Information processing device, program, and information processing method

Abstract

To provide technique capable of presenting degradation information related to the rate of deterioration of batteries installed in an electrical device to a user.SOLUTION: An information processor includes: a status information acquisition unit that acquires status information representing the status of the battery mounted on electrical equipment, which is driven by the battery; a related information acquisition unit that acquires related information representing the relation between the status of the battery and the deterioration rate thereof; a degradation information derivation unit that derives degradation information related to the deterioration rate of the battery on the basis of the degradation information and the related information; and an output unit that outputs the degradation information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device, a program, and an information processing method. [Background technology]

[0002] Patent Document 1 below discloses a technique for estimating the degradation state of a battery mounted on an electric vehicle. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Special Publication No. 2017-509103 Summary of the Invention [Problem to be solved by the invention]

[0004] The technology disclosed in Patent Document 1 can present the user with the state of battery deterioration, such as SOH. However, because SOH is merely information resulting from battery deterioration, the user cannot easily understand from the SOH how their driving style directly affects battery deterioration.

[0005] The present disclosure provides a technique capable of presenting to a user degradation information relating to the rate at which degradation of a battery mounted in an electrical device progresses (degradation rate). [Means for solving the problem]

[0006] An information processing device according to one aspect of the present disclosure includes a status information acquisition unit that acquires status information indicating the status of a battery installed in an electrical device powered by the battery, a related information acquisition unit that acquires related information indicating the relationship between the status of the battery and the deterioration rate of the battery, a deterioration information derivation unit that derives deterioration information related to the deterioration rate of the battery based on the status information and the related information, and an output unit that outputs the deterioration information. [Effects of the Invention]

[0007] According to the present disclosure, it is possible to present deterioration information relating to the rate of deterioration of a battery mounted in an electrical device. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a block diagram showing a configuration of an information processing device according to a first embodiment of the present disclosure. [Figure 2] FIG. 1 is a simplified diagram illustrating an example of a three-dimensional data map. [Figure 3] 10 is a flowchart showing the flow of processing executed by the information processing device. [Figure 4] FIG. 10 is a diagram showing an example of ΔSOH displayed on a display unit. [Figure 5] FIG. 10 is a block diagram showing a configuration of an information processing device according to a second embodiment of the present disclosure. [Figure 6] FIG. 1 is a simplified diagram illustrating an example of a three-dimensional data map. [Figure 7] 10 is a flowchart showing the flow of processing executed by the information processing device. [Figure 8] 10A and 10B are diagrams illustrating examples of displaying the main causes of deterioration on a display unit. [Figure 9] 10 is a flowchart showing the flow of processing executed by the information processing device. [Figure 10] 10 is a flowchart showing the flow of processing executed by the information processing device. [Figure 11] FIG. 10 is a simplified diagram showing a two-dimensional data map as an example of related information. [Figure 12] FIG. 10 is a block diagram showing a configuration of an information processing device according to a third embodiment of the present disclosure. [Figure 13A] 10 is a flowchart showing the flow of processing executed by the information processing device. [Figure 13B] 10 is a flowchart showing the flow of processing executed by the information processing device. [Figure 14] 10A and 10B are diagrams illustrating an example of a remaining battery life displayed on a display unit. [Figure 15] FIG. 10 is a block diagram showing a configuration of an information processing device according to a fourth embodiment of the present disclosure. [Figure 16] FIG. 10 is a simplified diagram showing a two-dimensional data map as an example of related information. [Figure 17] 10 is a flowchart showing the flow of processing executed by the information processing device. DETAILED DESCRIPTION OF THE INVENTION

[0009] (Findings that formed the basis of this disclosure) Electric vehicles equipped with a battery-powered traction motor are becoming increasingly popular. Batteries deteriorate according to the total distance traveled by the vehicle. The SOH (State of Health) is generally used as an indicator of the battery's deterioration state. Vehicles that display the battery's SOH on a display visible to the driver are also in practical use.

[0010] The above-mentioned Patent Document 1 discloses a device for estimating the state of health (SOH, etc.) of a battery installed in an electric vehicle. The device acquires time-series data related to the vehicle speed, extracts a section that satisfies a predetermined condition from the time-series data, and applies a predetermined estimation model to the section to estimate the state of health of the battery.

[0011] However, because SOH is merely information resulting from battery degradation, it is not easy for users to understand how their driving style directly affects battery degradation.

[0012] In order to solve the above problems, the inventors have discovered that by presenting the user with information related to the rate at which battery deterioration progresses (deterioration rate) rather than the SOH as a result of battery deterioration, it is possible to raise the user's awareness of battery deterioration, and ultimately to expect that improving driving methods can have the effect of suppressing battery deterioration, which led to the present disclosure.

[0013] Next, each aspect of the present disclosure will be described.

[0014] An information processing device according to one aspect of the present disclosure includes a status information acquisition unit that acquires status information indicating the status of a battery installed in an electrical device powered by the battery, a related information acquisition unit that acquires related information indicating the relationship between the status of the battery and the deterioration rate of the battery, a deterioration information derivation unit that derives deterioration information related to the deterioration rate of the battery based on the status information and the related information, and an output unit that outputs the deterioration information.

[0015] According to this configuration, the status information acquisition unit acquires status information indicating the status of the battery, and the related information acquisition unit acquires related information indicating the relationship between the battery status and the battery degradation rate. The degradation information derivation unit then derives degradation information related to the battery degradation rate based on the status information acquired by the status information acquisition unit and the related information acquired by the related information acquisition unit. The output unit outputs the degradation information, making it possible to present to the user degradation information related to the degradation rate of the battery installed in the electrical device. By presenting to the user degradation information related to the battery degradation rate, it is possible to raise the user's awareness of battery degradation, and ultimately to expect that improving the way the electrical device is used will have an effect in suppressing battery degradation.

[0016] In the above aspect, the state of the battery includes at least one of the temperature and the current value of the battery.

[0017] According to this configuration, by using the state information indicating at least one of the temperature and current value of the battery, it is possible to improve the accuracy of the deterioration information.

[0018] In the above aspect, the state of the battery further includes a remaining capacity of the battery.

[0019] According to this configuration, by using the status information that also indicates the remaining capacity of the battery, it is possible to further improve the accuracy of the deterioration information.

[0020] In the above aspect, the deterioration information derivation unit derives information indicating a deterioration rate of the battery as the deterioration information.

[0021] According to this configuration, it is possible to present information indicating the rate of deterioration of the battery to the user.

[0022] In the above aspect, the deterioration information derivation unit derives, as the deterioration information, information on a main cause that causes deterioration of the battery.

[0023] According to this configuration, it is possible to present information about the main causes of battery deterioration to the user.

[0024] In the above aspect, the device further includes a deterioration level information acquisition unit that acquires deterioration level information indicating the deterioration level of the battery, and the deterioration information derivation unit derives, as the deterioration information, a first remaining life, which is the remaining life of the battery according to the deterioration rate, based on the status information, the related information, and the deterioration level information.

[0025] According to this configuration, it is possible to present to the user the first remaining life, which is the remaining life of the battery according to the rate of deterioration.

