WO2016070937A1

WO2016070937A1 - Method for controlling an elevator system

Info

Publication number: WO2016070937A1
Application number: PCT/EP2014/074080
Authority: WO
Inventors: Janne Sorsa; Marja-Liisa Siikonen; Mirko RUOKOKOSKI
Original assignee: Kone Corporation
Priority date: 2014-11-07
Filing date: 2014-11-07
Publication date: 2016-05-12

Abstract

The invention relates to a method for controlling an elevator system (10) comprising at least one elevator group having several elevators (14), in which method an elevator control (12) uses an call allocation unit for allocating elevators to floor calls, in which allocation unit (20) the travel length of the elevators for servicing the pending calls is considered as an optimization criterion for the call allocation. By introducing the travel length of the elevator system to serve all pending calls as a parameter in the allocation decision, an elevator system is created which offers better energy saving potential and better information about past, current and future energy consumption.

Description

Method for controlling an elevator system

The present invention relates to a method for controlling an elevator system comprising at least one elevator group having several elevators. Usually, in such elevator groups an elevator control controlling the elevators of said at least one elevator group uses an allocation unit using an allocation algorithm for allocating the elevators to floor calls given by passengers. Generally, the allocation algorithm of the elevator system uses a cost function which considers several allocation parameters as for example passenger riding time, passenger waiting time, energy consumption, elevator load, etc. Eventually certain allocation rules are applied in the elevator traffic between different groups, e.g. at transfer floors. In finding the optimal allocation solution, these parameters are weighted by weighting factors to obtain the costs of an allocation decision of the allocation algorithm. Usually, the allocation algorithm comprises an optimization algorithm, e.g. a genetic algorithm leading to a best allocation solution associated with the lowest costs of the cost function. This allocation solution is then used to serve the pending elevator calls. Whereas the energy consumption of the elevator system is already a widespread goal in allocation algorithms, the present procedure is not satisfactory with respect to the general purpose of reducing any effort connected with the elevator system.

It is therefore object of the present invention to provide a method for controlling an elevator system which has the potential to lead to lower operation costs of the elevator system. The aim of the invention is also to provide an elevator system with lower operation costs, e.g. a reduced maintenance demand and/or energy consumption.

The object of the invention is solved with a method according to claim 1 and with an elevator system according to claim 12. Preferred embodiments of the invention are subject-matter of the dependent claims. In advance the function of an allocation unit shall be described: The call allocation in the allocation unit is performed in an optimization process by an optimization algorithm. Thereby several allocation solutions are generated e.g. by an allocation algorithm in the allocation unit. For the evaluation of the suitability of each allocation solution the optimization algorithm uses a cost function which considers allocation parameters which are deemed important to be considered in the service provided by an elevator system. These parameters may comprise e.g. service time, energy consumption, elevator load and now, according to the invention, travel length. The optimization algorithm establishes for each allocation solution the correlated costs according to the cost function and selects the allocation solution with the lowest costs as best allocation solution, which forms the allocation decision. The pending calls are then served by the elevators according to the allocation decision, which need a certain amount of travel length to service the calls.

According to the present invention, the new parameter "travel length" is introduced in the optimization process for the selection of the best allocation solution. This travel length of all elevators to serve the pending calls in connection with call allocation solution as an optimization criterion is an important improvement to call allocation. The consideration of travel length in the optimization process serves not only the reduction of energy consumption but particularly also the reduction of maintenance costs and the reduction of wear of the moving components of the elevator system. Until now the energy consumption has already been regarded as an optimization parameter in call allocation. Hereby the electric power used by the components of the elevator system has been considered as the essential quantity. Anyway, this goal is limited because it has not a direct effect to the amount of use of the moving components in the elevator system in total. Energy optimized solutions need not necessarily be solutions which provide minimized movements of the elevator components in the elevator system. Therefore, the consideration of travel length as an optimization criterion in call allocation first time considers the total use of the components in the elevator system and thus reduces wear and maintenance thereof. The term "travel length" designates the length of travel of all elevators which is necessary to service the pending calls in course of an allocation process in the allocation unit. The term "accumulated travel length" designates the travel lengths of all elevators since a certain date (e.g. date of putting into service, date of modernization, day, start of a new call allocation process) stored in a data processing unit of the elevator system. In reality the selection of routes for the elevators to serve landing calls during call allocation is a dynamic flowing process as with each new issued call the call allocation is started anew whereby older decisions may be altered.

