JPS5926872A - 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 The present invention relates to an elevator group management device, and more particularly to an elevator group R control device using a computer.

Conventional group management devices adapt to pill-specific traffic volume and do not perform fine-grained control, so the predicted time for the elevator to arrive at the floor where a hall call occurs is after the hall call service that has already been assigned. On the other hand, there was a drawback that errors occurred due to hall calls, etc.

SUMMARY OF THE INVENTION An object of the present invention is to provide a means for accurately determining the probability of a stop even during energy-saving operation, in order to accurately determine the estimated time and cost for an elevator to arrive at a floor where a hall failure occurs.

A feature of the present invention is that in group management control that is assigned to all elevators for hall calls, when calculating the predicted time i* for the elevator to arrive at the floor where the pole call occurs, it is calculated for each traffic demand, direction, and floor. By introducing the elevator stop probability and bringing it closer to the actual arrival time, we have achieved an efficient group management control time, and we have also introduced the elevator stop probability to obtain a good stop probability during energy-saving operation. The reason is that we decided to calculate the probability of stopping based on the number of people getting on and off, rather than the number of calls.

Hereinafter, the present invention will be explained in detail with reference to a specific embodiment shown in FIGS. 1 to 513.

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

The elevator group management device MA includes elevator operation control 1.
UB and in-building traffic collection function, traffic demand classification function based on traffic volume characteristics or time signals, etc. Signal calculation function, and function to calculate the number of times the elevator reverses direction. There is a microcomputer M that controls the function of calculating the probability that the elevator will stop for each direction.

The microcomputer M receives call signals 1. from the hall call device i-iD. (Ck parallel output circuit PIA(1)er
iphe, ral 1nterface Adapt
r), and also controls the elevators such as door opening/closing and car acceleration/deceleration commands;
1i) is a serial communication processor 5DA
1 to 5DAn via communication lines CM1 to CMn. On the other hand, a signal PM (not shown) from a setting device PD (not shown) that provides commands necessary for determining variable parameters is manually inputted via a circuit 1'IAi that inputs and outputs signals in parallel.

In addition, the machine control microcomputers E1 to En are equipped with car call information necessary for control, car load change information on each floor, various elevator safety limit names, and control consisting of relays J5 and P. Attendance element EIOI-4: IOn
The circuit PIA that inputs and outputs the signal in parallel with the signal line S
Connected via l0I-8l0nk.

The present invention will be explained in detail using FIG.

The microcomputer M has a built-in operation control program mainly for call assignment, and this operation control program takes in information necessary for control from the microcomputers E1 to En used on each car side and the hall call HC. Further, the operation NjIJ control program performs call assignment using variable parameter sounds. For example, this parameter includes the stop probability required to accurately determine the predicted elevator arrival time, which is an element of the evaluation function for call assignment, or the fullness prediction accuracy required to accurately predict the number of people.

These calculations are processed in real time according to traffic demand such as dispatch, first half of lunch, half of lunch, second half of lunch, normal times, normal congestion, leaving work, and closing hours, and the elevator Outputs the most ideal parameters for group management. Therefore, the elevator group management control according to the present invention is capable of responding to the ever-changing pill environmental conditions, and greatly contributes to improving the elevator group management performance.

The specific hardware configuration of each microcomputer is also shown below. These microcomputers can be easily configured as shown in FIGS. 2 and 3. hiPU is the center of the microcomputer
(Micro processing '(Jnit
), an 8-bit MPU is appropriate because it does not require much processing power, especially for the machine control microcomputers E1-EH. On the other hand, since the elevator operation control microcomputer M requires all complex calculations, a 16-bit MPU with excellent calculation performance is appropriate.

Now, each microcomputer has M as shown in Figures 2 and 3.
l) 1 is also OM (1 is also ead Qnly Memory) which stores the control program etc. in the path line BUS of U.
, 1ltlJ (wholesale data, work data, etc.)
ry), a circuit PIA that outputs signals in parallel, and a dedicated processor SDA that performs serial communication with other microcontrollers.
(5erialJJata Adapter) is concubined.

