TWI789269B - Automatic charging scheduling system - Google Patents

Abstract

The invention provides an automatic charging scheduling system, which is applied to multiple automatic guided vehicles (AGVs). The automatic charging scheduling system includes a charging module, a production module, and a control module. The control module receives the battery information of the remaining power of the AGVs through the charging module, and receives the work information transmitted by the production module. The control module calculates the required charging time based on the remaining power of the AGVs, calculates the waiting time for the AGV to resume work based on the charging time, and makes real-time judgments through algorithms to generate the AGVs’ charging schedules. With the use of industrial wireless transmission equipment, the system transmits the work information to each production line in real time, and successfully realizes AGV monitoring and dispatch system solutions, assisting enterprises in creating benefits such as smart manufacturing.

Description

Automatic scheduling system for charging progress

The invention relates to an automatic scheduling system for charging progress. In particular, the present invention relates to an automatic charging scheduling system applied to an automatic guided vehicle (Automated Guided Vehicle, AGV).

In recent years, with the rise of industrial automation, automated guided vehicles have been widely used in factories and warehouses to be responsible for loading, unloading, moving, storing and delivering materials. Traditionally, only 5% of the time in the manufacturing process of products is spent on manufacturing, and the remaining 95% of the time is spent on storage, loading and unloading, waiting for processing and delivery. Therefore, the introduction of automatic guided vehicles can reduce the waste of time. The overall production efficiency can also greatly reduce labor costs, save factory space allocation, and effectively reduce operating costs.

At present, automatic guided vehicles generally use rechargeable batteries as the power source for movement, but the current common rechargeable batteries still cannot provide the power for automatic guided vehicles to work for a full day. Once the battery power is exhausted, the battery must be charged. Since automatic guided vehicles are generally used to perform monotonous tasks, this type of work is to repeat the same actions repeatedly without the need for self-decision making, so human intervention is rarely required. Although there are automated charging modules currently on the market, their charging scheduling mainly relies on the rules and logic of dispatching workers. However, due to the current factory management, it is often faced with various contingencies such as new additions and eliminations of equipment, so many scheduling systems After the current production status changes, it is discarded because the scheduling results that meet the on-site production requirements cannot be discharged, and manual intervention is required to modify it. The automatic guided vehicle is in a discontinuous task loop, which will inevitably destroy the work integrity of the automatic guided vehicle. Sex, reduce the work efficiency of automatic guided vehicles and greatly increase labor costs.

Chinese Patent No. CN109591649A discloses an automatic guided vehicle power supply system based on RFID communication and Internet technology, including a background server and several automatic guided vehicle systems. The automatic guided vehicle system includes a charging station management computer, several power supply Charging station for automatic guided vehicle charging And several automatic guided vehicles that need to be charged; the battery management system of the automatic guided vehicle to be charged will transmit the parameters of the battery of the automatic guided vehicle to the corresponding charging station through RFID in real time, and the charging station will pass the parameters of the battery through the charging station The management computer sends it to the background server. The background server judges and corrects the battery charging curve according to the battery parameters, and sends the curve to the charging station. The charging station performs reasonable charging according to the corrected charging curve, thus ensuring automatic guidance. The charging safety of the battery of the vehicle prolongs the service life of the battery of the automatic guided vehicle and can meet the reliable collection and transmission of the battery pack data of hundreds of automatic guided vehicles on site.

However, the problem with the above-mentioned power supply system is that it is impossible to adjust the charging schedule according to the current production status of the production line. During the production process, the production status of the production line is a dynamic change. Cause the production line to delay the follow-up process. Therefore, how to provide a way to implement algorithms so that the charging station can make real-time dynamic adjustments to the power supply according to the current production status changes, so as to arrange the charging schedule results that meet the on-site production needs. The charging scheduling results can make At the two ends of production and charging management, under the condition of seamless information integration, it is an urgent problem to effectively reduce the demand for materials shortage between the production chains and improve the overall production capacity.

In view of the above-mentioned shortcoming, the inventor researches the way of improvement aiming at these shortcoming, finally has the present invention to produce.

The main purpose of the present invention is to provide an automatic scheduling system for charging progress, which is applied to a plurality of automatic guided vehicles. The automatic scheduling system for charging progress receives the battery information of the remaining power of the automatic guided vehicle through the charging module, and borrows The control module receives the work information sent by the production module, so that the control module calculates the required charging time according to the remaining power of the automatic guided vehicle, and at the same time calculates the waiting time for the automatic guided vehicle to resume work according to the charging time, through calculation There is no way to make real-time judgments to generate the charging schedule of automatic guided vehicles. This system is equipped with industrial wireless transmission equipment to transmit the work information of each production line in real time, and successfully realizes automatic guided vehicle monitoring and dispatching system solutions, helping enterprises create wisdom manufacturing benefits.

In order to achieve the above purpose and effect, the present invention provides an automatic scheduling system for charging progress, which is applied to a plurality of automatic guided vehicles. The automatic charging scheduling system includes: a plurality of charging modules, which are used for automatic The guided vehicle is charged, and can receive the battery information of the automatic guided vehicle including a remaining power; a production module: used to generate the working information of the automatic guided vehicle; a control module group, which is coupled to the charging modules and the production module, the control module receives the battery information of the automatic guided vehicles including the remaining power; wherein, when the remaining power of the automatic guided vehicles When the power is lower than a charging power, the automatic guided vehicle moves to the charging module for charging, and the control module controls the charging module to charge according to a target power set by the automatic guided vehicle. The group receives the work information of the automatic guided vehicle sent by the production module, and the control module calculates from the time point of receiving the work information to A charging time required for the automatic guided vehicle to charge to the target power is multiplied by a reward parameter to generate a charging benefit of the automatic guided vehicle, and a waiting time for the automatic guided vehicle to resume work is calculated based on the charging time multiplied by A penalty parameter generates a working benefit of the automatic guided vehicle, and the control module generates a difference by subtracting the charging benefit from the working benefit; if the remaining power of the automatic guided vehicle is greater than the chargeable power and the difference If it is less than zero, the control module controls the charging module to stop charging the automatic guided vehicle, and transmits the working information to the automatic guided vehicle through the charging module.

