Information processor, 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 listed 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] According to the technology disclosed in the above-mentioned Patent Document 1, it is possible to present the battery degradation state, such as SOH, to the user. However, since the SOH is merely information resulting from battery degradation, the user cannot easily understand from the SOH how his or her driving method directly affects the degradation of the battery.

[0005] The present disclosure provides a technique capable of presenting a user with 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 embodiment of the present disclosure includes a status information acquisition unit that acquires status information indicating a status of a battery installed in an electrical device powered by the battery, a related information acquisition unit that acquires related information indicating a 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. Effect of the Invention

[0007] According to the present disclosure, it is possible to present deterioration information relating to the deterioration rate of a battery mounted in an electrical device. [Brief description 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. [Diagram 2] FIG. 2 is a simplified diagram illustrating an example of a three-dimensional data map. [Diagram 3] 4 is a flowchart showing a flow of processing executed by the information processing device. [Figure 4] FIG. 13 is a diagram showing an example of how ΔSOH is displayed on a display unit. [Diagram 5] FIG. 11 is a block diagram showing a configuration of an information processing device according to a second embodiment of the present disclosure. [Figure 6] FIG. 2 is a simplified diagram illustrating an example of a three-dimensional data map. [Figure 7] 4 is a flowchart showing a flow of processing executed by the information processing device. [Figure 8] 13A and 13B are diagrams illustrating an example of a display of the main cause of deterioration on a display unit. [Figure 9] 4 is a flowchart showing a flow of processing executed by the information processing device. [Figure 10] 4 is a flowchart showing a flow of processing executed by the information processing device. [Figure 11] FIG. 1 is a simplified diagram illustrating a two-dimensional data map that is an example of related information. [Figure 12] FIG. 11 is a block diagram showing a configuration of an information processing device according to a third embodiment of the present disclosure. [Figure 13A] 4 is a flowchart showing a flow of processing executed by the information processing device. [Figure 13B] 4 is a flowchart showing a flow of processing executed by the information processing device. [Figure 14] 11A and 11B are diagrams illustrating an example of a remaining battery life displayed on a display unit. [Figure 15] FIG. 11 is a block diagram showing a configuration of an information processing device according to a fourth embodiment of the present disclosure. [Figure 16] FIG. 1 is a simplified diagram illustrating a two-dimensional data map that is an example of related information. [Figure 17] 4 is a flowchart showing a flow of processing executed by the information processing device. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] (Findings on which this disclosure is based) Electric vehicles equipped with a battery-powered traction motor are becoming more and more popular. The battery deteriorates 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 that estimates the degradation state (SOH, etc.) of a battery mounted on an electric vehicle. The device acquires time-series data on 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 degradation state of the battery.

[0011] However, because the SOH is merely information resulting from battery degradation, users cannot easily understand from the SOH 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 has led to the present disclosure.

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

[0014] An information processing device according to one embodiment of the present disclosure includes a status information acquisition unit that acquires status information indicating a status of a battery installed in an electrical device powered by the battery, a related information acquisition unit that acquires related information indicating a 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 deterioration rate. Then, the deterioration information derivation unit derives deterioration information related to the battery deterioration 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 deterioration information, making it possible to present the user with deterioration information related to the deterioration rate of the battery mounted on the electrical device. By presenting the user with deterioration information related to the battery deterioration rate, it is possible to increase the user's awareness of battery deterioration, and ultimately to expect an effect of suppressing battery deterioration by improving the way the electrical device is used.

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

[0017] According to this configuration, by using 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 further 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] With this configuration, it is possible to present the user with information indicating the rate of deterioration of the battery.

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

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

[0024] In the above aspect, the battery 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 deterioration rate.

[0026] In the above aspect, 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, and the second remaining life is a 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 a predicted temperature at a 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 deterioration rate of the battery. Then, the deterioration information derivation means derives deterioration information related to the deterioration rate of the battery 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 deterioration information, making it possible to present the user with deterioration information related to the deterioration rate of the battery mounted on the electrical device. By presenting the user with deterioration information related to the deterioration rate of the battery, it is possible to increase the user's awareness of battery deterioration, and ultimately to expect an effect of suppressing battery deterioration by improving the way the electrical device is used.

