Information processing method and information processing system

Abstract

An information processing device according to the present invention acquires power consumption information indicating information corresponding to a power consumption amount per usage unit of an electrical device driven by a battery, acquires initial capacity information indicating the initial capacity of the battery, calculates a first life span of the battery on the basis of the power consumption information and the initial capacity information, acquires a second life span of the battery established according to properties of the battery, and outputs, as a third life span of the battery, the shorter from among the first life span and the second life span.

Description

[Technical field]

[0001] The present disclosure relates to an information processing method and an information processing system. [Background technology]

[0002] The following Patent Document 1 discloses a technique for calculating information about the life of a battery (for example, battery capacity or replacement time) based on the detection result of the battery state.

[0003] In the technology disclosed in Patent Document 1, information regarding the battery life is calculated uniformly based on the battery state. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2018-54488 A Summary of the Invention

[0005] An object of the present disclosure is to provide a technique that makes it possible to calculate the life of a battery for driving an electrical device in accordance with the manner in which the electrical device is used while ensuring safety.

[0006] An information processing method according to one embodiment of the present disclosure includes an information processing device that acquires power consumption information indicating information corresponding to the amount of power consumed per unit of usage of an electrical device driven by a battery, acquires initial capacity information indicating the initial capacity of the battery, calculates a first life of the battery based on the power consumption information and the initial capacity information, acquires a second life of the battery that is set according to characteristics of the battery, and outputs the shorter of the first life and the second life as a third life of the battery. [Brief description of the drawings]

[0007] [Figure 1] 1 is a block diagram showing a configuration of an information processing system according to a first embodiment of the present disclosure. [Diagram 2] FIG. 2 is a block diagram showing functions of a data processing unit. [Diagram 3] FIG. 2 is a block diagram showing a configuration of an SoL calculation unit. [Figure 4] FIG. 13 is a diagram showing a simplified example of a planned travel distance. [Diagram 5] 10 is a flowchart showing the flow of processing executed by a data processing unit. [Figure 6] FIG. 13 is a diagram showing an example of a display mode of a remaining lifespan. [Figure 7] FIG. 11 is a block diagram showing a configuration of an information processing system according to a second embodiment of the present disclosure. [Figure 8] 10 is a flowchart showing the flow of processing executed by a data processing unit. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0008] (Findings on which this disclosure is based) Products purchased through mail order sales over the Internet, etc., are delivered to customers' homes, etc. by delivery companies. Delivery companies use multiple trucks to deliver packages within their assigned delivery area. In the future, electric vehicles (EVs) equipped with battery-powered driving motors are expected to become more widespread, and the number of delivery companies using EV trucks to deliver packages is expected to increase.

[0009] The battery of an EV deteriorates according to the total distance traveled from when the vehicle was new. The SoH (State of Health) is generally used as an indicator of the degree of battery deterioration. When the SoH drops to the lower allowable limit compared to the initial value when the vehicle was new, the EV (or battery) is considered to have reached the end of its life, and replacement with a new EV (or battery) is recommended. The lower allowable limit is usually set uniformly by the battery manufacturer or car manufacturer, for example at "80%."

[0010] However, the usage patterns of EVs vary, and there are cases where the continued use of an EV after the battery SoH has fallen below a uniform allowable lower limit does not pose a practical problem. For example, for an EV whose main use is short-distance driving and whose battery is frequently charged, the amount of power consumed per charge is small, and the SoH required for that usage pattern is small, so that the SoH falling below the allowable lower limit does not pose a practical problem. By continuing to use an EV after the SoH has fallen below the allowable lower limit, rather than replacing the EV every time the SoH falls below the uniform allowable lower limit, the EV replacement cycle can be extended. As a result, the long-term (e.g., 10-year) total cost of ownership (TCO) can be reduced. On the other hand, it is not desirable from the perspective of ensuring safety to allow the battery to continue to be used beyond a limit value set according to the battery characteristics such as safety. Therefore, in order to achieve both TCO reduction and safety assurance, it is important to determine the battery life individually according to the usage pattern of the EV while taking into account the battery characteristics such as safety.

[0011] The encoder device disclosed in the above Patent Document 1 includes a position detector that detects position information of a moving part, a battery that supplies power to the position detector, a battery detector that detects the state of the battery, and a calculator that calculates life information of the battery based on the detection result of the battery detector. The battery life information includes at least one of the time until the battery reaches a discharge end voltage, the remaining charge of the battery, the time during which the position detector can operate with the power supplied from the battery, and the time when the power supplied from the battery is insufficient for the power consumption of the position detector.