[0026] In the above aspect, the deterioration information derivation unit further derives a difference in remaining life between the first remaining life and the second remaining life as the deterioration information, and the second remaining life is the remaining life of the battery according to the degree of deterioration under predetermined standard usage conditions.

[0027] According to this configuration, it is possible to present the remaining life difference between the first remaining life and the second remaining life to the user.

[0028] In the above aspect, the device further includes a temperature information acquisition unit that acquires temperature information indicating the predicted temperature at the current location, and the deterioration information derivation unit derives suitable storage conditions for the electrical equipment as the deterioration information based on the status information, the related information, and the temperature information.

[0029] According to this configuration, it is possible to present to the user suitable storage conditions for the electrical device according to the predicted temperature at the current location.

[0030] A program according to one aspect of the present disclosure is a program for causing an information processing device to function as a status information acquisition means for acquiring status information indicating the status of a battery installed in an electrical device powered by the battery, a related information acquisition means for acquiring related information indicating the relationship between the status of the battery and the deterioration rate of the battery, a deterioration information derivation means for deriving deterioration information related to the deterioration rate of the battery based on the status information and the related information, and an output means for outputting the deterioration information.

[0031] According to this configuration, the status information acquisition means acquires status information indicating the status of the battery, and the related information acquisition means acquires related information indicating the relationship between the battery status and the battery degradation rate. The degradation information derivation means derives degradation information related to the battery degradation rate based on the status information acquired by the status information acquisition means and the related information acquired by the related information acquisition means. The output means outputs the degradation information, making it possible to present to the user degradation information related to the degradation rate of the battery installed in the electrical device. By presenting to the user degradation information related to the battery degradation rate, it is possible to raise the user's awareness of battery degradation, and ultimately to expect that improving the way the electrical device is used will have an effect in suppressing battery degradation.

[0032] An information processing method according to one aspect of the present disclosure includes an information processing device acquiring status information indicating the status of a battery installed in an electrical device powered by the battery, acquiring related information indicating the relationship between the status of the battery and the rate of deterioration of the battery, deriving deterioration information related to the rate of deterioration of the battery based on the status information and the related information, and outputting the deterioration information.

[0033] According to this configuration, the information processing device acquires status information indicating the battery status, acquires related information indicating the relationship between the battery status and the battery degradation rate, and derives deterioration information related to the battery degradation rate based on the acquired status information and related information. By outputting the deterioration information, it becomes possible to present deterioration information related to the degradation rate of the battery installed in the electrical device to the user. By presenting deterioration information related to the battery degradation rate to the user, it is possible to raise user awareness of battery degradation, and ultimately to expect the effect of suppressing battery degradation by improving the way the electrical device is used.

[0034] The above-described 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. Needless to say, such a computer program can be distributed as a computer-readable non-volatile recording medium such as a CD-ROM, or via a communication network such as the Internet.

[0035] The embodiments described below each illustrate a specific example of the present disclosure. The numerical values, shapes, components, steps, step orders, and the like 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 the independent claims that represent the highest concepts are described as optional components. Furthermore, the contents of each of the embodiments can be combined.

[0036] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. Elements with the same reference numerals in different drawings indicate the same or corresponding elements.

[0037] (First embodiment) 1 is a block diagram showing the configuration of an information processing device 1A according to a first embodiment of the present disclosure. In this embodiment, the information processing device 1A is mounted on an electric vehicle, which is an example of an electric device. However, the information processing device 1A is not limited to being mounted on an electric vehicle, and may be mounted on any electric device powered by a battery (for example, a vehicle such as an electric motorcycle or an electronic device such as a smartphone).

[0038] The electric vehicle includes a traction motor (not shown) for driving the vehicle and a battery 2 that supplies power to the traction motor. The battery 2 is a secondary battery such as a lithium-ion battery. The electric vehicle also includes a battery controller 3, a current value sensor 4, a temperature sensor 5, a memory unit 6, and a display unit 7. The battery controller 3 controls charging and discharging of the battery 2 and manages its status. The current value sensor 4 measures the current value of the charging and discharging current (at least the discharge current) of the battery 2. The temperature sensor 5 measures the temperature of the battery 2. The memory unit 6 is a flash memory or the like. The memory unit 6 stores related information 30A, which will be described later. The display unit 7 is a liquid crystal display, an organic EL display, or the like. The display unit 7 is located in a position visible to the driver of the electric vehicle when seated, such as an instrument panel in front of the driver's seat of the electric vehicle.

[0039] The information processing device 1A includes a state information acquisition unit 11, a related information acquisition unit 12, a degradation information derivation unit 13A, and an output unit 14. The state information acquisition unit 11 includes a SOC acquisition unit 21, a current value acquisition unit 22, and a temperature acquisition unit 23. These functions of the information processing device 1A may be performed in software by a signal processing unit such as a CPU reading and executing a computer program 9 stored in a nonvolatile recording medium 8 such as a ROM, or may be realized as hardware using a dedicated circuit such as an FPGA.

[0040] The state information acquisition unit 11 acquires state information indicating the state of the battery 2. Specifically, the SOC acquisition unit 21 acquires information indicating the remaining capacity (SOC: State Of Charge) of the battery 2 from the battery controller 3 and inputs the information as data D1 to the deterioration information derivation unit 13A. The current value acquisition unit 22 acquires information indicating the current value of the charge / discharge current of the battery 2 from the current value sensor 4 and inputs the information as data D2 to the deterioration information derivation unit 13A. The temperature acquisition unit 23 acquires information indicating the temperature of the battery 2 from the temperature sensor 5 and inputs the information as data D3 to the deterioration information derivation unit 13A.

[0041] The related information acquisition unit 12 acquires the related information 30A by reading data from the storage unit 6, and inputs the related information 30A to the deterioration information derivation unit 13A as data D4A. Note that instead of reading data from the storage unit 6, the related information acquisition unit 12 may acquire the related information 30A by receiving data via wireless communication from a cloud server external to the electric vehicle.

[0042] The related information 30A is information indicating the relationship between the state of the battery 2 (SOC, current value, and temperature) and the deterioration rate of the battery 2. The deterioration rate represents the amount of change in the deterioration level of the battery 2 per unit time or per unit travel distance. In this embodiment, the deterioration rate of the battery 2 is represented as "ΔSOH" using SOH, which is a general index that represents the deterioration level of a battery.

[0043] As a first example, the related information 30A is obtained as a trained model by machine learning. In the learning phase, a trained model is constructed using data on the SOC, current value, and temperature of the battery 2, with a ΔSOH labeled as the correct answer, as training data, to output a trained model indicating the relationship between the SOC, current value, and temperature of the battery 2 and ΔSOH. The related information 30A is obtained as this trained model. Then, in the usage phase, the information processing device 1A inputs the data on the SOC, current value, and temperature of the battery 2 as input information to the trained model, which then outputs ΔSOH after internal processing of the trained model. Note that the machine learning algorithm is not particularly limited as long as it achieves the above output result, and for example, a regression algorithm such as multiple regression analysis or a neural network can be used.

