JPH06156894A - Group control controller for elevator - Google Patents

Abstract

PURPOSE:To carry out the efficient operation control for an elevator by carrying out the group control by using the optimum operation control parameter for the traffic quantity data. CONSTITUTION:The variable parameter is calculated by comparing the elevator operation control function, in-building traffic quantity data collecting function, in-building traffic quantity data, and a plurality of traffic quantity data which is previously set. The operation control program performs call allotment by using the variable parameter. The variable parameter is calculated by using the getting-on/off passenger quantity information on each floor which can be obtained from the microcomputers E1-En for the respective No. machines, a plurality of traffic quantity which are previously set, and the instruction PM of a setting device PD. This calculation is processed in real time in each certain cycle, and the operation control parameter which is optimum for the elevator group control at each time is outputted. Accordingly, the efficient operation control for the elevator can be carried out.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an elevator group management device, and more particularly to an elevator group management control using a computer.

[0002]

2. Description of the Related Art A conventional group management device has been difficult to perform detailed group management control adapted to a traffic volume peculiar to a building.
There was a drawback that it was not possible to meet new traffic demand due to changes in the building structure, such as changing the complex building to a company-owned building or providing a connecting passageway with an adjacent building.

[0003]

DISCLOSURE OF THE INVENTION An object of the present invention is to provide an elevator group management device equipped with an in-building traffic volume collecting means for capturing traffic volume peculiar to a building, and group management operation adapted to the traffic volume peculiar to the building. An object of the present invention is to provide a group management device capable of calculating control parameters in a short time and generating new control parameters when new traffic demand occurs.

[0004]

The features of the present invention are, in a group management device for allocating hall calls to elevators, means for externally setting a target value of the traffic volume data, and a plurality of preset traffic volumes. (1 to m), the optimum traffic volume is obtained from the collected intra-building traffic volume, and among the traffic volume data (1 to n) corresponding to the optimum traffic volume, a plurality of traffic volume data similar to the target value To obtain the optimum traffic volume data, and to interpolate a plurality of operation control parameters set in advance corresponding to the traffic volume data,
A means for obtaining the optimum operation control parameter for the optimum traffic volume data is provided, and the group management control is realized by using this optimum operation control parameter for the evaluation function.

[0005]

Embodiments of the present invention will be described in detail below with reference to concrete embodiments shown in FIGS. In the description of the embodiments, first, the hardware configuration for realizing the present invention will be described, then the overall software configuration and its control concept will be described.
Finally, software for realizing the above control concept will be described with reference to a table configuration diagram and a flow.

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

The elevator group management apparatus MA compares the elevator operation control function, the in-building traffic volume data collection function, the in-building traffic volume data and a plurality of preset traffic volume data to calculate the above-mentioned variable parameters. There is a microcomputer M that controls the functions.

A circuit PIA (Periph) for inputting and outputting the call signal HC from the hall calling device HD in parallel is input to the microcomputer M.
The machine control microcomputers E1 to En that are connected via an eral interface adapter and that control individual elevators such as opening and closing doors and commanding car acceleration / deceleration (here, the elevator is the nth machine). ) Means serial communication processors SDA1 to SDAn and communication lines CM1 to CM
It is connected via n.

On the other hand, the signal PM from the setter PD that gives the command necessary for determining the variable parameter is input through the circuit PIA 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 safety limit switches for elevators, a control input consisting of relays and response lamps. Output element EI
A circuit PIA for inputting / outputting signals in parallel with O1 to EIOn is connected via signal lines SIO1 to SIOn.

The present invention will be generally described with reference to FIG.

The microcomputer M has a built-in operation control program mainly for call allocation, and this operation control program fetches information necessary for control from the respective unit control microcomputers E1 to En and the hall call HC. Further, the operation control program uses the variable parameters described above to perform call assignment. For example, this parameter includes a weighting coefficient indicating the relationship between the waiting time and the evaluation value of power consumption in the call allocation evaluation function, the time coefficient that determines the door opening / closing time, and the call allocation control logic, that is, the call allocation algorithm. There are control parameters to be selected.