[0012] However, the above-mentioned Patent Document 1 does not disclose anything about determining the life of a battery individually depending on the usage mode of the electrical device while taking into consideration battery characteristics such as safety.

[0013] In order to solve the above problems, the inventors have discovered that by calculating a first battery life in accordance with the usage pattern of the electrical equipment, obtaining a second battery life in accordance with the battery characteristics such as safety, and deriving the battery life based on this information, it is possible to achieve both a reduction in TCO and ensuring safety, and have come up with the present disclosure.

[0014] Next, each aspect of the present disclosure will be described.

[0015] An information processing method according to one embodiment of the present disclosure includes an information processing device that acquires power consumption information indicating information corresponding to the amount of power consumed per unit of usage of an electrical device driven by a battery, acquires initial capacity information indicating the initial capacity of the battery, calculates a first life of the battery based on the power consumption information and the initial capacity information, acquires a second life of the battery that is set according to characteristics of the battery, and outputs the shorter of the first life and the second life as a third life of the battery.

[0016] According to this configuration, the information processing device calculates a first lifespan based on the power consumption per unit of use of the electrical device and the initial capacity of the battery, obtains a second lifespan set according to battery characteristics such as safety, and outputs the shorter of these as the battery lifespan (third lifespan). Therefore, the battery lifespan can be derived according to the usage mode of the electrical device while ensuring safety. As a result, it is possible to achieve both a reduction in total costs and ensuring safety.

[0017] In the above aspect, the electrical device is a mobile body equipped with a motor driven by the battery, and the information processing device acquires driving information of the mobile body as the power consumption information, and calculates the amount of power consumption based on information on the travel distance per usage unit of the mobile body included in the driving information.

[0018] According to this configuration, it becomes possible to appropriately manage the life span of an electric vehicle (EV) or a battery installed therein, based on driving information of the EV as a moving body.

[0019] In the above aspect, the information processing device acquires deterioration information indicating a deterioration level of the battery, calculates a remaining life of the battery based on the third life and the deterioration level, and outputs the remaining life.

[0020] According to this configuration, it is possible to derive the remaining life of a battery mounted on a mobile object according to the manner in which the mobile object is used while ensuring safety.

[0021] In the above aspect, the information processing device calculates the remaining life based on a difference between a deterioration degree corresponding to the third life and the deterioration degree indicated by the deterioration information.

[0022] According to this configuration, it is possible to calculate the remaining life span from a comparison in terms of the degree of deterioration.

[0023] In the above aspect, the information processing device causes a presentation device to present the third life span or the remaining life span.

[0024] According to this configuration, the third life or remaining life can be presented by the presentation device, so that the user can understand the battery life for each usage mode. In particular, when the remaining life is presented, it is possible to provide the user with information that is intuitively easy for the user to understand.

[0025] In the above aspect, the information processing device acquires movement history information or movement plan information of the moving object as the movement information.

[0026] According to this configuration, it is possible to acquire movement information as power consumption information by using the movement plan information itself or by estimating future movement plan information from past movement history information.

[0027] An information processing system according to one embodiment of the present disclosure includes a first acquisition unit that acquires power consumption information indicating information corresponding to the amount of power consumption per unit of usage of an electrical device driven by a battery, a second acquisition unit that acquires initial capacity information indicating the initial capacity of the battery, a calculation unit that calculates a first life of the battery based on the power consumption information and the initial capacity information, a third acquisition unit that acquires a second life of the battery that is set according to characteristics of the battery, and an output unit that outputs the shorter of the first life and the second life as a third life of the battery.

[0028] According to this configuration, the calculation unit calculates the first life based on the power consumption per unit of use of the electrical device and the initial capacity of the battery, the third acquisition unit acquires the second life set according to the characteristics of the battery such as safety, and the output unit outputs the shorter of these as the battery life (third life). Therefore, the battery life can be derived according to the usage mode of the electrical device while ensuring safety. As a result, it is possible to achieve both a reduction in total costs and ensuring safety.

[0029] The above-mentioned general or specific aspects of the present disclosure can be realized as a system, an apparatus, a method, an integrated circuit, a computer program, or any combination thereof. It goes without saying that such a computer program can be distributed as a computer-readable non-volatile recording medium such as a CD-ROM, or distributed via a communication network such as the Internet.