Preferably, according to the charging schedule automatic scheduling system of the present invention, the amount of charge to be charged is less than 40% of the full charge of the automatic guided vehicle, but the present invention is not limited thereto.

Preferably, according to the charging progress automatic scheduling system of the present invention, wherein, the charging order of the remaining power of the automatic guided vehicle is lower than 20% of the full power is prior to the remaining power of the automatic guided vehicle The charging sequence is between 20% and 40% of the full charge, but the invention is not limited thereto.

Preferably, according to the charging progress automatic scheduling system of the present invention, the target electric quantity is more than 80% of the full electric quantity of the automatic guided vehicle, but the present invention is not limited thereto.

Preferably, according to the charging progress automatic scheduling system of the present invention, wherein the charging stop when the remaining power of the automatic guided vehicle is greater than 95% of the full power is ranked before the remaining power of the automatic guided vehicle The charging sequence is stopped at 80% to 95% of the full charge, but the invention is not limited thereto.

Preferably, according to the charging progress automatic scheduling system of the present invention, the battery information includes battery life, and when the remaining power of two or more of the automatic guided vehicles is lower than the charging power, the control module The battery is charged according to the battery with the lower remaining power; if the two remaining powers are the same, the control module is charged with the battery with the longer service life.

Preferably, according to the charging progress automatic scheduling system of the present invention, if the difference value of the automatic guided vehicle is greater than zero, the control module checks the charging time according to the charging of the charging module Calculate the charging benefit, the working benefit and the difference at the time point of the inspection time based on the speed and the charged amount of the automatic guided vehicle.

Preferably, the automatic scheduling system for charging progress according to the present invention further includes: an electricity price module, which is coupled to the control module, and the electricity price module transmits an electricity price information to the control module, and the electricity price The information changes with time; wherein, the control module further generates the charging benefit according to the electricity price information and the charging time.

In order to enable those skilled in the art to understand the purpose, features and effects of the present invention, the present invention will be described in detail below by means of the following specific embodiments and accompanying drawings.

100: Automatic scheduling system for charging progress

11: Charging module

12: Production module

13: Control module

200: Automatic guided vehicle

30:Battery information

31: remaining power

32: Electricity to be charged

33: Target power

34: Job information

35: Charging time

36: Charging benefits

37: Work Benefits

38: difference

39: Check the time

41: Charging upper limit

42: early departure value

43: Charging lower limit

44: The value that can be charged in advance

45: Charging needs

46:Battery life

51: Electricity price information

Fig. 1 is a schematic diagram of an automatic scheduling system for charging progress according to the present invention; Fig. 2 is a flow chart illustrating the actual execution process of the automatic scheduling system for charging progress according to the present invention; Fig. 3 is a diagram illustrating an automatic scheduling system for charging progress according to the present invention A block diagram of the actual execution process of the system; FIG. 4 is a schematic diagram of an automatic scheduling system for charging progress according to the first embodiment of the present invention; FIG. 5 is a flow chart illustrating the actual execution of charging rules according to the first embodiment of the present invention; FIG. 6 A block diagram illustrating the actual implementation of charging rules according to the first embodiment of the present invention; FIG. 7 is a flow chart illustrating the use of Markov decision-making process according to the first embodiment of the present invention; FIG. 8 is a charging progress according to the second embodiment of the present invention Schematic diagram of the automated scheduling system.

The inventive concept will now be explained more fully hereinafter with reference to the accompanying drawings, in which exemplary embodiments of the inventive concept are shown. Advantages and features of the inventive concept and methods for achieving it will be apparent below by referring to the exemplary embodiments described in more detail with reference to the accompanying drawings. It should be noted, however, that the inventive concept is not limited to the following exemplary embodiments, but can be implemented in various forms. Therefore, the exemplary embodiments are provided only to disclose the inventive concept and to make one skilled in the art understand the category of the inventive concept. In the drawings, the exemplary embodiments of the inventive concepts are not limited to the specific examples provided herein and are exaggerated for clarity.

The terminology used herein is for describing particular embodiments only and is not intended to be limiting of the invention. Unless the context clearly indicates otherwise, the terms "a" and "the" used herein It is intended to include plural forms as well. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.

Similarly, it should be understood that when the words "comprising" and "comprising" are used herein, it indicates the existence of the stated features, integers, steps, operations, elements, and/or components, but does not exclude one or more The presence or addition of other features, integers, steps, operations, elements, components, and/or groups thereof.

Furthermore, exemplary embodiments in the detailed description will be explained by means of cross-sectional views that are idealized exemplary views of the inventive concept. Accordingly, the shapes of the exemplary figures may be modified according to manufacturing techniques and/or allowable errors. Accordingly, exemplary embodiments of the inventive concepts are not limited to the specific shapes shown in the exemplary figures, but may include other shapes that may be produced according to manufacturing processes. Regions illustrated in the drawings have general characteristics and are used to illustrate specific shapes of elements. Accordingly, this should not be seen as limiting the scope of the inventive concept.

Additionally, exemplary embodiments are described herein with reference to cross-sectional and/or plan views, which are idealized exemplary illustrations. Accordingly, deviations from the illustrated shapes as a result, for example, of manufacturing techniques and/or tolerances are to be expected. Thus, example embodiments should not be construed as limited to the shapes of regions illustrated herein but are to include deviations in shapes that result, for example, from manufacturing. Thus, the regions shown in the figures are schematic and their shapes are not intended to illustrate the actual shape of a region of a device and are not intended to limit the scope of example embodiments.

