Elevator Car Mover Self-Learning Lateral Clearance Control

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Solution Overview

Problem

Existing elevator systems face challenges in maintaining precise lateral alignment and clearance control of motor-driven wheels on vertical track beams, leading to uneven motion and potential deviation from a straight path due to uneven wheel diameters and varying operational conditions.

Innovation Solution

An autonomous elevator car mover equipped with a self-learning lateral clearance control system that adjusts wheel motor parameters, such as velocity and torque, based on adjustment data from prior runs and sensor feedback, to maintain consistent wheel diameters and alignment using a controller and sensors.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional fixed-parameter wheel control is used, then the system structure is simple, but lateral alignment precision deteriorates due to uneven wheel diameters and varying operational conditions

Engineering Contradiction:

Improvelateral alignment precisionVSAvoidcontrol system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent implements feedback control by continuously monitoring lateral clearance between wheels and track using sensors, comparing it with reference values, and dynamically adjusting wheel motor parameters (velocity, torque) to correct deviations. This closed-loop feedback mechanism resolves the contradiction by achieving high alignment precision through adaptive control while keeping the base system structure relatively simple.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system employs self-learning capabilities where the controller automatically adjusts operational parameters based on accumulated data from prior runs, identifying optimal velocity and torque settings without external intervention. This self-service approach improves alignment precision while reducing the need for complex manual tuning and external control infrastructure.

Inventive Principle:

Principle #25Self-service

2Stability of the object's composition

If wheel parameters are dynamically adjusted based on prior run data, then alignment stability improves, but data processing requirements and computational load increase

Engineering Contradiction:

Improvealignment stabilityVSAvoiddata processing burden

Core Design Contradiction:

Stability of the object's compositionVSLoss of information

Solution Approach 1:

The system performs preliminary data collection during operational runs, storing lateral clearance measurements and operational parameters from each run. Before subsequent operations, this accumulated data is processed to identify optimal parameters, allowing the system to proactively adjust to varying conditions and maintain alignment stability without real-time computational complexity.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The control system dynamically adapts parameters based on learned patterns from historical data, adjusting velocity and torque commands in response to changing operational conditions such as wheel wear, load variations, and environmental factors. This dynamic adaptation maintains alignment stability while processing only essential data patterns rather than raw data streams.

Inventive Principle:

Principle #15Dynamics

3Manufacturing precision

If sensor feedback control is implemented, then lateral clearance control precision is improved, but system complexity and cost increase

Engineering Contradiction:

Improvelateral clearance control precisionVSAvoidsystem complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The patent uses sensor feedback to continuously measure lateral clearance between wheels and track, comparing measurements with reference values, and automatically adjusting wheel motor parameters to maintain precise clearance control. This feedback mechanism achieves high manufacturing precision through adaptive control while managing system complexity through efficient sensor integration and control algorithms.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS12528667B2Autonomous elevator car mover configured for self-learning lateral clearance control

Publication Date: 2026.01.20 OTIS ELEVATOR CO

AI summary

A car mover for autonomously moving an elevator car along a lane in a hoistway, including: first and second wheels of the car mover, configured to apply a pinch force against a track therebetween and to rotationally drive along the track, by respective first and second wheel motors of the car mover; and a controller configured to execute: a lateral clearance control self-learning module, wherein based on adjustment data, one or more operational parameters applied by one or more of the first and second wheel motors are adjusted; and a lateral clearance feedback control module, wherein based on one or more of a first lateral clearance adjacent the first wheel on the track and a second lateral clearance adjacent the second wheel on the track, torque applied by one or more of the first and second wheel motors is increased or decreased.