These variable parameters are calculated using information on the number of passengers getting in and out of each floor obtained from the respective unit microcomputers E1 to En, a plurality of preset traffic volumes, and a command PM from the setter PD. This calculation is processed in real time at regular intervals, and the optimum operation control parameters for elevator group management are output from time to time.

For example, when the setting device PD is instructed to minimize the waiting time, first, the in-building traffic data from that time point to a predetermined time before is compared with a plurality of preset traffic data, and the preset data is set. Select the traffic volume data that is closest to the in-building traffic volume data from among the multiple traffic volume data, and set the parameter that realizes the shortest waiting time in the list of waiting time data in the selected traffic volume data. select. This parameter is used as the optimum operation control parameter for the current traffic in the building. Therefore, according to the present invention, the elevator group management control can cope with the ever-changing environmental conditions of the building, which greatly contributes to the elevator group management performance improvement.

Next, specific hardware configurations of the respective microcomputers will be shown, but these microcomputers can be simply configured as shown in FIGS. MPU, the center of the microcomputer
As the (Micro Processing Unit), 8-bit, 16-bit, etc. are used, and the 8-bit MPU is suitable because the machine control microcomputers E1 to En do not require much processing capacity. On the other hand, the elevator operation control microcomputer M is
Since it requires complicated calculation, it has excellent calculation ability.
A bit MPU is suitable.

As shown in FIGS. 2 and 3, each microcomputer has a ROM (Read Only Memory) for storing a control program and the like on the bus line BUS of the MPU and a RAM (for storing control data, work data, etc.). Randam Access Memory)
In addition, a circuit PIA that inputs and outputs signals in parallel, a dedicated processor SDA (SerialDa) that performs serial communication with other microcomputers.
ta Adapter) is connected.

In each of the microcomputers M, E1 to En, the RAM and ROM are composed of a plurality of elements depending on the size of the control program and the like.

In FIG. 2, the setting device PD is composed of a setting volume VR and an A / D converter for converting the analog output voltage of this VR into a digital value, and this output PM
Are taken into RAM from PIA.

In FIG. 3, as elevator control data, for example, a car call button CB, a safety limit switch SWL, a relay contact SWRy, and a car weight Weig.
ht is taken into RAM from PIA. On the other hand, the data calculated by the MPU is output from the PIA to control output elements such as the response lamp Lamp and the relay Ry.

Here, the hardware configuration of the serial communication processor SDA between the microcomputers used in FIGS.
As shown in FIG. 7, it is mainly composed of a transmission buffer TXB, a reception buffer RXB, a P / S for parallel / serial conversion of data and an S / P for reverse conversion thereof, and a controller CNT for controlling timings thereof. . The transmission buffer TXB and the reception buffer RXB can be freely accessed by a microcomputer to write data,
Can read. On the other hand, SDA is the controller CNT
Therefore, it has a function of automatically transmitting the contents of the transmission buffer TXB to the reception buffer RXB of another SDA via the P / S. Therefore, the microcomputer does not need to perform any transmission / reception processing, and can concentrate on other processing. This S
The detailed configuration and operation explanation regarding the DA are disclosed in Japanese Patent Laid-Open No. 56-3797.
No. 2 and JP-A-56-37973.

Next, a software configuration according to an embodiment of the present invention will be described. First, the overall configuration of the software will be described with reference to FIG.

As shown in FIG. 5, the software is roughly divided into operation control system software SF1 and optimum operation control parameter calculation system software SF2, both of which are processed by the microcomputer M.

The operation control system software SF1 comprises an operation control program SF14 for directly instructing and controlling elevator group management control such as call assignment processing and elevator distributed standby processing. As input information of this program, a machine control program (Fig. 1: microcomputers E1 to E)
Elevator control table SF11 of elevator position, direction, car call, etc. sent from
The hall call table SF12, the elevator specification table SF13 such as the number of elevators to be managed, and the optimum operation control parameter calculation system liftware SF2 are used for calculation.
The output optimum operation control parameters etc. are used as input data.

