Elevator Dispatching Balancing Travel Time And Component Wear
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Solution Overview
Problem
Elevator dispatching systems often assign cars without considering the health and usage status of each car, leading to undesired wearing of components and inefficient service response.
Innovation Solution
A controller determines the health and usage state of elevator cars by analyzing factors such as door cycles, battery health, energy utilization, and maintenance records, and selects the most suitable car based on a scoring system that balances usage and health to optimize service response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If elevator dispatching assigns cars without considering health and usage status, then service response speed is improved, but component wear increases and reliability deteriorates
Solution Approach 1:
The dispatching system changes the selection parameters from purely travel-time-based to a composite scoring system that incorporates health metrics (door cycles, battery health, energy utilization, maintenance records) and usage metrics. This parameter transformation allows the system to balance rapid response with component preservation by selecting cars based on a comprehensive score rather than just proximity.
Solution Approach 2:
The patent replaces the traditional mechanical dispatching approach (assigning nearest car) with an intelligent control system that uses sensors, processors, and algorithms to evaluate multiple factors simultaneously. The controller computes health and usage scores, combines them with travel time, and makes optimized dispatching decisions, substituting simple mechanical rules with sophisticated electronic control.
2Productivity
If elevator dispatching prioritizes travel time only, then service efficiency is improved, but component lifespan decreases
Solution Approach 1:
The system transforms the dispatching criterion from a single parameter (travel time) to a multi-parameter scoring system that includes health metrics (door cycles, battery health, energy utilization, maintenance records) and usage metrics. This allows the system to maintain high service efficiency while accounting for component wear through the health score component.
Solution Approach 2:
The dispatching system implements feedback mechanisms by continuously monitoring elevator car conditions (door cycles, battery health, energy consumption, maintenance history) and using this information to adjust dispatching decisions. The health and usage scores are updated based on ongoing sensor data, creating a closed-loop system that adapts to component wear and optimizes both efficiency and lifespan.
3Duration of action of stationary object
If health and usage monitoring is implemented, then component lifespan is extended, but system complexity increases
Solution Approach 1:
The controller is designed as a multi-functional device that not only performs traditional dispatching based on travel time but also monitors health metrics (door cycles, battery health, energy utilization), tracks usage patterns, computes scoring, and makes optimized decisions. This universal controller consolidates multiple functions into a single system, managing complexity through integration rather than separate components.
Solution Approach 2:
The health and usage evaluation is segmented into distinct measurable factors (door cycles, battery health, energy utilization, maintenance records) that can be independently monitored and weighted. This segmentation allows the complex monitoring task to be broken down into manageable sensor inputs and computational steps, making the system implementable through modular sensor arrays and algorithmic processing.
4Measurement precision
If comprehensive health and usage factors are evaluated, then car selection accuracy is improved, but computational requirements increase
Solution Approach 1:
The system transforms multiple complex monitoring variables into a simplified composite scoring system. Health factors (door cycles, battery health, energy utilization, maintenance records) and usage factors are normalized and weighted to produce a single health/usage score that can be quickly compared across elevator cars. This parameter transformation reduces computational complexity while maintaining selection accuracy.
Solution Approach 2:
The dispatching system evaluates health and usage factors selectively rather than continuously for all possible parameters. The controller computes scores based on the most relevant factors for each specific dispatching decision, potentially ignoring less critical factors when they don't significantly impact the selection. This partial evaluation approach reduces computational overhead while maintaining sufficient accuracy for effective dispatching.
Data Source
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AI summary
An elevator system in a building having a plurality of levels, the system having elevator cars, a controller operationally coupled to the elevator cars, and configured to receive a service request, and render a first determination to select one of the elevator cars to respond to the service request, wherein the controller is configured to render the first determination from a determination of one or more of an elevator health and usage state of the elevator cars, and a travel time to respond to the service request by each of the elevator cars.