JPS6031482A - Elevator group management control device - Google Patents

Abstract

(57) [Summary] This bulletin contains application data before electronic filing, so abstract data is not recorded.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Use and Application of the Invention] The present invention relates to a group management and control system for elevators, and more particularly to a device suitable for group management and control of elevators using a computer.

[Background of the invention]

When a large number of traffic demands occur in an FPr that has cafeterias, restaurants, conference rooms, etc., a single Nirebake will be full or left unloaded, causing a decline in service.

Conventionally, as a countermeasure against this, a predetermined tF! There are methods to allocate two elevators to a hall call immediately after a full car occurs on the fth floor, a method to automatically register a hall call when a full car occurs, or a method to stop all elevators scheduled to pass through a crowded floor. Proposed.

However, all of these methods detect congestion after it has occurred and perform all congestion response controls, so they are not always timely, and by the time the congestion response function is activated, the congestion has already resolved. Sometimes there are.

On the other hand, increasing the sensitivity of congestion detection, i.e., detecting it early, may cause false detections and cause congestion response control to be performed even when there is no true congestion.

In addition, conventionally, congestion response control is often performed based on whether traffic demand exceeds a predetermined value or when the floor is full, without taking into account the overall congestion level of the floor.
In most cases, one predetermined corresponding control is usually commanded.

[Purpose of the invention]

SUMMARY OF THE INVENTION An object of the present invention is to provide an elevator group management control system that eliminates the above-mentioned drawbacks of the prior art and is capable of performing congestion handling control that is suitable for the current usage status of the elevator.

[Summary of the invention]

In order to achieve this object, the present invention includes a means for detecting elevator usage information, a means for collecting all the elevator publication information detected by the detecting means, a plurality of congestion response control means, The present invention is characterized by comprising at least means for selecting any one of the plurality of congestion handling control means according to the elevator usage information collected by the collection means.

[Embodiments of the invention]

Hereinafter, the present invention will be explained in detail with reference to a specific embodiment shown in FIGS. 1 to 15. The explanation of the embodiment will first describe the software configuration that embodies the present invention, then describe the overall software configuration and its control concept, and finally describe a flowchart for realizing the above control concept. I will explain.

FIG. 1 shows the overall hardware configuration of an embodiment of the present invention.

The elevator group management control device fly M A K has a microcomputer Ml that controls elevator operation control and a microcomputer M2 that controls simulation, and a serial communication processor 5DAc connects the microcomputers M1 and M2 via a communication line CMc. Data is communicated. The detailed configuration and operation description of this serial communication processor SDA is provided in Japanese Patent Application Laid-Open No. 1986-
No. 37972 and JP-A-56-37973. Further, although the microcomputer M2 is used in this embodiment, it is not necessarily necessary.

The microcomputer M1 that controls elevator operation receives a call signal HC7 from the hall call device HD! 1'' - connection via the row input/output circuit PIA, and microcontrollers E and -En (here, elevators), which control all of the individual elevators, such as door opening/closing and car acceleration/deceleration commands. The boarding/alighting number detecting device WD%, which consists of a load detector, etc., is a serial communication processor S similar to the above.
DA, -8DAn and SDA, and communication lines CMl-CMn
and CM o .

In addition, the machine control microcomputer Ml-En has control input/output circuits EIOI-EIOn, which are comprised of car call information necessary for control, various elevator safety limit switches, relays, and response lamps, as well as input/output circuits PIA and EIOn. Communication line 5I
Connected through Ot~5IOn association.

FIG. 2 shows the overall configuration of the software, which is roughly divided into operation control system software SFI and simulation system software SF2.

The operation control system software SFI is an operation control program 5F that directly commands and controls elevator group management control such as n-chip assignment processing and elevator distributed standby processing.
From 14, as input information for this program,
Nirebenikou control data table 5FII, hall call table 5F1, including elevator position, direction, car call, etc., transmitted from the machine control programs E1 to En.
2. Elevator specification table 5F13, such as the number of managed elevators, and optimal operation control parameters 5 calculated and output using simulation software SF2.
F29 etc. are used as input data.

On the other hand, the simulation software SF2 is composed of the following processing program.

