JPH0524067B2 - - Google Patents

Description

[Detailed description of the invention]

[Field of Application of the Invention] The present invention relates to an elevator group management control device,
In particular, the present invention relates to a device suitable for elevator group management and control using a computer. [Background of the Invention] Recently, microcomputers (hereinafter referred to as microcomputers) have been applied to various industries, and in the field of elevators, they have been used as group management control devices to efficiently manage multiple elevators, and to control individual elevators. It is applied to the unit control equipment. These efforts have made a significant contribution to elevator control equipment due to microcontrollers' small size, high functionality, high reliability, and low cost. For example, in the case of group management control, it is possible to monitor each hall call that occurs online, take into account the service status of all hall calls, and select and allocate the most suitable elevator, which greatly reduces waiting time. Contributing. In addition, it has become possible to perform priority service control, such as having multiple elevators serve a hall with a large number of passengers, or having elevators with short waiting times serve executive floors, making it possible to perform fine-grained control. ing. On the other hand, when allocating elevator calls, an evaluation function was calculated that took into account the service status of the entire building, and the elevator with the minimum (or maximum) evaluation function value was selected. In addition, several driving methods have been proposed that not only improve service performance for passengers but also save energy. The main call allocation methods that have been proposed so far are shown below. (1) Allocate the call to the elevator with the minimum expected waiting time. (2) Find the maximum value of the predicted waiting time of the assigned call for each elevator, and allocate the newly generated call to the elevator with the minimum value (see Japanese Patent Publication No. 47110/1983). (3) The deviation value of the predicted waiting time of a call from a predetermined standard waiting time is used as the evaluation value of the call, and a newly generated call is assigned to the elevator with the minimum value (see Japanese Patent Publication No. 55-21709). (4) Allocate the hall call that has occurred to the elevator that has the smallest sum or square sum of predicted waiting times assuming that it services all hall calls, or the elevator that has the smallest increment in the sum of the sums of all elevators. The basic call assignment method shown above does not include the positional relationship between elevators, so if left as is, all methods will result in dangling operation.
Service is not the best. Therefore, the concept of a stop-call evaluation function has been proposed (Japanese Patent Application Laid-Open No. 1983-1999-
47249, JP-A-52-12684). That is, the service evaluation value is calculated by considering the allocated hall calls and car calls of the elevator of interest starting from the floor closest to the generated call (by setting a weighted coefficient), thereby eliminating the sluggish operation. Furthermore, in order to set the weighting coefficient to the best value according to traffic demand, an improvement plan has been proposed in which a simulation function is provided to obtain the best weighting parameter (Japanese Patent Application No. 158739/1982). As described above, the use of computers such as microcomputers has led to significant improvements in performance and functionality compared to random logic configurations. However, each of the above-mentioned various call allocation systems has advantages and disadvantages, and the difference in performance changes depending on traffic demand. However, with conventional elevator group management control systems, operation is controlled using a fixed call assignment control method determined in advance, so the system is not necessarily adapted to the ever-changing building environment. . [Object of the Invention] The present invention has been made in view of the above, and its purpose is to provide an elevator group management control system that can efficiently and smoothly generate an optimal group management operation control program and has good responsiveness. It is about providing. [Summary of the Invention] The present invention is characterized by: a means for selecting an elevator to service a hall call according to an evaluation function having a plurality of variable parameters; a simulating means for simulating group management control; a first calculation means that simulates based on one variable parameter and calculates an optimal first parameter; and the optimal first parameter and second variable parameter calculated by the first calculation means. and second calculation means for calculating optimal second parameters by simulating with the simulation means based on The plurality