JPS6036275A - Controller for group of elevator - 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 Application of the Invention] The present invention relates to an elevator group management and control device, and particularly to a device suitable for group management and control of elevators using a computer.

[Background of the invention]

Conventionally, hall calls have been assigned by calculating a comprehensive evaluation value for each elevator using an evaluation function that takes into account the service status of the entire building, and then allocating the hall call to the elevator with the minimum or maximum overall evaluation value.

The predicted waiting time is often used as this overall evaluation value, but the evaluation function used to calculate this value does not only calculate the waiting time for the hall call to be allocated, but also the waiting time for the hall call that has already been allocated for service. Considering the call,
The duration after the hall call is generated is added as one of the evaluation factors. As a result, it is possible to equalize the waiting time of elevator hall customers and to prevent hall calls that result in long waiting times.

However, as traffic demand increases throughout the building and hall call buttons are operated on multiple floors, waiting times become longer on each floor, and especially on the busiest floors, large numbers of people arrive at the halls. When we arrived, the boarding area became crowded. and,
When an elevator arrives, all waiting passengers may not be able to board the elevator, it may take a long time for the elevator to descend, or many car calls may be made at once. There was a problem where calls from other floors would have to wait for a long time.

Also, if you are assigned a floor with many passengers, +1. Ih
This problem becomes even more severe when an elevator is assigned a new floor on its way to that floor.

The above problem is due to the fact that the conventional hall call allocation control did not take into account the increase in the number of customers waiting on the floor after the hall call was allocated.

[Purpose of the invention]

The purpose of the present invention is to eliminate the above-mentioned problems of the prior art,
To provide an elevator group management control device capable of equalizing the waiting time of elevator hall customers and preventing long waiting hall calls.

[Summary of the invention]

To achieve this objective, the present invention provides that the elevator
The waiting time of a hall call that has already been assigned to be serviced, e.g., the duration after the hall call is generated, is determined by the elevator at the floor to which the hall call is assigned.
Information about the customers, such as the average number of people boarding the elevator per hall call, the number of people boarding the elevator per unit time, and the number of hall calls per unit time, is made variable over time.

[Embodiments of the invention]

Hereinafter, the present invention will be explained in detail with reference to a specific embodiment shown in FIGS. 1 to 10. In addition, the explanation of the example will first be explained as follows.
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 the explanation will be given using a flowchart for realizing the above control concept.

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

The elevator group management control unit HMA includes a microcomputer M1 that controls elevator operation control and a microcomputer M2 that controls simulation. Data is communicated between the microcomputers M1 and M2 via a communication line CMc by a serial communication processor 5DAc. A detailed configuration and operation explanation regarding this serial communication processor SDA is provided in Japanese Patent Application Laid-Open No. 56-37972.
and 1Fifμn No. 1983-37973.

The microcomputer M1, which controls elevator operation, is connected to the call signal HC from the hall call device T (D via the parallel input/output circuit PIA, and is still in charge of opening and closing the door σ), as well as commands for accelerating and decelerating the car. The microcomputers E, ~En (here, it is assumed that there are n elevators) that control the respective elevators communicate with the same serial communication processors SDA+~SDAn and 5DAL. They are connected via lines CM and -CMn.

In addition, control input/output elements EIO, -EIO, consisting of call information, various elevator safety limit switches, relays, and response lamps necessary for control are input and output to the machine control microcomputers E and ~En. Circuit PIA and communication line S
IO, -3IOn.

FIG. 2 shows the overall configuration of the software, which is roughly divided into operation control system software SF1 and simulation system software SF2.

The operation control system software SFI handles call assignment processing,
Operation control program 5F1 that directly commands and controls group management control of elevators such as distributed standby processing of elevators
The input information for this program includes an elevator control data table 5F11 such as the elevator position, direction, and car noise, which are transmitted from the machine control programs E1 to En, a hall call table sr+2, and an elevator control data table 5F11, a hall call table sr+2, and an elevator Elevator specifications table 5, including number of managed units, etc.
F13fi and simulation software SF
Optimum operation control parameter 5F2 calculated and outputted in step 2
The input data is 9th grade.

10,000, simulation software 8F2 consists of the following processing programs.

(1) Data collection program 5F20...A program that samples the contents of the hall call table 5F12 and elevator control data table 5FII online at regular intervals and collects data for simulation. Mainly collect demand.

(2) Simulation data calculation program 5F
22...Online sampling data table 5F collected from data collection program 5F20
This program calculates all simulation data by taking into account the contents of 21 and the contents of the table for past time periods.

