Work support system

Abstract

To create a work plan for suitably supporting the work of electric work machines while preventing the stop of the electric work machines due to the abnormality of batteries.SOLUTION: A controller of a wok support system calculates a predicted value(s) of a battery state parameter(s) including at least one of the voltage, charge rate and temperature of each battery when each electric work machine is operated according to a work plan, a predicted work time and a predicted battery deterioration amount. The controller calculates a risk index showing the risk of the stoppage of each electric work machine based on the predicted value(s) of the battery state parameter(s). The controller adjusts the risk index based on at least one of an estimated error index showing an error in an estimated result of the operation of each electric work machine according to the work plan and a load fluctuation index showing the fluctuation width of a load on each battery in the work according to the work plan. The controller outputs the work plan when the values of objective functions including the predicted work time, the predicted deterioration amount and the adjusted risk index are equal to or below prescribed values.SELECTED DRAWING: Figure 10

Description

[Technical field]

[0001] The present invention relates to a work assistance system that assists in the work of an electric working machine. [Background technology]

[0002] Toward the realization of a carbon-free society, the electrification of work machines such as hydraulic excavators is accelerating. When planning work using an electric work machine, it is necessary to appropriately allocate work while taking into consideration the battery state, such as the battery charging rate and battery deterioration. Patent Document 1 discloses an operation plan creation device that creates an operation plan for multiple mobile objects having batteries. In order to suppress the variation in the degree of deterioration of the mobile objects, the operation plan creation device described in Patent Document 1 assigns to each mobile object a route on which the mobile object will operate during the planning period, using the number of times the mobile object is charged within a certain period prior to the planning period, which is the period for which the operation plan is created, and creates an operation plan using the assignment result. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2022-156628 A Summary of the Invention [Problem to be solved by the invention]

[0004] The degree of deterioration of the battery mounted on the electric work machine varies depending on the work performed by the electric work machine. The degree of deterioration of the battery also varies depending on the working time of the electric work machine. For this reason, the work plan needs to be created taking into consideration the work content and working time. Furthermore, when creating a work plan, it is necessary to estimate whether the electric work machine can complete the work without stopping due to a battery abnormality such as running out of power, and to allocate many tasks to electric work machines with a low risk of stopping. However, if the accuracy of the estimation of the risk of stopping is low, there is a risk that it is not possible to create a work plan that allows appropriate allocation of tasks. The technology described in Patent Document 1 has room for improvement in terms of the accuracy of the estimation of the risk of the electric work machine stopping.

[0005] An object of the present invention is to provide a work support system that creates a work plan that can appropriately support the work of an electric work machine while preventing the electric work machine from stopping due to a battery abnormality such as running out of power. [Means for solving the problem]

[0006] A work assistance system according to one aspect of the present invention includes a control device that acquires battery status information representing the state of a battery of an electric work machine and work content information representing the content of work, and calculates a work plan for the electric work machine based on the battery status information and the work content information. The control device calculates a predicted value of a battery state parameter including at least one of the voltage, charging rate, and temperature of the battery when the electric work machine operates in accordance with the work plan, a predicted work time, and a predicted amount of deterioration of the battery, calculates a risk index indicating the risk of the electric work machine stopping based on the predicted value of the battery state parameter, calculates a corrected risk index by correcting the risk index based on at least one of an estimation error index indicating an error in an estimation result of the operation of the electric work machine according to the work plan and a load variation index indicating a fluctuation range of the load on the battery during the work according to the work plan, determines whether a value of an objective function including the predicted work time, the predicted amount of deterioration, and the corrected risk index is less than or equal to a predetermined value, and if the value of the objective function is greater than the predetermined value, recalculates the work plan, and outputs the work plan if the value of the objective function is less than or equal to the predetermined value. Effect of the Invention

[0007] According to the present invention, it is possible to provide a work support system that creates a work plan that can appropriately support the work of an electric work machine while preventing the electric work machine from stopping due to a battery abnormality such as running out of power. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a system configuration diagram of a work support system according to a first embodiment. [Diagram 2] FIG. 2 is a system configuration diagram of a vehicle body control system 50 of the vehicle 1. As shown in FIG. [Diagram 3] FIG. 3 is a functional block diagram of the server 100 according to the first embodiment, showing the functions for creating a work plan. [Figure 4] FIG. 4 is a diagram showing the details of the function of the optimization calculation unit 101. [Diagram 5] FIG. 5 is a diagram showing battery state information of each vehicle 1. As shown in FIG. [Figure 6] FIG. 6 is a diagram showing basic plan information. [Figure 7] FIG. 7 is a diagram showing an example of information (data) for each vehicle 1 stored in the vehicle information storage unit 102. As shown in FIG. [Figure 8] FIG. 8 is a diagram showing an example of information (data) for each task stored in the task information storage unit 103. As shown in FIG. [Figure 9] FIG. 9 is a diagram showing an example of information (data) for each work location stored in the environmental information storage unit 104. As shown in FIG. [Figure 10] FIG. 10 is a flowchart showing an example of the flow of optimization calculation processing executed by the server 100. [Figure 11] FIG. 11 is a diagram showing a battery model. [Figure 12] FIG. 12 is a diagram showing the calculation results of the voltage transition, the charging rate transition, and the temperature transition of an operation plan created for a certain vehicle 1. In FIG. [Figure 13] FIG. 13 is a diagram showing the predicted work time, predicted deterioration rate, and risk index of each vehicle 1 in work plan plan 1 and work plan plan 2, and the values ​​of the objective functions of work plan plan 1 and work plan plan 2. [Figure 14] FIG. 14 is a functional block diagram of the server 200 according to the second embodiment, showing the function for creating a work plan. [Figure 15] FIG. 15 is a diagram illustrating an example of time-series data of battery state parameters. [Figure 16] FIG. 16 is a diagram illustrating an example of the work performance information. [Figure 17] FIG. 17 is a diagram showing the time variations of the battery state parameters (voltage and temperature). [Figure 18] FIG. 18 is a diagram illustrating an example of the work plan information. [Figure 19] FIG. 19 is a diagram showing an example of battery state information stored in the vehicle information storage unit 102 according to the third embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. The following description shows a specific example of the contents of the present invention, and the present invention is not limited to these descriptions. Various changes and modifications of the present invention are possible by those skilled in the art within the scope of the technical ideas disclosed in this specification. Furthermore, in all the drawings for explaining the present invention, parts having the same functions are given the same reference numerals, and repeated explanations thereof may be omitted.

[0010] First Embodiment A work support system according to a first embodiment of the present invention will be described with reference to Figs. 1 to 13. The work support system creates a schedule (hereinafter also referred to as a work plan) for work to be performed by a plurality of electric working machines 1, and supports the work of the plurality of electric working machines 1. Fig. 1 is a system configuration diagram of the work support system according to the first embodiment. Below, the configuration and functions of the work support system will be described in detail, taking as an example a case in which there are three electric working machines (hereinafter also referred to as vehicles) 1 as shown in Fig. 1.

[0011] As shown in Fig. 1, the work support system includes a server 100 that collects battery status information (vehicle information) from vehicle A (1A), vehicle B (1B), and vehicle C (1C) and creates a work plan based on the collected battery status information, and a terminal device 4 that displays the work plan created by the server 100 on a display screen. The terminal device 4 includes an input device 4a operated by a work manager 3, and a display device 4b that presents various information to the work manager 3. The work manager 3 manages multiple vehicles 1 using the work support system. The terminal device 4 is configured by, for example, a personal computer, a tablet terminal, or the like.

[0012] The vehicle 1 is a hydraulic excavator that operates on battery power. The vehicle 1 includes a vehicle body 51 and an articulated working device 52 attached to the vehicle body 51. The vehicle body 51 includes a running body 51a and a rotating body 51b attached to the running body 51a so as to be rotatable. The running body 51a has a travel motor that is a hydraulic motor, and the running body 51a is driven by the travel motor to drive the vehicle 1. The rotating body 51b is driven by a swing motor that is a hydraulic motor, and rotates relative to the running body 51a. The working device 52 includes a boom, an arm, and a bucket. The working device 52 is driven by a boom cylinder, an arm cylinder, and a bucket cylinder that are hydraulic cylinders, and performs excavation work and the like.

[0013] A hydraulic pump that discharges hydraulic oil, an electric motor 54 (see FIG. 2) that drives the hydraulic pump, and a control valve that controls the direction and flow rate of the hydraulic oil supplied from the hydraulic pump to hydraulic actuators such as hydraulic cylinders and hydraulic motors are mounted on the vehicle body 51. The direction and flow rate of the hydraulic oil discharged from the hydraulic pump are controlled by the control valve, thereby controlling the operations of the boom cylinder, arm cylinder, bucket cylinder, swing motor, and left and right traveling motors.