[0044] As a second example, the related information 30A is obtained as a three-dimensional data map in which the SOC, current value, and temperature of the battery 2 are input data and ΔSOH is output data. FIG. 2 is a simplified diagram showing an example of the three-dimensional data map. A two-dimensional data map in which the temperature and current value are input data and ΔSOH is output data is created for each SOC at a predetermined interval (10% interval in this example), thereby constructing the three-dimensional data map. In each two-dimensional data map, ΔSOH is smallest when the temperature of the battery 2 is optimal and the current value is minimal. The farther the temperature of the battery 2 is from the optimal temperature or the greater the current value of the battery 2, the larger the ΔSOH. Furthermore, under the same temperature and current conditions, the smaller the SOC, the smaller the ΔSOH. For an SOC value for which no two-dimensional data map is available, ΔSOH can be calculated by interpolation using two two-dimensional data maps that sandwich the SOC value.

[0045] In the first and second examples, the state of the battery 2 may include at least one of the current value and the temperature, but in order to improve the accuracy of ΔSOH, it is preferable to include both the current value and the temperature. Preferably, it is preferable to include all of the SOC, current value, and temperature, as shown in the first and second examples.

[0046] 1, the deterioration information derivation unit 13A derives deterioration information (ΔSOH itself in this embodiment) relating to the deterioration rate of the battery 2, which corresponds to the state information (SOC, current value, and temperature) of the battery 2 indicated by data D1 to D3, by referring to related information 30A (the above-mentioned trained model or three-dimensional data map) indicated by data D4A. The deterioration information derivation unit 13A inputs data D5A indicating the derived ΔSOH to the output unit 14, and the output unit 14 outputs the data D5A. The data D5A output by the output unit 14 is input to the display unit 7.

[0047] 3 is a flowchart showing the flow of processing executed by information processing device 1 A. When the electric vehicle is powered on and information processing device 1 A is started, execution of processing begins.

[0048] First, in step S101, the related information acquisition unit 12 acquires the related information 30A from the storage unit 6, and inputs the related information 30A to the degradation information derivation unit 13A.

[0049] Next, in step S102, the SOC acquisition unit 21 acquires information indicating the SOC of the battery 2 from the battery controller 3, and inputs the information to the deterioration information derivation unit 13A.

[0050] Next, in step S103, the current value acquisition unit 22 acquires information indicating the current value of the charge / discharge current of the battery 2 from the current value sensor 4, and inputs the information to the deterioration information derivation unit 13A.

[0051] Next, in step S104, the temperature acquisition unit 23 acquires information indicating the temperature of the battery 2 from the temperature sensor 5, and inputs the information to the deterioration information derivation unit 13A.

[0052] Next, in step S105, the deterioration information derivation unit 13A derives the ΔSOH of the battery 2 corresponding to the SOC, current value, and temperature of the battery 2 input in steps S102 to S104 by referring to the related information 30A input in step S101.

[0053] Next, in step S106, the output unit 14 outputs data D5A indicating ΔSOH derived in step S105. The data D5A output by the output unit 14 is input to the display unit 7.

[0054] Next, in step S107, the information processing device 1A determines whether or not the use of the electric vehicle has ended depending on whether or not the power supply of the electric vehicle has been turned off.

[0055] If the use of the electric vehicle has not ended (step S107: NO), the information processing device 1A repeatedly executes the processes of steps S102 to S107 at predetermined intervals (for example, one second intervals).

[0056] If the use of the electric vehicle has ended (step S107: YES), the information processing device 1A ends the process.

[0057] FIG. 4 is a diagram showing an example of ΔSOH displayed on the display unit 7. A warning light-like graphic 41 lights up when ΔSOH is equal to or greater than a predetermined threshold and turns off when ΔSOH is less than the threshold. A speedometer-like graphic 42 rotates its needle to the right as the ΔSOH value increases and to the left as the ΔSOH value decreases. A battery-like graphic 43 indicates the SOC. The SOH may be displayed in addition to the SOC. The display location is not limited to the instrument panel in front of the driver's seat, but may also be a display screen on a pre-registered mobile device (such as a user's smartphone). In this way, the current ΔSOH of the battery 2 can be presented to the user depending on the manner of information display on the display unit 7. The presentation is not limited to a display, but may also be audio output from a speaker, vibration to the pedals or steering wheel of an electric vehicle, or the like.

[0058] According to this embodiment, the state information acquisition unit 11 acquires state information indicating the state of the battery 2, and the related information acquisition unit 12 acquires related information 30A indicating the relationship between the state of the battery 2 and the degradation rate. Then, the degradation information derivation unit 13A derives degradation information related to the ΔSOH of the battery 2 based on the state information acquired by the state information acquisition unit 11 and the related information acquired by the related information acquisition unit 12. The output unit 14 outputs the degradation information, making it possible to present to the user degradation information related to the ΔSOH of the battery 2 mounted on an electric device such as an electric vehicle. Presenting the degradation information related to the ΔSOH of the battery 2 to the user can raise the user's awareness of the degradation of the battery 2, and ultimately, improving driving methods can be expected to have an effect of suppressing the degradation of the battery 2.

[0059] Furthermore, according to this embodiment, by using the state information indicating at least one of the temperature and current value of the battery 2, it is possible to improve the accuracy of ΔSOH.

[0060] Moreover, according to this embodiment, by using the state information that further indicates the SOC of the battery 2, it is possible to further improve the accuracy of ΔSOH.

[0061] Furthermore, according to this embodiment, the deterioration information derivation unit 13A derives information indicating the ΔSOH of the battery 2 as deterioration information, so that the information indicating the ΔSOH of the battery 2 can be presented to the user.

[0062] (Second embodiment) FIG. 5 is a block diagram showing a configuration of an information processing device 1B according to a second embodiment of the present disclosure. The differences from the configuration shown in FIG. 1 are as follows: The information processing device 1B includes a deterioration information derivation unit 13B instead of the deterioration information derivation unit 13A. The memory unit 6 stores related information 30B instead of related information 30A. The information processing device 1B includes a clocking unit 52. The clocking unit 52 measures elapsed time by counting the number of clocks of a system clock or the like having a known period. The electric vehicle includes a memory unit 51. The memory unit 51 is a flash memory or the like. The memory unit 51 stores information indicating the SOC output from the battery controller 3, information indicating the current value output from the current value sensor 4, and information indicating the temperature output from the temperature sensor 5.

[0063] The SOC acquisition unit 21 acquires information indicating the SOC of the battery 2 by reading it from the storage unit 51, and inputs the information as data D1 to the deterioration information derivation unit 13B. The current value acquisition unit 22 acquires information indicating the current value of the charge / discharge current of the battery 2 by reading it from the storage unit 51, and inputs the information as data D2 to the deterioration information derivation unit 13B. The temperature acquisition unit 23 acquires information indicating the temperature of the battery 2 by reading it from the storage unit 51, and inputs the information as data D3 to the deterioration information derivation unit 13B. The related information acquisition unit 12 acquires related information 30B by reading it from the storage unit 6, and inputs the related information 30B to the deterioration information derivation unit 13B as data D4B.

[0064] The related information 30B is information indicating the relationship between the state of the battery 2 (SOC, current value, and temperature) and the cause category that causes the deterioration of the battery 2.

