Operation support device and operation support method for electric work machine

Abstract

The invention provides an operation support device capable of suppressing deterioration of a storage battery of an electric working machine and prolonging the service life of the storage battery. An operation support device (1) allocates each of a plurality of electric work machines (EWM1, EWM2,..., EWMn) to each of a plurality of work sites (WS1, WS2,..., WSn). An operation support device (1) is provided with: an information storage unit (11) that stores work load information for each work site (WS); a state acquisition unit (12) that acquires the deterioration state of a battery (B) mounted on each electric work machine (EWM); a state prediction unit (13) that calculates a predicted deterioration state of the battery (B) when each electric work machine (EWM) is working at each work site (WS); and an operation planning unit (14). An operation planning unit (14) selects a work site (WS) in a descending order of work load on the basis of the information stored in the information storage unit (11), and allocates a specific electric work machine (EWM) from among the plurality of electric work machines (EWM1, EWM2,..., EWMn) on the basis of the predicted deterioration state with respect to the selected work site (WS).

Description

Technical Field

[0001] The present invention relates to an operation support device and an operation support method for an electric working machine. Background Art

[0002] Conventionally, there are known inventions related to power supply systems for construction machinery equipped with battery-driven electric motors (see Patent Document 1 below). The power supply system for construction machinery described in Patent Document 1 includes a plurality of towed vehicles, at least one construction machinery, a charging device, at least one transport vehicle, and a computer (paragraph 0009 and claim 1).

[0003] Each of the plurality of towed vehicles is equipped with a battery. The at least one construction machine tows one of the plurality of towed vehicles and includes an electric motor driven by electricity from the battery of the towed vehicle and a hydraulic pump driven by the electric motor. The charging equipment is used to charge the batteries installed in the plurality of towed vehicles.

[0004] The at least one transport vehicle tows a charged towed vehicle among the multiple towed vehicles that has been charged by the charging device to the vicinity of at least one construction machine, and replaces the charged towed vehicle and tows the towed vehicle towed by the construction machine to the charging device.

[0005] The computer predicts the number of replacements of towed vehicles to be replaced by the construction machine during the specified period and the timing of each replacement based on a workload plan for at least one construction machine during the specified period. Furthermore, the computer calculates the time at which at least one transport vehicle will tow the charged towed vehicle to the vicinity of the construction machine, in synchronization with each replacement timing.

[0006] Prior art literature

[0007] Patent Literature

[0008] Patent Document 1: Japanese Patent Application Laid-Open No. 2016-084633 Summary of the Invention

[0009] The conventional power supply system for construction machinery described above can estimate the battery replacement timing based on the construction machinery's workload plan, thereby improving the construction machinery's operating efficiency and battery utilization efficiency (Patent Document 1, paragraph 0010). However, this conventional system does not account for variations in the progression of battery degradation across construction machinery, leaving room for improvement in terms of suppressing battery degradation and extending battery life.

[0010] The present invention provides an operation support device and an operation support method for an electric working machine, which can suppress degradation of a battery of the electric working machine and extend its life.

[0011] One aspect of the present invention is an operation support device for an electric working machine, comprising a server for allocating multiple electric working machines to multiple work sites, the operation support device being characterized in that the server comprises: an information storage unit for storing information on the work loads of the multiple work sites; a state acquisition unit for acquiring the degradation states of the batteries respectively mounted on the multiple electric working machines; a state prediction unit for calculating the predicted degradation states of the batteries when the multiple electric working machines respectively perform work at any one of the multiple work sites; and an operation planning unit for selecting work sites in descending order of the work loads based on the information on the work loads stored in the information storage unit, and allocating specific electric working machines determined based on the degradation states of the batteries acquired by the state acquisition unit and the predicted degradation states of the batteries calculated by the state prediction unit from among the multiple electric working machines in the order of the selected work sites.

[0012] Effects of the Invention

[0013] An operation support device for an electric working machine can be provided that can suppress degradation of a battery of the electric working machine and extend its life. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1A This is a schematic diagram showing a first embodiment of the operation support device according to the present invention.

[0015] Figure 1B Yes Figure 1A The flowchart of an example of the operation of the operation support device shown is shown.

[0016] Figure 2 This is a flowchart illustrating a second embodiment of the operation support device according to the present invention.

[0017] Figure 3 This is a flowchart illustrating a third embodiment of the operation support device according to the present invention.

[0018] Figure 4 This is a flowchart illustrating a fourth embodiment of the operation support device according to the present invention.

[0019] Figure 5 This is a flowchart illustrating a fifth embodiment of the operation support device according to the present invention. DETAILED DESCRIPTION

[0020] Hereinafter, embodiments of an operation support device and an operation support method for an electric working machine according to the present invention will be described with reference to the accompanying drawings.

[0021] [Implementation Method 1]

[0022] Figure 1A This is a schematic diagram illustrating a first embodiment of an operation support device for an electric working machine according to the present invention. Operation support device 1 in this embodiment is, for example, a server configured as a computer having a central processing unit (CPU) and a storage device (not shown), and connected to a network N such as the Internet. Operation support device 1 distributes multiple electric working machines EWM1, EWM2, ..., EWMn to each of multiple work sites WS1, WS2, ..., WSn.

[0023] Each electric working machine EWM is equipped with, for example, a battery B. The electricity stored in the battery B rotates a motor to generate driving force. The multiple electric working machines EWM1, EWM2, ..., EWMn include, for example, at least one of an electric hydraulic excavator, an electric dump truck, or an electric material conveyor. Before being assigned to each work site WS by the operation support device 1, the multiple electric working machines EWM1, EWM2, ..., EWMn are on standby at, for example, a machine station MS.

[0024] Each electric working machine EWM has a communication device (not shown) such as a wireless communication device or a satellite communication device, and a controller (not shown) that calculates the degradation state of battery B. As the degradation state of battery B, for example, the ratio of the fully charged capacity of battery B at the time of degradation to the initial fully charged capacity, that is, "State of Health: SOH", can be used. The degradation state SOH of battery B is expressed as a percentage with the initial fully charged capacity as 100, and the percentage decreases as battery B deteriorates. In addition, the degradation state SOH can also be calculated based on the charge and discharge capacity of battery B during operation of the electric working machine EWM, and the charge capacity of battery B charged by the charging device.

[0025] The communication device mounted on each electric working machine EWM is connected to the operation support device 1 for information communication via, for example, a wireless communication line RCL including a wireless base station WBS or a satellite communication line SCL including a communication satellite CS and a satellite base station SBS, and a network N. The controller mounted on each electric working machine EWM transmits, for example, the state of degradation SOH of the battery B mounted on each electric working machine EWM to the operation support device 1 via the communication device mounted on each electric working machine EWM.

[0026] The operation support device 1 includes, for example, an information storage unit 11, a state acquisition unit 12, a state prediction unit 13, and an operation planning unit 14. Each of these components of the operation support device 1 is implemented by, for example, the CPU of the operation support device 1 executing a program stored in a storage device of the operation support device 1, thereby expressing each function of the operation support device 1. Figure 1B , the operation of the operation support device 1 of the present embodiment and the operation support method OSM for the electric working machine EWM of the present embodiment will be described.

