Information processing method and information processing system

Abstract

The information processing device performs the following steps: acquiring power consumption information, which represents information corresponding to the power consumption of a battery-powered electrical device in each utilization unit; acquiring initial capacity information representing the initial capacity of the battery; calculating a first lifespan of the battery based on the power consumption information and the initial capacity information; acquiring a second lifespan of the battery set according to the characteristics of the battery; and outputting the shorter of the first lifespan and the second lifespan as a third lifespan of the battery.

Description

Technical Field

[0001] This invention relates to information processing methods and information processing systems. Background Technology

[0002] Patent Document 1 below discloses a technique for calculating information about the lifespan of a battery (e.g., battery capacity or replacement period) based on the detection results of the battery state.

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

[0004] Existing technical documents

[0005] Patent documents

[0006] Patent Document 1: Japanese Patent Publication No. 2018-54488 Summary of the Invention

[0007] The purpose of this invention is to provide a technique that can calculate the lifespan of a battery used to drive an electrical device based on how the device is used, while ensuring safety.

[0008] An embodiment of the present invention relates to an information processing method that causes an information processing device to perform the following steps: acquiring power consumption information, the power consumption information representing information corresponding to the power consumption of a battery-driven electrical device in each utilization unit; acquiring initial capacity information representing the initial capacity of the battery; calculating a first lifespan of the battery based on the power consumption information and the initial capacity information; acquiring a second lifespan of the battery set according to the characteristics of the battery; and outputting the shorter of the first lifespan and the second lifespan as a third lifespan of the battery. Attached Figure Description

[0009] Figure 1 This is a block diagram illustrating the structure of the information processing system according to the first embodiment of the present invention.

[0010] Figure 2 This is a block diagram representing the functions of the data processing department.

[0011] Figure 3 This is a block diagram representing the structure of the SoL computation unit.

[0012] Figure 4 This is a simplified representation of a planned travel distance.

[0013] Figure 5 This is a flowchart representing the processing flow performed by the data processing department.

[0014] Figure 6This is a diagram illustrating an example of how remaining lifespan can be represented.

[0015] Figure 7 This is a block diagram illustrating the structure of the information processing system according to the second embodiment of the present invention.

[0016] Figure 8 This is a flowchart representing the processing flow performed by the data processing department. Detailed Implementation

[0017] (Basic knowledge of this invention)

[0018] Goods purchased via mail order using the internet are delivered to customers' homes by delivery companies. These companies use multiple vans to deliver goods within their designated delivery areas. It is anticipated that with the increasing prevalence of battery-powered electric vehicles (EVs), the number of delivery companies using EV vans will rise.

[0019] EV battery degradation occurs based on the total mileage driven since the vehicle was new. The degree of battery degradation is generally indicated by SoH (State of Health). If the SoH drops to the lower limit of acceptable values ​​compared to the initial value when the vehicle was new, the EV (or battery) is considered to have reached the end of its lifespan, and replacement with a new EV (or battery) is recommended. Typically, the lower limit is set uniformly by battery manufacturers or vehicle manufacturers, for example, "80%".

[0020] However, depending on the type of EV, its usage varies greatly. Sometimes, even after the battery's SoH (Solar Hysteresis) drops below a uniformly permissible lower limit, continuing to use the EV is not a practical problem. For example, for EVs primarily used for short-distance driving and with frequent battery charging, the power consumption per charge is low, and the required SoH is small. Therefore, even if the SoH drops below the permissible lower limit, practical use is not an issue. Instead of replacing the EV with a new one every time the SoH drops below the uniformly permissible lower limit, the replacement cycle of the EV is extended by continuing to use the EV even after the SoH drops below the permissible lower limit. As a result, the total cost of ownership (TCO) can be reduced over a long period (e.g., 10 years). On the other hand, from a safety perspective, it is not preferable to continue using the battery beyond the limits set based on battery characteristics such as safety. Therefore, in order to balance reducing TCO and ensuring safety, it is important to consider both battery characteristics such as safety and to assess battery lifespan individually based on the EV's usage.

[0021] The encoder device disclosed in Patent Document 1 includes a position detection unit for detecting position information of a moving part, a battery for supplying power to the position detection unit, a battery detection unit for detecting the state of the battery, and a calculation unit for calculating battery life information based on the detection results of the battery detection unit. The battery life information includes at least one of the following: the time until the battery reaches its discharge termination voltage, the remaining battery charge, the time during which the position detection unit can operate using power supplied from the battery, and the period during which the power supplied from the battery is insufficient relative to the power consumed by the position detection unit.