[0065] As a first example, the related information 30B is obtained as a trained model by machine learning. In the training phase, data on the SOC, current value, and temperature of the battery 2, to which correct labels of the cause categories of deterioration have been assigned, is used as training data to construct a trained model, thereby outputting a trained model indicating the relationship between the SOC, current value, and temperature of the battery 2 and the cause categories of deterioration. The related information 30B is obtained as this trained model. Then, in the usage phase, the information processing device 1B inputs the data on the SOC, current value, and temperature of the battery 2 as input information to the trained model, and the trained model outputs the cause categories of deterioration through internal processing. Note that the machine learning algorithm is not particularly limited as long as it achieves the above output result, and for example, a multi-class classification algorithm such as a support vector machine or a neural network can be used.

[0066] As a second example, the related information 30B is obtained as a three-dimensional data map having the SOC, current value, and temperature of the battery 2 as input data and the cause category of deterioration as output data. FIG. 6 is a diagram showing a simplified example of a three-dimensional data map. A two-dimensional data map having the temperature and current value as input data and cause categories A to C as output data is created for each SOC at predetermined intervals (10% intervals in this example), thereby constructing the three-dimensional data map. In each two-dimensional data map, if the current value of the battery 2 is greater than a predetermined threshold, it is classified into cause category A, which indicates that the current value is too high and is the cause of deterioration. If the current value of the battery 2 is equal to or less than the predetermined threshold and the temperature of the battery 2 is lower than a predetermined allowable lower limit, it is classified into cause category B, which indicates that the temperature is too low and is the cause of deterioration. If the current value of the battery 2 is equal to or less than the predetermined threshold and the temperature of the battery 2 is higher than a predetermined allowable upper limit, it is classified into cause category C, which indicates that the temperature is too high and is the cause of deterioration. The predetermined threshold, predetermined allowable lower limit, and predetermined allowable upper limit are set individually for each two-dimensional data map having a different SOC. For an SOC value for which no two-dimensional data map is available, the above-mentioned predetermined threshold, predetermined allowable lower limit, and predetermined allowable upper limit can be determined by interpolation using two two-dimensional data maps that sandwich the SOC value. As is clear from a comparison of Figures 2 and 6, cause categories A to C are set corresponding to areas with large ΔSOH. Therefore, the cause information of deterioration identified by the cause category classification can be considered as one piece of deterioration information related to the deterioration rate of battery 2.

[0067] 5, the deterioration information derivation unit 13B derives deterioration information (main cause information of deterioration in this embodiment) relating to the deterioration rate of the battery 2 corresponding to the state information (SOC, current value, and temperature) of the battery 2 indicated by data D1 to D3, by referring to related information 30B (the above-mentioned trained model or three-dimensional data map) indicated by data D4B. The deterioration information derivation unit 13B inputs data D5B indicating the derived main cause information to the output unit 14, and the output unit 14 outputs the data D5B. The data D5B output by the output unit 14 is input to the display unit 7.

[0068] 7 is a flowchart showing the flow of processing executed by information processing device 1B in an example in which the main causes of deterioration of battery 2 occurring during use of the vehicle are presented while the vehicle is in use. Execution of processing begins when the electric vehicle is powered on and information processing device 1B starts up. When the electric vehicle is powered on, battery controller 3, current value sensor 4, and temperature sensor 5 output information indicating SOC, information indicating current value, and information indicating temperature, respectively, at predetermined sampling intervals, and this status information is stored in storage unit 51. In the following example, the sampling interval for the status information is set to one second, but is not limited to this and may be any time interval from a few milliseconds to a few seconds.

[0069] First, in step S201, the related information acquisition unit 12 acquires the related information 30B from the storage unit 6, and inputs the related information 30B to the degradation information derivation unit 13B.

[0070] Next, in step S202, the status information acquisition unit 11 determines whether the time to acquire the status information has arrived based on the result of measuring the elapsed time by the timer unit 52. In the example of this embodiment, the target period for determining the cause of deterioration of the battery 2 is set to the most recent predetermined period. In the following example, the target period is the most recent 10 minutes, but is not limited to this and may be any period from several minutes to several hours. The status information acquisition unit 11 determines that the time to acquire the status information for the first time has arrived when 10 minutes have passed since the electric vehicle was powered on.

[0071] If the time to obtain the state information has not yet arrived (step S202: NO), the process of step S202 is repeatedly executed until the time to obtain the state information arrives.

[0072] If the time to acquire the status information has arrived (step S202: YES), then in step S203, the SOC acquisition unit 21 acquires information indicating the SOC for the last 10 minutes stored in the memory unit 51 from the memory unit 51, and inputs the information to the deterioration information derivation unit 13B.

[0073] Next, in step S204, the current value acquisition unit 22 acquires information indicating the current values ​​for the most recent 10 minutes stored in the storage unit 51 from the storage unit 51, and inputs the information to the degradation information derivation unit 13B.

[0074] Next, in step S205, the temperature acquisition unit 23 acquires, from the storage unit 51, information indicating the temperature for the most recent 10 minutes stored in the storage unit 51, and inputs the information to the deterioration information derivation unit 13B.

[0075] Next, in step S206, the deterioration information derivation unit 13B estimates a cause category of deterioration of the battery 2 based on the state information (SOC, current value, and temperature) of the battery 2 input in steps S203 to S205 by referring to the related information 30B input in step S201. Specifically, the deterioration information derivation unit 13B estimates a cause category of deterioration for a data set of SOC, current value, and temperature measured at the same time, based on the related information 30B. The deterioration information derivation unit 13B estimates a cause category for each of all data sets included in the target period. In this example, the target period is the most recent 10 minutes, and the sampling interval for the state information is 1 second, so there are 600 data sets within the target period. The deterioration information derivation unit 13B estimates a cause category for each of the 600 data sets based on the related information 30B.

[0076] Next, in step S207, the degradation information deriving unit 13B determines whether or not there is a frequent cause category whose occurrence frequency is equal to or greater than a predetermined value among all the cause categories estimated in step S206.

[0077] If there is no frequently occurring cause category (step S207: NO), the process returns to step S202 and the same process as above is executed. For the second and subsequent acquisitions of status information, the next acquisition time is set to the time when a predetermined time has elapsed since the previous acquisition time. The predetermined time is any time equal to or greater than the sampling interval of the status information, and is set to 10 seconds in the following example. In this example, the status information acquisition unit 11 newly acquires status information for the most recent 10 seconds from the storage unit 51 and inputs it to the deterioration information derivation unit 13B. The deterioration information derivation unit 13B discards the oldest 10 seconds of status information among the 10 minutes of status information it holds, and adds the new 10 seconds of status information input from the status information acquisition unit 11, thereby performing the same process as above for the new target period of the most recent 10 minutes.

[0078] If a frequently occurring cause category exists (step S207: YES), then in step S208, the deterioration information deriving unit 13B derives the frequently occurring cause category as the main cause of the deterioration of the battery 2.

[0079] Next, in step S209, the output unit 14 outputs data D5B indicating the main cause of the deterioration derived in step S208. The data D5B output by the output unit 14 is input to the display unit 7.

