Charging management system, charging management method, and charging management program

Abstract

In the present invention, a charging management system, a charging management method, and a charging management program use a controller that controls a charging time during which a battery of a mobile body is continuously charged. The controller calculates the charging time on the basis of a driving time for each mobile body, total power consumption of all the mobile bodies, and total charging power of all the charging spots. The controller calculates, for each mobile body, a timing at which charging needs to be started, and, if the number of other timings falling within a period from a given timing until the charging time elapses is equal to or greater than the number of charging spots, the controller sets a timing at which charging of the battery of the mobile body associated with the given timing is actually started to a time earlier than the given timing.

Description

Charging management system, charging management method, and charging management program

[0001] The present disclosure relates to a charging management system, a charging management method, and a charging management program.

[0002] Patent Document 1 discloses an automatic charging method for a transport system including a plurality of transport vehicles loaded with rechargeable batteries serving as a power source, and a charging device. According to this automatic charging method, the charging device charges the battery of a transport vehicle whose battery current has dropped below a current value that is difficult for carrying out transport work.

[0003] Japanese Patent No. 2694793

[0004] According to the automatic charging method described in Patent Document 1, there is a difference in battery power consumption among a plurality of moving bodies, and the timings at which the remaining battery level falls below a threshold value may overlap. In order to suppress the reduction in efficiency of the entire system caused by moving bodies waiting for battery charging, it is necessary to increase the battery capacity or increase the number of charging spots, which poses a problem of increased cost.

[0005] The present disclosure has been made in view of the above problems. An object of the present disclosure is to provide a charging management system, a charging management method, and a charging management program that can suppress a reduction in efficiency of the entire system caused by moving bodies waiting for battery charging while suppressing an increase in cost.

[0006] The charging management system, charging management method, and charging management program described herein utilize a plurality of mobile units powered by electricity from onboard batteries, charging spots for charging the batteries, and a controller that controls the charging time for continuously charging the batteries of the mobile units. The controller calculates the charging time based on the operating time of each mobile unit, the total power consumption obtained by summing the power consumption of each mobile unit across all mobile units, and the total charging power obtained by summing the charging power of each charging spot across all charging spots. The controller then calculates the timing at which charging of the battery needs to begin for each mobile unit, and if the number of other timings included between one timing and the elapsed charging time is greater than or equal to the number of charging spots, the controller starts charging the battery of the mobile unit at one timing earlier than the timing at that timing.

[0007] The controller may calculate the operating time based on the total battery energy, which is the sum of the battery energy amounts determined by the battery capacity of each mobile unit, and the total power consumption.

[0008] The controller may use the value obtained by dividing the total battery energy by the total power consumption as the operating time.

[0009] The controller may, if the number of other timings included between one timing and the elapsed charging time is greater than or equal to the number of charging spots, actually terminate the charging of the battery of the mobile object related to one timing earlier than any of the other timings.

[0010] The controller may acquire the drive plan of the moving object and estimate the power consumption based on the drive plan.

[0011] The controller may acquire the driving history of the moving object and estimate the power consumption based on that history.

[0012] The controller may calculate the timing for each mobile unit based on its remaining battery level and power consumption.

[0013] According to this disclosure, it is possible to provide a charging management system, a charging management method, and a charging management program that can suppress the decrease in overall system efficiency caused by a mobile vehicle waiting for its battery to charge, while suppressing the increase in costs.

[0014] This is a block diagram showing the configuration of the charging management system related to this disclosure. This is a flowchart showing the operation flow of the charging management system related to this disclosure. This is a diagram showing an example of the charging start timing when there is overlap. This is a diagram showing an example of the charging start timing when there is no overlap.

[0015] Several exemplary embodiments will be described below with reference to the drawings. Common parts in each drawing are denoted by the same reference numerals, and redundant explanations will be omitted.

[0016] This disclosure describes a charging management system that efficiently manages the charging of batteries mounted on multiple mobile robots. The key feature of this charging management system is that it manages the power consumption and battery level of multiple mobile robots, predicts overlapping charging timings, and proactively performs early charging, thereby suppressing a decrease in system efficiency due to waiting for charging. In this disclosure, "mobile robot" is an example of a mobile device.