[0022] However, Patent Document 1 does not disclose any content regarding determining battery lifespan by considering both battery characteristics such as safety and the way electrical equipment is used.

[0023] In order to solve the aforementioned problem, the inventors obtained the insight that by calculating the first lifespan of a battery according to the usage of electrical equipment and obtaining the second lifespan of a battery corresponding to battery characteristics such as safety, and deriving the battery lifespan based on this information, it is possible to balance reducing TCO and ensuring safety, and thus the present invention was conceived.

[0024] Next, various embodiments of the present invention will be described.

[0025] An embodiment of the present invention relates to an information processing method that causes an information processing device to perform the following steps: acquiring power consumption information, the power consumption information representing information corresponding to the power consumption of a battery-driven electrical device in each utilization unit; acquiring initial capacity information representing the initial capacity of the battery; calculating a first lifespan of the battery based on the power consumption information and the initial capacity information; acquiring a second lifespan of the battery set according to the characteristics of the battery; and outputting the shorter of the first lifespan and the second lifespan as a third lifespan of the battery.

[0026] According to this configuration, the information processing device calculates a first lifespan based on the power consumption of each unit of the electrical equipment 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 lifespans as the battery lifespan (third lifespan). Therefore, it is possible to derive the battery lifespan based on the usage of the electrical equipment while ensuring safety. As a result, it is possible to balance reducing overall cost with ensuring safety.

[0027] In this manner, the electrical device is a mobile body equipped with a motor driven by the battery, and the information processing device further performs the following steps: acquiring the movement information of the mobile body as the power consumption information; and calculating the power consumption based on the movement distance information of the mobile body in each utilization unit contained in the movement information.

[0028] According to this configuration, the lifespan management of the EV or the battery mounted on it can be appropriately performed based on the mobility information of the electric vehicle (EV) as a mobile entity.

[0029] In the aforementioned manner, the information processing device further performs the following steps: acquiring degradation information representing the degree of degradation of the battery; and calculating the remaining lifespan of the battery based on the third lifespan and the degree of degradation; and outputting the remaining lifespan.

[0030] According to this configuration, the remaining lifespan of the battery mounted on the mobile body can be derived based on the way the mobile body is used, while ensuring safety.

[0031] In this manner, the information processing device calculates the remaining lifetime based on the difference between the degree of degradation corresponding to the third lifetime and the degree of degradation indicated by the degradation information.

[0032] Based on this configuration, the remaining lifespan can be calculated by comparing the degree of degradation.

[0033] In this manner, the information processing device causes the prompting device to indicate the third lifespan or the remaining lifespan.

[0034] According to this configuration, by having the indicator device display the third lifespan or remaining lifespan, the user can understand the battery's lifespan for each usage method. In particular, when displaying the remaining lifespan, information that is easily and intuitively understood by the user can be provided.

[0035] In this method, the information processing device acquires the mobile body's movement history information or movement plan information as the movement information.

[0036] According to this structure, by utilizing the mobility planning information itself, or by inferring future mobility planning information based on past mobility history information, mobility information as power consumption information can be obtained.

[0037] An embodiment of the present invention relates to an information processing system comprising: a first acquisition unit for acquiring power consumption information, the power consumption information representing information corresponding to the power consumption of a battery-powered electrical device in each utilization unit; a second acquisition unit for acquiring initial capacity information representing the initial capacity of the battery; a calculation unit for calculating a first lifespan of the battery based on the power consumption information and the initial capacity information; a third acquisition unit for acquiring a second lifespan of the battery set according to the characteristics of the battery; and an output unit for outputting the shorter of the first lifespan and the second lifespan as a third lifespan of the battery.

[0038] According to this configuration, the calculation unit calculates a first lifespan based on the power consumption of each user unit of the electrical equipment and the initial capacity of the battery, the third acquisition unit acquires a second lifespan set according to battery characteristics such as safety, and the output unit outputs the shorter of these lifespans as the battery lifespan (third lifespan). Therefore, the battery lifespan can be derived based on the usage of the electrical equipment while ensuring safety. As a result, it is possible to balance reducing overall cost and ensuring safety.