(1) Data collection program 5F20...A program that samples the contents of the hall call table 5F12 and the elevator control team IX CHIEF 11 online at regular intervals and collects data for simulation. Mainly collects traffic volume and traffic demand by destination floor.

(2) Simulation data calculation program 5F2
2. This is a program that calculates simulation data by taking into account the contents of the online sampling data table 5F21 collected by the song data collection program 5F20 and the contents of the chifuls in the past time period.

(3) Traffic demand classification program 5F33...Simulation data table 5F24! This is a program that uses the obtained destination-specific traffic demand and time information as input and divides the traffic volume within the building into traffic demands such as dispatch, before lunch, during lunch, after lunch, normal, normal congestion, leaving work, and quiet.

(4) Simulation v-show/execution program SF 35-
...Simulation data table 5F24, traffic demand classification table 5F34, and elevator service A
The contents of /S F 2 s are input, the simulation is executed, and the results are output to the simulation statistical processing data table 5F36.

(5) Various curve calculation program 5F23 by simulation: Input the data of the statistical processing data table 5F36 by simulation, execute the simulation 71c for each of a plurality of predetermined parameters, and calculate various curves r-da. Examples of the department white line data table 5F26 include an average waiting time curve table and a congestion relief time curve table.

(6) Optimal operation control nocrameter calculation program 5F
27...Inputs the contents of the various curve data tables 5F26 and the fully set congestion control table SF28, and calculates and outputs the optimal operation control parameter 5F29.

(7) Statistical processing calculation Progera, M5F32...
Statistical processing data table 5F3 by simulation
6, υ stop probability, full capacity prediction, etc. are calculated and a statistical table 5F371C is output.

An embodiment of the overall software configuration of the present invention has been described above.

FIG. 3 shows the table structure of the operation control system software used in one embodiment of the present invention.
-Control data table 5FII, Ho pv Il'J
' It is composed of blocks of U f-pull 5F12 and elevator service table 5F13. The tables in each block will be described each time the operation control program described below is explained.

First, we will explain the entire operation control system program, and then we will explain the simulation system program. The program described below is a system program that divides the program into multiple tasks and performs efficient control, that is,
It shall be managed under the operating system (O8).

However, programs can be started freely from the system timer or from other programs.

Now, FIGS. 4 to 7 show flowcharts of the operation control program. In addition, the calculation program for the elevator-predicted arrival time table and the call assignment program, which are the most important in the operation control program, will be explained.

Figure 4 shows the basic magnetic data that should be used to calculate the waiting time evaluation value.
This is a flowchart of a program that calculates the predicted arrival time to an arbitrary floor of an elevator. This program is activated periodically every second, and calculates the predicted arrival time to any floor from the current position of the elevator for all floors and for all elevators.

In FIG. 4, steps E40 and E90 indicate loop processing for all elevators. In step E20, an initial value is first set in the time table T for arrival, and its contents are set in the predicted arrival time table shown in FIG. The initial values are the open/closed state of the door,
Consider the number of seconds remaining before departure, or the predetermined opening time until activation when the elevator is out of service.

Next, advance one floor (step E30) and compare whether the floor is the same as the elevator position (step E40). If they are the same, one elevator -
Once the predicted arrival time table has been calculated, jump to step E90 and repeat the same process for the other elevators.
For N0jl, the first floor running time T is in the time table T.
Add r (step E50). Then, this time tape /l/T is set in the predicted arrival time table (step E60). Next, it is determined whether there is a car call or an assigned hall call, that is, a call to be serviced by the elevator of interest, and if so, the elevator is stopped for one stop time TII? ]l is added to the time table (step E80). Next step E30
Jump to and return the above process to <) for all 0 floors.

In addition, the first floor running time T and one stop time T8 in step E50 and step E80 are determined by the maximum operation control factor and parameter 1 from the simulation software.
As one, it is given.

Figure 5 is a flowchart of the call allocation program.
This program is activated when a hall call occurs. In this program, the call allocation algorithm is in step H5.
0 is a long-waiting call minimization call allocation algorithm (described later in FIG. 6). When a hall call occurs,
First, in step HIO, all generated hole calls are externally read. Then, step I (20 and H80, step H3
0 and H70 perform loop processing for floors and directions. Step H40 determines whether there is a hall call. If not, jump to step (70) and process all floors and directions.