Please refer to Figs. 1-3, Fig. 1 is a schematic diagram of the charging progress automatic scheduling system according to the present invention; Fig. 2 is a flow chart illustrating the actual execution process of the charging progress automatic scheduling system according to the present invention; Fig. 3 is an illustration A block diagram of the actual execution process of the charging schedule automatic scheduling system according to the present invention. As shown in FIG. 1 , the charging schedule automatic scheduling system 100 according to the present invention is applied to a plurality of automatic guided vehicles 200. The charging schedule automatic scheduling system 100 includes: a charging module 11, a production module 12, and a control Module 13.

Specifically, the charging module 11 according to the present invention is used for charging the automatic guided vehicles 200 and can receive the battery information 30 including the remaining power 31 of the automatic guided vehicles 200 . Specifically, in some embodiments, the charging module 11 can be contact charging, that is, all charging circuits need to use cables and charging contacts to connect the automatic guided vehicle 200 to the charging module 11, so that the automatic guided vehicle 200 can be directly connected to the charging module 11. The lead car 200 is charged. The advantage of contact charging is that it can provide a larger charging current to achieve fast charging. However, the disadvantage of contact charging is that it is not suitable for frequent random charging, and there are charging contacts The problem of wear and tear needs to be replaced regularly. At the same time, there are safety hazards such as sparks during the charging process, and it cannot work normally in low temperature, humid, flammable or explosive environments. Specifically, in some embodiments, the charging module 11 may be non-contact charging, and non-contact charging does not require additional cables to connect the automatic guided vehicle 200 to the charging module 11. The advantage is that the charging module 11 and the automatic The guided vehicle 200 can realize the advantage of no exposed conductive contacts. The wireless charging technology enables the electrical isolation between the charging module 11 and the automatic guided vehicle 200, eliminating the risk caused by the contact charging method, and greatly improving the charging module 11. safety and applicability. However, the disadvantages of non-contact charging are that the technical requirements are more complicated, and the implementation cost is higher. At the same time, the wireless charger with high wattage is bulky, which is not suitable for the automatic guided vehicle 200 .

Specifically, the production module 12 according to the present invention is used to generate the work information 34 of the automatic guided vehicles. In some embodiments, the work information 34 may be for material scheduling requirements on the production line process, and the work information 34 must be processed in real time through the automatic guided vehicle 200 to ensure that the production module 12 can continue to perform production work stably, so that if the automatic The inability of the guided vehicle 200 to process the work information 34 in real time will reduce the production capacity of the production module 12 and delay the follow-up process, thereby generating corresponding work benefits, but the present invention is not limited thereto.

Specifically, according to the control module 13 of the present invention, it can be a combination of software, hardware, and firmware, and the control module 13 can be used to control the charging module 11 for automatic guided vehicles. 200 charging sequence and release sequence are sorted. It should be further explained that the control module 13 can select more than one swarm intelligence grouping algorithm to realize artificial intelligence (artificial intelligence, AI), which can be but not limited to K-means cluster analysis (K-Means Clustering), ant colony Algorithm (Ant Colony Optimization, ACO), Particle Swarm Optimization (PSO), Bacterial Foraging Algorithm (BFO), Shuffled Frog Leaping Algorithm (SFLA) , artificial bee colony algorithm (Artificial Bee Colony, ABC) or a combination thereof, to perform data processing to evaluate the charging efficiency and working efficiency of the automatic guided vehicles 200 .

In order to further understand the structural features of the present invention, the use of technical means and the expected effects, the algorithm process of the control module 13 of the present invention is described, and it is believed that the present invention can be understood more deeply and specifically as follows. Description: Specifically, please refer to Fig. 2 and Fig. 3, first, when the remaining power 31 of the automatic guided vehicle 200 is lower than the charging power 32, the automatic guided vehicle 200 moves to the charging module 11 for charging, and the control The module 13 controls the charging module 11 to charge according to the target power 33 set by the automatic guided vehicle 200; after that, When a part of the automatic guided vehicle 200 moves to the charging module 11 for charging, if the control module 13 does not receive the work information 34 sent by the production module 12, the control module 13 will follow the target power set by the automatic guided vehicle 200 33 controls the charging module 11 to charge, and continuously detects whether the remaining power 31 of the automatic guided vehicle 200 is higher than the target power 33; otherwise, if the control module 13 receives the work information 34 sent by the production module 12, then control The module 13 generates the charging time 35 according to the charging rate of the charging module 11 and the current remaining power of the automatic guided vehicle 200. The control module 13 generates the charging benefit 36 of the automatic guided vehicle 200 according to the charging time 35 multiplied by the reward parameter. Charging time calculation The waiting time for the automatic guided vehicle 200 to resume work is multiplied by the penalty parameter to generate the working benefit 37 of the automatic guided vehicle 200, and the difference 38 is generated by subtracting the charging benefit 36 and the working benefit 37; among them, if the automatic If the remaining power 31 of the guided vehicle 200 is greater than the amount to be charged 32 and the difference 38 is less than zero, the control module 13 controls the charging module 11 to stop charging the automatic guided vehicle 200 , and transmits the work information 34 through the charging module 11 Send to the automatic guided vehicle 200.

It should be further explained that, please refer to FIG. 2 and FIG. 3 , if the difference 38 of the automatic guided vehicle 200 is greater than zero, the control module checks the time 39 at intervals and then again according to the charging rate of the charging module 11 and the automatic The remaining power 31 of the guidance vehicle 200 calculates the charging benefit 36 , working benefit 37 and difference 38 at the time point of the inspection time 39 .