[0027] Figure 1B Yes Figure 1A The flowchart of the operation support device 1 shown is a flowchart illustrating the steps of the operation support method OSM of this embodiment. The operation support method OSM of this embodiment is a method of using the operation support device 1 to allocate each of a plurality of electric working machines EWM1, EWM2, ..., EWMn to each of a plurality of work sites WS1, WS2, ..., WSn.

[0028] If you start Figure 1B In the operation support method OSM shown in FIG. 1 , the operation support device 1 first executes an information storage step S1. In this step S1, the information storage unit 11 stores, for example, workload information for each work site WS. The workload information is input to the input / output unit of the operation support device 1 via a network N, for example, from an information terminal (not shown) held by a user of the electric working machine EWM. The information storage unit 11 then stores the workload information in the storage device of the operation support device 1. Table 1A below shows an example of workload information for each work site WS stored by the information storage unit 11.

[0029] Table 1A

[0030]

[0031] In the example shown in Table 1A, workload information includes, for example, the number of working days, the average temperature during the operating hours (daytime) of the electric working machine (EWM), the average temperature during the non-operating hours (nighttime) of the electric working machine (EWM), daily charge and discharge amounts, discharge power, and charge power. Alternatively, workload information may include discharge current and charge current instead of discharge power and charge power. Next, the operation support device 1 executes a state acquisition step S2 for acquiring the state of degradation (SOH) of the battery B mounted on each electric working machine (EWM).

[0032] In step S2, the state acquisition unit 12 of the operation support device 1 acquires the state of degradation SOH of the battery B mounted on each electric working machine EWM. The controller of each electric working machine EWM acquires the state of degradation SOH of the battery B mounted on each electric working machine EWM, for example, at a predetermined period and transmits the state of degradation SOH to the operation support device 1 via a communication device, a wireless communication line RCL or a satellite communication line SCL, and a network N. The state acquisition unit 12 acquires the state of degradation SOH of the battery B of each electric working machine EWM transmitted from the electric working machine EWM via the input / output unit of the operation support device 1.

[0033] Next, the operation support device 1 executes a work availability prediction step S3 for predicting whether each electric working machine EWM can operate. In step S3, the state prediction unit 13 predicts whether each electric working machine EWM can operate at each work site WS based on, for example, information on the workload of each work site WS stored in the information storage unit 11.

[0034] More specifically, the state prediction unit 13 obtains the specifications of the battery B of each electric working machine EWM stored in the storage device, for example, through the information storage unit 11, and compares these specifications with the daily charge / discharge amount and discharge power required at each work site WS. If the battery B of a particular electric working machine EWM cannot meet the daily charge / discharge amount and discharge power required by a particular work site WS, the prediction unit 13 records that the electric working machine EWM is unable to handle that work site WS.

[0035] Next, the operation support device 1 executes a state prediction step S4 for calculating the predicted state of degradation ESOH of battery B. In this step S4, the state prediction unit 13 of the operation support device 1 calculates the predicted state of degradation ESOH of battery B when each electric working machine EWM performs work at each work site WS. The predicted state of degradation ESOH is the predicted value of the state of degradation SOH of battery B of each electric working machine EWM after each electric working machine EWM performs a predetermined work at each work site WS.

[0036] The state prediction unit 13 predicts the predicted degradation state ESOH of the battery B of each electric working machine EWM, using, for example, all or some of the workload items shown in Table 1A as degradation factors. More specifically, the state prediction unit 13 calculates the predicted degradation state ESOH using, for example, the following equations (1) to (3).

[0037]

Formula 1

[0038]

[0039]

Formula 2

[0040]

[0041]

Formula 3

[0042] ESOH[%]=100-a st ×d 0.5 -a cyc ×d…(3)

[0043] In the above formula (1), a_st is the storage degradation rate of battery B. 0.5 ] (d: day). In the right side of the equation (1), T_st is the storage absolute temperature [K], SOC_st is the storage SOC (0≤SOC_st<1), a0 to a2 are coefficients, and a3 is a constant.

[0044] In equation (2), a_cyc represents the degradation rate of battery B (d). On the right side of equation (2), T_op represents the average operating temperature (°C), D_day represents the daily discharge amount, Dp represents the discharge power, and Cp represents the charge power. Q_bat represents the battery capacity of battery B, a4 to a7 represent coefficients, and a8 represents a constant.

[0045] In the above formula (3), ESOH is the estimated degradation state [%]. In addition, a_st on the right side of the formula (3) is the storage degradation rate of the battery B obtained by the above formula (1) [ / d 0.5 ], a_cyc is the deterioration rate of the battery B obtained by the above formula (2), and d is the number of operating days of the electric working machine EWM.

[0046] That is, the estimated degradation state ESOH is calculated based on the storage degradation rate a_st, which is the degradation rate of battery B during storage or rest without charging or discharging, and the degradation rate a_cyc, which is the cyclic degradation rate due to charging and discharging of battery B. Furthermore, the coefficients a0, a1, a3 to a7, and the constants a3 and a8 in equations (1) and (2) differ for each battery B. Therefore, these coefficients and constants are stored in advance in a storage device for each battery B, for example, via the information storage unit 11 of the operation support device 1.

[0047] Next, the operation support device 1 executes an operation plan creation step S5 for allocating electric working machines (EWMs) to each work site WS. In step S5, the operation planning unit 14 of the operation support device 1 first selects work sites WS in descending order of workload based on workload information for each work site WS stored in the storage device (see Table 1A).

[0048] In step S5, the operation planning unit 14 further allocates a specific electric working machine EWM, determined based on the predicted degradation state ESOH, from among the plurality of electric working machine EWMs to the selected work site WS. An example of the order in which the operation planning unit 14 allocates the electric working machine EWMs to each work site WS is described with reference to Table 1B below.

[0049] Table 1B

[0050]

[0051] In Table 1B, Machine No. is, for example, the identification number of each of the plurality of electric working machines EWM1, EWM2, ..., EWMn. Battery Manufacturer, Battery Capacity, and SOH are, for example, the manufacturer, battery capacity, and latest state of degradation SOH of the battery B mounted on each electric working machine EWM.

[0052] ESOH is the predicted degradation state of battery B after each electric working machine EWM performs specified work at each work site WS. The predicted degradation state ESOH is calculated for each combination of a plurality of work sites WS1, WS2, ..., WSn, selected in descending order of work load (highest on the left, lowest on the right), and a plurality of electric working machines EWM1, EWM2, ..., EWMn.

[0053] ΔSOH is the amount of battery degradation calculated based on the current state of degradation (SOH) and the predicted state of degradation (ESOH) of battery B in each electric working machine (EWM). Specifically, ΔSOH is the change in the state of degradation (SOH) from the current state of degradation (SOH) of battery B in each electric working machine (EWM) to the predicted state of degradation (ESOH) when each electric working machine (EWM) performs work at each work site (WS).