of variable parameters include weighted coefficient parameters constituting the evaluation function, and the plurality of variable parameters are set in advance. The present invention is configured to include an evaluation function selection parameter for selecting one of a plurality of evaluation functions. [Embodiment of the Invention] Hereinafter, the present invention will be explained in detail with reference to a specific embodiment shown in FIGS. 1 to 16. In the description of the embodiment, first, the hardware configuration for realizing the present invention will be described, then the overall software configuration and its control concept will be described, and finally, a flowchart for realizing the above control concept will be explained. FIG. 1 shows the overall hardware configuration of an embodiment of the present invention. The elevator group management control device MA includes a microcomputer M1 that controls elevator operation and a microcomputer M2 that controls simulation.
Between 1 and M2 is a serial communication processor SDA _C.
Data is communicated via communication line _CMC . In addition,
Detailed configuration and operation explanation regarding this _SDAC are disclosed in Japanese Patent Laid-Open No. 56-37972 and Japanese Patent Laid-Open No. 56-37973. In addition, in this embodiment, the microcomputer M2
is also used, but it can also be configured entirely with the microcontroller M1. A call signal HC from a hall call device HD is connected to the microcomputer M1 that controls elevator operation via a parallel input/output circuit PIA.
The microcomputers E ₁ to _{E o} (here, it is assumed that there is elevator number n) that control individual elevators, such as door opening/closing and car acceleration/deceleration commands, are serial communication processors SDA ₁ similar to those described above. ~
It is connected to SDA _o via communication lines CM ₁ to _{CM o} . On the other hand, the microcomputer M2 receives a signal PM from the power saving target setter PD, which provides information necessary for determining the optimum operation control parameters for the simulation, through the parallel input/output circuit PIA. In addition, the control input/output elements EIO ₁ to EIO _o , which are composed of car call information necessary for control, various elevator safety limit switches, relays, and response lamps, are connected to the communication line SIO to the microcontrollers E ₁ to E _o for controlling the units. ₁
~Connected via SIO _o . Figure 2 is an overall configuration diagram of the software.
Software can be broadly divided into operation control software
It consists of SF1 and learning software SF2. The operation control system software SF1 consists of an operation control program SF14 that directly commands and controls elevator group management control such as call assignment processing and elevator distributed standby processing. Elevator control data table SF1 including elevator position, direction, car call, etc. sent from
1. Hall call table SF12, elevator specification table SF1 for managing number of elevators, etc.
3 and the learning software SF2,
There is data such as the output optimal operation method, selection parameters, and call assignment control parameters. On the other hand, the learning software SF2 is composed of the following processing programs. (1) Elevator usage information collection program SF2
0 This is a program that samples the number of people getting on and off, hall calls, and the contents of elevator control data tables SF12 and 11 online at regular intervals, and collects data for selection of call allocation method and simulation. Mainly collect. (2) Traffic demand learning calculation program SF22 This calculates traffic demand data by taking into account the contents of the online sampling data in the sampling data table SF21 collected by the elevator usage information collection program SF20 and the contents in past time periods. The result is a transportation demand data table
Output to SF23. (3) Traffic demand classification program SF24 This inputs the preceding traffic demand and time information obtained from the traffic demand data table SF23, and calculates the traffic volume in the building for work, before lunch, during lunch, after lunch, normal, and normal. This is a program that divides traffic demand into traffic demands that have characteristics that affect the operational control efficiency of elevator group management, such as congestion, clock-out, and closure.The results are shown in the traffic demand classification table SF2.
Output to 5. (4) Driving program generation system SF3 This is a configuration that combines the individual functions of items (5) to (8) explained below, and the driving program generation system SF3 as a whole can be used to respond to traffic demand with certain characteristics. Generate an optimal driving program. Note that Table 1 shows a list of the types of various operation control parameters output by the operation program generation system SF3 and their calculation methods.