[0080] Next, in step S210, the information processing device 1B determines whether or not the use of the electric vehicle has ended depending on whether or not the power supply of the electric vehicle has been turned off.

[0081] If the use of the electric vehicle has not ended (step S210: NO), the information processing device 1B repeatedly executes the processes of steps S202 to S210.

[0082] If the use of the electric vehicle has ended (step S210: YES), the information processing device 1B ends the process.

[0083] Through the above process, the main causes of deterioration of the battery 2 occurring during use of the electric vehicle are presented to the user while the electric vehicle is in use.

[0084] FIG. 8 is a diagram showing an example of displaying the main cause of deterioration on the display unit 7. A graphic 44 resembling a warning light lights up if a main cause of deterioration exists in the latest target period, and goes out if no main cause of deterioration exists. A text message for notifying the user of the main cause of deterioration is displayed in the message display area 45. In the example shown in FIG. 8, an excessively large current value of the battery 2 is determined to be the main cause of deterioration in the latest target period, and a text message is displayed in the message display area 45 notifying the user that a large accelerator opening will accelerate the deterioration of the battery 2. Note that if there are multiple main causes of deterioration for the same target period, the multiple main causes may be displayed simultaneously in the message display area 45.

[0085] 9 is a flowchart showing the flow of processing executed by the information processing device 1B in an example in which the main causes of deterioration of the battery 2 that occurred during use of the vehicle are presented after the vehicle has been used. When the electric vehicle is powered on, the battery controller 3, the current value sensor 4, and the temperature sensor 5 each output status information (SOC, current value, and temperature) of the battery 2 at a predetermined sampling interval (1 second in this example), and this status information is stored in the storage unit 51.

[0086] When the power supply of the electric vehicle is turned off, the information processing device 1B is started up and starts executing the processing shown in FIG.

[0087] First, in step S211, the related information acquisition unit 12 acquires the related information 30B from the storage unit 6, and inputs the related information 30B to the degradation information derivation unit 13B.

[0088] Next, in step S212, the SOC acquisition unit 21 acquires from the memory unit 51 information indicating the SOC accumulated in the memory unit 51 during the current use (i.e., from when the electric vehicle is turned on to when it is turned off), and inputs the information to the deterioration information derivation unit 13B.

[0089] Next, in step S213, the current value acquiring unit 22 acquires, from the storage unit 51, information indicating the current value accumulated in the storage unit 51 by the current use, and inputs the information to the deterioration information deriving unit 13B.

[0090] Next, in step S214, the temperature acquisition unit 23 acquires, from the storage unit 51, information indicating the temperature accumulated in the storage unit 51 by the current use, and inputs the information to the deterioration information derivation unit 13B.

[0091] Next, in step S215, the deterioration information derivation unit 13B refers to the related information 30B input in step S211 to estimate a cause category of deterioration of the battery 2 based on the state information (SOC, current value, and temperature) of the battery 2 input in steps S212 to S214. That is, the deterioration information derivation unit 13B estimates a cause category for each of all data sets of state information accumulated in the storage unit 51 by the current use, based on the related information 30B.

[0092] Next, in step S216, the degradation information deriving unit 13B determines whether or not there is a frequent cause category whose occurrence frequency is equal to or greater than a predetermined value among all the cause categories estimated in step S215.

[0093] If there is no frequently occurring cause category (step S216: NO), the information processing device 1B ends the process.

[0094] If a frequently occurring cause category exists (step S216: YES), then in step S217, the degradation information deriving unit 13B derives the frequently occurring cause category as the main cause of the degradation of the battery 2.

[0095] Next, in step S218, the output unit 14 outputs data D5B indicating the main cause of the deterioration derived in step S217. The data D5B output by the output unit 14 is input to the display unit 7.

[0096] Through the above process, the main cause of deterioration of battery 2 that occurred during the current use of the electric vehicle is presented to the user after the electric vehicle has been used. For example, if excessively high temperature of battery 2 during the current use is determined to be the main cause of deterioration, a text message notifying the user that excessively high operating temperature will accelerate deterioration of battery 2 is displayed in message display area 45 shown in Fig. 8.

[0097] 10 is a flowchart showing the flow of processing executed by information processing device 1B in an example in which the main causes of deterioration of battery 2 that occurred during storage of the vehicle are presented after the vehicle has started to be used. When the power supply of the electric vehicle is turned off, information processing device 1B is started up and starts executing the processing.

[0098] First, in step S221, the information processing device 1B determines whether or not the time to save the state information of the battery 2 has arrived based on the result of measurement of the elapsed time by the timer unit 52. The information processing device 1B determines that the time to save the state information of the battery 2 has arrived every time a predetermined time interval has elapsed since the power supply of the electric vehicle was turned off. In the following example, the predetermined time interval is set to one hour, but is not limited to this and may be any time from several minutes to several hours.

[0099] If the time to save the state information has not yet arrived (step S221: NO), the process of step S221 is repeatedly executed until the time to save the state information arrives.

[0100] If the time to save the state information has arrived (step S221: YES), then in step S222, the information processing device 1B causes the battery controller 3 to output information indicating the SOC of the battery 2 at that time and saves the information in the storage unit 51.

[0101] Next, in step S223, the information processing device 1B causes the temperature sensor 5 to output information indicating the temperature of the battery 2 at that time, and stores the information in the storage unit 51.

[0102] Next, in step S224, the information processing device 1B determines whether use of the electric vehicle has started depending on whether the power of the electric vehicle has been turned on.

[0103] If the use of the electric vehicle has not started (step S224: NO), the information processing device 1B repeatedly executes the processes of steps S221 to S224.

[0104] If the use of the electric vehicle has started (step S224: YES), then in step S225 the related information acquisition unit 12 acquires the related information 30B from the storage unit 6 and inputs the related information 30B to the degradation information derivation unit 13B.

[0105] FIG. 11 is a simplified diagram showing a two-dimensional data map, which is an example of related information 30B. A two-dimensional data map is constructed using the temperature and SOC of battery 2 as input data and cause categories D to F as output data. If the temperature of battery 2 is lower than a predetermined allowable lower limit, it is classified into cause category E, which indicates that the temperature is too low and is the cause of deterioration. If the temperature of battery 2 is higher than a predetermined allowable upper limit, it is classified into cause category F, which indicates that the temperature is too high and is the cause of deterioration. If the temperature of battery 2 is equal to or higher than the allowable lower limit and is equal to or lower than the allowable upper limit, and the SOC is equal to or higher than a predetermined threshold, it is classified into cause category D, which indicates that the SOC is too high and is the cause of deterioration.

[0106] Referring to FIG. 10, next, in step S226, the SOC acquisition unit 21 acquires, from the storage unit 51, information indicating the SOC accumulated in the storage unit 51 during this storage period (i.e., from when the electric vehicle is powered off until it is powered on), and inputs the information to the deterioration information derivation unit 13B.

[0107] Next, in step S227, the temperature acquisition unit 23 acquires, from the storage unit 51, information indicating the temperature accumulated in the storage unit 51 during this storage, and inputs the information to the deterioration information derivation unit 13B.