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

[0033] According to this configuration, the information processing device acquires status information indicating the state of the battery, acquires related information indicating the relationship between the battery state and the deterioration rate of the battery, and derives deterioration information related to the deterioration rate of the battery based on the acquired status information and related information. By outputting the deterioration information, it becomes possible to present deterioration information related to the deterioration rate of the battery mounted on the electrical device to the user. By presenting the deterioration information related to the deterioration rate of the battery to the user, it is possible to increase the user's awareness of battery deterioration, and it is expected that the effect of suppressing battery deterioration can be achieved by improving the way the electrical device is used.

[0034] The above-mentioned general or specific aspects of the present disclosure can be realized as a system, an apparatus, a method, an integrated circuit, a computer program, or any combination thereof. It goes without saying that such a computer program can be distributed as a computer-readable non-volatile recording medium such as a CD-ROM, or distributed via a communication network such as the Internet.

[0035] Each of the embodiments described below shows a specific example of the present disclosure. The numerical values, shapes, components, steps, order of steps, etc. shown in the following embodiments are merely examples and are not intended to limit the present disclosure. Furthermore, among the components in the following embodiments, components that are not described in an independent claim showing a top concept are described as optional components. Furthermore, in all embodiments, the contents of each component can be combined.

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

[0037] (First embodiment) 1 is a block diagram showing a configuration of an information processing device 1A according to a first embodiment of the present disclosure. In the example of this embodiment, the information processing device 1A is mounted on an electric vehicle as an example of an electric device. However, the information processing device 1A is not limited to an electric vehicle, and may be mounted on any electric device driven 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 driving motor (not shown) for driving the vehicle, and a battery 2 for supplying power to the driving 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 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 disposed 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 deterioration 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 executed as software by a signal processing unit such as a CPU reading and executing a computer program 9 stored in a non-volatile 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 to the deterioration information derivation unit 13A as data D1. 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 as data D2. 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 as data D3.

[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 mileage. In this embodiment, the deterioration rate of the battery 2 is represented as "ΔSOH" using SOH, which is a general index representing 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 of the SOC, current value, and temperature of the battery 2, to which a correct answer label of ΔSOH is added, as teacher data, to output a trained model showing 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 utilization phase, the information processing device 1A inputs the data of the SOC, current value, and temperature of the battery 2 as input information, and outputs ΔSOH through 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 having the SOC, current value, and temperature of the battery 2 as input data and ΔSOH as output data. FIG. 2 is a simplified diagram showing an example of the three-dimensional data map. A two-dimensional data map having the temperature and current value as input data and ΔSOH as 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 minimum when the temperature of the battery 2 is optimal and the current value is minimum, and ΔSOH increases as the temperature of the battery 2 moves away from the optimal temperature or as the current value of the battery 2 increases. In addition, if the temperature and current value are the same, the smaller the SOC, the smaller the ΔSOH. For a value of SOC for which no two-dimensional data map is prepared, ΔSOH can be obtained by an interpolation calculation 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. It is preferable to include all of the SOC, the current value, and the 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 the data D1 to D3, by referring to the related information 30A (the above-mentioned trained model or three-dimensional data map) indicated by the 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 the information processing device 1 A. When the electric vehicle is powered on and the information processing device 1 A starts up, execution of the 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 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 been 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 display of ΔSOH on the display unit 7. A figure 41 imitating a warning light is turned on when ΔSOH is equal to or greater than a predetermined threshold value, and is turned off when ΔSOH is less than the threshold value. A figure 42 imitating a speedometer has a needle that rotates to the right as the value of ΔSOH increases, and rotates to the left as the value of ΔSOH decreases. A figure 43 imitating a battery shape indicates SOC. SOH may be displayed in addition to SOC. The display location is not limited to the instrument panel in front of the driver's seat, and may be a display screen provided on a pre-registered mobile terminal (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 manner of presentation is not limited to display, and may be audio output from a speaker, or vibration generation to the pedals or steering wheel of an electric vehicle.