[0014] The vehicle body control system 50 of the vehicle 1 will be described with reference to Fig. 2. Fig. 2 is a system configuration diagram of the vehicle body control system 50 of the vehicle 1. As shown in Fig. 2, the vehicle 1 includes an electric motor 54 that drives a hydraulic pump, a battery pack (hereinafter also simply referred to as a battery) 60 that supplies power to the electric motor 54, and the vehicle body control system 50 that controls devices such as the electric motor 54.

[0015] The battery pack (battery) 60 includes a plurality of battery modules 61 connected in series. The plurality of battery modules 61 may be connected in parallel, or may be connected in series and parallel. Each battery module 61 is composed of a plurality of secondary battery cells (hereinafter simply referred to as battery cells) 62. The plurality of battery cells 62 constituting the battery module 61 are connected in series. Each battery cell 62 is, for example, a lithium ion battery. That is, the battery pack (battery) 60 is an electricity storage device having a plurality of battery cells 62.

[0016] The vehicle body control system 50 includes a BMU (Battery Management Unit) 57, a VCU (Vehicle Control Unit) 55, an ammeter 56, a charging unit 58, and an inverter 59.

[0017] The ammeter 56 is, for example, connected in series to the multiple battery modules 61 connected in series, and detects the current value I of the current flowing through each battery cell 62. When the multiple battery modules 61 are connected in parallel, one ammeter 56 is provided for each of the multiple battery modules 61, and detects the current value I of the current flowing through the battery cells 62 that constitute each battery module 61. The ammeter 56 outputs a signal indicating the detection result to the BMU 57.

[0018] The BMU 57 manages and controls the battery 60. The BMU 57 is connected to each battery module 61 via a signal line. The BMU 57 includes a processing device such as a CPU, and a storage device. The BMU 57 monitors the state of the battery cells 62 that make up each battery module 61. The BMU 57 detects the voltage value and temperature of the battery cells 62 and stores them in the storage device. The BMU 57 stores time-series data (data log for each time) of battery state information that indicates the state of the battery 60, which is the driving source of the vehicle 1.

[0019] The battery state information includes, for example, the voltage value of the battery 60 (including the average cell voltage value, the voltage value of the battery pack 60, etc.), the current value, the temperature, SOC: State of Charge (charging rate), and SOH: State of Health (deterioration rate). The deterioration rate SOH includes SOHQ: State of Health of Q (capacity deterioration rate) and SOHR: State of Health of Resistance (resistance deterioration rate). The resistance deterioration rate SOHR is the rate of increase in the battery internal resistance that increases with deterioration of the battery pack 60, and is calculated by the BMU 57. The capacity deterioration rate SOHQ is the rate of decrease in the full charge capacity that decreases with deterioration of the battery pack 60, and is calculated by the BMU 57.

[0020] The charging unit 58 is connected to a charger (not shown) installed outside the vehicle 1. The charging unit 58 supplies power from the charger to the battery 60 to charge the battery 60. The inverter 59 converts the DC power supplied from the battery 60 into AC power and supplies it to the electric motor 54. The electric motor 54 is driven by the power supplied from the battery 60, and drives a hydraulic pump to generate power for the vehicle 1.

[0021] The VCU 55 manages and controls the entire vehicle 1. The VCU 55 is connected to the BMU 57, the charging unit 58, the inverter 59, and the communication device 70 via signal lines. The VCU 55 acquires battery state information (temperature, voltage value, current value, charging rate SOC, and deterioration rate SOH of the battery 60) from the BMU 57. The VCU 55 controls the charging unit 58 and the inverter 59 based on the battery state information. The VCU 55 communicates with the server 100 using the communication device 70.

[0022] The server 100 shown in Fig. 1 is installed at a location away from the work site where the vehicle 1 is performing work. The server 100 is installed, for example, in a management facility that manages multiple vehicles 1. The server 100 is connected to a communication device 15. The terminal device 4 is possessed by a work manager 3. The communication device 70 (see Fig. 2) installed in the vehicle 1, the communication device 15 installed in the management facility, and a communication device (not shown) mounted on the terminal device 4 each have a communication interface that enables two-way communication via a communication line NT of a wide area network.

[0023] The server 100 outputs the created work plan to the communication device 15. The communication device 15 functions as an output device that outputs the work plan created by the server 100 to the terminal device 4 via the communication line NT. The display device 4b is a liquid crystal display device, an organic EL display device, or the like. The display device 4b functions as an output device that outputs the work plan created by the server 100 as an image. The input device 4a is a keyboard or a touch sensor provided on the display screen of the display device 4b, or the like. The work manager 3 operates the input device 4a to input information required for creating a work plan to the terminal device 4.

[0024] The server 100 is composed of a computer equipped with a processing device 11, a storage device 12, an input / output interface 13, and other peripheral circuits. These pieces of hardware work together to operate software and realize multiple functions. The controller may be composed of one computer or multiple computers. The processing device 11 is composed of a CPU (Central Processing Unit), an MPU (Micro Processing Unit), a DSP (Digital Signal Processor), etc. The storage device 12 is composed of non-volatile memories such as ROM (Read Only Memory), flash memory, and hard disk drives, and volatile memories called RAM (Random Access Memory).

[0025] The non-volatile memory constituting the storage device 12 stores programs capable of executing various calculations. In other words, the storage device 12 is a storage medium capable of reading programs that realize the functions of this embodiment. The volatile memory constituting the storage device 12 temporarily stores the results of calculations performed by the processing device 11 and signals input from the input / output interface 13. The processing device 11 is a device that loads the programs stored in the non-volatile memory into the volatile memory and executes calculations, and performs predetermined calculations on data taken in from the input / output interface 13 and the storage device 12 in accordance with the programs.

[0026] The input / output interface 13 converts a signal input from the communication device 15 into data that can be calculated by the processing device 11. The input / output interface 13 also generates an output signal according to the calculation result in the processing device 11, and outputs the signal to the communication device 15.

[0027] Fig. 3 is a functional block diagram of the server 100, showing functions for creating a work plan. As shown in Fig. 3, the server 100 functions as a vehicle information storage unit 102, a work information storage unit 103, an environmental information storage unit 104, an outside air temperature collation unit 105, and an optimization calculation unit 101. Fig. 4 is a diagram showing the details of the functions of the optimization calculation unit 101.

[0028] The vehicle 1 transmits the battery state information together with the identification information of the vehicle itself to the server 100. The server 100 acquires the battery state information from each vehicle 1 and stores it.

[0029] Fig. 5 is a diagram showing battery state information of each vehicle 1. As shown in Fig. 5, the battery state information includes the current charging rate SOC of the battery 60, the current capacity deterioration rate SOHQ of the battery 60, and the current resistance deterioration rate SOHR of the battery 60.

[0030] 1, the work manager 3 inputs information required for creating a work plan (hereinafter also referred to as plan basic information) using application software installed in a terminal device 4. In response to an operation by the work manager 3, the terminal device 4 transmits the plan basic information to the server 100. The server 100 acquires and stores the plan basic information.

[0031] FIG. 6 is a diagram showing the plan basic information. As shown in FIG. 6, the plan basic information includes identification information (work vehicle information) of the vehicle 1 to be incorporated into the work plan, work content information indicating the content of the work that can be performed by the vehicle 1, information on the work location (work site), and information on the available work time. The work content information includes the type of work and the work time required to complete the work. The type of work is, for example, excavation work (hereinafter referred to as work 1), ground leveling work (hereinafter referred to as work 2), and earthworking work (hereinafter referred to as work 3). Note that, in the example shown in FIG. 6, an example is shown in which the work contents (work 1 to work 3) of each vehicle 1 are the same, but the work content information of each vehicle 1 may be different. The work content information is information that indicates candidates for work to be assigned to the vehicle 1 in the work plan. In this embodiment, work 1 to work 3 are listed as candidates for work to be assigned to each vehicle 1. Note that, in the case where the vehicle 1 is a vehicle type that allows work while charging, various work while charging may be included as the type of work. In addition, in the example shown in FIG. 6, the available work time of each vehicle 1 is the same, but the available work time of each vehicle 1 may be different.