If step H40 is "YES", step) H5
0 long-waiting call minimization call allocation algorithm is performed to allocate the call to the optimal elevator (step H60)
.

FIG. 6 is a processing flowchart of the long-waiting call minimization call allocation algorithm. In order to determine which elevator is optimal, steps I15'0-1 and) t50-
7) Perform loop processing using one elevator. The processing in the loop is as follows: First, in step I (50-2, elevators to which the hall call has already been assigned are excluded from the elevators to be selected).Next, in step H3O-3, the assigned hall on the previous floor containing the generated hall call is excluded. Calculate the maximum predicted waiting time 'rmax of the call.The predicted waiting time is the sum of the hall call elapsed time, which indicates the elapsed time from the occurrence of the hall call to the present, and the predicted arrival time.Elevator - Calculate the evaluation value Tzk depending on the state (Step I (
50-4). This evaluation value TE and the aforementioned maximum predicted waiting time T
Compute the comprehensive evaluation function φ with m&X (step H3O
-5). Then, the smallest elevator is selected from this comprehensive evaluation function φ (step H3O-6). If the above process is executed for all elevators, the elevator with the optimal comprehensive evaluation value will be selected by the calculation in step I (50=6).

The process up to this point is the normal allocation elm bake selection process.

At this time, if multiple units allocation for congestion response control is specified, steps H3O-1-H2O are performed until the specified number is reached.
-Repeat the process of 7. - In this way, control in response to congestion is performed. However, as with the above-mentioned IC, it is necessary to deal with congestion in a timely manner, taking into consideration the overall balance, and for this reason, it is necessary to collect elevator usage information.

For example, when determining whether congestion handling control is necessary based on the presence or absence of unloaded cargo, the following equation is one criterion.

R/(ui -r-N/RTT)〉1 (1) Here, the number of people boarding R2 unit time (number of users) [person/second] U-2 utilization rate (average i The ratio of 111 people to the capacity (111 people can fit or get on) [H] r: Capacity [people] N: Number of elevators in group management [units] RTT Knee lap time [seconds] The meaning of formula (1) is (RTT/N) In other words, it indicates whether or not backlogs will occur when people who visit the platform of the crowded floor i use the elevator at the average utilization rate ui·r during the average operation interval.

Therefore, it is necessary to collect data regarding R# ul* RTT in equation (1), and these data can be collected for each traffic demand or time period, and for Rr ul, it can be processed in a more detailed and highly accurate manner by floor and direction. By collecting the information in a timely manner, it becomes possible to perform congestion response control in a timely manner and with no excess or deficiency.

In order to collect elevator usage information in this way, simulation is not necessarily necessary, and in this case, in the software configuration shown in FIG.
Since F36 and the like are not required, the system can be constructed at low cost.

However, in the case of congestion control based only on the collection of elevator usage information, it is possible to evaluate the merits of selecting static congestion control, but the system performance when the selected congestion control is actually applied impact on,
In particular, it is difficult to understand things related to dynamic factors. Therefore, simulation becomes necessary.

FIG. 7 shows the table structure of the simulation software. Optimum operation control parameter 5F29, each blade curve data table S'F26, congestion response control table S
F 2 B, sampling data table 5F21.
Simulation data table 5F24, elevator specification table S F25 (1ζ similar to FIG. 3, not shown), traffic demand classification team 7' 5F34. Statistical processing data table by simulation SF 36
:l'6 and the structure of the subsequent open data table 5F37 are shown.

Next, the simulation software program will be explained. First, data collection program 5F20
is started at a constant period (often 1.1 seconds), and
When data is collected for a certain period of time (for example, 10 minutes), it is stored in the sampling data table 5F21 in FIG. There are various data collection items, but in the program of the present invention, in particular, destination traffic volume Q, boarding traffic volume R1 - same time R
TT.

Data such as utilization rate U is being collected.

5F22 simulation data? The Jl[n program predicts and calculates the data for periodic start-up simulation using online measured data and past data by adding an appropriate coupling variable θ.

For example, the destination traffic volume is calculated using the following formula.