On the other hand, the optimum operation control parameter calculation system software SF2 is composed of the following processing programs.

(1) Building traffic data collection program S
F21: A program that mainly collects the traffic in the building by sampling the contents of the elevator call table and elevator control table online every predetermined period.

(2) Optimal traffic volume calculation and optimal operation control parameter calculation program SF25 ... Traffic volume data in the building collected for a predetermined time, a plurality of preset traffic volume data, and a target arbitrarily set by the building manager Enter the value
First, a traffic volume whose difference from the traffic volume within a building is within a reference value is selected from a plurality of preset traffic volumes. if,
If the difference between all the preset traffic volumes and the intra-building traffic volume is not within the specified standard value, the intra-building traffic volume among the traffic volumes obtained by adding and subtracting multiple preset traffic volumes Select the traffic volume with the smallest difference. This selected traffic volume is the optimum traffic volume at the present time. Next, based on the optimum traffic volume, operation control parameters that achieve the target value set by the building manager within a predetermined reference value are selected from the optimum traffic volume data. If there is no driving control parameter that achieves the target value within the predetermined reference value in the optimal traffic volume data, then among the driving control parameters obtained by interpolating multiple driving control parameters in the optimal traffic volume data, Then, the operation control parameter that minimizes the difference from the target value is selected. The selected operation control parameter is set as the optimum operation control parameter. As described above, this program outputs the optimum operation control parameter. Next, a table configuration used in one embodiment of the present invention will be described with reference to FIGS. FIG. 6 shows a table structure of operation control system software, which is roughly classified into an elevator control table SF11 and a hall call table S.
F12, the elevator specification table SF13. The table in each block will be described each time the operation control program described below is described.

FIG. 7 is a table structure of the optimum operation control parameter calculation system software, which is a building traffic data table SF22, a plurality of preset traffic data tables SF23, a target value table SF24, and an optimum operation control parameter table. It is composed of blocks of SF26.

Next, an embodiment of the software of the present invention will be described.

First, the program of the operation control system will be explained.
Next, the program of the optimum operating parameter calculation system will be described. Note that the program described below is a system program that divides the program into a plurality of tasks and performs efficient control, that is, an operating system (OS).
Shall be managed under. Therefore, the program can be started from the system timer or from other programs.

The flow of the operation control program is shown in FIGS. Among the operation control programs, two particularly important elevator arrival predicted time table calculation programs and call assignment programs will be described.

FIG. 8 is a flow of a program for calculating the estimated arrival time to an arbitrary floor of the elevator, which is the basic data for the waiting time evaluation calculation. This program is periodically activated, for example, every 1 second, and calculates the estimated arrival time from the current position of the elevator to any floor for all floors and for all elevators.

In FIG. 8, steps E10 and E90 are performed.
Indicates that loop processing is performed for all elevators. In step E20, first, an initial value is set in the time table T for work, and its contents are set in the estimated arrival time table in FIG. As an initial value, it can be considered how many seconds can be left after the door is opened and closed, and a predetermined time until the elevator is started when the elevator is stopped.

Next, the floor is advanced by one (step E3).
0), and it is compared whether or not the floor is the same as the elevator position (step E40). If they are the same, 1
Since the estimated arrival time table for each elevator has been calculated, the process jumps to step E90 and the same process is repeated for other elevators. On the other hand, if “NO” in the step E40, the first floor traveling time _Tr is added to the time table T (step E50). Then, this time table T is set in the estimated arrival time table (step E60). Next, it is determined whether there is a car call or an assigned hall call, that is, a call that the elevator of interest should service, and if there is, the elevator is stopped, so the stop time T _s is added once to the time table (step E80). Then step E
Jump to 30 and repeat the above process for all floors.