[0030] Each of the embodiments described below shows a specific example of the present disclosure. The numerical values, shapes, components, steps, order of steps, etc. shown in the following embodiments are merely examples and are not intended to limit the present disclosure. Furthermore, among the components in the following embodiments, components that are not described in an independent claim showing a top concept are described as optional components. Furthermore, in all embodiments, the contents of each component can be combined.

[0031] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In addition, elements with the same reference numerals in different drawings indicate the same or corresponding elements.

[0032] (First embodiment) FIG. 1 is a block diagram showing a configuration of an information processing system 1 according to a first embodiment of the present disclosure. In the example of this embodiment, the information processing system 1 is constructed as a management system of a delivery company that delivers packages to customers' homes or the like by using an electric vehicle (EV). As an example, this delivery company has a plurality of business offices in charge of each delivery area and a head office that manages the plurality of business offices. A local PC 12 is installed in the head office and each business office and is connected to a cloud server 11. In addition, a plurality of vehicles 13 for delivering packages are deployed in each business office. The cloud server 11, the local PC 12, and the vehicles 13 can communicate with each other via an arbitrary communication network 14 such as an IP network. In addition, a battery information database 15 is connected to the communication network 14. The battery information database 15 accumulates battery information indicating the specifications of a battery 41 provided by a battery manufacturer, an analysis manufacturer, or the like. The specifications include at least an initial capacity FCC_init and a second life EoL_b, which will be described later. The cloud server 11 can access the battery information database 15 via the communication network 14. In the present embodiment, the moving body is a vehicle, but is not limited thereto. For example, the moving body may be an aircraft such as a drone, a ship, or a mobile robot.

[0033] The cloud server 11 includes a data processing unit 22, a storage unit 23, and a communication unit 24. The local PC includes a display unit 31, a data processing unit 32, a storage unit 33, a communication unit 34, and an input unit 35. The display unit 31 is a liquid crystal display or an organic EL display, etc. The data processing units 22, 32 are processors such as a CPU. The storage units 23, 33 are HDDs or SSDs, etc. The communication units 24, 34 are communication modules that perform data communication according to a predetermined communication standard such as IP. The input unit 35 is a mouse or a keyboard, etc.

[0034] The vehicle 13 is an EV truck or the like, and includes a battery 41, a control unit 42, and a communication unit 43. The battery 41 is a secondary battery such as a lithium ion battery for driving a driving motor mounted on the vehicle 13. The control unit 42 is a BMS (Battery Management System) for controlling the operation and managing the state of the battery 41. The communication unit 43 is a communication module that performs data communication according to a predetermined communication standard such as IP.

[0035] The application of the information processing system 1 according to this embodiment is not limited to delivery businesses, but may also be any business that uses multiple EVs, such as a taxi business, a rental car business, a car sharing business, or a designated driving business.

[0036] Fig. 2 is a block diagram showing functions of the data processing unit 22 of the cloud server 11. As shown in Fig. 2, the data processing unit 22 has a plan information acquisition unit 51, a battery information acquisition unit 52, a log information acquisition unit 53, and an SoL calculation unit 55. These functions may be realized in software by a CPU executing a program read from a ROM or the like.

[0037] 3 is a block diagram showing the configuration of the SoL calculation unit 55. As shown by the connection relationship in FIG. 3, the SoL calculation unit 55 includes an EoL_u calculation unit 551, an EoL_t derivation unit 552, an SoH calculation unit 553, and an SoL calculation unit 554.

[0038] The EoL_u calculation unit 551 calculates the first life EoL_u of the battery 41 based on the initial capacity FCC_init input from the battery information acquisition unit 52 and the required capacity FCC_u input from the plan information acquisition unit 51. The initial capacity FCC_init is the capacity of the battery 41 when it is new, and is catalog information provided by the manufacturer of the battery 41 or the like. The required capacity FCC_u is power consumption information indicating the amount of power consumed per unit of use (per charge) of each vehicle 13, calculated according to the usage mode of each vehicle 13. The first life EoL_u is the life (End of Life) calculated according to the usage mode of each vehicle 13. The EoL_u calculation unit 551 calculates the first life EoL_u of the battery 41 based on the initial capacity FCC_init input from the battery information acquisition unit 52 and the required capacity FCC_u input from the plan information acquisition unit 51. The initial capacity FCC_init is the capacity of the battery 41 when it is new, and is catalog information provided by the manufacturer of the battery 41 or the like. The required capacity FCC_u is power consumption information indicating the amount of power consumed per unit of use (per charge) of each vehicle 13, calculated according to the usage mode of each vehicle 13.