[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 deterioration rate. Then, the deterioration information derivation unit 13A derives deterioration 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 deterioration information, so that it is possible to present the deterioration information related to the ΔSOH of the battery 2 mounted on an electric device such as an electric vehicle to the user. By presenting the deterioration information related to the ΔSOH of the battery 2 to the user, it is possible to increase the user's awareness of the deterioration of the battery 2, and it is possible to expect an effect of suppressing the deterioration of the battery 2 by improving the driving method.

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

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

[0061] Furthermore, according to the present 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 storage 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 storage unit 51. The storage unit 51 is a flash memory or the like. The storage unit 51 accumulates 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 to the deterioration information derivation unit 13B as data D1. 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 to the deterioration information derivation unit 13B as data D2. 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 to the deterioration information derivation unit 13B as data D3. 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 association information 30B is information indicating an association between the state of the battery 2 (SOC, current value, and temperature) and a cause category that causes 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 learning phase, the data of the SOC, current value, and temperature of the battery 2, to which a correct answer label of the cause category of deterioration is added, is used as teacher data to construct a trained model, and a trained model showing the relationship between the SOC, current value, and temperature of the battery 2 and the cause category of deterioration is output. The related information 30B is obtained as this trained model. Then, in the utilization phase, the information processing device 1B inputs the data of the SOC, current value, and temperature of the battery 2 as input information to the trained model, and outputs the cause category of deterioration through 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 multi-item 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 the three-dimensional data map. A two-dimensional data map having the temperature and current value as input data and the cause categories A to C as 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, when the current value of the battery 2 is greater than a predetermined threshold, it is classified into cause category A in which the current value is too large as the cause of deterioration. When the current value of the battery 2 is equal to or less than a predetermined threshold and the temperature of the battery 2 is lower than a predetermined allowable lower limit, it is classified into cause category B in which the temperature is too low as the cause of deterioration. When the current value of the battery 2 is equal to or less than a predetermined threshold and the temperature of the battery 2 is higher than a predetermined allowable upper limit, it is classified into cause category C in which the temperature is too high as the cause of deterioration. The above-mentioned 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 prepared, the above-mentioned predetermined threshold value, the predetermined allowable lower limit value, and the predetermined allowable upper limit value can be obtained by an interpolation calculation using two two-dimensional data maps that sandwich the SOC value. As is clear from a comparison between Fig. 2 and Fig. 6, cause categories A to C are set corresponding to a region where ΔSOH is large. Therefore, the cause information of deterioration specified by the classification of the cause category can be regarded as one of the deterioration information related to the deterioration speed of the 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 the data D1 to D3 by referring to the related information 30B (the above-mentioned trained model or three-dimensional data map) indicated by the 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 the information processing device 1B in an example in which the main causes of deterioration of the battery 2 occurring during use of the vehicle are presented while the vehicle is in use. The execution of processing is started by turning on the power supply of the electric vehicle and starting up the information processing device 1B. When the power supply of the electric vehicle is turned on, the battery controller 3, the current value sensor 4, and the temperature sensor 5 output information indicating the SOC, information indicating the current value, and information indicating the temperature, respectively, at a predetermined sampling interval, and these status information are accumulated in the storage unit 51. In the following example, the sampling interval of the status information is set to 1 second, but is not limited to this and may be any time interval from several milliseconds to several 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 or not the time to acquire the status information has arrived based on the result of measurement of the elapsed time by the timer unit 52. In 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 first time the status information is acquired has arrived because 10 minutes have passed since the electric vehicle was turned 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 obtain the status information has arrived (step S202: YES), then in step S203, the SOC obtaining unit 21 obtains 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 information indicating the temperature 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.

[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 of the state information is 1 second, so that 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 time when a predetermined time has elapsed since the previous acquisition time is set as the next acquisition time. The predetermined time is any time equal to or longer 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 latest 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 held for the 10 minutes, 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 derivation unit 13B derives the frequently occurring cause category as a main cause of 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 being used.