[0017] For example, the mobile device may be an AMR (Autonomous Mobile Robot) that autonomously navigates within a logistics warehouse and transports goods. Alternatively, the mobile device may be an AGV (Automated Guided Vehicle). The mobile device is not limited to the examples given here.

[0018] [Configuration of the charging management system] Figure 1 is a block diagram showing the configuration of the charging management system according to this disclosure. The charging management system 1 comprises a plurality of mobile robots 10, one or more charging spots 20, and a control and control device 30 (Fleet Management System).

[0019] The mobile robot 10 is managed by the charging management system 1 and moves within a predetermined area. The mobile robot 10 comprises a battery 11, a power consumption monitoring unit 12, a remaining charge monitoring unit 13, a charging unit 14, a drive unit 15, a self-position estimation unit 16, a movement control unit 17, and a communication unit 18. In the following description, the mobile robot 10 will be described as an AMR (Anti-Mobile Robot).

[0020] Battery 11 is a rechargeable power source that supplies power to the mobile robot 10 as its power source. Battery 11 is composed of a secondary battery, such as a lithium-ion battery. Battery 11 is discharged from a fully charged state to a certain level and then recharged at the charging spot 20, and this process is repeated. Based on its battery characteristics, Battery 11 is designed to be used efficiently within a range such as 20% to 90% State of Charge (SOC). The lower limit of SOC set to efficiently use Battery 11 will be called the "lower SOC limit," and the upper limit of SOC will be called the "upper SOC limit" below. According to the example of the SOC range "20% to 90%" shown above, the lower SOC limit is 20% and the upper SOC limit is 90%. The lower SOC limit and upper SOC limit are not limited to this example and can be arbitrarily set based on the battery characteristics of Battery 11.

[0021] The power consumption monitoring unit 12 has the function of measuring and monitoring the power consumption from the battery 11. The power consumption monitoring unit 12 measures the amount of power consumed in real time as the mobile robot 10 operates using a current sensor and a voltage sensor. The measured power consumption data is transmitted to the control device 30 via the communication unit 18. This allows the control device 30 to grasp the power consumption trend of each mobile robot 10 and predict future power consumption.

[0022] The remaining charge monitoring unit 13 has the function of measuring and monitoring the remaining charge (SOC) of the battery 11. The remaining charge monitoring unit 13 calculates the current battery charge with high accuracy using parameters such as the voltage, current, and temperature of the battery 11. The calculated battery charge data is transmitted to the control device 30 via the communication unit 18. This battery charge data is an important factor in determining when charging is necessary.

[0023] The charging unit 14 has the function of charging the battery 11 by connecting to the charging spot 20. The charging unit 14 includes a charging connector, a charging control circuit, etc., and realizes efficient charging. The charging unit 14 starts and stops charging based on instructions from the control device 30 and monitors the state of the battery during charging. It also switches between rapid charging and normal charging, enabling charging in a short time while maximizing the life of the battery 11.

[0024] The drive unit 15 has the function of driving the mobile robot 10 using power from the battery 11. The drive unit 15 includes a motor and a motor driver, and controls the speed and direction of movement of the mobile robot 10 based on instructions from the movement control unit 17. The motor drives the wheels of the mobile robot 10, and the motor driver controls the power supply to the motor. The drive unit 15 is the main power source of the mobile robot 10, and its power consumption varies depending on the speed of movement, the load weight, and the incline of the travel path.

[0025] The self-position estimation unit 16 has the function of estimating the current position of the mobile robot 10. The self-position estimation unit 16 estimates its own position in the warehouse in real time using sensors such as LiDAR, cameras, and encoders. The estimated position information is provided to the mobile control unit 17 and is also transmitted to the control and control device 30 via the communication unit 18.

[0026] The movement control unit 17 has the function of controlling the movement of the mobile robot 10 based on position information obtained from the self-position estimation unit 16 and route information received from the control device 30. The movement control unit 17 plans the optimal route to the destination (work location or charging spot) and controls the drive unit 15 to realize movement along that route.