The minimization or optimization of the travel length of the elevators in the optimization process of call allocation can be realized in different ways.

In one embodiment, the pending calls are allocated to the elevators of the elevator system by minimizing the travel length as a parameter of a cost function in the optimization algorithm of the allocation unit. Via this way, the elevator control always ensures that always a call allocation solution is selected which leads to a reduced length of the elevator travel compared with known methods. E.g. in the cost function the weighting factor of the travel length parameter may have a higher value than the weighting factors of possible other allocation parameters of the cost function of the optimization algorithm, e.g. service time, energy consumption, elevator load.

In another embodiment of the invention, the accumulated travel length of all elevators is measured beginning from a preset starting point. From this point on, the increase of the accumulated travel length is considered for each allocation decision so that the increase to the accumulated travel length by the travel length of the elevators to serve the pending calls is minimized. This method has the advantage that the use of the elevator system gets information about the total travel length provided by the elevator system from a preset date on (e.g. the date of installation, modernization, day, new allocation pro- cess) which may be an important factor in the evaluation of the efficiency and the usage of the elevator system.

The call allocation performed according to the present invention may of course consider the current and/or estimated traffic situation and may comprise the option to set one or more elevators of the elevator system into a standby mode as to save travel length. Accordingly, the minimization or optimization of the travel length in an optimization process can also include the changing of the operating status of an elevator in the elevator system.

One advantage of the invention is that it can be realized very simple. In a preferred simplest solution no energy or other extra measuring devices is needed. The unit of "travel length" can be simply measured via "floors" (or "meters" which can anyway be calculated easily when the floor height of the different floors is the same in the building), or "number of travelled floors" which can be easily calculated in an elevator control (or "elevator group control" which term is used in this application as a synonym to "elevator control").

Of course, an allocation decision is not performed isolated without regard of all the other allocation parameters as waiting time, travel time, energy consumption and elevator load. Therefore, preferably, the travel length is introduced in a multipurpose decision of the elevator control with a high priority. Accordingly, the weighting factor for the travel length parameter may e.g. be higher than the weighting factor of the other parameters or higher than the weighting factor of at least the half of the other parameters.

In one preferred embodiment of the invention, at least two non-commensurable quantities, e.g. even contrary to each other, i.e. service time and travel length, are optimized. In order to render these quantities commensurable and mutually comparable, the routes R of the elevators are preferably so chosen that the cost term J=W_T · T_N(R)+ W_L ( 1) is minimized. T_N(R) is a normalized sum of call times for route alternative R, and correspondingly L_N(R) is the normalized travel length (=travel length of all elevators) to serve the calls associated with route alternative R. W_T and W_L are weighting coefficients of the above-mentioned cost term, so that

The individual waiting times are exponentially distributed, but their sum T(R) approximately follows the normal distribution, which means that they permit the application of normalization T_N(R)=(T(R)^_T)/O_T. Similarly for the travel length term L_N(R)=(L(R)-

The expectation values μ and average distributions σ are the characteristic numbers of the entire set of targets, i.e. of the route alternatives applicable in the current call situation. In practice, because the number of route alternatives grows exponentially with the number of active landing calls, it is necessary to make do with sample quantities: instead of an expectation value, sample averages T and ^ are used, and instead of a standard deviation, sample standard deviations S_T and S_E are used. This yields T_N =

(T(R)- T (R)/S_T(R) and L_N(R) « (L(R)- ^L (R))/S_L(R), where R is a number of stochastically generated route alternatives that is sufficient to produce reliable estimators for μ and σ. After normalization, both optimization goals show approximately the distribution N(0, 1), and thus they can be summed without problems.

When landing calls are allocated in this way, two extreme points can be observed in the operation of the system, i.e. a situation where W_T=1 and W_L=0, and a situation where W_T=0 and W_L=1. In the first situation, the optimization process finds elevator routes such that the total waiting time for the calls is as short as possible. In the second situation, the optimization process devises the routes so as to minimize the travel length of the elevators. Of course, the weighting factors for the cost function will be chosen to adequately consider the minimization of the travel length goal as well as the elevator comfort, implemented by the service time goal, i.e. they will be usually assigned values between 0,2 and 0,8. Of course further parameters can be regarded in the cost function, as e.g. the energy consumption, which would result in following cost function:

J = W_T · T_N(R) + W_L · L_N(R) + W_E · E_N(R) (3) with E_N(R) is a normalized energy consumption associated with route alternative R and W_E is the correlated weighting coefficient for the energy consumption in the above- mentioned cost term. This cost function covers a three parameter goal. Of course

W_T + W_L + W_E = 1 (4).