FIG. 9 is a flow of the call assignment program, which is activated when a hall call occurs.
In this program, the call allocation algorithm is the long waiting call minimization call allocation algorithm (described later in FIG. 10) as shown in step A50.

When a hall call is generated, first, in step A10, the generated hall call is read from the outside. And
In steps A20 and A80 and steps A30 and A70, the following processing is looped. That is, if there is a generated hall call, this call is assigned to the elevator that is optimal in the sense that the long waiting call is minimum (step A60).

FIG. 10 is a processing flow of the long waiting call minimum call assignment algorithm. In order to determine which elevator is optimal, a loop process is performed by the number of elevators in steps A50-1 and A50-6. In the processing in the loop, first, in step A50-2, the maximum predicted time Tmax of the assigned hall call on the front floor including the generated hall call is calculated. The predicted waiting time is the sum of the hall call elapsed time indicating the elapsed time from when the hall call is generated until the present time and the estimated arrival time (see FIG. 6). In the next step A50-3, the stop call evaluation value T _c is calculated from the stop calls of the predetermined floors before and after including the generated hall call, and the evaluation function φ is calculated from this evaluation value and the above-mentioned maximum predicted time Tmax ( Step A50-4). Then, the smallest elevator is selected in this evaluation function φ (A50-
4). When the above process is executed for all elevators, the elevator having the optimum evaluation value is selected by the calculation in step A50-5.

The processing flow of the estimated arrival time table calculation program and the call allocation program, which are the operation control programs, has been described above. In addition to these, the operation control program includes a service processing program for a plurality of vehicles to a congested floor and a traffic volume. There is a distributed standby processing program etc. that makes the elevator stand by at a predetermined floor when there is no traffic, but these explanations are omitted.

Next, a program of the optimum operation control parameter calculation system software will be described with reference to FIGS.

FIG. 11 is a flow of the in-building traffic data collection program.

First, at step SA10, the number of passengers and the number of passengers getting on the stopped elevator are measured.
Next, in step SA20, in the elevator direction,
SA30 detects the stop floor. By updating the in-building traffic volume G (i, j, k) from the above measurement data,
The traffic volume in the building can be collected (step SA40).

12 to 16 show a program which is the point of the optimum operation control parameter calculation system.

This program is executed for a predetermined time (for example, 10
Min) has elapsed and the current tendency of the traffic volume in the building is extracted by comparing and interpolating a plurality of preset traffic volumes. Next, the optimum driving control parameters for the extracted trends are calculated, and the optimum driving control parameters for each traffic volume of a plurality of preset traffic volumes are obtained in advance by a simulation method or the like. And stored in a plurality of preset traffic volume data tables SF23. The operation control parameters include a forecasted parameter for full capacity, which has a large impact on service performance due to traffic demand, and a stop probability parameter for each floor or direction required to accurately determine the estimated arrival time required for an elevator to reach the hall calling floor. , Lockout parameters for preferentially assigning the above generated hall call to elevators with car calls at the generated hall call floor, elevators with hall calls or car calls on consecutive floors, Area priority parameters for preferentially allocating hall calls generated on nearby floors, door opening / closing time control parameters for controlling door opening / closing times, priority service level parameters for preferentially servicing crowded floors Etc. The above-mentioned operation control parameters vary greatly not only with traffic demand but also with patterns such as attendance and normal times.

Next, the basic idea of the optimum operation parameter calculation will be described.

First, the in-building traffic volume is compared with a plurality of preset traffic volumes, and the traffic volume having the most similar traffic demand and parameters is selected from among the preset traffic volumes, If the similarity is within a certain standard value,
The current intra-building traffic volume is considered to be the same as the selected traffic volume, and the driving control parameters for the selected traffic volume are used as the optimal driving control parameters for the current intra-building traffic volume. However, if the similarity is not within a certain reference value, the traffic demands and patterns selected above are interpolated between multiple traffic volumes in the vicinity of the traffic volume considered to be the most similar, and Create a traffic volume that is similar to the traffic volume. As the operation control parameter, the operation control parameter for the created traffic volume is created by the same interpolation calculation as above.