[0054] Specifically, the operation planning unit 14 calculates the battery degradation amount ΔSOH for each electric working machine EWM when operating at each work site WS based on the state of degradation SOH and the predicted state of degradation ESOH of battery B. Furthermore, the operation planning unit 14 selects, for example, work site WS1 with the highest workload and, from among the multiple electric working machines EWM1, EWM2, ..., EWMn, allocates to this work site WS1 the electric working machine EWM2 with a battery degradation amount ΔSOH of -5% and the smallest decrease in state of degradation SOH.

[0055] In the example shown in Table 1B, the electric working machine EWM3, machine No. 3, is predicted to be unable to perform work at the work site WS1 (NA) in the above-mentioned step S3 of predicting whether the electric working machine EWM can operate. In this case, the operation planning unit 14 does not assign the electric working machine EWM3 to the work site WS1.

[0056] After step S5 is completed, the operation planning unit 14 executes step S6, for example, to determine whether all electric working machines (EWMs) have been assigned to work sites WS. If the operation planning unit 14 determines in step S6 that at least one electric working machine (EWM) has not been assigned (No), step S5 is repeated to assign each electric working machine (EWM) to each work site WS.

[0057] In the second step S5, the operation planning unit 14 selects work site WS2, which has the second highest workload. The operation planning unit 14 then assigns to selected work site WS2 the electric working machine EWMn with a battery degradation amount ΔSOH of -5% and the smallest decrease in the degradation state SOH, from among the multiple electric working machines EWM1, EWM3, ..., EWMn, excluding the electric working machine EWM2 already assigned to work site WS1.

[0058] Similarly, in the third step S5, the electric working machine EWM1 is allocated to the work site WS3 with the third highest workload, and in the fourth step S5, the electric working machine EWM3 is allocated to the work site WS4 with the fourth highest workload. Then, in step S6, if the operation planning unit 14 determines that the allocation of the electric working machine EWM to all the work sites WS has been completed (yes), the operation ends. Figure 1B The Operation Support Method OSM is shown.

[0059] The operation planning unit 14, for example, creates an operation plan for the electric working machines EWM and transmits it to the user's information terminal of the electric working machines EWM via the network N. The operation plan includes information about the work sites WS assigned to each electric working machine EWM. Furthermore, the operation planning unit 14 transmits information about the work sites WS assigned to each electric working machine EWM to each electric working machine EWM via the network N and the satellite communication line SCL or the wireless communication line RCL.

[0060] Hereinafter, the effects of the operation support device 1 and the operation support method OSM for the electric working machine EWM according to the present embodiment will be described.

[0061] The operation support device 1 of this embodiment is a device having a server that distributes multiple electric working machines EWM1, EWM2, ..., EWMn to multiple work sites WS1, WS2, ..., WSn. The server has an information storage unit 11, a state acquisition unit 12, a state prediction unit 13, and an operation planning unit 14. The information storage unit 11 stores information on the workload of each of the multiple work sites WS1, WS2, ..., WSn. The state acquisition unit 12 acquires the degradation state of the battery B mounted on each of the multiple electric working machines EWM1, EWM2, ..., EWMn. The state prediction unit 13 calculates the predicted degradation state ESOH of the battery B when each of the multiple electric working machines EWM1, EWM2, ..., EWMn performs work at any of the multiple work sites WS1, WS2, ..., WSn. The operation planning unit 14 selects the work site WS in descending order of the work load based on the work load information stored in the information storage unit 11, and allocates a specific electric working machine EWM determined based on the degradation state of battery B acquired by the state acquisition unit 12 and the predicted degradation state ESOH of battery B calculated by the state prediction unit 13 from among multiple electric working machines EWM1, EWM2, ..., EWMn in the order of the selected work site WS.

[0062] In other words, the operation support device 1 of this embodiment is a server that assigns each of the plurality of electric working machines EWM1, EWM2, ..., EWMn to each of the plurality of work sites WS1, WS2, ..., WSn, as described above. The operation support device 1 includes an information storage unit 11, a state acquisition unit 12, a state prediction unit 13, and an operation planning unit 14. The information storage unit 11 stores information on the workload of each work site WS. The state acquisition unit 12 acquires the state of degradation SOH of the battery B mounted on each electric working machine EWM. The state prediction unit 13 calculates the predicted state of degradation ESOH of the battery B when each electric working machine EWM performs work at each work site WS. The operation planning unit 14 selects a work site WS in descending order of workload based on the information stored in the information storage unit 11 and assigns a specific work site WS, determined based on the predicted state of degradation ESOH, to the selected work site WS from among the plurality of electric working machines EWM.

[0063] With this configuration, the operation support device 1 of this embodiment can allocate appropriate electric working machines EWMs to multiple work sites WS1, WS2, ..., WSn, based on the predicted degradation state ESOH of battery B, in order from work sites WS with high workload to work sites WS with low workload. This prevents the degradation state SOH of battery B from becoming extremely low in each electric working machine EWM, thereby suppressing degradation of battery B and extending its life.

[0064] Furthermore, in the operation support device 1 of this embodiment, the operation planning unit 14 calculates the battery degradation amount ΔSOH when multiple electric working machines EWM1, EWM2, ..., EWMn perform work at multiple work sites WS1, WS2, ..., WSn, based on the degradation state SOH of battery B and the predicted degradation state ESOH of battery B. Furthermore, the operation planning unit 14 selects the electric working machine EWM with the smallest battery degradation amount ΔSOH from among the multiple electric working machines EWM1, EWM2, ..., EWMn as the specific electric working machine WS.

[0065] In other words, in the operation support device 1 of this embodiment, for example, as shown in Table 1B, the operation planning unit 14 calculates the battery degradation amount ΔSOH for each electric working machine EWM when operating at each work site WS based on the degradation state SOH and the predicted degradation state ESOH of battery B. Furthermore, the operation planning unit 14 allocates the electric working machine EWM with the smallest battery degradation amount ΔSOH from among the plurality of electric working machines EWM1, EWM2, ..., EWMn to the work site WS selected in descending order of workload.

[0066] With this configuration, the operation support device 1 of this embodiment can minimize the decrease in the state of degradation (SOH) of the battery B after each electric working machine EWM performs work at each work site WS. As a result, the degradation of the multiple batteries B installed in the multiple electric working machines EWM1, EWM2, ..., EWMn can be suppressed overall, thereby extending the overall life of these batteries B.

[0067] Furthermore, the operation support method OSM of this embodiment is a method for allocating multiple electric working machines EWM1, EWM2, ..., EWMn to multiple work sites WS1, WS2, ..., WSn. As described above, the operation support method OSM of this embodiment includes an information storage step S1, a state acquisition step S2, a state prediction step S4, and an operation plan creation step S5. The information storage step S1 is a step for storing information on the workload of each of the multiple work sites WS1, WS2, ..., WSn. The state acquisition step S2 is a step for acquiring the state of degradation SOH of the batteries B mounted on each of the multiple electric working machines EWM1, EWM2, ..., EWMn. The state prediction step S4 is a step for calculating the predicted state of degradation ESOH of the batteries B when each of the multiple electric working machines EWM1, EWM2, ..., EWMn performs work at any of the multiple work sites WS1, WS2, ..., WSn. The operation plan making process S5 is a process of selecting the work site WS in descending order of the work load based on the work load information stored in the information storage process S1, and allocating a specific electric working machine EWM determined based on the degradation state SOH of the battery B obtained by the state acquisition process S2 and the predicted degradation state ESOH of the battery B calculated by the state prediction process S4 from among multiple electric working machines EWM1, EWM2, ..., EWMn in the order of the selected work site WS.