In addition, each My: 77# El ~ En, It A M
.

IL OM depends on the size of its control program, etc.
Consists of multiple elements.

FIG. 2 shows the configuration of the elevator group management device.

@ In Figure 3, the elevator control data includes, for example, the car call button CB-? , safety limit switch S
W L, relay contact 5WRY, car weight We
igbt is taken into AM from PIA. On the other hand, the data calculated by the MPU is sent from the PIA via the response lamp La1T11) -? It is output to a control output element such as an IJ relay.

Here, the node configuration of the serial communication processor + jsDA between the microcomputers used in FIGS. 2 and 3 (as shown in FIG. A P/S that performs parallel/serial conversion, an S/P that performs inverse conversion, and a controller CNT that controls their timing, etc.
Consisted of. Transmission buffer TX11. The reception buffer RXB can be freely accessed by the microcomputer and can store, write, and read data. On the other hand, from the sDA & controller CN 'I', the transmission buffer T
It also has a function of automatically transmitting to the other 51) A's receiving buffer XB via the Uchitani P/S' of 1. Therefore, since the microcomputer t does not need to perform any transmission/reception processing, the microcomputer t can concentrate on other processing. In addition, details regarding this 5IJA +
l'III configuration and operation explanation l Samurai Kaisho 56-379
No. 72 and Japanese Unexamined Patent Publication No. 56-37973.

Next, software that is an embodiment of the present invention will be explained from the overall configuration with reference to FIG.

As shown in Figure 5, the software includes software that calculates all stop probabilities, and an operation control program 5F1 that performs group management operation '+fjl) # based on the obtained stop probabilities.
1 and υ, both of which are processed by the microcomputer MK. However, since the stop probability calculation software and the operation control software can be simply separated, they can be configured using separate microcomputers.

The Wholesale Program 5FII is software that directly commands and controls the wholesale of elevators such as call assignment processing, elevator distributed waiting area, etc. This program As the input information for
The control program (Fig. 1: built in the microcomputers E1 to En) is transmitted to the elevator control table S L'1, hall call table SF2, and stop probability performance software, including the elevator position, direction, car call, etc. The performance of the software is 3:1.It is output as 7ζ stop accuracy rate parameters, etc., and is made up of human-powered data.

On the other hand, the outage probability calculation software consists of the following burial program.

(υ In-building Matatsu Remains Collection Program (SF'3 J...
...This is a program that samples the hall call, elevator 1UIJ b+1 table yt online at predetermined intervals, and mainly collects the traffic volume within the pill.

(2) Traffic demand segmentation program (SF5) ...The traffic surface table SF4 obtained by the in-building traffic collection program SF3 and the report at time 1 1"I are used as human power, and the traffic in the building is dispatched. Before lunch, It is a block rim that divides traffic into 8 traffic areas: during lunch, after lunch, normal, normal congestion, leaving work, and quiet.

(3) Elevator direction reversal count calculation program (S
F7)...This is a program that calculates the number of times each elevator has turned or reversed during each traffic demand period divided by the above-mentioned traffic demand classification program sJi''5.

(4) Stop probability calculation program 8 F 9...Song/traffic l, table SF4 and traffic demand classification signal sII''6fc
The stop probability is calculated by traffic demand, direction, floor, and floor, and the stop probability parameter table SFI O
It is a program that learns the optimal stopping probability by exponentially smoothing the stopping probability parameter of υ, and detects the current traffic volume in the pill and sets a flag.

Next, a table configuration used in an embodiment of the present invention will be explained with reference to FIGS. 6 and 7. Figure 6 is luck Qti 1l
tlJ (+m) The table structure of program SFI 1 is roughly divided into elevator control table SF1 and hall call table SF2.The tables in each block will be explained each time when the entire operation control program described below is explained. state

Figure 7 shows the daple configuration of the stop probability calculation software, including a traffic volume table SF4 and a transit demand classification table SF6.
, a direction reversal table SF8, and a stop probability parameter academic table SFI O blocks 1!1q.