As described above, by interpolating not only the preset plurality of traffic volumes but also the drive control parameters for the preset multiple traffic volumes, the optimum operation control parameters for the current intra-building traffic volume are obtained. Is the important point of this patent.

Referring to FIG. 12, first, at step SB1, the in-building traffic volume table G (i, j,
k) (where i ... passenger table or descending person table, j ... elevator direction, k ... indicate elevator stop floor) and m preset traffic volume H (i, j,
k, l) (l = 1, ..., m) is compared and the optimum traffic volume H
Determine (i, j, k, l *). In step SB2, the optimal traffic control parameters are determined by comparing the optimal traffic volume H (i, j, k, l *) table with the target value table.

Next, FIG. 13 shows step SB1 of FIG.
It is a program that explained.

First, in step SB1-1, the building traffic volume G (i, j, k) and m preset traffic volumes H are set.
(I, j, k, l) (l = 1, ..., m) difference E (i, j,
Calculate the square of k, l). In step SB1-2,
The variable I (indicating the number of passengers or the number of passengers) is squared by E (i, j, k, l), and step SB1−
In 3, the variable J (elevator direction Up or Down) is squared with E (i, j, k, l), and in step SB1-4, the variable K (elevator stop floor 1 to 1) is calculated.
N) is squared with E (i, j, k, l), and in step SB1-5, traffic volume G (i, j, k) in the building is calculated.
And a preset traffic volume H (i, j, k, l) (l = 1,
m) the sum of squares of the difference S (l) (l = 1, ... 0 ..., m). Next, in step SB1-6, m S
The minimum value Min (l *) is obtained in (l), and it is determined that the l * th traffic volume H (i, j, k, l *) is the closest to the intra-building traffic volume. At step SB1-7, Min (l *)
Is smaller than the reference value ST. As a result,
If it is within the reference value, the preset traffic volume H (i, j,
k, l *) is equated with traffic in the building (step SB
1-9), and step SB1 is ended. But Min
When (l *) is larger than the reference value ST, the preset traffic volume H (i, j, k, l *) is not identified with the intra-building traffic volume, and is preset in step SB1-8. Interpolation calculation is performed on the plurality of traffic volumes to create a traffic volume within the reference value ST.

FIG. 14 illustrates a program for interpolating the preset traffic volume in step SB1-8 of FIG.

In step SB1-8-1, the traffic volume G (i, j, k) in the building and H (i, j, k, preset) are set.
1) and E (i, j, k, l2) and E (i, j, k, l2) having different signs are determined in the difference E (i, j, k, l) There is. If it exists, the building traffic volume G (i, j, k) is equal to the preset traffic volume H.
Since it is in the middle of (i, j, k, l1) and H (i, j, k, l2), the reference value ST
It can be created by interpolating the traffic volume within H (i, j, k, l *) as in the following equation (1).

H (i, j, k, l *) = α · H (i, j, k, l1) + (1-α) · H (i, j, k, l2) (1) (step) SB1-8-3).

The difference E (i, i) between the traffic volume G (i, j, k) in the building and the preset traffic volume H (i, j, k, l)
If there is no difference (i, j, k, l) with different signs in (j, k, l) (l = 1 to m), the traffic volume H that satisfies the reference value ST even if interpolation is performed. Since (i, j, k, l *) cannot be created, the minimum value S (l *) of the sum SCl of the squares of the difference E that is the calculation result of step SB-6 in FIG. The preset traffic volume H (i, j,
Identifies k, l *) as traffic in the building. However, since the traffic volume in the building will be examined in detail when the building is completed, the upper and lower limits of the traffic volume in the building can be predicted.