[0039] EoL_u=(FCC_u / FCC_init)×100 ···(1)

[0040] The first life EoL_u is calculated by performing the following calculation.

[0041] The EoL_t derivation unit 552 derives a third life EoL_t, which is the life of the battery 41, based on the first life EoL_u input from the EoL_u calculation unit 551 and the second life EoL_b input from the battery information acquisition unit 52. The second life EoL_b is a limit value set by the manufacturer or analysis manufacturer of the battery 41 according to battery characteristics such as safety. The EoL_t derivation unit 552

[0042] EoL_t=max(EoL_u,EoL_b) ···(2)

[0043] By performing the following calculation, the larger of the first life EoL_u and the second life EoL_b (that is, the shorter life) is derived as the third life EoL_t.

[0044] The SoH calculation unit 553 calculates the degree of deterioration SoH of the battery 41 based on the history information of charging and discharging of the battery 41 from the log information input from the log information acquisition unit 53 .

[0045] The SoL calculation unit 554 calculates the remaining life SoL of the battery 41 based on the third life EoL_t input from the EoL_t derivation unit 552 and the deterioration level SoH input from the SoH calculation unit 553. The remaining life SoL is a deterioration index (State of Life) obtained by normalizing the deterioration level SoH by the third life EoL_t. The SoL calculation unit 554 calculates the remaining life SoL of the battery 41 based on the third life EoL_t.

[0046] (SoH-EoL_t) / (100-EoL_t)×100 ···(3)

[0047] The remaining life SoL is calculated by performing the following calculation, and the calculated remaining life SoL is output.

[0048] FIG. 4 is a simplified diagram showing an example of driving plan information formulated by a certain business establishment. A planned daily driving distance (km / day) is set for each year for each of a plurality of vehicles 13 (four vehicles A to D in this example). This planned driving distance is an optimal value calculated by a predetermined prediction model based on the long-term business plan of the business establishment, deterioration characteristics of the battery 41 relative to the total driving distance, and cost information including driver labor costs and vehicle purchase costs. The prediction model can be derived by machine learning using artificial intelligence. As an algorithm for the prediction model, route optimization by linear programming, neural network, multiple regression analysis, or the like can be used.

[0049] 4, it can be seen that the planned mileage increases and decreases significantly from year to year even for the same vehicle 13 (for example, vehicle C). For example, the graph related to vehicle A disappears after six years. This indicates that vehicle A will be sold (or scrapped) in six years. For example, the graph related to vehicle C appears after three years. This indicates that vehicle C will be purchased in three years.

[0050] The driving plan information shown in FIG. 4 is transmitted from the local PC 12 to the cloud server 11 via the communication network 14 and stored in the storage unit 23. However, the driving plan information may be created by the cloud server 11. The plan information acquisition unit 51 acquires the required capacity FCC_u of each vehicle 13 based on the driving plan information read from the storage unit 23. Assuming that each vehicle 13 is charged every day at the business, for example, the required capacity FCC_u of vehicle A at present (0 years later) is a capacity equivalent to a driving distance of 60 km. The plan information acquisition unit 51 inputs the required capacity FCC_u of each vehicle 13 acquired by converting the planned driving distance into the power consumption amount to the SoL calculation unit 55 as data D1.

[0051] FIG. 5 is a flowchart showing the flow of the process executed by the data processing unit 22 of the cloud server 11 to calculate the remaining life SoL of an EV.

[0052] When the cloud server 11 receives a request to calculate the remaining life SoL for a certain vehicle 13 from the local PC 12, first in step S01, the battery information acquisition unit 52 acquires EV specification information indicating the specifications of the vehicle 13 from the local PC 12 or from a database provided by a car manufacturer, etc. The specifications of the vehicle 13 include information indicating the type (model number, etc.) of the battery 41 installed in the vehicle 13.

[0053] Next, in step S02, the battery information acquisition unit 52 accesses the battery information database 15 to acquire the second life EoL_b and the initial capacity FCC_init for the battery 41 of the type identified in step S01 from the battery information database 15. The battery information acquisition unit 52 inputs the acquired second life EoL_b and initial capacity FCC_init to the SoL calculation unit 55 as data D2.