[0032] FIG. 7 is a diagram showing an example of information (data) for each vehicle 1 stored in the vehicle information storage unit 102. As shown in FIG. 7, the vehicle information storage unit 102 stores a battery model data group corresponding to each vehicle 1, an estimated error index, and the above-mentioned battery state information. The battery state information, the battery model data group, and the estimated error index are stored in the vehicle information storage unit 102 in a state associated with the identification information of the vehicle 1. The battery model data group is a data group required for estimating the battery operation using a battery model described later. The battery model data group is composed of parameters extracted at the time of manufacture, and is stored in the vehicle information storage unit 102 at the time of manufacture. As described above, the battery state information includes the charging rate SOC, the capacity deterioration rate SOHQ, and the resistance deterioration rate SOHR (see FIG. 5). The battery state information stored in the vehicle information storage unit 102 is updated as appropriate by data transmitted from each vehicle 1.

[0033] The estimation error index is an index that represents an error in an estimation result of the operation of the vehicle 1 according to the work plan. The estimation error index is determined for each vehicle 1 at the time of manufacture and is stored in the vehicle information storage unit 102 at the time of manufacture. The battery model data group and the estimation error index may be determined for each vehicle model, or may be determined as a value unique to each vehicle 1 even if the vehicle is of the same vehicle model.

[0034] Fig. 8 is a diagram showing an example of information (data) for each task stored in the work information storage unit 103. As shown in Fig. 8, the work information storage unit 103 stores an average load, a maximum load, and a load fluctuation index of the battery 60 corresponding to each task. The average load, the maximum load, and the load fluctuation index of the battery 60 are stored in the work information storage unit 103 in association with the identification information of the task. The average load and the maximum load as the load information of the battery 60 are determined in advance by experiments or the like, and are stored in the work information storage unit 103 at the time of manufacture.

[0035] The load variation index is an index that represents the fluctuation range of the load on the battery 60 during work according to a work plan. When a specified work is performed, even if the work is the same, the magnitude of the load on the battery 60 varies (fluctuations) depending on the worker and the environment. Environmental factors that affect the load fluctuations, that is, environmental factors that affect the running of the vehicle 1 and the work, include, for example, soil quality, road surface condition, weather, and work site condition. The load variation index is determined in advance based on experimental data and the like, taking into account the maximum value of the fluctuation range of the load magnitude, and is stored in the work information storage unit 103 during manufacture.

[0036] The method for calculating the load fluctuation index for task 1 is, for example, as follows. Task 1 is performed under multiple conditions with different workers and environments, and the load is measured. The average value of the measured load (hereinafter referred to as the representative measurement value) is calculated for each of the multiple conditions. The load fluctuation index (load fluctuation rate) for task 1 is calculated by dividing the fluctuation range of the representative measurement value for each of the multiple conditions (maximum value - minimum value of the representative measurement values ​​for each condition) by the average value of the representative measurement values ​​obtained for each of the multiple conditions. In this way, the load fluctuation index is the fluctuation range of the measured load expressed as a ratio [%].

[0037] 1, the work manager 3 inputs environmental information using application software installed in the terminal device 4. The terminal device 4 transmits the environmental information to the server 100 in response to an operation by the work manager 3. The server 100 acquires the environmental information and stores the acquired environmental information in the environmental information storage unit 104 (see FIG. 3).

[0038] FIG. 9 is a diagram showing an example of information (data) for each work location stored in the environmental information storage unit 104. As shown in FIG. 9, the environmental information storage unit 104 stores environmental information corresponding to each work location. The environmental information includes charger information and location information. The charger information includes the distance from the charger to the work site, the number of chargers, and the output of the charger. The location information is information for identifying the work location, such as longitude and latitude. The location information is used when referring to weather data at each work location, which will be described later. The charger information and location information are stored in the environmental information storage unit 104 in a state associated with the identification information of the work location.

[0039] 3, the outside temperature checking unit 105 acquires location information corresponding to the information of the work location input from the input device 4a from the environmental information storage unit 104. The outside temperature checking unit 105 checks the outside temperature based on the acquired location information. For example, a method of checking the outside temperature is adopted in which weather forecast data is referred to on the Internet.

[0040] 4, the optimization calculation unit 101 has a plan proposal calculation unit 106, a deterioration amount calculation unit 107, a risk index calculation unit 108, and a work plan evaluation unit 109. The plan proposal calculation unit 106 calculates a work plan based on information (battery state information, etc.) stored in the vehicle information storage unit 102, the work information storage unit 103, and the environmental information storage unit 104, and information (work content information, etc.) input from the input device 4a. The work plan is created by combining the temporal arrangements of multiple types of operation items.

[0041] The operation items of the work plan include work, movement, charging, and rest. The working state refers to a state in which the vehicle 1 is in a key-on state, i.e., the vehicle 1 is started, and the working device 52, the revolving body 51b, and the like are operating. The working state may also include a state in which the working device 52, the revolving body 51b, and the like are stopped, and only accessories such as an air conditioner are operating. The moving state refers to a state in which the running body 51a is operating and the vehicle 1 is moving. The charging state refers to a state in which power is supplied from a charger to the battery 60 of the vehicle 1, and the battery 60 is charged. The resting state refers to a state in which the vehicle 1 is in a key-off state and the vehicle 1 is stopped (a state in which the working device 52, the revolving body 51b, and the running body 51a are stopped). In other words, in the resting state, neither charging of the battery 60 by the charger nor discharging of the battery 60 for supplying power to drive targets such as the electric motor 54 and accessories is performed. That is, the resting state corresponds to a state in which the battery 60 is only undergoing natural discharge.

[0042] The work plan calculated by the proposed plan calculation unit 106 is transmitted to the terminal device 4 if it is evaluated as appropriate by the work plan evaluation unit 109 described below, but is not transmitted if it is evaluated as inappropriate. For this reason, the work plan calculated by the proposed plan calculation unit 106 and before it is evaluated as appropriate by the work plan evaluation unit 109 will be referred to as a proposed work plan hereinafter.

[0043] The plan calculation unit 106 calculates predicted values ​​of battery state parameters of the battery 60 when the vehicle 1 operates according to the work plan proposal, and a predicted work time of the vehicle 1 when the vehicle 1 operates according to the work plan. The battery state parameters in this embodiment include the voltage value, charging rate SOC, and temperature of the battery 60.

[0044] Furthermore, the plan calculation unit 106 calculates a predicted representative value of the battery state when the vehicle 1 operates according to the proposed work plan. The predicted representative value of the battery state includes, as first representative values, the temperature of the battery 60 at rest, the charging rate SOC of the battery 60 at rest, the average temperature of the battery 60 during work, the daily discharge amount of the battery 60, the average discharge power of the battery 60, and the average charge power of the battery 60. The predicted representative value of the battery state includes, as second representative values, the minimum predicted value of the voltage of the battery 60, the minimum predicted value of the charging rate SOC, and the maximum predicted value of the temperature of the battery 60.

[0045] The deterioration amount calculation unit 107 calculates a predicted deterioration amount ΔSOHQ of the battery 60 when the vehicle 1 operates according to the proposed work plan. The predicted deterioration amount ΔSOHQ corresponds to the difference between the current capacity deterioration rate and the capacity deterioration rate after operation according to the proposed work plan. The deterioration amount calculation unit 107 calculates the predicted deterioration amount ΔSOHQ, which is a change in the capacity deterioration rate of the battery 60, based on the battery state information and battery model data group stored in the vehicle information storage unit 102, and the first representative value of the battery state calculated by the proposed plan calculation unit 106.

[0046] The risk index calculation unit 108 calculates a risk index based on the second representative value of the battery state calculated by the plan calculation unit 106 and the estimation error index and the load fluctuation index stored in the work information storage unit 103.

[0047] The work plan evaluation unit 109 evaluates whether the proposed work plan calculated by the plan calculation unit 106 is appropriate or not based on the predicted work time calculated by the plan calculation unit 106, the predicted deterioration amount ΔSOHQ of the battery 60 calculated by the deterioration amount calculation unit 107, and the risk index calculated by the risk index calculation unit 108. If the proposed work plan is evaluated to be inappropriate, the proposed work plan is calculated by the plan calculation unit 106. If the proposed work plan is evaluated to be appropriate, the proposed work plan is confirmed as a work plan for output and output to the terminal device 4. In other words, the optimization calculation unit 101 repeatedly calculates the proposed work plan until the proposed work plan is evaluated to be appropriate, and outputs the work plan evaluated to be appropriate. The new proposed work plan is created by changing the temporal arrangement of the operation items (work, movement, charging, rest) for the proposed evaluated work plan.

