Battery level prediction system

Abstract

To provide a battery remaining amount prediction system that can accurately predict the remaining amount of a battery and encourage charging to prevent overdischarge without providing a new configuration.SOLUTION: In a battery remaining amount prediction system 1, a server 20 comprises: a battery remaining amount prediction unit 21 that predicts the remaining amount of a battery of a work vehicle 10 based on at least one of the operating hours and the number of operating days of the work vehicle 10, and selects a vehicle that is likely to be overdischarged based on the predicted remaining amount of the battery as an overdischarge target vehicle; a determination unit 22 that, in response to a request to predict the remaining amount of a battery for an arbitrary work vehicle, determines whether the work vehicle for which the prediction is requested is included in the overdischarge target vehicle; and a notification unit 23 that, when the work vehicle for which the prediction is requested is determined to be included in the overdischarge target vehicle, notifies a result of prediction of the remaining amount of a battery of the work vehicle for which the prediction is requested to at least one of the work vehicle for which the prediction is requested and a terminal 30.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] The present invention relates to a battery remaining capacity prediction system, and more particularly to a battery remaining capacity prediction system that predicts the remaining capacity of a battery mounted on a work vehicle. [Background technology]

[0002] Batteries mounted on work vehicles have the problem of over-discharging (so-called dead batteries) due to reasons such as the work vehicle not operating for a long period of time. In order to avoid over-discharging, as described in Patent Document 1, for example, a device is used that acquires a weather information map for a region including the position information of the work vehicle, predicts the outside air temperature while the work vehicle is stopped, calculates the amount of self-discharge discharged from the battery based on the predicted outside air temperature, and further predicts the remaining capacity (hereinafter referred to as the remaining capacity) of the battery according to this calculated amount of self-discharge, thereby preventing over-discharge. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2012-65498 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, the device described in Patent Document 1 has the following problems: First, it is necessary to newly provide components such as an acquisition means for acquiring the work vehicle's position information and a weather information map, and a prediction means for predicting the outside air temperature and remaining battery charge during a stoppage, which increases costs.

[0005] In addition, the discharge of batteries installed in work vehicles depends on various factors such as the vehicle's operating status, operating time, frequency, and operating environment (e.g., outside temperature), and it is highly likely that sufficient prediction accuracy cannot be ensured by considering the outside temperature alone.

[0006] In view of the above circumstances, the present invention aims to provide a battery remaining capacity prediction system that can accurately predict battery remaining capacity without providing any new configuration and can encourage charging to prevent over-discharge. [Means for solving the problem]

[0007] The battery remaining capacity prediction system of the present invention is a battery remaining capacity prediction system that is communicatively connected to a plurality of work vehicles equipped with batteries, and includes a server that collects operation information of the work vehicles and predicts the remaining capacity of the batteries, and the server is characterized in that it includes a battery remaining capacity prediction unit that predicts the remaining battery capacity of each of the plurality of work vehicles based on at least one of the operating hours and number of operating days of the plurality of work vehicles, and selects vehicles that may be over-discharged as vehicles subject to over-discharge based on the predicted battery remaining capacity, a judgment unit that, in response to a prediction request for the remaining battery capacity for any of the work vehicles, determines whether the work vehicle for which the prediction request has been made is included in the vehicles subject to over-discharge, and a notification unit that, when it is determined that the work vehicle for which the prediction request has been made is included in the vehicles subject to over-discharge, notifies at least one of the work vehicle for which the prediction request has been made and a terminal capable of communicating with the server of the battery remaining capacity prediction result of the work vehicle for which the prediction request has been made.

[0008] In the battery remaining amount prediction system according to the present invention, the server includes a battery remaining amount prediction unit that predicts the battery remaining amount of each of the work vehicles based on at least one of the operating hours and the number of operating days of the work vehicles, and selects vehicles that may be over-discharged as over-discharge target vehicles based on the predicted battery remaining amount, so that the battery remaining amount can be predicted accurately without providing a new configuration. In addition, the server includes a determination unit that determines whether the work vehicle for which the prediction request is made is included in the over-discharge target vehicles in response to a battery remaining amount prediction request for any work vehicle, and a notification unit that notifies at least one of the work vehicle for which the prediction request is made and a terminal that can communicate with the server of the battery remaining amount prediction result of the work vehicle for which the prediction request is made, so that by notifying an operator who operates the work vehicle or a maintenance worker who has a terminal, it is possible to encourage charging to prevent over-discharge. As a result, it is possible to avoid over-discharge of the battery. Effect of the Invention