(3) Traffic demand classification program 5F33... Input the destination-specific traffic demand and time information obtained from the simulation data table 5F24, and calculate the traffic volume in the building, before lunch, during lunch, after lunch, etc. This is a program that divides traffic demand into normal, normal congestion, leaving work, and quiet traffic.

(4) Simulation execution program 5F35...
...Simulation data table 5F24 and 9
The contents of the traffic demand classification table 5F34 and the elevator specification f-pull 5F25 are input, a simulation is executed, and the results are output to the simulation statistical processing data table S17'36.

(5) Each gentle curve calculation program 5F23 by simulation inputs the data of the statistical processing data table 5F36 by simulation, performs simulation for each predetermined number of parameters, and calculates and outputs various curve data. Various curve data tables S,
As F26, for example, one average waiting time curve table,
These are power consumption curve tables, etc.

(6) Optimal operation control parameter calculation program 5F2
7...Input the data of the various curve data tables 5F26 and output all calculations of the optimum operation control parameters 5F29.

(7) Synthesis processing calculation program 5F32...Simulation statistical processing data table 5F36
By inputting the data, the probability of stopping, the number of passengers per hall call, the number of people getting off per car call, etc. are calculated for each floor, and the results are output to the statistical table 5F37.

Above, one embodiment of the overall software configuration of the present invention has been described in section A.

Next, a method for calculating optimal operation control parameters using simulation will be explained.

A stop call evaluation function and an evaluation function based on elevator status are used as a call allocation method. Here, the concept of the stop call evaluation function is disclosed in Japanese Patent Application Laid-Open No. 52-47249 and Japanese Patent Application Publication No. 52-126845.

1! Using the above stop call evaluation function and the evaluation function based on elevator shape tracing! The q number is called a comprehensive evaluation function. This comprehensive evaluation function φ can be expressed by the following equation.

φ−Tmax−α+Tα+Ta Ta = ΣβS 'l'B;= kα2 Here, 'rmaX is the waiting time evaluation value, T6 is the stop call evaluation value, α1 is the waiting time evaluation value Tma, x; and the stop call evaluation value. It is a weighting coefficient with Tα. This is called the αlk area priority parameter. Further, β is a weighting coefficient for the stop call S (the call to be serviced is called 10) on the floor adjacent to the generated hall call, and is in the range of 0 to 20, for example.

Furthermore, TE consists of an elevator-state evaluation interval tQf, a predetermined coefficient, and a load concentration parameter α2.

The elevator state includes, for example, a door closed state, an assigned hall not called, a light-out state in the car, etc., and the value of the coefficient is set according to this state.

FIG. 3 shows the table configuration of the operation control system software used in one embodiment of the present invention, which can be roughly divided into elevators and
ffflJ Go f-tatapuru 5FII, hall call table 5F12. It is composed of blocks of elevator specification table 5F13. The tables in each block will be described each time the operation control program described below is explained.

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

Therefore, the program cannot be started from the system printer or from other program forces.75'
You can do it freely.

Now, FIGS. 4 to 7 show flowcharts of the 13-mile can control block. A program for calculating the 11-hour table for elevator-M arrival and a call error estimation program, which are particularly important in the operation ffj control program, will be explained.

The 40th is the basic data of waiting time evaluation value calculation and the
J'l valve up to any 1@ in the elevator? Yogin 11
This is the flow of a program that calculates time. For example, the program runs once every second.
, the predicted time for up to lJ minutes from the current elevator position to any floor is calculated for all floors and all envelopes.

In FIG. 4, steps E10 and E90 indicate roof processing for all elevators. At step E20, for work y11 1) Set the initial value in 11 table T, and set its V] volume as if, 3 L
)'1σ) Arrival i'i'i'11111 Set in the time table.As an initial value, the number of seconds left for departure after the door is opened/closed (rt4), and the predetermined time until the elevator is activated when it is idle, etc. Conceivable.

Next, the process advances one floor (step E30) and compares whether the floor is the same as the elevator position (step E40). If they are the same, it means that the predicted arrival time table for one elevator has been calculated, and the process jumps to step E90 to repeat the same process for the other elevators. On the other hand, if II N O++ is determined in step E40, the first floor running time T is added to the time table T (step E50). This time table T is then set in the predicted arrival time table (step E60). Next, when calling a car, the allocated car elevator stops, so the stopping time is T.

It is added to the total time table (step E80). Next, the process jumps to step E30, and the above process is repeated for all floors.

Note that the first floor running time Tr and one-time stop time T in step E50 and step E80 are determined by the optimum operation 11i11 fa (1
) is given as one of the parameters.

