Multi-car Elevator Research Articles

A study of linear PMSM driven ropeless elevators

In recent years, buildings have become taller and wider. The conventional approach of one roped elevator car per hoistway seems increasingly impractical. The idea of ropeless elevators using linear motors was proposed more than 30 years ago, but it was merely treated as wishful thinking by the industry at that time due to lots of safety concerns. And discussion by the industry has mainly been qualitative in nature. In recent years, an international manufacturer announced the development of a prototype and the world's first installation may probably be open to public before the end of 2018. So far, academic studies have mainly focused on the study of linear motors with generic applications, while this paper focuses on the performance of the motor drive from an elevator's point of view. In this paper, we investigate the mechanism of the drive, and the linear permanent magnet synchronous motor and, by discretizing the equations of the full mathematical model, we fine tune the parameters and design suitable controllers. We evaluate its performance by computer simulation, based on the necessary kinematics of a real elevator, so as to arrive at some design guidelines. Finally, the most critical safety concern, i.e. free fall during a total power failure, is quantitatively studied by short circuiting all motor windings. Methods to achieve a reasonably constant and low descending speed, have been studied with parameters estimated analytically, and are verified by simulation. For the sake of illustrating the concept as an initial trial, simplified circuit models, controllers and sensors are all assumed as being ideal. It is hoped that this paper will stimulate the research interest of both the academic world and the industry, while the inclusion of more losses, armature reactions, and imperfections, etc., could be tackled in a further study. Practical application: The application of one roped elevator car in taller and wider buildings seems increasingly impractical. This paper considers the analysis of the application of ropeless elevators using linear motors focusing on the performance of the motor drive from an elevator's point of view. A basic mathematical framework is developed to study and design the controllers and drive of a multi-car elevator system by using linear permanent magnet synchronous motors with emphasis on the elevator performance as a whole system. The paper is aimed at stimulating research interest to drive the appropriate analysis and application of linear permanent magnet synchronous motor driven ropeless elevators.

Trip-Based Integer Linear Programming Model for Static Multi-Car Elevator Operation Problems

Trip-Based Integer Linear Programming Model for Static Multi-Car Elevator Operation Problems

Group control of multi-car elevator systems without accurate information of floor stoppage time

A multi-car elevator system is an elevator system that has more than one car installed in each elevator shaft. This system enables us to improve the transportation capability without increasing the occupied floor space. The primary purpose of this study is to consider the group control problem of operating cars efficiently without collision nor reversal in a multi-car elevator system, based on a detailed and realistic model where floor stoppage time of cars cannot be known in advance. In the context of elevator systems, reversal means that a car travels in the direction opposite to the desired direction of on-board passengers, which is prohibited because it makes passengers uncomfortable. We first propose an optimization-based collision and reversal avoidance method to operate cars in the same shaft. Next, we construct simple methods to allocate calls to individual cars under immediate and delayed guidance policies. Under the immediate guidance policy a call is allocated to a car immediately after it is registered, while under the delayed guidance policy the allocation may be changed until it is actually served. The effectiveness of the proposed group control method is examined by computer simulation.

A Review of Multi-Car Elevator System

This paper presents a review of a new generation of elevator system, the Multi-Car Elevator System. It is an elevator system which contains more than one elevator car in the elevator shaft. In the introduction, it explains why the Multi-Car Elevator System is a new trend elevator system based on its structural design, cost saving and efficiency in elevator system. Different types of Multi-Car Elevator System such as circulation or loop-type, non-circulation and bifurcate circulation are described in section 2. In section 3, researches on dispatch strategies, control strategies and avoidance of car collision strategies of Multi-Car Elevator System since 2002 are reviewed. In the discussion section, it reveals some drawbacks of the Multi-Car Elevator System in transport capability and the risk of car collision. There are recommendations to the future work as well.

The Research of Multi-Car Elevator Control Method Based on PSO-GA

Multi-car elevator system is a new technique which can reduce the occupied area and improve the transport efficiency in the high-rise and super high-rise buildings. It is remain to be studied in both the control strategy and scheduling method compared with the traditional single elevator group control system, In order to improve the utilization rate and shorten the waiting time, the particle swarm algorithm PSO and GA genetic algorithm optimization control method are studied aiming at the rationality of scheduling strategy of the rationality of elevator. Combining the advantages of two algorithms proposed a novel optimal scheduling algorithm for PSO-GA and carried on simulation analysis, the experimental results demonstrate the effectiveness of the new method of improved PSO-GA.