[0009] According to the present invention, it is possible to accurately predict the remaining battery charge and to prompt charging to prevent over-discharge without providing a new configuration. [Brief description of the drawings]

[0010] [Figure 1] 1 is a schematic configuration diagram showing a battery remaining capacity prediction system according to an embodiment; [Diagram 2] 1 is a schematic block diagram showing a configuration of a battery remaining capacity prediction system according to an embodiment; [Diagram 3] 13 is an example of a selection table for selecting vehicles that may be over-discharging based on the operation time of the work vehicle. [Figure 4] 13 is an example of a selection table for selecting vehicles that may be over-discharged based on the number of days that the work vehicle has been in operation. [Diagram 5] 13 is an example of a selection table for selecting vehicles that may be over-discharged based on the operation time and number of operation days of the work vehicle. [Figure 6]4 is a flowchart showing a control process on the server side in the battery remaining capacity prediction system. [Figure 7] 11 is another flowchart showing the control process on the server side in the battery remaining capacity prediction system. [Figure 8] 13 is an example showing notification content displayed on a display of a terminal. [Figure 9] 13 is an example showing notification content displayed on a display of a terminal. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] Hereinafter, an embodiment of a battery remaining capacity prediction system according to the present invention will be described with reference to the drawings. In the description of the drawings, the same elements are given the same reference numerals, and duplicated description will be omitted. In the following description, in order to avoid complication of the description, a work vehicle may be abbreviated to simply "vehicle", and the work vehicle includes a work machine such as a hydraulic excavator.

[0012] Fig. 1 is a schematic diagram showing a battery remaining capacity prediction system according to an embodiment, and Fig. 2 is a schematic block diagram showing the configuration of the battery remaining capacity prediction system according to an embodiment. The battery remaining capacity prediction system 1 according to this embodiment is a system for preventing over-discharging of the battery by predicting the remaining capacity of a battery mounted on a work vehicle 10 based on operation information of the work vehicle 10 and notifying the work vehicle 10 (e.g., an operator of the work vehicle 10) and / or a terminal 30 (e.g., a maintenance worker or a user having the terminal 30) of the predicted battery remaining capacity upon request. Here, over-discharging refers to discharging beyond a capacity that can ensure operation, and for example, in the case where a battery supplies power to a starter motor for starting an engine mounted on a work vehicle, discharging to a level where the starter motor cannot be started.

[0013] 1, the battery remaining capacity prediction system 1 mainly includes a plurality of work vehicles 10, a server 20 communicatively connected to the work vehicles 10, and a terminal 30 communicatively connected to the server 20. Note that, although this embodiment will be described taking an example in which there are a plurality of work vehicles 10 and one terminal 30, the present invention can also be applied to cases in which there is a single work vehicle 10 and a plurality of terminals 30.

[0014] The work vehicle 10 is, for example, a hydraulic excavator, and is used by a predetermined user (for example, the owner of the work vehicle or a rental contractor) at a work site where civil engineering work, construction work, demolition work, dredging work, etc. are performed. The work vehicle 10 is equipped with a battery 11. The battery 11 is configured to supply power to a starter motor for starting an engine provided on the work vehicle 10, and is charged by a generator driven by the engine, and is, for example, a lead battery.

[0015] As shown in FIG. 2, the work vehicle 10 has a vehicle communication unit 12 for communicating with the server 20, the terminal 30, etc., a control unit 13 for controlling the entire work vehicle 10, and a display unit 14 for displaying various information to the operator who operates the work vehicle 10. The control unit 13 is configured to periodically transmit operation information of the work vehicle 10 to the server 20, for example, via the vehicle communication unit 12. The operation information includes the operation time and the number of operation days of the work vehicle 10. In addition, the control unit 13 is configured to display the information received from the server 20 via the vehicle communication unit 12 on the display unit 14, thereby notifying the operator. The display unit 14 is, for example, a display, and is arranged inside the cab.

[0016] The server 20 is the main computer constituting the battery remaining capacity prediction system 1, and is installed in the head office, branch office, factory or management center of the manufacturer of the work vehicles 10, periodically collecting operation information from each of the multiple work vehicles 10, and centrally managing these work vehicles 10. The server 20 is composed of a microcomputer that combines, for example, a CPU (Central Processing Unit) that executes calculations, a ROM (Read Only Memory) as a secondary storage device that stores programs for the calculations, and a RAM (Random Access Memory) as a temporary storage device that saves the calculation progress and temporary control variables, and performs each process by executing the stored programs.

