Elevator Group Control via Threshold Load Optimization
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Solution Overview
Problem
Optimizing route determination for an elevator group to minimize energy consumption while considering other parameters, as a route with the lowest energy consumption may not be the most effective when accounting for occupancy rates and load values.
Innovation Solution
An elevator control apparatus and method that determines threshold loads for each elevator based on counterweight balance, allocating elevators to minimize load differences from these thresholds to optimize route determination and prevent energy inefficient allocations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If route determination minimizes total energy consumption, then energy efficiency is improved, but other parameters such as occupancy rate and load value may deteriorate
Solution Approach 1:
The patent introduces threshold load parameters for each elevator (first threshold for up direction, second threshold for down direction) that are determined based on counterweight balance. These parameters serve as decision criteria for route determination, changing the optimization from pure energy minimization to a parameter-based allocation that balances multiple factors including occupancy rate and load value while maintaining energy efficiency.
2Adaptability or versatility
If elevators are allocated based on predicted occupancy rate and load value, then occupancy balance is improved, but energy consumption optimization may deteriorate
Solution Approach 1:
The patent determines threshold loads based on counterweight balance parameters and uses these thresholds as the primary decision criterion for route determination. This parameter-based approach ensures that elevators are allocated in a way that maintains counterweight balance optimization, thereby minimizing energy consumption while still considering occupancy and load value through the threshold comparison mechanism.
3Productivity
If route determination considers multiple parameters simultaneously, then overall system performance is improved, but route determination complexity increases
Solution Approach 1:
The patent simplifies the multi-parameter optimization problem by transforming it into a threshold-based decision process. Instead of simultaneously optimizing multiple parameters, the system determines threshold loads in advance based on counterweight balance, then uses simple threshold comparisons for real-time route determination. This reduces computational complexity while maintaining system performance.
Data Source
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AI summary
According to one aspect, there is provided a method for controlling an elevator group comprising at least a first elevator (202) and a second elevator (210), wherein a counterweight balance of the first elevator (202) differs from a counterweight balance of the second elevator (210), the method comprising: controlling the elevator group comprising at least the first elevator (202) and the second elevator (210); determining threshold loads for the first (202) and second elevator (210) separately for up and down direction, a threshold load being dependent of the counterweight balance of the corresponding elevator, wherein the threshold load being a load for which consumed energy per up-down run is approximately zero; and controlling, when allocating an elevator in response to a destination call, route determination for the first (202) and second elevator (210) comprises minimizing a load difference from the threshold loads.