A Review of Research on the Development of Elevator Group Control Technology

Abstract

This paper introduces the growing demand for elevator traffic in the urbanization process in our country. It emphasizes the need for multiple elevators to be installed to meet this demand. If the elevators are unable to work in synchronization, it can result in multiple elevators responding to a single call signal. After analyzing the cause of the problem, we establish a mathematical model and use the objective function of the algorithm to optimize elevator group control. The main feature of this system is that it utilizes current elevator group control technology to collect statistical data on passenger flow and elevator usage frequency within the elevator group. Based on this data, a combination of fuzzy control optimization, expert system optimization, neural network optimization, and genetic algorithm optimization is selected to achieve efficient scheduling, tailored to the specific needs of the situation. The practical application of this technology demonstrates its ability to effectively address the issues of single response signal in traditional elevators, long waiting times, and significant energy loss. The technical model is more accurate, but the algorithm is complex and the solution takes a long time. Additionally, the timeliness problems affecting elevator group control technology will need to be further improved by introducing cloud computing in the future.