[0017] In this embodiment, the server 20 includes a battery remaining capacity prediction unit 21, a determination unit 22, a notification unit 23, a server communication unit 24, and an information storage unit 25. The server 20 performs wireless communication with the work vehicle 10 and with the terminal 30 via the server communication unit 24. The information storage unit 25 stores and accumulates operation information transmitted from the work vehicle 10. The information storage unit 25 also stores relationship diagrams, relationship equations, relationship tables, and the like used for battery remaining capacity prediction. Furthermore, the information storage unit 25 also stores tables shown in Figs. 3 to 5 described below.

[0018] The battery remaining capacity prediction unit 21 predicts the remaining battery capacity of each work vehicle 10 based on at least one of the operation time and the number of operation days of each work vehicle 10, using the operation information of each work vehicle 10 stored in the information storage unit 25, and selects the number of vehicles that may be over-discharged (vehicles subject to over-discharge) based on the predicted remaining battery capacity. This will be described in detail below with reference to Figs. 3 to 5.

[0019] FIG. 3 is an example of a screening table for screening vehicles that may be over-discharged based on the operating time of the work vehicle. Specifically, FIG. 3 shows, for a work vehicle 10 of any model (number of operating units: 3,000 units), the vehicles (over-discharge target vehicles) that may be over-discharged at different operating times at the prediction time when there is a battery remaining amount prediction unit 21. In FIG. 3, A1 to A4 indicate different operating times (actual results) of the work vehicle 10, and the operating time becomes longer in the order of A1 to A4 (that is, A1 < A2 < A3 < A4, for example, A1 = 10 hours, A2 = 30 hours, A3 = 50 hours, A4 = 100 hours). X, Y, and Z indicate a plurality of patterns of the number of days traced back from the prediction time, and the number of days increases in the order of X, Y, Z (that is, X < Y < Z). The numbers shown in "target number" indicate the number of work vehicles having an operating time at the number of days traced back from each prediction time. When the prediction time is the present, it indicates the number of work machines that have reached that operating time by operating from how many days ago in the past to the present. For example, taking the present as the prediction starting point, if the operating time is A1, the number of work machines with an operating time of 10 hours from 5 days ago (X days ago) to the present is 100, the number of work machines with an operating time of 10 hours from 10 days ago (Y days ago) to the present is 50, and the number of work machines with an operating time of 10 hours from 20 days ago (Z days ago) to the present is 25. The same applies to A2 to A4. The battery has a longer charging time as the operating time of the work vehicle becomes longer, and the longer the time without operating, the longer the discharge time during which it is discharged without being charged, and the longer this time, the more likely it is to be in an over-discharged state. Also, even if the cumulative operating time within a predetermined period is long, if most of it is past operating time and the most recent operating time is short, it may not be charged and the discharge time may become long, resulting in an over-discharged state. Also, regarding the operating time, the greater the average operating time per day compared to the cumulative operating time, the better the charging state of the battery. For example, when the operating time in the past 10 days is 5 hours and when it is 100 hours in 100 days, the latter has less impact on the over-discharge of the battery. Therefore, in the embodiment of the present invention, the over-discharged state of the battery is predicted based on this knowledge.

[0020] Therefore, for example, if the operating time is A2 (e.g., 30 hours) and the number of operating days from the prediction point is counted back 20 days (Y=20), the battery remaining capacity prediction unit 21 predicts the remaining battery capacity of each of the 3,000 work vehicles 10, and selects 100 vehicles as vehicles that may be over-discharged (vehicles subject to over-discharge) based on the prediction results. In other words, these 100 work vehicles 10 may have dead batteries. These 100 work vehicles 10 are each assigned a management number or the like that can identify them, and are identified and managed by the server 20.

[0021] As a method for predicting the remaining battery charge based on the operating time of the work vehicle 10, a technique that is already well known can be used. For example, the battery remaining charge prediction unit 21 makes a prediction using the type of battery used, a relationship diagram between the battery voltage and the operating time, a relationship formula, a relationship table, and the like. Meanwhile, the judgment as to whether or not there is a possibility of battery over-discharge is performed by comparing the predicted result with a predetermined reference value. The predetermined reference value is set in advance according to, for example, the type of battery, and is stored in the information storage unit 25. The predetermined reference value may be set at the time of shipment from the factory of the work vehicle equipped with the battery, may be set manually by a maintenance person after shipment, or may be set automatically by the server 20 according to the number of times the battery is charged and discharged.