From this result, if the upper and lower traffic volumes are also set in advance, the traffic according to the method of this patent can be identified with the intra-building traffic volume G (i, j, k) with high accuracy in practical use. It can be created by comparing or interpolating quantities.

In step SB1-8-4, the average waiting time T _{l *} q and the long waiting rate P _{l *} q in the traffic volume H (i, j, k, l *) created by interpolation in the equation (1). , Power consumption PW
_{l *} q (q = 1 to n) is a preset traffic volume H (i,
j, k, 11) and H (i, j, k, 12) average waiting times T ₁ q and T ₂ q, long waiting rates P ₁ q and P ₂ q, and power consumption value P
W ₁ q, PW ₂ q (q = 1 to n) and a positive number α are used to interpolate as in the following equations (2) to (4).

T _{l *} q = αT _l1 q + (1-α) T _l2 q (q = 1 to n) (2) P _{l *} q = α T _l1 q + (1-α) P _l2 q (q = 1 ~ N) (3) PW _{l *} q = α PW _l1 q + (1-α) PW _l2 q (q = 1 to n) (4) Similarly, the above T _{l *} q, P _{l *} q, PW _{l *} q (q = 1 to n)
The operation control parameter for realizing is also obtained by interpolation as in the following equations (5) to (8) using the positive number α. Area priority parameter K _{l *} q (q = 1 to n) is K _{l *} q = αK _l1 q + (1-α) K _l2 q (5) Door opening / closing time control parameter D _{l *} q (q = 1 to n) n) is D _{l *} q = αD _l1 q + (1-α) D _l2 q (6) The full capacity prediction parameter F _{l *} q (q = 1 to n) is F _{l *} q = αF _l1 q + (1 -Α) F _l2 q (7) The stop probability parameter S _{l *} q (q = 1 to n) is S _{l *} q = αS _l1 q + (1-α) S _l2 q (8) Step SB1-8 -6, step SB1-
Traffic volume H (i, j, k, l created in 8-3
It is determined whether the square of the difference between *) and the traffic volume G (i, j, k) in the building is smaller than the reference value ST. If it is small, the optimum traffic volume and the positive number α have been obtained. However, if it is larger than the reference value ST, 0.1 is added to the positive number α in step SB1-8-7, and the equation (1) is repeated to add 0.1 to the new positive number α to obtain the equation (1). ) Is repeated to interpolate a new traffic volume H (i, j, k, l *), and the above processing is repeated. In this way, the traffic volume H (i, j, k, l *) and the operation control parameter that are optimal for the traffic volume in the building were obtained.

15 to 16 are program flows for interpolating optimum operation control parameters for realizing the target values in the target value table SF24 externally set by the building manager or the like.

FIG. 15 is a flow chart of the operation control parameter calculation program for accurately achieving the target value when the target value is the average waiting time.

This program is a program for the case where the target value is the average waiting time, but with the same configuration, a program that can calculate the optimum operation control parameters even if the target value is the long waiting rate or the power consumption value is created. It is possible.

In step SB2-1, it is determined whether the target value is the average waiting time. If not, the process ends, and if it is the average waiting time, in step SB2-2, the average waiting time in the target value table and the optimum traffic volume H (i, j, k, l *).
2 of difference A (q) of average waiting time T _{l *} q (q = 1 to n)
Calculate the power A ² (q) {A ² (q) = (target value−T _{l *} q) ² , q
= 1 to n}, and in the next step SB2-3, A ² (q)
The minimum value Min (q *) is obtained among (q = 1 to n). In step SB2-4, it is determined whether Min (q *) is smaller than the reference value TU. If smaller, average waiting time T _{l *} q *
Is regarded as equal to the target value, and the operation control parameters that realize T _{l *} q * are optimized operation control parameters (area priority parameter K _{l *} q *, door opening / closing time control parameter D _{l *} q *, full capacity prediction parameter F). _{l *} q *, stop probability parameter S _{l *} q *
Etc.) (step SB2-6).