Qpre "θQnew + (1-θ) Qold Therefore, the larger the coupled variable θ, the greater the weight of the online measured destination traffic volume data.

Note that the suffix ``pre'' is added to predicted data, the suffix ``new'' is added to online measured data, and the suffix ``old'' is added to past data.

Then, the simulation execution program 5F35 is executed based on the prediction data calculated by this program.

Based on the above forecast data, the predicted data of boarding traffic is dispatched based on Sarariko time information, and eight types of traffic demand are calculated: before lunch, during lunch, after lunch, normal, normal congestion, leaving work, and quiet. The transportation demand classification program 5F33 divides the traffic demand into two.

FIG. d is a flowchart of the simulation execution program 5F35. A simulation is executed for each parameter case, with the congestion handling control parameter set as a simulation parameter. First, all simulation data such as boarding traffic volume etc. are set (step 5 CIO). Next, step 5C20
The congestion handling control nocerameter is set in step 5C30, and the simulation is executed. Note that the congestion response control parameter α is, for example, 0. D.c.

B and A. The simulation results for each case are then stored for each parameter (step 5C50).
These include average waiting time, number of people left on board, congestion relief time, congestion detection level, and excessive service. After completing the simulation for all the above cases (step 5C40), optimal congestion handling control parameters are calculated (step 5C6).
(+).

The simulation execution of step 5C30 will be described in detail using chart 70 in FIG. 9.

First, congestion handling control/4' parameter α input processing is performed 5 (step AID). Next, simulation variables are initialized (step A20).

Here, the elevator that determines the necessity of congestion control
These include initial settings of detection levels such as usage status, initial settings of random numbers for passenger generation processing, and initial settings of hall call tables, etc., which will be described later. In step A30, statistical processing variables are initialized. Here, do all the initial settings for the statistical table. In step A40, the time is set to zero, and in step A90, the time is added to a predetermined value, which is set to 1 here.

), it is determined whether this time exceeds a predetermined time (step A100). The processes from step A50 to step A90 are performed until the above-mentioned time exceeds a predetermined time. In step A50, passenger generation processing is performed, and step A60
Step A70 is a group management process for allocating a hall call when a hall call is generated, and step A70 is a group management process for performing elevator running and stopping, door opening/closing, etc. Step A80 is syntax 1 for collecting statistical data.
This is a data collection process.

Here, steps A50 to A70 will be explained. In the passenger generation process of step A50, the passenger generation floor 11 and passenger destination IIJi2e are determined by uniform random numbers based on the destination traffic volume prediction data obtained by the simulation data calculation program 5F22. Furthermore, the number of passengers from the 911th floor to the 1ffi floor is determined using the uniform random number, and a hall call is issued to the 11th floor.

Next, in the group management process of step A60, if the above-mentioned hall call occurs, call assignment is performed. The method of Il'l' assignment is the same as that described for the operation control program. The car number processing in step A70 includes processing such as the running state and stopped state of the elevator, door opening/closing, and car call generation.

At this time, data such as the number of people boarding each floor per unit time, average utilization rate, and detection level of congestion control are collected and compiled by conducting a simulation in which they are actually applied to congestion control.

FIG. 1O shows a detection level L1 for determining whether or not congestion handling control is necessary based on elevator usage information, such as traffic demand.

As is clear from the previous explanation, this detection level L
1 is provided for each of a plurality of congestion response controls, and is modified based on traffic demand at that time, and can also be modified based on the level of congestion on that floor relative to all floors.

This detection level does not correspond to the capacity, but is determined through data collection or simulation, and is determined to actually prevent backlogs and eliminate congestion as early as possible.

Furthermore, a release level for congestion handling control can be similarly provided.

FIG. 11 shows how congestion is predicted and detected early based on past data collection and simulation, and congestion response control is performed. In other words, by collecting data, we can predict the congestion state of the fifth floor upward as shown in (a), and when a hall call occurs for the fifth floor upward as shown in (b), the congestion corresponding to the predicted congestion state of the fifth floor upward row will be predicted. Performs corresponding control.

FIG. 12 shows a specific example of selecting and instructing congestion handling control.

The congestion handling control table 2 is created based on the data collected by the elevator usage information collection means 1, for example, according to the criterion shown in equation (1) above. Note that this table may be a predetermined menu.