[0022] Here, since the operating status of the work vehicles 10 varies from day to day and the number of vehicles that may be subject to battery over-discharge also changes, it is preferable to have a large number of operating vehicles. In this way, the accuracy of predicting the remaining battery charge can be improved.

[0023] Generally, the remaining battery charge is proportional to the operating time of the work vehicle, and the longer the work vehicle is operating, the longer the battery charging time will be, and the shorter the battery discharging time will be. On the other hand, the longer the time the work vehicle is not operating, the longer the battery discharging time will be, and the more likely it is to become over-discharged.

[0024] In the example shown in FIG. 3, the combination of A1 and Z has the shortest operating time and the longest non-operating period, so the possibility of battery over-discharge is the highest. On the other hand, the combination of A4 and X has a longer operating time than A1 to A3 and a shorter non-operating period, so the possibility of battery over-discharge is the lowest.

[0025] As a factor of battery over-discharge, not only the above-mentioned operating time but also the number of operating days is considered. That is, just because the operating time is short, it is not necessarily the case that the battery will be over-discharged. For example, even if the operating time is long but the number of operating days is small, it is likely to lead to battery over-discharge.

[0026] FIG. 4 is an example of a screening table for screening vehicles that may be over-discharged based on the number of operating days of a work vehicle. Specifically, FIG. 4 shows, for a work vehicle 10 of any model (number of operating units: 3000 units), the vehicles that may be over-discharged by battery are screened by the number of operating days at the prediction time when there is a battery remaining amount prediction unit 21. In FIG. 4, B1 to B4 indicate different operating days of the work vehicle 10, and the number of operating days increases in the order of B1 to B4 (that is, B1 < B2 < B3 < B4, for example, B1 = 1 day, B2 = 5 days, B3 = 10 days, B4 = 20 days). X, Y, and Z indicate a plurality of patterns of the number of days traced back from the prediction time as described above, and the number of days increases in the order of X, Y, Z (that is, X < Y < Z). The numbers shown in "target number" are the total number of vehicles (over-discharge target vehicles) that may be over-discharged by battery when different retroactive days are applied according to the number of operating days of the vehicle.

[0027] In FIG. 4, the number of work vehicles having the number of days of operation going back from the prediction time point is shown, and when the prediction time point is the present, the number of work machines having the number of days of operation back from the present is shown. For example, when the present is the prediction start point and the number of days of operation is B1, the number of work machines having one day of operation from 5 days ago (X days ago) to the present is 100, the number of work machines having one day of operation from 10 days ago (Y days) to the present is 50, and the number of work machines having one day of operation from 20 days ago (Z days) to the present is 25. The same applies to B2 to B4. Therefore, for example, when the number of days of operation is B3 (10 days of operation) and 45 days ago (Z=45) going back from the prediction time point, the battery remaining amount prediction unit 21 predicts the remaining battery amount of each of the 3,000 work vehicles 10, and selects 100 target vehicles as vehicles that may have a battery over-discharge based on the prediction result. In other words, there is a possibility that the batteries of these 100 work vehicles 10 are dead. Note that these 100 work vehicles 10 are given management numbers or the like that can identify them, and are identified and managed by the server 20.

[0028] As a method for predicting the remaining battery charge based on the number of days of operation of the work vehicle 10, a technique that is already well known can be used. For example, the prediction is made using the type of battery used, a relationship diagram between the battery voltage and the number of days of operation, a relationship formula, a relationship table, etc. Meanwhile, the judgment as to whether or not there is a possibility of battery over-discharge is made by comparing the predicted result with a predetermined reference value. The predetermined reference value is set in advance according to, for example, the type of battery, and is stored in the information storage unit 25. The predetermined reference value may be set at the time of shipment from the factory of the work vehicle equipped with the battery, may be set manually by a maintenance worker after shipment, or may be set automatically by the server 20 according to the number of times the battery is charged and discharged.

[0029] 4, the combination of B1 and Z has fewer operating days and longer non-operating periods than B2 to B4, and therefore has the highest possibility of battery over-discharge. On the other hand, the combination of B4 and X has the longest operating days and shortest non-operating periods, and therefore has the lowest possibility of battery over-discharge.

[0030] In the above, it has been explained that the battery remaining capacity prediction unit 21 predicts the remaining battery capacity based on the operating hours (see FIG. 3) or number of operating days (see FIG. 4) of the work vehicle 10, and selects vehicles that may be over-discharged based on the predicted remaining battery capacity. However, when considering improving the accuracy of predicting the remaining battery capacity, it is preferable to make a prediction based on the operating hours and number of operating days of the work vehicle 10 and select vehicles that may be over-discharged (vehicles subject to over-discharge).