0 < W_T < 1

0 < W_L < 1

0 < W_E < 1

The quantity used as service time may be e.g. the call time, passenger waiting time, passenger travel time or passenger riding time. This solution considers the elevator comfort without using a multi-goal cost function according to the above embodiment of the invention.

In another preferred embodiment of the invention which also considers the service time goal in the above sense for the allocation of landing calls a target value is assigned to a given service time of the elevator group. Landing calls are then so allocated that the assigned target value of service time is achieved on the average, the energy consumption of the elevator group being thus reduced.

By considering the travel length in the allocation of elevators to floor calls not only the energy consumption is affected in a positive way but also the total travel length of the elevator is reduced which leads to reduction in the maintenance effort and wear of the elevator system. In one preferred embodiment of the inventive method, an average energy consumption of an elevator together with its travel length are measured in a test run and from these results an estimated specific energy consumption per travel length of the elevator is derived. This is advantageous as from the estimated specific energy consumption/travel length the company operating the elevator system can estimate from the accumulated travel length the total energy consumption since the preset date. On the other hand, the elevator system is able to use the estimated specific energy consumption per travel length in connection with estimated traffic forecast of a forecast unit of the elevator control to predict the energy consumption of the elevator system in the future. This is a valuable information for the owner or operator of the elevator system.

When a test run is performed for obtaining the estimated specific energy consumption per travel length, the elevator system could be modified to minimize its specific energy consumption per travel length. This could for example be realized by running an optimization process in the elevator allocation algorithm, for example under use of a genetic algorithm. The modified data can then be used to repeat the test run to verify whether the modification of the elevator system has indeed led to reduced estimated specific energy consumption per travel length. Via this measure an effective reduction of the energy consumption of the elevator system can be realized in an optimization process. In the optimization process also a model of the elevator system can be used to estimate the impact of the modifications on the elevator system. Of course, as mentioned above, the parameter of the travel length is not the only parameter which is to be considered in an allocation decision. Therefore, preferably, a target value for a service time of a floor call is defined. The service time is for example the waiting time for a passenger from issuing a call until arrival of an elevator to serve the call. Depending on the difference between the target value and the measured value for the service time, the weighing factors of the cost function are modified and/or one or several elevators are set into a standby mode. This step ensures that the service time of the elevator which is an essen- tial parameter in the comfort provided by an elevator system is not affected too much by the optimization of the travel length.

Accordingly, the minimization of the travel length can be limited depending on the difference between the target value and the measured value of the service time. If for example this difference becomes too much, the weighting factor for the travel length in the allocation decision can be reduced.

Also the usual known allocation parameters maybe considered in the allocation procedure aside of the travel length, which e.g. comprise the service time, i.e. passenger riding time, passenger waiting time, total travel time of the passenger, the energy consumption as well as the elevator load.

As already mentioned above, the invention adds the travel length as an important parameter in the allocation decision whereby these other allocation parameters may be considered according to accordingly selected weighting factors in the cost function of the allocation algorithm.

The present invention also refers to an elevator system comprising at least one elevator group controlled by an elevator control, which elevator control comprises an allocation unit for allocating elevators of the elevator group to floor calls. The allocation unit comprises an optimization algorithm using a cost function which considers several allocation parameters, weighted by weighting factors to obtain the costs of an allocation decision as the decisive factor for the optimization algorithm. The allocation unit has a module which calculates for each allocation solution the travel length of all elevators for servicing the pending calls. Finally, the optimization algorithm in the allocation unit is configured to consider the additional travel length as an optimization criterion. With respect to the function and advantages of the invention it is referred to the description of the inventive method. Preferably, the elevator control comprises a calculating unit for summing up the accumulated travel length of all elevators starting from a preset date and the travel length of the allocation solution selected in the optimization algorithm is added to the accumulated travel length. The allocation unit uses an optimization algorithm utilizing a cost function which considers for each allocation solution several allocation parameters, weighted by weighting factors to obtain the costs of the allocation solution as the decisive criterion in the optimization process (algorithm). The allocation unit is configured to modify the weighting factors of the cost function and/or to set elevators into a standby mode in order to minimize the travel length caused by the serving of the pending calls according to the selected allocation solution.