[0048] An example of the flow of the optimization calculation process by the optimization calculation unit 101 will be described with reference to the flowchart in Fig. 10. Fig. 10 is a flowchart showing an example of the flow of the optimization calculation process executed by the server 100. In this embodiment, a work plan is created so that the value of an objective function, which will be described later, is minimized. The optimization calculation is started when an execution operation of the optimization calculation is performed by the input device 4a of the terminal device 4.

[0049] In step S100, the optimization calculation unit 101 acquires information necessary for the optimization calculation (battery model data group, battery state information, load information, charger information, outside temperature information, work vehicle information, work content information, available work time, estimated error index, and load fluctuation index) from the vehicle information storage unit 102, the work information storage unit 103, the environmental information storage unit 104, the outside air temperature comparison unit 105, and the input device 4a. When acquisition of the information necessary for the optimization calculation is completed, the optimization calculation unit 101 advances the process to step S110.

[0050] In step S110, the plan calculation unit 106 of the optimization calculation unit 101 calculates an operation plan that satisfies the constraint conditions. The operation plan is created using a battery model that predicts the voltage value and temperature of the battery 60.

[0051] FIG. 11 is a diagram showing a battery model. As shown in FIG. 11, the battery model is an equivalent circuit model that estimates a voltage value of the battery 60 when the vehicle 1 operates according to the proposed work plan. The battery model is expressed by an OCV (Open Circuit Voltage) component that is the electromotive force of the battery 60, a DC resistance component R0 that is the ohmic resistance of the components that constitute the battery 60, and a polarization term Vp component that is resistance due to ion diffusion and electronic conduction in a solid. The polarization term Vp is expressed by a polarization resistance Rp and a capacitor with a time constant τp. According to the equivalent circuit model, a closed circuit voltage CCV is calculated by the following formula (1). In addition, the polarization term Vp is calculated by the following formula (2), and the charging rate SOC is calculated by the following formula (3).

[0052]

number

[0053] Here, I is the current value of the battery 60, SOHR is the resistance deterioration rate of the battery 60, and T battery is the temperature of the battery 60.

[0054]

number

[0055] Here, t is time, and Vp_z is the previous value of the polarization term, i.e., the polarization term Vp calculated in the previous calculation cycle.

[0056]

number

[0057] Here, SOCz is the previous SOC value, i.e., the SOC calculated in the previous calculation cycle. BattCap. is the fully charged capacity of the battery 60 when it is new (at the reference time), and SOHQ is the capacity deterioration rate of the battery 60. Δt is the amount of change over time, i.e., the calculation cycle.

[0058] The initial value of the polarization term Vp is 0 (zero), and the initial value of the SOC is the current SOC obtained from each vehicle 1. The OCV is a value that changes depending on the SOC. The vehicle information storage unit 102 stores a data table or a relational expression as OCV characteristic information that defines the relationship between the SOC and the OCV. The plan calculation unit 106 refers to the OCV characteristic information and calculates the OCV based on the SOC. R0 and Rp are the ratios of the SOC and the temperature T battery The vehicle information storage unit 102 stores the SOC and temperature T battery The vehicle information storage unit 102 stores a data table or a relational expression as R0 characteristic information that defines the relationship between the SOC and the temperature T battery A data table or a relational expression is stored as Rp characteristic information that defines the relationship between the SOC and the polarization resistance Rp. The plan calculation unit 106 refers to the R0 characteristic information and calculates the SOC and the temperature T battery The plan calculation unit 106 calculates the DC resistance component R0 based on the Rp characteristic information and calculates the SOC and temperature T battery The polarization resistance Rp is calculated based on this.

[0059] The plan calculation unit 106 calculates the battery model data group (OCV characteristic information, R0 characteristic information, Rp characteristic information, and time constant τp on the equivalent circuit model), the SOC, SOHR, and SOHQ updated based on the battery state information acquired from each vehicle 1, and the temperature T battery Based on this, the time transition of the voltage (CCV) corresponding to the proposed work plan is calculated.

[0060] The temperature model used to calculate the time transition of the temperature of the battery 60 corresponding to the proposed work plan is expressed by, for example, the following equations (4), (5), (6), and (7). battery is calculated by the formula (4), and the total heat generation amount Q total is calculated by equation (5).

[0061]

number

[0062]

number

[0063] Here, Q transfer is the amount of heat loss due to heat transfer to the outside air, and is calculated using equation (6).

[0064]

number

[0065] where S is the surface area of ​​the battery 60 exposed to the outside air, and T battery is the temperature of the battery 60, and T amb is the outside air temperature, and α is the heat transfer coefficient to the outside air. The temperature rise ΔT of the battery 60 is calculated by equation (7).

[0066]

number

[0067] Here, C is the heat capacity of the battery 60. The surface area S, the heat transfer coefficient α, and the heat capacity C are stored in advance in the vehicle information storage unit 102 as information included in the battery model data group. amb is calculated by the outside air temperature collation unit 105. The plan calculation unit 106 couples the above-mentioned voltage model and temperature model, and calculates the temperature transition and voltage transition when a certain action item (for example, task 1) is input.

[0068] The plan calculation unit 106 calculates the predicted value of CCV at each time obtained by equation (1) as a voltage transition. The plan calculation unit 106 calculates the predicted value of SOC at each time obtained by equation (3) as a charging rate transition. The plan calculation unit 106 calculates the predicted value of the temperature of the battery 60 at each time as a temperature transition based on the temperature rise ΔT obtained by equation (7) and the initial value of the temperature of the battery 60.

[0069] FIG. 12 is a diagram showing the calculation results of the voltage transition, the charging rate transition, and the temperature transition of a proposed work plan created for a certain vehicle 1. The horizontal axis indicates the elapsed time t from the start time of work according to the proposed work plan. (a) shows the chronological arrangement of the action items of the proposed work plan, (b) shows the voltage transition, (c) shows the charging rate transition, and (d) shows the temperature transition. Note that FIG. 12 shows the voltage value, charging rate, and temperature transition of the proposed work plan for one vehicle 1, but the voltage value, charging rate, and temperature transition according to the proposed work plan for other vehicles 1 are also calculated in the same way.

[0070] The plan proposal calculation unit 106 judges whether the calculated work plan proposal satisfies the constraint conditions. The constraint conditions according to this embodiment include, for example, the following (Condition 1) to (Condition 7). If all of the following (Condition 1) to (Condition 7) are satisfied, the plan proposal calculation unit 106 judges that the work plan proposal satisfies the constraint conditions, and if at least one of (Condition 1) to (Condition 7) is not satisfied, the plan proposal calculation unit 106 judges that the work plan proposal does not satisfy the constraint conditions. (Condition 1) The work time defined in the work plan (see Figure 6) is ensured. (Condition 2) The work defined in the proposed work plan is completed within the available work time (see Figure 6). (Condition 3) Travel time is ensured taking into account the distance from the work site to the location where the charger is installed (see Figure 9). (Condition 4) The number of vehicles being charged simultaneously is less than or equal to the number of chargers (see FIG. 9). (Condition 5) The minimum voltage value Vmin is equal to or greater than the lower limit voltage (see FIG. 12). (Condition 6) The minimum state of charge SOCmin is equal to or greater than the lower limit state of charge (see FIG. 12). (Condition 7) The maximum battery temperature Tmax is equal to or lower than the upper limit temperature (see FIG. 12).

[0071] If the plan proposal calculation unit 106 determines that the calculated work plan proposal satisfies the constraint conditions, the plan proposal calculation unit 106 advances the process to step S120 in FIG.

[0072] In step S120, the deterioration amount calculation unit 107 of the optimization calculation unit 101 calculates a predicted deterioration amount ΔSOHQ of the battery 60 based on the calculation result of the plan calculation unit 106. The battery deterioration prediction equation used to predict battery deterioration is expressed by, for example, equations (8), (9), and (10). The battery deterioration prediction equation can be divided into storage deterioration, which is deterioration when the battery 60 is not being charged or discharged, and cycle deterioration, which is deterioration when the battery 60 is being charged or discharged. The storage deterioration rate a st is calculated by the formula (8). The cycle deterioration rate a cyc is calculated by equation (9).

[0073]

number

[0074]

number

[0075] In the formulas (8) and (9), a0 to a8 are constants according to the specifications of the battery 60 and are stored in advance in the vehicle information storage unit 102. The constants a0 to a8 are determined in advance by evaluating the battery 60 through experiments or the like. st is the temperature of the battery 60 at rest. SOC st is the charging rate SOC of the battery 60 at rest. op is the average temperature of the battery 60 during operation (charging and discharging). DisAh is the daily discharge amount of the battery 60, DisPave is the average discharge power of the battery 60, and ChgPave is the average charge power of the battery 60. T st ,SOC st ,T op , DisAh, DisPave, and ChgPave are predicted representative values ​​(first representative values) of the battery state calculated by the plan calculation unit 106.

