Chiller Digital Twin Rating for Actual Operating Conditions

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Solution Overview

Problem

Chillers have become increasingly complex, making it difficult to evaluate and control their components effectively under actual operating conditions at building sites, as their performance differs from peak design conditions.

Innovation Solution

A method and system that involve obtaining a device model for physical building equipment, adapting it to actual operating conditions, generating a virtual device representation, and using a rating engine to assess performance, with automated actions taken based on comparisons between expected and actual performance data.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If chiller complexity increases with technological improvements and component advances, then chiller performance capability improves, but evaluation and control difficulty increases

Engineering Contradiction:
Improvechiller performance capabilityVSAvoidevaluation and control difficulty
Core Design Contradiction:
ReliabilityVSDevice complexity

Solution Approach 1:

The patent creates a digital twin (virtual copy) of the physical chiller that replicates its behavior and performance characteristics. This virtual model allows evaluation and control operations to be performed on the copy rather than the complex physical system, reducing the difficulty of assessing and controlling chiller components while maintaining accurate performance capability analysis

Inventive Principle:
Principle #26Copying

2Manufacturing precision

If chiller performance is modeled under peak design operating conditions, then design performance is optimized, but actual operating performance evaluation becomes inaccurate

Engineering Contradiction:
Improvedesign performance optimizationVSAvoidactual operating performance accuracy
Core Design Contradiction:
Manufacturing precisionVSMeasurement precision

Solution Approach 1:

The patent transitions from static peak design condition modeling to dynamic modeling that adapts to actual operating conditions. The digital twin continuously adjusts to reflect real-time operational parameters, enabling accurate performance evaluation across varying conditions rather than only at peak design points

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The system changes the operating parameters from fixed peak design conditions to variable actual operating conditions. By adapting the model to reflect real-time parameters such as load variations, ambient temperatures, and component states, the system achieves accurate performance measurement across the full range of operational conditions

Inventive Principle:
Principle #35Parameter changes

3Productivity

If quick evaluation of chiller components under actual operating conditions is needed, then operational responsiveness improves, but model adaptation complexity increases

Engineering Contradiction:
Improveevaluation speedVSAvoidmodel adaptation complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The patent performs preliminary actions by pre-building the digital twin model with all necessary performance characteristics and relationships established before actual operation. This upfront modeling work enables rapid evaluation during operation without requiring complex real-time model adaptation, as the virtual copy is already configured to respond quickly to operational data

Inventive Principle:
Principle #10Preliminary action

Data Source

PatentEP4254115A1Chiller rating engine digital twin and energy balance model
Publication Date: 2023.10.04 JOHNSON CONTROLS TYCO IP HLDG LLP
  • EP4254115A1 patent drawingFigure 1
  • EP4254115A1 patent drawingFigure 2
  • EP4254115A1 patent drawingFigure 3

AI summary

A method for controlling building equipment. The method includes obtaining a device model for a physical device of building equipment installed at a building site, the device model indicating an expected performance of the physical device under design operating conditions. The method further includes obtaining operating conditions under which the physical device is operating at the building site, and generating a virtual device representing the physical device by adapting the device model to the operating conditions. The method also includes using a rating engine to generate a device rating for the virtual device, the device rating indicating an expected performance of the physical device under the operating conditions. The method also includes obtaining actual operating data indicating an actual performance of the physical device under the operating conditions, and initiating an automated action based on a comparison of the actual operating data with the device rating for the virtual device.