[0027] The communication unit 18 has the function of performing wireless communication with the control and control device 30. The communication unit 18 transmits data such as battery power consumption, battery level, and location information to the control and control device 30 using wireless communication technology such as Wi-Fi, and receives instructions (route information, charging instructions, etc.) from the control and control device 30. In order to ensure the reliability of communication, the communication unit 18 also monitors the communication status and switches the communication method as needed.

[0028] The charging spot 20 is a facility for charging the battery 11 of the mobile robot 10. The charging spot 20 includes a charging device 21 and a communication device 22. The charging device 21 supplies power to the battery 11 by connecting to the charging unit 14 of the mobile robot 10. The charging device 21 supports multiple charging modes (rapid charging, normal charging, slow charging, etc.) and performs optimal charging according to the instructions of the control device 30. Here, rapid charging is a power receiving method that supplies more power in a shorter time than normal charging. Slow charging is a charging method in which the charging speed is intentionally slower than normal charging. Slow charging may be used to suppress heat generation in the battery 11 and extend the life of the battery 11. The communication device 22 communicates with the control device 30, transmits information such as the charging status and the operating status of the charging device, and receives charging control instructions from the control device 30.

[0029] The control device 30 is a central control unit that manages and controls the entire charging management system 1. The control device 30 comprises a system control unit 31, a charging management unit 32, a communication unit 33, a storage unit 34, and a WCS interface 35. Here, WCS is an abbreviation for Warehouse Control System.

[0030] The system control unit 31 controls the operation of the entire control device 30 and has the function of managing the operation of the mobile robot 10. Based on the transport instructions received from the WCS 40, the system control unit 31 assigns the mobile robot 10, plans the work, plans the route, etc., to realize optimal logistics operations. It also works in conjunction with the charging management unit 32 to comprehensively optimize the work plan and the charging plan.

[0031] The charging management unit 32 optimally manages the battery charging of the mobile robots 10. The charging management unit 32 functions as a controller and analyzes battery power consumption and battery level data received from the mobile robots 10 to understand the battery status of the entire group of mobile robots. Based on this, it predicts when each mobile robot 10 will need to be charged (charging start timing) and determines the optimal charging schedule, taking into account the number of charging spots 20. In particular, if it is predicted that the charging start timings will overlap, it may instruct some of the mobile robots 10 to start charging early while they still have sufficient battery level. This prevents a decrease in system efficiency due to concentrated charging.

[0032] Here, the controller is, for example, a general-purpose computer equipped with a CPU (Central Processing Unit), memory, and an input / output unit. The controller has a computer program (charging management program) installed for controlling the charging management system 1. This disclosure shows an example of realizing an information processing circuit using software. However, it is also possible to configure the information processing circuit by preparing dedicated hardware. The computer program may be stored in a storage medium that can be read and written by the computer, or it may be distributed via a telecommunications line.

[0033] The communication unit 33 has the function of performing wireless communication with the mobile robot 10 and the charging spot 20. Using wireless communication technology such as Wi-Fi, the communication unit 33 receives battery information, location information, etc. from the mobile robot 10 and transmits route instructions, charging instructions, etc. to the mobile robot 10. It also communicates with the charging spot 20 to monitor the charging status and control charging.

[0034] The memory unit 34 is a storage device that stores data necessary for the operation of the control device 30. The memory unit 34 stores data such as the battery power consumption history, battery level history, and charging history of the mobile robot 10. This data is analyzed using techniques such as machine learning and used to predict more accurate battery power consumption and charging start timing. The memory unit 34 includes non-volatile storage media such as a hard disk and flash memory, and stores various programs and data.

[0035] The WCS interface 35 has the function of communicating with the higher-level system, WCS 40. The WCS 40 is a system that issues instructions for transport operations in the logistics warehouse to the control and control device 30, and the WCS interface 35 receives instructions for transport operations from the WCS 40 and provides those instructions to the system control unit 31. It also transmits information such as the progress of the work and the operating status of the mobile robot 10 to the WCS 40. Through the cooperation between the WCS 40 and the control and control device 30, the logistics management of the entire warehouse and the operational management of the mobile robot 10 are integrated and optimized.

