting this disclosure. Various alternative embodiments, examples, and operational techniques will become apparent to those skilled in the art from this disclosure. For example, the configurations disclosed in the first to sixth embodiments can be combined as appropriate to the extent that they do not contradict each other. Thus, this disclosure naturally includes various embodiments and the like that are not described herein. Therefore, the technical scope of this disclosure is determined solely by the inventive features relating to the claims that are appropriate from the above description.

[0081] 1...Battery reuse support device, 2...User, 3...Own vehicle, 3a-3c...Other vehicles, 4...User terminal, 4a-4c...Secondary use terminal, 5...Display unit, 6...Network, 7, 7a-7c...Battery, 10...Processing unit, 11...Model generation unit, 12...Degradation prediction unit, 13...Sales price calculation unit, 20...Storage unit, 30...Communication unit, 21...Vehicle information DB, 22...User information DB, 23...Secondary use information DB

Claims

1. A battery reuse support method comprising the steps of: obtaining the user's planned sale date for the battery; predicting the battery degradation during the user's primary use and the secondary use of the battery by the secondary user based on the obtained planned sale date; calculating the remaining value of the battery based on the battery degradation prediction results; and calculating the selling price of the battery using transaction price information that defines the relationship between the calculated remaining value of the battery and the transaction price.

2. The battery reuse support method according to claim 1, which calculates the remaining value of the battery at the end of the secondary use.

3. A battery reuse support method according to claim 1 or 2, wherein, when predicting battery degradation during the initial use, usage information and battery status information are obtained from each of a plurality of vehicles; a vehicle usage prediction model is generated by a first statistical processing using the usage information; a capacity estimation model is generated by a second statistical processing using the battery status information; and battery degradation during the initial use is predicted using the generated vehicle usage prediction model and capacity estimation model.

4. The battery reuse support method according to claim 3, wherein the vehicle usage information includes charging frequency, charging method, application, and driving frequency.

5. The battery reuse support method according to claim 3, wherein the generated vehicle usage prediction model predicts the usage status of an individual vehicle of a user using the usage status information of that user's individual vehicle.

6. The battery reuse support method according to claim 1 or 2, wherein, when predicting battery degradation during secondary use, the generated capacity estimation model predicts battery degradation during secondary use using the expected usage conditions of the secondary use site or the usage information of the secondary use site.

7. The battery reuse support method according to claim 1 or 2, wherein the step of calculating the remaining value of the battery is to calculate the remaining value of the battery based on the specifications of the secondary use destination.

8. A battery reuse support method according to claim 1 or 2, which calculates the selling price of the battery based on the raw material price of the battery.

9. The battery reuse support method according to claim 1 or 2, which proposes a method of use to encourage the user to increase the remaining capacity of the battery after the initial use.

10. The battery reuse support method according to claim 1 or 2, which proposes to the user a recommended time for selling the battery.

11. The battery reuse support method according to claim 1 or 2, which proposes to the secondary user a method for suppressing the degradation of the battery based on the prediction result of the battery degradation during secondary use.

12. The battery reuse support method according to claim 1 or 2, wherein the selling price of the battery is a single price or a price range.

13. The battery reuse support method according to claim 1 or 2, wherein the secondary use destination includes a plurality of types of use destinations.

14. A battery reuse support device comprising: a degradation prediction unit that obtains the user's planned sale date for the battery and predicts the battery degradation during the user's primary use and the secondary use of the battery by the secondary user based on the obtained planned sale date; and a selling price calculation unit that calculates the remaining value of the battery based on the battery degradation prediction result and calculates the selling price of the battery using transaction price information that defines the relationship between the calculated remaining value of the battery and the transaction price.

Images