It is worth mentioning that, in some embodiments, the control module 13 can independently set the charging power 32 and the target power 33 of the automatic guided vehicles 200 according to the current situation of the production line, or the control module 13 can use inspiration Formula algorithm, machine learning algorithm, or deep learning algorithm predicts the better charging power 32 and target power 33 of the automatic guided vehicle 200 according to the load capacity of the production module 12, so as to avoid production bottlenecks. Specifically, in some embodiments, the electric quantity 32 to be charged is less than 40% of the fully charged electric quantity (not shown) of the automatic guided vehicle 200, and the target electric quantity 33 is more than 80% of the fully charged electric quantity of the automatic guided vehicle 200, however The present invention is not limited thereto.

It is worth mentioning that, in some embodiments, the amount to be charged 32 can be further divided into a lower limit for charging and a value that can be charged in advance, and the target amount of electricity 33 can be further divided into an upper limit for charging and a value that can be left in advance. The guided vehicle 200 must go to the charging module 11 for charging under any circumstances. The advance charging value means that the automatic guided vehicle 200 can independently decide whether to continue charging through an algorithm according to the current situation of the production line. In addition, The charging upper limit means that the AGV 200 will leave the charging module 11 to end charging under any circumstances, and the early departure value means that the AGV 200 can independently decide whether to end charging through an algorithm according to the current situation of the production line. In this way, by further subdividing the electric quantity to be charged 32 and the target electric quantity 33, the present invention provides a specific and feasible The automatic charging schedule system 100 makes decisions independently through algorithms and implements them in detail, so as to achieve a very small amount of manpower control, effectively reduce manual operations between production chains, and increase overall production capacity. Specifically, in some embodiments, the charging lower limit may be that the remaining power of the automatic guided vehicle 200 is less than 20% of the full power, and the advance charging value may be that the remaining power of the automatic guided vehicle 200 is between 20% of the full power. % to 40%, the charging upper limit can be that the remaining power of the automatic guided vehicle 200 is higher than 95% of the full power, and the value that can be left early can be that the remaining power of the automatic guided vehicle 200 is between 80% and 80% of the full power. 95%, but the present invention is not limited thereto.

Therefore, it can be known from the above description that the charging progress automatic scheduling system 100 of the present invention adopts a dynamic calculation method, so that the charging module 11 can make real-time dynamic adjustments to the power supply according to changes in the current production situation, so as to arrange a schedule that meets the requirements of the site. The charging scheduling results of production demand, the charging scheduling results can enable both ends of production and charging management, in the case of seamless information integration, effectively reduce the demand for lack of materials between the production chains and improve the overall production capacity.

Hereinafter, with reference to the drawings, the first embodiment of the charging progress automatic scheduling system 100 of the present invention will be described, so that those skilled in the art of the present invention can understand possible changes more clearly. Components denoted by the same reference numerals as above are substantially the same as those described above with reference to FIGS. 1-3 . The same elements, features, and advantages as those of the charging schedule automatic scheduling system 100 will not be repeated here.

Please refer to Figs. 4-7, Fig. 4 is a schematic diagram of an automatic scheduling system for charging progress according to the first embodiment of the present invention; Figs. 5A-5C are flow charts illustrating the actual execution of charging rules according to the first embodiment of the present invention ; FIGS. 6A-6C are block diagrams illustrating the actual implementation of charging rules according to the first embodiment of the present invention; FIG. 7 is a flowchart illustrating the use of Markov decision-making process according to the first embodiment of the present invention. As shown in FIG. 4 , the charging progress automatic scheduling system 100 according to the first embodiment of the present invention includes: a charging module 11 , a production module 12 , a control module 13 , and a production line 14 .

Specifically, in this embodiment, the battery information 30 of the automatic guided vehicles 200 received by the charging module 11 may further include a battery life 46. The battery life 46 is used to indicate whether the batteries of the automatic guided vehicles 200 are new or old. And the battery life 46 is positively correlated with the charging efficiency, that is, when the battery life 46 is newer, the charging efficiency of the battery is better, on the contrary, when the battery life 46 is older, the charging efficiency of the battery is worse, thereby, the present invention The charging progress automatic scheduling system 100 further improves the utilization rate and charging efficiency of the automatic guided vehicle 200 by prioritizing the charging of the battery with a newer battery life 46 .

Specifically, in this embodiment, the production line 14 is coupled to the production module 12, and the production line 14 may further include a high degree of automation and a big data database, so as to transmit work through forecasting capacity demand The information 34 reaches the production module 12, and the movement of the automatic guided vehicle 200 satisfies the work information 34, realizes intelligent logistics, and achieves the goals of flexible production according to order demand and multiple products in a single production line.

It is worth mentioning that, in this embodiment, the information transmission between the control module 13 and the automatic guided vehicle 200 can be carried out through the Internet of Things (IoT), so that the control module 13 can further directly receive The battery information 30 of the automatic guided vehicle 200 can further automatically schedule the charging sequence of the automatic guided vehicle 200 based on the current battery information 30 of the automatic guided vehicle 200 , but the present invention is not limited thereto.

Specifically, please refer to FIG. 5A to FIG. 6C. In this embodiment, the control module 13 controls the charging module 11 to charge the automatic guided vehicle 200 according to the charging rules shown in FIG. 5A-5C, wherein, The charging rule can be mainly divided into three parts, namely generating charging demand, ending charging schedule, and charging sequence scheduling. It should be further explained that the generation of charging demand part of the charging rule mainly uses the automatic guided vehicle 200 to detect the remaining power 31 of its own battery information 30 to determine whether the automatic guided vehicle 200 has a charging demand 45; The end of the charging schedule part mainly uses the charging module 11 to receive the battery information 30 of the automatic guided vehicle 200 and the remaining power 31 to determine whether to control the charging module 11 to end the charging of the automatic guided vehicle 200 to release Part of the charging module 11 is used for the charging sequence scheduling part of the subsequent charging rule; the charging sequence scheduling part of the charging rule mainly receives the battery information 30 of the automatic guided vehicle 200 with the charging demand 45 through the control module 13 The remaining power 31 and battery life 46, together with the calculation of the current remaining charging module 11, generates the best charging sequence through the algorithm to establish the charging sequence schedule of the automatic guided vehicle 200, thereby improving the automatic guided vehicle The duty ratio is 200, but the present invention is not limited thereto.