On the other hand, the elevator usage information detection means 3 detects and monitors elevator usage information that changes from moment to moment, and based on this detected data and the above-mentioned collected data, the congestion handling control selection means 4 selects the most appropriate control for the congestion situation. In addition to issuing all congestion response control commands, it also commands the congestion detection level.

According to this specific example, it is possible to select and issue the optimal congestion handling control at any time for a small number of tables.

FIG. 13 shows another specific example of selecting and instructing congestion handling control.

Based on data collected by the elevator usage information collection means or simulation, traffic demand TRI to TRM, each floor IF to NF, direction UP.

Select congestion handling control for each DN and create its table 2.

Then, based on the data detected by the elevator usage information detection means 3 and the data collected by the elevator usage information collection means 1, a command is given for congestion response control corresponding to the traffic demand, the floor, and the direction. 5 is an AND circuit.

According to this specific example, when detecting or predicting congestion, there is no need to select a congestion response control, so a prompt response is possible.

FIG. 14 shows a specific example of congestion handling control.

Congestion is detected at time to and the state continues at time 1. For hall calls that occur during this time, the hall call response light will be turned on and continuous service will be provided until the congestion is resolved.

That is, even if the first elevator arrives at time t2, the traffic demand does not fall below the release level L2, so continuous service is continued. The second elevator is at time t3
When the traffic demand falls below the release level L2 k,
The request for congestion response control has been lifted, and the third elevator
At time t4, when the hall call response light is turned off.

According to this specific example, the elevators are serviced continuously and the hall call response light remains lit, so passengers left behind can wait without doing anything. L.

Historically, given the allocation time pressure and the current traffic volume t, it is decided to preferentially allocate an elevator that corresponds to the predicted traffic volume that will increase by 94 minutes during the predicted arrival time of the assigned elevator. Yes, continuous service can be kept to a minimum number of times.

FIG. 15 shows another specific example of congestion handling control.

This is a case where congestion is detected and three elevators are turned on at once.

In this specific example, for the three assigned elevators, from the one with the smallest predicted arrival time, (1) flicker 1 from the time of assignment, (2) continuous arrival forecast light, and (3) arrival forecast light only. The display mode of each hall call allocation car number display device is made different.

According to this specific example, the crowded waiting passengers are appropriately dispersed, so it is possible to improve the overall service efficiency, such as shortening boarding time, and to quickly eliminate congestion.

In addition to the above-mentioned specific example, the following specific example may be considered as the congestion response control.

(1) Increase the length of time the door is open on crowded floors.

(2) Disable the close button function (3) Allocate preferentially to elevators with a small amount of N in the car.

(→When allocating multiple elevators, allocate elevators that are spaced apart as much as possible.

In addition, for the detection of congestion response control, (1) It remembers that a large number of people dropped off before a predetermined time limit (meeting start), and corrects the congestion detection level to lower it in proportion to the time since then.・Kukoto.

Congestion response control selection is as follows: (1) Congestion response control is selected based on the number of people in the hall, based on the number of people getting off to the floor and the number of passengers who are called in the hall.

etc. are possible.

According to the embodiments of the present invention described above, the following effects can be obtained.

The first effect is that the microcontroller M2 collects data online about the ever-changing building environment.
Based on this data, an elevator simulation is performed by changing the congestion control parameters, and the meters and congestion detection levels for optimal congestion control are collected. Since it is based on I calculation, the group management control device can easily adapt to changes in the building environment. As a result, the average waiting time will be shortened, greatly contributing to the early elimination of congestion.

The second effect is that by using the waiting time evaluation value and the evaluation value based on elevator status as the evaluation function for call assignment, and changing the weighting coefficient β between these evaluation values, the average waiting time can be minimized. In addition to being controllable, it is also possible to eliminate congestion in the shortest possible time, and control can be easily performed.

As a third effect, since data is collected online, parameters necessary for elevator simulation can be collected and calculated, and the accuracy of the simulator can be improved.

〔Effect of the invention〕

As described above, according to the present invention, it is possible to carry out congestion handling control that is suitable for the elevator use status at that time, and it is possible to eliminate congestion early and with just the right amount of service.