[0108] Next, in step S228, the deterioration information derivation unit 13B refers to the related information 30B input in step S225 to estimate a cause category of deterioration of the battery 2 based on the state information (SOC and temperature) of the battery 2 input in steps S226 and S227. That is, the deterioration information derivation unit 13B estimates a cause category for each of all data sets of state information accumulated in the memory unit 51 by the current storage, based on the related information 30B.

[0109] Next, in step S229, the degradation information deriving unit 13B determines whether or not there is a frequent cause category whose occurrence frequency is equal to or greater than a predetermined value among all the cause categories estimated in step S228.

[0110] If there is no frequently occurring cause category (step S229: NO), the information processing device 1B ends the process.

[0111] If a frequently occurring cause category exists (step S229: YES), then in step S230, the degradation information deriving unit 13B derives the frequently occurring cause category as the main cause of the degradation of the battery 2.

[0112] Next, in step S231, the output unit 14 outputs data D5B indicating the main cause of deterioration derived in step S230. The data D5B output by the output unit 14 is input to the display unit 7.

[0113] Through the above process, the main cause of deterioration of battery 2 that occurred during the current storage of the electric vehicle is presented to the user after the electric vehicle starts to be used. For example, if it is determined that the main cause of deterioration during the current storage is that the SOC of battery 2 is too high, a text message notifying that storing battery 2 in a nearly fully charged state will accelerate deterioration of battery 2 is displayed in message display area 45 shown in Fig. 8.

[0114] According to this embodiment, it is possible to present to the user information on the main causes of deterioration of the battery 2. This allows the user to easily understand how their own driving or storage methods directly affect the deterioration of the battery 2.

[0115] (Third embodiment) FIG. 12 is a block diagram showing a configuration of an information processing device 1C according to a third embodiment of the present disclosure. The differences from the configuration shown in FIG. 1 are as follows: The information processing device 1C includes a deterioration information derivation unit 13C instead of the deterioration information derivation unit 13A. The information processing device 1C includes a state information acquisition unit 11C instead of the state information acquisition unit 11. The state information acquisition unit 11C includes an SOH acquisition unit 20. The memory unit 6 stores related information 30C instead of related information 30A. The information processing device 1C includes a traveling log information acquisition unit 54 and a ΔSOH memory unit 55. The ΔSOH memory unit 55 is a ROM, a RAM, or the like. The electric vehicle includes a traveling log information memory unit 53. The traveling log information memory unit 53 is a flash memory, or the like. The traveling log information memory unit 53 accumulates traveling log information such as the traveling time, traveling distance, and traveling speed of the electric vehicle.

[0116] The SOH acquisition unit 20 acquires information indicating the SOH as the degree of deterioration of the battery 2 from the battery controller 3, and inputs the information to the deterioration information derivation unit 13C as data D12.

[0117] The driving log information acquisition unit 54 acquires the driving log information by reading it from the driving log information storage unit 53, and inputs the driving log information to the deterioration information derivation unit 13C as data D11.

[0118] The related information acquisition unit 12 acquires the related information 30C by reading it from the storage unit 6, and inputs the related information 30C to the deterioration information derivation unit 13C as data D4C. Similar to the related information 30A, the related information 30C is information indicating the relationship between the state of the battery 2 (SOC, current value, and temperature) and the deterioration rate (ΔSOH) of the battery 2.

[0119] The degradation information derivation unit 13C derives a ΔSOH corresponding to the data set of data D1 to D3 by referring to the related information 30C indicated by data D4C. The degradation information derivation unit 13C inputs the derived ΔSOH to the ΔSOH storage unit 55 as data D10. As a result, the ΔSOH derived by the degradation information derivation unit 13C is stored in the ΔSOH storage unit 55. The degradation information derivation unit 13C repeatedly executes this series of processes at a predetermined sampling interval (1 second in this example). As a result, the ΔSOH corresponding to each of the multiple data sets is stored in the ΔSOH storage unit 55.

[0120] Furthermore, the deterioration information derivation unit 13C calculates an average value (average deterioration rate) of ΔSOH per unit time or per unit traveling distance during the current use (i.e., from when the electric vehicle is powered on to when it is powered off) based on the traveling log information input as data D11 from the traveling log information acquisition unit 54 and the ΔSOH read out from the ΔSOH storage unit 55. Based on the current SOH input as data D12 from the SOH acquisition unit 20 and the calculated average deterioration rate, the deterioration information derivation unit 13C derives a first remaining life, which is the remaining life of the battery 2 according to the average deterioration rate. As an example of calculating the average deterioration rate based on time, if the current SOH is 80(%), the lower limit SOH recommended by the manufacturer is 50(%), and the average deterioration rate is 0.002(% / min), then (80-50) / 0.002=15000(min) becomes the first remaining life of the battery 2. As an example of calculating the average deterioration rate based on the mileage, if the current SOH is 80(%), the lower limit SOH recommended by the manufacturer is 50(%), and the average deterioration rate is 0.002(% / km), then (80-50) / 0.002=15000(km) becomes the first remaining life of battery 2. Since the first remaining life varies depending on ΔSOH, it can be considered as one piece of deterioration information related to the deterioration rate of battery 2.

[0121] Furthermore, a deterioration rate (standard deterioration rate) of the battery 2 under standard usage conditions with no unnecessary deterioration factors related to temperature, current value, etc. is set in advance, and this setting information is held by the deterioration information derivation unit 13C. Based on the current SOH input as data D12 from the SOH acquisition unit 20 and the standard deterioration rate, the deterioration information derivation unit 13C derives a second remaining life, which is the remaining life of the battery 2 according to the standard deterioration rate. As an example in which the standard deterioration rate is set based on time, if the current SOH is 80(%), the lower limit SOH recommended by the manufacturer is 50(%), and the standard deterioration rate is 0.0015(% / min), then (80-50) / 0.0015=20000(min) becomes the second remaining life of the battery 2. As an example in which the standard deterioration rate is set based on the mileage, if the current SOH is 80(%), the lower limit SOH recommended by the manufacturer is 50(%), and the standard deterioration rate is 0.0015(% / km), then (80-50) / 0.0015=20000(km) becomes the second remaining life of the battery 2. The deterioration information derivation unit 13C derives the remaining life difference between the first remaining life and the second remaining life by subtracting the first remaining life from the second remaining life. This remaining life difference varies depending on ΔSOH, and therefore can be considered as one piece of deterioration information related to the deterioration rate of the battery 2.

[0122] The deterioration information derivation unit 13C inputs data D5C indicating the derived first remaining lifespan and remaining lifespan difference to the output unit 14, and the output unit 14 outputs the data D5C. The data D5C output by the output unit 14 is input to the display unit 7.

[0123] 13A and 13B are flowcharts showing the flow of processing executed by information processing device 1C. The flowcharts shown in Fig. 13A and 13B are connected to each other by connection point 1. When the electric vehicle is powered on and information processing device 1C is started, execution of processing begins.

[0124] First, in step S301, the related information acquisition unit 12 acquires the related information 30C from the storage unit 6, and inputs the related information 30C to the degradation information derivation unit 13C.