[0036] [Operation of the Charging Management System] Figure 2 is a flowchart showing the operation flow of the charging management system according to this disclosure.

[0037] In step S101, the charging management unit 32 collects battery power consumption and battery level from each mobile robot 10. This data is collected periodically via the communication unit 33, enabling real-time monitoring of the battery status.

[0038] In step S102, the charging management unit 32 determines the total power consumption of the entire group of mobile robots. Specifically, it calculates the total power consumption by summing the power consumption of each mobile robot 10 that is not being charged. Note that for the purpose of calculation, the power consumption of each mobile robot 10 that is being charged may be treated as zero. The power consumption of each mobile robot 10 obtained in this way may then be summed up across all the mobile robots 10 to calculate the total power consumption. In addition, the charging management unit 32 calculates the total battery energy by summing the remaining power of the batteries 11 of each mobile robot 10 that is not being charged up to the lower limit of SOC. For example, if the lower limit of SOC is 20% and the SOC is 60%, then "60% - 20% = 40%" of the capacity of the battery 11 will be the remaining power of each mobile robot 10 that is not being charged. Note that for the purpose of calculation, the remaining power of each mobile robot 10 that is being charged may be treated as zero. The remaining power of each mobile robot 10 obtained in this way may then be summed up across all the mobile robots 10 to calculate the total battery energy.

[0039] In step S103, the charging management unit 32 determines the charging capacity of the charging spots 20. Specifically, the charging management unit 32 calculates the total charging power by summing the charging power of each charging spot 20 and evaluates the overall charging capacity of the system.

[0040] In step S104, the charging management unit 32 calculates the operating time of the mobile robot group. The operating time is calculated as the theoretical operating time of the mobile robot group by dividing the total battery energy by the total power consumption. Based on this operating time, the time until each mobile robot 10 needs to be charged is also predicted. The operating time is determined based on the total power consumption of the mobile robots 10 that are not being charged, and the total remaining power of the battery 11 up to the lower limit of its State of Charge (SOC).

[0041] In step S105, the charging management unit 32 calculates the charging time. The charging time is calculated based on the operating time, total power consumption, and total charging power of each mobile robot 10. Specifically, the time required to charge the battery 11 to a predetermined level is calculated.

[0042] In step S106, the charge management unit 32 calculates, for each mobile robot 10, the timing at which it is necessary to start battery charging. This timing is determined based on the current remaining battery level, predicted power consumption, the allowable range of remaining battery level (SOC range), and the like.

[0043] In step S107, the charge management unit 32 determines whether or not charging start timings overlap. Specifically, the charge management unit 32 determines whether the number of other timings included in the period from a certain timing until the charging time elapses is equal to or greater than the number of charging spots 20. In this way, a situation in which more mobile robots 10 than the number of charging spots 20 require charging at the same time is detected. If no overlap of charging start timings is detected (NO in step S107), the process proceeds to step S110.

[0044] If an overlap of charging start timings is detected (YES in step S107), in step S108, the charge management unit 32 advances the actual charging start timing of batteries 11 of some mobile robots 10. Specifically, a mobile robot 10 having a relatively large remaining battery margin is instructed to move to a charging spot 20 earlier than the original charging start timing. This minimizes waiting time at the charging spots 20 and prevents a decrease in efficiency of the entire system.

[0045] In step S109, the charge management unit 32 also adjusts the "actual end timing of charging" (charging end timing) for each mobile robot 10 as necessary. When the overlap of charging start timings is severe, some mobile robots 10 may be instructed to end charging at the charging end timing before reaching full charge, and to yield the charging spot 20 to other mobile robots 10. In this case, even if it is partial charging, charging is reliably performed to a level that allows operation until the next charging start timing.

[0046] In step S110, the charge management unit 32 transmits a charging instruction to each mobile robot 10 based on the optimized charging schedule. This instruction includes the timing for moving to the charging spot 20, the designation of the charging spot 20 to be used, the designation of the charging mode, and the like.