[Brief explanation of the drawing]

FIG. 1 is an overall configuration diagram of a group management control device according to an embodiment of the present invention, FIG. 2 is an overall configuration diagram of its software, and FIG.
The figure is a table configuration diagram of the group management operation control system software.
Fig. 4 is a flowchart for calculating the predicted arrival time table, Fig. 5 is a flowchart for calculating call allocation, Fig. 6 is a flowchart for calculating long waiting minimization call allocation, Fig. 7 is a table configuration diagram of the simulation system software. Figure 8 shows optimal area priority No. 4 based on simulation.
Fig. 9 is a flowchart for simulation execution, Fig. 1υ is an explanatory diagram showing the relationship between elevator usage information and congestion response control detection level,
Fig. 11 is an explanation of the case where congestion control is performed by predicting congestion. Fig. 12 and Fig. 13 are diagrams showing specific examples of different congestion control selection means. A time chart showing a specific example of correspondence control, and FIG. 15 are explanatory diagrams showing an example of display when a plurality of elevators are allocated. MA... Elevator group management control device, IC...
Hall call device, Ml... Elevator group management operation f
ltll General use microcomputer, M2...Microcomputer for simulation, El-En...Microcomputer for machine control, E
IQI~EIOn...control input/output element, WD...device for detecting the number of people getting on and off, SFI...operation control software, SF2...simulation system software, l.
...Elevate. - information collection means for elevators, 2... congestion handling control table, 3... elevator usage information detection means, 4... congestion handling system a11 selection means. Island 1 Mouth Figure 4 Figure 5 Notebook 6 Mouth 7 Mouth 82nd 1st O Massage Figure 11 Figure 12121 Look! 3 Mouth No. 140 Liquid output ↓ t U t+ L2ts t4

Claims (1)

[Scope of Claims] 1. A plurality of elevators operating between multiple floors, a hall call registration device provided on each of the floors, and a hall call assignment means for assigning the hall call to the elevator. An elevator group management control device comprising a means for detecting elevator usage information, a means for collecting elevator usage information detected by the detection means, a plurality of congestion response control means, and at least the above-mentioned collection means. 1. An elevator group management control device comprising: means for selecting one of the plurality of congestion handling control means according to the elevator usage information collected by the elevator. 2. In claim 1, the selection means:
Selects one of the plurality of congestion response control means and instructs its execution in accordance with the elevator usage information collected by the collection means and the elevator usage information detected by the detection means. A group management control device for an electric heater characterized by the following. 3. In claim 1, the selection means:
The above-mentioned detection means selects one of the plurality of congestion response control means according to the elevator usage information collected by the collection means, and the detection means An elevator characterized in that it instructs execution of selected congestion response control.
Group management control device. 4. In claim 1, the selection means includes:
The elevator is configured to include means for comparing the elevator usage information detected by the detection means with a selection reference value, and to select one of the plurality of congestion response control means according to the comparison result. An elevator group management control device, further comprising a simulation means for calculating the selection reference value. 5. In claim 1, the plurality of congestion response control means include means for blocking hall call reset control as one of them, and the elevator is continuously operated in response to a hall call on a floor where congestion occurs. A group management control device for an elevator, characterized in that it is configured to provide service. 6. In claim 5, it is further provided that the hall call registration fi=? Equipped with a display panel, the above-mentioned continuous elevator
1. A group management control device for an elevator, characterized in that the hall call registration display device is configured to operate continuously from 1# while the hall call registration display device is in service. 7. In Claim 1, the selection means comprises means for comparing the elevator usage information detected by the detection means with a congestion relief reference value, and the selection means is configured to perform the selection according to the comparison result. What is claimed is: 1. A group management control device for elevators, which is configured to terminate an execution command for congestion response control, and further comprises a simulation means for instantly calculating the congestion relief reference value. 8. The elevator group management control device according to claim 1, wherein the plurality of congestion response control means includes means for allocating a plurality of elevators. 9. In claim 8, each floor, floor,
An elevator characterized in that each car is provided with a hall call allocation car display device, and the display device is configured such that the display mode of the display device becomes C (for each allocated car) when the plurality of elm bakers are allocated. - Group management control device.