[0068] In other words, the operation support method OSM of the present embodiment is a method of allocating each of a plurality of electric working machines EWM1, EWM2, ..., EWMn to each of a plurality of work sites WS1, WS2, ..., WSn. As described above, the operation support method OSM of the present embodiment includes an information storage step S1, a state acquisition step S2, a state prediction step S4, and an operation plan preparation step S5. The information storage step S1 is a step of storing information on the work load of each work site WS. The state acquisition step S2 is a step of acquiring the degradation state SOH of the battery B mounted on each electric working machine EWM. The state prediction step S4 is a step of calculating the predicted degradation state ESOH of the battery B when each electric working machine EWM performs work at each work site WS. The operation plan making process S5 is a process of selecting a work site WS in descending order of work load based on the information stored in the information storage process S1, and allocating a specific electric working machine EWM from a plurality of electric working machines EWM1, EWM2, ..., EWMn based on the predicted degradation state ESOH of the battery B relative to the selected work site W.

[0069] With this configuration, the operation support method OSM of this embodiment allows for the allocation of appropriate electric working machines EWMs to multiple work sites WS1, WS2, ..., WSn, based on the predicted degradation state ESOH of battery B, in order from work sites WS with high workload to work sites WS with low workload. This prevents the degradation state SOH of battery B from becoming extremely low in each electric working machine EWM, thereby suppressing degradation of battery B and extending its life.

[0070] As described above, according to the present embodiment, it is possible to provide the operation support device 1 and the operation support method OSM for an electric working machine that enable suppression of degradation and extension of the life of the battery B of the electric working machine EWM.

[0071] [Implementation Method 2]

[0072] Below, refer to Figure 1A 、 Figure 2 and Table 2, a second embodiment of the operation support device and operation support method for an electric working machine according to the present invention will be described. Figure 2 It is a flowchart for explaining the operation of the operation support device 1 according to the present embodiment, and is a flowchart for explaining each step of the operation support method OSM2 according to the present embodiment.

[0073] In the operation support device 1 and operation support method OSM2 of this embodiment, the operation of the operation planning unit 14 in the operation plan creation step S5a differs from the operation support device 1 and operation support method OSM of the aforementioned embodiment 1. The operation support device 1 and operation support method OSM2 of this embodiment are otherwise identical to the operation support device 1 and operation support method OSM of the aforementioned embodiment 1. Therefore, identical portions are denoted by the same reference numerals, and their descriptions are omitted.

[0074] When the operation support device 1 of this embodiment starts Figure 2 The operation support method OSM2 shown in FIG. 1 is similar to the operation support method OSM described above, and proceeds from the information storage step S1 to the state prediction step S4. Thus, as shown in Table 2, the predicted degradation state ESOH and battery degradation amount ΔSOH are calculated for each of the plurality of electric working machines EWM1, EWM2, ..., EWMn when operating at each of the plurality of work sites WS1, WS2, ..., WSN.

[0075]

Table 2

[0076]

[0077] The operation planning unit 14 of the operation support device 1 then executes the operation plan creation step S5a. In the operation support method OSM2 of this embodiment, the operation plan creation step S5a includes, for example, the following steps S51a through S55a. In step S51a, the operation planning unit 14 determines whether any of the multiple electric working machines EWM1, EWM2, ..., EWMn has a predicted degradation state ESOH of the battery B that is greater than a predetermined value when each of the multiple electric working machines EWM1, EWM2, ..., EWMn is operating at the selected work site WS.

[0078] Here, the operation planning unit 14 sets the predetermined value used for the determination in step S51a to, for example, 80%. Furthermore, in step S51, as shown in Table 2, the operation planning unit 14 determines whether any of the plurality of electric working machines EWM1, EWM2, ..., EWMn has a predicted degradation state ESOH exceeding a predetermined value when operating at the initially selected work site WS1.

[0079] At work site WS1, the predicted degradation state ESOH of battery B in electric working machines EWM1 and EWM4, machines No. 1 and 4, is 80% or higher, a predetermined value. Therefore, in step S51a, the operation planning unit 14 determines that there is an electric working machine EWM with a predicted degradation state ESOH exceeding the predetermined value (Yes), and proceeds to the subsequent step S52a.

[0080] In step S52a, the operation planning unit 14 determines whether there are multiple electric working machines (EWMs) with a predicted state of degradation (ESOH) exceeding a specified value. At worksite WS1, the predicted state of degradation (ESOH) of battery B in electric working machines EWM1 and EWM4, machines No. 1 and 4, is 80% or higher, the specified value. Therefore, in step S52a, the operation planning unit 14 determines that there are multiple electric working machines (EWMs) with a predicted state of degradation (ESOH) exceeding the specified value (Yes), and proceeds to the subsequent step S53a.

[0081] In step S53a, the operation planning unit 14 allocates a specific electric working machine EWM from among the plurality of electric working machines EWM1, EWM2, ..., EWMn to the selected work site WS1 based on the predicted state of degradation ESOH of battery B when each electric working machine EWM performs work at the work site WS1. More specifically, as shown in Table 2, for example, the electric working machine EWM4 having the smallest battery degradation amount ΔSOH calculated based on the state of degradation SOH of battery B and the predicted state of degradation ESOH of each electric working machine EWM is allocated to the work site WS1.

[0082] Furthermore, in step S53a, the operation planning unit 14, similar to the first embodiment described above, excludes the work site WS3, which was determined in step S3 to be unable to handle the work (NA) within the work site WS1, from the plurality of electric working machines EWM1, EWM2, ..., EWMn assigned to the work site WS1. Next, the operation planning unit 14, similar to the first embodiment described above, executes step S6. If it is determined that the assignment of the electric working machines EWM to all work sites WS is not complete (No), the steps following step S51a are repeated.

[0083] In the second step S51a, the operation planning unit 14 selects the work site WS2 with the second highest workload, for example, as shown in Table 2. Then, the operation planning unit 14 determines whether, among the plurality of electric working machines EWM1, EWM2, ..., EWMn, excluding the electric working machine EWM4 already assigned to the other work site WS1, there is an electric working machine EWM whose predicted state of degradation ESOH, when operating at the work site WS2, is greater than or equal to a predetermined value.

