Nowadays, for the public, the requirements of service indexes have been more and more. The study of the elevator in large buildings indicates that the key point of the elevator carrier systems is meeting the endurance physically and mentally for the passengers. However, in the theory, there are lots of group control strategies of cluster elevators, and various group control strategies have different carrying capacity and satisfaction of passengers. Besides, the strategies have different strengths, weaknesses, and application scenarios. For example, some group control strategies apply in the lower floor rather than upper and some apply in fewer stairs building rather than more stairs building. Consequently, aiming at some specific scenario, there will be a more suitable group control strategy relatively.

Aiming at different scale building, there will always be a better strategy in kinds of group control strategies of cluster elevators. Even though at the same building, the same is true in the different application scenarios and time. To appropriately choose the most suitable group control strategy, the experience of people and the carrying capacity of elevators in some time are not enough to assess. So, there should be a set of the entire assessment system. Jian Chen [1] took a series of accumulation as kernel potential variables of passenger satisfaction. This is similar to the construction of the efficiency indicator system of the elevator group control strategy. Focused on the different carrying environment and conditions, the quantitative analysis should be used to assess the quality of multiple group control strategies. So, the efficiency assessment is widely used.

2) Research status of efficiency assessment

For a relative and quantitative system efficiency, specific application scenarios and objectives should be considered. Assessment of system efficiency aims at design, analysis, optimization, and assessment. If in the management system, there are different symptoms and the indicators measured deviate from the default range, the relative indicators will change. According to the reasonable classification and definition of the range of the indicator, the levels of current assessment can be obtained [2].

With the analysis of multiple objective decisions, Jinwei Guo et al. [3] thought that the weight was affected by many factors, such as the effect of the subjective factors on the weight configuration, reasonable configuration proportion. Currently, there are a lot of ways to configure the weight. After normalization, the 5-minute load factor was used as a significant reference to find the best elevator. Dongmei Song et al. [4] suggested an objective weighting method. The part of this method was based on the CARTTI method and entropy method and considered sufficiently the discreteness, correlation, and contrastive intension of data.

Shixin Gong et al. [5] found that if the failure model was assessed directly, the solution of the failure model would be invalid because the complete assessment system was lacked. Víctor Giménez [6] analyzed from 2 static and temporary perspectives to assess the total factor productivity (the hospital performance changing) in the whole time and the changing of its component. Referring to these components, it would help to define the variables and parameters in the system. For constructing the application scenario, it was a critical process.

A traction elevator is a relatively complicated device. The elevator usually, from the structure, is divided into the elevator machine room, elevator shaft, lift car, lift hall, and so on. This paper aims at 6 ten-floor elevators model. The floors are composed of first-floor lobby supermarket, second and third floors mall, fourth and ninth-floor office, and tenth-floor lounge. The whole structure of the elevator simulation model is shown in Figure 1.

When the elevator is working, the passenger flow is continuously changing. The most suitable group control scheduling algorithm can be chosen only by getting the passenger flow change and determining the elevator transportation modes. The ten floors medium comprehensive office building (the floors are composed of first-floor lobby supermarket, second and third floors mall, fourth and ninth-floor office, and tenth-floor lounge) is used as the research object in this design. Referring to the change of passenger flow in different time, the transportation mode is divided into 5 types: morning peak mode, lunch hour peak mode, afternoon peak mode, normal low passenger flow mode, and evening peak mode.

According to the scoring system of the simulation platform, shown as Figure 2, the following points will be composed as an assessment system.

Multiple elevator group control systems will generally generate several assessment indicators referring to the different demands for building and passengers. There are several types of indicators and several factors in EGCS and the main object needs to intensify as much as possible; for the EGCS with more comprehensive considerations, the assessment standard is relatively higher. Conversely, when the consideration is less, the standard is relatively lower. In this design, several indicators will be used as consideration to analyze the multiple performance indicators and influence parameters of the EGCS. What’s more, two methods have been determined: the shortest distance scheduling algorithm and minimum waiting time scheduling algorithm (in the following, they will be simplified as the shortest distance and minimum waiting time).

The elevator control system consists of PLC S7-1214C, communication module, call-button, control loop, Three-phase AC asynchronous motor, LED digital tube, PC STATION/WINCC RT ADVANCE and so on, shown as Figure 6.