If not smaller, T _{l *} q (q = 1 to
n) is interpolated to produce optimum operation control parameters (step SB2-5).

FIG. 16 shows the optimum traffic volume H (i, j, k, l
If the squared difference between the average waiting time T _{l *} q (q = 1 to n) and the average waiting time target A ² (q) (q = 1 to n) in _* ) is larger than the reference value TU, T _{l *} q (q = 1 to n) is interpolated and the operation control parameters K _{l *} q, D _{l *} q, F _{l *} q, S _{l *} q (q
= 1 to n) is also interpolated, and the average waiting time T _{l *} q * and the operation control parameters K _{l *} q *, D _{l *} q *, F smaller than the reference value TU
_This is a program for obtaining _{l *} q * and _{Sl *} q *.

At step SB2-5-1, the difference A (q)
A (q1) and A (q
It is determined whether 2) exists. If not, the average waiting time target value is the optimum traffic volume H (i, j,
k, l *) average waiting time T _{l *} q (q = 1 to
n) means that the optimum operation control parameter is larger or smaller than that in step SB2-6 in FIG.
The operation control parameter selected in step 1 is used as the optimum operation control parameter. However, it can be seen that the average waiting time target value, if present, lies between the average waiting times T _{l *} q1 and T _{l *} q2. Therefore, in step SB-5-2, β
= 0, and in step SB-5-3, T _{l *} q1, T
_{Using l *} q2, Tl _* q * is calculated by the following equation.

T _{l *} q * = β T _{l *} q1 + (1−β) T _{l *} q2 Next, at step SB2-5-4, the operation control for realizing the newly created average waiting time T _{l *} q * is performed. Parameters are being calculated. That is, the area priority parameter K _{l *} q *, the door opening / closing time control parameter D _{l *} q *, the full-occupancy prediction parameter F _{l *} q *, etc. are K _{l *} q * = βK _{l *} q1 + (1-β) K _{l * q2 D l * q * =} βD l * q1 + (1-β) is determined to _{D l * q2 F l * q} * = βF l * q1 + (1-β) F l * q2. In step SB2-5-5, it is determined whether the square of the difference between the average waiting time T1 _* q * obtained in step SB2-5-3 and the average waiting time target value is smaller than the reference value TU. If not smaller, step SB2-5
At -6, 0.1 is added to β and the above process is repeated. If it is smaller, T _{l *} q * at that time is identified with the average waiting time target value, and the operation control parameters K _{l *} q *, D _{l *} q *, F _{l *} q *, etc. are set as the optimum operation control parameters. . This is the end of this program.

By performing group management control based on the optimum operation control parameters obtained by the above-mentioned optimum operation control parameter calculation system software, the elevator operation control desired by the building manager can be performed, and the building-specific control is possible. It turned out to be adaptable to the traffic volume.

In the optimum operation control parameter calculation system software, only the average waiting time is taken as an example of the target value, but a long waiting rate may be used, or power saving may be used if energy saving is performed.

In the above embodiment, when the difference between the collected traffic volume and the preset traffic volume is more than a predetermined value, the group management control parameter suitable for the traffic volume of the building cannot be determined. There is. However, in that case, if the group management control device is provided with a means for simulating group management control, the collected traffic volume can be calculated by the simulation means into suitable driving control parameters for all in-building traffic volumes. Is possible.

The embodiment of the present invention has been described above. The effect of the embodiment of the present invention will be described below.