[0084] Here, as shown in Table 2, for example, if the prescribed value is set to 80%, then when only electric working machine EWM1, in addition to electric working machine EWM4, performs work at work site WS2, the predicted state of degradation ESOH is greater than the prescribed value. Therefore, in this second step S51a, the operation planning unit 14 determines that there is an electric working machine EWM with a predicted state of degradation ESOH greater than the prescribed value (Yes), and further, in the second step S52a, determines that there are not multiple electric working machines EWM with a predicted state of degradation ESOH greater than the prescribed value (No).

[0085] In this case, the operation planning unit 14 executes step S54a to allocate the electric working machine EWM1 having a predicted degradation state ESOH of a predetermined value or greater to the selected work site WS2. Furthermore, the operation planning unit 14 executes step S6 for the second time, determines that the allocation of the electric working machine EWM to all the work sites WS has not been completed (No), and executes step S51a for the third time. In this third step S51a, the operation planning unit 14 selects the work site WS3 having the third highest workload.

[0086] Here, as shown in Table 2, if the prescribed value is set to 80%, for example, there are no electric working machines EWMs whose predicted state of degradation ESOH of battery B exceeds the prescribed value after performing work at work site WS3, except for electric working machines EWM4 and EWM1 already assigned to other work sites WS1 and WS2. Therefore, in this third step S51a, the operation planning unit 14 determines that there are no electric working machines EWMs whose predicted state of degradation ESOH exceeds the prescribed value (No), and proceeds to the subsequent step S55a.

[0087] In step S55a, the operation planning unit 14 assigns the electric working machine EWM3, which has the highest predicted state of degradation ESOH of battery B, to the selected work site WS3, from among the multiple electric working machines EWM2, EWM3, ..., EWMn, excluding the electric working machines EWM4 and EWM1 already assigned to the other work sites WS1 and WS2. The operation planning unit 14 then proceeds through step S6 and the fourth step S51a, and executes the second step S55a.

[0088] In this second step S55a, the operation planning unit 14 selects the work site WS4 with the fourth highest workload. Furthermore, the operation planning unit 14 excludes the electric working machines EWM4, EWM1, and EWM3 already assigned to the other work sites WS1, WS2, and WS3 from the candidate electric working machines EWM to be assigned to the selected work site WS4. Furthermore, the operation planning unit 14 assigns the electric working machine EWMn with the highest predicted state of degradation ESOH of battery B from among the multiple electric working machines EWM2, ..., EWMn, to the selected work site WS4.

[0089] Then, in step S6, if the operation planning unit 14 determines that the allocation of the electric working machines EWM to all the work sites WS has been completed (Yes), the operation support device 1 ends. Figure 2 The operation support method OSM2 is shown.

[0090] As described above, in the operation support device 1 of this embodiment, the operation planning unit 14 determines whether, among the plurality of electric working machines EWM1, EWM2, ..., EWMn, there is an electric working machine EWM whose predicted state of degradation ESOH of battery B is greater than or equal to a predetermined value. Furthermore, if such an electric working machine EWM is present, the operation planning unit 14 selects, from among the plurality of electric working machines EWM1, EWM2, ..., EWMn, an electric working machine EWM4 whose predicted state of degradation ESOH of battery B is greater than or equal to the predetermined value and whose battery degradation amount ΔSOH is the smallest, as the specific electric working machine EWM.

[0091] In other words, in the operation support device 1 of this embodiment, the operation planning unit 14 determines whether there are multiple electric working machines EWMs whose predicted degradation state ESOH is greater than or equal to a predetermined value among the multiple electric working machines EWM1, EWM2, ..., EWMn. Furthermore, if such multiple electric working machines EWMs exist, the operation planning unit 14 allocates, to the selected work site WS1, the electric working machine EWM4 whose predicted degradation state ESOH of battery B is greater than or equal to the predetermined value and whose battery degradation amount ΔSOH is minimized from among the multiple electric working machines EWM1, EWM2, ..., EWMn.

[0092] With this configuration, the operation support device 1 of this embodiment can allocate an electric working machine EWM4, whose battery B has a predicted state of degradation ESOH greater than a predetermined value and a minimum battery degradation amount ΔSOH, to a work site WS1, where the workload is higher than that of other work sites WS2, WS3, ..., WSn. Therefore, compared to allocating electric working machines EWM1, EWM2, ..., EWMn equipped with batteries B having relatively low predicted states of degradation ESOH and relatively large battery degradation amounts ΔSOH to the work site WS1 with a relatively high workload, the operation support device 1 of this embodiment can suppress the degradation of the batteries B and extend their lifespans in the multiple electric working machines EWM1, EWM2, ..., EWMn.

[0093] In addition, in the operation support device 1 of the present embodiment, when the operation planning unit 14 determines that there is only one electric working machine EWM1 whose predicted degradation state ESOH is greater than a specified value among a plurality of electric working machines EWM1, EWM2, ..., EWMn, the electric working machine EWM1 whose predicted degradation state ESOH is greater than a specified value is allocated to the selected work site WS2.

[0094] With this configuration, the operation support device 1 of this embodiment can allocate an electric working machine EWM1 whose battery B has a predicted degradation state ESOH of at least a predetermined value to a work site WS2 where the workload is higher than that of the other work sites WS3 and WS4. Therefore, compared to allocating electric working machines EWM2, EWM3, ..., EWMn equipped with batteries B having relatively low predicted degradation states ESOH to the work site WS2 where the workload is relatively high, the operation support device 1 of this embodiment can suppress the degradation of the batteries B in the plurality of electric working machines EWM2, EWM3, ..., EWMn and extend their lifespan.

[0095] In addition, in the operation support device 1 of the present embodiment, when there is no electric working machine EWM in which the predicted degradation state ESOH of battery B is greater than a specified value among the multiple electric working machines EWM2, EWM3, ..., EWMn, the operation planning unit 14 selects the electric working machine EWM in which the predicted degradation state ESOH of battery B is the largest from among the multiple electric working machines EWM2, EWM3, ..., EWMn as the specific electric working machine EWM.

[0096] In other words, in the operation support device 1 of this embodiment, the operation planning unit 14 allocates the electric working machine EWM3 having the largest predicted state of degradation ESOH from among the plurality of electric working machines EWM2, EWM3, ..., EWMn, to the selected work site WS3. Similarly, the operation planning unit 14 allocates the electric working machine EWMn having the largest predicted state of degradation ESOH from among the plurality of electric working machines EWM2, ..., EWMn, to the selected work site WS4.

[0097] With this configuration, the operation support device 1 of this embodiment can allocate the electric working machine EWM3, which has the highest predicted state of degradation ESOH for battery B, to work site WS3, where the workload is higher than at other work sites WS4. Similarly, the electric working machine EWMn, which has the highest predicted state of degradation ESOH for battery B, can be allocated to work site WS4, where the workload is higher than at other work sites WS. Therefore, the operation support device 1 of this embodiment can suppress the degradation of batteries B and extend their lifespans in multiple electric working machines EWM2, EWM3, ..., EWMn.

[0098] As described above, according to this embodiment, similar to the first embodiment, it is possible to provide an operation support device 1 and an operation support method OSM2 for an electric working machine EWM that can suppress degradation of the battery B and extend the life of the battery B.