[0076] The deterioration amount calculation unit 107 calculates the storage deterioration rate a stand the cycle deterioration rate a calculated using equation (9) cyc Using equation (10), a predicted deterioration amount ΔSOHQ is calculated, which indicates how much the capacity deterioration rate will progress from the start point (present) of the work according to the work plan to the end point of the work. The predicted deterioration amount ΔSOHQ can also be said to be the change in the capacity deterioration rate from the start point to the end point of the work according to the work plan.

[0077]

number

[0078] day_z is the number of days that have elapsed since the manufacturing date (base date) to the present, and day is the number of days that have elapsed since the manufacturing date (base date) to after the operation.

[0079] The battery deterioration equations (8) to (10) are used to calculate the predicted deterioration amount ΔSOHQ when the vehicle 1 operates according to the proposed work plan, thereby quantifying the impact on the deterioration of the battery 60. When the predicted deterioration amount ΔSOHQ is calculated by the deterioration amount calculation unit 107, the process proceeds to step S130.

[0080] In step S130, the risk index calculation unit 108 of the optimization calculation unit 101 calculates a risk index Bop based on the calculation result of the plan proposal calculation unit 106. The risk index Bop is an index that indicates the risk of the vehicle 1 stopping due to an abnormality in the battery 60. The risk index Bop is an index that quantifies the probability that the vehicle 1 can complete a task when performing the task, and can therefore also be expressed as the uncertainty of task completion. The risk index Bop is calculated by the following formula (11). The larger the risk index Bop, the higher the risk of stopping, i.e., the higher the probability that the task cannot be completed.

[0081]

number

[0082] Here, b0 to b4 are constants for weighting each term, and are set in advance.

[0083] V limit is the lower limit of the voltage of the battery 60 (hereinafter, also referred to as the lower limit voltage). limit is determined in advance for each vehicle 1 and stored in the vehicle information storage unit 102. min is the minimum predicted value of the voltage of the battery 60 when the vehicle 1 operates according to the proposed work plan (hereinafter, also referred to as the predicted minimum voltage). min is calculated by the plan calculation unit 106 as one of the predicted representative values ​​(second representative value) of the battery state. The first term on the right side of the formula (11) is an index (hereinafter also referred to as a voltage abnormality index) that indicates the risk of the vehicle 1 stopping due to an abnormal drop in the voltage of the battery 60. The voltage abnormality index is a function of the predicted minimum voltage V min and the lower limit voltage V limit Difference with (V min -V limit The voltage anomaly index is calculated based on the predicted minimum voltage V min is the lower limit voltage of battery 60 V limit The closer it gets, the larger it becomes.

[0084] SOC limit is the lower limit of the charging rate of the battery 60 (hereinafter, also referred to as the lower limit charging rate). limit is determined in advance for each vehicle 1 and stored in the vehicle information storage unit 102. min is the minimum predicted value of the state of charge of the battery 60 when the vehicle 1 operates according to the proposed work plan (hereinafter, also referred to as the predicted minimum state of charge). min is calculated by the plan calculation unit 106 as one of the predicted representative values ​​(second representative value) of the battery state. The second term on the right side of the formula (11) is an index (hereinafter also referred to as the charging rate abnormality index) that indicates the risk of the vehicle 1 stopping due to an abnormal drop in the charging rate of the battery 60. The charging rate abnormality index is the predicted minimum charging rate SOC min and the lower limit of SOC limit The charge rate anomaly index is calculated based on the difference between the predicted minimum charge rate SOC and the min The lower limit of the battery charge rate SOC of 60 limit The closer it gets, the larger it becomes.

[0085] T limit is the upper limit of the temperature of the battery 60 (hereinafter, also referred to as the upper limit temperature). limit is determined in advance for each vehicle 1 and stored in the vehicle information storage unit 102. max is the maximum predicted value of the temperature of the battery 60 when the vehicle 1 operates according to the proposed work plan (hereinafter, also referred to as the predicted maximum temperature). max is calculated by the plan calculation unit 106 as one of the predicted representative values ​​(second representative value) of the battery state. The third term on the right side of the formula (11) is an index (hereinafter also referred to as the temperature abnormality index) that indicates the risk of the vehicle 1 stopping due to an abnormal rise in the temperature of the battery 60. The temperature abnormality index is calculated based on the difference between the predicted maximum temperature and the upper limit temperature. The temperature abnormality index is calculated based on the predicted maximum temperature T max The upper limit temperature T limit The closer it gets, the larger it becomes.

[0086] The sum of the voltage abnormality index, the charging rate abnormality index, and the temperature abnormality index is a risk index that indicates the risk of the vehicle 1 stopping due to abnormalities in the voltage, charging rate, and temperature of the battery 60, and is hereinafter also referred to as risk index Bop0.

[0087] Here, an error occurs in the operation estimation using the battery model. For example, even if the predicted minimum charging rate of the battery 60 as a result of the operation estimation is higher than the lower limit charging rate of the battery 60, if the error of the operation estimation is large, the minimum charging rate may fall below the lower limit charging rate of the battery 60 during the actual operation of the vehicle 1. For this reason, if the error of the operation estimation is not taken into consideration, the voltage of the battery 60 may fall below the lower limit voltage, the charging rate of the battery 60 may fall below the lower limit charging rate, or the temperature of the battery 60 may exceed the upper limit temperature. Therefore, in this embodiment, the risk index is calculated by taking into account an estimation error index that indicates an error in the estimation result of the operation of the vehicle 1 according to the work plan. EstError in formula (11) is an estimation error index, and is stored in advance in the vehicle information storage unit 102. The fourth term on the right side of formula (11) is a correction term based on the estimation error index EstError, and increases in proportion to the estimation error index EstError. By taking the estimation error index EstError into consideration, it is possible to appropriately prevent the occurrence of a battery shortage during work.

[0088] Furthermore, if the load on the battery 60 during work varies due to differences in workers or environments, the voltage of the battery 60 may fall below a lower limit voltage during actual operation of the vehicle 1, resulting in a risk of battery running out. Therefore, in this embodiment, the risk index is calculated by further taking into account a load variation index that indicates the fluctuation range of the load on the battery during work according to the work plan. PError in formula (11) is a load variation index, which is stored in advance in the work information storage unit 103. The fifth term on the right side of formula (11) is a correction term based on the load variation index PError, and increases in proportion to the load variation index PError. By taking the load variation index PError into account, it is possible to appropriately prevent battery running out during work.

[0089] As described above, the risk index calculation unit 108 calculates the risk index Bop0 based on the predicted values ​​of the battery state parameters (predicted values ​​of the voltage, charging rate, and temperature of the battery 60), and calculates the corrected risk index Bop by correcting the risk index Bop0 based on the estimation error index and the load fluctuation index. When the risk index Bop is calculated by the risk index calculation unit 108, the process proceeds to step S140.

[0090] In step S140, the work plan evaluation unit 109 calculates the predicted work time Time calculated by the plan calculation unit 106 using the following formula (12): op The deterioration amount calculation unit 107 calculates the predicted deterioration amount ΔSOHQ calculated by the deterioration amount calculation unit 107, and the corrected risk index Bop calculated by the risk index calculation unit 108, and the objective function value Kop is calculated.

[0091]

number

[0092] Here, k0 to k2 are the predicted work times Time op , the predicted deterioration amount ΔSOHQ, and the corrected risk index Bop, and are set in advance. In other words, the value of the objective function Kop is op , the predicted deterioration amount ΔSOHQ, and the corrected risk index Bop are weighted and summed up.

[0093] When the objective function value Kop is calculated in step S140, the process proceeds to step S150. In step S150, the work plan evaluation unit 109 judges whether the objective function value Kop of the optimization is equal to or less than a predetermined threshold (predetermined value) Kth. If it is judged that the objective function value Kop is equal to or less than the threshold Kth, the work plan evaluation unit 109 confirms the proposed work plan created in step S110 as the work plan for output, and proceeds to step S160. If it is judged that the objective function value Kop is greater than the threshold Kth, the process returns to step S110. Thereby, a proposed work plan that satisfies the constraint conditions is searched for again.