Next, the actual software tAN of the present invention will be described.

Operation control program first? Next, the stop probability calculation software will be explained. It is assumed that the programs described below are managed under a system program that divides programs into a plurality of tasks and performs efficient control, that is, an operating system (O8). Therefore, programs can be started freely from the system timer or from other programs.

Now, FIGS. 8 to 10 show the flow of the operation control program. Two particularly important elevator arrival time table calculation programs and a call assignment program, which are particularly important in the operation 11tlJ Misaki program, will be explained.

FIG. 8 is a flowchart of a program that calculates the predicted arrival time 'a [to an arbitrary floor of the elevator], which is the basic data for the waiting time evaluation 1+i calculation. This program is
For example, it is activated periodically every - second, and the predicted arrival time from the current position of the elevator to any floor is calculated for all floors and all elevators using the stop probability parameter sound.

In FIG. 8, steps EIO and Eloo indicate looping through all elevator car failures. In step E20, first, the time table T for work is
The initial shift is set to 1, and the contents are set in the predicted arrival time table of FIG.

Examples of initial changes include the opening and closing of doors, the number of seconds left before departure, and the predetermined time until activation when an 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, it means that the predicted arrival time table for one elevator has been calculated, and the process jumps to step E100 to repeat the same process for the elevator in the song. On the other hand, in step E40, 'NO'
If so, the first floor running time 'i' is in the time table Ill.
r i is added (step E50). Then, this time table T is set in the predicted arrival time table (Stella; 'E60). Next, it is determined whether there is a car call or an assigned hall call, that is, a call that should be serviced by the elevator of interest, and if so, the first floor stop time ゛■゛8 is added to the time table in order to stop the elevator. (step E80). Next, the process jumps to step E30 and repeats the above process for all floors. But if not, the elevator will not stop at this time. However, since there may be a stop due to a car call, etc. after the allocated hall call service, the stop probability Pj′fc calculated for each traffic demand, floor j, and direction is determined by the time table T K P ”: T Add 8 (
(E90).

FIG. 9 shows the flow of the call assignment program, which is activated when a hall call occurs.

In this program, the call allocation algorithm is a long-waiting call minimization call 1-to-1 allocation algorithm (described later in FIG. 10) as shown in step A50.

When a hall call occurs, first, in step A1.0, all the generated hall calls are read from outside. And step A
20 and A80. Step A:30 and A,70 perform the following processing money loop calculation.

In other words, if a hall call occurs, this call is assigned to the elevator that is most suitable in terms of minimizing long-waiting calls. (
Step A60).

FIG. 10 is a processing flow of the long-waiting call minimum call allocation algorithm. In order to fully determine which elevator is optimal, loop processing is performed using the number of υ elevators in steps A30-1, A, and 50-6. In the process in the loop, first, in step A30-2, the maximum predicted waiting time T□X of the allocated hall call on the front floor including the generated pole call is calculated. Note that the predicted waiting time is the sum of the hall call elapsed time (see FIG. 6), which indicates the elapsed time from the occurrence of the hall call to the present time. In the next step A30-3, the stop call evaluation value Tc is calculated from the stop calls on the predetermined floors before and after the generated pole call, and the evaluation function φ is calculated using this evaluation 1llIi direct and the maximum predicted waiting time %z mentioned above. is calculated (step A30-4). Then, select the smallest elevator f in this evaluation function φ (A5 (1-5). If the above process is executed for all elevators, the elevator with the optimum evaluation will be found by the calculation in step A30-5. selected.

Next, run the stop probability calculation software program in the 11th
12.