[Table] (5) Simulation execution management program SF2
6 This inputs the contents of the traffic demand data table SF23, the traffic demand classification table SF25, and the elevator specification table SF27, executes the simulation, and outputs the result to the statistical processing data table SF28 based on the simulation. In addition, this program does not rely on simulation, but directly selects parameters from the data in the traffic demand classification table SF25, which is classified by characteristics, or calculates a predetermined function value from data such as traffic demand and past average waiting time. It is also possible to have a configuration in which (6) Various curve calculation program SF29 using simulation This program inputs the contents of statistical processing data table SF28 using simulation, performs simulation for each predetermined plurality of parameters, calculates various curves, and displays the results in various curve data tables. Output to SF30. The various curve data table SF30 includes, for example, an average hall call duration (or average waiting time) curve table,
There are power consumption curve tables, long waiting probability curve tables, first-come-first-served rate curve tables, etc. (7) Calculation program for optimal operation control parameters
SF31 This is a power saving target value table SF3 set by various curve data tables SF30 and an external target setting device PD (see Figure 1).
2 is input, the optimum group management operation control parameter corresponding to the power saving request is calculated, and the optimum operation control parameter SF33 is output. In addition,
If there is no power saving request, the system outputs group management operation control parameters that are optimal for the characteristics of traffic demand.
It is also possible to input target values for the first-come-first-served rate and the probability of long waiting. (8) Statistical processing calculation program SF34 This is a statistical processing calculation program that performs calculations such as stop probability and fullness prediction from the contents of statistical processing data table SF28 by simulation and creates a statistical table.
Output to SF35. An embodiment of the overall software configuration of the present invention has been described above. Next, a method of calculating various parameters forming the optimum operation control program SF14 by simulation will be explained. First, a general explanation of the main terms used in the following explanation will be given. (b) Power consumption (E _P ) Refers to the power consumed by the entire group control elevator during a specified period. Here, the estimated power consumption value is calculated by calculating the number of times the elevator is activated, the running time, and the average number of passengers in the car for each direction of operation, as well as the car light lighting time and elevator drive preparation circuit energization time by simulation. (b) Service index ( _FT ) This is an index for evaluating the service performance of the elevator group management system. For this purpose,
The average waiting time has generally been used, but since it is not possible to measure the average waiting time in actual operating conditions, we use the hall call duration time (the waiting time for the first arriving passenger) to manage the simulation results and the actual service results. This enables manual verification and automatic correction of various simulation constants. Note that when using the long-lasting rate instead of the average as the target value for energy-saving control, this index is also used as the long-lasting rate. (c) Operation method parameter This is a parameter that specifies the operation method of the group control elevator itself. For example, it is used to determine by simulation whether split express operation is necessary when the traffic volume is extremely large (at work or lunch time). There is a method in which the main parameter is the number of groups to be divided, and the sub-parameters are the divided floors and the number of elevators for each divided group. Here, it is applied to the case of skip service, which is particularly suitable when an elevator hall and stairs are arranged side by side. This method shortens the average elevator time for one revolution by thinning out service floors, improving passenger transportation capacity and shortening waiting time (Japanese Patent Application No. 136234/1986). reference). (d) Call assignment method parameters There are various call assignment methods (call assignment algorithms) for group-controlled elevators, but the basic method is shown in Figure 3. Each call assignment method has its advantages and disadvantages, and the evaluation (simulation results) varies depending on traffic demand (including not only traffic volume but also the flow of people between floors). Therefore, it is necessary to select the optimal call allocation method based on traffic demand and target values using indicators such as the power saving rate, long waiting rate, and average waiting time required by the purpose and environment of the building. Furthermore, it is necessary to generate an optimal call allocation program by combining a plurality of call allocation methods according to weighted coefficients. This weighted coefficient (or selection signal) is called a call allocation method parameter. (E) Allocation Suppression Parameter When allocating hall calls, elevators that are in a