[0094] In step S160, the work plan evaluation unit 109 outputs the work plan for output to the communication device 15. The communication device 15 outputs the work plan to the terminal device 4. The terminal device 4 displays the work plan on a display screen. When the output process of the work plan is completed in step S160, the flowchart in FIG. 10 ends.

[0095] A specific example of the flow up to outputting a work plan will be described with reference to Fig. 13. Fig. 13 is a diagram showing the predicted work time, predicted deterioration rate, and risk index of each vehicle 1 in work plan proposal 1 and work plan proposal 2, and the values ​​of the objective functions of work plan proposal 1 and work plan proposal 2. When work plan proposal 1 that satisfies the constraint conditions is calculated (step S110 in Fig. 10), the predicted deterioration amount ΔSOHQ, risk index Bop, and objective function value Kop when vehicle 1 operates according to work plan proposal 1 are calculated (steps S120, S130, S140 in Fig. 10).

[0096] The objective function value Kop is the predicted work time Time op The sum of the total (14 hours) of the predicted deterioration amounts ΔSOHQ of the batteries 60 of each vehicle 1 multiplied by a constant k0 (=20), the total (0.04%) of the predicted deterioration amounts ΔSOHQ of the batteries 60 of each vehicle 1 multiplied by a constant k1 (=1500), and the total (160) of the risk indexes Bop of each vehicle 1 multiplied by a constant k2 (=1). In the proposed work plan 1, the objective function value Kop is 500, which is greater than the threshold value Kth (=450). For this reason, the proposed work plan 1 is evaluated as inappropriate as a work plan (No in step S150 of FIG. 10).

[0097] Then, when a work plan 2 that satisfies the constraint conditions is calculated (step S110 in FIG. 10), the predicted deterioration amount ΔSOHQ, risk index Bop, and objective function value Kop when vehicle 1 operates according to that work plan 2 are calculated (steps S120, S130, S140 in FIG. 10).

[0098] The objective function value Kop is the predicted work time Time opThe sum of the total (15 hours) of the predicted deterioration amounts ΔSOHQ of the batteries 60 of the vehicles 1 multiplied by a constant k0 (=20), the total (0.035%) of the predicted deterioration amounts ΔSOHQ of the batteries 60 of the vehicles 1 multiplied by a constant k1 (=1500), and the total (90) of the risk indexes Bop of the vehicles 1 multiplied by a constant k2 (=1). In the work plan 2, the objective function value Kop is 442.5, which is equal to or smaller than the threshold value Kth (=450). Therefore, the work plan 2 is evaluated as being appropriate as a work plan (Yes in step S150 of FIG. 10). As a result, the work plan 2 is transmitted to the terminal device 4 as an appropriate work plan (step S160 of FIG. 10). In this way, in this embodiment, the risk index Bop corrected based on the estimation error index and the load fluctuation index is utilized in creating the work plan, so that a work plan that can prevent the vehicle 1 from stopping can be created.

[0099] In the example shown in FIG. 13, when only the predicted work time is considered, the work plan 1 is preferable because it is smaller. However, the predicted deterioration amount ΔSOHQ and the risk index Bop are smaller in the work plan 2. As a result, the objective function value Kop is smaller in the work plan 2 than in the work plan 1. In this way, in this embodiment, an appropriate work plan can be output by considering not only the predicted work time but also the progressing deterioration rate (predicted deterioration amount) and the uncertainty of the work completion (risk index). Therefore, it is possible to ensure the long-term reliability of the vehicle 1 and the short-term reliability of the work. The constants (weighting coefficients) k0 to k2 used in the optimization calculation can be input and changed using the input device 4a of the terminal device 4. Therefore, the weighting coefficients k0 to k2 change depending on whether the work manager 3 places emphasis on shortening the work time, on the progress of deterioration, or on the reliability of whether the work will be completed.

[0100] According to the above-described embodiment, the following advantageous effects are obtained.

[0101] (1) The work assistance system includes a server 100 as a control device that calculates a work plan for multiple vehicles (electric working machines) 1. The server 100 acquires battery state information that indicates the state of the battery 60 of the vehicle 1 and work content information that indicates the content of the work performed by the vehicle 1. The server 100 calculates a work plan for the vehicle 1 based on the battery state information and the work content information. The server 100 outputs the work plan to the terminal device 4 via the communication device 15.

[0102] The server 100 calculates predicted values ​​of battery state parameters including the voltage value, charging rate, and temperature of the battery 60 when the vehicle 1 operates according to the work plan. The server 100 calculates predicted work time Time op The server 100 calculates a predicted deterioration amount ΔSOHQ of the battery 60 when the vehicle 1 operates according to the work plan. The server 100 calculates a risk index Bop0 that indicates the risk that the vehicle 1 will stop due to an abnormality in the battery 60, based on the predicted values ​​of the battery state parameters.

[0103] The server 100 according to the present embodiment calculates a predicted value of the voltage of the battery 60, a predicted value of the charging rate of the battery 60, and a predicted value of the temperature of the battery 60. The server 100 calculates a voltage abnormality index (the first term on the right side of the formula (11)) representing the risk of the vehicle 1 stopping due to an abnormal drop in the voltage of the battery 60 based on the difference between the calculated predicted value of the voltage of the battery 60 and a predetermined lower limit voltage of the battery. The server 100 also calculates a charging rate abnormality index (the second term on the right side of the formula (11)) representing the risk of the vehicle 1 stopping due to an abnormal drop in the charging rate of the battery 60 based on the difference between the calculated predicted value of the charging rate of the battery 60 and a predetermined lower limit charging rate of the battery 60. The server 100 also calculates a temperature abnormality index (the third term on the right side of the formula (11)) representing the risk of the vehicle 1 stopping due to an abnormal rise in the temperature of the battery 60 based on the difference between the calculated predicted value of the temperature of the battery 60 and a predetermined upper limit temperature of the battery 60. The server 100 calculates a risk index (the sum of the first to third terms on the right side of equation (11)) Bop0 based on the calculated voltage abnormality index, charging rate abnormality index, and temperature abnormality index.

[0104] The server 100 calculates a corrected risk index Bop by correcting the risk index Bop0 based on an estimation error index that indicates an error in the estimation result of the operation of the vehicle 1 according to the work plan and a load fluctuation index that indicates a fluctuation range of the load on the battery 60 during the work according to the work plan. The server 100 calculates a corrected risk index Bop by correcting the risk index Bop0 based on the calculated predicted work time Time op The server 100 judges whether the value Kop of the objective function including the predicted deterioration amount ΔSOHQ and the corrected risk index Bop is equal to or less than a threshold (predetermined value) Kth. If the value Kop of the objective function is greater than the threshold Kth, the server 100 calculates the work plan again. If the value Kop of the objective function is equal to or less than the threshold Kth, the server 100 outputs the work plan.

[0105] The work plan output from the server 100 is displayed on the display screen of the terminal device 4. For example, as shown in FIG. 1, the work plan is displayed as a graph in which the operation items are arranged in chronological order. Note that the display form of the work plan is not limited to this. The work manager 3 notifies the worker of the contents of the displayed work plan. As a result, each vehicle 1 is able to perform work according to the work plan without stopping. As described above, according to this embodiment, it is possible to provide a work support system that creates a work plan that can appropriately support the work of the vehicle 1 while preventing the vehicle 1 from stopping due to an abnormality in the battery 60, such as running out of power, in addition to taking into account the deterioration of the battery 60. As a result, the burden on the work manager 3 can be reduced.

[0106] (2) The objective function value Kop is the predicted work time Time op The estimated work time Time is the sum of the weighted values ​​of the estimated deterioration amount ΔSOHQ, and the corrected risk index Bop. op The weighting coefficients (constants) k0, k1, and k2 used for weighting the estimated deterioration amount ΔSOHQ, the corrected risk index Bop, respectively, can be changed using the input device 4a. Therefore, the work manager 3 can easily set the priorities of the work time, the deterioration amount, and the stoppage risk.

[0107] <Second embodiment> A work support system according to a second embodiment of the present invention will be described with reference to Figures 14 to 18. Note that the same or corresponding configurations as those described in the first embodiment are denoted by the same reference numerals, and differences will be mainly described.

[0108] The information stored in the vehicle information storage unit 202 and the information stored in the work information storage unit 203 according to the second embodiment are similar to those in the first embodiment (see Figs. 7 and 8). In the first embodiment, an example was described in which the estimated error index stored in the vehicle information storage unit 102 and the load variation index stored in the work information storage unit 103 are fixed values. In contrast, in the second embodiment, when the vehicle 1 actually operates according to the work plan, the estimated error index and the load variation index are updated based on data (battery information and work performance information) measured in the vehicle 1.