A new active position sensing method for ropeless elevator

Traditional cable driven elevators perform poorly in high-rise buildings because the weight of the cable limits the payload, and its elasticity degrades control performance. Further, it is not mechanically possible to include several elevator cars in the same hoistway because of the cable. However such multi-car elevator systems are desirable since they reduce passenger waiting time and reduce the space requirements of the elevator system. A promising solution is to use long armature linear motors spanning the hoistway to directly drive elevator cages. In such applications, the mover position sensing method must be explicitly addressed since most active position sensing methods require traveling cables, which are also an obstacle for multi-car elevator systems.In this paper, the linear-motor active position sensing method is formally introduced and the principle of operation, design and real-time operation methods are presented. The proposed method is used to measure the position of the mover of a long armature permanent magnet linear synchronous motor requiring no active components on the mover, thus traveling cables are eliminated. The principle of operation is inspired by linear variable differential transformer: A magnetic shunt positioned at a fixed distance ahead of the mover deforms the magnetic field created by one of the armature coils. The deformation can be determined by measuring the induced voltages on the neighboring coils, and the position of the shunt, and thus the mover, can be calculated.A design method for the optimal dimensions of the shunt for a given armature to provide long measurement range and small maximum position error is presented, accompanied by a real-time measurement algorithm that will enable the motor to be driven using the method. Finally the method is verified by simulations and experimental results conducted on a full scale linear-motor elevator prototype that was constructed in the laboratory.

Performance Evaluation of an Option-Based Learning Algorithm in Multi-Car Elevator Systems

In this letter, we present the evaluation of an option-based learning algorithm, developed to perform a conflict-free allocation of calls among cars in a multi-car elevator system. We evaluate its performance in terms of the service time, its flexibility in the task-allocation, and the load balancing.

Assignment strategy selection for multi-car elevator group control using reinforcement learning

This paper discusses the group control of elevators in the web monitoring system for improving efficiency and saving energy; an efficient control method for multi-car elevator using reinforcement learning is proposed. In the method, the control agent selects the best strategy among three strategies, namely distance-strategy, passenger-strategy, and zone-strategy, according to traffic flow. The control agent takes the number of total passengers and the distance from the departure floor to the destination floor of a call into account. Through experiments, the performance of the proposed method is shown; the average service time of the proposed method is compared with the average service time for the cases where the car assignment is made by each of the three strategies.

Multicar-Elevator Group Control Algorithm for Interference Prevention and Optimal Call Allocation

The need to improve the efficiency of elevator systems is growing as higher buildings are being constructed. Increasing the number of elevators within a building is a commonly used strategy to achieve a greater passenger transportation capacity. However, the area required by elevator shafts limits the number of elevators that can be built. Multicar-elevator (MCE) systems, consisting of two or more elevator cars within a single shaft, have been proposed as a solution to increase the passenger transportation capacity without requiring extra space within the building. Yet, the implementation of MCEs requires the prevention of interference among elevator cars, which traditional group control methods are unable to achieve. Therefore, an MCE group control method that can perform an efficient allocation of service calls while preventing interference among cars is required. In this paper, we propose an MCE group control algorithm implementing an interference risk evaluation, a schedule-completion-time minimization function, and idle-car parking strategies. With our algorithm, we aim to achieve an efficient allocation of calls and prevent interference, but without restricting the operation of elevator cars like the existing MCE group control methods do. The simulation results show that our algorithm has a good performance under low and medium passenger arrival rates.

Linear motor for multi--car elevators: design and position measurement

Multi-car elevator is an emerging technology consisting of two or more elevator cars moving independently in an elevator hoistway, which has become more appealing as building heights increase. In this paper, the design and drive methodologies for a linear motor driven multi-car elevator system with independently moving cars is introduced together with experimental results. Additionally, a safety method developed for the linear motor elevator and the conditions necessary for its proper operation are discussed. The new results introduced in this paper are in the areas of the design method of the linear motor for multi-car elevator system, and the preliminary results for the position measurement system.

Multicar elevator group supervisory control system using genetic network programming

AbstractElevator group control systems are the transportation systems for handling passengers in the buildings. With the increasing demand for high‐rise buildings, it becomes important to improve the elevator service. The multicar elevators consist of plural cars in a single elevator shaft. It contributes to the improvement in passengers' handling capacity, while allowing the reduction of the space occupied in the building. In contrast with traditional elevator systems, the cars can no longer operate freely, where there are several restrictions on their available movements. This requires a more difficult control including stochastic scheduling with high combinatorial complexity in order to make the system more flexible. At present, lots of buildings with more than 40 floors are being built, which are usually divided into several zones served by local elevator groups. In addition, the cars should be operated at equal time intervals, especially in such a building with multicar elevator systems (MCES) in order to obtain its good performance. Genetic network programming (GNP), one of the evolutionary computations, can realize a rule‐based MCES due to its directed graph structure of the individual, which makes the system more flexible. This paper discusses MCES using GNP in high‐rise buildings. Also, the positions of elevators are considered to avoid the bunching phenomenon. The performance of MCES is studied and compared with single‐deck elevator system (SDES) and double‐deck elevator system (DDES). © 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Design and Implementation of a Linear Motor for Multicar Elevators