[0039] The general or specific embodiments of the present invention described above can be implemented as a system, apparatus, method, integrated circuit, computer program, or any combination thereof. Furthermore, needless to say, the computer program can be distributed as a computer-readable non-volatile storage medium such as a CD-ROM, or through a communication network such as the Internet.

[0040] The embodiments described below represent specific examples of the present invention. The numerical values, shapes, constituent elements, steps, and order of steps shown in the following embodiments are examples and are not intended to limit the present invention. Furthermore, in the constituent elements of the following embodiments, constituent elements not described in the independent claims representing the highest-level concept are described as arbitrary constituent elements. Moreover, in all embodiments, the various elements may be combined.

[0041] Hereinafter, embodiments of the present invention will be described in detail using the accompanying drawings. Furthermore, elements labeled with the same reference numerals in different drawings represent the same or corresponding elements.

[0042] (First Implementation)

[0043] Figure 1This is a block diagram illustrating the structure of an information processing system 1 according to a first embodiment of the present invention. In this embodiment, the information processing system 1 is constructed as a management system for a delivery company that delivers goods to customers' homes via electric vehicles (EVs). This delivery company, as an example, has multiple branches responsible for various delivery areas and a head office that centrally manages these branches. Local PCs 12 are installed at the head office and each branch, and are connected to a cloud server 11. Furthermore, each branch is equipped with multiple delivery vehicles 13. The cloud server 11, local PCs 12, and vehicles 13 can communicate with each other via any communication network 14, such as an IP network. Furthermore, a battery information database 15 is connected to the communication network 14. The battery information database 15 stores battery information representing the specifications of the battery 41, provided by battery manufacturers or solution providers. The specifications include at least the initial capacity FCC_init and the second lifespan EoL_b, which will be described later. The cloud server 11 can access the battery information database 15 via the communication network 14. In this embodiment, the moving body is a vehicle, but it is not limited to this. For example, the mobile body can be an aircraft such as an unmanned aerial vehicle, a ship, or a mobile robot.

[0044] 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 (LCD) or an organic EL display, etc. The data processing units 22 and 32 are processors such as CPUs. The storage units 23 and 33 are HDDs or SSDs, etc. The communication units 24 and 34 are communication modules that perform data communication according to communication standards such as IP. The input unit 35 is a mouse or keyboard, etc.

[0045] Vehicle 13 is an EV truck, etc., and includes a battery 41, a control unit 42, and a communication unit 43. Battery 41 is a secondary battery such as a lithium-ion battery used to drive the drive motor mounted on vehicle 13. Control unit 42 is a BMS (Battery Management System) used for controlling the operation and managing the state of battery 41. Communication unit 43 is a communication module that performs data communication according to communication standards such as IP.

[0046] Furthermore, the application of the information processing system 1 involved in this embodiment is not limited to delivery services, but can also be any business such as taxi services, car rental services, car sharing services, or chauffeur services that use multiple EVs for operation.

[0047] Figure 2 This is a block diagram illustrating the functions of the data processing unit 22 of the cloud server 11. For example... Figure 2As shown, the data processing unit 22 includes a plan information acquisition unit 51, a battery information acquisition unit 52, a log information acquisition unit 53, and a SoL calculation unit 55. These functions can be implemented as software by the CPU executing programs read from ROM or the like.

[0048] Figure 3 This is a block diagram showing the structure of the SoL computation unit 55. For example... Figure 3 As shown in the connection relationship, the SoL calculation unit 55 includes the EoL_u operation unit 551, the EoL_t derivation unit 552, the SoH operation unit 553, and the SoL operation unit 554.

[0049] The EoL_u calculation unit 551 calculates the first lifespan EoL_u of the battery 41 based on the initial capacity FCC_init input from the battery information acquisition unit 52 and the necessary capacity FCC_u input from the planning 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 battery manufacturer, etc. The necessary capacity FCC_u is power consumption information representing the power consumption of each utilization unit (per charge) of each vehicle 13, calculated according to the usage pattern of each vehicle 13. The first lifespan EoL_u is the lifespan (End of Life) calculated according to the usage pattern of each vehicle 13. The EoL_u calculation unit 551 calculates the first lifespan EoL_u of the battery 41.

[0050] EoL_u=(FCC_u / FCC_init)×100 (1),

[0051] Calculate the first lifetime EoL_u.