[0084] FIG. 8 is a diagram showing an example of displaying the main cause of deterioration on the display unit 7. A figure 44 resembling a warning light is turned on when the main cause of deterioration exists in the latest target period, and is turned off when the main cause does not exist. A text message for notifying the user of the contents of the main cause of deterioration is displayed in the message display area 45. In the example shown in FIG. 8, the main cause of deterioration in the latest target period is derived to be that the current value of the battery 2 is too large, and as a result, a text message is displayed in the message display area 45 notifying the user that the deterioration of the battery 2 will be accelerated if the accelerator opening is large. Note that when 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 a 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 use of the vehicle. When the power supply of the electric vehicle is turned on, the battery controller 3, the current value sensor 4, and the temperature sensor 5 each output state information (SOC, current value, and temperature) of the battery 2 at a predetermined sampling interval (1 second in this example), and this state 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 process 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 due to 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 derivation 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 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 S212 to S214 by referring to the related information 30B input in step S211. 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 deterioration information derivation unit 13B derives the frequently occurring cause category as a main cause of deterioration 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 the 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 it is determined that the main cause of deterioration during the current use was that the temperature of the battery 2 was too high, a text message notifying the user that the battery 2 will deteriorate more quickly if it is used at too high a temperature is displayed in the message display area 45 shown in FIG.

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

[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 point 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 point, and stores the information in the storage unit 51.

[0102] Next, in step S224, the information processing device 1B determines whether or not use of the electric vehicle has started depending on whether or not the power supply of the electric vehicle has been turned on.

[0103] If 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 deterioration information derivation unit 13B.

[0105] FIG. 11 is a diagram showing a simplified two-dimensional data map, which is an example of related information 30B. A two-dimensional data map is constructed with the temperature and SOC of battery 2 as input data and cause categories D to F as output data. When 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. When 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. When the temperature of battery 2 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 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 to when 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 the current storage, and inputs the information to the degradation information derivation unit 13B.

[0108] Next, in step S228, the deterioration information derivation unit 13B estimates 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 by referring to the related information 30B input in step S225. 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 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 deterioration information derivation unit 13B derives the frequently occurring cause category as a main cause of deterioration of the battery 2.

[0112] Next, in step S231, the output unit 14 outputs data D5B indicating the main cause of the 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 the deterioration of the 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 the deterioration during the current storage is that the SOC of the battery 2 is too high, a text message notifying the user that the deterioration of the battery 2 will be accelerated if it is stored in a nearly fully charged state is displayed in the message display area 45 shown in FIG.

[0114] According to the present 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 his / her own driving method or storage method directly affects 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 a SOH acquisition unit 20. The storage 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 storage unit 55. The ΔSOH storage unit 55 is a ROM or a RAM, etc. The electric vehicle includes a traveling log information storage unit 53. The traveling log information storage unit 53 is a flash memory, etc. The traveling log information storage 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 out 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. The related information 30C is information indicating the association between the state (SOC, current value, and temperature) of the battery 2 and the deterioration rate (ΔSOH) of the battery 2, similar to the related information 30A.

[0119] The degradation information derivation unit 13C derives ΔSOH corresponding to the data sets 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] Further, the deterioration information derivation unit 13C calculates an average value (average deterioration speed) of ΔSOH per unit time or per unit driving distance in the current use (i.e., from when the power supply of the electric vehicle is turned on to when it is turned off) based on the driving log information inputted as data D11 from the driving log information acquisition unit 54 and the ΔSOH read out from the ΔSOH storage unit 55. Based on the current SOH inputted as data D12 from the SOH acquisition unit 20 and the calculated average deterioration speed, 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 speed. As an example of calculating the average deterioration speed based on time, if the current SOH is 80(%), the lower limit SOH recommended by the manufacturer is 50(%), and the average deterioration speed 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 the battery 2. Since the first remaining life varies according to ΔSOH, it can be regarded as one piece of deterioration information related to the deterioration rate of the battery 2.