Figure 5 is a flowchart of the call allocation program.
This program is from Hall 111-4
t, 11 will be done. In this program, the alcohol rhythm for all call assignments is long (1 to n) as shown in step H50.
7bi If.

Minimized call assignment algorithm (later in Figure 6:, 7B,
). When a hall call occurs, the first step is "l".
At step 110, all generated hall calls are read from outside. Soshi-C
%Step I (20 and H80, Step FI30 and Ti
70, a loop is performed for l'i floors and directions. Step H40 is the generation hole call 75 (force 1
judge.

If not, jump to step H70 and save σ) F
) V floor, process for direction. Step H4075E
If ``yE S'', perform the call allocation algorithm (step) (50 long waiting calls r) - J'αl'' and allocate all calls to the appropriate elevator (step, Ti60) + Figure 6 shows the long waiting calls. It is a processing flowchart of the call minimization call allocation algorithm 11.

In order to fully determine which elevator is optimal, step H
3O-1 and i (loop processing with one elevator by 50-7, 1-ro. Processing in the loop is step I (
At 50-2, the maximum predicted waiting time THIaxk of the allocated hall call on the front floor including all generated pole calls is calculated. In addition,
The predicted waiting time is the sum of the hall call elapsed time, which indicates the elapsed time from the time the hall call was generated, to the time weighted using information about the customers on the floor, and the predicted arrival time. ? Step X) In I50-3,
Calculate the stop call evaluation value T from the stop calls of the predetermined 15) v floors including the generated pole call. Furthermore, an evaluation value TE based on the elevator status is calculated (step H3O-
4). Using these evaluation values Tα+TE and the aforementioned maximum predicted waiting time T'max, a total value function φ is calculated (step H3O-5).

Then, the minimum elevator − in this comprehensive evaluation function φ
is selected (step H3O-6). If the above process is executed for all elevators, step H3O
− Elevator of the optimum value of f↑ by the calculation of 6 −
7 is a flowchart of the calculation of the maximum predicted waiting time TmaX. By the way, a new outbreak 1. A method will be described in which only hall calls that have already been assigned and which are located on floors ahead of the hall calls that have been assigned are subject to evaluation.

Maximum predicted waiting time in step H3O-21"' 1naX
v? :,=ii Set the expected arrival waiting time of the raw hall call floor to the initial 1111 value. Next step H50-L
Step H50-22 advances the floor by one floor, and it is compared in step H50-23 whether that floor is the same as the elevator position. If (7) is the same, it means that the maximum predicted waiting time T maX for the floor ahead of the newly generated hall call has been calculated, so the process ends.
? ;'Ts It is determined in step I (5o-24) whether there is a hall call already assigned to the elevator.

If there is no assigned hall call, step) [50-
Return to 22. If there is an assigned hall call, go to step [50-25 and set the predicted waiting time 'Fc of the floor to 7''.
Calculate 7'4. The calculation formula for the predicted waiting time Tc of B is expressed by the following formula.

T c = T A + I T B Here, TA is the predicted arrival time of the elevator at the floor as explained in FIG. It is a weighting coefficient determined from information about elevator users on a floor,
There are C's that are unreleased on every floor. This weighting value is set so that it becomes larger for floors with a large number of elevator users.

The above weighting coefficients include the average number of passengers per hall call, the number of people boarding the elevator per unit time,
The number of hall calls generated per unit time may be considered, but these are all calculated by the statistical processing calculation program SF"32, which will be described later, and are stored in the revenge table 5F37, which is the output result.

Next, in steps ll5O-26, f (50-27,
Calculated predicted waiting time Tc and maximum predicted waiting time T4 for the relevant floor
na For example, the predicted waiting time Tc for the floor is newly set as the maximum predicted waiting time, and the process returns to step E (50-22).

FIG. 8 shows the table configuration of the simulation software 117). Optimal operation control/<Rameku S Ii'
29, various curve data tables 5F26, sample link theta table 5F21, cheetah table for simulation 5F24. Elevator - Specifications Chiful 5F25
(not shown because it is similar to FIG. 3) shows the configuration of a correspondence demand classification table SF34, a statistical processing data table 5F36 based on simulation, and a statistical data table 5F37.

Next, the simulation software program will be explained. First, data collection program 5F20
is activated at regular intervals (for example, 1 second), 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 correspondence volume Q1 elevator 1st floor travel time t
r, i times standard stop time ts1 Data such as the number of hall calls are collected. First floor running time tr of the above elevator
To calculate the number of standard stops t8 per time, after the sampling time ends, the running time for the first floor can be calculated by dividing the running time by the number of floors traveled, and the number of elevator stops and the time between doors (stops). Standard stop time can be calculated once.