[0052] The EoL_t derivation unit 552 derives a third lifespan EoL_t, which is the lifespan of the battery 41, based on the first lifespan EoL_u input from the EoL_u calculation unit 551 and the second lifespan EoL_b input from the battery information acquisition unit 52. The second lifespan EoL_b is a limit value set by the battery 41 manufacturer or analysis company based on battery characteristics such as safety. The EoL_t derivation unit 552 performs calculations...

[0053] EoL_t=max(EoL_u,EoL_b) (2),

[0054] The lifetime of the larger of the first lifetime EoL_u and the second lifetime EoL_b (that is, the lifetime of the shorter lifetime) is derived as the third lifetime EoL_t.

[0055] The SoH calculation unit 553 calculates the degradation degree SoH of the battery 41 based on the charging and discharging history information of the battery 41 in the log information input from the log information acquisition unit 53.

[0056] The SoL calculation unit 554 calculates the remaining lifespan SoL of the battery 41 based on the third lifespan EoL_t input from the EoL_t derivation unit 552 and the degradation degree SoH input from the SoH calculation unit 553. The remaining lifespan SoL is a degradation index (State of Life) that normalizes the degradation degree SoH using the third lifespan EoL_t. The SoL calculation unit 554 calculates...

[0057] (SoH-EoL_t) / (100-EoL_t)×100 (3),

[0058] Calculate the remaining lifetime SoL and output the calculated remaining lifetime SoL.

[0059] Figure 4 This is a simplified diagram illustrating an example of a driving plan established by a business location. For each of the multiple vehicles 13 (four vehicles A through D in this example), a planned daily driving distance (km / day) is set for each year. This planned driving distance is the optimal value calculated using a prescribed predictive model, based on the business location's long-term business plan, the degradation characteristics of battery 41 relative to the total driving distance, and cost information including driver personnel expenses and vehicle purchase costs. The predictive model can be derived using machine learning with artificial intelligence. The algorithm for the predictive model can use path optimization using linear programming, neural networks, or multiple regression analysis, etc.

[0060] Reference Figure 4 Therefore, even for the same vehicle 13, the planned mileage increases or decreases significantly each year (e.g., for vehicle C). Furthermore, the graph for vehicle A disappears after 6 years, indicating that vehicle A will be sold (scrapped) 6 years later. Conversely, the graph for vehicle C reappears after 3 years, indicating that vehicle C will be purchased 3 years later.

[0061] Figure 4 The driving plan information shown is sent 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 can also be created by the cloud server 11. The plan information acquisition unit 51 obtains the necessary capacity FCC_u for each vehicle 13 based on the driving plan information read from the storage unit 23. If it is assumed that each vehicle 13 is charged daily at the business office, then, for example, the necessary capacity FCC_u for vehicle A at present (0 years from now) is equivalent to the capacity for driving 60km. The plan information acquisition unit 51 inputs the necessary capacity FCC_u for each vehicle 13, obtained by converting the planned driving distance into electricity consumption, as data D1 into the SoL calculation unit 55.

[0062] Figure 5This is a flowchart illustrating the process performed by the data processing unit 22 of the cloud server 11 to calculate the remaining lifetime (SoL) of the EV.

[0063] If the cloud server 11 receives a calculation request for the remaining life (SoL) of a vehicle 13 from the local PC 12, then in step S01, the battery information acquisition unit 52 first obtains EV specification information representing the specifications of the vehicle 13 from the local PC 12 or a database provided by the automobile manufacturer, etc. The specifications of the vehicle 13 include information indicating the type (model, etc.) of the battery 41 installed in the vehicle 13.

[0064] Next, in step S02, the battery information acquisition unit 52 accesses the battery information database 15 and retrieves the second lifespan EoL_b and initial capacity FCC_init related to the type of battery 41 determined in step S01. The battery information acquisition unit 52 inputs the retrieved second lifespan EoL_b and initial capacity FCC_init as data D2 into the SoL calculation unit 55.

[0065] Next, in step S03, the planning information acquisition unit 51 acquires the driving plan information of the target vehicle 13 by reading from the storage unit 23. Furthermore, based on this driving plan information, the planning information acquisition unit 51 acquires the necessary capacity FCC_u for the target vehicle 13 and inputs this necessary capacity FCC_u as data D1 into the SoL calculation unit 55. Alternatively, if no driving plan information for the target vehicle 13 is created, the planning information acquisition unit 51 can also receive the driving history information of the vehicle 13 from the vehicle 13 via the communication network 14, and predict future driving plans based on the past driving distance trends contained in the driving history information.