[0047] In step S111, the mobile robot 10 moves to the charging spot 20 in accordance with the instruction from the charge management unit 32 and performs charging. Even during charging, the battery state is reported to the traffic control device 30, and charging parameters are adjusted as necessary.

[0048] After charging is completed, the mobile robot 10 returns to normal operation, and the above process is repeated. Through this cycle, the entire group of mobile robots is efficiently operated, and the reduction in system efficiency caused by waiting for charging is minimized.

[0049] [Specific example of charging start timing] FIG. 3 is a diagram showing an example of charging start timing when there is overlapping timing. In FIG. 3, the upper part is a graph showing the time change of SOC, and the lower part is a time chart showing the state change of each mobile robot 10 (10A to 10C). It is assumed that there are three mobile robots 10 and only one charging spot 20 in this situation.

[0050] In the SOC graph of FIG. 3, the vertical axis represents the remaining battery level (SOC), and the horizontal axis represents time. A polygonal line CV1 indicates the SOC of the battery 11 provided in the mobile robot 10A. Similarly, a polygonal line CV2 indicates the SOC of the battery 11 provided in the mobile robot 10B, and a polygonal line CV3 indicates the SOC of the battery 11 provided in the mobile robot 10C. In the SOC graph, the threshold value requiring charging (SOC 20%) is indicated by a broken line.

[0051] In this example, the SOC of the batteries 11 of the mobile robots 10A, 10B, and 10C all reach 20% at time T1. This indicates a situation where the three mobile robots require charging at the same time, and overlapping of charging timing occurs.

[0052] In the time chart of Figure 3, times T1, T2, T3, and T4 indicate the timing when the operating state of each mobile robot changes. State ST1 indicates that the mobile robot is operational. State ST2 indicates that the mobile robot is charging. State ST3 indicates that the mobile robot is in standby mode, specifically a state where it is unable to charge because the charging spot is in use, even though it needs to be charged.

[0053] At time T1, the State of Charge (SOC) of the batteries 11 of mobile robots 10A, 10B, and 10C all reach 20%, but due to the limitation of the number of charging spots 20 (e.g., one), not all mobile robots can start charging simultaneously. In this example, mobile robot 10A is given priority and starts charging from time T1 (state ST2).

[0054] Meanwhile, mobile robots 10B and 10C also require charging at time T1, but since charging spot 20 is being used by mobile robot 10A, they enter a standby state (state ST3). Mobile robot 10B starts charging at time T2 after mobile robot 10A has finished charging, and mobile robot 10C starts charging at time T3 after mobile robot 10B has finished charging.

[0055] Once each mobile robot has finished charging, its State of Charge (SOC) increases (upward line on the graph), and it returns to an operational state (state ST1). However, with this charging method, if the charging timings of multiple mobile robots overlap, the number of mobile robots exceeding the number of charging spots will enter a waiting state (state ST3), resulting in a decrease in the overall operational efficiency of the system during the waiting period.

[0056] To address this problem, the charging management system 1 of this disclosure predicts overlapping charging timings in the future and controls some mobile robots to start charging early when there is sufficient battery charge remaining. This suppresses the occurrence of the standby state ST3 and improves the overall efficiency of the system.

[0057] Figure 4 shows an example of the charging start timing when there is no overlap. In particular, Figure 4 shows an example of early charging control to avoid overlapping charging timings. In Figure 4, the upper part is a graph showing the time change of SOC (State of Charge), and the lower part is a time chart showing the state changes of each mobile robot. Each state is the same as in Figure 3.

[0058] In the SOC graph of Figure 4, the vertical axis represents the remaining battery capacity (SOC), and the horizontal axis represents time. Similar to Figure 3, line CV1 shows the SOC of battery 11 related to mobile robot 10A, line CV2 shows the SOC of battery 11 related to mobile robot 10B, and line CV3 shows the SOC of battery 11 related to mobile robot 10C. The threshold for when charging is required (SOC 20%) is indicated by a dashed line in the SOC graph.