state of suspension or are likely to be suspended (no assigned hall calls) and elevators that are in a state of continuing service (with assigned hall calls) In some cases, the overall evaluation of call allocation is a coefficient that suppresses the allocation of new hall calls to elevators whose service is interrupted because priority is given to elevators whose service continues. Used for function calculations. This is effective for energy saving control, etc., but is also useful for optimal service control. (f) Area priority parameter In order to prevent dangling operation due to inconvenient operation when allocating hall calls, the concept of a stop call evaluation function has been proposed (Japanese Patent Laid-Open Nos. 52-47249 and 126845). (see publication). In other words, the area priority (stop call) evaluation function T _C is calculated by considering the allocated hall calls and car calls that exist on the floors adjacent to the generated hall call (within the area specified by this parameter). Priority allocation is performed according to the size of the value. Next, an overview of area priority parameter calculation will be described as an example of optimum parameter calculation using simulation. As a recent call allocation method, a hall call allocation method is used in which the service status (waiting time) of each hall call is monitored, the service of the entire call is taken into consideration, and the generated hall calls are allocated to elevators. In this method, waiting time is used as an evaluation function for call assignment (the main types of assignment methods are shown in FIG. 3). For example, the method is to use the longest waiting time of the allocated hall call on the floor in front of the generated hall call as the evaluation value, and as a variation of the method, the sum of the squares of the waiting time of the allocated hall call in the front floor There is a method of using this as the evaluation value. In addition, the method uses the waiting time of generated hall calls as an evaluation value, and the method uses a reference time (T _n ) parameter to improve performance when the traffic volume of the method increases (especially when the number of hall calls is large). This is what I used. In addition, the method uses the average waiting time of each elevator as an evaluation value in order to optimize the average waiting time. Other call assignment methods have also been devised that aim to minimize service completion time. However, since these evaluation values do not include the space between the positions of the elevators, if left as is, the elevators will run in a dangling manner, and no improvement in performance can be expected. Therefore, in order to prevent the dangling operation, the concept of a stop call evaluation function as shown in FIG. 4 has been proposed (see Japanese Patent Laid-Open No. 52-47249 and Japanese Patent Laid-open No. 52-126845). That is, the stopped call evaluation value T _A is obtained by taking into account the hall call HC _{i -1} and car calls CC _i and CC _i+2 of the elevator E that has been allocated from the floors adjacent to the generated hall call HC i, and this A new evaluation function φ is created that takes into account T _A and the evaluation value of the waiting time. Expressing this in a formula, when the waiting time evaluation value is T, and the weighting coefficient between the waiting time evaluation value T and the stop call evaluation value T _A is α, φ=T−αT _A ...(1) T _A =ΣαS...(2). Here, T〓 is a weighting coefficient for a stop call (referring to a call to be serviced) on an adjacent floor to the generated hall call, and is, for example, 0 to 20. Also, S is
Indicates outage probability and indicates if there are any calls to service.
1.0, and if there is a predicted call, an appropriate value (0
S1). FIG. 4 shows values that ignore predicted calls. By using the evaluation function of equation (1), the adjacent stop calls of the generated hall call are taken into account and the elevator is prevented from running in a dangling manner. In addition, the stop call evaluation value T _A in the example of Fig. 4 is calculated by considering the two floors before and after the generated call floor i, as follows: T _A =ΣT〓S=5×1.0+10×0+20×1.0 +10×1.0+5× 0=35 (seconds). Therefore, assuming that the waiting time evaluation value T is the same for each elevator, the elevator with a larger T _A will be determined to be optimal, and the generated hall call will be assigned to that elevator. Now, in equation (1), if we pay attention to the weighting coefficient α between the waiting time evaluation value T and the stop call evaluation value T _A , there is a value for this α that is most effective in preventing reckless driving; The waiting time (average waiting time) can be minimal. On the other hand, as α increases, elevators with many stop calls are preferentially selected, so it can be seen that the load is concentrated on a certain elevator and the average waiting time increases. Conversely, since the load on other elevators is lighter, the number of times the elevator stops (starts) as a whole decreases, and power consumption decreases. An example of the above relationship is shown in Table 2 and FIG. 6. This is an example of a simulation under the conditions of a building with 13 floors, 6 elevators, and an elevator speed of 150 m/min. Here, the weighting coefficient α is called the area priority parameter, and α=0,
We are conducting simulations for five cases: 1, 2, 3, and 4.