[0031] Fig. 5 is an example of a selection table for selecting vehicles that may be over-discharged based on the operation time and number of operation days of the work vehicle. Fig. 5 shows that for the same retroactive date among the multiple retroactive dates shown in Fig. 3 and Fig. 4, the battery remaining amount prediction unit 21 predicts the remaining battery amount based on the operation time (A1 to A4) and number of operation days (B1 to B4), and further selects vehicles that may be over-discharged.

[0032] Although Figures 3 and 4 show an example of going back up to 60 days from the prediction point in time, this number of days is not limited as long as it is a sufficient period to notify the user of the need to replace the battery, and the number of days may be changed as appropriate depending on the type of battery, intended use, and other circumstances.

[0033] On the other hand, the determination unit 22 performs each determination on the server 20 side. For example, in response to a request for predicting the remaining battery charge for an arbitrary work vehicle, the determination unit 22 determines whether or not the work vehicle for which the prediction request has been made is included in the vehicles selected by the remaining battery charge prediction unit 21 (vehicles subject to over-discharge).

[0034] The notification unit 23 notifies the work vehicle 10 and the terminal 30 of the notification from the server 20. For example, when the notification unit 23 determines that the work vehicle for which a prediction request has been made is included in the vehicles (vehicles subject to over-discharge) selected by the battery remaining capacity prediction unit 21, it notifies at least one of the work vehicle and the terminal for which the prediction request has been made of the remaining battery capacity prediction result of the work vehicle for which the prediction request has been made. At that time, the notification unit 23 transmits a signal corresponding to the prediction result via the server communication unit 24 to at least one of the work vehicle and the terminal for which the prediction request has been made.

[0035] The terminal 30 is a PC (Personal Computer) or a mobile terminal. Examples of mobile terminals include a smartphone, a tablet terminal, a mobile phone, and a PDA (Personal Data Assistant). A maintenance worker or a user can request a remaining charge prediction of a battery 11 mounted on any work vehicle 10 from the server 20 via the terminal 30, or can receive a prediction result transmitted from the server 20 via the terminal 30.

[0036] Hereinafter, the control process on the server 20 side in the battery remaining capacity prediction system 1 will be described with reference to FIGS.

[0037] 6 is a flowchart showing the control process on the server side in the battery remaining capacity prediction system. As described above, the server 20 periodically collects operation information of each work vehicle 10, periodically predicts the remaining battery capacity of each work vehicle 10 based on the operation information of each work vehicle 10, and provides the predicted results in response to a request from the terminal 30 or the work vehicle 10.

[0038] First, in step S11, when a maintenance worker or the like wishes to predict the remaining charge of the battery 11 mounted on an arbitrary work vehicle 10 (including vehicles at the time of shipment from the factory), the maintenance worker or the like inputs the management number or the like of the work vehicle 10 into the terminal 30, or selects the management number of the work vehicle 10 displayed on the terminal 30, thereby making a request to the server 20 via the terminal 30. Also, when an operator wishes to predict the remaining charge of the battery 11 mounted on the work vehicle 10 that he or she is operating, the operator sends a signal corresponding to the battery remaining charge prediction request to the server 20 via the control unit 13 and vehicle communication unit 12 of the work vehicle 10 by manual input or the like.

[0039] In the server 20, the server communication unit 24 receives a signal from the terminal 30 or the vehicle communication unit 12 and outputs it to the determination unit 22. When a signal is output from the server communication unit 24, the determination unit 22 determines that there is a request to predict the remaining battery capacity of the work vehicle 10, and identifies the management number of the work vehicle 10 for which the prediction request was made. When it is determined that there is a request to predict the remaining battery capacity of the work vehicle 10, the control process proceeds to step S12.

[0040] On the other hand, if there is no signal output from the server communication unit 24, the determination unit 22 determines that there is no request for predicting the remaining battery capacity of the work vehicle 10. If it is determined that there is no request for predicting the remaining battery capacity of the work vehicle 10, the control process ends.