[0059] The time chart in Figure 4 shows times E1, E2, T1, and T2. Times E1 and E2 indicate the timing of the start of early charging determined by the charging management system 1 of this disclosure.

[0060] In the charging management system 1 of this disclosure, the controller (charging management unit 32) monitors the battery power consumption and remaining battery level of all mobile robots and predicts when future charging will be required. Then, as shown in Figure 4, if a situation is predicted at time T1 in which three mobile robots will need to be charged simultaneously (overlapping charging timings), the controller controls mobile robot 10A to start charging early at time E1 and mobile robot 10B to start charging early at time E2, while their battery levels are still sufficient.

[0061] Specifically, at time E1, mobile robot 10A enters a charging state (state ST2), and at time E2, before charging is complete, mobile robot 10B enters a charging state (state ST2). Furthermore, at time T1, mobile robot 10C enters a charging state (state ST2). By staggering the charging timing in this way, the standby state (state ST3) that occurred in the method shown in Figure 3 is eliminated, and all mobile robots are operated only in the operational state (state ST1) and the charging state (state ST2).

[0062] According to the early charging control shown in Figure 4, each mobile robot will not experience waiting time due to charging, improving the overall efficiency of the system. Furthermore, at the start of early charging (times E1 and E2), the battery level is still well above the 20% SOC threshold, allowing the mobile robots to operate.

[0063] Thus, the charging management system 1 of this disclosure grasps the remaining battery level and battery power consumption of the entire group of mobile robots and predicts overlapping charging timings. By instructing some mobile robots to charge early, it is possible to suppress a decrease in the overall efficiency of the system without increasing the number of charging spots.

[0064] In this embodiment, the timing for charging is set when the battery level of the mobile robots 10A, 10B, and 10C reaches 20% of the State of Charge (SOC). However, this SOC threshold can be appropriately set depending on the type of battery, the intended use of the mobile robots, a predetermined margin, etc. Furthermore, the timing for starting early charging (times E1, E2) is determined by the controller according to the number of charging spots, the number of mobile robots, the predicted overlap of charging timings, etc.

[0065] [Other] The following alternative embodiments of the charging management system of this disclosure are also possible.

[0066] By placing the charging spot 20 near the mobile robot 10's waiting area or the loading / unloading location (transfer location), charging can be performed between tasks. Specifically, the charging spot 20 is strategically placed at the load transfer location to the mobile robot 10 (AMR), the transfer waiting location, and the waiting location for adjusting the order of load arrival. This allows the mobile robot 10 to be charged while it is stopped during work. This reduces the dedicated travel time for charging and is expected to further improve efficiency.

[0067] Furthermore, work assignments and charging schedules may be optimized simultaneously. This enables more efficient system operation. For example, a mobile robot 10 with a low battery level can be assigned work near a charging spot 20. In addition, by calculating the predicted power consumption of each mobile robot 10 based on the work plan from the higher-level system, WCS 40, the work content and charging plan can be optimized in an integrated manner. In particular, if the transport distance or load weight is known in advance, more accurate power consumption prediction becomes possible.

[0068] Based on operational data accumulated in a database, an advanced power consumption prediction model may be constructed that takes into account factors such as time of day (morning, afternoon, evening), day of the week (weekdays, holidays), and season (summer, winter, etc.). By registering the power consumption of the AMR group in a database and calculating power consumption using a machine learning algorithm based on these temporal elements, it becomes possible to make predictions that also take into account fluctuations according to environmental conditions or operating patterns. This enables even more accurate prediction of charging timing.

[0069] Additional features may be implemented to maximize battery life through charge cycle management. For example, battery degradation can be suppressed by avoiding frequent complete discharges and promoting operation within the appropriate SOC range.

[0070] In addition, charging costs and efficiency can be optimized by adjusting the timing and speed of charging, taking into account factors such as battery status, peak electricity demand, and electricity rates.