Specifically, as shown in FIG. 5A and FIG. 6A , the automatic guided vehicle 200 executes the charging requirement part in the charging rule, and the automatic guided vehicle 200 confirms whether the remaining power 31 of its own battery information 30 is lower than the charging lower limit 43, and if so, Then the automatic guided vehicle 200 generates a charging demand 45 and moves to the charging module 11 for charging; otherwise, the automatic guided vehicle 200 further confirms whether the remaining power 31 of its own battery information 30 is lower than the chargeable value 44 in advance, and if so, Then the automatic guided vehicle 200 generates the charging demand 45 and moves to the charging module 11 for charging, wherein the automatic guided vehicle 200 with the charging demand 45 performs charging sequence scheduling in the charging sequence scheduling part of the subsequent charging rules.

Specifically, please refer to FIG. 5B and FIG. 6B , the control module 13 executes the end of the charging schedule part of the charging rule, the control module 13 receives the remaining power 31 of all automatic guided vehicles 200 in charging, and confirms the remaining Whether the electric quantity 31 exceeds the charging upper limit 41, if so, the control module 13 controls the charging module 11 to finish charging the automatic guided vehicle 200; otherwise, the control module 13 confirms that all the Whether the remaining power 31 of the automatic guided vehicle 200 exceeds the value 42 that can leave in advance, and the control module 13 further confirms whether to receive the work information 34 from the production module 12. If the work information 34 of the production module 12 is received at the same time and If the remaining power 31 of the automatic guided vehicle 200 exceeds the value 42 that can leave early, the charging of the automatic guided vehicle 200 will be stopped, and the working information 34 will be sent to the automatic guided vehicle 200 through the charging module 11; otherwise, the control module will 13 Repeat the end of the charging schedule part of the charging rule again after checking the time 39 at an interval. It is worth mentioning that when the charging module 11 finishes charging the automatic guided vehicle 200, the charging module 11 will release the automatic guided vehicle 200, which means that part of the charging module 11 will be released at the same time for subsequent charging rules. Partial use of charging sequence scheduling.

Specifically, as shown in FIG. 5C and FIG. 6C , the control module 13 executes the charging sequence scheduling part of the charging rule, and the control module 13 receives the remaining power 31 of the automatic guided vehicle 200 with a charging demand 45 at the moment, and confirms Those whose remaining power 31 is lower than the charging lower limit 43 are given priority to charging, and at the same time, the control module 13 sorts the charging sequence of the automatic guided vehicles 200 with charging requirements 45 according to the battery life 46, so that those with longer battery life are given priority to charging; The control module 13 confirms whether the remaining power 31 is lower than the charging lower limit 43. If all the automatic guided vehicles 200 whose remaining power 31 is lower than the charging lower limit 43 have been charged, there are still other charging modules 11 At this time, the control module 13 receives the remaining power 31 of the automatic guided vehicle 200 with the current charging demand 45, and confirms that the remaining power 31 is lower than the advance charge value 44. 46 Sort the charging order of the automatic guided vehicles 200 with the charging demand 45; if all the automatic guided vehicles 200 whose remaining power 31 is lower than the advance charging value 44 are all charged, there are still other charging modules 11 , the control module 13 confirms whether there is still an automatic guided vehicle 200 with the charging demand 45; finally, the control module 13 repeatedly executes the part of generating the charging demand in the charging rule.

In this way, the charging progress automatic scheduling system 100 of the first embodiment of the present invention, through the mutual matching of the generation charging demand part, the ending charging scheduling part, and the charging sequence scheduling part, according to the automatic guided vehicle 200 in different states The remaining power 31 provides an automatic charging schedule scheduling system 100 that can generate charging schedules and schedules through algorithms, so as to achieve the purpose of optimizing logistics operations in the field and improving operating efficiency and product quality.

Specifically, please refer to FIG. 7. In this embodiment, the control module 13 controls the charging module 11 to charge the automatic guided vehicle 200 according to the above-mentioned charging rules through a Markov decision process (Markov decision process, MDP). Scheduling and enabling autonomous decision-making capabilities. As shown in FIG. 7 , in this embodiment, I _t represents the automatic guided vehicle 200 that does not have the work information 34 and is parked in the standby area, and J _t represents the automatic guided vehicle 200 that is charging in the charging module 11 but has not yet been charged. Leading vehicle 200, L _t represents the automatic guided vehicle 200 with work information 34. Specifically, a certain state of each automatic guided vehicle 200 in the random process is represented by the following formula (1), wherein C _it represents the state of the automatic guided vehicle 200 in consideration of the I _t state or the J _t state The remaining power 31, BA _it represents the state considering the battery life 46 of the automatic guided vehicle 200. Specifically, with the following formula (2), where A _t represents a certain action that can be executed in a certain state, wherein the variable x _it represents that the control module 13 decides to give the automatic guided vehicle 200 in the state J _t The charging amount at that time, the variable y _it indicates whether the automatic guided vehicle 200 needs to be charged; wherein, when the variable y _it of the automatic guided vehicle 200 is 1, it indicates that the remaining power 31 of the automatic guided vehicle 200 is low At the charging lower limit 43 or the remaining power 31 of the AGV 200 is lower than the advance charging value 44, on the contrary, when the variable yit of the AGV 200 _is 0, it means that the remaining power 31 has exceeded the charging upper limit 41 or The remaining power 31 of the automatic guided vehicle 200 exceeds the early departure value 42, but the present invention is not limited thereto.