[0041] In step S12, the determination unit 22 determines whether or not the identified work vehicle 10 (i.e., the work vehicle for which a prediction request was made) has operating hours and operating days based on the management number of the identified work vehicle 10. As described above, the server 20 periodically collects operating information of the work vehicle 10, and stores and accumulates the collected operating information in the information storage unit 25. Therefore, the determination unit 22 checks whether or not the operating hours and operating days of the work vehicle 10 are present in the information storage unit 25. Note that, if the work vehicle 10 is not operating, the operating information of the work vehicle 10 is not transmitted, and therefore is no longer collected by the server 20 after a certain period of time has passed. At this time, the determination unit 22 determines that the work vehicle 10 has no operating hours and operating days. As a result, the control process proceeds to step S13, and a message saying "There is no operating information. Please operate the vehicle" is sent to the requesting terminal or the like to prompt the vehicle to operate. Thereafter, the control process returns to step S11.

[0042] On the other hand, if it is determined in step S12 that the work vehicle 10 for which the prediction request has been made has operating hours and operating days, the control process proceeds to step S14. In step S14, the determination unit 22 determines whether or not the work vehicle 10 for which the prediction request has been made is included in the vehicles subject to over-discharge. At this time, the determination unit 22 determines whether or not the work vehicle 10 is included in the target number shown in FIG. 5 above, based on the management number of the identified work vehicle 10. Note that, although an example of predicting the remaining battery charge based on the operating hours and operating days of the work vehicle 10 will be described here, the remaining battery charge prediction may be based on the operating hours of the work vehicle 10 as shown in FIG. 3, or based on the number of operating days of the work vehicle 10 as shown in FIG. 4.

[0043] If it is determined that the work vehicle for which the prediction request has been made is included in the vehicles subject to over-discharge, i.e., if it is determined that the work vehicle for which the prediction request has been made is a vehicle subject to notification, the control process proceeds to step S15. Here, "vehicle subject to notification" refers to a vehicle that may have a dead battery (i.e., over-discharged). If included in the above target number, the work vehicle becomes a vehicle subject to notification (in other words, a vehicle to which notification is to be sent). Then, in step S15, the notification unit 23 notifies at least one of the terminal 30 and the work vehicle 10 for which the prediction request has been made of the remaining battery charge prediction result for the work vehicle 10 for which the prediction request has been made.

[0044] The notification form of the notification unit 23 may be varied in many ways.

[0045] For example, when a battery remaining capacity prediction for the work vehicle 10 is requested via the terminal 30, the notification unit 23 basically notifies only the terminal 30 of the prediction result, but may notify both the terminal 30 and the work vehicle 10 that made the prediction request depending on the settings. Similarly, when a battery remaining capacity prediction for the work vehicle 10 is requested by the work vehicle 10, the notification unit 23 basically notifies only the work vehicle 10 that made the prediction request of the prediction result, but may notify both the work vehicle 10 that made the prediction request and the terminal 30 depending on the settings.

[0046] At this time, it is preferable that the notification unit 23 also notifies a warning message according to the prediction result of the remaining battery power. An example of the warning message is "The possibility of the battery running out is increasing. We recommend that you drive the work vehicle."

[0047] When the battery remaining charge prediction result and a warning message are notified to the terminal 30 or the work vehicle 10, they are displayed, for example, on the display of the terminal 30 or the display unit 14 of the work vehicle 10. FIG. 8 is an example showing the content displayed on the display of the terminal. In the bar graph shown in FIG. 8, the vertical axis represents the battery remaining charge prediction result, and the horizontal axis represents the number of days. In other words, it shows that the battery remaining charge decreases according to the number of days that pass after the remaining charge prediction date if the work vehicle is not operated. A maintenance worker or the like who has the terminal 30 can easily grasp information regarding the prediction result of the battery remaining charge of the work vehicle 10 by looking at the graph displayed on the display.

[0048] Here, when a maintenance worker or the like taps the bar graph to specify it, detailed information on the remaining battery level and the number of days is preferably enlarged and displayed (see FIG. 8). Here, the remaining battery level may be displayed as a percentage according to the number of days elapsed in a certain period from the time when the remaining battery level is desired, such as "xx%". In this way, the predicted result of the remaining battery level can be easily understood. Furthermore, it is more preferable that the bar graph is displayed in a color according to a preset urgency level based on the predicted result of the remaining battery level. For example, when the predicted result of the remaining battery level is in the range of 15% to 20% of the fully charged capacity, the corresponding bar graph is displayed in blue, when it is in the range of 10% to 15%, the corresponding bar graph is displayed in yellow, and when it is in the range of 5% to 10%, the corresponding bar graph is displayed in red. In this way, visibility can be improved, and the effect of encouraging charging can be improved.