[0109] FIG. 14 is a functional block diagram of the server 200 according to the second embodiment, showing functions for creating an operation plan. As shown in FIG. 14, the server 200 acquires, from each vehicle 1, time series data of actual measured values ​​of battery state parameters as battery information when the vehicle 1 actually operates according to the operation plan. FIG. 15 is a diagram showing an example of the time series data of the battery state parameters. As shown in FIG. 15, the time series data of the battery state parameters includes information on the cell voltage value, charging rate SOC, current, and cell temperature of the battery 60 for each predetermined time period (e.g., every minute).

[0110] As shown in Fig. 14, the server 200 acquires from each vehicle 1 work performance information including the actual measured value of the load on the battery 60 when the vehicle 1 actually operated according to the work plan. Fig. 16 is a diagram showing an example of the work performance information. As shown in Fig. 16, the work performance information includes identification information of the vehicle 1 that performed the work, the type of work, the actual measured value of the work time, the actual measured value of the average load, and the actual measured value of the maximum load. In other words, the work performance information is information indicating which vehicle performed which work, how many hours the work was performed, and what the average load and maximum load were during the work.

[0111] As shown in FIG. 14, the server 200 according to the second embodiment has the functions described in the first embodiment, and further has functions as an error index calculation unit 211 and a load index calculation unit 212. The error index calculation unit 211 uses a battery model similar to the plan calculation unit 106, and estimates the time change of the battery state parameters (voltage and temperature) when a current value is input from the battery state of the initial value of the time series data of the actual measurement value of the battery state parameters. FIG. 17 is a diagram showing the time change of the battery state parameters (voltage and temperature). In FIG. 17, the solid line indicates the time change of the actual measurement value, and the dashed line indicates the time change of the predicted value (estimated value). The error index calculation unit 211 calculates an estimated error index based on the difference between the battery state parameters estimated by the battery model (i.e., the predicted value of the battery state parameter) and the actual measurement value of the battery state parameter. The estimated error index is calculated by the following formula (13).

[0112]

number

[0113] Here, c0 and c1 are weighting constants. Act is the actual measured cell voltage value of the battery 60, and V Est is a predicted value of the cell voltage value of the battery 60. The cell voltage is the voltage of the battery cell 62 that constitutes the battery pack 60. T Act is the measured cell temperature of battery 60, and T Est is a predicted value of the cell temperature of the battery 60. Ave is an averaging process. The cell temperature is the temperature of the battery cell 62 that constitutes the battery pack 60. V Act may be the actual measured voltage value of the battery pack 60. In this case, V Est is the predicted voltage value of the battery pack 60. Similarly, T Act may be the actual measured temperature of the battery pack 60. In this case, T Est is the predicted value of the temperature of the battery pack 60.

[0114] The error index calculation unit 211 calculates an average error based on the actual measured value and the predicted value in the time interval in which the time-series data of the battery state parameter exists, based on the formula (13), and calculates an estimation error index that represents an error in the operation estimation of the battery model by performing a weighted average with the voltage error and the temperature error. The estimation error index calculated by the error index calculation unit 211 is stored in the vehicle information storage unit 202. As a result, the estimation error index is updated.

[0115] The update method may be a method of simply rewriting the calculated estimated error index with the existing estimated error index, or another method. For example, the error index calculation unit 211 may use the calculated estimated error index as an update value and calculate a new estimated error index by averaging this update value and the original stored value (existing estimated error index). The error index calculation unit 211 replaces the original stored value with the calculated new estimated error index.

[0116] 18 is a diagram showing an example of work plan information. The load index calculation unit 212 holds work plan information that has been determined in advance for a specific day on which work is to be performed. The work plan information includes the work content (type of work) for each vehicle 1, a predicted work time, a predicted average load, and a predicted maximum load.

[0117] The VCU 55 of the vehicle 1 calculates an actual measured average load value and an actual measured maximum load value based on the time series information of the load on the battery 60 when the work was actually performed on the specified day, and transmits them to the server 200. The load index calculation unit 212 acquires work performance information (see FIG. 16) of the work actually performed on the specified day from each vehicle 1. The work performance information includes the actual work content on the specified day, the actual measured work time, the actual measured average load value and the actual measured maximum load value of the battery 60.

[0118] The load index calculation unit 212 calculates a load fluctuation index based on the actual measured value of the load of the battery 60 included in the work performance information of the vehicle 1 and the predicted value of the load of the battery 60 held as the work plan information. The load fluctuation index is calculated, for example, by the following formula (14).

[0119]

number

[0120] Here, P Act is the actual measured value of the average load on battery 60, and P Est is the predicted value of the average load of the battery 60. The load index calculation unit 212 calculates the load variation index using equation (14), and updates the load variation index stored in the work information storage unit 203 based on the calculated load variation index. For example, if the average load (actual value) when work 1 is actually performed is 5 [kW], while the average load (predicted value) in the work plan is 4.5 [kW], the load variation index is 10%. In other words, there is an error of 10% between the actual measured value and the predicted value of the average load. If the load variation index before the update was 5%, this means that a larger error has occurred, so it is preferable to update the load variation index.

[0121] The update method may be a method of simply rewriting the calculated load variation index with the existing load variation index, or another method. For example, the load index calculation unit 212 may use the calculated load variation index as an update value and calculate a new load variation index by averaging this update value and the original stored value (existing load variation index). The load index calculation unit 212 replaces the original stored value with the calculated new load variation index.

[0122] In this way, the server 200 according to the second embodiment acquires actual measurement values ​​of the battery state parameters (actual measurement values ​​of voltage and temperature) when the vehicle 1 actually operates according to the work plan. The server 200 updates the estimated error index based on the acquired actual measurement values ​​of the battery state parameters and the predicted values ​​of the battery state parameters. The corrected risk index is calculated by correcting the risk index based on the estimated error index. With this configuration, the estimated error index can be appropriately updated based on the actual measurement values ​​of the battery state parameters, making it possible to create a more reliable work plan.

[0123] Moreover, the server 200 according to the second embodiment acquires an actual measurement value of the load (average load) of the battery 60 when the vehicle 1 actually operates according to the work plan. The server 200 updates the load variation index based on the acquired actual measurement value of the load of the battery 60 and the predicted value of the load of the battery 60. The corrected risk index is calculated by correcting the risk index based on the load variation index. According to this configuration, the load variation index can be appropriately updated based on the actual measurement value of the load of the battery 60, making it possible to create a more reliable work plan.

[0124] <Third embodiment> A work support system according to a third embodiment of the present invention will be described with reference to Fig. 19. Note that the same reference numerals are used to designate configurations that are the same as or equivalent to those described in the first embodiment, and differences will be mainly described.

[0125] As in the first embodiment, the server 100 uses the battery state information to calculate the proposed work plan, the predicted amount of deterioration, and the risk index. If there is a large discrepancy between the date and time when the battery state information was acquired and the current date and time, the proposed work plan, the predicted amount of deterioration, and the risk index may not be calculated appropriately. For example, if the vehicle 1 is not driven for a long period of time, the server 100 cannot acquire the battery state information from the vehicle 1 for a long period of time.

[0126] Therefore, in the third embodiment, the server 100 corrects the risk index by taking into account the acquisition date and time of the battery state information. FIG. 19 is a diagram showing an example of battery state information stored in the vehicle information storage unit 102 according to the third embodiment. As shown in FIG. 19, when the server 100 acquires the battery state information from the vehicle 1, the server 100 stores the date and time when the battery state information was acquired as the data update date and time. The risk index calculation unit 108 calculates the corrected risk index Bop by using the following formula (15).

[0127]

number

[0128] Here, b5 and b6 are arbitrary constants. Time is the current date and time, and DataTime is the date and time when the battery status information was acquired (data update date and time). (Time-DataTime) is the date and time difference between the data update date and time and the current date and time (hereinafter, also referred to as the number of days without update). b5 is given to adjust the contribution of the number of days without update (Time-DataTime) to the corrected risk index Bop. b6 is given to prevent the corrected risk index Bop from becoming 0 (zero) when the number of days without update (Time-DataTime) is 0 (zero) (b6≠0). The risk index Bop becomes larger as the number of days without update (Time-DataTime) becomes longer.

[0129] In the example shown in FIG. 19, if today is Feb. 28, 2023, the number of days without update for vehicle A is 0 (zero), and the number of days without update for vehicle C is 365 days.