[0066] Next, in step S04, the EoL_u calculation unit 551 calculates the first lifespan EoL_u of the battery 41 by performing the calculation shown in equation (1) based on the initial capacity FCC_init input from the battery information acquisition unit 52 as data D2 and the necessary capacity FCC_u input from the planning information acquisition unit 51 as data D1.

[0067] Next, in step S05, the EoL_t derivation unit 552 derives the third lifespan EoL_t of the battery 41 by performing the operation shown in equation (2) based on the first lifespan EoL_u input from the EoL_u calculation unit 551 and the second lifespan EoL_b input as data D2 from the battery information acquisition unit 52.

[0068] 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 the driving history information of the vehicle 13 and the charging and discharging history information of the battery 41. The log information acquisition unit 53 inputs the acquired log information as data D3 into the SoL calculation unit 55.

[0069] Next, in step S07, the SoH calculation unit 553 calculates the degradation degree SoH of the battery 41 based on the charge and discharge history information of the battery 41 in the log information input from the log information acquisition unit 53.

[0070] Next, in step S08, the SoL calculation unit 554 calculates the remaining lifespan SoL of the battery 41 by performing the calculation shown in equation (3) based on the third lifespan EoL_t input from the EoL_t derivation unit 552 and the degradation degree SoH input from the SoH calculation unit 553.

[0071] Next, in step S09, the SoL calculation unit 554 outputs the remaining lifespan SoL calculated in step S08. The remaining lifespan SoL output from the SoL calculation unit 554 is sent to the local PC 12 via the communication network 14, and the information indicating the remaining lifespan of the target vehicle 13 is displayed on the display unit 31. Alternatively, the remaining lifespan SoL output from the SoL calculation unit 554 can also be sent to the target vehicle 13 via the communication network 14, and the information indicating the remaining lifespan of the vehicle 13 is displayed on a display visible to the driver of the vehicle 13. In addition to the aforementioned display method, the remaining lifespan information can also be displayed via voice output, etc. Furthermore, a third lifespan EoL_t can be displayed instead of the remaining lifespan SoL or based on the remaining lifespan SoL.

[0072] According to this embodiment, the data processing unit 22 of the cloud server 11 (information processing device) calculates a first lifespan EoL_u based on the necessary capacity FCC_u representing the power consumption of each utilization unit of the vehicle 13 (per charge) and the initial capacity FCC_init of the battery 41. Furthermore, the data processing unit 22 obtains a second lifespan EoL_b set according to the characteristics of the battery 41, such as safety. The data processing unit 22 then derives the shorter of the first lifespan EoL_u and the second lifespan EoL_b as the lifespan of the battery 41 (a third lifespan EoL_t). Therefore, the lifespan of the battery 41 can be derived according to the utilization mode of the vehicle 13 while ensuring safety. As a result, both reducing overall cost and ensuring safety can be achieved.

[0073] Furthermore, according to this embodiment, the lifespan management of the EV or the battery 41 mounted on it can be appropriately performed based on the driving information (driving plan information or driving history information) of the EV as a mobile entity.

[0074] Furthermore, according to this embodiment, the remaining lifespan SoL of the battery 41 mounted on the EV can be derived based on the EV's utilization method while ensuring safety.

[0075] Furthermore, according to this embodiment, the remaining lifetime SoL is calculated by comparing the degradation degree from the perspective of degradation degree by calculating the difference between the degradation degree corresponding to the third lifetime EoL_t and the degradation degree SoH.

[0076] Furthermore, according to this embodiment, by displaying the third lifespan EoL_t or remaining lifespan SoL on the display device (display unit 31, etc.), the user can understand the lifespan of the battery 41 for each usage mode. In particular, when the remaining lifespan SoL is displayed, information that is easy for the user to understand intuitively can be provided.

[0077] Figure 6 This is a diagram illustrating an example of how the remaining lifetime (SoL) is displayed. Figure 6 The results for six vehicles A through F are shown. The left graph shows the display of the degradation level SoH using battery 41, and the right graph shows the display of the remaining life SoL using the degradation level SoH from the left graph, normalized by the third life EoL_t. Additionally, examples are shown where the third life EoL_t for vehicles A through C is 80%, and for vehicles D through F it is 70%. For example, if we focus on vehicle F, the current degradation level SoH is 90%, and the third life EoL_t is 70%, therefore, the remaining life SoL is (90-70) / (100-70)×100=66%. Based on the display of the remaining life SoL (right graph), users can intuitively understand that if the value on the vertical axis drops to 0%, then vehicle 13 has reached the end of its lifespan.