[0071] The charging management system 1 can also operate in conjunction with the air conditioning system and other power-consuming equipment within the warehouse. Specifically, by integrating with the energy management system, the charging schedule can be synchronized with the building's overall power demand pattern, leveling out peak power demand. This reduces investment costs in physical power infrastructure and results in a concrete reduction in electricity costs. Furthermore, a simulation function may be added to optimize the physical placement of charging spots. This enables a specific layout design that simultaneously minimizes the travel distance of mobile robots and maximizes work efficiency.

[0072] These alternative implementations are options that extend the functionality of the basic charging management system and accommodate a wider range of operating environments. In actual deployment, these functions can be selectively implemented depending on the operating environment and requirements.

[0073] [Effects of the Embodiment] As described in detail above, the charging management system, charging management method, and charging management program according to this disclosure use a plurality of mobile bodies driven by power from an onboard battery, a charging spot for charging the battery, and a controller that controls the charging time for continuously charging the battery related to the mobile body. The controller calculates the charging time based on the driving time of each mobile body, the total power consumption obtained by summing the power consumption of each mobile body over the entire mobile body, and the total charging power obtained by summing the charging power of each charging spot over the entire charging spot. The controller then calculates the timing at which charging of the battery needs to start for each mobile body, and if the number of other timings included between one timing and the elapsed charging time is greater than or equal to the number of charging spots, the timing at which charging of the battery related to the mobile body related to one timing is actually started is brought earlier than one timing.

[0074] This helps to suppress cost increases while mitigating the overall system efficiency reduction that occurs when mobile units wait for their batteries to charge.

[0075] In particular, by diversifying the timing of charging, multiple mobile units can be operated efficiently without increasing battery capacity or the number of charging stations. This makes it possible to achieve both overall system cost reduction and improved operational efficiency. Furthermore, optimizing battery capacity enables lighter, faster, and more power-efficient mobile units. In addition, reducing wasted waiting time due to charging contributes to faster work and more efficient use of human resources.

[0076] The controller may calculate the operating time based on the total battery energy, which is the sum of the battery energy amounts determined by the battery capacity of each mobile unit, and the total power consumption. This enables accurate operating time prediction that takes into account the energy balance of the entire system, and allows for more precise charge management. Even when there are multiple mobile units of different types or capacities, optimal operation of the entire system becomes possible.

[0077] The controller may use the value obtained by dividing the total battery power by the total power consumption as the operating time. This makes it easier to predict the operating time in real time and enables efficient use of computing resources. In addition, it allows for an intuitive understanding of the operating time of the entire system, which helps in supporting administrator decision-making.

[0078] The controller may, if the number of other timings included between one timing and the elapsed charging time is greater than the number of charging spots, actually end the charging of the battery of the mobile device related to one timing earlier than any of the other timings. This allows for flexible adjustment of not only the start but also the end timing of charging, further improving the utilization efficiency of charging spots. By continuing operation with the minimum necessary charge, the occupancy time of charging spots is reduced, and charging opportunities can be provided to more mobile devices.

[0079] The controller may acquire the drive plan of the moving object and estimate power consumption based on the drive plan. This enables proactive power consumption forecasting that takes future work content into account, and allows for planned charging management. In particular, in environments where fluctuations in workload are expected, this function enables preparation for charging at the appropriate time.

[0080] The controller may acquire the driving history of the mobile unit and estimate power consumption based on that history. This enables highly accurate power consumption prediction based on actual operational data and prevents problems caused by discrepancies between theoretical and measured values. Furthermore, it has the advantage that prediction accuracy continuously improves as data accumulates over time.

[0081] The controller may calculate the timing for each mobile unit based on its battery level and power consumption. This allows for precise management of the charging start timing, taking into account the individual circumstances of each mobile unit, achieving both overall system optimization and stable operation of individual units. This function is particularly important in environments where mobile units of different types or usage conditions are mixed.

[0082] Each of the functions described in the embodiments above may be implemented by one or more processing circuits. These processing circuits may include programmed processors, electrical circuits, and further may include devices such as application-specific integrated circuits (ASICs), or circuit components arranged to perform the described functions.

[0083] According to this disclosure, the overall efficiency of the system will be improved, leading to increased labor productivity. Therefore, for example, it can contribute to Goal 8 of the United Nations-led Sustainable Development Goals (SDGs), "Promote inclusive and sustainable economic growth and full and productive employment and decent work for all."