[0054] Next, in step S03, the plan information acquisition unit 51 acquires driving plan information for the target vehicle 13 by reading it from the storage unit 23. The plan information acquisition unit 51 also acquires a required capacity FCC_u for the target vehicle 13 based on the driving plan information, and inputs the required capacity FCC_u as data D1 to the SoL calculation unit 55. If driving plan information for the target vehicle 13 has not been created, the plan information acquisition unit 51 may receive driving history information of the vehicle 13 from the vehicle 13 via the communication network 14, and estimate a future driving plan from a transition trend of past driving distances included in the driving history information.

[0055] Next, in step S04, the EoL_u calculation unit 551 calculates the first life EoL_u of the battery 41 by performing the calculation shown in the above equation (1) based on the initial capacity FCC_init input as data D2 from the battery information acquisition unit 52 and the required capacity FCC_u input as data D1 from the plan information acquisition unit 51.

[0056] Next, in step S05, the EoL_t derivation unit 552 derives the third life EoL_t of the battery 41 by performing the calculation shown in the above equation (2) based on the first life EoL_u input from the EoL_u calculation unit 551 and the second life EoL_b input as data D2 from the battery information acquisition unit 52.

[0057] Next, in step S06, the log information acquisition unit 53 acquires log information from the target vehicle 13 via the communication network 14. The log information includes driving history information of the vehicle 13 and charge / discharge history information of the battery 41. The log information acquisition unit 53 inputs the acquired log information to the SoL calculation unit 55 as data D3.

[0058] Next, in step S 07 , the SoH calculation unit 553 calculates the degree of deterioration SoH of the battery 41 based on the charge / discharge history information of the battery 41 included in the log information input from the log information acquisition unit 53 .

[0059] Next, in step S08, the SoL calculation unit 554 calculates the remaining life SoL of the battery 41 by performing the calculation shown in the above equation (3) based on the third life EoL_t input from the EoL_t derivation unit 552 and the deterioration level SoH input from the SoH calculation unit 553.

[0060] Next, in step S09, the SoL calculation unit 554 outputs the remaining life SoL calculated in step S08. The remaining life SoL output from the SoL calculation unit 554 is transmitted to the local PC 12 via the communication network 14, and information indicating the remaining life of the target vehicle 13 is displayed on the display unit 31. Alternatively, the remaining life SoL output from the SoL calculation unit 554 may be transmitted to the target vehicle 13 via the communication network 14, and information indicating the remaining life of the vehicle 13 may be displayed on a display visible to the driver of the vehicle 13. Note that, in addition to the above display, the manner of presenting the information indicating the remaining life may be audio output or the like. Also, instead of or in addition to the remaining life SoL, the third life EoL_t may be presented.

[0061] According to this embodiment, the data processing unit 22 of the cloud server 11 (information processing device) calculates the first life EoL_u based on the required capacity FCC_u indicating the power consumption per unit of use (per charge) of the vehicle 13 and the initial capacity FCC_init of the battery 41. The data processing unit 22 also acquires the second life EoL_b set according to the characteristics of the battery 41 such as safety. Then, the data processing unit 22 derives the shorter of the first life EoL_u and the second life EoL_b as the life (third life EoL_t) of the battery 41. Therefore, the life of the battery 41 can be derived according to the usage mode of the vehicle 13 while ensuring safety. As a result, it is possible to achieve both a reduction in total costs and ensuring safety.

[0062] Furthermore, according to this embodiment, it is possible to appropriately manage the life span of an EV or the battery 41 mounted thereon, based on driving information (driving plan information or driving history information) of the EV as a moving body.

[0063] Moreover, according to this embodiment, it is possible to derive the remaining life SoL of the battery 41 mounted on the EV in accordance with the usage mode of the EV while ensuring safety.

[0064] Furthermore, according to this embodiment, by calculating the remaining life SoL based on the difference between the deterioration level corresponding to the third life EoL_t and the deterioration level SoH, it is possible to calculate the remaining life SoL from a comparison in terms of the deterioration level.

[0065] Moreover, according to the present embodiment, the third life EoL_t or the remaining life SoL is presented by a presentation device (such as the display unit 31), so that the user can grasp the life of the battery 41 for each usage mode. In particular, when the remaining life SoL is presented, it is possible to provide the user with information that is intuitively easy for the user to understand.