[0125] Next, in step S302, the SOC acquisition unit 21 acquires information indicating the SOC of the battery 2 from the battery controller 3, and inputs the information to the deterioration information derivation unit 13C.

[0126] Next, in step S303, the current value acquisition unit 22 acquires information indicating the current value of the charge / discharge current of the battery 2 from the current value sensor 4, and inputs the information to the deterioration information derivation unit 13C.

[0127] Next, in step S304, the temperature acquisition unit 23 acquires information indicating the temperature of the battery 2 from the temperature sensor 5, and inputs the information to the deterioration information derivation unit 13C.

[0128] Next, in step S305, the deterioration information deriving unit 13C derives ΔSOH of the battery 2 corresponding to the data set of the state information input in steps S302 to S304 by referring to the related information 30C input in step S301.

[0129] Next, in step S306, the degradation information derivation unit 13C stores the ΔSOH derived in step S305 in the ΔSOH storage unit 55.

[0130] Next, in step S307, the information processing device 1C determines whether or not the use of the electric vehicle has ended depending on whether or not the power supply of the electric vehicle has been turned off.

[0131] If the use of the electric vehicle has not ended (step S307: NO), the information processing device 1C repeatedly executes the processes of steps S302 to S307 at predetermined sampling intervals (one second intervals in this example).

[0132] If the use of the electric vehicle has ended (step S307: YES), then in step S308, the driving log information acquisition unit 54 acquires the driving log information accumulated during this use (i.e., from the time the electric vehicle is turned on to the time it is turned off) from the driving log information storage unit 53, and inputs the driving log information to the deterioration information derivation unit 13C.

[0133] Next, in step S309, the deterioration information deriving unit 13C reads out from the ΔSOH storage unit 55 the ΔSOH accumulated in the current use.

[0134] Next, in step S310, the deterioration information deriving unit 13C calculates the average deterioration speed in the current use based on the driving log information acquired in step S308 and the ΔSOH read out in step S309.

[0135] Next, in step S311, the degradation information derivation unit 13C determines whether the average degradation rate calculated in step S310 is equal to or greater than a predetermined value. For example, the above-mentioned standard degradation rate may be set as the predetermined value.

[0136] If the average deterioration rate is less than the predetermined value (step S311: NO), the information processing device 1C ends the process.

[0137] If the average deterioration rate is equal to or greater than the predetermined value (step S311: YES), then in step S312, the SOH acquisition unit 20 acquires the current SOH of the battery 2 from the battery controller 3, and inputs the information to the deterioration information derivation unit 13C.

[0138] Next, in step S313, the degradation information derivation unit 13C derives a first remaining life of the battery 2 based on the current SOH input in step S312 and the average deterioration rate calculated in step S310. The degradation information derivation unit 13C also derives a second remaining life of the battery 2 based on the current SOH input in step S312 and the standard deterioration rate. Furthermore, the degradation information derivation unit 13C derives a remaining life difference between the first remaining life and the second remaining life by subtracting the first remaining life from the second remaining life.

[0139] Next, in step S314, the output unit outputs data D5C indicating the first remaining lifespan and remaining lifespan difference derived in step S313. The data D5C output by the output unit is input to the display unit .

[0140] FIG. 14 is a diagram showing an example of the remaining life of the battery 2 displayed on the display unit 7. A graphic 46 resembling a warning light lights up if the battery 2 has deteriorated beyond the standard level during current use, and goes out if it has not. A message display area 47 displays a text message to notify the user of the remaining life of the battery 2. In the example shown in FIG. 14, a text message is displayed in the message display area 47 notifying the user of the first remaining life of "15000 minutes / 15000 km" and the remaining life difference of "5000 minutes / 5000 km".

[0141] According to this embodiment, it is possible to present to the user the first remaining life, which is the remaining life of the battery 2 according to ΔSOH, and the remaining life difference, thereby further increasing the user's awareness of the deterioration of the battery 2.

[0142] (Fourth embodiment) FIG. 15 is a block diagram showing a configuration of an information processing device 1D according to a fourth embodiment of the present disclosure. The differences from the configuration shown in FIG. 1 are as follows: The information processing device 1D includes a degradation information derivation unit 13D instead of the degradation information derivation unit 13A. The information processing device 1D includes a state information acquisition unit 11D instead of the state information acquisition unit 11. In the state information acquisition unit 11D, the current value acquisition unit 22 and the temperature acquisition unit 23 shown in FIG. 1 are omitted. The storage unit 6 stores related information 30D instead of related information 30A. The information processing device 1D includes a temperature information acquisition unit 61. The electric vehicle includes a communication unit 60. The communication unit 60 is a communication module for wireless communication with a server device (not shown) that provides a weather forecast service via any communication network such as an IP network.

[0143] The temperature information acquisition unit 61 acquires the predicted maximum temperature information for a predetermined period (e.g., one week) included in the weather forecast for the current location of the electric vehicle from the server device via the communication unit 60, and inputs the information as data D20 to the deterioration information derivation unit 13D.

[0144] The related information acquisition unit 12 acquires the related information 30D by reading it out from the storage unit 6, and inputs the related information 30D to the degradation information derivation unit 13B as data D4D.

[0145] The related information 30D is information indicating the relationship between the state of the battery 2 (SOC) and the predicted maximum temperature of the current location, and the cause category that causes deterioration of the battery 2.

[0146] FIG. 16 is a simplified diagram showing a two-dimensional data map, which is an example of related information 30D. A two-dimensional data map is constructed using the SOC of battery 2 and the predicted maximum temperature at the current location as input data and cause categories G, H, and J as output data. If the predicted maximum temperature is lower than a predetermined allowable lower limit, it is classified as cause category G, which indicates that the temperature is too low and is the cause of deterioration. If the predicted maximum temperature is higher than a predetermined allowable upper limit, it is classified as cause category H, which indicates that the temperature is too high and is the cause of deterioration. If the predicted maximum temperature is equal to or higher than the allowable lower limit and equal to or lower than the allowable upper limit, and the SOC is equal to or higher than a predetermined threshold, it is classified as cause category J, which indicates that the SOC is too high and is the cause of deterioration.

[0147] 15, the deterioration information derivation unit 13D classifies the cause into categories G, H, and J based on the SOC of the battery 2 indicated by data D1 and the predicted maximum temperature indicated by data D20, by referring to the related information 30D indicated by data D4D. The deterioration information derivation unit 13D also derives advice information indicating suitable storage conditions for the vehicle to avoid the causes of deterioration in each of the cause categories G, H, and J. The content of the advice information is predetermined corresponding to the causes of deterioration in each of the cause categories G, H, and J.

[0148] For cause category G, which is classified as a case where the predicted maximum temperature is lower than the allowable lower limit, a text message such as "The temperature is expected to be low. To prevent battery deterioration, please store the vehicle in a place where it is unlikely to get cold" is set as advice information. For cause category H, which is classified as a case where the predicted maximum temperature is higher than the allowable upper limit, a text message such as "The temperature is expected to be high. To prevent battery deterioration, please store the vehicle in a place where it is unlikely to get hot" is set as advice information. For cause category J, which is classified as a case where the SOC is equal to or higher than the threshold, a text message such as "Storing the vehicle with a battery that is nearly fully charged will accelerate battery deterioration. Consider implementing V2H" is set as advice information.