When the sampling time ends, the collected data undergoes the above-mentioned calculation and is stored in the online measurement table and time zone table of the sampling data table 5F21 in FIG. 8, respectively. The data table for this online measurement is QneVl' r trne
w Add a new subscript to the item name, such as 1tsnev, and add Qold t yold y to the time zone table.
It is written with the subscript "old" added, such as "jsold".

The simulation data calculation program of 5F22 is activated periodically, and the simulation data is predictively calculated using online measured data and past data, taking into account an appropriate coupling variable θ.

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

Qpre””θQ new + (1-θ) Q, o
id Therefore, the larger the coupled variable θ is, the more the data on the destination traffic volume measured online becomes more distorted.

Note that a subscript of pre is added to the predicted data.

Similarly to the above, the predicted data t rpr of the first floor running time and one standard stopping time. yt8pre is also shown, and this Lrpje + t9pre data is "1" of the optimum operation control parameter SF2'9 shown in the 8th diagram.
．． It is set in the LTs table. Then, the simulation execution program 5F35 is activated based on the predicted data calculated by this program.

Furthermore, based on the above forecast data, the forecast data of destination traffic volume is further divided into eight types of traffic demand based on time information: dispatch, before lunch, during lunch, after lunch, normal, normal congestion, leaving work, and quiet. This is the transportation demand classification program 5F33.

FIG. 9 is a flowchart of the simulation execution program 5F35. There is an area priority parameter that is a weighting factor as a simulation parameter.
Run the simulation for each parameter case. First, simulation data such as destination traffic information is set (step 5CIO). next,
In step SC'20, the area priority parameter is set to 7, and a simulation is executed (step 5C30).

Note that the area priority parameter α is, for example, 0, 1,
2°3.4.5. The simulation results for each case are stored for each parameter (
Step 5C50). Note that simulation results are stored in terms of average waiting time, power consumption values, etc. ” End the simulation for all cases (Step 5)
C40), and calculate optimal area priority parameters (step 5C60).

The simulation execution of the above step 7'5C30 will be explained in detail using the flowchart 2- in FIG.

First, input processing of the area priority parameter α is performed (step A10). Next, all initial settings of simulation variables are performed (step A20). For example, this includes the initial setting of random numbers for passenger generation processing, which will be described later, and the initial setting of a hall call table. In step A30, statistical processing variables are initialized, and here the statistical table is initialized. 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 one here. ), it is determined whether this time exceeds a predetermined time (step A100). The processing from step A50 to step A90 is continued until the above-mentioned time exceeds a predetermined time.

In step A50, a passenger generation process is performed, step A60 is a group management process to allocate a hall call when a hall call occurs, and step A70 is a
Performs elevator operations such as running and stopping elevators and opening and closing doors. Step A80 is a statistical data collection process for collecting statistical data.

Here, steps A50 to A70 will be explained. In the passenger generation process in step A50, the passenger generation floor iI and the passenger destination floor 12 are determined by uniform random numbers based on the destination traffic volume prediction data obtained by the simulation data calculation program 5F22. moreover,
The number of passengers generated from the 11th floor to the 17th floor is determined by the uniform random number mentioned above, and hall calls are generated on all 18 floors. next,
In the step A600 group management process, if a second pole call occurs, call assignment is performed. The method of call assignment is the same as that explained in the operation control program above. The car processing in step A70 includes processing such as the running state of the elevator, the stopped state, the door opening/closing, and the generation of car calls.

Next, the statistical processing calculation program 5F32 will be explained. This program 5F32 is a program that performs the statistical processing 32 based on the statistical data (table 5F36) collected at step 880 in FIG.

First, the average number of passengers per hall call is calculated by dividing the number of boarders for each floor by the number of hall calls for each floor. Next, by dividing the number of people boarding each floor by the unit time, we calculate the number of boarders per unit time, and further by dividing the number of hall calls generated by each floor by the unit time, we calculate the number of hall calls per unit time. Number of occurrences t
Hama: n', (ru.In addition, each of these calculations is performed according to the demand band.

Let's do that. The results of these calculations are stored in the statistical table FIF3.
Set to 7.

According to this embodiment, since the allocation evaluation value reaches the end of the floor 17) where there are many already allocated customers before a newly generated hall call, it is difficult to allocate a newly generated hall call. This will prevent long waiting times on floors with many customers.