As a first effect, a plurality of traffic volumes and optimum operation control parameters for the traffic volume (for example, an area priority parameter that minimizes waiting time, an area priority parameter that enables energy-saving operation, floors) And door opening / closing time control parameters set for each direction, full capacity prediction parameters, and stop probability parameters for accurately calculating the estimated arrival time required for the elevator to reach the hall call hall) and the number of elevator passengers Average waiting time when group management operation is performed under the above operation control parameters until
Service performance evaluation value such as long wait rate and power consumption value and economic evaluation value are set in advance, and a plurality of traffic volumes whose difference from the collected traffic volume in the building at the present time is below a certain reference value are set in advance. Traffic volume below a certain reference value is calculated by interpolating a plurality of traffic volumes selected or preset from among the above traffic volumes, and the optimum operation control parameters and the service performance evaluation value / economic evaluation value are also interpolated. Therefore, it is possible to obtain the optimum operation control parameter for the current traffic in the building. As a result, the group management device can be easily adapted to changes in the building environment, and this greatly contributes to shortening the average waiting time, reducing long waiting times, reducing the number of people occupied, and reducing power consumption.

As a second effect, since the optimum operation control parameter for the current traffic in the building is sought, the control delay is small and the building environment can be quickly changed.
The waiting time can be surely shortened.

As an effect of FIG. 3, by installing the target value setting device in the group management device, the building manager can perform the desired operation. For example, if you want to drive with an average waiting time of 20 seconds,
Optimal operation control parameters are interpolated, and if you want to reduce energy consumption by 10%, the area priority parameter that achieves 10% energy saving can be interpolated, so man-machine performance is significantly improved compared to conventional group management devices. is doing.

[0071]

As described above, according to the group management control of the present invention, it is possible to realize a highly efficient service performance or economic efficiency that a building manager desires, which responds quickly to the traffic volume peculiar to the building. It is possible to provide an elevator service with excellent man-machine characteristics.

[Brief description of drawings]

FIG. 1 is an overall configuration diagram of an elevator system.

FIG. 2 is a block diagram of a group management control device.

FIG. 3 is a configuration diagram of a machine control device.

FIG. 4 is a block diagram of SDA.

FIG. 5 is a diagram for explaining the overall configuration of software.

FIG. 6 is a table diagram of operation control system software.

FIG. 7 is a table diagram of optimum operation control parameter calculation system software.

FIG. 8 is a flowchart for calculating an estimated arrival time table.

FIG. 9 is a flowchart for long waiting call minimization assignment calculation.

FIG. 10 is a flowchart for long waiting call minimization assignment calculation.

FIG. 11 is a flowchart for collecting traffic in a building.

FIG. 12 is a flowchart of the entire optimum operation parameter calculation system software.

FIG. 13 is a flowchart for selecting a traffic volume whose difference from the traffic volume in a building is a predetermined reference value or less from preset traffic volumes.

FIG. 14 is a flowchart for interpolating a preset traffic volume, average waiting time, long waiting rate, power consumption value, and operation control parameter.

FIG. 15 is a flowchart for selecting the optimum operation control parameter for realizing the set target value.

FIG. 16 is a flowchart for interpolating an optimum operation control parameter that realizes a set target value.

[Explanation of symbols]

SB1 ... A portion for calculating the optimum traffic volume from the in-building traffic volume and a preset traffic volume, and SB2 ... A section for comparing the in-building traffic volume with a target value to determine the optimal operation control parameters.

 ─────────────────────────────────────────────────── ─── Continuation of the front page (72) Inventor ▲ Kudaku Kinuki Soshiro 3-1-1, Saiwaicho, Hitachi City, Ibaraki Hitachi Ltd. Hitachi Research Laboratory (72) Inventor Kenji Yoneda Katsuta City, Ibaraki Prefecture 1070, Ma, Mito Plant, Hitachi, Ltd.

Claims (1)

[Claims] 1. A traffic demand detecting means, a means for judging which traffic demand mode among a plurality of traffic demand modes registered in advance the output of the traffic demand detecting means, and the judged traffic demand mode. An elevator control device comprising means for determining a control parameter to be applied to the traffic demand corresponding to, and means for controlling a plurality of elevators serving for multiple floors according to the determined control parameter, When it is determined that the detected traffic demand is a new traffic demand mode that does not belong to any of the pre-registered traffic demand modes, means for generating new control parameters to be applied to this new traffic demand. An elevator group management device characterized by being equipped with.