〔Effect of the invention〕

As explained above, according to the present invention, an optimal group management operation control program can be efficiently and smoothly generated, the responsiveness is good, and moreover, the effect is that it greatly contributes to shortening the average waiting time and reducing power consumption. There is.

[Brief explanation of drawings]

FIG. 1 is an overall hardware configuration diagram showing an embodiment of the elevator group management control device of the present invention;
Fig. 2 is an overall configuration diagram showing one embodiment of the software of the elevator group management control device of the present invention, Fig. 3 is a diagram for explaining the types of call assignment methods, and Fig. 4 is an illustration of the area priority control. Fig. 5 to Fig. 8 are explanatory diagrams of performance evaluation curves showing the relationships between various parameters and waiting time, power consumption, and probability of occurrence of long waiting. Fig. 9 is an explanatory diagram of the evaluation function of Fig. 2. Operation control system software table configuration diagram, No. 10
The figure is a flowchart showing an example of a program for calculating the predicted arrival time of the operation control program shown in Fig. 2, Fig. 11 is a flowchart showing an example of the call assignment program, and Fig. 12 is a flowchart showing an example of the program for calculating the predicted arrival time of the operation control program shown in Fig. 11. Flowchart of processing at step H50,
FIG. 13 is a flowchart of the process at step H516 in FIG. 12, FIG. 14 is a table configuration diagram of the learning software in FIG.
FIG. 16 is a flowchart showing an embodiment of the simulation execution management program shown in the figure. FIG. 16 is a processing flowchart at step SC30 in FIG. MA...Elevator group management control device, HD...
...Hall calling device, M1...Microcomputer for elevator group management operation control, M2...Microcomputer for simulation, _E1 to E _o ...Microcomputer for controlling machine numbers,
PD...Goal setting device.

Claims (1)

[Scope of Claims] 1. A plurality of elevators operating between multiple floors, a hall call device provided on each floor for calling the elevators, and a hall call device provided in an elevator cage for indicating the preceding floor. and a group management control device that allocates a hall call to a selected one of the plurality of elevators, the group management control device comprising: a car call device and assigning a hall call to a selected one of the plurality of elevators; a means for simulating group management control; a first calculating means for simulating based on a first variable parameter by the simulating means to calculate an optimal first parameter; a second calculation means for calculating an optimal second parameter by simulating with the simulation means based on the optimal first parameter and second variable parameter calculated by the calculation means; The plurality of variable parameters include a call allocation method weighting parameter in an evaluation function that calculates a comprehensive evaluation value from evaluation function values of a plurality of preset call allocation methods, and the plurality of variable parameters constitute the evaluation function. An elevator group management control device comprising a weighted coefficient parameter, and further comprising an evaluation function selection parameter for selecting one of a plurality of preset evaluation functions. 2. The evaluation function is a function of the waiting time for a hall call and the power consumption required to service the hall call, and the coefficient parameter is a weighting coefficient between the waiting time and the power consumption. The elevator group management control device according to item 1. 3. The evaluation function selected by the evaluation function selection parameter includes at least an evaluation function using waiting time for an already allocated hall call, and other evaluation functions. Device. 4. The simulating means includes a simulator equivalent to the means for selecting the elevator, and is configured to at least calculate specific parameters obtained as a result of inputting and simulating the position information and call information of the elevator. An elevator group management control device according to claim 1. 5. The simulation means includes means for setting a control target value, and is configured to calculate a specific parameter by comparing the simulation result and the control target value. group management control device for elevators. 6. The simulation means includes at least a data collection means for collecting group management control information for a predetermined period of time, a means for calculating simulation data from this collected data, and a means for simulating group management control of the plurality of elevators from this simulation data. An elevator group management control device according to claim 1, comprising: means. 7. The simulation means includes a simulator equivalent to the evaluation function having the variable parameters, creates a performance curve from the results of multiple simulations obtained by sequentially switching the variable parameters, and determines the optimal parameters from this performance curve. An elevator group management control device according to claim 1, which is configured to calculate.