Elevator Group Allocation for Load-Balanced Passenger Flow
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Solution Overview
Problem
Existing elevator systems in large buildings often struggle to optimally allocate elevators, leading to passenger frustration due to complex layouts and inefficient resource utilization, particularly in optimizing energy consumption and load balancing.
Innovation Solution
The system groups elevators based on load unbalance, detecting service calls within a predefined time window, evaluating passenger demand, and selecting an elevator group to minimize load differences, thereby optimizing energy consumption and reducing component wear.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If elevator allocation is postponed until the last moment to allow optimization of resources, then energy efficiency and load balancing are improved, but passenger waiting time and frustration increase due to complex layouts and inability to locate suitable elevators
Solution Approach 1:
The system performs preliminary actions by predicting future passenger flow patterns and pre-positioning elevators in optimal groups before demand occurs. The controller evaluates historical data and current conditions to anticipate which elevator groups will be needed, preparing them in advance rather than reacting at the last moment. This reduces both waiting time and energy consumption by avoiding last-minute elevator movements.
Solution Approach 2:
The elevator grouping configuration is made dynamic rather than static. The controller continuously adjusts elevator group assignments based on real-time passenger flow patterns, floor demand, and energy consumption data. This dynamic reconfiguration allows the system to optimize energy efficiency while simultaneously adapting to changing passenger needs, reducing waiting times without sacrificing energy savings.
2Ease of operation
If elevators are grouped and arranged to serve certain floors to help passengers locate suitable elevators, then passenger satisfaction improves, but system flexibility and resource optimization capability decrease
Solution Approach 1:
The elevator grouping system is implemented as a dynamic configuration that can be continuously adjusted by the controller. Elevator groups are not fixed but are reconfigured in real-time based on changing passenger flow patterns, floor demand, and system performance data. This maintains passenger satisfaction through consistent grouping while preserving full system flexibility to adapt to different operational conditions.
Solution Approach 2:
The system incorporates feedback mechanisms where the controller continuously monitors passenger behavior, elevator usage patterns, and energy consumption. This feedback is used to automatically adjust elevator group configurations, maintaining optimal groupings that satisfy passengers while adapting to changing conditions. The feedback loop ensures both passenger satisfaction and system flexibility are maintained.
3Use of energy by moving object
If more sophisticated grouping solutions are introduced to optimize passenger service and energy saving, then energy efficiency and passenger satisfaction improve, but system complexity and control difficulty increase
Solution Approach 1:
The elevator system implements self-service through automated controller algorithms that independently analyze passenger flow data, evaluate energy consumption patterns, and reconfigure elevator groupings without human intervention. The system serves itself by automatically optimizing its own operation, reducing the need for complex manual control systems while achieving energy savings and improved passenger satisfaction.
Solution Approach 2:
The system optimizes energy efficiency by dynamically changing operational parameters such as elevator group configurations, assignment patterns, and scheduling intervals. Rather than requiring complex hardware modifications, the solution achieves energy savings through software-based parameter adjustments that the controller implements automatically, maintaining simplicity while improving performance.
Data Source
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AI summary
The invention relates to a method for allocating an elevator (120A, 120B, 120C; 130A, 130B; 140A, 140B, 140C) in an elevator system (100), the elevator system (100) comprising elevator groups (120; 130; 140), each group (120, 130, 140) comprising elevators, the elevator groups are formed based on a load unbalance of the elevators, the method comprises: detecting (210) received service calls in a predefined time window; evaluating (220) a number of passengers requesting service based on the received number of service calls; selecting (230), based on the evaluated number of passengers, an elevator group to serve the floor; and allocating (240) an elevator belonging to the selected elevator group to provide service. The invention also relates to an apparatus, an elevator system, and a computer program.