FIG. 11 is a program for calculating the number of elevator direction reversals. First, in step IIO, an elevator whose direction has been reversed is detected in the elevator status table, and in step I20, 1 is added to the number of direction reversals of the elevator whose direction has been reversed. In step I30, the updated number of direction reversals is stored in the direction reversal table.

FIG. 12 is a program for calculating the stop probability that is activated every time the traffic demand signal changes.

In step I (10, traffic demand on -day is classified into seven types: dispatch, before lunch, during lunch, after lunch, normal, normal congestion, and quiet. In step I (20), direction reversal table SF8
The number of directional reversals Σ for all elevators is determined from Σ, and in step 30, all floors j are initially set in order to determine the stop probability for each direction.

In step 1 (40), in order to obtain the stop probability for each direction, the direction money is first set to UP.

Next, in step 50, it is determined whether floor j is the second floor or not. If it is not the top floor, step 1, step I ((30, add 1 to floor j. If, If it is the top floor, in step 70, the floor j is changed from Hatsumoe-Hisotoshi-kata-JD Zen UI) to D6°.

(-+7)ffl, add floor jvko1 at K2O.

In step 80, how many people are boarding the train for each floor (j1 direction) of the traffic volume table? and the number of neighbors T? And the probability of stopping P based on the total number of direction reversals Σ of all elevators? 'Find fc.

Here, α and β are coefficients. At step 90,
Determined stopping probability 1) j and stopping probability learning table S■i''
From the stop probability 91 found in the past in 10, a new stop i1fjif<Q+ kQ+ = r-Pj-1
-(1-r)Q+. Here r is a coefficient. This result is Q? is stored in the stop probability learning table 5FIO as the learned stop probability.

Next, in step 100, if the floor J is the top floor and the direction is D swa, then all the stop probabilities Q? has been determined, and in the next step 110, the direction reversal table and the traffic volume table are cleared and the process ends. If this is not the case, since the stop probability Qj of all C has not been determined, the stop probability QV is determined by setting the stop probability Qj to 50 in step 7'.

According to the present invention, compared to the conventional predicted arrival time calculation method, the predicted time for the elevator to arrive at the hall called floor is
can be determined accurately. As a result, long waiting times are shortened,
This has the effect of reducing average waiting time.

[Brief explanation of the drawing]

1 to 4 are hardware configuration diagrams of an embodiment of the present invention, FIG. 5 is an overall software configuration diagram of the present invention,
6 and 7 are table configuration diagrams of FIG. 5, FIGS. 8 to 10 are operation control program flowcharts, and FIGS. 11 and 12 are stop probability calculation program flowcharts that are the center of the present invention. It is. MA...Elevator group management device, I-IL)...Hall call device. $ 1st Ell)l 1Ji)Z
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Claims (1)

[Claims] 1. A plurality of elevators operating between multiple floors, a pole calling device provided at each floor landing for calling the elevators, and a destination floor provided in each elevator car. A means for collecting traffic money within the pole, a means for calculating signals for classifying traffic demand based on the characteristics of the traffic volume or time signals, etc. means for selecting an elevator to service, in group management control for allocating a pole call to the elevator selected from the plurality of elevators, means for calculating the number of times the elevator reverses direction; This elevator group management device is patented as having a means for collecting internal traffic data and a means for calculating the probability that the elevator will stop for each floor and direction from this means. 2. Permissible sW Scope In the first term, the means to calculate the number of times the elevator reverses direction, the means to collect all the traffic volume in the pill, and the means to calculate all the probability that the elevator will stop for each floor direction are: , an elevator group management device characterized by being configured to be aggregated by traffic demand. 3. In claim 2, the elevator stop probability determined by traffic demand, direction, and floor, and the elevator stop probability determined for the same traffic demand, same floor, and same direction. An elevator group management device characterized by learning by calculating a new stop (11a rate) from a probability. 4. Scope of claims An elevator group management device N0 characterized in that it is equipped with means for selecting an elevator that services a pole call according to an evaluation function used as a fully variable elevator stop probability parameter.