The Control system mainly includes a PLC host and power module (Table 1 and Figure 7).

Wincc and S7-1200CPU of PC, and the elevator simulation system were connected by the ProfiNET Industrial Ethernet. This would come into being an entire simulation process finishing on the coaxial cable.

The passenger table would be set and the test time was all 10 minutes (Table 2).

The weights of above 6 indicators are represented as W 1 ~ W 6 . The goal of the algorithm design in the elevator group control system is to achieve the shortest waiting time outside the hall, reduce the long waiting rate of passengers, shorten the travel of each elevator, allocate the elevator response reasonably, prevent the clustering and uneven busy and idle, so as to meet the requirements of comfort, safety and economy. However, there may be conflicts in the above conditions. For example, the pursuit of the minimum waiting time must cause a certain degree of energy loss. Therefore, this paper will be divided into two cases for weight distribution. It focuses on the psychological indicators of passengers and energy consumption indicators, and adopts the method of average distribution for non important influencing factors.

At the normal low passenger flow mode, the elevator will not overweight basically, because the passengers distributed on every floor are relatively less and the exchange of passengers is mainly between floors. Therefore, at this time, the energy conservation indicator will be considered significant and put at first [7]. At the peak mode, the first goal is transforming the passengers to the target floor quickly. At this time, the key indicators will be the average waiting time of passengers, ride time, and waiting rate in a long time. These indicators will directly affect the experience of passengers, so the energy cost will not be the first goal to consider. The weight configuration shows in Table 3.

3) Efficiency assessment results

The above 6 indicators are represented as formulation:

S ( i ) = W 1 min ( A HT ( i ) ) A HT ( i ) + W 2 min ( A CT ( i ) ) A CT ( i ) + W 3 min ( P CHT ( i ) ) P CHT ( i )     + W 4 min ( L YX ( i ) ) L YX ( i ) + W 5 min ( T S ( i ) ) T S ( i ) + W 6 T A ( i ) max ( T A ( i ) ) (4-1)

The indicator parameters show as Table 4 and all the maximum and minimum indicators are the indicators of the best reference model.

The test results of 6 cumulative amounts in the simulation platform are taken into the evaluation function to calculate. The calculation results are shown as follow Table 5.

The assessment result will be shown in a histogram to compare the assessment indicators conveniently and directly, shown as Figure 7. But these 6 indicators are different in unit and order of magnitude, the data in the figure are all the result of normalization.

2) Lunch hour peak mode (Table 6)

3) Afternoon peak mode (Table 7)

4) Normal low passenger flow mode (Table 8)

5) Evening peak mode (Table 9)

According to the calculation, the assessment value of 2 group control strategies can be obtained in 5 passenger flow modes. The results are as follow:

1) In the 5 passenger flow modes, the assessment values of the shortest distance and minimum time are very close to each other. And the latter is slightly higher than the former because the total working time and total stopping time were considered accurately in the minimum time. Compared to the former, the consideration was more specific.

2) In the normal flow passenger low mode, it is similar for the energy conservation indicators of 2 type group control strategies and the assessment results are similar too. Because, at this time, the energy conservation indicator takes more proportion, and other indicators are weakened. The advantages of group control strategies cannot appear easily.

3) In this design, aiming at the morning peak mode, the most representative mode, in the 5 passenger flow modes, the number of transporting the passengers measured in this mode is not ideal, because this is to be more in line with reality. The type of passenger was set as No Patient, and they would leave when the waiting time was so long. So this would lose some passengers and make the number of transporting passengers to be lower than other conditions.

To sum up, the scheduling algorithm of the minimum waiting time is the best, and one of the highlights of the algorithm is: in the peak passenger flow, such as class peak, as long as it is in the peak state, the first floor passengers do not need to press the up call button, the elevator will also give priority to alleviate the first floor congestion.

The authors declare no conflicts of interest regarding the publication of this paper.

Meng, L.Y., Zou, X. and Qu, T. (2020) Study on Group Control Strategy of Multiple Elevators and Its Efficiency Evaluation. Open Access Library Journal, 7: e6410. https://doi.org/10.4236/oalib.1106410