[0099] [Implementation Method 3]

[0100] Below, refer to Figure 1A 、 Figure 3 , Table 3A and Table 3B illustrate a third embodiment of the operation support device and operation support method for an electric working machine according to the present invention. Figure 3 It is a flowchart for explaining the operation of the operation support device 1 according to the present embodiment, and is a flowchart for explaining each step of the operation support method OSM3 according to the present embodiment.

[0101] The operation support device 1 and operation support method OSM3 of this embodiment differ from the operation support device 1 and operation support method OSM of the first embodiment described above in that the operation planning unit 14 executes the sales review step S7 and in the subsequent operation plan creation step S5b. The operation support device 1 and operation support method OSM3 of this embodiment are otherwise similar to the operation support device 1 and operation support method OSM of the first embodiment described above. Therefore, identical components are denoted by identical reference numerals and their descriptions are omitted.

[0102] When the operation support device 1 of this embodiment starts Figure 3 The illustrated operation support method OSM3 executes steps S1 through S4, similar to the first embodiment described above. The operation support device 1 then executes a sales review step S7. This step S7, for example, includes subsequent steps S71 through S73. In step S71, the operation planning unit 14 of the operation support device 1 determines whether each of the plurality of electric working machines EWM1, EWM2, ..., EWMn meets the evaluation criteria for the used market.

[0103] More specifically, the operation planning unit 14 obtains, from the information storage unit 11, the state of degradation (SOH), usage period, and total operating time of the battery B of each electric working machine EWM stored in the storage device, as shown in Table 3A below, for example. Furthermore, the operation planning unit 14 obtains, from the information storage unit 11, the secondhand market valuation index for each of the plurality of electric working machines EWM1, EWM2, ..., EWMn stored in the storage device, as shown in Table 3B below, for example.

[0104] Table 3A

[0105]

[0106] Table 3B

[0107]

[0108] For example, as shown in Table 3B, the secondhand market evaluation indicators for each electric working machine EWM include conditions such as the usage period, total operating time, and the state of degradation (SOH) of the battery B, which are set for each of the multiple electric working machines EWM1, EWM2, ..., EWMn. These conditions can be set to any conditions that allow each electric working machine EWM to be sold at a price higher than that determined by the secondhand market.

[0109] Furthermore, the state of degradation (SOH), usage period, total operating time, and secondhand market evaluation index for each electric working machine (EWM) change over time and can therefore be updated periodically, for example. Furthermore, this information is updated if the battery manufacturer or battery capacity is changed, such as by replacing battery B.

[0110] In step S71, the operation planning unit 14, for example, excludes the electric working machine EWM3, which was determined in step S3 to be incapable of handling the work site WS1 (NA), from the determination targets. Furthermore, in step S71, the operation planning unit 14 compares the degradation state SOH, usage period, and total operating time of the battery B of each of the plurality of electric working machines EWM1, EWM2, ..., EWMn shown in Table 3A, for example, with the conditions of each electric working machine EWM shown in Table 3B.

[0111] In the example shown in Table 3A, excluding electric working machine EWM3, the state of degradation (SOH) of battery B, the usage period, and the total operating time of electric working machines EWM1, EWM2, and EWM4 (machines No. 1, 2, and 4, respectively, enclosed by bold frames) meet the secondhand market evaluation indicators for each of the electric working machines EWM1, EWM2, and EWM4 enclosed by bold frames in Table 3B. In this case, the operation planning unit 14 determines in step S71 that electric working machines EWM1, EWM2, and EWM4 meet the secondhand market evaluation indicators (Yes).

[0112] Furthermore, the operation planning unit 14 determines in step S71 that the electric working machines EWM3 and EWMn do not meet the evaluation index of the second-hand market (No). The operation planning unit 14 then executes step S72 to determine whether the electric working machines EWM1, EWM2, and EWM4 meeting the evaluation index of the second-hand market can be sold.

[0113] More specifically, in step S72, the operation planning unit 14 transmits a query to the user's terminal regarding the availability of electric working machines EWM1, EWM2, and EWM4, and receives an input from the user regarding the availability of the electric working machines. In step S72, the operation planning unit 14 determines, based on the input availability of the electric working machines EWM1, EWM2, and EWM4, whether the electric working machines EWM1, EWM2, and EWM4 are available for sale. If the operation planning unit 14 determines in step S72 that the electric working machines EWM1, EWM2, and EWM4 are not available for sale (No), step S5b is executed for the first time.

[0114] In this first step S5b, the operation planning unit 14, similar to the first embodiment described above, selects the work site WS1 with the highest workload. Furthermore, as shown in Table 3A, the operation planning unit 14 assigns the electric working machine EWM2 whose battery B has the lowest battery degradation amount ΔSOH when working at the selected work site WS1 to the selected work site WS1. The operation planning unit 14 then proceeds to the second step S71, via step S6.

[0115] In this second step S71, the operation planning unit 14 determines that the electric working machines EWM1 and EWM4 meet the evaluation criteria for the used market (Yes), and then executes the second step S72. If, in this second step S72, the operation planning unit 14 determines that the electric working machines EWM1 and EWM4 are unsaleable (No), the second step S5b is executed. In this second step S5b, the operation planning unit 14 allocates the electric working machine EWM4, which has the smallest battery degradation amount ΔSOH, from the remaining multiple electric working machines EWM1, EWM3, EWM4, and EWMn, to the work site WS2 with the second highest workload.

[0116] The operation planning unit 14 then proceeds to step S71 for the third time, after step S6. In step S71, the operation planning unit 14 determines whether the electric working machines EWM1 and EWM3 meet the secondhand market evaluation criteria (Yes), and then proceeds to step S72 for the third time. In step S72, if the operation planning unit 14 determines that the electric working machine EWM1 is unsaleable (No) and that the electric working machine EWM3 is sellable (Yes), for example, then proceeds to step S73.

[0117] In step S73, the operation planning unit 14 records the information of the electric working machine EWM3 to be sold in the storage device, for example, via the information storage unit 11. Then, step S5b is executed for the third time. In this third step S5b, the operation planning unit 14 assigns the electric working machine EWM3 to be sold, for example, that was determined to be available for sale (yes) in the previous step S72, to the work site WS3 with the third highest workload. Furthermore, the electric working machine EWM3 to be sold is sold on the secondhand market, for example, after the work at the work site WS3 is completed. The operation planning unit 14 then executes step S71 for the fourth time, via step S6.

[0118] In this fourth step S71, the operation planning unit 14 determines that the electric working machine EWM1 meets the evaluation criteria for the used market (Yes), and then executes the fourth step S72. In this fourth step S72, if the operation planning unit 14 determines that the electric working machine EWM1 is unsaleable (No), for example, the operation planning unit 14 executes the fourth step S5b. In this fourth step S5b, the operation planning unit 14 allocates the electric working machine EWMn with the smallest battery degradation amount ΔSOH, for example, from among the remaining multiple electric working machines EWM1 and EWMn, to the work site WS4 with the fourth highest workload.