[0130] In this way, the server 100 according to the third embodiment corrects the risk index Bop0 based on the date and time that has passed since the date and time when the battery state information was acquired (the number of days since an update was made). With this configuration, tasks are assigned to vehicles 1 that have not been updated for a long time, so that the voltage abnormality index, the charging rate abnormality index, the temperature abnormality index, and the like become smaller, compared to vehicles 1 that have not been updated for a short time. This makes it possible to appropriately prevent vehicles 1 that have not been updated for a long time from stopping due to an abnormality such as a lack of power.

[0131] <Fourth embodiment> A work support system according to a fourth embodiment of the present invention will be described. Note that the same reference numerals are used to designate components that are the same as or equivalent to those described in the first embodiment, and differences will be mainly described.

[0132] In the first embodiment, the risk index Bop0 is calculated based on a battery state representative value obtained from the voltage transition, the charging rate transition, and the temperature transition calculated using a battery model data group determined at the time of manufacture. Therefore, as the deterioration of the battery 60 progresses, the battery model data group may not match the actual situation.

[0133] Therefore, in the fourth embodiment, the server 100 corrects the risk index based on the deterioration rate of the battery 60 included in the battery state information (see FIG. 5). The risk index calculation unit 108 calculates the risk index Bop by using the following formula (16).

[0134]

number

[0135] Here, b7 and b8 are arbitrary constants. SOHQ is the current capacity degradation rate of the battery 60. (100-SOHQ) indicates the degree of degradation from the time of manufacture to the present (hereinafter also referred to as the degradation progress degree) when the capacity degradation rate at the time of manufacture (i.e., the initial value of the capacity degradation rate) is set to 100. b7 is given to adjust the contribution of the degradation progress degree (100-SOHQ) to the corrected risk index Bop. b8 is given to prevent the corrected risk index Bop from becoming 0 (zero) when the degradation progress degree (100-SOHQ) is 0 (zero) (b8≠0). The risk index Bop becomes larger as the degradation progress degree (100-SOHQ) becomes larger.

[0136] In this way, the server 100 according to the fourth embodiment corrects the risk index Bop0 based on the deterioration rate (capacity deterioration rate SOHQ) of the battery 60 included in the battery state information. With this configuration, for a vehicle 1 with a high degree of deterioration, tasks are assigned to reduce the voltage abnormality index, charging rate abnormality index, temperature abnormality index, and the like, compared to a vehicle 1 with a low degree of deterioration. This makes it possible to appropriately prevent a vehicle 1 with a high degree of deterioration from stopping due to an abnormality such as a lack of power.

[0137] The following modified examples are also within the scope of the present invention, and it is possible to combine the configurations shown in the modified examples with the configurations described in the above-mentioned embodiments, to combine the configurations described in the different embodiments above, or to combine the configurations described in the different modified examples below.

[0138] <Variation 1> In the above embodiment, an example has been described in which a work plan is created for three vehicles 1. However, the present invention is not limited to this. The present invention may be applied to cases in which a work plan is created for one, two, or four or more vehicles 1.

[0139] <Variation 2> In the above embodiment, an example has been described in which the server 100 corrects the risk index Bop0 by using both the estimation error index and the load variation index. However, the present invention is not limited to this. The server 100 may correct the risk index Bop0 by using one of the estimation error index and the load variation index.

[0140] <Variation 3> In the above-described embodiment, an example has been described in which the risk index Bop0 is calculated based on the voltage, charging rate, and temperature of the battery 60 when the vehicle 1 operates according to the work plan. However, the present invention is not limited to this. The risk index Bop0 may be calculated based on one or two of the voltage, charging rate, and temperature of the battery 60 when the vehicle 1 operates according to the work plan. In other words, one or two of the first to third terms on the right-hand side of equation (11) may be omitted.

[0141] <Modification 4> The constraint conditions are not limited to the above examples. Some of the constraint conditions (Condition 1) to (Condition 7) may be omitted, or new conditions may be added.

[0142] Although the embodiments of the present invention have been described above, the above-mentioned embodiments merely show some of the application examples of the present invention, and it is not intended that the technical scope of the present invention be limited to the specific configurations of the above-mentioned embodiments. [Explanation of symbols]

[0143] 1...vehicle (electric work machine), 1A...vehicle A, 1B...vehicle B, 1C...vehicle C, 3...work manager, 4...terminal device, 4a...input device, 4b...display device, 11...processing device, 12...storage device, 13...input / output interface, 15...communication device, 50...vehicle body control system, 51...vehicle body, 51a...traveling body, 51b...rotating body, 52...working device, 54...electric motor, 55...vehicle control unit, 56...ammeter, 57...battery management unit, 58...charging unit, 59...inverter, 60...battery pack (battery), 61...battery module, 62...battery cell, 70...communication device, 100 ...Server (control device), 101...Optimization calculation unit, 102...Vehicle information storage unit, 103...Work information storage unit, 104...Environmental information storage unit, 105...Outside temperature collation unit, 106...Plan proposal calculation unit, 107...Deterioration amount calculation unit, 108...Risk index calculation unit, 109...Work plan evaluation unit, 200...Server, 202...Vehicle information storage unit, 203...Work information storage unit, 211...Error index calculation unit, 212...Load index calculation unit, Bop...Risk index after correction, Bop0...Risk index before correction, k0, k1, k2...Weighting coefficients (constants used for weighting), NT...Communication line, ΔSOHQ...Predicted deterioration amount

Claims

1. Acquiring battery status information that indicates the status of the battery of the electric working machine and work content information that indicates the content of the work; A work support system including a control device that calculates a work plan for the electric work machine based on the battery state information and the work content information, The control device includes: calculating a predicted value of a battery state parameter including at least one of a voltage, a charging rate, and a temperature of the battery, a predicted work time, and a predicted amount of deterioration of the battery when the electric working machine operates in accordance with the work plan; calculating a risk index representing a risk of the electric working machine stopping based on the predicted value of the battery state parameter; calculating a corrected risk index by correcting the risk index based on at least one of an estimation error index that indicates an error in an estimation result of the operation of the electric working machine according to the work plan and a load fluctuation index that indicates a fluctuation range of the load on the battery during the work according to the work plan; determining whether a value of an objective function including the predicted operation time, the predicted deterioration amount, and the corrected risk index is equal to or less than a predetermined value; if the value of the objective function is greater than the predetermined value, recalculating the work plan; If the value of the objective function is equal to or less than the predetermined value, output the work plan. A work support system comprising:

2. The work support system according to claim 1, The control device includes: Calculating a predicted value of the voltage of the battery; calculating a voltage abnormality index that indicates a risk of the electric working machine stopping due to an abnormal drop in the battery voltage, based on a difference between the calculated predicted voltage value and a predetermined lower limit voltage of the battery; Calculating a predicted charging rate of the battery; calculating a charging rate abnormality index that indicates a risk of the electric working machine stopping due to an abnormal decrease in the charging rate of the battery, based on a difference between the calculated predicted value of the charging rate and a predetermined lower limit charging rate of the battery; Calculating a predicted value of the temperature of the battery; calculating a temperature abnormality index that indicates a risk of the electric working machine stopping due to an abnormal rise in temperature of the battery, based on a difference between the calculated predicted temperature value and a predetermined upper limit temperature of the battery; The risk index is calculated based on the voltage abnormality index, the charging rate abnormality index, and the temperature abnormality index. A work support system comprising:

3. The work support system according to claim 1, The control device includes: acquiring actual measured values ​​of the battery state parameters when the electric operating machine actually operates in accordance with the work plan; updating the estimation error index based on the acquired actual measurement value of the battery state parameter and the predicted value of the battery state parameter; The corrected risk index is calculated by correcting the risk index based on the estimated error index. A work support system comprising:

4. The work support system according to claim 1, The control device includes: acquiring an actual measurement value of the load on the battery when the electric operating machine actually operates according to the work plan; updating the load fluctuation index based on the acquired actual measured value of the load of the battery and the predicted value of the load of the battery; The corrected risk index is calculated by correcting the risk index based on the load variation index. A work support system comprising:

5. The work support system according to claim 1, The control device includes: The risk index is corrected based on the date and time that has elapsed since the date and time that the battery state information was acquired. A work support system comprising:

6. The work support system according to claim 1, The control device includes: The risk index is corrected based on a deterioration rate of the battery included in the battery state information. A work support system comprising:

7. The work support system according to claim 1, a value of the objective function is a sum of weighted values ​​of the predicted operation time, the predicted deterioration amount, and the corrected risk index, The constants used for weighting the predicted work time, the predicted deterioration amount, and the corrected risk index can be changed using an input device. A work support system comprising:

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