It should be further explained that, in order to ensure that the control module 13 controls the charging module 11 to schedule the charging of the automatic guided vehicle 200 according to the above-mentioned charging rules, the present invention further uses the variable p _it to indicate how much power the work information 34 needs to consume Carrying out, by comparing with the power of the automatic guided vehicle 200 at the moment, if C _it is greater than p _it, the automatic guided vehicle 200 can serve this demand, but the present invention is not limited thereto.

In order to further understand the structural features, technical means and expected effects of the present invention, the Markov decision-making process of the first embodiment of the present invention is described. It is believed that the present invention can be understood more deeply and specifically as follows. Description: Specifically, please refer to FIG. 7 , where J _t represents the automatic guided vehicle 200 that is being charged in the charging module 11 but not yet fully charged. When updating in the J _t state, the control module 13 uses the The following formula (3) judges whether the automatic guided vehicle 200 in the state of J _t is removed, and the formula (3) indicates that the remaining power 31 of the automatic guided vehicle 200 in the state of J _t has exceeded the charging limit 41 Or, under the premise of having the working information 34, the remaining power 31 of the automatic guided vehicle 200 in the J _t state exceeds the value 42 that can leave early, that is, the formula (3) will be in the J _t state. If the variable y _it of car 200 is 0, it is removed. Also, when updating in the J _t state, the _control module 13 judges whether the automatic guided vehicle 200 is converted to the J _t state by the following formula (4). If the remaining power 31 of the automatic guided vehicle 200 is lower than the charging lower limit 43, or if the remaining power 31 of the automatic guided vehicle 200 is lower than the chargeable value 44 in advance, it will be converted into a state of J _t , that is, the formula (4) will be in I When the variable y _it of the automatic guided vehicle 200 in the _t state is 1, the transition is made to the J _t state.

Specifically, please refer to Fig. 7, wherein, I _t represents the automatic guided vehicle 200 that does not have the work information 34 and is parked in the standby area. When updating in the I _t state, the control module 13 uses the following Formula (5) and formula (6) determine whether to remove the automatic guided vehicle 200 in the state of I _t , and formula (5) means to remove the remaining power 31 of the automatic guided vehicle 200 in the state of _It If the charging lower limit is 43 or is lower than the value 44 that can be charged in advance, the formula (6) means that the AGV 200 in the I _t state has working information 34 and the remaining power 31 exceeds (includes) the value 42 that can be left in advance (i.e. 20% BC _i ), that is, the formula (5) converts the qualified AGV 200 in the I _t state to the J _t state, and the formula (6) converts the qualified AGV 200 in the I _t state The lead car 200 is converted to the L _t state. Also, when updating in the I _t state, the control module 13 judges whether the automatic guided vehicle 200 is converted to the I _t state by the following formula (7) and formula (8), and the formula (7) means that it will be in The automatic guided vehicle 200 in the J _t state does not need to be charged and does not have the working information 34, and it is converted to the I _t state. The formula (8) means that the automatic guided vehicle 200 in the L _t state does not have the working information 34 Or, the remaining power 31 of the automatic guided vehicle 200 is less than the value 42 that can be left in advance and is converted to the state of I _t , that is, the formula (7) converts the qualified automatic guided vehicle 200 in the J _t state to the _It state , the formula (8) converts the qualified automatic guided vehicle 200 in the L _t state to the I _t state.

Specifically, please refer to FIG. 7 , where L _t represents the automatic guided vehicle 200 with the working information 34. When updating in the L _t state, the control module 13 judges that it is in the state according to the following formula (9). Whether the automatic guided vehicle 200 in the state of Lt is removed, the formula (9) means that the automatic guided vehicle 200 in the state of _Lt does not have the working information 34 or the remaining power 31 of the automatic guided vehicle 200 is less than possible If the departure value is 42 ahead of time, that is, the formula (9) converts the qualified automatic guided vehicle 200 in the L _t state to the I _t state. Also, when updating in the L _t state, the control module 13 judges whether the automatic guided vehicle 200 is converted to the L _t state by the following formula (10) and formula (11), and the formula (10) means that it will be in The automatic guided vehicle 200 in the J _t state does not need to be charged and has the working information 34 to switch to the L _t state. The formula (11) means that the automatic guided vehicle 200 in the _It state has the working information 34 and the remaining If the electric quantity exceeds (includes) the value of 42 that can leave in advance, it will be converted to the state of L _t , that is, the formula (10) will convert the qualified automatic guided vehicle 200 in the state of J _t into the state of L _t , and the formula (11) will A qualified AGV 200 in the I _t state transitions to the L _t state.

It should be further explained that in this embodiment, in order to ensure that the control module 13 controls the charging module 11 to schedule the charging of the automatic guided vehicle 200 according to the above-mentioned charging rules, the present invention further uses the following restriction formula (12 )-(20), so that the control module 13 can stably control the charging module 11, so as to dynamically adjust the power supply in real time according to the change of the current production situation. It can be understood that the formula (12) expresses that the number of automatic guided vehicles 200 that are limited to be charged by the charging module 11 must not exceed the number (C) of the charging module 11; The remaining quantity must be greater than (including) the _quantity of the automatic guided vehicle 200 that is in the It state and is about to be converted into the J _t state; formula (14) means that the remaining power 31 for the automatic guided vehicle 200 in the It state is lower than the charging If the lower limit is 43 or is lower than the chargeable value 44 in advance, the control module 13 will give priority to charging the remaining power 31 lower than the charging lower limit 43; the formula (15) means to limit when the remaining power 31 of the automatic guided vehicle 200 is too low can not receive the work information 34; the formula (16) means that the variable yit of the automatic guided vehicle 200 that is limited to charging in the charging module 11 but has not yet been charged is 0 or 1; the formula (17) means that the variable y _it is limited to the charging module 11. If the remaining power 31 of the automatic guided vehicle 200 charged exceeds the charging upper limit 41, the charging ends; the formula (18) means that the remaining power of the automatic guided vehicle 200 limited to the charging module 11 has the working information 34 31 Those who exceed the value that can be left in advance and 42 end charging.