[0049] The notification unit 23 may notify at least one of the work vehicle 10 and the terminal 30 that requested the prediction according to a preset urgency level based on the prediction result of the battery remaining capacity of the work vehicle 10. For example, the notification unit 23 may set a state in which the prediction result of the battery remaining capacity is in the range of 15% to 20% of the full charge capacity as urgency level 1, a state in which the battery remaining capacity is in the range of 10% to 15%, and a state in which the battery remaining capacity is in the range of 5% to 10% as urgency level 3, and notify only the terminal 30 in the case of urgency level 1, while notifying both the terminal 30 and the work vehicle 10 that requested the prediction in the case of urgency levels 2 and 3. Note that the notification destination and the level of urgency level described above are only examples, and may be set arbitrarily according to the convenience of the user. The range of urgency level may also be set arbitrarily. In this way, the effect of encouraging charging to prevent over-discharge can be improved.

[0050] In addition, if the judgment unit 22 judges that the battery is deteriorating based on the battery remaining capacity prediction result, the notification unit 23 may also notify the terminal 30 of information regarding the timing of battery replacement according to the number of days that have passed in the future, and may notify maintenance personnel, for example, by displaying a graph showing the timing of battery replacement on the display.

[0051] Figure 9 shows an example of the notification content displayed on the terminal display. The notification content is a warning message such as "The possibility of the battery running out is increasing. We recommend that you drive the work vehicle. The last day of operation was February 15th," as shown in Figure 9.

[0052] Furthermore, it is preferable that the contents be notified by voice at the same time as the contents are displayed on the display of the terminal 30.

[0053] Also, since the information required differs depending on the recipient of the notification (e.g., a maintenance worker or an agency), the notification content may differ. For example, the maintenance worker's terminal may be notified of the above message, "There is a high possibility that the battery is dead. We recommend that you operate the work vehicle. Last operation date: February 15th," but the agency's terminal may be notified of only the message, "There is a high possibility that the battery is dead. We recommend that you operate the work vehicle.", i.e., no notification of the last operation date. The reverse may also be possible. Furthermore, different standard phrases may be used depending on the recipient of the notification.

[0054] 8 and 9 are also applied to the display unit 14 of the work vehicle 10. By looking at the content displayed on the display unit 14, the operator can easily grasp information related to the prediction results of the remaining battery charge of the work vehicle 10 that he or she is operating.

[0055] The frequency of notifications may be set arbitrarily, although it is sufficient that the notification is sent once when the device is included in the target number in the above process. For example, after the notification is sent once, the same notification may be sent again every hour or every day to alert the maintenance personnel or operator.

[0056] Also, when notifying both the terminal 30 and the work vehicle 10 that has requested the prediction, the frequency of notifications may initially be set to three times per day to the work vehicle 10 and once to the terminal 30, and when no improvement in the remaining battery level due to operation is observed after a certain period of time, notification may be sent twice per day only to the work vehicle 10, and when no improvement in the remaining battery level due to operation is observed, notification may be sent once each to the work vehicle 10 and the terminal 30. Whether or not there has been an improvement in the remaining battery level due to operation can be determined by the battery remaining level prediction unit 21 periodically predicting the remaining battery level based on the operation information of the work vehicle 10, and the determination unit 22 comparing the predicted result with the previous prediction result.

[0057] Also, for example, when the predicted result of the remaining battery charge is one step away from becoming extremely low, the notification unit 23 may notify the prediction result only to the administrator of the server 20, and not notify the terminal 30 held by the maintenance personnel, etc., and when the predicted result of the remaining battery charge has become extremely low, the notification unit 23 may also notify the terminal 30 held by the maintenance personnel, etc.

[0058] The notification timing may be set appropriately, and the notification frequency and notification timing may be set manually or automatically.

[0059] On the other hand, if it is determined in step S14 that the work vehicle for which a prediction request has been made is not included in the vehicles subject to over-discharge, i.e., if it is determined that the work vehicle for which a prediction request has been made is not a vehicle subject to notification, the battery of that work vehicle is not in an over-discharged state, and so the control process ends.

[0060] Fig. 7 is another flowchart showing the control process on the server side in the battery remaining capacity prediction system. The control process shown in Fig. 7 differs from the control process shown in Fig. 6 in that if it is determined in step S14 that the work vehicle for which a prediction has been requested is not included in the vehicles subject to over-discharging, a further determination is made as to whether a prediction under different conditions is desired. Only the differences will be described below.