[0119] As described above, in the operation support device 1 of this embodiment, the operation planning unit 14 records, as sales targets, electric working machines EWM4 that meet predetermined secondhand market evaluation indicators and are determined by the user to be resaleable, among the plurality of electric working machines EWM1, EWM2, ..., EWMn. With this configuration, the operation support device 1 and operation support method OSM3 of this embodiment not only achieve the same effects as the operation support device 1 and operation support method OSM of the first embodiment described above, but also enable the selection of electric working machines EWM with high market value and their subsequent sale at high prices on the secondhand market.

[0120] [Implementation Method 4]

[0121] Below, refer to Figure 1A 、 Figure 4 and Table 4, a fourth embodiment of the operation support device and operation support method for an electric working machine according to the present invention will be described. Figure 4 It is a flowchart for explaining the operation of the operation support device 1 according to the present embodiment, and is a flowchart for explaining each step of the operation support method OSM4 according to the present embodiment.

[0122] In the operation support device 1 and operation support method OSM4 of this embodiment, the operation of the operation planning unit 14 in the operation plan creation step S5c differs from the operation support device 1 and operation support method OSM of the aforementioned embodiment 1. The operation support device 1 and operation support method OSM4 of this embodiment are otherwise identical to the operation support device 1 and operation support method OSM of the aforementioned embodiment 1. Therefore, identical portions are denoted by the same reference numerals and their descriptions are omitted.

[0123] When the operation support device 1 of this embodiment starts Figure 4The illustrated operation support method OSM4 executes steps S1 to S4, similarly to the first embodiment described above. The operation support device 1 then executes the operation plan creation step S5c. In step S5c, the operation planning unit 14 of the operation support device 1 selects work sites WS in descending order of workload based on the information stored in the information storage unit 11, similarly to the first embodiment described above.

[0124] Furthermore, similar to the first embodiment described above, the operation planning unit 14 allocates a specific electric working machine EWM, determined based on the predicted degradation state ESOH, from among the plurality of electric working machine EWMs to the selected work site WS. Here, for example, as shown in Table 4 below, the operation planning unit 14 allocates the electric working machine EWM having the highest predicted degradation state ESOH from among the plurality of electric working machine EWMs to the selected work site WS.

[0125]

Table 4

[0126]

[0127] As shown in Table 4, at work site WS1, which has the highest workload, electric work machine EWM1, which has the highest predicted state of degradation ESOH, is assigned from among multiple electric work machines EWM1, EWM2, ..., EWMn, excluding electric work machine EWM3, which was excluded due to inability to handle (NA). Similarly, electric work machine EWM2 is assigned to work site WS2, electric work machine EWMn is assigned to work site WS3, and electric work machine EWM3 is assigned to work site WS4.

[0128] According to the operation support device 1 and operation support method OSM4 of this embodiment, electric working machines EWM with the highest predicted degradation state ESOH of battery B after operation can be allocated sequentially from work sites WS with high workloads to work sites WS with low workloads. Therefore, according to this embodiment, similar to the above-described first embodiment, an operation support device 1 and operation support method OSM4 for electric working machines can be provided, which enable the reduction of degradation of battery B in electric working machines EWM and the extension of their lifespan.

[0129] [Implementation 5]

[0130] Below, refer to Figure 1A 、 Figure 5 , Table 5A and Table 5B illustrate a fifth embodiment of the operation support device and operation support method for an electric working machine according to the present invention. Figure 5 It is a flowchart for explaining the operation of the operation support device 1 according to the present embodiment, and is a flowchart for explaining each step of the operation support method OSM5 according to the present embodiment.

[0131] In the operation support device 1 and operation support method OSM5 of this embodiment, the operation of the operation planning unit 14 in the operation plan creation step S5d differs from the operation support device 1 and operation support method OSM of the aforementioned embodiment 1. The operation support device 1 and operation support method OSM5 of this embodiment are otherwise identical to the operation support device 1 and operation support method OSM of the aforementioned embodiment 1. Therefore, identical portions are denoted by the same reference numerals and their descriptions are omitted.

[0132] When the operation support device 1 of this embodiment starts Figure 5 The illustrated operation support method OSM5 executes steps S1 through S4, similar to the first embodiment described above. The operation support device 1 then executes the operation plan creation step S5d. In the operation support method OSM5 of this embodiment, the operation plan creation step S5d includes, for example, steps S51d through S55d below. The operation plan creation step S5d executed by the operation support device 1 according to this embodiment will be described below with reference to Tables 5A and 5B.

[0133] Table 5A

[0134]

[0135] Table 5B

[0136]

[0137] In step S51d, after selecting the work site WS1 with the highest workload, the operation planning unit 14 determines whether there is an electric working machine (EWM) that meets the specified evaluation criteria. The evaluation criteria for the electric working machine (EWM) include, for example, the usage period, total operating time, and state of degradation (SOH) set for each electric working machine (EWM), as shown in Table 5B.

[0138] Here, let's refer to the predicted state of degradation ESOH of batteries B of each electric working machine EWM, when work is being performed at work site WS1, as shown in Table 5A. The predicted state of degradation ESOH of electric working machine EWM1 satisfies the conditions for the state of degradation SOH shown in Table 5B, as well as the conditions for the period of use and total operating time. Meanwhile, the predicted state of degradation ESOH of batteries B of the other electric working machines EWM do not meet the state of degradation SOH requirements of the evaluation indicators for each electric working machine EWM.

[0139] In this case, the operation planning unit 14 determines in step S51d that an electric working machine EWM that meets the evaluation criteria exists (Yes). In the subsequent step S52d, it determines that no electric working machines EWM meet the evaluation criteria (No). Furthermore, the operation planning unit 14 executes step S54d to assign an electric working machine EWM1 that meets the evaluation criteria to the selected work site WS1. The operation planning unit 14 then executes step S6 and executes step S51d a second time.

[0140] In this second step S51d, the operation planning unit 14 selects work site WS2, which has the second highest workload. Furthermore, the operation planning unit 14 determines whether there is an electric working machine EWM whose usage period, total operating time, and predicted degradation state ESOH of battery B when working at the selected work site WS2 meet the evaluation criteria. At work site WS2, only electric working machine EWM4, machine No. 4, meets the evaluation criteria.

[0141] In this case, the operation planning unit 14 determines in the second step S51d that an electric working machine EWM that meets the evaluation criteria exists (Yes), and in the second step S52d that no multiple electric working machines EWM meet the evaluation criteria (No). Furthermore, the operation planning unit 14 executes the second step S54d to assign an electric working machine EWM4 that meets the evaluation criteria to the selected work site WS2. The operation planning unit 14 then proceeds to the third step S51d via step S6.

[0142] In this third step S51d, the operation planning unit 14 selects work site WS3, which has the third highest workload. Furthermore, the operation planning unit 14 determines whether there is an electric working machine EWM whose usage period, total operating time, and predicted degradation state ESOH of battery B when working at the selected work site WS3 meet the evaluation criteria. At work site WS3, only electric working machine EWM3, machine No. 3, meets the evaluation criteria.