The inventive elevator system is configured to minimize the total accumulated travel length of all elevators of the elevator system during operation of the elevator system. Furthermore, this elevator system facilitates the calculation of past and future energy consumption. In connection with a traffic forecast this elevator system according to the invention facilitates the prediction of future operation costs of the elevator system.

Preferably, the elevator system comprises a test unit for measuring an average energy consumption and the corresponding travel length of an elevator in a test run to obtain an estimated specific energy consumption per travel length of the elevator system. This value provides the owner or operator of the elevator system with valuable information about the efficiency of the elevator system as well as with the option to easily calculate past and future costs of the elevator system caused by maintenance, wear and energy consumption.

Preferably, the elevator system comprises a forecast unit for the expected traffic of the elevator system and a forecast calculating unit for calculating an expected future energy consumption of the elevator system. The forecast calculating unit is connected with the allocation unit and with the test unit and is configured to calculate a future energy demand based on the relationship between the estimated specified energy consumption per travel length, the accumulated travel length and the expected traffic from the forecast unit.

The inventive content of the invention may also consist of several separate inventions, especially if the invention is considered in the light of expressions or implicit subtasks or from the point of view of advantages or categories of advantages achieved. In this case, some of the attributes contained in the claims below may be superfluous from the point of view of separate inventive concepts.

Furthermore, it should be clear for the skilled person that the features mentioned in the claims may be provided as a single component or as multiple components and further can be provided as a central unit or as units distributed over the elevator system. Of course, the allocation unit is normally a part of the elevator control but the allocation unit can also be a separate part which is connected to the elevator control, for example a plug-in module. Preferably, the allocation unit comprises an own processor and memory necessary for performing the call allocation process in the elevator system. The allocation unit usually comprises an allocation algorithm and optimization algorithm, which can be implemented separately or in one program, e.g. in a genetic algorithm.

Furthermore, it should be clear for the skilled person that allocation algorithms and/or optimization algorithms may differ what has been presented. For example, it is possible to solve optimization problem of the invention by defining partial objective/cost functions, calculate total cost based on those functions and selecting the solution which gives smallest total cost in the view of target(s).

The above-mentioned embodiments of the invention can be combined with each other as long as they do not interfere with each other.

The invention is described in the enclosed drawing via an example. This shows a schematic diagram of a part of an elevator system. The elevator system 10 according to Fig. 1 comprises an elevator control 12 which is connected to several elevators 14 of one or several elevator groups. The elevator control 12 is connected or comprises a calculating unit 16 for summing up the accumulated travel length of all elevators 14 in the elevator system 10 as well as a test unit 18 which is intended to perform drive tests with elevators 14 to obtain their energy consumption in connection with their travel length to obtain an estimated specific energy consumption per travel length. Integrated in the elevator control 12 is an allocation unit 20 comprising a module 22 which calculates for each allocation decision a travel length of all elevators for servicing the pending calls as well as optionally a forecast unit 24 which provides statistical data about the elevator system operation in the past and with a calculator to obtain or estimate future behaviour of the elevator system.

The elevator control 12 obtains from the elevators 14 the current power demand via a first connecting line 26 as well as the location and/or movement data of the elevators via a second connecting line 28. Of course, in practice, these different connecting lines can be realized by a common serial bus to which the different data are transmitted in a per se known way.

The above-mentioned elevator system is able to calculate via the test unit 18 an estimated specific energy consumption per travel length of the elevator system by running the elevators 14 in a test run for a set period of time and to measure via the connecting lines 26 and 28 their energy consumption and correlated travel length. In some cases test run procedure may include test runs with different car loads and/or between different floors. Via these data it is possible for the elevator control 12 to establish an estimated specific energy consumption per travel length of the elevator system.