It is worth mentioning that in this embodiment, the control module 13 uses the following formulas (19) and (20) to perform weighted calculations using the arithmetic sequence and the geometric sequence, respectively, so as to ensure that the charging module 11 is charged but not Among the automatic guided vehicles 200 that have not been fully charged, the control module 13 gives priority to the one with the higher remaining power 31. If the remaining power 31 of the automatic guided vehicles 200 is the same, the control module 13 gives priority to the one with the longer battery life 46. to charge. Specifically, the formula (19) expresses the battery life 46 of the automatic guided vehicle 200 through the arithmetic sequence arrangement. In this embodiment, θ1 is _0.1 as the tolerance value of the arithmetic sequence, and the battery life 46 is divided into AGVs are divided into 200 groups (for example: 1,...,BN _t ), among them, those with a longer battery life of 46 have a larger tolerance value for weighted calculation, and those with a shorter battery life of 46 have a smaller tolerance value for weighted calculation , the control module 13 calculates the formula (19) to give priority to charging the one with the larger value, so as to realize the priority to charge the battery with a longer service life 46, so that the charging progress automatic scheduling system 100 of the present invention can have better charging efficiency, Increased utilization rate of AGV 200. Specifically, the formula (20) represents the remaining power 31 of the automatic guided vehicle 200 through the geometric sequence arrangement. In this embodiment, _θ2 is 0.9 as the common ratio of the geometric sequence, and according to the remaining power 31 will automatically 200 guided vehicles are divided into groups (for example: 1,...,DN _t ), those with more remaining power 31 have a larger tolerance value for weighted calculation, and those with less remaining power 31 have a smaller tolerance value for weighted calculation, control The module 13 calculates the larger value of the formula (20) to give priority to charging, and realizes to give priority to charging the one with a higher remaining power 31, so that the charging progress automatic scheduling system 100 of the present invention can have better charging efficiency, and further Increased utilization rate of AGV 200.

It is worth mentioning that, in this embodiment, the control module 13 further optimizes the calculation of the difference 38 to form a reward function, and uses the following formula (21) as the reward function to calculate the charging progress of the automatic scheduling system 100 according to the current production The remuneration generated by the change of the current situation is used as the basis for the automatic charging progress scheduling system 100 to realize artificial intelligence, wherein the remuneration function includes calculating the charging upper limit 41 as the charging time of 95% of the full charge (i.e. Ti (95%) minus Multiply the time saved by the charging time of the charging upper limit 41 generated by the current automatic scheduling system 100 according to the current production status (ie Ti(ci _(t+1) /BC _i )) by the estimated production value saved per minute ( That is, R), multiplied by the judgment formula of the binary function b of the variable p _it (namely b(p _it )), to ensure that the automatic guided vehicle 200 provides service production needs in advance, and then multiplied by the judgment of the variable y _it Formula, to ensure that the automatic guided vehicle 200 on the charging module 11 will stop charging, and add up to calculate the output value provided by the current continuous charging, wherein the output value is equivalent to the reward parameter described in the present invention. In addition, the reward function includes calculation All the AGVs 200 that are currently being charged by the charging module 11 but have not yet been fully charged and have the work information 34 to continue charging are multiplied by the estimated cost per minute (i.e. P), and summed up to calculate the current cost of continuing to charge The resulting cost, where the cost corresponds to the penalty parameter described in the present invention. In this way, the control module 13 can find a better value through the calculation of the reward function, so as to enhance the accuracy and flexibility of the automatic scheduling system 100, so that the charging module 11 can immediately make power supply according to the current production status. Dynamically adjust to arrange charging scheduling results that meet on-site production needs.

In this way, the automatic scheduling system 100 of the present invention realizes a calculation of the output value provided by continuing charging based on the remaining power 31 of the automatic guided vehicle 200 through the Markov decision process and the above-mentioned formulas (1)-(21). Time calculation calculates the cost of continuing to charge at present, and makes real-time judgments through algorithms to generate the charging schedule of automatic guided vehicles. This system is equipped with industrial wireless transmission equipment to transmit the work information of each production line in real time34, successfully realizing a The automatic guided vehicle 200 monitoring and dispatching system solution helps enterprises to create benefits such as smart manufacturing.

Other examples of the automatic scheduling system 100 are provided below, so that those skilled in the art of the present invention can understand possible variations more clearly. Components denoted by the same reference numerals as in the above embodiment are substantially the same as those described above with reference to FIG. 1 and FIG. 2 . The same elements, features, and advantages as those of the automatic scheduling system 100 will not be repeated.

Please refer to FIG. 8 , which is a schematic diagram of an automatic scheduling system for charging progress according to a second embodiment of the present invention. As shown in FIG. 8 , the charging schedule automatic scheduling system 100 according to the first embodiment of the present invention includes: a charging module 11 , a production module 12 , a control module 13 , a production line 14 , and an electricity price module 15 .

Specifically, the main difference between the second embodiment of the present invention and the first embodiment is that the charging progress automatic scheduling system 100 of the second embodiment further includes an electricity price module 15, which is coupled to the control module 11, and the electricity price The module 15 transmits the electricity price information 51 to the control module 13. The electricity price information 51 changes with time, and the control module 13 further optimizes the calculation of the difference 38 according to the electricity price information 51 to form a reward function.