[0061] Specifically, if it is determined in step S14 that the work vehicle for which the prediction was requested is not included in the vehicles subject to over-discharge, the control process proceeds to step S16. In step S16, the determination unit 22 determines whether or not a prediction under different conditions is desired. "Desiring a prediction under different conditions" indicates that a confirmation is made as to whether a vehicle is included in the vehicles subject to over-discharge when the conditions of the number of operating days or operating hours of a given vehicle are changed. Specifically, this is the case when a given work vehicle is not included in the number of targets at the time of the remaining charge prediction request (in other words, the battery of the given work vehicle is not over-discharged), but the maintenance worker or operator wants to grasp the current state of the remaining battery charge of the given work vehicle and requests a prediction of the remaining battery charge. As in the above, such a request is requested to the server 20 via the control unit 13 and vehicle communication unit 12 of the terminal 30 or the work vehicle 10.

[0062] Then, if it is determined that a prediction under different conditions is desired, the control process proceeds to the above-mentioned step S15, and the notification unit 23 outputs the current prediction result of the remaining battery level to the terminal 30 or the work vehicle 10 in response to the request, and displays the result on the display of the terminal 30 or the display unit 14 of the work vehicle 10.

[0063] On the other hand, if it is determined in step S16 that prediction under different conditions is not desired, the control process ends.

[0064] In the battery remaining capacity prediction system 1 of this embodiment, the server 20 predicts the remaining battery capacity of each of the multiple work vehicles 10 based on at least one of the operating hours and number of operating days of the multiple work vehicles 10, and is equipped with a battery remaining capacity prediction unit 21 that selects vehicles that may be over-discharged (vehicles subject to over-discharge) based on the predicted battery remaining capacity, so that the battery remaining capacity can be accurately predicted without the need for a new configuration.

[0065] In addition, the server 20 includes a determination unit 22 that, in response to a battery remaining capacity prediction request for any work vehicle 10, determines whether the work vehicle 10 for which a prediction request has been made is included among vehicles subject to over-discharge, and a notification unit 23 that notifies at least one of the work vehicle 10 for which the prediction request has been made and the terminal 30 of the battery remaining capacity prediction result of the work vehicle 10 for which the prediction request has been made when it is determined that the work vehicle 10 for which the prediction request has been made is included among vehicles subject to over-discharge, so that by notifying the operator operating the work vehicle 10 or a maintenance worker with the terminal 30, charging to prevent over-discharge can be encouraged. As a result, over-discharge of the battery can be avoided.

[0066] Although the embodiments of the present invention have been described in detail above, the present invention is not limited to the above-described embodiments, and various design modifications can be made without departing from the spirit of the present invention as described in the claims. [Explanation of symbols]

[0067] 1 Battery level prediction system 10 Work vehicles 11 Batteries 12 Vehicle communication unit 13 Control section 14 Display section 20 Servers 21 Battery level prediction section 22 Judgment section 23 Notification Department 24 Server Communication Department 25 Information storage section 30 Terminals

Claims

1. A battery remaining capacity prediction system including a server that is communicatively connected to a plurality of work vehicles equipped with batteries, collects operation information of the work vehicles, and predicts remaining capacity of the batteries, The server, a battery remaining capacity prediction unit that predicts the remaining battery capacity of each of the plurality of work vehicles based on at least one of the operating hours and number of operating days of the plurality of work vehicles, and selects vehicles that may be over-discharged as vehicles to be over-discharged based on the predicted remaining battery capacity and at least one of a combination of a plurality of patterns of the number of days going back from the prediction time point and different operating times of the work vehicles in the number of days going back from the prediction time point, or a combination of a plurality of patterns of the number of days going back from the prediction time point and different numbers of operating days of the work vehicles in the number of days going back from the prediction time point; a determination unit that, in response to a request for prediction of a remaining battery capacity for any one of the work vehicles, determines whether the work vehicle for which the prediction request has been made is included in the vehicles subject to over-discharge; a notification unit that notifies at least one of the work vehicle that has requested the prediction and a terminal that can communicate with the server of a battery remaining capacity prediction result of the work vehicle that has requested the prediction when it is determined that the work vehicle that has requested the prediction is included in the vehicle that is subject to over-discharge; A battery remaining capacity prediction system comprising:

2. The battery remaining capacity prediction system according to claim 1, wherein the notification unit notifies at least one of the work vehicle for which the prediction request was made and the terminal according to a predetermined urgency level based on the battery remaining capacity prediction result of the work vehicle for which the prediction request was made.

3. 3. The battery remaining capacity prediction system according to claim 1, wherein a request for predicting a remaining battery capacity for any one of the work vehicles is made via the terminal.

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