The multicar elevator system is a revolutionary new technology for high-rise buildings, promising outstanding economic benefits, but also requiring new technology for propulsion, safety, and control. In this paper, we report on experimental results with new components for linear-motor-driven multicar elevators. We show that linear synchronous motors with optimized design and with our new safety and control system can be considered as core components of a new generation of elevator systems. The main new results concern the development of a safety system integrated into the propulsion system, the design methodology of a linear motor optimized for the multicar elevator task, and the motion control system that is expected to be usable for extra high-rise buildings.

Algorithm for Controlling Multi-Car Elevator Systems Based on Procedures Estimating Efficiency of Passenger Transport and Call Assignability

Recently multi-car elevator (MCE) consisting of several elevator cars in a single elevator shaft received great interest as transportation systems for high-rise buildings. Algorithms for efficiently controlling elevator cars are necessary to put MCEs to practical use. We propose an algorithm for controlling MCEs to reduce passenger-waiting time. A feature of our algorithm is the introduction of a simple function estimating efficiency of passenger transport and a procedure checking assignability of a car. We evaluate the performance of our algorithm using a simulation and show that it performs better compared with a previous algorithm.

Simulation of a Four-Car Elevator Operation Using MATLAB

The design and simulation of a four-cars-elevator controller in a nine storey building is described in this paper. The design and simulation were accomplished using MATLABTM fuzzy logic toolbox. The logic of the controller of a multi-car elevator has to be designed in such a way that the average waiting time is minimized while keeping the energy consumption of the system optimum. This is a multi-criteria optimization problem in stochastic environment and is best approached through Artificial Intelligent techniques. The work here focuses mainly on extracting the rules to minimize factors (i.e. waiting time, travelled distance and riding time) in order to minimize the energy consumed by the system. In this paper a detailed algorithm is presented to achieve the multiple objectives of minimizing the waiting time and the distance travelled simultaneously. This was accomplished by distributing different weightage to different quantities and then minimizing a combined cost. A simulator has been built with interactive GUI in Matlab to evaluate the efficacy of the algorithm.

An Algorithm to Minimize Average Service Completion Time for the Group Controller of Multi-Car Elevator Systems

Recently, multi-car elevator (MCE) system has captured attention as an effective mean for the improvement of transportation capability in a high-rise building. The MCE has two or more cars in one shaft. In this paper, we propose an algorithm for group controllers of MCE system, and show the effectiveness of our algorithm through computer simulation.

MceSim: A Multi-Car Elevator Simulator

Multi-Car Elevator (MCE) systems, which consist of several independent cars built in the same shaft, are being considered as the elevators of the next generation. In this paper, we present MceSim, a simulator of MCE systems. MceSim is an open source software available to the public, and it can be used as a common testbed to evaluate different control methods related to MCE systems. MceSim was used in the group controller performance competition: CST Solution Competition 2007. This experience has proven MceSim to be a fully functional testbed for MCE systems.

110 循環式マルチカーエレベーター基本駆動技術の開発

Multi-car elevator system with large handling capacity can reduce elevator space in the large-scale building. We focused on circulating multi-car elevator which is effective for local transportation. The circulating multi-car elevator consists of two elevator shafts, and plural cages move circularly inside them. In this paper, we propose practical specification and feasible mechanism with looped-wire ropes. In order to affirm mechanical performance, 1/10 scale prototype is developed. We conclude that driving unit with multiple pulley realizes individual operation of plural cages. And stable motion at the turnaround points is also verified.

Stochastic Control for Multi Car Elevator by using Learning Automatons

Stochastic Control for Multi Car Elevator by using Learning Automatons

A Study on Design Method of Multi-car Elevator System

The multi-car elevator system in which two or more cages run at one shaft will be one of the elevator systems in the near future, in order to solve increase of the traffic demand in high-rise buildings.In this paper, we propose the calculation method of handling capacity for multi-car elevator systems two cages run at one shaft, or two or more cages run in the same direction at a loop-type shaft, in consideration of the position of cages in the same shaft. And we propose the design method for multi-car elevator systems, which decides the required number of cages, branches and shafts to meet the traffic demand. Moreover, we compare handling capacity of multi-car elevators and investigate optimal elevator facilities for high-rise buildings.

遺伝的アルゴリズムによるマルチカーエレベータ制御ルールのシミュレーションベースド最適化

遺伝的アルゴリズムによるマルチカーエレベータ制御ルールのシミュレーションベースド最適化