The calculating unit 16 sums up the travel length of the elevators for servicing the elevator calls starting from a preset date (e.g. the date of installation or modernization or putting into service or the beginning of a new call allocation process). The call alloca- tion in the allocation unit is performed in an optimization process by an optimization algorithm. Thereby several allocation solutions are generated by an allocation algorithm. The optimization algorithm establishes for each allocation solution the correlated cost according to the cost function of the call allocation process and selects the allocation solution with the lowest costs as allocation decision. The calls are then served according to the allocation decision. The allocation algorithm in the allocation unit 20 calculates in connection with the module 22 for each allocation solution in the optimization process the travel length of all elevators to service the pending calls. After servicing the calls according to the selected allocation decision the travel length of the allocation decision is added to the accumulated travel length stored in the calculating unit 16 of the elevator system. The optimization or minimization of travel length for servicing the pending calls according to the allocation decision enables the owner or operator of the elevator system to run the elevator system with a reduced amount of elevator travel which leads on one hand to a reduced energy consumption and on the other hand to reduced maintenance demand and wear of the moving components of elevator system.

The above-mentioned embodiment should not be understood as delimiting for the present invention. The invention can be carried out within the scope of the appended patent claims.

Claims

Claims:

1. Method for controlling an elevator system (10) comprising at least one elevator group having several elevators (14), in which method an elevator control (12) uses an call allocation unit for allocating elevators to floor calls, in which allocation unit (20) the travel length of the elevators for servicing the pending calls is considered as an optimization criterion for the call allocation.

2. Method according to claim 1, wherein the allocation unit uses an optimization process utilizing a cost function, which cost function considers several allocation parameters weighted by weighting factors to obtain the costs of an allocation solution as a decisive factor in said optimization process, in which cost function the travel length is introduced as an allocation parameter together with a corresponding weighting factor.

3. Method according to claim 1 or 2, wherein one or several elevators (14) are set into a standby mode depending on the current traffic situation and/or estimated traffic situation.

4. Method according to one of the preceding claims, wherein the accumulated travel length of all elevators (14) of the elevator system (10) is measured starting from a preset date and the travel length of an allocation solution selected in the optimization process is added to the accumulated travel length.

5. Method according to claim 4, wherein an average energy consumption of an elevator (14) together with its travel length are measured in a test run and wherein from these results an estimated specific energy consumption /travel length of the elevator system (10) is derived.

6. Method according to claim 5, wherein the estimated specific energy consumption/travel length is used together with statistical data on traffic forecast to obtain an estimated future energy consumption of the elevator system (10).

7. Method according to claim 5 or 6 wherein the control of the elevator system (10) is modified to minimize its specific energy consumption/travel length.

8. Method according to claim 7, wherein after the modification of the elevator system (10) the test run is repeated.

9. Method according to one of the preceding claims, wherein a target value for a service time of a floor call is defined, and wherein depending on the difference between the target value and the measured value for the service time the weighing factors of the cost function are modified and/or one or several elevators (14) are set into a standby mode.

10. Method according to claim 9, wherein a minimization of the travel length is limited depending on the difference between the target value and the measured value of service time.

11. Method according to one of the preceding claims, wherein the allocation parameters comprise passenger riding time, passenger waiting time, energy consumption and elevator load.

12. Elevator system (10) comprising at least one elevator group controlled by an elevator control (12), which elevator control comprises an allocation unit (20) for allocating elevators (14) to floor calls, which allocation unit comprises an optimization al- gorithm and which allocation unit has a module (22) which calculates for each allocation solution the travel length of all elevators for servicing the pending calls, and in which allocation unit the optimization algorithm is configured to consider said travel length as an optimization criterion.

13. Elevator system according to claim 12, wherein the elevator control comprises a calculating unit (16) for summing up the accumulated travel length of all elevators starting from a preset date and the travel length of the selected allocation solution is added to the accumulated travel length.

14. Elevator system (10) according to claim 12 or 13, comprising a test unit (18) for measuring an average energy consumption and the corresponding travel length of an elevator (14) in a test run to obtain an estimated specific energy consumption/travel length of the elevator system.

15. Elevator system (10) according to claim 12, 13 or 14 comprising a forecast unit (24) for the expected traffic of the elevator system, and a forecast calculating unit for calculating an expected future energy consumption of the elevator system, which forecast calculating unit is connected with the allocation unit and with the measurement unit and is configured to calculate a future energy demand based on the relationship between the estimated specified energy consumption/travel length, the accumulated travel length and the expected traffic.

16. Elevator system (10) according to one of claims 12 to 15, wherein the elevator control and/or the allocation unit is configured to set one or several elevators (14) into a standby mode depending on the current traffic situation and/or estimated traffic situation.