[0066] FIG. 6 is a diagram showing an example of a display mode of the remaining life SoL. FIG. 6 shows results for six vehicles A to F. The graph on the left shows a display mode using the deterioration level SoH of the battery 41, and the graph on the right shows a display mode using the remaining life SoL in which the deterioration level SoH in the left diagram is normalized by the third life EoL_t. Note that an example is shown in which the third life EoL_t of the vehicles A to C is 80%, and the third life EoL_t of the vehicles D to F is 70%. For example, when focusing on the vehicle F, the current deterioration level SoH is 90%, and the third life EoL_t is 70%, so the remaining life SoL is (90-70) / (100-70)×100=66%. According to the display mode of the remaining life SoL (right diagram), the user can intuitively understand that the vehicle 13 will reach the end of its life when the value on the vertical axis drops to 0%.

[0067] According to the present embodiment, the data processing unit 22 acquires, as driving information (power consumption information), driving plan information or driving history information of the vehicle 13. By using the driving plan information itself, or by estimating future driving plan information from past driving history information, it becomes possible to appropriately acquire driving information as power consumption information.

[0068] Second embodiment In the first embodiment, the cloud server 11 calculates the remaining life SoL of the battery 41 for a battery-powered EV, but the present invention is not limited to this example. The cloud server 11 may calculate the remaining life of a battery for any electric device driven by a battery. The electric device is, for example, a power storage device. The power storage device may have a power generation function. The usage plan information of the electric device can be formulated as power consumption information indicating the total amount of power consumption of the battery. When the usage plan information is unknown, the plan information acquisition unit 51 may estimate the usage plan information from the tendency based on history information indicating the past usage status of the electric device or the battery.

[0069] Fig. 7 is a block diagram showing a configuration of an information processing system 1 according to a second embodiment of the present disclosure. The vehicle 13 shown in Fig. 1 is replaced with an electric device 113. The electric device 113 has a battery 141, a control unit 142, and a communication unit 143. The battery 141, the control unit 142, and the communication unit 143 correspond to the battery 41, the control unit 42, and the communication unit 43 shown in Fig. 1, respectively.

[0070] In this embodiment, the cloud server 11 derives the life of the battery 141 (third life EoL_t or remaining life SoL) according to the usage mode of the electric device 113, while taking into consideration the characteristics of the battery 141 such as safety.

[0071] FIG. 8 is a flowchart showing the flow of the process executed by the data processing unit 22 of the cloud server 11 to calculate the remaining life SoL of the electric device 113.

[0072] When the cloud server 11 receives a request to calculate the remaining life SoL for a certain electric device 113 from the local PC 12, first, in step S01, the battery information acquisition unit 52 acquires specification information indicating the specifications of the electric device 113 from the local PC 12 or from a database provided by an electric appliance manufacturer, etc. The specifications of the electric device 113 include information indicating the type (model number, etc.) of the battery 141 mounted in the electric device 113.

[0073] Next, in step S02, the battery information acquisition unit 52 accesses the battery information database 15 to acquire the second life EoL_b and the initial capacity FCC_init for the battery 141 of the type identified in step S01 from the battery information database 15. The battery information acquisition unit 52 inputs the acquired second life EoL_b and initial capacity FCC_init to the SoL calculation unit 55 as data D2.

[0074] Next, in step S03, the plan information acquisition unit 51 acquires the usage plan information for the target electrical appliance 113, which is received from the local PC 12 and stored in the storage unit 23, by reading it from the storage unit 23. Furthermore, the plan information acquisition unit 51 acquires a required capacity FCC_u for the target electrical appliance 113 based on the usage plan information, and inputs the required capacity FCC_u as data D1 to the SoL calculation unit 55. Note that, if the usage plan information for the target electrical appliance 113 has not been created, the plan information acquisition unit 51 may receive usage history information of the electrical appliance 113 from the electrical appliance 113 via the communication network 14, and estimate a future usage plan from a transition trend of the amount of power consumption in the past included in the usage history information.

[0075] Next, in step S04, the EoL_u calculation unit 551 calculates the first life EoL_u of the battery 141 by performing the calculation shown in the above equation (1) based on the initial capacity FCC_init input as data D2 from the battery information acquisition unit 52 and the required capacity FCC_u input as data D1 from the plan information acquisition unit 51.