Specifically, in this embodiment, the following formula (22) is used as the reward function to calculate the reward generated by the charging automatic scheduling system 100 according to the change of the current production status, so as to be realized as the charging automatic scheduling system 100 The basis for artificial intelligence. Compared with the reward function of the first embodiment, the reward function of the second embodiment further includes calculating how much electricity (ie x _it ) the automatic guided vehicle 200 that is currently being charged in the charging module 11 but not yet fully charged is charged at the moment Multiply the electricity price information 51 (ie σ _t ), and add up to calculate the charging cost t generated by continuing charging at the moment. In this way, the control module 13 can further calculate the reward function through the electricity price information 51 to find a better value, further enhance the accuracy of the automatic scheduling system 100, so that the charging module 11 can change according to the current electricity price information 51 over time, Real-time power supply dynamic adjustments are made to arrange charging scheduling results that meet economic benefits and production needs.

Hereby, the features of the present invention and the expected effect that can be achieved are stated as follows:

First, the automatic charging schedule system 100 of the present invention adopts a dynamic calculation method, so that the charging module 11 can make real-time dynamic adjustments to the power supply according to changes in the current production situation, so as to arrange charging schedules that meet the needs of on-site production. The results of the charging schedule can allow both ends of production and charging management to effectively reduce the shortage of materials between the production chains and increase the overall production capacity under the condition of seamless information integration.

Second, the charging progress automatic scheduling system 100 of the present invention, through the mutual matching of the generation charging demand part, the end charging scheduling part, and the charging sequence scheduling part, according to the remaining power 31 of the automatic guided vehicle 200 in different states , providing an automatic charging schedule scheduling system 100 that can generate charging schedules and schedules through algorithms, so as to achieve the purpose of optimizing logistics operations in the field and improving operational efficiency.

Third, the automatic scheduling system 100 of the present invention uses the Markov decision process and the above-mentioned formulas (1)-(21) to realize a calculation of the output value provided by continuing charging based on the remaining power 31 of the automatic guided vehicle 200, and at the same time according to the charging Time calculation calculates the cost of continuing charging at the moment, and makes real-time judgments through the algorithm to generate the charging progress schedule of the automatic guided vehicle. This system is equipped with industrial wireless transmission equipment to transmit the work information of each production line in real time34, successfully realizing automatic The guided vehicle 200 monitoring and dispatching system solution assists enterprises in creating benefits such as smart manufacturing.

Fourth, according to the second embodiment of the present invention, the charging control module 13 can further calculate the reward function through the electricity price information 51 to find a better value, and further strengthen the accuracy of the automatic scheduling system 100, so that the charging module 11 can be based on the current After the electricity price information 51 changes over time, dynamic power supply adjustments are made in real time, so as to arrange charging scheduling results that meet economic benefits and production needs.

The above is to illustrate the implementation of the present invention through specific specific examples. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the scope of the present invention; all other equivalent changes or modifications that do not deviate from the spirit disclosed in the present invention should be included in the scope of the following patents Inside.

100: Automatic scheduling system for charging progress

11: Charging module

12: Production module

13: Control module

200: Automatic guided vehicle

30:Battery information

34: Job information

Claims (8)

An automatic scheduling system for charging progress, which is applied to a plurality of automatic guided vehicles, the automatic scheduling system for charging progress includes: A plurality of charging modules, which are used to charge the automatic guided vehicles and can receive battery information of the automatic guided vehicles including a remaining power; A production module, which is used to generate the operation information of the automatic guided vehicles; and A control module, which is coupled to the charging modules and the production module, the control module receives the battery information of the automatic guided vehicles including the remaining power; Wherein, when the remaining electric quantity of the automatic guided vehicle is lower than a chargeable electric quantity, the automatic guided vehicle moves to the charging module for charging, and the control module controls according to a target electric quantity set by the automatic guided vehicle When the charging module is charging, when the control module receives the work information of the automatic guided vehicle sent by the production module, the control module according to the charging rate of the charging module and the remaining Calculation of electric quantity: From the time point of receiving the work information to the charging time required for the automatic guided vehicle to charge to the target electric quantity multiplied by a reward parameter to generate the charging benefit of the automatic guided vehicle, the automatic guided vehicle is calculated according to the charging time The waiting time for the guided vehicle to return to work is multiplied by a penalty parameter to generate a working benefit of the automatic guided vehicle, and the control module generates a difference by subtracting the charging benefit from the working benefit; if the automatic guided vehicle If the remaining power is greater than the chargeable power and the difference is less than zero, the control module controls the charging module to stop charging the automatic guided vehicle, and transmits the working information to the automatic guided vehicle through the charging module . The charging progress automatic scheduling system as claimed in item 1, wherein the chargeable electric quantity is less than 40% of the fully charged electric quantity of one of the automatic guided vehicles. The charging progress automatic scheduling system of claim item 2, wherein the charging sequence of the automatic guided vehicle whose remaining power is less than 20% of the full power is prior to the automatic guided vehicle whose remaining power is between the full 20% to 40% of the charge sequence. The charging progress automatic scheduling system of claim item 1, wherein the target electric quantity is more than 80% of the full electric quantity of the automatic guided vehicle. The charging progress automatic scheduling system of claim item 4, wherein, the charging stop when the remaining power of the automatic guided vehicle is greater than 95% of the full power is prioritized before the remaining power of the automatic guided vehicle is between the full power 80% to 95% of the electricity stop charging sequence. If the charging progress automatic scheduling system of claim item 1, wherein the battery information includes a battery life, when the remaining power of two or more of the automatic guided vehicles is lower than the charging power, the control module is based on The battery with the lower remaining power is charged first; if the two remaining powers are the same, the control module gives priority to charging the battery with the longer service life. The charging progress automatic scheduling system as claimed in item 1, wherein, if the difference of the automatic guided vehicle is greater than zero, the control module checks the interval according to the charging rate of the charging module and the automatic guided vehicle Calculate the charging benefit, the working benefit and the difference at the time point of the check time based on the remaining power. For example, the charging progress automatic scheduling system of claim 1 further includes: An electricity price module, which is coupled to the control module, the electricity price module transmits an electricity price information to the control module, and the electricity price information changes with time; Wherein, the control module further generates the charging benefit according to the electricity price information and the charging time.

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