[0078] Furthermore, according to this embodiment, the data processing unit 22 acquires the vehicle 13's driving plan information or driving history information as driving information (power consumption information). By utilizing the driving plan information itself, or by inferring future driving plan information based on past driving history information, driving information as power consumption information can be appropriately acquired.

[0079] (Second Implementation)

[0080] In the first embodiment, the cloud server 11 calculates the remaining lifespan SoL of the battery 41 for a battery-powered EV, but is not limited to this example. The cloud server 11 may also calculate the remaining lifespan of the battery for any battery-powered electrical device. Such electrical devices are, for example, energy storage devices. Furthermore, energy storage devices may also have a power generation function. The usage plan information for the electrical device can be formulated as power consumption information representing the total power consumption of the battery. When the usage plan information is unclear, the plan information acquisition unit 51 may also infer the usage plan information based on historical information representing the past usage of the electrical device or battery, according to its tendencies.

[0081] Figure 7 This is a block diagram illustrating the structure of the information processing system 1 according to the second embodiment of the present invention. Figure 1 The vehicle 13 shown is replaced with an electrical device 113. The electrical device 113 includes a battery 141, a control unit 142, and a communication unit 143. The battery 141, control unit 142, and communication unit 143 respectively correspond to… Figure 1 The battery 41, control unit 42, and communication unit 43 are shown.

[0082] In this embodiment, the cloud server 11 derives the lifespan (third lifespan EoL_t or remaining lifespan SoL) of the battery 141 separately based on the usage of the electrical equipment 113, taking into account the characteristics of the battery 141 such as safety.

[0083] Figure 8 This is a flowchart illustrating the process performed by the data processing unit 22 of the cloud server 11 to calculate the remaining lifespan (SoL) of the electrical equipment 113.

[0084] If the cloud server 11 receives a calculation request from the local PC 12 regarding the remaining life (SoL) of a certain electrical device 113, then in step S01, the battery information acquisition unit 52 first obtains specification information representing the specifications of the electrical device 113 from a database provided by the local PC 12 or the electrical device manufacturer, etc. The specifications of the electrical device 113 include information indicating the type (model, etc.) of the battery 141 installed in the electrical device 113.

[0085] Next, in step S02, the battery information acquisition unit 52 accesses the battery information database 15 and retrieves the second lifespan EoL_b and initial capacity FCC_init related to the type of battery 141 determined in step S01. The battery information acquisition unit 52 inputs the retrieved second lifespan EoL_b and initial capacity FCC_init as data D2 into the SoL calculation unit 55.

[0086] Next, in step S03, the planning information acquisition unit 51 acquires the usage plan information for the target electrical equipment 113 received from the local PC 12 and stored in the storage unit 23 by reading from the storage unit 23. Furthermore, based on this usage plan information, the planning information acquisition unit 51 acquires the necessary capacity FCC_u for the target electrical equipment 113 and inputs this necessary capacity FCC_u as data D1 into the SoL calculation unit 55. Alternatively, if no usage plan information for the target electrical equipment 113 is created, the planning information acquisition unit 51 can also receive the usage history information of the electrical equipment 113 from the electrical equipment 113 via the communication network 14, and predict future usage plans based on past electricity consumption trends contained in the usage history information.

[0087] Next, in step S04, the EoL_u calculation unit 551 calculates the first lifespan EoL_u of the battery 141 by performing the calculation shown in equation (1) based on the initial capacity FCC_init input from the battery information acquisition unit 52 as data D2 and the necessary capacity FCC_u input from the planning information acquisition unit 51 as data D1.

[0088] Next, in step S05, the EoL_t derivation unit 552 derives the third lifespan EoL_t of the battery 141 by performing the operation shown in equation (2) based on the first lifespan EoL_u input from the EoL_u calculation unit 551 and the second lifespan EoL_b input as data D2 from the battery information acquisition unit 52.

[0089] Next, in step S06, the log information acquisition unit 53 acquires log information from the target electrical device 113 via the communication network 14. The log information includes usage history information of the electrical device 113 and charge / discharge history information of the battery 141. The log information acquisition unit 53 inputs the acquired log information as data D3 into the SoL calculation unit 55.