[0143] In this case, the operation planning unit 14 determines in the third step S51d that an electric working machine EWM that meets the evaluation criteria exists (Yes), and in the third step S52d that no multiple electric working machines EWM meet the evaluation criteria (No). Furthermore, the operation planning unit 14 executes the third step S54d to assign the electric working machine EWM3 that meets the evaluation criteria to the selected work site WS3. The operation planning unit 14 then proceeds to step S6 and executes the fourth step S51d.

[0144] In this fourth step S51d, the operation planning unit 14 selects work site WS4, which has the fourth highest workload. Furthermore, the operation planning unit 14 determines whether there are any electric working machines EWM whose usage period, total operating time, and predicted degradation state ESOH of battery B when working at the selected work site WS4 meet the evaluation criteria. At work site WS4, two electric working machines, EWM2 and EWMn, machines No. 2 and n, meet the evaluation criteria.

[0145] In this case, the operation planning unit 14 determines in the fourth step S51d that an electric working machine EWM that meets the evaluation criteria exists (Yes), and in the fourth step S52d that multiple electric working machines EWM meet the evaluation criteria (Yes). Furthermore, the operation planning unit 14 executes the subsequent step S53d to assign the electric working machine EWM2 with the highest predicted degradation state ESOH among the multiple electric working machines EWM2 and EWMn that meet the evaluation criteria to the selected work site WS4.

[0146] On the other hand, if the operation planning unit 14 determines in step S51d that there is no work machine that meets the evaluation index (No), it executes step S55d of allocating the electric work machine EWM with the smallest battery degradation amount ΔSOH to the selected work site WS. Then, if the operation planning unit 14 determines in step S6 that the allocation of the electric work machine EWM to all work sites WS is completed, the operation support device 1 ends. Figure 5 The operation support method OSM5 is shown.

[0147] As described above, in the operation support device 1 of this embodiment, when there is an electric working machine EWM that meets the specified evaluation indicators among multiple electric working machine EWMs, the operation planning unit 14 selects an electric working machine EWM that meets the evaluation indicators and has the largest predicted degradation state ESOH of the battery B from among the multiple electric working machine EWMs as a specific electric working machine EWM.

[0148] In other words, in the operation support device 1 of this embodiment, when multiple electric working machine EWMs satisfying a predetermined evaluation criterion exist among multiple operation support devices 1, the operation planning unit 14 allocates, from among the multiple electric working machine EWMs, an electric working machine EWM that satisfies the evaluation criterion and has the highest predicted degradation state ESOH, to the selected work site WS. With this configuration, the operation support device 1 and operation support method OSM5 of this embodiment achieve the same effects as those of the aforementioned first embodiment, while also enabling appropriate management of the specifications of the electric working machine EWMs allocated to each work site WS.

[0149] The above describes in detail the implementation of the operation support device and operation support method for an electric working machine of the present invention using the accompanying drawings, but the specific structure is not limited to this implementation. Design changes can be made within the scope of the present invention, and these are also included in the present invention.

[0150] Description of Reference Numerals

[0151] 1: Server (operation support device)

[0152] 11: Information storage department

[0153] 12: Status acquisition unit

[0154] 13: Status Prediction Department

[0155] 14: Operation Planning Department

[0156] B: Battery

[0157] ESOH: Predicting Degradation State

[0158] EWM, EWM1-EWMn: Electric working machinery

[0159] OSM, OSM2-OSM5: Operation support methods

[0160] S1: Information storage process

[0161] S2: Status acquisition process

[0162] S4: Status prediction process

[0163] S5, S5a-S5d: Operation plan making process

[0164] SOH: State of Deterioration

[0165] WS, WS1-WSn: Work site

[0166] ΔSOH: Battery degradation amount.

Claims

1. An operation support device for an electric working machine, comprising a server for distributing a plurality of electric working machines to a plurality of working sites, The operation support device is characterized in that: The server has: an information storage unit for storing information on work loads of the plurality of work sites; a state acquisition unit configured to acquire a deterioration state of the batteries respectively mounted on the plurality of electric working machines; a state prediction unit that calculates a predicted deterioration state of the battery when each of the plurality of electric working machines performs work at any one of the plurality of work sites; and An operation planning unit selects a work site in descending order of the work load based on the information of the work load stored in the information storage unit, and allocates a specific electric working machine determined based on the degradation state of the battery acquired by the state acquisition unit and the predicted degradation state of the battery calculated by the state prediction unit from among the plurality of electric working machines in the order of the selected work sites.

2. The operation support device for an electric working machine according to claim 1, wherein: The operation planning unit calculates the battery degradation amount when the plurality of electric working machines respectively perform work at the plurality of work sites based on the battery degradation state and the predicted battery degradation state, and selects the electric working machine with the smallest battery degradation amount from the plurality of electric working machines as the specific electric working machine.

3. The operation support device for an electric working machine according to claim 2, wherein: When there is an electric working machine among the plurality of electric working machines whose predicted degradation state of the battery is greater than a specified value, the operation planning unit selects an electric working machine from the plurality of electric working machines whose predicted degradation state of the battery is greater than the specified value and whose battery degradation amount is the smallest as the specific electric working machine.

4. The operation support device for an electric working machine according to claim 2, wherein: If there is no electric working machine among the plurality of electric working machines whose predicted battery degradation state is greater than or equal to a predetermined value, the operation planning unit selects an electric working machine with the highest predicted battery degradation state from among the plurality of electric working machines as the specific electric working machine.

5. The operation support device for an electric working machine according to claim 3, wherein: If there is no electric working machine among the plurality of electric working machines whose predicted battery degradation state is greater than or equal to a predetermined value, the operation planning unit selects an electric working machine with the highest predicted battery degradation state from among the plurality of electric working machines as the specific electric working machine.

6. The operation support device for an electric working machine according to claim 1, wherein: When an electric working machine that satisfies a predetermined evaluation index exists among the plurality of electric working machines, the operation planning unit selects, as the specific electric working machine, an electric working machine that satisfies the evaluation index and has the highest predicted degradation state of the battery from among the plurality of electric working machines.

7. The operation support device for an electric working machine according to claim 1, wherein: The operation planning unit records, as sales targets, electric working machines that satisfy a predetermined secondhand market evaluation index and are determined by a user to be sellable, among the plurality of electric working machines.

8. A method for supporting the operation of an electric working machine, comprising: allocating a plurality of electric working machines to a plurality of working sites; The operation support method is characterized by comprising: an information storage step of storing information on work loads of the plurality of work sites; a state acquisition step of acquiring a degradation state of batteries respectively mounted on the plurality of electric working machines; a state prediction step of calculating a predicted deterioration state of the battery when each of the plurality of electric working machines performs work at any one of the plurality of work sites; and An operation plan making process selects a work site in descending order of the work load based on the information of the work load stored in the information storage process, and allocates a specific electric working machine from among the plurality of electric working machines in the order of the selected work sites based on the degradation state of the battery acquired by the state acquisition process and the predicted degradation state of the battery calculated by the state prediction process.

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