[0076] Next, in step S05, the EoL_t derivation unit 552 derives the third life EoL_t of the battery 141 by performing the calculation shown in the above equation (2) based on the first life EoL_u input from the EoL_u calculation unit 551 and the second life EoL_b input as data D2 from the battery information acquisition unit 52.

[0077] Next, in step S06, the log information acquiring unit 53 acquires log information from the target electric device 113 via the communication network 14. The log information includes usage history information of the electric device 113 and charge / discharge history information of the battery 141. The log information acquiring unit 53 inputs the acquired log information to the SoL calculation unit 55 as data D3.

[0078] Next, in step S 07 , the SoH calculation unit 553 calculates the deterioration level SoH of the battery 141 based on the charge / discharge history information of the battery 141 from the log information input from the log information acquisition unit 53 .

[0079] Next, in step S08, the SoL calculation unit 554 calculates the remaining life SoL of the battery 141 by performing the calculation shown in the above equation (3) based on the third life EoL_t input from the EoL_t derivation unit 552 and the deterioration level SoH input from the SoH calculation unit 553.

[0080] Next, in step S09, the SoL calculation unit 554 outputs the remaining life SoL calculated in step S08. The remaining life SoL output from the SoL calculation unit 554 is transmitted to the local PC 12 via the communication network 14, and information indicating the remaining life of the target electrical appliance 113 is displayed on the display unit 31. Alternatively, the remaining life SoL output from the SoL calculation unit 554 may be transmitted to the target electrical appliance 113 via the communication network 14, and information indicating the remaining life of the electrical appliance 113 may be displayed on a display visible to the user of the electrical appliance 113. Note that the manner of presenting the information indicating the remaining life may be, in addition to the above display, audio output, or the like.

[0081] According to this embodiment, the data processing unit 22 of the cloud server 11 (information processing device) calculates the first life EoL_u based on the required capacity FCC_u indicating the power consumption per unit of use (per charge) of the electric device 113 and the initial capacity FCC_init of the battery 141. The data processing unit 22 also acquires the second life EoL_b set according to the characteristics of the battery 141 such as safety. Then, the data processing unit 22 derives the shorter of the first life EoL_u and the second life EoL_b as the life (third life EoL_t) of the battery 141. Therefore, the life of the battery 141 can be derived according to the usage mode of the electric device 113 while ensuring safety. As a result, it is possible to achieve both reduction in total cost and ensuring safety. [Industrial Applicability]

[0082] The technology according to the present disclosure is particularly useful for technology to derive the lifespan of a battery in any electric device such as an EV that is powered by a battery.

Claims

1. An information processing device, obtaining power consumption information indicating information corresponding to the amount of power consumed per unit of use of the electrical device driven by the battery; obtaining initial capacity information indicating an initial capacity of the battery; Calculating a first life span of the battery based on the power consumption information and the initial capacity information; obtaining a second life of the battery that is set according to a characteristic of the battery; outputting the shorter of the first life and the second life as a third life of the battery; Information processing methods.

2. the electrical device is a moving object including a motor driven by the battery, The information processing device includes: acquiring movement information of the moving object as the power consumption information; calculating the power consumption amount based on travel distance information of the moving object per unit of use included in the travel information; The information processing method according to claim 1 .

3. The information processing device includes: acquiring deterioration information indicating a deterioration level of the battery; Calculating a remaining life of the battery based on the third life and the deterioration degree; outputting the remaining lifespan; The information processing method according to claim 2 .

4. The information processing device includes: calculating the remaining life based on a difference between a deterioration degree corresponding to the third life and the deterioration degree indicated by the deterioration information; The information processing method according to claim 3.

5. The information processing device includes: causing a presentation device to present the third life span or the remaining life span; 5. The information processing method according to claim 3.

6. The information processing device includes: acquiring movement history information or movement plan information of the moving object as the movement information; The information processing method according to any one of claims 2 to 5.

7. a first acquisition unit that acquires power consumption information indicating information corresponding to a power consumption amount per usage unit of an electrical device driven by a battery; A second acquisition unit that acquires initial capacity information indicating an initial capacity of the battery; a calculation unit that calculates a first life span of the battery based on the power consumption information and the initial capacity information; a third acquisition unit that acquires a second life of the battery that is set according to a characteristic of the battery; an output unit that outputs the shorter of the first life and the second life as a third life of the battery; An information processing system comprising:

Images