[0090] Next, in step S07, the SoH calculation unit 553 calculates the degradation degree SoH of the battery 141 based on the charge and discharge history information of the battery 141 in the log information input from the log information acquisition unit 53.

[0091] Next, in step S08, the SoL calculation unit 554 calculates the remaining lifespan SoL of the battery 141 by performing the calculation shown in equation (3) based on the third lifespan EoL_t input from the EoL_t derivation unit 552 and the degradation degree SoH input from the SoH calculation unit 553.

[0092] Next, in step S09, the SoL calculation unit 554 outputs the remaining lifespan SoL calculated in step S08. The remaining lifespan SoL output from the SoL calculation unit 554 is sent to the local PC 12 via the communication network 14, and the information indicating the remaining lifespan of the target electrical device 113 is displayed on the display unit 31. Alternatively, the remaining lifespan SoL output from the SoL calculation unit 554 can also be sent to the target electrical device 113 via the communication network 14, and the information indicating the remaining lifespan of the electrical device 113 can be displayed on a user-visible display of the electrical device 113. In addition to the above-described display method, the remaining lifespan information can also be displayed via voice output, etc.

[0093] According to this embodiment, the data processing unit 22 of the cloud server 11 (information processing device) calculates a first lifespan EoL_u based on the necessary capacity FCC_u representing the power consumption of each utilization unit (per charge) of the electrical device 113 and the initial capacity FCC_init of the battery 141. Furthermore, the data processing unit 22 obtains a second lifespan EoL_b set according to the characteristics of the battery 141, such as safety. The data processing unit 22 then derives the shorter of the first lifespan EoL_u and the second lifespan EoL_b as the lifespan of the battery 141 (a third lifespan EoL_t). Therefore, the lifespan of the battery 141 can be derived based on the utilization method of the electrical device 113 while ensuring safety. As a result, both reduced overall cost and ensured safety can be achieved.

[0094] Industrial availability

[0095] The technology involved in this invention is particularly valuable as a technique for extending the lifespan of batteries in any electrical device such as a battery-powered EV.

Claims

1. An information processing method, characterized in that, Instruct the information processing device to perform the following steps: Acquire power consumption information, which represents information corresponding to the power consumption of battery-powered electrical equipment in each utilization unit; Obtain initial capacity information representing the initial capacity of the battery; Based on the power consumption information and the initial capacity information, the first lifespan of the battery is calculated; Obtain a second lifespan of the battery, which is set according to the characteristics of the battery; as well as, The shorter of the first lifespan and the second lifespan is output as the third lifespan of the battery.

2. The information processing method according to claim 1, characterized in that, The electrical device is a moving body equipped with a motor driven by the battery. The information processing device also performs the following steps: The movement information of the mobile body is obtained as the power consumption information; and, The power consumption is calculated based on the distance traveled by the mobile body in each utilization unit, which is included in the mobile information.

3. The information processing method according to claim 2, characterized in that, The information processing device also performs the following steps: Obtain degradation information representing the degree of degradation of the battery; and, Based on the third lifetime and the degree of degradation, the remaining lifetime of the battery is calculated; Output the remaining lifetime.

4. The information processing method according to claim 3, characterized in that, The information processing device calculates the remaining lifetime based on the difference between the degree of degradation corresponding to the third lifetime and the degree of degradation shown in the degradation information.

5. The information processing method according to claim 3 or 4, characterized in that, The information processing device causes the prompting device to indicate the third lifespan or the remaining lifespan.

6. The information processing method according to any one of claims 2 to 4, characterized in that, The information processing device acquires the mobile body's movement history information or movement plan information as the movement information.

7. The information processing method according to claim 5, characterized in that, The information processing device acquires the mobile body's movement history information or movement plan information as the movement information.

8. An information processing system, characterized in that... include: The first acquisition unit acquires power consumption information, which represents information corresponding to the power consumption of the battery-powered electrical equipment in each utilization unit. The second acquisition unit acquires initial capacity information representing the initial capacity of the battery; The computing unit calculates the first lifespan of the battery based on the power consumption information and the initial capacity information; The third acquisition unit acquires a second lifespan of the battery, which is set according to the characteristics of the battery. as well as, The output unit outputs the shorter of the first lifespan and the second lifespan as the third lifespan of the battery.

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