[0149] The deterioration information derivation unit 13B inputs data D5D indicating the derived advice information to the output unit 14, and the output unit 14 outputs the data D5D. The data D5D output by the output unit 14 is input to the display unit 7. Note that the cause categories G, H, and J all correspond to areas where ΔSOH is greater than the allowable value. Therefore, the classification information of the cause categories G, H, and J and the advice information corresponding thereto can be considered as one piece of deterioration information related to the deterioration rate of the battery 2.

[0150] 17 is a flowchart showing the flow of processing executed by information processing device 1D. When use of the electric vehicle is finished and the power is turned off, information processing device 1D is started up and begins executing processing.

[0151] First, in step S401, the related information acquisition unit 12 acquires the related information 30D from the storage unit 6, and inputs the related information 30D to the degradation information derivation unit 13D.

[0152] Next, in step S402, the SOC acquisition unit 21 acquires information indicating the SOC of the battery 2 from the battery controller 3, and inputs the information to the deterioration information derivation unit 13D.

[0153] Next, in step S403, the temperature information acquisition unit 61 acquires the predicted maximum temperature information for the current location of the electric vehicle from the server device via the communication unit 60, and inputs the information to the deterioration information derivation unit 13D.

[0154] Next, in step S404, the degradation information deriving unit 13D determines whether advice on storage conditions is necessary based on the SOC input in step S402 and the predicted maximum temperature input in step S403, by referring to the related information 30D input in step S401. The degradation information deriving unit 13D determines that advice on storage conditions is necessary if the output value corresponding to the SOC and the predicted maximum temperature belongs to any of cause categories G, H, or J. On the other hand, the degradation information deriving unit 13D determines that advice on storage conditions is not necessary if the output value corresponding to the SOC and the predicted maximum temperature does not belong to any of cause categories G, H, or J.

[0155] If advice on storage conditions is not required (step S404: NO), the information processing device 1D ends the process.

[0156] If advice on storage conditions is required (step S404: YES), then in step S405, the deterioration information derivation unit 13D derives cause categories G, H, and J corresponding to the SOC and the predicted maximum temperature, and derives advice information set corresponding to the cause category.

[0157] Next, in step S406, output unit 14 outputs data D5D indicating the advice information derived in step S405. Data D5D output by output unit 14 is input to display unit 7. As a result, the above-mentioned text message indicating the appropriate storage conditions for the vehicle is displayed on display unit 7.

[0158] According to this embodiment, it is possible to present to the user suitable storage conditions for the vehicle according to the vehicle state (SOC) and the predicted temperature at the current location, and as a result, it is possible to suppress deterioration of the battery 2. [Industrial Applicability]

[0159] The technology disclosed herein is useful as a technology for suppressing battery deterioration in general electrical devices driven by secondary batteries. [Explanation of symbols]

[0160] 1A~1D Information processing equipment 2 Battery 9 Program 11, 11C, 11D Status information acquisition unit 12 Related Information Acquisition Department 13A~13D Deterioration information derivation section 14 Output section 20 SOH Acquisition Department 21 SOC Acquisition Department 22 Current value acquisition unit 23 Temperature acquisition section 30A~30D Related Information 54 Driving log information acquisition unit

Claims

1. a status information acquiring unit that acquires status information indicating a status of a battery mounted in an electrical device driven by the battery; a related information acquisition unit that acquires related information indicating a relationship between the state of the battery and a deterioration rate of the battery; a deterioration information deriving unit that derives deterioration information related to a deterioration rate of the battery based on the state information and the related information; an output unit that outputs the degradation information; Equipped with the deterioration information derivation unit derives a frequent cause category having a frequency of occurrence equal to or greater than a predetermined value as a main cause of deterioration of the battery, and derives main cause information indicating the main cause as the deterioration information; The output unit outputs data indicating the main cause.

2. The information processing apparatus according to claim 1 , wherein the output unit outputs the data indicating the main cause while the electric device driven by the battery is in use.

3. The information processing device according to claim 1 , wherein the state of the battery includes at least one of a temperature and a current value of the battery.

4. The information processing device according to claim 3 , wherein the battery status further includes a remaining capacity of the battery.

5. 5. The information processing device according to claim 1, wherein the deterioration information deriving unit derives information indicating a deterioration rate of the battery as the deterioration information.

6. a deterioration level information acquisition unit that acquires deterioration level information indicating a deterioration level of the battery; The information processing device described in any one of claims 1 to 5, wherein the deterioration information derivation unit derives a first remaining life, which is the remaining life of the battery according to the deterioration rate, as the deterioration information based on the status information, the related information, and the deterioration level information.

7. the deterioration information derivation unit further derives a remaining life difference between the first remaining life and the second remaining life as the deterioration information; The information processing device according to claim 6 , wherein the second remaining life is a remaining life of the battery according to the degree of deterioration under preset standard usage conditions.

8. A temperature information acquisition unit is further provided to acquire temperature information indicating the predicted temperature at the current location, 8. The information processing device according to claim 1, wherein the deterioration information deriving unit derives suitable storage conditions for the electrical device as the deterioration information based on the state information, the related information, and the temperature information.

9. An information processing device a status information acquiring means for acquiring status information indicating the status of a battery mounted in an electrical device driven by the battery; related information acquiring means for acquiring related information indicating a relationship between the state of the battery and a deterioration rate of the battery; a deterioration information deriving means for deriving deterioration information relating to a deterioration rate of the battery based on the state information and the related information; an output means for outputting the deterioration information; It functions as the deterioration information deriving means derives a frequent cause category having a frequency of occurrence equal to or greater than a predetermined value as a main cause of deterioration of the battery, and derives main cause information indicating the main cause as the deterioration information; the output means outputs data indicating the main cause. program.

10. The information processing device acquiring status information indicating a status of a battery mounted in an electrical device driven by the battery; acquiring related information indicating a relationship between the state of the battery and a deterioration rate of the battery; deriving deterioration information relating to a deterioration rate of the battery based on the state information and the related information; outputting the degradation information; In deriving the deterioration information, a frequent cause category whose occurrence frequency is equal to or greater than a predetermined value is derived as a main cause causing deterioration of the battery, and main cause information indicating the main cause is derived as the deterioration information; In outputting the deterioration information, data indicating the main cause is output. Information processing methods.

11. A vehicle powered by a battery, the battery; an information processing device mounted on the vehicle; Equipped with The information processing device includes: a state information acquisition unit that acquires state information indicating the state of the battery; a related information acquisition unit that acquires related information indicating a relationship between the state of the battery and a deterioration rate of the battery; a deterioration information deriving unit that derives deterioration information related to a deterioration rate of the battery based on the state information and the related information; an output unit that outputs the degradation information; Equipped with the deterioration information derivation unit derives a frequent cause category having a frequency of occurrence equal to or greater than a predetermined value as a main cause of deterioration of the battery, and derives main cause information indicating the main cause as the deterioration information; The output unit outputs data indicating the main cause.

Images