[0084] Although several embodiments have been described, it is possible to modify or transform the embodiments based on the above disclosure. All components of the above embodiments, and all features described in the claims, may be taken individually and combined, provided that they do not conflict with each other.

[0085] The entire contents of Japanese Patent Application No. 2025-049849 (Filing Date: March 25, 2025) are incorporated herein by reference.

[0086] 1 Charging Management System 10 Mobile Robot (Mobile Unit) 11 Battery 12 Power Consumption Monitoring Unit 13 Remaining Charge Monitoring Unit 14 Charging Unit 15 Drive Unit 16 Self-Position Estimation Unit 17 Movement Control Unit 18 Communication Unit 20 Charging Spot 21 Charging Device 22 Communication Device 30 Control and Control System 31 System Control Unit 32 Charging Management Unit 33 Communication Unit 34 Memory Unit 35 WCS Interface 40 WCS

Claims

1. A charging management system comprising: a plurality of mobile bodies powered by electricity from an onboard battery; a charging spot for charging the battery; and a controller for controlling the charging time for continuously charging the battery relating to the mobile body, wherein the controller calculates the charging time based on the driving time for each mobile body, the total power consumption obtained by summing the power consumption of each mobile body over the entire mobile body, and the total charging power obtained by summing the charging power of each charging spot over the entire charging spot; calculates the timing at which charging of the battery needs to be started for each mobile body; and, if the number of other timings included between one of the timings and the elapsed charging time is equal to or greater than the number of charging spots, the timing at which charging of the battery relating to one of the timings is actually started is earlier than one of the timings.

2. The charging management system according to claim 1, wherein the controller calculates the operating time based on the total battery energy, which is the sum of the battery energy amounts determined based on the battery capacity of each mobile unit, and the total power consumption.

3. The charging management system according to claim 2, wherein the controller uses the value obtained by dividing the total battery energy by the total power consumption as the operating time.

4. The charging management system according to claim 1, wherein the controller advances the timing at which the charging of the battery relating to the mobile body relating to one timing is actually completed, if the number of other timings included between one timing and the elapsed charging time is equal to or greater than the number of charging spots.

5. The charging management system according to claim 1, wherein the controller acquires a drive plan for the mobile body and estimates the power consumption based on the drive plan.

6. The charging management system according to claim 1, wherein the controller acquires the driving record of the mobile body and estimates the power consumption based on the driving record.

7. The charging management system according to any one of claims 1 to 6, wherein the controller calculates the timing for each mobile body based on the remaining battery charge and the power consumption.

8. A charging management method relating to a charging management system comprising: a plurality of mobile bodies driven by power from an installed battery; a charging spot for charging the battery; and a controller for controlling the charging time for continuously charging the battery relating to the mobile body, wherein the controller calculates the charging time based on the driving time for each mobile body, the total power consumption obtained by summing the power consumption of each mobile body over the entire mobile body, and the total charging power obtained by summing the charging power of each charging spot over the entire charging spot; calculates the timing at which charging of the battery needs to be started for each mobile body; and, if the number of other timings included between one of the timings and the elapsed charging time is equal to or greater than the number of charging spots, the timing at which charging of the battery relating to one of the timings is actually started is earlier than one of the timings.

9. A charging management program relating to a charging management system comprising: a plurality of mobile bodies driven by power from an installed battery; a charging spot for charging the battery; and a controller for controlling the charging time for continuously charging the battery relating to the mobile body, the program comprising: a step of calculating the charging time based on the driving time for each mobile body, the total power consumption obtained by summing the power consumption of each mobile body over the entire mobile body, and the total charging power obtained by summing the charging power of each charging spot over the entire charging spot; a step of calculating the timing at which charging of the battery for each mobile body is required to begin; and a step of accelerating the timing at which charging of the battery relating to one of the mobile bodies is actually started, if the number of other timings included between one of the timings and the elapsed charging time is equal to or greater than the number of charging spots.

Images