The 11th time is the maximum child or 11 waiting time 'I explained in Figure 7.
This is a flowchart of another embodiment in which the calculation method of "max" is changed.In this embodiment, the elevator
This is an example in which all hall calls that have already been assigned are subject to evaluation. Specifically, step 1 (50-23
The judgment condition is ``For all floors! 11j has been fixed (step H50-53) Even if it has been changed to j, σ).

According to the embodiment, in addition to the effects of the embodiment described above,
It becomes difficult to allocate a hall call that occurs on a floor beyond the floor where there are many users who have already been assigned, and it is possible to prevent long waiting times on floors beyond the floor where there are many users.

Further, FIG. 12, ω) is a graph for explaining another embodiment in which the calculation formula for the predicted waiting time Tc explained in FIG. 7 is changed to the following formula.

Here, %TA is the predicted arrival time of the elevator on the floor, TB is the duration of the hall call on the floor, ΔL is the activation period of this program, and γ(TB) is the weighting coefficient, whose value is the hall call duration. This is a function that takes the duration as a parameter.

FIG. 12(c) shows this function γ(TB). γ0
is a weighting coefficient determined from information regarding the customers of the elevator in question. In this example, the weighting factor γ. is increased in stages as the hall call duration increases.

FIG. 12 CB) shows the above function γ. The second term φ of the hall call duration Tn and predicted waiting time Tc when calculated using
□ Showing the relationship between 'rc' □ Even when 1,000 predicted waiting time calculation formulas are included as in this embodiment, the same effect as that of the above-mentioned embodiment can be obtained; [Effect of the invention] As explained above. As described above, according to the present invention, a hit elevator is already assigned to service 11. Since the waiting time for a hall call is made variable using information about the elevator users on the floor where the hall call ≠: 1j is assigned, it is possible to change the waiting time for a hall call that serves the floor with the most customers. To suppress the allocation of new hall calls to customers, equalize the waiting time of elevator hall customers, and prevent hall calls from being delayed for a long time.75
I can do five.

[Brief explanation of drawings]

Fig. 1 is an overall configuration diagram of a group 16 control system according to an embodiment of the present invention, Fig. 2 is an overall configuration diagram of its software, and Fig. 3 is a group management operation control system software. The table configuration diagram in Figure 4 shows the arrival child σ4+1 n! 11H
Flowchart for calculating I boolean, Figure 5 0 or 1+
7ζy'-tl allocation calculation flowchart, Figure 6 is the long wait minimization call allocation calculation flowchart 1.
Figure 8 is a flowchart for calculating the maximum predicted waiting time, Figure 8 is a table configuration diagram of simulation software, Figure 9 is a flowchart for calculating optimal area priority parameters by simulation, Figure 10 is a flowchart for simulation execution, and Figure 11 is a flowchart for calculating the optimum area priority parameter by simulation. Flowchart for calculating the maximum predicted waiting time of a group management control device according to another embodiment of the present invention, FIG. This is a graph for 1 Etsumei. MA...Elevator group management control device, HC
... Hall calling device, Ml ... Elevator group management operation control microcomputer, M2 ... Simulation microcomputer %EI"En ... No. machine control microcomputer, EIO, -EIOn...Control input/output element, SFI...Operation control system software, SF2...Simulation system software. 3rd Port 4-Figure 50 Figure 6 Exit 8 Figure 9 IO Exit Figure 11

Claims (1)

[Scope of Claims] 1. A plurality of elevators in service between multiple floors, a hall calling device for calling the elevators installed on the floors, and a car inside the elevator car of each elevator. a call device for indicating the destination floor installed in the
and means for allocating a hall call to an elevator using the overall evaluation value calculated for each elevator, the evaluation value corresponding to the waiting time of the pole call already allocated to the elevator. 1. A group management control device for elevators, characterized in that the elevator group management control device is equipped with means for changing the function of the elevator using information regarding elevator users on the floor to which the hall call is assigned. 2. An IR-g control device for an elevator according to claim 1, wherein the waiting time is a duration of time after a hall call is generated. 3-'l'3 The elevator group management control device according to claim 1, wherein the information regarding the passengers is an average number of deaths per hall call. 4. An elevator group management control device according to claim 1, wherein the information regarding the passengers is the number of people boarding the elevator per unit time. 5. The elevator group management control device according to claim 1, wherein the information regarding the customers is the number of hall calls generated per unit time. 6. An elevator group management control device according to claim 1, characterized in that the information regarding the users is provided for each traffic demand zone. 7. An elevator group management control device according to claim 1, wherein the information regarding the passengers is obtained by simulating the group management.