[0121] In addition, a deterioration rate (standard deterioration rate) of the battery 2 under standard use conditions without unnecessary deterioration factors with respect to temperature, current value, etc. is set in advance, and the setting information is held by the deterioration information derivation unit 13C. Based on the current SOH inputted 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 according to ΔSOH, and therefore can be regarded as one piece of deterioration information related to the deterioration rate of the battery 2.

[0122] The degradation 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 the information processing device 1C. The flowcharts shown in Fig. 13A and 13B are connected to each other by a connection point 1. When the electric vehicle is powered on and the information processing device 1C is started, the execution of the processing is started.

[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 acquired 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 derivation 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 been terminated (step S307: NO), the information processing device 1C repeatedly executes the processes of steps S302 to S307 at a predetermined sampling interval (one second interval in this example).

[0132] If 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 when the electric vehicle is turned on to when 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 during the current use.

[0134] Next, in step S310, the deterioration information derivation 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 speed calculated in step S310 is equal to or greater than a predetermined value that is set in advance. For example, the above-mentioned standard degradation speed 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 14 outputs data D5C indicating the first remaining lifespan and remaining lifespan difference derived in step S313. The data D5C output by the output unit 14 is input to the display unit 7.

[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 turns on if the battery 2 has deteriorated beyond the standard level during the current use, and turns off if the battery 2 has not deteriorated beyond the standard level. A text message is displayed in a message display area 47 to inform 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 to inform the user of the first remaining life of "15000 min / 15000 km" and the remaining life difference of "5000 min / 5000 km".

[0141] According to the present 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. This makes it possible to further increase 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 deterioration information derivation unit 13D instead of the deterioration 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 an arbitrary communication network such as an IP network.

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

[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 at 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 that is an example of related information 30D. A two-dimensional data map is constructed with 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. When the predicted maximum temperature is lower than a predetermined allowable lower limit, it is classified into cause category G, which indicates that the temperature is too low and is the cause of deterioration. When the predicted maximum temperature is higher than a predetermined allowable upper limit, it is classified into cause category H, which indicates that the temperature is too high and is the cause of deterioration. When 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 into 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 categories G, H, and J based on the SOC of the battery 2 indicated by the data D1 and the predicted maximum temperature indicated by the data D20 by referring to the related information 30D indicated by the data D4D. In addition, the deterioration information derivation unit 13D derives advice information indicating suitable storage conditions for the vehicle to avoid the deterioration causes of each of the cause categories G, H, and J. The contents of the advice information are predetermined corresponding to the deterioration causes of each of the cause categories G, H, and J.

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

[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 above-mentioned advice information corresponding thereto can be regarded 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 the information processing device 1D. When the use of the electric vehicle is finished and the power is turned off, the information processing device 1D is started up and starts 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 acquired 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 deterioration information derivation unit 13D determines whether or not 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 deterioration information derivation unit 13D determines that advice on storage conditions is necessary when 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 deterioration information derivation unit 13D determines that advice on storage conditions is not necessary when 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 needed (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 those cause categories.

[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 suitable 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 state of charge (SOC) of the vehicle 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 degradation in general electrical devices powered by secondary batteries. [Explanation of symbols]

[0160] 1A~1D Information processing equipment 2 Battery 9. Program 11, 11C, 11D Status information acquisition section 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 section 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 derivation 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 derivation 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 according to any one of claims 1 to 5, wherein the deterioration information derivation unit derives a first remaining life, which is a 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 degree 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 for acquiring temperature information indicating a predicted temperature at a current location is further provided, 8. The information processing device according to claim 1, wherein the deterioration information derivation unit derives suitable storage conditions for the electrical appliance 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 a status of a battery mounted in an electrical device driven by the battery; a 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; Function as a 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. An information processing device, acquiring status information indicating a status of a battery mounted in an electrical device driven by the battery; acquiring association information indicating an association 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 having a frequency of occurrence equal to or greater than a predetermined value is derived as a main cause of deterioration of the battery, and main cause information indicating the main cause is derived as the deterioration information; In the output of 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 acquiring unit that acquires state information indicating a 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 derivation 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